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Whelan TM, O'Brien MA, Villasis-Keever M, et al. Impact of Cancer-Related Decision Aids. Evidence Report/Technology Assessment Number 46. (Prepared by McMaster University under Contract No. 290-97-0017.) AHRQ Publication No. 02-E004, Rockville, MD: Agency for Healthcare Research and Quality. July 2002.
The Agency for Healthcare Research and Quality (AHRQ), through its Evidence-based Practice Centers (EPCs), sponsors the development of evidence reports and technology assessments to assist public- and private-sector organizations in their efforts to improve the quality of health care in the United States. The reports and assessments provide organizations with comprehensive, science-based information on common, costly medical conditions and new health care technologies. The EPCs systematically review the relevant scientific literature on topics assigned to them by AHRQ and conduct additional analyses when appropriate prior to developing their reports and assessments.
To bring the broadest range of experts into the development of evidence reports and health technology assessments, AHRQ encourages the EPCs to form partnerships and enter into collaborations with other medical and research organizations. The EPCs work with these partner organizations to ensure that the evidence reports and technology assessments they produce will become building blocks for health care quality improvement projects throughout the Nation. The reports undergo peer review prior to their release.
AHRQ expects that the EPC evidence reports and technology assessments will inform individual health plans, providers, and purchasers as well as the health care system as a whole by providing important information to help improve health care quality.
We welcome written comments on this evidence report. They may be sent to: Director, Center for Practice and Technology Assessment, Agency for Healthcare Research and Quality, 6010 Executive Blvd., Suite 300, Rockville, MD 20852.
| Carolyn Clancy, M.D. | Robert Graham, M.D. |
| Acting Director | Director, Center for Practice and |
| Agency for Healthcare Research and Quality | Technology Assessment |
| Agency for Healthcare Research and Quality |
| The authors of this report are responsible for its content. Statements in the report should not be construed as endorsement by the Agency for Healthcare Research and Quality or the U.S. Department of Health and Human Services of a particular drug, device, test, treatment, or other clinical service. |
Decision aids have been developed to improve communication between health professionals and patients, and to help involve patients in health care decisions. The area of cancer-related decisions has been found to be particularly problematic with respect to health professional-patient communication and decisionmaking for a number of reasons, including difficulties in communicating information about poor prognoses and modest benefits of treatments used. The objectives of this review were to describe the different cancer-related decision aids (DAs) that have been developed and to evaluate the effectiveness of these interventions.
Studies were identified by searching MEDLINE (1977 to April 2001), HEALTHstar, Cancerlit, Cinahl, Sociological Abstracts, PsycINFO (1977 to August 2000), and EMBASE (1995 to August 2000); the Cochrane Library (issue 3, 2000), reference lists of included studies, and personal files of experts. The main search terms were decisionmaking; decision analysis; patient education; patient participation; and neoplasms.
Primary studies about prevention, screening, and treatment decisionmaking focused on cancer that met the definition of a decision aid were included. Exclusion criteria were studies of benign prostatic hyperplasia, hormone replacement therapy, and smoking cessation as well as unpublished studies or those published as abstracts only.
Two reviewers independently extracted data, including methodological quality items for all studies. Disagreements were resolved by consensus. Descriptive statistics were calculated for all fields of the database. Evidence tables were constructed to describe the most salient features of the studies according to the review questions. Data were not pooled, because clinical heterogeneity existed across the studies (different types of cancer, diverse range of decisions: prevention, screening, treatment, and different study designs), outcomes measurements were inconsistent, and, overall, the studies had low methodological quality scores.
61 unique studies (including 18 randomized controlled trials, 5 nonrandomized controlled trials, as well as other study designs) were included after all screening processes were completed.
22 studies examined the development process of the DAs. In general, all studies had the same phases: assessment of construct validity and reliability in noncancer participants, followed by field-testing in cancer survivors in some studies. The majority (14/22, 64%) studied breast cancer treatment decisions.
The effectiveness of the DA was assessed in 39 studies; only 16 were randomized controlled trials (RCTs). Various DAs or a combination of strategies were evaluated: brochures, audiotapes, videotapes, interactive computer programs, educational scripts, decision boards, counseling, and informal decision analysis. Breast (23) and prostate cancer (11) were the most frequent types of cancer.
Across the studies, patients' decisions, knowledge, anxiety, depression, satisfaction, and acceptability of the DA were the most frequent outcome measures evaluated.
Overall, among RCTs, DAs appeared to increase knowledge and patient involvement in decisionmaking. Anxiety and depression scores appeared not to be increased by the DA. In patients making prostate cancer screening decisions, significantly fewer men decided to proceed with screening after receiving a DA.
Our results support that decision aids are helpful for some cancer screening decisions. In these situations, DAs can increase knowledge, do not increase anxiety, and, in some circumstances, can influence the decision made. In contrast, there is very little data available evaluating decision aids for cancer-treatment-related decisions, and further evidence is still needed. The early stage of development of this field and the gaps in our knowledge determined by this systematic review underline the need for further research. A number of different areas were identified, such as developing a better understanding of how and when decisionmaking occurs; who is involved (clinician, patient, or others); and the extent of their involvement. The key features of quality decisionmaking need to be determined from patients and clinicians to help investigators develop appropriate interventions and to identify and prioritize outcome measures of effectiveness. Multicenter collaboration to formally set a research agenda is needed because integration of different research efforts in the field appears to be suboptimal. National or international collaboration would permit development of consensus about important basic concepts regarding decisionmaking, decision aids, and important outcomes.
Decision aids are mechanisms or interventions that have been developed to improve communications between health professionals and patients and to help involve patients in making decisions regarding their health care. Decision aids can include brochures, videotapes, or interactive computer programs. Recent reviews have suggested that decision aids may be effective in supporting general health care decisions.
Cancer screening or treatment have been found to be particularly prone to difficulties in communication and decisionmaking between health professionals and their patients. There are a number of reasons for these problems, including difficulties in communicating information about poor prognoses and the modest benefits of the treatments used. The objective of this study was to conduct a comprehensive, systematic review of the literature to determine the impact of decision aids on cancer prevention, screening, and treatment decisions.
A set of questions was initially proposed by the National Cancer Institute's Division of Cancer Control and Population Sciences, and was further refined with input from members of the McMaster University Evidence-based Practice Center (MU-EPC) and the project officer at the Agency for Healthcare Research and Quality (AHRQ), which funds the EPC program.
The Technical Expert Panel (TEP) for this project included individuals who represented providers of health care, experts in study methodology, and researchers. After consultation with the TEP, the following key questions were selected as the focus of the Evidence Report.
What models of decisionmaking (e.g., informed, shared) underpin decision aids that have been used?
What clinical contexts (e.g., prevention, screening, and treatment) have been investigated?
What has been the clinical focus of the decision aids (e.g., type of cancer and extent of disease)?
What has been the mode of delivery (e.g., print, interactive video)?
On what populations has the research been conducted?
Have decision aids been developed for or used by members of special populations (e.g., the elderly, ethnic groups, and people with a low level of education)?
What outcomes have been evaluated (e.g., increase in knowledge, satisfaction, and behaviors)?
Are there any key outcomes that are associated with specific characteristics of decision aids?
What is the effectiveness of decision aids?
What is the effectiveness of decision aids in different clinical contexts?
What is the effectiveness of different modes of delivery?
What is the effectiveness of decision aids on special populations?
What specific direction is needed in future research on cancer-related decision aids?
The authors regarded as potentially eligible any article that (1) described a study in humans and (2) was about the development or evaluation of a cancer-related decision aid. There was no exclusion based on study design or language of publication. Primary studies about prevention, screening, and treatment decisionmaking; that focused on cancer; and that met the definition of a decision aid were included. A decision aid was defined as "an intervention designed primarily to help patients (or patients and clinicians together) with making cancer-related health care decisions, when options are available for prevention, screening, and treatment. At a minimum, it should target some component of decisionmaking (e.g., information exchange, involvement in the decision process)."
Studies of benign prostatic hyperplasia, hormone replacement therapy, and smoking cessation were excluded, as were studies published in abstract form only.
The research team used a two-stage screening process. In the first step, six raters worked in pairs to screen the titles and abstracts identified by the searches. In the second step, randomly assigned pairs of raters screened full text articles, then three reviewers checked all included studies and categorized them according to the context of the decision and type of study. Discrepancies were resolved by discussion.
Citations of potentially relevant studies were identified through a systematic research of: MEDLINE from 1977 to the end of April 2001; HealthSTAR, CANCERLIT, CINAHL, Sociological Abstracts, and PsycINFO from 1977 to August 2000; EMBASE from 1995 to August 2000; The Cochrane Library (Issue 3, 2000); reference lists of included studies; and the personal files of research team members. The development and refinement of the search strategy followed an iterative process using the MEDLINE database. The refined MEDLINE strategy was modified to meet the specific features of the other electronic databases.
In consultation with the TEP and project officer, all data extraction forms were developed, pilot-tested, and revised by members of the local research team. Two reviewers completed data extraction independently for all studies. Any disagreements were resolved by consensus. Following consensus on each item, the data forms were scanned into a Microsoft Access database using Teleform software.
Descriptive statistics were calculated for all fields of the database. Evidence tables were constructed to describe the most salient features of the included studies according to the review questions. The local research team at the MU-EPC, in consultation with members of the partner organizations and the project officer, evaluated the overall quantity and quality of the data available. A draft of the report was sent to an international Peer Review panel, comprised of researchers in the field of decisionmaking, methodologists, and consumers. This report incorporates many of the suggestions of the Peer Review panel and represents a detailed qualitative synthesis of the existing evidence, emphasizing the directions that future researchers could take to fill knowledge gaps.
The analysis of the yield of the literature and the general characteristics of the studies showed that:
A total of 1,056 full text articles were retrieved and screened. After a preliminary screening process, 207 articles met the inclusion criteria. Of the 207 articles, there were 168 unique studies with 39 reported in more than one publication. After the final screening process, 61 unique studies that focused on either the development or effectiveness of a cancer-related decision aid were included and form the basis of the Evidence Report.
Sixty-seven percent of studies were published between 1996 and 2001.
Ninety-seven percent of studies were published in English.
The setting for 74 percent of studies was North America.
Overall, 18 studies were randomized controlled trials (RCTs), five were nonrandomized controlled trials, and the remaining studies had a mix of designs.
Overall, the studies had low methodological quality scores.
Twenty-two studies examined the development process of decision aids. In general, all studies had the same phases: testing of content and construct validity, followed by the assessment of reliability in noncancer participants. There were three studies of prevention or screening decisions and 19 of treatment decisions. There were 14 studies involving breast cancer patients; two each of prostate, ovarian, and lung cancer patients; and one study each of colon cancer and leukemia patients. Only two developmental studies focused on special populations (Mexican-American women and impoverished African-American women).
The effectiveness of a decision aid was assessed in 39 studies: 16 RCTs, 4 nonrandomized studies, 2 nonconcurrent controlled studies, 6 pre/post designs, and 11 case series. Various decision aids or a combination of strategies were used: brochures, audiotapes, videotapes, interactive computer programs, educational scripts, decision boards, counseling, and informal decision analysis. Breast (23) and prostate cancer (11) were the most frequent types of cancer included.
Of the 39 studies that evaluated a decision aid in a clinical context, the ethnicity of participants was reported in 11 studies. In 10 studies, the majority of participants were Caucasian. Only one study evaluated the effect of a decision aid in a special population.
Across the studies, patients' decisions, knowledge, anxiety, depression, satisfaction, and acceptability of the decision aids were the most frequent outcome measures evaluated.
Overall, among RCTs, the decision aids appeared to increase knowledge and patient involvement in decisionmaking. Anxiety and depression scores did not appear to be increased. In patients making prostate cancer screening decisions, significantly fewer men decided to proceed with screening after receiving a decision aid.
These results support the proposal that decision aids are helpful for a number of cancer-screening decisions. In these situations, such instruments can increase knowledge, do not increase anxiety, and can influence the decision made. In contrast, there are few data available evaluating aids for decisions related to cancer treatment. Unfortunately, further evidence is still needed before making specific conclusions regarding decision aids in this situation.
The early stage of development of this field and the gaps in knowledge outlined in this systematic review underline the need for further research. A number of different areas were identified. Future research efforts should:
Develop a better understanding of how and when decisionmaking occurs in the real world, who is involved (clinician, patient, or others), and the extent of their involvement. Further work is needed to identify the processes involved and when they occur. Presumably, information transfer is the first step, but what are the stages of deliberation and how do patients and clinicians interact at this stage? How do they ultimately make a decision?
Determine the key features of quality decisionmaking from patients and clinicians. Such information will have a number of important benefits to help investigators develop instruments to facilitate quality decisionmaking and, perhaps most importantly, to identify, prioritize, and measure outcomes of effectiveness.
Determine patients' understanding of numerical estimates of risk. Are such numbers meaningful for them? What is the impact of providing risk estimates on real-life decisions?
Determine whether decision aids are effective for cancer-related treatment decisions. Research in other disease sites besides breast and prostate cancer and for metastatic disease is also necessary. The latter may be particularly challenging in terms of explicit discussion of benefits and risks of proposed treatments.
Focus on which components of a decision aid are necessary and effective (e.g., besides exchanging information, is counseling helpful)? How should it be instituted? Are different types of decision aids more effective than others?
Investigate whether decisionmaking regarding cancer is really different from decisionmaking in other chronic medical illnesses. In view of the life-threatening nature of this disease, are special approaches necessary here (e.g., psychosocial support techniques, patient support groups, teleconferences, or use of repetition)?
Determine what patient, clinician, or decisionmaking factors influence the effectiveness of decision aids. Are decision aids more or less useful in particular situations (i.e., do decision aids facilitate communication for clinicians who are less likely to spend time talking with their patients)? Or, alternatively, do decision aids impede communication in a more interactive clinician-patient relationship? Are there particular groups of patients that benefit from decision aids? Who are they (e.g., patients having difficulty making a decision)? Can they be identified a priori?
Establish whether decision aids are useful for members of special populations (e.g., the elderly, ethnic groups, or people with a low level of education). Should decision aids be modified for these populations, and how should this be done?
In addition to focusing on these areas, future research efforts should consider:
Multicenter collaboration to formally set a research agenda. From this review, there appeared to be poor integration of different research efforts in the field. National or international collaboration would permit development of a consensus about important basic concepts regarding decisionmaking, what a decision aid is, and important outcomes.
Development of an accepted conceptual framework for decisionmaking, standardized definitions of a decision aid, and a core set of outcomes would have important benefits for patients, clinicians, and policymakers. Outcomes should be important to all parties and could include for patients and clinicians: knowledge, satisfaction, comfort with decisionmaking, involvement in decisionmaking, and resources utilized both for the decisionmaking and the treatment chosen.
With respect to evaluation, larger studies with more rigorous design, more comprehensive reports, and studies with longer-term followup are needed to clearly establish effectiveness and adverse effects (if any) of decision aids, especially for cancer-related treatment decisions. Ideal studies would include evaluation of instruments developed based on sound principles compared to usual practice, with random allocation of intervention. Cluster randomization may be necessary so that the control group does not inadvertently receive the intervention. Appropriate outcomes should be assessed using survey instruments soon after administration of the intervention and with long followup to determine any latent effects. Studies should have sufficient statistical power to detect important differences and to look at factors predictive of effect. Multicenter collaboration is likely to facilitate this process and may have additional benefits in terms of increasing opportunities for dissemination of research results.
Other collaborative efforts, such as workshops and the development of practice guidelines by policymakers, clinicians, and patients, and other methods to improve the dissemination and implementation of decision aids should be instituted.
More involvement of consumer groups in helping to set the agenda, advocate for funding, facilitate the development of research studies, and disseminate research results should be considered.
The report concludes that funding should be sought from government and industry sources to support this research.
Decisionmaking for many chronic medical illnesses is a difficult task. The process requires clinicians and patients to weigh the immediate costs of inconvenience and potential morbidity of a preventive, screening, or treatment option against potential future benefits such as reduction in morbidity or disability. This tradeoff is further complicated by the uncertainty of these outcomes for the individual patient. With the rapid progress of modern health care, this process has become more challenging as clinicians and patients are often confronted with more than one or two options. Many of these new treatments are accompanied by more modest potential benefits and significant side effects, making the decisionmaking process even more difficult.
In the past, clinicians often tended to make decisions for patients with little patient input.1,2 More recently, patients have indicated their need for more information about their disease and the desire to be involved in decisions about their care.3 Clinicians and policy makers increasingly have realized the importance of including patient's values when making treatment decisions. The principle of informed choice (i.e., disclosure of treatment alternatives rather than merely informed consent) also has been endorsed at several government levels in the United States, Canada, and the United Kingdom.
Decisions are made most often in the context of clinician- (often physician-) patient encounter. Recent research recognizes the complexity of this interaction and the many forms that it may take.4,5 In general, the encounter involves several stages, including the exchange of information between the clinician and the patient, deliberation, and decisionmaking.6 The encounter also may take several forms based on the preferred type of interaction by the patient and the clinician. One extreme is the older, paternalistic type of interaction where information flows in one direction -- from the clinician to the patient -- and the clinician alone makes the decision. At the other extreme is the "informed" type of interaction where, again, information flows mainly in one direction, but the patient alone makes the decision.4 Recently, Charles and colleagues have described the shared model.5 The essential characteristic of this model is that both the clinician and the patient share all stages of the decisionmaking process simultaneously. In its purest form, there is a two-way exchange of information where both physician and patient reveal treatment preferences and both agree on the decision and implement it. However, decisionmaking is a dynamic process and, in any particular clinician-patient encounter, approaches may lie between and move between these types of interaction.
Several investigators have suggested problems with the paternalistic type of physician-patient encounter, particularly with the transfer of information between the physician and the patient.7,8 Treatment decisionmaking has been found to be particularly problematic for physicians and cancer patients.7,9-14 This is perhaps not unexpected given that the cancer patient can be faced with difficult information about a poor prognosis with limited treatment options. Physicians may find it difficult to openly share this type of information and patients may understandably be anxious or depressed, making it increasingly difficult for them to understand the information presented and take part in the decisionmaking.
Siminoff and Fetting7 studied 100 consecutive physician-patient encounters regarding adjuvant chemotherapy in women with early breast cancer to assess the consultative approach. They observed that the communication pattern, particularly that of the physician, was independent of the characteristics of the patient and severity of her disease. The risks and benefits of treatment were discussed, but the physician exchanged little in the way of specific information. The impact of treatment on the patient's lifestyle and emotional state often was not routinely addressed. Not surprisingly, the majority of patients (60 percent) overestimated their chance of cure by 20 percent or more and underestimated the severity of common side effects by a similar amount. Although patients were given alternative options, physicians, perhaps acknowledging the difficulty in communication, generally recommended one treatment and this had a definite influence on the patient's decision. Similarly, Rimer reviewed 116 consultations between physicians and cancer patients.9 Clinicians, on average, told patients less than 70 percent of the information relevant to their disease and treatment and patients, on average, recalled only 40 percent of the information that they were told. Other studies have described similar difficulties with information transfer in the oncology encounter.15,16
Aside from these problems in communication, researchers have also identified specific problems in treatment decisionmaking. Degner et al.13 examined the experiences of 1,012 women with breast cancer regarding their participation in decisionmaking. Twenty-two percent of women indicated they wanted to select their own treatment (active role); 44 percent wanted to select treatment collaboratively with their physician (shared role), and 34 percent wanted to delegate the responsibility to their physician (passive role). However, only 42 percent of patients were able to achieve their preferred role of decisionmaking, and this was even less for those who preferred a more active or shared role.
In light of these problems, researchers have responded by investigating better ways of transferring information to patients and supporting them in decisionmaking. Decision aids have been previously defined as "interventions designed to help people make specific and deliberative choices among options (including the status quo) by providing (at a minimum) information on the options and outcomes relevant to a patient's health."14 Decision aids differ from traditional patient education materials that are provided to patients. Decision aids provide an explicit presentation of different treatment options and the associated benefits and risks. The information is often tailored to individual characteristics of the patient and their decision. In addition to providing information, decision aids may support patients in other ways to help them make a decision. Examples of these types of decision aids are written materials, computer-based programs, videotapes, audio-guided workbooks and decision boards.
Recently, a number of decision aids have been developed for cancer patients because of the difficulties in communication and treatment decisionmaking identified in the literature. There has been a marked interest in decision aids for cancer patients and their physicians for several reasons: (1) poor understanding may be due to multiple factors, including poor communication techniques, information overload, patient anxiety, and denial; (2) patients with cancer are especially vulnerable dealing with the distressing and difficult diagnosis of a potentially terminal illness; (3) research suggests that communication can be especially poor when dealing with the ethnically diverse, poorly educated, or elderly, who are often overrepresented in the cancer population; (4) treatment decisionmaking in oncology is particularly problematic with a number of different treatments available and many associated with rather modest benefits and significant side effects; and (5) the cancer continuum identifies a number of areas in prevention, screening, diagnosis, treatment, and end-of-life care where the treatment decisions will vary considerably with respect to options available and associated benefits and risks.
Since 1999, there have been six reports (five systematic reviews14,15,17-19 and one review of reviews20) on decision aids. For example, O'Connor and colleagues14 conducted a systematic review of decision aids in various health conditions. Of the 17 randomized trials included, six studies were related to cancer. A number of different cancer-related decision aids (DA) interventions were identified. The authors conclude that, overall, decision aids improved patient knowledge. In a small subgroup of studies, decision aids also appeared to help patients be more involved in decisionmaking and feel more comfortable about their choices, but decision aids did not appear to have a consistent impact on patient satisfaction or anxiety. Molenaar and colleagues19 conducted a DA review that included all study designs (controlled and noncontrolled). Thirty studies of DA interventions were identified, 18 of which were related to cancer. The authors report that decision aids were found to be both feasible and acceptable to patients. Like the O'Connor review,14 the authors found that DAs improved patient knowledge of available options. Generally, all of these reviews are consistent, demonstrating a variable impact of decision aids on the specific outcomes evaluated. One reviewer concluded that the variability in the impact observed may be related to the different decision aids evaluated and the different contexts studied.19
| Systematic Review | Inclusion Criteria | Exclusion Criteria | Time period included in literature search |
|---|---|---|---|
| Bekker, H. Health Technology Assessment (1999) Volume 3, Number 1 | - not limited to cancer - real patients making a health decision (decision could be real, intended, or hypothetical) - experimental studies with a comparison group (RCTs, non-randomized concurrent, historical studies, and before/after studies with same sample) | - non-English articles - healthy volunteers as subjects - health professionals making decisions about another's care | Electronic database search (1991 to 1996) Three key journals hand searched from 1986 to 1996 |
| O'Connor, A Journal of the National Cancer Institute Monographs (1999a) 25: 67-80 | - not limited to cancer - before/after studies with patients - randomized trials with patients compared to usual care - randomized experiments comparing DAs (included hypothetical choices) | - none explicitly stated | Start date: 1966 End date: early 1998 |
| O'Connor, A BMJ (1999b) 319: 731-734 | - not limited to cancer - randomized trials of DAs - screening or treatment - subjects > 14 years old | - hypothetical choices - clinical trial entry - compliance - advocates an option | Range: 1966 to 1998 [refer to paper] |
| Molenaar, S. Medical Decision Making (2000) 20: 112-127 | - not limited to cancer -abstracts | - non-English articles | - two annotated bibliographies: (1) shared decisionmaking; and (2) decision aids - electronic database search of Medline from January 1993 to August 1998 |
| Estabrooks, C. Consumer Decision Aids: Where do we stand? Institute for Clinical Evaluative Sciences March (2000) | - not limited to cancer - decisionmaker must be a consumer | - hypothetical decisions - compliance - education only - clinical trial entry - advanced directives -smoking cessation -did not evaluate the DA -did not report measurement of one or more outcome | Start date: 1992 End date: October 1998 - Medline updated monthly. A few key journals hand searched for 1999 |
| NHS Effective Health Care bulletin, December (2000) volume 6, number 6 | - in the part of the report focused on DAs, three systematic reviews of DAs were identified (all three are included in this table; two are the reviews by O'Connor and the one by Molenaar) - the DA section of the report was limited to participants who had a cancer diagnosis | - systematic reviews of decision aids were identified by a search of electronic databases (1966 to August 2000) - reran O'Connor (1999a) search strategy with the additional criteria that participants had to have a cancer diagnosis; updated search to October 2000 | |
| Whelan, T. Impact of cancer-related Decision Aids: An evidence report Agency for Healthcare Research and Quality (2001) | - cancer-related DAs - abstracts published before 1995 were excluded if no followup paper. Abstracts > 1995: included if author contacted (either if paper to come or no paper); excluded if author not contacted or no further paper. | - advocates a particular option - compliance - BPH or HRT - clinical trial entry, palliative care, usual care, and research use only studies | Electronic database search. Start date: 1977 End date: April 2001 |
| Cancer-related RCT studies included in decision aid systematic reviews a | Bekker (1999) | O'Connor (1999a) | O'Connor (1999b) | Molenaar (2000) | NHS Bulletin (2000) | Estabrooks (2000) | Whelan (2001) | |
|---|---|---|---|---|---|---|---|---|
| Author | Year | |||||||
| North | 1992 |
 (E)
c | ||||||
| Butow | 1994 |
|
| Exclude d | ||||
| Llewellyn-Thomas | 1995 |
|
|
| Exclude d | |||
| Sebban | 1995 |
|
|
(D)
c | ||||
| Street | 1995 |
|
|
|
|
|
|
(E)
c |
| VanRuiswijk [abstract] b | 1995 |
|
| Exclude d | ||||
| Whelan | 1995 |
[RCT]
b |
[not RCT]
b | |||||
| Flood | 1996 |
[RCT]
b |
[RCT]
b |
[CT]
b |
[CT]
b |
[CT]
b | ||
| Wolf | 1996 |
|
|
|
|
(E)
c | ||
| Davison | 1997 |
|
|
|
(E)
c | |||
| Lerman | 1997 |
|
|
|
(E)
c | |||
| Inglehart | 1998 |
(E)
c | ||||||
| Maslin | 1998 |
|
(E)
c | |||||
| Watson | 1998 |
(E)
c | ||||||
| Davison | 1999 |
|
(E)
c | |||||
| Hack | 1999 |
(E)
c | ||||||
| Irwin | 1999 |
(E)
c | ||||||
| Rolnick | 1999 |
(D)
c | ||||||
| Volk | 1999 |
[abs]
b |
(E)
c | |||||
| Pignone | 2000 |
(E)
c | ||||||
| Schapira | 2000 |
(E)
c | ||||||
| Wolf | 2000 |
(E)
c | ||||||
| Goel | 2001 |
[abs]
b |
[in press]
b |
(E)
c | ||||
RCT studies that assessed patient compliance, clinical trial entry or advocated a particular course of action are not reported in the above table.
[] notation is used when either: (1) the study was reported as an RCT by one review and a different design by another, or (2) to distinguish inclusion of an abstract, in press, or published paper.
(E) means the RCT included the effectiveness chapter and (D) that the study was included in the development chapter.
Identified by our search strategy, not included in the review: Butow was excluded as secondary purpose; Llewellyn-Thomas excluded as research use only; and VanRuiswijk was excluded as abstract only.
Given the unique challenges this clinical condition may have on the decisionmaking process, a more comprehensive understanding of the decision aids is warranted. A systematic review of decision aids for cancer patients would provide an overview of what has been developed and determine whether these instruments do improve communication and decisionmaking for cancer patients and clinicians. Such a review would also provide other added benefits not studied in previous reviews, including an opportunity to address the impact of different instruments in a more homogeneous population and to evaluate the impact of different points on the continuum of care on the efficacy of decision aids.
The McMaster University Evidence-based Practice Centre (MU-EPC) was notified in March 2000 that it was successful in its bid to undertake the development of an evidence report on the "Impact of Cancer-Related Decision Aids." This topic was nominated by the National Cancer Institute (NCI), Division of Cancer Control and Population Sciences. The goal in this project was to identify and summarize the best available information for each question; to make the results available to patients, clinicians, policymakers, and researchers; and to encourage further evaluation of these instruments in clinical practice.
To conduct the systematic review, a local expert and research team was assembled. This team consisted of members of the MU-EPC whose areas of expertise include medical and professional aspects of cancer care and patient support; models and theoretical understanding of decisionmaking processes; systematic reviews; and other health research methodology. Highly trained research assistants and administrative support staff augmented this team.
A second organizational sector of those involved in this systematic review include our partner, the NCI (represented by Drs. Barbara Rimer and Michael Stefanek), who commissioned the report, and Margaret Coopey, our Task Order Officer (TOO), who represented the Agency for Healthcare Research and Quality (AHRQ) and consulted with our team.
The Technical Expert Panel (TEP) for this Task Order was composed of individuals whose collective expertise represented several of the major components in the delivery of cancer care, including health services researchers, health care providers, and consumers (see Appendix A). These individuals are recognized as national and international leaders in the area of cancer-related consumer information and were selected in consultation with our local research team experts, AHRQ, and our partners at NCI. The main function of the TEP was to provide an external review of this project at various stages throughout its course.
Questions to be addressed in the task order were identified by the NCI. Refined questions and project scope were negotiated and achieved through consensus between the local research team and the NCI. Results of this process yielded an operational definition of a decision aid and a specific series of questions to be answered in this systematic review.
For the purposes of this systematic review, a definition was sought that was broad enough to encompass and be inclusive of the broad range of thinking in this area. Specifically, a "decision aid" was defined as: An intervention designed primarily to help patients or patients and clinicians together, with making cancer-related health care decisions, when options are available for prevention, screening and treatment. At a minimum, it should target some component of decisionmaking (e.g., information exchange, involvement in the decision process).
A decision aid was considered an "intervention" when it involved some process or instrument that was above and beyond "usual or standard care." For the purpose of this Evidence Report, usual care was defined as standard practice as indicated by the primary study authors. We expected that the components of usual care would vary from study to study depending on the clinical context, but, most of the time, would involve some discussion of risks and benefits of options. Patients must have been involved in the use of the instrument (i.e., patient alone, patient together with significant others). Those tools designed purely for clinicians (e.g., clinical guideline algorithms to standardize care pathways) that provided some form of decision assistance were excluded. The definitive set of questions negotiated between the local research team, the NCI, and AHRQ addressed various themes in the decision aids literature, including the development process of these tools; their effectiveness, including outcomes emerging from their use; and future research directions. The specific questions included:
What models of decisionmaking (e.g., informed, shared) underpin decision aids that have been used?
What clinical contexts (e.g., prevention, screening, and treatment) have been investigated?
What has been the clinical focus of the decision aids (e.g., type of cancer and extent of disease)?
What has been the mode of delivery (e.g., print, interactive video)?
On what populations has the research been conducted?
Have decision aids been developed for or used by members of special populations (e.g., the elderly, ethnic groups, and people with a low level of education)?
What outcomes have been evaluated (e.g., increase in knowledge, satisfaction, and behaviors)?
Are there any key outcomes that are associated with specific characteristics of decision aids?
What is the effectiveness of decision aids?
What is the effectiveness of decision aids in different clinical contexts?
What is the effectiveness of different modes of delivery?
What is the effectiveness of decision aids on special populations?
What specific direction is needed in future research on cancer-related decision aids?
A health science librarian on the local research team assisted with designing and pretesting the literature search strategies for electronic databases. The search strategy for the MEDLINE search is found in Appendix B. Studies were identified using MEDLINE, HealthSTAR, CANCERLIT, CINAHL, Sociological Abstracts, PsycINFO, and the Cochrane Library electronic databases (January 1977 to August 2000) without language restrictions. EMBASE was searched from 1995-2000. The MEDLINE search was subsequently updated to the end of April 2001. In addition to searching major electronic databases, citations of relevant references from published reviews on decision aids, from reference lists of primary articles selected for inclusion, and from suggestions made by members of the local research team and the TEP were also reviewed. Unpublished studies were not included because of concerns about potential threats to internal validity and lack of a peer review process.
A range of inclusion criteria were chosen to reflect methodological, conceptual, and clinical considerations:
primary human studies
studies of any design
interventions that met our definition of a decision aid and involved a decision along the cancer care continuum.
There were no restrictions by the type of outcome measures used by the primary study authors to evaluate the impact of the decision aid.
news articles, letters, or editorials;
tools designed solely for clinicians;
interventions focused on benign prostatic hyperplasia, hormone replacement therapy, and smoking cessation;
interventions advocating a particular course of action; and
interventions evaluated after a decision was made.
Three criteria were used in the initial screening. The article had to: (1) be a primary study, systematic review, or useful support document; (2) demonstrate evidence that the clinical context was cancer; and (3) meet the definition of a decision aid or describe the development or validation of an outcome measure (see Appendix C). Those articles that met the eligibility criteria were retrieved in full text and subject to the secondary review.
Seven trained reviewers participated in the initial screening process. Each reviewer received a block of citations. There was approximately a 10 percent overlap in citations from one reviewer to the next, resulting in 10 percent of the initial 10,772 citations being screened by at least two independent reviewers. Discrepancies were resolved by consensus and, where consensus could not be reached, the opinions of a third reviewer were requested.
To ensure systematic application of inclusion and exclusion criteria and to document the process of full-text screening, a "relevance form" was developed (see Appendix D) for this phase. Articles considered in this phase were allocated to the reviewers following a randomization schedule implemented by an unblinded project assistant. Two reviewers rated each article independently. For each article, the "relevance form" was completed and a rating of "Include," "Exclude" or "Uncertain" was made. A consensus process that was documented on the "consensus" relevance form resolved discrepancies. In circumstances in which articles were rated as "Uncertain" or where consensus between the two initial reviewers could not be reached, a third reviewer or members of the local research team were called in to resolve the discrepancy.
Exceptions to this protocol were made for articles published in a language other than English; only one reviewer who was proficient in the language of publication assessed the article for eligibility and completed the relevance form.
Three data extraction forms were developed, pilot-tested, and revised by members of the local research team. One form was designed for each of general study characteristics, study outcomes, and study quality. Two reviewers completed data extraction independently of all the articles. Discrepancies were resolved by consensus, and the final forms were scanned into a Microsoft Access database using Teleform software (TELEform Standard version 6.0, Cardiff Software Incorporated, San Marcos, CA, USA).
The quality assessment of the randomized controlled trials (RCTs) was based on three scales: Jadad, et al. scale,21 Downs and Black scale,22 and Guyatt, et al. scale.23 For other study designs-such as non-RCTs, nonconcurrent cohort studies, and case series -- in assessing the methodological quality, the Downs and Black scale22 was employed only.
Descriptive statistics were calculated for all fields of the database. Evidence tables were constructed to describe the most salient figures of the included studies using the review questions as an organizational framework. Two tables for each study were designed: the general study characteristics and the study results.
The local research team evaluated the overall quantity and quality of the data available. Given the heterogeneity across studies (i.e., type of decision aids; type of cancer; type of decisions [prevention, screening, treatment]; study designs; inconsistency in outcomes measured; inconsistency in theoretical predications about outcomes; and poor study quality), a meta-analysis was not undertaken. Thus, this report represents a systematic qualitative review of the existing evidence, emphasizing the directions that future researchers could take to fill existing knowledge gaps.
A preliminary list of potential peer reviewers was drafted in July 2000 and sent to our partners. In February 2001, reviewers were contacted to request their assistance in reviewing the draft version of the Evidence Report; 16 of the 29 proposed reviewers agreed to be our peer reviewers (see Appendix E).
| MEDLINE a | Health STAR | CANCERLIT | CINAHL | Sociological Abstracts | PsycINFO | EMBASE | Cochrane Library | Experts | Reference Lists b | Contact With Author | Totals | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
# Titles and abstracts:
| 6,373 | 5,909 | 4,542 | 1707 | 119 | 447 | 2,931 d | 251 | 22,279 | |||
# Titles and abstracts:
| 6,309 | 249 | 0 | 1,394 | 84 | 438 | 2,159 | 75 | 10,772 | |||
| # Articles requested e | 496 | 32 | 0 | 112 | 3 | 31 | 172 | 19 | 12 | 190 | 1 | 1,068 |
| # Articles that could not be located | 2 | 0 | 0 | 7 | 0 | 1 | 2 | 0 | 0 | 0 | 0 | 12 |
| # Articles in languages other than English | 32 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 1 | 0 | 38 |
| # Articles reviewed | 494 | 32 | 0 | 105 | 3 | 30 | 170 | 19 | 12 | 190 | 1 | 1056 |
| # Articles excluded e | 384 | 28 | 0 | 91 | 2 | 22 | 143 | 16 | 5 | 157 | 1 | 849 |
| # Articles included e | 110 | 4 | 0 | 14 | 1 | 8 | 27 | 3 | 7 | 33 | 0 | 207 |
MEDLINE search was updated to April 2001.
Total number of citations identified in the reference lists of included studies, review articles, and background articles. Many of these already belonged to the main database.
These figures contain some duplication of citations.
Results of the search of EMBASE from 1995 to 2000.
Figures reported represent the results of the preliminary screening of full text articles.
Overall, 1,068 full text articles were requested from the library. Twelve articles could not be located, resulting in 1,056 full text articles that were retrieved and screened by two reviewers.
| Total number of full text articles screened | 1,056 |
| Total number of excluded articles | 849 |
| Reasons for exclusion General education Not a primary study Not related to cancer Informed consent Mathematical model | 450 334 51 8 6 |
| Total number of articles included on preliminary screening of full text articles | 207 |
|
Ashcroft JJ, Leinster SJ, and Slade PD. Breast cancer patient choice of treatment: preliminary communication. J R Soc Med 1985;78(1): 43-6.
|
Brundage MD, Feldman SD, Dixon P, et al. A treatment trade-off based decision aid for patients with locally advanced non-small cell lung cancer. Health Expectations 2000;3(1):55-68.
|
Brundage MD, Davidson JR, Mackillop WJ. Trading treatment toxicity for survival in locally advanced non-small cell lung cancer. J.Clin.Oncol. 1997 Jan;15(1):330-340.
|
Carrère MO, Moumjid-Ferdjaoui N, Charavel M, et al. Eliciting patients' preferences for adjuvant chemotherapy in breast cancer: development and validation of a bedside decision-making instrument in a French Regional Cancer Centre. Health Expectations 2000:97-113.
|
Davison BJ, Degner LF. Empowerment of men newly diagnosed with prostate cancer. Cancer Nurs 1997;20(3):187-96.
|
Flood AB, Wennberg JE, Nease RF Jr, et al. The importance of patient preference in the decision to screen for prostate cancer. Prostate Patient Outcomes Research Team. J Gen Intern Med 1996;11(6):342-9.
|
Goel V, Sawka CA, Thiel EC, Gort EH, O'Connor AM. Randomized trial of a patient decision aid for choice of surgical treatment for breast cancer. Med Decis Making 2001;21:1-6.
|
Gustafson D, Wise M, McTavish F, et al. Development and pilot evaluation of a computer-based support system for women with breast cancer. J Psychosocial Oncol 1993;11(4):69-93.
|
Iglehart JD, Miron A, Rimer BK, et al. Overestimation of hereditary breast cancer risk. Ann Surg 1998;228:375-384.
|
Irwin E, Arnold A, Whelan TJ, et al. Offering a choice between two adjuvant chemotherapy regimens: A pilot study to develop a decision aid for women with breast cancer. Patient Educ Couns 1999;37(3):283-291.
|
Lerman C, Biesecker B, Benkendorf JL, et al. Controlled trial of pretest education approaches to enhance informed decision-making for BRCA1 gene testing. J Natl Cancer Inst 1997 Jan;89(2):148-57.
|
Maslin AM, Baum M, Walker JS, et al. Shared decision-making using an interactive video disk system for women with early breast cancer... including commentary by Beaver K. Nt Research 1998;3(6):444-55.
|
McTavish FM, Gustafson DH, Owens BH, et al. CHESS (Comprehensive Health Enhancement Support System): an interactive computer system for women with breast cancer piloted with an underserved population. J Ambulatory Care Manage 1995;18(3), 35-41.
|
Stalmeier P, Unic I, Verhoef L, et al. Evaluation of a shared decision making program for women suspected to have a genetic predisposition to Breast Cancer. Med Decis Making 1999;19:230-41.
|
Street RL Jr, Voigt B, Geyer C Jr, et al. Increasing patient involvement in choosing treatment for early breast cancer. Cancer 1995;76(11):2275-85.
|
Volk RJ, Cass AR, Spann SJ. A randomized controlled trial of shared decision making for prostate cancer screening. Arch Fam Med 1999 Jul;8(4):333-40.
|
Wolberg WH, Tanner MA, Romsaas EP, et al. Factors influencing options in primary breast cancer treatment. J Clin Oncol 1987 Jan;5(1): 68-74.
|
Wolf AM, Nasser JF, Schorling, J. B. The impact of informed consent on patient interest in prostate-specific antigen screening. Arch Intern Med 1996 Jun;156(12):1333-6.
|
| Screening categories | Number of unique studies (n = 168) a |
|---|---|
| Include | |
| Effectiveness of a Decision Aid | 39 |
| Development of a Decision Aid | 22 |
| Total | 61 |
| Exclude Research Use Only Usual Care Clinical Trial Entry Outcome Measure Other Intervention Palliative Care Other Focus (e.g., education, mathematical model, not cancer related) Abstract Only | 37 28 9 7 9 4 11 2 |
| Total | 107 |
Of the 207 articles included on the initial screening of full text, 39 articles have been considered companion articles to 168 unique studies.
| Author | Related articles | Citation | Chapter | Evidence Table |
|---|---|---|---|---|
| Adler K. 1999 | Adler K. Research in brief. Chemotherapy: the patient's choice. Eur J Oncol Nurs 1999 Jun;3(2):102-4. | Effectiveness | 5.4 a, b | |
| Ashcroft JJ. 1985 | Ashcroft JJ. 1984 Owens RG. 1987 Leinster SJ. 1987 | Ashcroft JJ, Leinster SJ, Slade PD. Breast cancer--patient choice of treatment: preliminary communication. J R Soc Med 1985 Jan;78(1):43-6. | Effectiveness | 5.29 a, b |
| Brundage MD. 1997 | Brundage MD. 1998 | Brundage MD, Davidson JR, Mackillop WJ. Trading treatment toxicity for survival in locally advanced non-small cell lung cancer. J Clin Oncol 1997 Jan;15(1):330-40. | Development | 4.10 a, b |
| Brundage MD. 2000 | Brundage MD. 1998 Brundage MD. 1997 Brundage MD. 2001 | Brundage MD, Feldman SD, Dixon P, et al. A treatment trade-off based decision aid for patients with locally advanced non-small cell lung cancer. Health Expect 2000;3(1):55-68. | Effectiveness | 5.39 a, b |
| Carrère M. 2000 | Ferdjaoui N. 1999 | Carrère M, Moumjid-Ferdjaoui N, Charavel M et al. Eliciting patients' preferences for adjuvant chemotherapy in breast cancer: development and validation of a bedside decision-making instrument in a French Regional Cancer Centre. Health Expect 2000;97-113. | Development | 4.18 a, b |
| Cassileth BR. 1989 | Cassileth BR, Soloway MS, Vogelzang NJ, et al. Patients' choice of treatment in stage D prostate cancer. Urology 1989 May;33(5 Suppl):57-62. | Effectiveness | 5.3 a, b | |
| Chapman GB. 1995 | Chapman GB, Elstein AS, Hughes KK. Effects of patient education on decisions about breast cancer treatments: a preliminary report. Med Decis Making 1995 Jul;15(3):231-9. | Development | 4.7 a, b | |
| Cotton T. 1995 | Cotton T. Patient choice in breast cancer treatment. Nurs Times 1995;91(17):12 | Effectiveness | 5.26 a, b | |
| Cotton T. 1991 | Cotton T, Locker AP, Jackson L, et al. A prospective study of patient choice in treatment for primary breast cancer. Eur J Surg Oncol 1991 Apr;17(2):115-17. | Effectiveness | 5.25 a, b | |
| Davison BJ. 1997 | Pasacreta JV. 1998 | Davison BJ, Degner LF. Empowerment of men newly diagnosed with prostate cancer. Cancer Nurs 1997 Jun;20(3):187-96. | Effectiveness | 5.35 a, b |
| Davison BJ. 1999 | Davison BJ, Kirk P, Degner LF, et al. Information and patient participation in screening for prostate cancer. Patient Educ Couns 1999;37 July(3):255-63. | Effectiveness | 5.24 a, b | |
| Dolan JG. 1995 | Dolan JG. Are patients capable of using the analytic hierarchy process and willing to use it to help make clinical decisions? Med Decis Making 1995 Jan;15(1):76-80. | Development | 4.6 a, b | |
| Elit LM. 1996 | 2 studies in 1 article | Elit LM, Levine MN, Gafni A, et al. Patients' preferences for therapy in advanced epithelial ovarian cancer: development, testing, and application of a bedside decision instrument. Gynecol Oncol 1996 Sepa;62(3):329-35. | Development | 4. 14 a, b |
| Elit LM. 1996 | 2 studies in 1 article | Elit LM, Levine MN, Gafni A, et al. Patients' preferences for therapy in advanced epithelial ovarian cancer: development, testing, and application of a bedside decision instrument. Gynecol Oncol 1996 Sepb;62(3):329-35. | Development | 4.15 a, b |
| Fiset V. 2000 | 2 studies in 1 article | Fiset V, O'Connor AM, Evans W, et al. Development and evaluation of a decision aid for patients with stage IV non-small cell lung cancer. Health Expect 2000;3(2):125-36. | Effectiveness | 5.13 a, b |
| Fiset V. 2000 | 2 studies in 1 article | Fiset V, O'Connor AM, Evans W, Graham I, DeGrasse C, Logan J. Development and evaluation of a decision aid for patients with stage IV non-small cell lung cancer. Health Expect 2000;3:125-36. | Development | 4.21 a, b |
| Flood AB. 1996 | Anonymous 1996 2 studies in 1 article | Flood AB, Wennberg JE, Nease RFJ, et al. The importance of patient preference in the decision to screen for prostate cancer. Prostate Patient Outcomes Research Team. J Gen Intern Med 1996 Juna;11(6):342-49. | Effectiveness | 5.16 a, b |
| Flood AB. 1996 | Anonymous 1996 2 studies in 1 article | Flood AB, Wennberg JE, Nease RFJ, et al. The importance of patient preference in the decision to screen for prostate cancer. Prostate Patient Outcomes Research Team. J Gen Intern Med 1996 Junb;11(6):342-9. | Effectiveness | 5. 17 a, b |
| Goel V. 2001 | Goel V. 1998 | Goel V, Sawka CA, Thiel EC, et al. Randomized trial of a patient decision aid for choice of surgical treatment for breast cancer. Med Decis Making 2001;21(1):1-6. | Effectiveness | 5.12 a, b |
| Gramlich EP. 1998 | Gramlich EP, Waitzfelder BE. Interactive video assists in clinical decision making. Methods Inf Med 1998 Jun;37(2):201-5. | Effectiveness | 5.23 a, b | |
| Gustafson D. 1993a | Owens BH. 1996 Gustafson DH. 1993 Taylor JO. 1994 2 studies in 1 article | Gustafson D, Wise M, McTavish F, et al. Development and pilot evaluation of a computer-based support system for women with breast cancer. J Psychosoc Oncol 1993a;11(4):69-93. | Development | 4.2 a, b |
| Gustafson D. 1993b | 2 studies in 1 article | Gustafson D, Wise M, McTavish F, et al. Development and pilot evaluation of a computer-based support system for women with breast cancer. J Psychosoc Oncol 1993b;11(4):69-93. | Development | 4.3 a, b |
| Hack TF. 1999 | Hack TF, Pickles T, Bultz BD, et al. Feasibility of an audiotape intervention for patients with cancer: A multicenter, randomized, controlled pilot study. J Psychosoc Oncol 1999;17(2):1-15 | Effectiveness | 5.10 a, b | |
| Iglehart JD. 1998 | Miron A. 2000 Bluman LG. 1999 | Iglehart JD, Miron A, Rimer BK, et al. Overestimation of hereditary breast cancer risk. Ann.Surg. 1998;228:375-384. | Effectiveness | 5.2 a, b |
| Irwin E. 1999 | Irwin E 1995 | Irwin E, Arnold A, Whelan TJ, et al. Offering a choice between two adjuvant chemotherapy regimens: A pilot study to develop a decision aid for women with breast cancer. Patient Educ Couns 1999;37(3):283-91. | Effectiveness | 5.30 a, b |
| Jenkinson J. 1998 | Jenkinson J, Wilson-Pauwels L, Jewett MA, et al. Development of a hypermedia program designed to assist patients with localized prostate cancer in making treatment decisions. J Biocomm 1998;25(2):2-11. | Development | 4.8 a, b | |
| Klass W. 1992 | Klass W, Varenhorst E, Hjertberg H, et al. A study on prostatic cancer. The patient can decide himself: medical or surgical treatment. Lakartidningen 1992 May;89(19):1659-61. | Effectiveness | 5.6 a, b | |
| Lawrence VA. 2000 | Lawrence VA, Streiner D, Hazuda HP, et al. A cross-cultural consumer-based decision aid for screening mammography. Prev Med 2000;30(3):200-8. | Development | 4.17 a, b | |
| Lerman C. 1997 | Lerman C. 1999 | Lerman C, Biesecker B, Benkendorf JL, et al. Controlled trial of pretest education approaches to enhance informed decision-making for BRCA1 gene testing. J Natl Cancer Inst 1997 Jan;89(2):148-57. | Effectiveness | 5.34 a, b |
| Levine MN. 1992 | 2 studies in 1 article | Levine MN, Gafni A, Markham B, et al. A bedside decision instrument to elicit a patient's preference concerning adjuvant chemotherapy for breast cancer. Ann Intern Med 1992 Jula;117(1):53-8. | Effectiveness | 5.33 a, b |
| Levine MN. 1992 | 2 studies in 1 article | Levine MN, Gafni A, Markham B, et al. A bedside decision instrument to elicit a patient's preference concerning adjuvant chemotherapy for breast cancer. Ann Intern Med 1992 Julb;117(1):53-8. | Development | 4.11 a, b |
| Maslin AM. 1998 | Maslin AM. 1998 | Maslin AM, Baum M, Walker JS, et al. Shared decision-making using an interactive video disk system for women with early breast cancer... including commentary by Beaver K. Nt Research 1998 Nova;3(6):444-55. | Effectiveness | 5.20 a, b |
| McTavish FM. 1995 | Taylor JO. 1994 Gustafson D. 1993 Owens BH. 1996 | McTavish FM, Gustafson DH, Owens BH, et al. CHESS (Comprehensive Health Enhancement Support System): an interactive computer system for women with breast cancer piloted with an underserved population. J Ambulatory Care Manage 1995;18(3):35-41. | Development | 4.4 a, b |
| Molenaar S. 2001 | Molenaar S, Sprangers MA, Rutgers EJ, et al. Decision support for patients with early-stage breast cancer: effects of an interactive breast cancer CDROM on treatment decision, satisfaction, and quality of life. J Clin Oncol 2001;19(6):1676-87. | Effectiveness | 5.22 a, b | |
| North N. 1992 | North N, Cornbleet MA, Knowles G, et al. Information giving in oncology: a preliminary study of tape-recorder use. Br.J.Clin.Psychol. 1992 Sep;31(3):357-9. | Effectiveness | 5.11 a, b | |
| Okamato M. 1999 | Okamato M, Takahashi HO, Yao K, et al. A prospective study of introducing self-determined treatment policy for the patients with hypopharyngeal cancer. Nippon Jibiinkoka Gakkai Kaiho [Journal of the Oto-Rhino-Laryngological Society of Japan] 1999 Jul;102(7):918-24. | Effectiveness | 5.28 a, b | |
| Onel E. 1998 | Onel E, Hamond C, Wasson JH, et al. Assessment of the feasibility and impact of shared decision making in prostate cancer. Urology 1998 Jan;51(1):63-6. | Effectiveness | 5.18 a, b | |
| Pignone M. 2000 | Pignone M, Harris R, Kinsinger L. Vidoetape-Based Decision Aid for Colon Cancer Screening. Ann Intern Med 2000;133:761-9. | Effectiveness | 5.15 a, b | |
| Protiere C. 2000 | Protiere C, Viens P, Genre D, et al. Patient participation in medical decision-making: a French study in adjuvant radio-chemotherapy for early breast cancer. Ann Oncol 2000 Jan;11(1):39-45. | Effectiveness | 5.5 a, b | |
| Ravdin PM. 2001 | Ravdin PM, Siminoff LA, Davis GJ, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J ClinOncol 2001;19(4):980-91. | Development | 4.9 a, b | |
| Rolnick SJ. 1999 | Rolnick SJ, Owens B, Botta R, et al. Computerized information and support for patients with breast cancer or HIV infection. Nurs Outlook 1999 Mar;47(2):78-83. | Development | 4.5 a, b | |
| Sandison AJ. 1996 | Sandison AJ, Gold DM, Wright P, et al. Breast conservation or mastectomy: treatment choice of women aged 70 years and older. Br J Surg 1996 Jul;83(7):994-6. | Effectiveness | 5.27 a, b | |
| Sawka C. 1998a | 2 studies in 1 article | Sawka C, Goel V, Mahut C, et al. Development of a patient decision aid for choice of surgical treatment for breast cancer. Health Expect 1998a;1:23-36. | Development | 4.19 a, b |
| Sawka C. 1998b | 2 studies in 1 article | Sawka C, Goel V, Mahut C, et al. Development of a patient decision aid for choice of surgical treatment for breast cancer. Health Expect 1998b;1:23-36. | Development | 4.20 a, b |
| Schapira MM. 1997 | Schapira MM, Meade C, Nattinger AB. Enhanced decision-making: the use of a videotape decision-aid for patients with prostate cancer. Patient Educ Couns 1997 Feb;30(2):119-27. | Development | 4.1 a, b | |
| Schapira MM. 2000 | Schapira MM, VanRuiswyk J. The effect of an illustrated pamphlet decision-aid on the use of prostate cancer screening tests. J Fam Pract 2000;49(5):418-24. | Effectiveness | 5.1 a, b | |
| Sebban C. 1995 | Sebban C, Browman G, Gafni A, et al. Design and validation of a bedside decision instrument to elicit a patient's preference concerning allogenic bone marrow transplantation in chronic myeloid leukemia. Am J Hematol 1995 Apr;48(4):221-7. | Development | 4.13 a, b | |
| Sepucha KR. 2000 | Sepucha KR, Belkora JK, Tripathy D, et al. Building bridges between physicians and patients: Results of a pilot study examining new tools for collaborative decision making in breast cancer. J Clin Oncol 2000;18(6):1230-8. | Effectiveness | 5.36 a, b | |
| Stalmeier P. 1999 | Unic I. 1998 Unic I. 2000 | Stalmeier P, Unic I, Verhoef L, et al. Evaluation of a shared decision making program for women suspected to have a genetic predisposition to Breast Cancer. Med Decis Making 1999;19:230-41. | Effectiveness | 5.37 a, b |
| Street RLJ. 1995 | Street RL. 1997 | Street RLJ, Voigt B, Geyer CJ, et al. Increasing patient involvement in choosing treatment for early breast cancer. Cancer 1995 Dec;76(11):2275-85. | Effectiveness | 5.21 a, b |
| Unic I. 1998 | Stalmeier P. 1999 Unic I. 2000 | Unic I, Stalmeier PF, Verhoef LC, et al. Assessment of the time-tradeoff values for prophylactic mastectomy of women with a suspected genetic predisposition to breast cancer. Med Decis Making 1998 Jul;18(3):268-77. | Development | 4.22 a, b |
| Volk RJ. 1999 | Volk RJ. 1998 | Volk RJ, Cass AR, Spann SJ. A randomized controlled trial of shared decision making for prostate cancer screening. Arch Fam Med 1999 Jul;8(4):333-40. | Effectiveness | 5.14 a, b |
| Watson M. 1998 | Watson M, Duvivier V, Wade WM, et al. Family history of breast cancer: What do women understand and recall about their genetic risk? J Med Genet 1998;35(9):731-8. | Effectiveness | 5.9 a, b | |
| Whelan T. 1999 | 2 studies in 1 article | Whelan T, Levine M, Gafni A, et al. Mastectomy or lumpectomy? Helping women make informed choices. J Clin Oncol 1999 Juna;17(6):1727-35. | Effectiveness | 5.32 a, b |
| Whelan T. 1999 | 2 studies in 1 article | Whelan T, Levine M, Gafni A, et al. Mastectomy or lumpectomy? Helping women make informed choices. J Clin Oncol 1999 Junb;17(6):1727-35. | Development | 4.16 a, b |
| Whelan TJ. 1995 | 2 studies in 1 article | Whelan TJ, Levine MN, Gafni A, et al. Breast irradiation postlumpectomy: development and evaluation of a decision instrument. J Clin Oncol 1995 Apra;13(4):847-53. | Effectiveness | 5.31 a, b |
| Whelan TJ. 1995 | 2 studies in 1 article | Whelan TJ, Levine MN, Gafni A, et al. Breast irradiation postlumpectomy: development and evaluation of a decision instrument. J Clin Oncol 1995 Aprb;13(4):847-53. | Development | 4.12 a, b |
| Wilson RG. 1988 | Wilson RG, Hart A, Dawes PJ. Mastectomy or conservation: the patient's choice. BMJ 1988 Nov;297(6657):1167-9. | Effectiveness | 5.19 a, b | |
| Wolberg WH. 1987 | Wolberg WH. 1989 Wolberg WH. 1991 Ward S. 1989 | Wolberg WH, Tanner MA, Romsaas EP, et al. Factors influencing options in primary breast cancer treatment. J Clin Oncol 1987 Jan;5(1):68-74. | Effectiveness | 5.38 a, b |
| Wolf AM. 1996 | Wolf AM. 1998 Wolf AM. 1997 | Wolf AM, Nasser JF, Schorling JB. The impact of informed consent on patient interest in prostate-specific antigen screening. Arch Intern Med 1996 Jun;156(12):1333-6. | Effectiveness | 5.7 a, b |
| Wolf AM. 2000 | Wolf AM, Schorling JB. Does informed consent alter elderly patients' preferences for colorectal cancer screening? Results of a randomized trial. J Gen Intern Med 2000 Jan;15(1):24-30. | Effectiveness | 5.8 a, b |
| Year of Publication | Overall n (%) | Effectiveness of a Decision Aid n (%) | Development of a Decision Aid n (%) |
| 1981-1985 | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| 1986-1990 | 3 (4.9) | 3 (7.7) | 0 (0.0) |
| 1991-1995 | 16 (26.2) | 7 (17.9) | 9 (40.9) |
| 1996-2001 | 41 (67.2) | 28 (71.8) | 13 (59.1) |
| Total a | 61 (99.9) | 39 (100.0) | 22 (100.0) |
Not exactly 100% due to rounding error.
| Language of Publication | Overall n (%) | Effectiveness of a Decision Aid n (%) | Development of a Decision Aid n (%) |
| English | 59 (96.7) | 37 (94.9) | 22 (100.0) |
| Japanese | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| Swedish | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| Total a | 61 (99.9) | 39 (100.1) | 22 (100.0) |
Not exactly 100% due to rounding error.
| Country Where Study Was Centered (more than one possible) | Overall n (%) | Effectiveness of a Decision Aid n (%) | Development of a Decision Aid n (%) |
| United States | 25 (41.0) | 16 (41.0) | 9 (41.0) |
| Canada | 20 (32.8) | 10 (25.6) | 10 (45.5) |
| Australia | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| United Kingdom | 7 (11.5) | 7 (18.0) | 0 (0.0) |
| France | 3 (4.9) | 1 (2.6) | 2 (9.1) |
| Japan | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| Netherlands | 3 (4.9) | 2 (5.1) | 1 (4.6) |
| Sweden | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| Not Clear | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| Source of Funding | Overall n (%) | Effectiveness of a Decision Aid n (%) | Development of a Decision Aid n (%) |
| Industry | 2 (3.3) | 0 (0.0) | 2 (9.1) |
| Other | 35 (57.4) | 24 (61.5) | 11 (50.0) |
| Not reported | 23 (37.7) | 14 (35.9) | 9 (40.9) |
| Not clear | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| Total | 61 (100.0) | 39 (100.0) | 22 (100.0) |
| Design of Primary Study (more than one possible) | Overall n (%) | Effectiveness of a Decision Aid n (%) | Development of a Decision Aid n (%) |
| Case series | 28 (45.9) | 16 (41.0) | 12 (54.6) |
| Randomized controlled trial | 18 (29.5) | 16 (41.0) | 2 (9.1) |
| Other | 9 (14.8) | 2 (5.1) | 7 (31.8) |
| Controlled trial | 5 (8.2) | 4 (10.3) | 1 (4.6) |
| Survey | 1 (1.6) | 0 (0.0) | 1 (4.6) |
| One group pre/post design | 2 (3.3) | 1 (2.6) | 1 (4.6) |
| Focus of the Study: Focal Disease (more than one possible) | Overall n (%) | Effectiveness of a Decision Aid n (%) | Development of a Decision Aid n (%) |
| Breast cancer | 37 (60.7) | 23 (59.0) | 14 (63.6) |
| Colorectal cancer | 3 (4.9) | 2 (5.1) | 1 (4.6) |
| Leukemia | 1 (1.6) | 0 (0.0) | 1 (4.6) |
| Lung cancer | 4 (6.6) | 2 (5.1) | 2 (9.1) |
| Oral/Pharyngeal cancer | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| Ovarian cancer | 4 (6.6) | 2 (5.1) | 2 (9.1) |
| Prostate cancer | 13 (21.3) | 11 (28.2) | 2 (9.1) |
| Not specified | 1 (1.6) | 1 (2.6) | 0 (0.0) |
| Other | 1 (1.6) | 0 (0.0) | 1 (4.6) |
| Focus of the Study: Type of Decision (more than one possible) | Overall n (%) | Effectiveness of a Decision Aid n (%) | Development of a Decision Aid n (%) |
| Prevention | 2 (3.2) | 1 (2.6) | 1 (4.6) |
| Screening | 15 (24.6) | 12 (30.8) | 3 (13.6) |
| Treatment | 47 (77.1) | 28 (71.8) | 19 (86.4) |
| Other | 1 (1.6) | 0 (0.0) | 1 (4.6) |
| Characteristics of Sample (more than one possible) | Overall n (%) | Effectiveness of a Decision Aid n (%) | Development of a Decision Aid n (%) |
| Patients with focal disease | 41 (67.2) | 28 (71.8) | 13 (59.1) |
| Patients with noncancer disease | 1 (1.6) | 0 (0.0) | 1 (4.6) |
| Healthy people at risk for cancer | 14 (23.0) | 11 (28.2) | 3 (13.6) |
| Health care volunteers | 6 (9.8) | 1 (2.6) | 5 (22.7) |
| Nonhealth care volunteers | 6 (9.8) | 0 (0.0) | 6 (27.3) |
| Age Category (more than one possible) | Overall n (%) | Effectiveness of a Decision Aid n (%) | Development of a Decision Aid n (%) |
| Adults (18 years or older) | 61 (100.0) | 39 (100.0) | 22 (100.0) |
| Adolescents (age 13-17) | 0 (0.0) | 0 (0.0) | 0 (0.0) |
| Children (<13 years) | 0 (0.0) | 0 (0.0) | 0 (0.0) |
The number of studies has more than doubled during the 5 years from 1996 to 2001.
Thirty-eight percent of the studies did not report any information about the source of funding for the research.
Seventy-four percent of studies were centered in North America.
Ninety-seven percent of studies were published in English.
Case series designs (28) accounted for 46 percent of all included reports. There were 16 RCTs, four non-RCTs, and the remaining studies were a mix of other designs.
Sixty-one percent of studies (37) included patients with breast cancer. Twenty-one percent included patients with prostate cancer, 7 percent ovarian cancer, and the remaining studies included patients with a mix of different types of cancer.
In nearly all studies (99 percent), the participants were over age 18.
Across all studies, the most common context of the decision was treatment (71 percent), followed by screening and prevention (28 percent). However, when only RCTs were considered, in 44 percent (7/16) of studies, decisions were made in a treatment context, and in 56 percent (9/16) of studies, the context was screening.
Thirty-six percent (22/61) reported the developmental process of a decision aid, and 64 percent (39/61), the effectiveness of a decision aid.
Of the 39 studies investigating the effectiveness of a decision aid, only 1 study focused on a special population (women over 70 years). Only 2 studies of 22 developed a decision aid for special populations (Spanish-speaking Mexican-American women and low-income African-American women).
Twenty-two studies that report the development of cancer-related decision aids are described in this chapter. These studies share one main characteristic: the development of a DA intervention that could be used in a real clinical situation. Seven of the 22 DAs have already been used to help people in the decisionmaking process,24-30 and the results regarding their effectiveness are described in Chapter 5. Of the remaining development studies, one of the studies reported that their DA intervention is currently being tested with patients at the point of decisionmaking.31 The aim of this chapter is to summarize and characterize the DAs' development process, in which the authors have tried to evaluate the psychometric characteristics of the instrument, as well as the participants' perceptions of using the DAs.
Eight studies reported the development of decision board (DB) interventions.27-29,32-36 Seven studies assessed interactive computer programs.24,37-42 One study investigated the use of a computer program that generated patient-specific printed output.31 One study assessed the use of a videotape intervention,24 and one study explored the use of a tradeoff analysis supplemented with "visual aids."26 Three studies investigated the use of audiotape workbooks.43-45 One study30 reported the development of a complex DA intervention consisting of a DA videotape, DA brochure, and counseling.
Nineteen studies evaluated DAs in the context of treatment decisionmaking.24-29,31-34,36-40,42-44,46 Two studies involved screening decisions,35,41 and one study was about prevention.30
Of the 22 studies included, there were 14 studies on breast cancer24,27-31,35-40,43,44 and two each on prostate cancer,42,46 ovarian cancer,33 and lung cancer.25,26,34 There was one study each on colon cancer41 and leukemia.32
All the studies included adult populations. For the evaluation of the DA, the authors selected healthy volunteers in nine studies;27-29,32,33,35,36,41 in one study, primary care patients without cancer were included.46 In 12 studies, cancer patients participated; 1 study included previously treated cancer patients,26 8 were after the treatment decision was made,25,31,33,37-40,42 and 4 studies included cancer patients at the point of treatment decisionmaking.34,39,43,44 In one study, women suspected of having a genetic predisposition to breast cancer who were making preventive decisions were participants.30
Two studies were specifically performed to evaluate a DA in special populations. McTavish and colleagues39 assessed an interactive computer program, the Comprehensive Health Enhancement Support System (CHESS) in eight African-American breast cancer patients from impoverished neighborhoods.39 As well, Lawrence and colleagues developed a DB for breast cancer screening decisions among European-American and Mexican-American women in the United States.35
| Author (year) | Intervention | Design | Type of Decision | Type of Cancer | Sample | Outcomes |
|---|---|---|---|---|---|---|
| Shapira (1997) | Videotape | One group pre/post-intervention | Treatment | Prostate | Primary care patients without cancer | Clarity of DA Comprehensibility of DA Knowledge Attitudes toward decisionmaking Satisfaction |
| Gustafson (1993) Study 1 | Interactive computer program | Case series | Treatment | Breast | Breast cancer patients | Acceptability of DA Feasibility Would recommend DA to other patients Emotions |
| Gustafson (1993) Study 2 | Interactive computer program | Case series | Treatment | Breast | Breast cancer patients | Acceptability of DA Feasibility Would recommend DA to other patients Emotions Satisfaction |
| McTavish (1995) | Interactive computer program | Case series | Treatment | Breast | Breast cancer patients | Acceptability of DA Feasibility Emotions Decision |
| Rolnick (1999) | Interactive computer program | RCT | Treatment | Breast | Breast cancer patients | Acceptability of DA Feasibility |
| Dolan (1995) | Interactive computer program | Case series | Screening | Colon | Healthy volunteers | Feasibility of DA Acceptability of DA Decision Reasons for patients' choice treatment |
| Chapman (1995) | Interactive computer program | Controlled Trial | Treatment | Breast | Nursing and psychology students | Knowledge Preference |
| Jenkinson (1998) | Interactive computer program | Case series | Treatment | Prostate | Prostate cancer patients | Acceptability of DA |
| Ravdin (2001) | Computer program with printed output | Case series | Treatment | Breast | Breast cancer patients | Acceptability of DA |
| Brundage (1997) | Tradeoff analysis | Test-Retest | Treatment | Lung | Previously treated cancer patients | Construct validity of DA Reliability of DA Feasibility of DA Decision Desire level of involvement in decisions |
| Levine (1992) | Decision Board | Test-Retest | Treatment | Breast | Healthy volunteers and previously treated breast cancer patients | Construct validity of DA Reliability of DA Decision |
| Whelan (1995) | Decision Board | Survey | Treatment | Breast | Healthy volunteers | Comprehensibility of DA |
| Sebban (1995) | Decision Board | RCT & Test-Retest | Treatment | Leukemia | Healthy volunteers | Construct validity of DA Reliability of DA Feasibility of DA Clarity of DA Comprehensibility of DA Decision Satisfaction with the choice |
| Elit (1996) Study 1 | Decision Board | Test-Retest | Treatment | Ovarian | Healthy volunteers and ovarian cancer patients after chemotherapy | Construct validity of DA Reliability of DA Feasibility of DA Acceptability of DA Knowledge Anxiety Decision |
| Elit (1996) Study 2 | Decision Board | Case series | Treatment | Ovarian | Ovarian cancer patients | Feasibility of DA Acceptability of DA Knowledge Anxiety Decision |
| Whelan (1999) | Decision Board | Test-Retest | Treatment | Breast | Healthy volunteers | Construct validity of DA Reliability of DA Acceptability of DA Decision |
| Lawrence (2000) | Decision Board | Test-Retest Case series | Screening | Breast | Staff and healthy volunteers | Construct validity of DA Reliability of DA Knowledge Decision |
| Carrere (2000) | Decision Board | Test-Retest | Treatment | Breast | Healthy volunteers | Construct validity of DA Reliability of DA Knowledge Decision |
| Sawka (1998) Study 1 | Audiotape + workbook | Case series | Treatment | Breast | Breast cancer patients | Clarity of DA Acceptability of DA Satisfaction with the DA Anxiety Knowledge Decisional conflict |
| Sawka (1998) Study 2 | Audiotape + workbook | Case series | Treatment | Breast | Breast cancer patients | Knowledge Decisional conflict |
| Fiset (2000) | Audiotape + workbook | Case series; survey | Treatment | Lung | Lung cancer patients; oncologists | Acceptability of DA Usefulness of DA |
| Unic (1998) | Counseling + Videotape + Pamphlet | Test-Retest | Prevention | Breast | Healthy women at risk of breast cancer | Convergent validity of DA Reliability of DA Feasibility of DA Decision |
Ten studies were case series,25,31,34,37-39,41-44 and six studies used a test/retest design.26,27,29,30,33,36 There was a combination of designs in two studies;32,35 a subgroup of participants in an RCT32 were enrolled in a test/retest study, and the authors of one case series35 used the same population to perform a test/retest study. There was one study each of the following study designs: survey,28 one-group pre/post intervention,46 RCT,40 and controlled trial.24
| Author (Year) | ID # | Reporting | External Validity | Internal Validity: Bias | Internal Validity: Confounding | FINAL SCORE |
|---|---|---|---|---|---|---|
| Brundage, 1997 | 149 | 8/8 (100%) | 1/3 (33%) | 4/6 (66.6%) | 2/2 (100%) | 15/19 (78.9%) |
| Carrere, 2000 | 5013 | 7/8 (88%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 11/19 (57.8%) |
| Chapman, 1995 | 116 | 6/9 (67%) | 0/3 (0%) | 2/6 (33.1%) | 3/4 (75%) | 11/22 (50%) |
| Dolan, 1995 | 4933 | 5/8 (63%) | 0/3 (0%) | 3/6 (50%) | 2/2 (100%) | 10/19 (52.6%) |
| Elit, 1996 [Study 1] | 119 | 4/8 (50%) | 0/3 (0%) | 3/6 (50%) | 2/2 (100%) | 9/19 (47.3%) |
| Elit, 1996 [Study 2] | 7539 | 4/8 (50%) | 1/3 (33%) | 2/6 (33.1%) | 1/2 (50%) | 10/19 (52.6%) |
| Fiset, 2000 | 7873 | 4/8 (50%) | 0/3 (0%) | 1/6 (16.6%) | 1/2 (50%) | 6/19 (31.5%) |
| Gustafson, 1993 [Study 1] | 1196 | 3/8 (38%) | 0/3 (0%) | 3/7 (42.8%) | 1/2 (50%) | 7/20 (35%) |
| Gustafson, 1993 [Study 2] | 7538 | 3/8 (38%) | 0/3 (0%) | 3/7 (42.8%) | 1/2 (50%) | 7/20 (35%) |
| Jenkinson, 1998 | 814 | 4/7 (57%) | 0/3 (0%) | 2/6 (33.1%) | 1/2 (50%) | 7/18 (38.8%) |
| Lawrence, 2000 | 5012 | 6/8 (75%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 10/19 (52.6%) |
| Levine, 1992 | 7117 | 5/8 (63%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 9/19 (47.3%) |
| McTavish, 1995 | 5045 | 2/8 (25%) | 0/3 (0%) | 3/7 (42.8%) | 1/2 (50%) | 6/20 (30%) |
| Ravdin, 2001 | 7852 | 3/8 (38%) | 0/3 (0%) | 1/6 (16.6%) | 1/3 (33.3%) | 5/20 (25%) |
| Rolnick, 1999 | 386 | 1/9 (11%) | 0/3 (0%) | 4/7 (57.1%) | 2/5 (40%) | 7/24 (29.1%) |
| Sawka, 1998 [Study 1] | 199 | 6/7 (86%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 10/18 (55.5%) |
| Sawka, 1998 [Study 2] | 7537 | 6/7 (86%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 10/18 (55.5%) |
| Sebban, 1995 | 117 | 7/8 (88%) | 0/3 (0%) | 2/6 (33.1%) | 3/5 (60%) | 12/22 (54.5%) |
| Shapira, 1997 | 123 | 4/7 (57%) | 0/3 (0%) | 2/6 (33.1%) | 1/2 (50%) | 7/18 (38.8%) |
| Unic, 1998 | 872 | 8/8 (100%) | 1/3 (33%) | 4/6 (66.6%) | 2/2 (100%) | 15/19 (78.9%) |
| Whelan, 1995 | 7535 | 3/7 (43%) | 0/3 (0%) | 1/6 (16.6%) | 1/2 (50%) | 5/18 (27.7%) |
| Whelan, 1999 | 7536 | 5/8 (63%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 9/19 (47.3%) |
Only one study described the development of a videotape intervention. Schapira and colleagues46 reported the development of a DA to assist patients in considering treatment options (radiation therapy, radical prostatectomy, watchful waiting) for localized prostate cancer.
The videotape script content was based on a review of the literature about the morbidity and mortality associated with the three treatment options, and on input from a multidisciplinary team of experts (i.e., a radiation oncologist, a urologist). Subsequently, the relevance of the information was evaluated by two groups of patients who had been treated for clinically localized prostate cancer. These focus groups addressed the importance of information regarding treatment complications, such as impotence as well as the presentation of quantitative information rather than qualitative ('risk of impotence is 40 percent' instead of 'a small risk'). After gathering all the information, the final content of the script included: anatomy of the prostate gland, epidemiology of prostate cancer, treatment options and outcomes, efficacy of treatment and management of possible treatment side effects. A 20-minutes long videotape was designed following the principle of role modeling to encourage active involvement in decisionmaking. A professional filming company produced the videotape; and the edited version was piloted on a group of 10 previously treated prostate patients; men responded favorably to the DA with respect to the relevance of content, clarity and flow of information.
Validity. Not reported.
Reliability. Not reported.
Feasibility. Not reported.
The authors reported that "97 percent of the participants felt that the information presented in the videotape was clear and easy to understand." Participants expressed satisfaction with the information in this format, and stated that the inclusion of patient interviews was helpful in making the information relevant.
The authors developed a 20-item questionnaire to evaluate knowledge about the videotape content. Participants answered the questionnaire before and after having viewed the videotape. After the intervention, there was a statistically significant increase in correct responses in 10 of the 14 questions (p < 0.05).
Seven studies24,37-42 focused on the development of interactive computer programs (ICP). Four37-40 evaluated the use of the "Comprehensive Health Enhancement Support System" (CHESS) in breast cancer patients. Of the other three studies, one assessed an ICP for helping people choose among different alternatives for colon cancer screening.41 A second study was a preliminary evaluation of the videodisk, "A Shared Decision Program," for women with breast cancer.24 The third study assessed an ICP that was designed to assist prostate cancer patients in making treatment decisions.42
Since 1993, Gustafson and colleagues have been evaluating CHESS in different populations. Three of the reviewed studies were case series37-39 and one was an RCT.40 CHESS is a disease-specific computer-based system that is designed to meet information and support needs in a user-controlled and nonthreatening manner for people facing health problems. In the prototype, the visual interface was interactive, easy to use, and utilized color and graphics on a personal computer with a VGA monitor and a modem. This program contained modules for breast cancer, acquired immunodeficiency syndrome, substance abuse, sexual assault, and other conditions. The components of CHESS evolved from 7 in the first study37 to 11 in the last study.40 These components were grouped into three main areas: information, social support, and a problem-solving component. Of particular relevance was one module called, "Decision Aid," that used utility theory to help patients through difficult decisions such as what surgery to have and whether to take adjuvant chemotherapy or tamoxifen treatment. Users could read the description of each option or read an excerpt from a personal story of a woman who chose that option. They could read the criteria used by other women to make a choice and a research summary about their choice. Different treatment choices were included such as choice of surgery (mastectomy vs. lumpectomy), choice of adjuvant hormonal therapy or chemotherapy, or choice of joining a clinical trial. The authors reported that the "Decision Aid" section helped users work through difficult and specific decisions, but the module "does not tell users what they should do; it shows users how the computer used their input to predict the choice they might make." The "Action Plan" module helped users implement a decision by combining statistical decision theory and change theory. The module asked users their plan to implement a decision, predicted the likelihood of success, and suggested how they could strengthen their prospects. Through a modem, users of CHESS also had the opportunity to interchange information and experiences with other patients in an on-line support group that included trained facilitators to monitor the group.
The selection of content for CHESS began with a needs assessment that used focus groups and survey research. A panel of breast cancer patients, their partners, and daughters; a surgeon and a nurse practitioner; and two researchers developed three information needs surveys for patients, partners, and adult children. The authors surveyed 400 patients and family members at diagnosis and 3 and 9 months later; all participants were recruited from breast cancer clinics. CHESS was planned for users' homes, workplaces, libraries, and other community sites; thus far, its evaluation has been conducted at patients' homes. The first version was designed at a 10th-grade reading level. The authors reported that they intended to simplify the reading level to grade 8 and to add sound and voice recognition, motion video, and touch screens; however, it is not clear whether or not these features have been incorporated. They also reported that CHESS is reviewed and updated biannually, and that "...this easy update feature allows users access to the most recent information and discoveries about breast cancer...."
The first two field studies37,38 included newly diagnosed breast cancer patients who had chosen surgical (mastectomy or lumpectomy) and adjuvant (radiation, chemotherapy, or tamoxifen) treatment. Ten breast cancer patients and five adult daughters were enrolled in the first pilot study, and 20 patients in the second. Women in the first pilot study suggested many enhancements; and after another year of development, the second pilot study was conducted (details not provided). In the third study, CHESS was evaluated among eight African-American women, with stage I or II breast cancer, from impoverished neighborhoods in Chicago. The final study was an RCT to assess the impact on quality of life and the costs of care. The authors studied 36 newly diagnosed stage 0-II breast cancer patients who received CHESS (intervention group, n = 19), or Dr. Susan Love's Breast Book (control group, n = 17). In this study, the authors focused their results on the patients' use and impressions of CHESS.
Validity. Not reported.
Reliability. Not reported.
Feasibility. Across the four studies, the authors quantified the time that each patient spent using each program component. Overall, the 10 women in the first study37 used CHESS 546 times during the 50-day trial, and the 20 women in the second study38 used it 1,131 times during the 70-day trial. In the first two studies, the Decision Aid and Action Plan were the least used components; however, the authors reported that the first CHESS versions only contained the surgery decision program, and most of the women had already made their decision before the studies had begun. African-American women in the third study39 used CHESS 886 times within the 15-week access period. Fifty five percent of the total time of use was spent in the social support sections, 41 percent in the information components, and only 4 percent in the Decision Aid and Conflict components. The authors reported that each of the 36 women in the RCT40 used an average of 62 "hits" during the 3 months of implementation. Initially, all participants used the system more frequently; its use decreased to an average of twice per week between the 3rd and 7th week, and once per week through to the end of the 3 months. The Discussion Group was the component most used, whereas the Decision Aid and Action Plan were less used.
In the first two studies,37,38 participants rated the value of each CHESS component on a 1- to 5-point scale. In both studies, patients' mean scores were 3.0 or higher (see Evidence Tables 4.2b and 4.3b for each component). The African-American women39 utilized a 1- to 7-point scale for this outcome; their mean scores were 6.5 or higher.
Women in the first two studies were asked to appraise the perceived value of using CHESS for other patients during diagnosis, treatment, and after treatment. They assessed this item on a 1- to 5-point scale; participants' mean scores were 3.5 or higher. The value of CHESS during diagnosis and treatment was rated the highest.
In the second study,38 the authors reported that 6 of 17 patients preferred talking with a visiting nurse or with a patient survivor rather than using CHESS, because they wanted rapid and precise answers to their questions.
None of the studies were primarily focused on the actual decisions that were made. However, in the study of African-American women,39 the authors reported that one woman had avoided a surgical decision for months and, after receiving CHESS, she re-entered treatment.
Based on a 1- to 7-point scale, the authors asked women in the first three studies37-39 to rate their "emotions" while using CHESS. They considered two types of "emotions" -- positive (7 items) and negative feelings (11 items). Overall, participants' mean ratings were 4.0 or higher for the positive feelings and 4.0 or less for the negative feelings (see Evidence Tables 4.2b, 4.3b, and 4.4b).
In the RCT,40 the authors reported that CHESS was well received by the women. They found it easy to use and considered that having the software for 3 months was adequate. Fewer than half of all the CHESS users said they would be willing to purchase the tool, but 50 percent reported interest in borrowing computers or software.
Dolan41 described the results of using an analytic hierarchy process (AHP) in 20 volunteers who were offered five options regarding screening regimens for colon cancer. The authors reported that the AHP evaluated was a user-friendly technique that could provide a way to effectively engage patients in the process of medical decisionmaking because it enabled users to elicit subjective values and combine them in an explicit, unbiased manner.
The author did not report how the AHP was developed. The decision aid used for the study was based on Eddy's "balance sheet" that described the pros and cons of alternative approaches to colon cancer screening for 50-year-old men who had a family history of colon cancer in a first-degree relative. At the top of the AHP model was the goal of the decision, to maintain health and well-being. The five decision criteria located in the middle level of the model represented the potential risks and benefits of screening (i.e., decrease the risk of colon cancer, avoid false positive tests, minimize costs). The five alternatives at the bottom level provided a spectrum of risk-benefit profiles varying from "careful followup," which was considered the least likely to decrease cancer risk but the best in terms of the other four criteria, to "colonoscopy every 5 years," which was described as the biggest reduction in cancer risk but the worst alternative in every other way.
The analysis consisted of pair-wise comparisons among the screening alternatives and pair-wise comparisons among the criteria relative to the goal. The author reported that "Expert Choice" was the software used for the AHP analysis, which was described as a standard AHP software package running on a laptop computer.
The intervention consisted of a structured interview where the participants imagined that they were 50 years old, had a relative with colon cancer, and were making a decision about a colon cancer screening program for the next 25 years. The author explained the different options for colon cancer screening: careful followup, sigmoidoscopy, annual stool test and sigmoidoscopy, barium enema, and colonoscopy. After the participant understood the problem, he/she completed a guided AHP analysis using "Expert Choice" software. Following the analysis, the results were discussed with the participants.
Validity. Not reported.
Reliability. Not reported.
Feasibility. The author reported this outcome as a cutoff time: the participants were judged to be capable of using the AHP if they completed the analysis in 45 minutes or less. The mean time required to complete the analysis was 35 minutes, and 19 participants finished the analysis in less than 45 minutes.
Nineteen of the 20 participants agreed that if they had a close relative with colon cancer, they would prefer to go through this type of analysis before making a decision. Nineteen felt that they learned useful information about colon cancer screening. All the participants indicated that, if the scenario were real, they would choose the option that came out best on the analysis. Eighteen of 20 participants answered positively when they were asked about using this type of analysis for other health care decisions.
According to the AHP analysis, the best option was colonoscopy every 5 years for 10 participants, careful followup for 9, and barium enema every 5 years for 1. Minimizing the chances of developing cancer was ranked the most important priority by 15 participants; 4 considered the side effects, and 1 wished to avoid costs.
Chapman and colleagues24 reported the preliminary evaluation of the videodisk entitled "Treating Your Breast Cancer" produced by the Foundation for Informed Medical Decision Making. The Shared Decision Program (SDP) is an interactive videodisk containing two sections: a core program with relatively few interactive options and a more interactive "Learn More" section, where the viewer selects from a menu of topics.
Not reported.
Participants were not exposed to the videodisk program. Instead, the authors used a 40-minute linear videotape version. Participants watched the core program, which was one of the two SDP sections. This program contained information about the breast and breast cancer and an overview of the surgical treatment options (breast-sparing with radiation treatment, mastectomy followed by breast reconstruction, and mastectomy followed by use of a breast prosthesis), including the advantages and disadvantages of each surgical procedure. The program included interviews with five breast cancer survivors who talked about the decision they made and how satisfied or unsatisfied they were after having made the decision and going through the treatment they chose. The authors compared the videotape with a decision aid brochure whose text was produced from the video script. The booklet contained photos selected to closely match those presented in the video, but did not contain the interviews and cartoon drawings. Nursing (n = 34) and psychology (n = 48) students participated in this controlled trial study; half of each student group viewed the video (n = 40), and the other half read the booklet (n = 42). The authors did not report how they assigned participants to the study groups.
Validity. Not reported.
Reliability. Not reported.
Feasibility. Not reported.
The authors reported the knowledge scores in the same order as described above. The authors reported that there was no difference between video and booklet groups (F < 1; p value was not specified). Nursing students pre- and posttest knowledge scores were significantly higher than those of the psychology students (p < 0.0001). Mean scores for knowledge were significantly higher in the posttest than in the pretest evaluation (p < 0.0001).
The first prototype was developed after interviewing 10 prostate cancer patients who provided their information needs and their opinions about three different interfaces. Subsequently, the authors incorporated information obtained from different sources, such as patient education materials and literature aimed at educating specialists. A group of experts reviewed the material to ensure accuracy and offered suggestions for improvement. The resulting interactive program contained information regarding the diagnosis (i.e., diagnostic test), treatment options (radical prostatectomy, radiation therapy, watchful waiting), followup (i.e., side effects of treatment), and role of support groups as well as links to the Internet, glossary, and bibliography. The prototype incorporated text, graphics, and a video interview with a patient. The patient discussed his reactions to a diagnosis of localized prostate cancer, his treatment choice, and his subsequent recovery from surgery.
The first prototype was evaluated in a qualitative pilot study with five patients.
Validity. Not reported.
Reliability. Not reported.
Feasibility. Not reported.
Using a semistructured one-on-one interview, the authors reported that, after the session with the computer, participants had positive responses and described the prototype as relevant, useful, and navigable.
Ravdin and colleagues31 report the development of a computer program called "Adjuvant" that assisted women diagnosed with breast cancer in deciding whether to have adjuvant treatment (chemotherapy or endocrine therapy).
The computer program produced prognosis estimates using survival outcomes from surveillance, epidemiology, and end-results data. The program used the results of the 1998 overviews of randomized trials of adjuvant therapy to provide estimates regarding the efficacy of adjuvant treatment.
The Adjuvant computer program was designed to allow an oncologist to enter patient-specific information (age, menopausal status, comorbidity estimate, tumor size, number of positive lymph nodes, and estrogen receptor status). The program then used actuarial analysis to project overall survival and disease-free survival with and without adjuvant therapy for an individual patient. For adjuvant chemotherapy, the computer program based its estimates on the efficiacy of polychemotherapy (cyclophosphamide/methotrexate/fluorouracil-like regimens, or anthracycline-based therapy, or therapy based on both an anthracycline and a taxane). For adjuvant endocrine therapy, the computer program used estimates of the efficacy of 5 years of tamoxifen treatment. The patient-specific survival estimates generated by the computer program were provided to the patient as a printed output in either a numerical or graphical format.
Validity. Not reported.
Reliability. Not reported.
Feasibility. Not reported.
The authors assessed the acceptability of the printed output format with 24 breast cancer patients who were currently undergoing adjuvant treatment or followup care. The authors did not report the raw data; however, they did cite examples of the types of changes that were made to reflect patient responses. After the output format was revised, the authors then tested the acceptability of the new format with another group of breast cancer patients (n=25; no data provided).
Brundage and colleagues26 evaluated a treatment-tradeoff interview for helping lung cancer patients make treatment decisions between high-dose radiotherapy versus low-dose radiotherapy, and between combination treatment with chemoradiotherapy versus high-dose radiotherapy.
The content of the intervention was supported by the results of published clinical trials and from a chart review of patients who had attended the authors' institution.
The intervention consisted of a 1-hour structured interview. For each comparison, treatment description cards were laid out so that two treatments could be viewed side-by-side. The description components included details of the actual treatment regimen, side effects, and effects of the treatment on personal functioning, emotional state, social interaction, and disease symptoms. Survival data were displayed using a time line that indicated time from treatment and a sliding-bar instrument that indicated percentage alive and percentage dead at a given time. For both comparisons, participants stated their preference (participants could decline both treatments) after the two treatments were described. First, the authors displayed the 6-month survival percentages for the two treatments as being equal. Subsequently, the survival associated with the nonpreferred treatment was then raised systematically until the participant's preference shifted to the alternative treatment; the authors recorded the switch point of preference. This same procedure was performed for 1-year and 3-year survival.
The authors included 56 cancer patients who had completed treatment and 20 staff members. They were asked to imagine being a stage IIIB non-small-cell lung cancer patient and to state their treatment preferences for each comparison.
The authors calculated the survival advantage threshold (SAT) for the six tradeoffs (desired survival percentage minus baseline survival percentage). There was a wide range of SATs for patient and staff, from -5 percent to 60 percent. The authors reported that cancer patient thresholds were generally lower than those declared by staff.
Twenty participants were interviewed a second time to determine the consistency of their responses (preferences and SATs) 3 or more weeks after the first intervention. The authors reported that the preference consistencies ranged from 70 and 100 percent for the six tradeoffs. Percentages for SATs exact agreement ranged from 20 to 40 percent (median 32.5 percent) and agreements within 5 percent ranged from 55 to 85 percent. The lowest correlation coefficient was 0.7.
All but three participants completed the intervention; two lung cancer patients did not understand the method and could not state a preference. Another lung cancer patient became frustrated with the method, apparently because of the numbers and proportions; he could not participate in the second tradeoff. Three additional patients understood the method but were unable to provide responses for the 6-month and/or 1-year survival time points. The authors reported that the mean time to complete the interview was 60 minutes.
The authors also assessed participants' desired level of involvement in decisions; staff members were more likely than patients to prefer active roles (p < 0.01), and no staff members preferred a passive role in decisions about their own medical treatment.
Whelan and colleagues47 described the DB as a visual aid that targeted the physician-patient interaction to improve communication by presenting information in a standardized manner, using spoken and written language supported by the use of visual aids and relying on repetition. The DBs permitted patients to state their preference for treatment or screening options. Eight studies27-29,32-36 about the development of the DB were reviewed; two of these studies were described in the same paper.33,34 All but one study focused on treatment decisions; Lawrence and colleagues35 designed a DB for screening decisions. Four DBs27-29,36 were developed for breast cancer patients, two for ovarian cancer,33,34 and one for leukemia.32
Overall, the eight studies followed the same steps for developing the DB; a review of the literature about the different treatment or screening options was reported in five studies.27-29,32,35 In two studies,33,34 the authors based the DB content on the observation of four patient consultations with their oncologist and included information about the disease status, treatment options, and treatment protocol. Evaluation of the information contained in the DB by focus groups of patients and clinicians was described in six studies.27,29,33-36 Details of the DB clarity and comprehensibility were provided in all eight studies; these items were assessed only by clinicians,27,28,32,36 or by previously treated patients and clinicians.29,33-35
The following studies are reported based on the year of publication.
Levine and colleagues27 enrolled 30 healthy volunteers who were asked to choose between adjuvant chemotherapy and no treatment after viewing a DB. Scenarios were initially created that described adjuvant chemotherapy options for patients with early stage breast cancer postsurgery. The scenarios provided information describing a patient's choice, a patient's quality of life based on her choice of treatment compared with no treatment, and the possible outcomes (recurrence compared with no recurrence). The authors presented the risk for treatment failure in terms of recurrence of breast cancer (negative framing). Morbidity was described to the patient in the chemotherapy scenario using probabilistic language "to capture the uncertainty of the potential treatment's side effects." The authors used a verbal description of the uncertainty (i.e., likely) rather than a numerical one (i.e., 0.8). The DB had three subtitles: "treatment choice," "chance of outcome," and "outcome," and, except for the titles, the board was empty when the interview began. The information cards were held by the patient while the interviewer read aloud; the plastic-laminated card was then attached to the DB with Velcro. By the end of the session, all the information was on the board. The board was described as "large enough to permit the patient to read the display, but not so large that it is cumbersome to store and carry."
Whelan and colleagues28 assessed, in 10 healthy female volunteers and 16 node-negative patients who had been treated with breast irradiation postlumpectomy, a DB developed for breast cancer patients to elicit their preference between radiation and no radiation after lumpectomy. The authors created an introduction and scenarios. The introduction provided the patient with some background information about the disease, prognosis, and the purpose of the board. The scenarios described the treatment options of radiation therapy or no radiation and the subsequent outcome of chance of recurrence of cancer in the breast for women with node-negative breast cancer who were treated by lumpectomy and axillary dissection. Descriptions of the risk of recurrence were developed using visual aids. The radiation therapy scenario described the treatment program as well as potential side effects. The probability rates were tailored to known patient prognostic factors of age and tumor size. The DB had two subtitles, "treatment choice" and "results of treatment choice," and the board was empty at the beginning of the interview. The patient and clinician (nurse or physician) read each information card and attached it to the board with Velcro. At the end of the discussion, all of the information cards were on the board.
Whelan and colleagues29 developed a DB for primary treatment in breast cancer patients; 30 healthy female volunteers chose between lumpectomy plus radiation or mastectomy. Scenarios were developed to give information about the disease, the purpose of the decision instrument, the two treatment options (mastectomy and lumpectomy plus radiation), the acute and long-term side effects associated with each treatment, long-term survival, and quality of life. The DB was used by surgeons and had four titles: "treatment choice," "side effects," "results of treatment choice for the breast," and "results for treatment choice for survival." Below each heading were two information panels (one for mastectomy and one for lumpectomy plus radiation), resulting in eight separate panels. Initially, each panel was covered by a sliding door; the panel was then opened to reveal information in a sequential fashion. The patient and the surgeon read each panel together. During and after the presentation, the patient was encouraged to ask questions. At the end of the presentation, the patient was faced with a complete visual representation of the options and outcomes. The authors reported that an additional card with details regarding breast reconstruction was also available. After the DB presentation, the patient was given a takehome version of the DB.
Carrère and colleagues36 reported the results of the initial evaluation of a DB in 40 healthy female volunteers; this treatment DB was developed for postmenopausal women with node-positive breast cancer and positive hormonal receptors. The postoperative treatment options were chemotherapy or no chemotherapy. The authors reported that the risks and benefits of the two treatment options were described in an unbiased manner by means of written material and visual aids. The written material included all the information to be described and served as the physician's guide for using the visual aids. As in other studies, the visual aid was empty at the beginning of the interview and, each time a piece of information was orally provided to the patient, a corresponding card with written information was attached to the board with Velcro. By the end of the interview, all the information cards were on the board. The authors presented the two options simultaneously in eight successive sections: results of cancer surgery; presentation of mandatory treatments (tamoxifen and radiation treatment); formulation of therapeutic choice; description of chemotherapy treatment; presentation of the risks of relapse associated with the two options (5-year relapse rates were 30 percent with chemotherapy vs. 40 percent without chemotherapy), information about overall survival; presentation of chemotherapy side-effects (hair loss, nausea, vomiting, tiredness, and infection); and treatment schedules. The treatment options were presented by colors (pale yellow for chemotherapy and pale orange for no chemotherapy). The information concerning relapse rates was provided using bar charts.
Whelan and colleagues29 assessed validity by changing the information provided as described above and determining whether preferences changed in a predictable manner; 89 percent of women who chose lumpectomy plus radiation switched their preference when survival was decreased, and 82 percent of women who chose mastectomy switched their preference when survival was reduced.
Whelan and colleagues29 did not report how validity was assessed.
Levine and colleagues27 evaluated reliability in a second interview conducted 2 weeks after presentation of the first instrument. They used the same intervention described above; preference in both assessments was measured on a 6-point Likert scale. The authors reported that 28 of the 30 patients had the same preference in both assessments and that agreement between preference responses, expressed as a kappa statistic, was 0.86.
Whelan and colleagues29 reported that the DB was administered on two occasions by a skilled interviewer and that women's responses were stable over time. After 3 to 4 weeks, 28 of the 30 had the same preference (kappa statistic = 0.86)
Carrère and colleagues36 evaluated the across-time consistency of the preference. The authors measured a participant's choice and her strength of preference on a 0-to-10 visual analogue scale after the intervention and 2 weeks after the first intervention. The authors reported than none of the women shifted their choice between the two interviews (intraclass correlation coefficient = 0.97)
Whelan and colleagues28 did not report reliability data.
None of the four studies reported this outcome.
Whelan and colleagues28 reported that participants found the instrument easy to read and that participants appeared to have a good understanding regarding most issues concerning breast irradiation. They had some difficulty understanding that breast irradiation was not associated with a survival benefit; however, the authors did not report raw data.
Whelan and colleagues28 reported that 80 percent of the women found the DB useful, 97 percent recommended its use for breast cancer patients, and 100 percent indicated that the DB was easy to understand.
Carrère and colleagues36 tested comprehension with a 13-item questionnaire; they reported that after the first intervention, the proportion of correct answers for each of the 13 questions was never lower than 87.5 percent, and "none of the questions were randomly answered (P < 5.10-6, one tailed X 2 test)."
Levine and colleagues27 reported that 17 of the 30 women chose chemotherapy, and 13 chose no chemotherapy. Carrère and colleagues36 reported that 18 of 40 participants chose chemotherapy, and 22 chose no chemotherapy.
For screening decisions, Lawrence and colleagues35 developed a mammography DA for European-American and Mexican-American women. They pretested a DB in 56 healthy female volunteers older than 49 years. Twenty-eight were mainly English speaking, and 28 mainly Spanish-speaking women. The authors reported that the DB provided evidence about the risks of screening and that it was comprehensible across a wide spectrum of educational levels. The authors described the DB as a visual aid that consisted of graphics and written material describing clinical alternatives, outcomes, and probabilities. As reported in previous studies, the DB was initially empty and then interactively assembled by a trained administrator with one or more participants. The authors reported that the interaction was a key feature of the decision aid and it included probes to ensure comprehension and encourage spontaneous questions. When completed, the DB visually summarized the choices, outcomes, and probabilities. The DB had four parts: (1) "introduction," which provided information about breast cancer and mammography; (2) "choice," which presented detailed information about logistics of screening (cost, procedure, description, discomfort, time needed), potential risk of false-positive and false-negative results, and other options (i.e., self-examination, examination by health professional, or no surveillance); (3) "chance of developing breast cancer," which provided age-based probabilities for developing breast cancer over 10 years; and (4) "outcomes of breast cancer," which provided the probabilities of dying from breast cancer and recurrence after 10 years with and without screening, the absolute risk reduction with mammography, and the possibilities of surgery, chemotherapy, and metastatic disease.
Lawrence and colleagues35 assessed validity with qualitative and quantitative testing. Comprehension of the information was reported as excellent, based on responses to standardized probes. For the quantitative testing of validity, the authors used a similar process to that previously reported. They hypothesized that, if women understood the information, they should reverse their decisions when risk or benefit information was reversed. Twenty-two of 28 women changed their preference as predicted with changed probabilities.
The authors reported that all 28 women participated in a second intervention 1 to 2 weeks after the first DB presentation. They all made the same decision in the second session: 26 chose mammography and 2 did not choose mammography.
Not reported.
Sebban and colleagues32 evaluated a DB about leukemia treatment options; participants chose between bone marrow transplant (BMT) and chemotherapy. The DB included visual aids and written material. It provided detailed information on the patient's options, outcomes, probabilities of outcomes and their meaning, and quality of life associated with treatment choices and potential outcomes. The authors reported that they developed several scenarios. The sequence of scenarios was as follows: (1) a scenario introduced patients to the specific clinical problem and to the context of the choice, (2) how BMT would be performed, and (3) how the chemotherapy would be administered. There were four outcome scenarios for each treatment option (BMT vs. chemotherapy) describing potentially favorable (i.e., "you will feel better") and unfavorable (i.e., "your bone marrow might have difficulties to work properly") outcomes at different points of time (3 months, and 2 and 5 years). The scenarios emphasized the relevant components of the choice: severity of the disease and uncertainty of its evolution, potential toxicity of BMT, morbidity related to graft versus host disease, the intensive monitoring of BMT patients in contrast with the relatively easy monitoring of chemotherapy patients, and the inability of chemotherapy to cure the disease. The authors described the uncertainty about potential treatment side effects verbally rather than numerically (i.e., "likely" vs. 0.8). The administration of the DB was similar to those reported by others.27-29 The first evaluation of the leukemia DB was performed among 42 healthy volunteers (staff and individuals from a rural donor clinic). The authors reported that participants were randomly allocated to the final version of the DB or to the short version followed by the standard DB version. The short DB version only displayed the survival probabilities without details about the procedures and their outcomes. A test-retest study was completed with 16 of the 42 participants in the RCT.
The authors assessed validity using four different constructs: (1) systematic manipulations of the scenarios or of the survival probabilities to determine an subject's understanding of the information; (2) comparison of the two DB versions (short vs. standard DB) to evaluate the impact of the quantity of information on the expressed choice; (3) correlation of the preference with the participant's age (the authors hypothesized that older people made more conservative choices; i.e., chemotherapy); and (4) comparison of the satisfaction with the decision across the two DBs (short vs. standard DB). The authors hypothesized that participants using the standard DB would be more satisfied with their choices compared with participants using the short version. The first construct was tested in 16 participants; the authors reported that, in all cases, preferences shifted in the predicted direction. The 11 participants who initially chose BMT changed to chemotherapy when the survival probabilities for the BMT were reduced. All respondents shifted their preference when chemotherapy survival probabilities were increased. The same results were seen in the six participants who chose chemotherapy, but in the opposite direction.
The authors reported that, for the 20 individuals who were exposed to the short version of the DB first, the correlation between preference scores elicited using both versions was 0.7, "suggesting that choices elicited by the two instruments differ." They indicated that "respondents were inclined to choose BMT more often when presented first with the short version...." The authors did not find a statistically significant correlation between the respondent's age and treatment choice. Participants were significantly more satisfied with the standard DB version than with the short version (p < 0.01)
Based on a 7-point Likert scale, the authors assessed the strength of preference (1 = "I definitely prefer BMT," to 7 = "I definitely prefer chemotherapy"); the intraclass correlation coefficient was 0.87.
The authors reported that all participants who were approached participated in the intervention. Each interview lasted from 20 to 30 minutes.
Twenty six (61.9 percent) participants rated the DB as "very clear," and 16 (38.1 percent) rated it as "clear enough"; 32 (76.2 percent) rated the amount of information as "about right", and 10 (23.8 percent) felt the amount of information was not sufficient. The authors reported that 73.7 percent felt comfortable with the method of presentation and that three did not feel comfortable with the method.
The authors reported that 10 of 22 participants (45.4 percent) exposed to the standard DB chose BMT, 11 chose chemotherapy, and one did not choose either of the two options. Thirteen of the 20 (65 percent) exposed to the short version chose BMT, and the rest chose chemotherapy.
The authors asked participants to indicate who should make decisions about treatment; 54.8 percent felt that it should be the patient and relatives, and the rest reported that it should be a shared decision between the patient (with or without the relatives) and the physician.
Elit and colleagues in two different studies33,34 evaluated the use of a DB for ovarian cancer patients. The authors asked participants to choose between two different treatments: cisplatin + cyclophosphamide (Plan A) vs. cisplatin + paclitaxel (Plan B). In the first study,33 37 healthy female volunteers and 11 women who had completed first-line chemotherapy for ovarian cancer were included. For the second study,34 13 newly diagnosed patients with stage III or IV epithelial ovarian cancer expressed their preference for one of the two treatments, but the patients did not undergo the treatment chosen.34 The authors reported that the DB was written in English, in a narrative format, and with a readability index at a grade 7 level. All outcome information was provided using a mixed frame (positive and negative), and the names of the chemotherapy agents in each treatment plan were not disclosed ("Plan A included two cancer-fighting drugs"). The DB was divided into five parts: "introduction," "treatment choices," "side effects," "outcome," and "description of the outcome." The introduction described information about the disease and the need for chemotherapy. The treatment option section described the administration of the two chemotherapy combinations; bar graphs were used to portray the rates of the most common side effects. The outcomes (cure, recurrence) were presented as probabilities on a wheel and described by narrative material. ("All tests and examinations over the next 5 years show that you have no cancer. ...Even though... you are cancer-free, from time to time you may worry about the cancer coming back.") The administration was similar to that described previously.27-29 The authors designed the DB for administration by a physician or a research assistant.
Validity was assessed in a similar manner to that reported in the other studies. The authors reported that the predicted shifts in treatment choice occurred 95 percent of the time, and that the strength of preference for Plan B was statistically higher than for Plan A (p < 0.001).
The authors evaluated the reproducibility of the participant's choices in 10 volunteers; participants were interviewed on two occasions approximately 3 weeks apart. The authors reported that women's treatment choices showed 100 percent agreement on repeated testing (kappa = 1.0)
In the first study, the authors reported that respondents took approximately 20 to 30 minutes to review the DB. For the second study, the authors approached 13 ovarian cancer patients; only one was not interested in reviewing the survival information.
The authors reported the treatment choice of the 10 female volunteers involved in the test-retest study. One respondent chose Plan A, and nine chose Plan B. In the second study, the authors gave participants 24 hours to make a treatment decision in a hypothetical scenario; four chose Plan A, and eight chose Plan B.
The authors reported that 96 percent of women in the first study group found the DB either easy or very easy to understand, and 89 percent said they would not change the information on the DB. Nine women in the second study recommended using the DB with other patients like themselves.
The authors used the State Trait Anxiety Inventory to assess anxiety in both studies. They reported that anxiety did not change appreciably before and after the DB application (p > 0.05), but they did not provide raw data. The authors reported that the 11-item comprehension questionnaire was answered correctly by 96 percent of healthy volunteers, 92 percent of ovarian cancer patients who had completed chemotherapy, and 86 percent of the newly diagnosed ovarian cancer patients.
Three studies reported the development of audiotape workbook interventions.25,43,44 Two of the studies were conducted by Sawka and colleagues,43,44 and the results were published in the same article. The authors developed and pilot tested a DA for women facing surgical treatment for breast cancer. The third study, by Fiset and colleagues,25 reported the development of an audiotape workbook to assist patients with non-small-cell stage IV lung cancer in deciding whether to have chemotherapy in addition to supportive care and radiation therapy.
Sawka and colleagues developed and conducted two pilot studies43,44 of a DA designed to help breast cancer patients decide between lumpectomy plus radiation therapy versus mastectomy. The DA consisted of an audiotape supplemented by a workbook. The intervention contained specific information regarding the two treatment options: the surgical procedures, a description of radiation, side effects of radiation, and appearance after mastectomy (refer to Evidence Tables 4.19a and 4.20a). The workbook was illustrated with color photographs of the treatment effects, figures providing quantitative information, and a value-clarification exercise in which the women could achieve a better understanding of their choices with similar hypothetical cases. The audiotape provided a verbal description of the workbook contents.
Before the DA was tested, a steering committee (surgeons, a radiation oncologist, a medical oncologist, a breast cancer survivor, and two researchers) oversaw all aspects of development and evaluation of the DA. The content was based on a systematic literature review, the steering committee's input, a needs assessment based on focus groups of women previously diagnosed with breast cancer, and women who were at the point of making a decision about breast cancer. A draft DA was reviewed and critiqued by the steering committee, by nine women who had previously participated in the needs assessment, and by two radiation oncologists and four surgeons not associated with the study. The revised DA was also reviewed by two focus groups of oncology nurses.
The authors performed two pilot studies;43,44 both studies (n = 18 and 10, respectively) included women with stage I or II breast cancer who were making a decision about surgical management. With their input and the comments of four surgeons and seven oncology nurses, a preliminary version of the DA was developed. In the second study, the authors provided a final version to the patients. In both studies, the patients reviewed the DA after discussion with the surgeon about the diagnosis and treatment options. During the first pilot study, a research nurse answered questions.
Validity. Not reported.
Reliability. Not reported.
Feasibility. Not reported.
In the first study,43 10/18 patients did not find any sections of the DA unclear. Three reported that the discussion about adjuvant systemic treatment was unclear. This outcome was not addressed in the second study.
In the first study,43 18 patients indicated that the DA helped them to clarify information given by the surgeon, 17 had positive reactions and were very satisfied with the DA, 6 women thought that the photos were useful in decisionmaking, and 5 felt that the DA raised new questions about what the surgeon first explained. Again, this was not addressed in the second study.
In both studies, the authors evaluated the women's knowledge about breast cancer after the intervention with a previously validated 18-item questionnaire. The authors reported the data as the number of incorrect responses per item; 12/18 patients in the first study answered the questionnaire, and all women answered it in the second study. The high number of incorrect responses in the first group led the authors to change the wording of the questionnaire. The results were presented as number of incorrect responses per group, and no comparisons between groups were reported.
Based on the women's self reports, the authors described that among patients in the first study, 13/18 found themselves "unaffected," and four "relieved" after using the DA. No information was given about anxiety in the second study.
After the intervention, both groups completed the O'Connor's Decisional Conflict Scale.48 The mean score for the first group was 1.8; and for the second, 2.2. The authors reported that the results were consistent with respondents who make decisions after being informed.
Fiset and colleagues25 developed a DA to assist patients with non-small-cell stage IV lung cancer in deciding whether or not to have chemotherapy in addition to supportive care and radiation therapy. The intervention consisted of an audiotape and a companion workbook. The audiotape provided a description of lung cancer and its stages, the functional impact of the disease, and the treatment options available to the patients (i.e., chemotherapy, radiation therapy, and supportive care). The audiotape detailed the risks and benefits of chemotherapy and then discussed the steps in the decisionmaking process. The accompanying workbook consisted of a booklet containing information similar to the audiotape and a worksheet. The worksheet was used by patients to clarify personal values regarding the advantages and disadvantages of chemotherapy, identify any remaining questions, identify patient preference for participation in the decisionmaking process, and finally to determine patient treatment preference.
The content of the audiotape workbook intervention was based on the Cancer Care Ontario practice guidelines for the treatment of stage IV non-small-cell lung cancer. The DA intervention incorporated the Ottawa Decision Support Framework : (1) to provide information on options and outcomes to improve patient knowledge, (2) to provide guidance and examples of the decisionmaking process, and (3) to help to clarify a patient's personal values.49 Before the DA was tested, a development panel (two medical oncologists, two decisionmaking researchers, and two oncology nurses) reviewed each draft of the DA intervention. The draft DA was then reviewed and critiqued by a practitioner panel (all the medical and radiation oncologists in the region who treated lung cancer patients).
The authors tested the acceptability of the audiotape workbook with stage IV non-small-cell lung cancer patients (n=6) who had already made a decision about chemotherapy (four accepted and two declined). The authors also conducted a cross-sectional mail survey of thoracic surgeons and respirologists currently involved in the treatment of lung cancer patients to investigate physician opinion of the DA intervention.
Validity. Not reported.
Reliability. Not reported.
Feasibility. Not reported.
All of the patients (n=6) found the audiotape workbook acceptable in terms of amount, length, clarity, and appropriateness. Three of the patients found the absolute survival benefit of chemotherapy upsetting (all three were currently on chemotherapy). Of the 29 physicians who reviewed the DA and completed the survey, 25 agreed with the clinical practice guideline on which the intervention was based. Nineteen physicians responded that they would be comfortable giving the DA to their patients, six physicians were neutral, and four physicians stated that they would be uncomfortable giving the DA to their patients.
The authors also assessed the usefulness of the DA intervention. All of the patients (n=6) responded that the audiotape workbook would be useful for patients faced with this decision. Of the 28 physicians who answered this part of the survey, 17 felt that the DA would complement their usual approach; 14 stated that the DA would be easy to use in their practice; and 21 responded that they would be very likely, likely, or somewhat likely to use the audiotape workbook in the future.
Unic and colleagues30 assessed a time-tradeoff (TTO) method to elicit preferences for breast cancer prevention strategies, specifically for prophylactic mastectomy (PM).
Not reported.
The authors evaluated the intervention in 44 women suspected of carrying the BRCA1 and BRCA2 mutation. The TTO was used as part of a "shared-decisionmaking program" that the authors developed. This program included three or four sessions. During the first session, participants received information (videotape and pamphlet) to be studied at home and the preference assessment was administered. In the 32-minute videotape called, "Breast Cancer in the Family," high-risk women, their partners, and relatives talked about the physical and psychological aspects of PM and breast cancer screening (BCS). The brochure contained information about breast cancer and risk of breast cancer for BRCA1/2-mutation carriers, BCS, PM, and breast reconstruction. In session two, the first replication of the preference assessment was done. In the third session, the second replication of the preference assessment was carried out; and in the forth session, the authors reviewed the decision analytic results and provided advice to the participants.
The TTO offered the women two alternatives: inferior health (x) for a certain number of life years (with PM or BCS), followed by death; and the best-ranked health state (t) for a number of life years, followed by death (with PM or BCS). The authors began by presenting x equal to t to check the understanding of the TTO questions. Next, x was set equal to zero. Then, "x was varied via bisection until the woman was indifferent between the alternatives." Four tradeoffs were done for different values of t, depending on the woman's age. The authors did not provide information about the sources they used to build the TTO.
The authors compared the women's preference for PM using the TTO with a rating scale (RS) to evaluate convergent validity. The authors reported that four women (proven carriers) chose PM as the most preferred health state; and 47 of 51 women ranked BCS as the most preferred health state. The comparison of the two instruments was done using results obtained in the second preference assessment. The correlation coefficient between the TTO values and the RS values was 0.5; RS values were significantly lower than TTO values (p < 0.001).
This outcome was evaluated in 46 women. The authors reported that Pearson's correlation coefficient between the RS values for the two first sessions was 0.67; however, the TTO values coefficient was obtained with pooled data (the first two and last two sessions).
The authors reported that 42 women were able to complete the TTO and the RS on two occasions. Three women completed both preference assessments on only one occasion. Nine women completed the TTO a third time because of discrepancies between the TTO values obtained in the first and second sessions.
In this chapter, we reviewed 22 published studies that described the developmental process of DAs. Nineteen DAs were developed for treatment decisions, two for screening, and one for prevention. The type of DA most frequently described was the DB (eight studies), followed by interactive computer programs (seven studies: four CHESS and three other), and audiotapes complemented by workbooks (three studies: two with same DA and one other). Across all interventions, written or verbal information was provided with the aid of visual or graphic displays. Most DAs focused on breast cancer; followed by prostate, lung, and ovarian cancer. All study participants were adults from developed countries. Only two DAs were developed for members of special populations (Spanish-speaking Mexican-American women and low-income African-American women).
The rationale for the development of the DA was reported in 10 studies. In seven studies, the authors reported that the DA was developed to promote shared decisionmaking, although there was insufficient description of this process. In three studies, the DA was developed to support an "informed" process of decisionmaking.
In most studies, some psychometric properties, such as reliability, validity, feasibility and clarity of the DA, were measured. Reliability was determined by focusing on the stability of participants' decisions (eight studies). Construct validity was usually measured by altering the information presented to determine whether users' preferences shifted in the expected direction (seven studies). Twelve studies measured acceptability, and 10 studies assessed feasibility. In contrast, for the outcome measures (e.g., knowledge, satisfaction, or decision), there was an almost complete lack of reporting on why particular outcome measurement tools had been selected or their psychometric properties.
Overall, the studies in this chapter followed similar steps or phases in the process of developing a DA. In the initial phase, the investigators determined why an intervention was required and exactly what was needed. During the second stage, the authors gathered scientific and nonscientific information to be presented in the DA. Information contained in the DA was derived from a variety of sources: research evidence, input from multidisciplinary experts, and, less frequently, patient chart reviews. In general, information consisted of the nature and prognosis of the disease; description of the options for prevention, screening, or treatment; as well as the positive and negative (physical, social, emotional) outcomes associated with the options. Some DAs also included plans regarding implementation of the decision, managing negative outcomes, and links to support groups or other sources of information. Once the information was collected, most authors attempted to determine its relevance through surveys, interviews, or focus groups with experts (e.g., clinicians, epidemiologists, surgeons) and former patients. The fourth phase of the development process involved the actual construction of the DA. After constructing the DA, the final phase of the development process involved evaluation. Generally, in most studies, the newly constructed DA was first pilot-tested among different focus groups such as health care professionals, healthy volunteers, former cancer patients, or patients with other illnesses. Subsequently, DAs for treatment decisions were tested with actual cancer patients at the point of decisionmaking (two studies) or previous patients (three studies). For decisions related to prevention, the DA was tested in women at risk of cancer (one study). In the two studies about screening decisions, healthy volunteers were used.
In summary, most of the studies involved a thorough systematic process for the development of DAs. However, only half of the studies described the rationale for the development of the DA and, consequently, there was sizeable variation in the types of outcome measures selected. Surprisingly, given the amount of time and effort needed to develop a DA, few investigators to date have conducted followup studies to evaluate the effectiveness of the DA in controlled studies. In future studies, investigators should provide documentation of the process used to develop a DA, including the rationale for the choice of DA and outcome measures as well as the psychometric properties. In studies about the development of DAs for treatment, the aid should be field-tested with cancer patients. To date, few DAs have been developed for special populations, resulting in a gap in knowledge about their needs. Finally, as discussed in subsequent chapters, once a DA has been developed and tested, more studies need to be conducted to evaluate the effectiveness in actual clinical situations.
This chapter focuses on those studies that evaluated the effectiveness of a DA in a clinical rather than a research situation. As discussed in Chapter 2, we defined a DA as "an intervention designed primarily to help patients or patients and clinicians together, with making cancer-related health care decisions, when options are available for prevention, screening and treatment. At a minimum, it should target some component of decisionmaking (e.g., information exchange, involvement in the decision process)." In this chapter, we address all but one of the questions posed by our partners at NCI. These questions are listed below. Following each question, we indicate the relevant sections of text and tables where information can be found. In Chapters 6 and 7, we return to the questions.
The chapter is organized into sections. After listing the questions, we describe the characteristics of the studies, including the types of design, interventions, outcomes, and comparisons. We then report the methodological quality of each study. The results are presented according to the type of intervention and outcome.
| Type of Intervention | Study Design | Author (year) | Decisionmaking Model Stated by Authors | Decisionmaking Model Determined by Reviewers |
|---|---|---|---|---|
| Information Pamphlet or DA brochure | RCT | Schapira (2000) | Informed | Informed |
| RCT | Street (1995) | NR | Informed | |
| RCT | Iglehart (1998) | NR | Informed | |
| RCT | Goel (2001) | Shared | Not clear | |
| Case series | Cassileth (1989) | NR | Informed | |
| Case series | Adler (1999) | NR | Informed | |
| Case series | Protiere (2000) | Shared | Informed | |
| Case Series | Klass (1992) | NR | Informed | |
| Educational Script | RCT | Wolf (1996) | NR | Informed |
| RCT | Wolf (2000) | NR | Informed | |
| Audiotape | RCT | Watson (1998) | NR | Informed |
| RCT | Hack (1999) | NR | Informed | |
| RCT | North (1992) | NR | Informed | |
| RCT | Goel (2001) | See pamphlet section | See pamphlet section | |
| Case Series | Fiset (2000) | NR | Informed | |
| Videotape | RCT | Volk (1999) | Shared | Informed |
| RCT | Pignone (2000) | NR | Informed | |
| CT | Flood (1996) | Shared | Informed | |
| CT | Flood (1996) | Shared | Informed | |
| Case series | Onel (1998) | Shared | Informed | |
| Case series | Wilson (1988) | NR | Informed | |
| Interactive Computer Program | RCT | Maslin (1998) | Shared | Informed |
| RCT | Street (1995) | See pamphlet section | See pamphlet section | |
| CT | Molenaar (2001) | Shared | Informed | |
| Case series | Gramlich (1998) | Shared | Not Clear | |
| Counselling | RCT | Davison (1999) | NR | Informed |
| Case series | Cotton (1995) | NR | Informed | |
| Case series | Cotton (1991) | NR | Informed | |
| Case series | Sandison (1996) | NR | Informed | |
| Case series | Okamato (1999) | NR | Informed | |
| Informal Decision Analysis | Case series | Ashcroft (1985) | NR | Shared |
| Decision Board | RCT | Irwin (1999) | Shared | Informed |
| Nonconcurrent cohort studies | Whelan (1995) | Shared | Informed | |
| Whelan (1999) | Shared | Not Clear | ||
| Case series | Levine (1992) | Shared | Informed | |
| Complex Decision Aids | RCT | Lerman (1997) | Informed | Informed |
| RCT | Davison (1997) | Other: empowerment | Informed | |
| CT | Sepucha (2000) | Shared | Shared | |
| Case series | Stalmeier (1999) | Shared | Informed | |
| Case series | Wolberg (1987) | NR | Informed | |
| Case series | Brundage (2000) | NR | Informed |
The following definitions were used to categorize the model of decisionmaking :Paternalistic model: Explicitly assumes a passive role for the patient in the decisionmaking process. The clinician is seen as dominating the encounter. This model leaves the patient outside the decisionmaking process.Informed model: Incorporates the idea of information sharing (primarily from clinician to patient), but the information sharing does not necessarily lead to a sharing of the decisionmaking process. This model leaves the clinician out of the decisionmaking process.Shared model: Involves at least two participants in the decision: the clinician and the patient. Both parties take steps to participate in the process of treatment decisionmaking. Information sharing is a prerequisite to this model: both patient and clinician bring information and values to the process and they come together to make the decision.
Definitions are from Charles et al. (1999): Decision-making in the physician-patient encounter: revisiting the shared treatment decision-making model.
| Type of Decision | Author (Year) | Type of Cancer | Components of DA Intervention and Comparison Groups | Type of Comparison |
|---|---|---|---|---|
| Genetic Testing | Lerman (1997) | Breast | Wait list control group vs. DA educational session + DA brochure vs. DA educational session + DA brochure + Standard genetic counseling | Wait list control group vs. DA only vs. Standard genetic counseling + DA |
| Inglehart (1998) | Breast and Ovarian | DA brochure + Standard genetic counseling vs. Individualized DA brochure + Standard genetic counseling | Standard genetic counseling + DA vs. Standard genetic counseling + DA | |
| Genetic Testing/ Prevention | Watson (1998) | Breast | Genetic Counseling + Physical Examination + Summary Letter vs. Genetic Counseling + Physical Examination + Summary Letter + Audiotape of Consultation | Usual Care vs. Usual Care + DA |
| Screening | Davison (1999) | Prostate | Usual Care + Unrelated Discussion vs. Usual Care + Counseling + DA brochure | Usual Care vs. Usual Care + DA |
| Pignone (2000) | Colorectal | Usual Care + unrelated videotape and brochure about car safety vs. Usual Care + DA videotape + targeted DA brochure + chart marker | Usual Care vs. Usual Care + DA | |
| Schapira (2000) | Prostate | Information pamphlet + research assistant (RA) available to answer questions + followup visit vs. DA brochure + RA available to answer questions + followup visit | Usual Care vs. DA | |
| Volk a (1999) | Prostate | Usual Care vs. Usual Care + DA videotape + DA brochure vs. Usual Care + DA videotape + DA brochure + Utility assessment | Usual Care vs. Usual Care + DA vs. Usual Care + DA | |
| Wolf (1996) | Prostate | Brief information statement vs. Educational DA script read by a research assistant | Usual Care vs. DA | |
| Wolf (2000) | Colorectal | Listening to a brief statement vs. Listening to an educational relative risk reduction DA script vs. Listening to an educational absolute risk reduction DA script | Usual Care vs. DA1 vs. DA2 | |
| Treatment | Davison (1997) | Prostate | Usual Care + Information pamphlet vs. Usual Care + Information pamphlet + Counseling + Audiotape of consultation + Question List | Usual Care vs. Usual Care + DA |
| Goel (2001) | Breast | Usual Care + DA brochure vs. Usual Care + Audiotape workbook with values clarification exercise | Usual Care + DA vs. Usual Care + DA | |
| Hack b (1999) | Breast and Prostate | Usual Care vs. Usual Care + Audiotape of consultation vs. Usual Care + Option to have audiotape of consultation | Usual Care vs. Usual Care + DA vs. Usual Care + DA | |
| Irwin (1999) | Breast | Decision Board with treatment presentation AC c - CMF d vs. Decision Board with treatment presentation CMF** - AC* | DA vs. DA | |
| Maslin (1998) | Breast | Usual Care vs. Usual Care + Interactive Computer Program | Usual Care vs. Usual Care + DA | |
| North (1992) | Not Specified | Usual Care + Physician Checklist vs. Usual Care + Physician Checklist + Audiotape of Consultation | Usual Care vs. Usual Care + DA | |
| Street (1995) | Breast | Usual Care + DA brochure vs. Usual Care + Interactive Computer Program | Usual Care + DA vs. Usual Care + DA |
The authors reported no significant difference between the two intervention groups and presented results as pooled intervention group data. Note: In Chapter 5 summary table, only the pooled data are discussed.
The authors reported much of the result data pooled for the two intervention groups. Note: In Chapter 5 summary table, only the pooled data are discussed.
Adriamycin + Cyclophosphamide
Cyclophosphamide + Methotrexate + 5-Fluorouracil
| Type of Decision | Author (Year) | Type of Cancer | Components of DA Interventionand Comparison Groups | Type of Comparison |
|---|---|---|---|---|
| Screening | Flood (1996) | Prostate | Usual Care vs. Usual Care + Pamphlet (no description) + DA videotape | Usual Care vs. Usual Care + DA |
| Flood (1996) | Prostate | Information videotape (advocates PSA test) vs. DA videotape + Pamphlet (no description) | Usual Care vs. DA | |
| Treatment | Molenaar (2001) | Breast | Usual Care + Information Pamphlet vs. Usual Care + Interactive computer program | Usual Care vs. Usual Care + DA |
| Sepucha (2000) | Breast | Usual care + Preconsultation Planning + Consultation Observation vs. Usual care + Preconsultation Planning + Consultation Recording | Usual Care + DA vs. Usual Care + DA | |
| Whelan (1995) | Breast | Usual Care vs. Usual Care + Physician Checklist vs. Usual Care + DB + Take-home version of DB | Usual Care vs. Usual Care vs. Usual Care + DA | |
| Whelan (1999) | Breast | Usual Care vs. Usual Care + DB + Take-home version of DB | Usual Care vs. Usual Care + DA |
| Type of Decision | Author (Year) | Type of Cancer | Components of Decision Aid Intervention |
|---|---|---|---|
| Genetic Testing | Stalmeier (1999) | Breast | Individual counseling + Utility assessment + Information videotape and pamphlet |
| Treatment | Adler (1999) | Breast | Usual Care + Pamphlet (no description provided) |
| Ashcroft (1985) | Breast | Usual Care + Informal Decision Analysis | |
| Brundage (2000) | Lung | Usual Care + Counseling + Decision Board + Treatment Tradeoff Exercises + DA brochure | |
| Cassileth (1989) | Prostate | Usual Care + DA brochure | |
| Cotton (1991) | Breast | Usual Care + Individual Counseling with visual aids + Information pamphlet | |
| Cotton (1995) | Breast | Usual Care + Individual Counseling + Information pamphlet | |
| Fiset (2000) | Lung | Usual Care + Audiotape booklet with worksheet | |
| Gramlich (1998) | Breast | Usual Care + Interactive Video Disc Program | |
| Klass (1992) | Prostate | Usual Care + DA brochure | |
| Levine (1992) | Breast | Usual Care + Decision Board + Take-home version of Decision Board | |
| Okamato (1999) | Hypopharyngeal | Usual Care + Individual counseling with visual aids + Additional counseling sessions as needed | |
| Onel (1998) | Prostate | Usual Care + DA videotape | |
| Protiere (2000) | Breast | Usual Care (consultation based on pamphlet) + DA brochure | |
| Sandison (1996) | Breast | Usual Care + Individual Counseling + DA brochure | |
| Wilson (1988) | Breast | Usual Care + Individual Counseling + Tape/slide Presentation | |
| Wolberg (1987) | Breast | Usual Care + Individual Counseling + Slide/tape Presentation + DA brochure |
What has been the clinical focus of the decision aids (e.g., type of cancer and extent of disease)? (Type of decision and type of cancer; Tables 20 to 22)
What has been the mode of delivery (e.g., print, interactive video)? (Type of decision aid interventions; Tables 20 to 22)
| Author (Year) | Type of Cancer | Gender (# of subjects) | Age | Annual Family Income (# of subjects) | Education (# of subjects) | Ethnicity (# of subjects) | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | < High school | > High school | Caucasian | African-American | Other | ||||
| Davison (1997) | Prostate | IG: 30 CG: 30 | N/A | IG: mean 66.0, SD 8.3 range: NR CG: mean 69.8, SD 5.0 range: NR | NR | IG: 15 CG: 20 | IG: 15 CG: 10 | NR | NR | NR |
| Davison (1999) | Prostate | IG: 50 CG: 50 | N/A | Men 50 to 79 years: IG: mean 63.8 years, SD 8.0 CG: mean 60.7 years, SD 8.6 | NR | IG: 23 CG: 21 | IG: 27 CG: 29 | NR | NR | NR |
| Goel (2001) | Breast | NA | IG1:50 IG2: 86 | IG1: mean 57.4 years, SD 12.8, range: NR IG2: mean 57.6 years, SD 12.0, range: NR | NR | IG1: 27 IG2: 46 | IG1: 23 IG2: 40 | NR | NR | NR |
| Hack (1999) | Breast & Prostate | 18 | 18 | Female: mean 52 years, SD NR range: 34 to 77 years Male: mean 67 years, SD NR range: 51 to 79 years | NR | Total: 8 | Total: 28 | NR | NR | NR |
| Iglehart (1998) | Breast & Ovarian | NA | 213 a | Total: mean 49 years, SD NR, range: 28 to 88 years | NR | 0 | 213 | 202 | 8 | 3 |
| Irwin (1999) | Breast | N/A | Total: 46 | Total: mean 45.5 years, SD NR range: 34 to 53 years | < $30,000 (Cdn): 29 | Total: 7 | Total: 39 | NR | NR | NR |
| Lerman (1997) | Breast | N/A | IG1: 114 IG2: 122 CG: 164 | Age > 50 years: IG1: mean 34 years, SD, range: NR IG2: mean 30 years SD, range: NR CG: mean 50 years SD, range: NR | < $35,000 (US): IG1: 22; IG2: 27 CG: 107 | IG1: 7 IG2: 14 CG: 20 | IG1: 107 IG2: 108 CG: 144 | IG1: 84 IG2: 92 CG: 107 | IG1: 29 IG2: 28 CG: 49 | IG1: 1 IG2: 2 CG: 7 |
| Maslin (1998) | Breast | N/A | IG: 51 CG: 49 | Total: mean 52.1 years, SD NR range: 28 to 73 years | NR | NR | NR | NR | NR | NR |
| North (1992) | Not Specified | IG: 9 CG: 7 | IG: 9 CG: 9 | IG: mean 54.1 years, SD, range NR CG: mean 56.4 years, SD, range NR | NR | NR | NR | NR | NR | NR |
| Pignone (2000) | Colorectal | IG: 51 CG: 48 | IG: 74 CG: 76 | IG: mean: 63.1 years, SD NR CG: mean: 62.7 years, | NR | IG: 34 CG: 20 | IG: 91 CG: 104 | IG: 105 CG: 112 | NR | NR |
| Schapira (2000) | Prostate | IG: 122 CG: 135 | N/A | Men 50 to 80 years: IG: mean 69.4 years, SD 7.3 CG: mean 70.4 years, SD 6.4 | NR | NR | NR | IG: 116 CG: 122 | IG: 1 CG: 6 | IG: 5 CG: 6 |
| Street (1995) | Breast | N/A | IG: 30 CG: 30 | IG: mean 57.4, SD NR range: 35 to 76 years CG: mean 60.8, SD NR range: 35 to 82 years | NR | IG: 1 CG: 0 | IG: 29 CG: 30 | IG: 28 CG: 27 | NR | IG: 2 CG: 3 |
| Volk (1999) | Prostate | IG: 80 CG: 80 | N/A | Men 45 to 70 years: IG: mean 58.5, SD NR CG: mean 59.5, SD NR | < $9,999 (US): IG: 14 CG: 17 | IG: 14 CG: 21 | IG: 64 CG: 59 | IG: 48 CG: 49 | IG: 18 CG: 12 | IG: 14 CG: 19 |
| Watson (1998) | Breast | N/A | IG: 55 CG: 56 | NR | NR | NR | NR | NR | NR | NR |
| Wolf (2000) | Colorectal | IG1: 48 IG2: 48 CG: 51 | IG1: 82 IG2: 88 CG: 82 | IG1: mean 74 years, SD 6 IG2: mean 74 years, SD 6 CG: mean 75 years, SD 6 | < $15,000 (US) IG1: 79 IG2: 77 CG: 82 | IG1: 58 IG2: 61 CG: 70 | IG1: 72 IG2: 75 CG: 63 | IG1: 98 IG2: 98 CG: 102 | NR | IG1: 32 IG2: 38 CG: 31 |
| Wolf (1996) | Prostate | IG: 103 CG: 102 | N/A | Men > 50 years of age: IG: mean 64.5, SD 9.8 CG: mean 65.0, SD 8.4 | < $15,000 (US): IG: 69 CG: 64 | IG: 72 CG: 69 | IG: 31 CG: 33 | IG: 64 CG: 65 | NR | IG: 39 CG: 37 |
Demographic data are on the 213 subjects who completed genetic testing.
| Author (Year) | Type of Cancer | Gender (# of subjects) | Age | Annual Family Income (# of subjects) | Education (# of subjects) | Ethnicity (# of subjects) | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | < High school | > High school | Caucasian | African-American | Other | ||||
| Flood (1996) | Prostate | 409 | NA | IG: mean 64.3 years, SD NR CG: mean 63.6 years, SD NR | NR | NR | IG: 99 CG: 107 | NR | NR | NR |
| Flood (1996) | Prostate | 222 | NA | Men > 50 years of age: IG: mean 66.5 years, SD NR CG: mean 64.4 years, SD NR | NR | NR | IG: 81 CG: 60 | NR | NR | NR |
| Molenaar (2001) | Breast | NA | IG: 92 CG: 88 | IG: mean 55.4 years, SD 10.8 CG: mean 54.6 years, SD 10.6 | NR | IG: 9 CG: 9 | IG: 83 CG: 79 | NR | NR | NR |
| Sepucha (2000) | Breast | NA | IG: 12 CG: 12 | IG: mean 47 years, SD 6.9 CG: mean 48 years, SD 6.7 | NR | NR | IG: 11 CG: 12 | IG: 10 CG: 11 | NR | IG: 2 CG: 1 |
| Whelan (1995) | Breast | NA | IG: 30 CG1: 23 CG2: 29 | # women > 50 years: IG: 23 CG1: 19; CG2: 21 | NR | IG: 5 CG1: 0 CG2: 6 | IG: 25 CG1: 23 CG2: 23 | NR | NR | NR |
| Whelan (1999) | Breast | NA | IG: 175 CG: 194 | IG: mean 56.2 years, SD NR Number > 60 years: 66 CG1: mean, SD NR; Number > 60 years: 90 | NR | IG: 52 CG: NR | IG: 123 CG: NR | NR | NR | NR |
| Author (Year) | Type of Cancer | Gender (# of subjects) | Age | Annual Family Income (# of subjects) | Education (# of subjects) | Ethnicity (# of subjects) | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | < High school | > High school | Caucasian | African-American | Other | ||||
| Adler (1999) | Breast | NA | 41 | mean, SD NR; range: 21 to 60 years | NR | NR | NR | NR | NR | NR |
| Ashcroft (1985) | Breast | NA | 18 | mean, SD NR; range: 20 to 70 years | NR | NR | NR | NR | NR | NR |
| Brundage (2000) | Lung | 10 | 8 | mean 68.2 years, SD 8.0 | NR | 11 | 7 | NR | NR | NR |
| Cassileth (1989) | Prostate | 147 | NA | mean, SD NR; range: 48 to 96 years | NR | 59 | 88 | 99 | NR | NR |
| Cotton (1995) | Breast | NA | 20 | mean, SD NR; range: 51 to 67 years | NR | NR | NR | NR | NR | NR |
| Cotton (1991) | Breast | NA | 91 | Not clear | NR | NR | NR | NR | NR | NR |
| Fiset (2000) | Lung | 12 | 8 | mean 63 years, SD 11, range: 38 to 83 years | NR | 5 | 15 | NR | NR | NR |
| Gramlich (1998) | Breast | NA | Not clear (103?) | NR | NR | NR | NR | 46% (n=47?) | NR | NR |
| Klass (1992) | Prostate | 101 | NA | mean 73 years, SD NR | NR | NR | NR | NR | NR | NR |
| Levine(1992) | Breast | NA | 37 | mean 43.6 years, SD NR | NR | NR | NR | NR | NR | NR |
| Okamato (1999) | Hypopharyngeal | NR | NR | mean, SD, range: NR | NR | NR | NR | NR | NR | NR |
| Onel (1998) | Prostate | 111 | NA | mean 67 years, SD NR | NR | 0 | 111 | NR | NR | NR |
| Protiere (2000) | Breast | NA | 71 | Not clear | NR | 27 | 44 | NR | NR | NR |
| Sandison (1996) | Breast | NA | 50 | Women age >70 years: mean, SD NR, range 70 to 94 years | NR | NR | NR | NR | NR | NR |
| Stalmeier (1999) | Breast | NA | 54 | mean 38 years, SD 11 | NR | 7 | 47 | NR | NR | NR |
| Wilson (1988) | Breast | NA | 153 | mean, SD NR; range 27 to 65 years | NR | NR | NR | NR | NR | NR |
| Wolberg (1987) | Breast | NA | 250 | NR | NR | NR | NR | NR | NR | NR |
| Author (year) | Type of Decision | Outcomes Measured | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Genetic Testing | Screening | Prevention | Treatment | Decision | Acceptability of DA | Anxiety | Decisional conflict | Decisional regret | Depression | Determinants of choice | Knowledge | Limitation of The test | Optimism | Quality of life | Risk perception | Satisfaction | Other | ||
| Prostate Cancer | |||||||||||||||||||
| Davison (1997) | X | X | X | X | X | ||||||||||||||
| Davison (1999) | X | X | X | X | X | ||||||||||||||
| Schapira (2000) | X | X | X | ||||||||||||||||
| Volk (1999) | X | X | X | X | |||||||||||||||
| Wolf (1996) | X | X | X | ||||||||||||||||
| Breast Cancer | |||||||||||||||||||
| Goel (2001) | X | X | X | X | X | X | X | ||||||||||||
| Irwin (1999) | X | X | X | X | X | ||||||||||||||
| Lerman (1997) | X | X | X | X | X | ||||||||||||||
| Maslin (1998) | X | X | X | X | X | X | X | ||||||||||||
| Street (1995) | X | X | X | X | |||||||||||||||
| Iglehart (1998) | X | X | X | X | X | ||||||||||||||
| Watson (1998) | X | X | X | X | X | X | X | ||||||||||||
| Breast and Prostate cancer | |||||||||||||||||||
| Hack (1999) | X | X | X | X | |||||||||||||||
| Colorectal cancer | |||||||||||||||||||
| Wolf (2000) | X | X | X | X | |||||||||||||||
| Pignone (2000) | X | X | X | ||||||||||||||||
| Not specified | |||||||||||||||||||
| North (1992) | X | X | X | X | |||||||||||||||
| Author (Year) | Design | Type of Decision | Outcomes Measured | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Genetic testing | Screening | Treatment | Decision | Acceptability of DA | Decisional conflict | Determinants of choice | Knowledge | Quality of life | Satisfaction | Would recommend DA to others | |||
| Prostate Cancer | |||||||||||||
| Flood (1996) | Controlled Trial | X | X | X | |||||||||
| Flood (1996) | Controlled Trial | X | X | X | |||||||||
| Breast Cancer | |||||||||||||
| Molenaar (2001) | Controlled Trial | X | X | X | X | X | |||||||
| Sepucha (2000) | Controlled Trial | X | X | X | |||||||||
| Whelan (1995) | Nonconcurrent cohorts | X | X | X | X | ||||||||
| Whelan (1999) | Nonconcurrent cohorts | X | X | X | X | X | X | ||||||
| Author (Year) | Type of Decision | Outcomes Measured | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Genetic Testing | Screening | Prevention | Treatment | Decision | Anxiety | DA acceptability | DA helps patient decide | Decision burden | Decisional conflict | Decision uncertainty | Depression | Determinants of choice | Knowledge | Quality of life | Satisfaction | Would choose again | Would recommend DA | Other | ||
| Breast | ||||||||||||||||||||
| Adler (1999) | X | X | X | X | X | |||||||||||||||
| Ashcroft (1985) | X | X | X | X | ||||||||||||||||
| Cotton (1995) | X | X | X | X | X | X | ||||||||||||||
| Cotton (1991) | X | X | ||||||||||||||||||
| Gramlich (1998) | X | X | X | X | X | |||||||||||||||
| Levine (1992) | X | X | X | X | X | X | ||||||||||||||
| Protiere (2000) | X | X | X | X | X | X | X | |||||||||||||
| Sandison (1996) | X | X | X | |||||||||||||||||
| Stalmeier (1999) | X | X | X | X | X | X | X | |||||||||||||
| Wilson (1988) | X | X | X | X | X | |||||||||||||||
| Wolberg (1987) | X | X | X | X | X | X | X | |||||||||||||
| Lung | ||||||||||||||||||||
| Brundage (2000) | X | X | X | X | X | X | X | |||||||||||||
| Fiset (2000) | X | X | X | X | X | |||||||||||||||
| Prostate | ||||||||||||||||||||
| Cassileth (1999) | X | X | X | X | X | |||||||||||||||
| Klass (1992) | X | X | X | |||||||||||||||||
| Onel (1998) | X | X | X | X | X | X | X | |||||||||||||
| Hypopharyngeal | ||||||||||||||||||||
| Okamato (1999) | X | X | X | |||||||||||||||||
What is the effectiveness of decision aids? (See Chapters 6 and 7.)
What is the effectiveness of decision aids in different clinical contexts? (See Type of DA Interventions and Type of Decisions, below, and Tables 20 to 22.)
What is the effectiveness of different modes of delivery? (See Type of DA Interventions, below, and Tables 20 to 22.)
What is the effectiveness of decision aids on special populations? (See DAs for Special Populations, page 71, and Chapters 6 and 7.)
Thirty-nine studies evaluated a DA intervention with patients who were offered an actual choice or who expressed a preference in a clinical rather than a hypothetical situation.
Of the 39 studies, 16 were RCTs,50-65 four were nonrandomized controlled trials,66-69 two were nonconcurrent cohort studies,70,71 six were pre/post designs,72-77 and the remaining 11 were case series.78-88 For the remainder of the chapter, the pre/post studies will be reported with the case series studies.
The DAs evaluated in these studies range from simple take-home pamphlets to complex interventions consisting of multiple components (Tables 20 to 22). In eight studies, written materials or DA brochures were used.55,59,62,65,84-87 Three studies gave patients an audiotape of their consultation.51,57,60 Two studies evaluated the use of audiotape workbooks.65,77 Six studies investigated videotape (or slide/tape interventions).52,63,66,67,74,81 Four studies evaluated interactive computer programs.56,59,69,75 In seven studies, the DAs were primarily counseling or educational sessions.53,54,64,79,80,83,88 One study used informal decision analysis to assist patients in making a decision.76 There were four studies that assessed the use of DBs.61,70,71,78 The remaining six studies involved complex DA interventions with a number of the above components.50,58,68,72,73,82 (Refer to Tables 20 to 22.)
We used a continuum of cancer care to order the types of decisions (preventive care, screening, diagnosis, and treatment). There were two studies that used DAs to support women at high risk for developing breast cancer in deciding between taking preventive measures or opting for breast cancer surveillance.51,72 One study evaluated a DA to assist women in deciding whether to provide a blood sample for future genetic testing.50 One study explored the use of a DA to help women with breast or ovarian cancer who had a high probability of carrying a breast cancer gene mutation in deciding whether to undergo genetic testing.62 In eight studies, DAs were used to assist patients in deciding whether to have a screening test.52-55,63,64,66,67 The majority of DA interventions (27 of 39 studies) were used to facilitate a choice between different treatment options.56-61,65,68-71,73-88
Twenty-two studies evaluated DAs related to the prevention or treatment of breast cancer.50,51,56,59,61,62,65,68-72,75,76,78-85 In 10 studies, the interventions were related to prostate cancer.52-55,58,66,67,74,86,87 One study assessed a DA in both breast and prostate cancer patients.57 Two studies evaluated DAs to assist patients with advanced non-small-cell lung cancer make a treatment decision.73,77 Two studies assessed interventions related to colorectal screening.63,64 One study involved the use of a DA intervention for patients with hypopharyngeal cancer.88 One study evaluated an audiotape DA in a diverse group of cancer patients.60
The sample characteristics of the 39 studies are summarized in Tables 23 to 25. In eight studies, the eligibility criteria limited the sample to a certain age range.52-55,63,64,67,83 Five of these studies involved prostate cancer screening.52-55,67 All of these studies restricted their samples to middle or older age men (lower age limit varied from 45 to 50 years; upper limit from 70 years to no limit). Similarly, the two studies investigating colorectal screening restricted their samples to older individuals (lower age limit varied from 50 to 65 years; upper limit from 75 years to no limit).63,64 The study by Sandison, et al.83 investigated breast cancer treatment decisionmaking in women age 70 years or older (refer to DAs for special populations section below for more detail). Only five studies reported information regarding income level.50,52,54,61,64 None of the studies targeted a particular SES class. However, in the prostate cancer screening study by Wolf and colleagues,54 more than 50 percent of the participants had annual incomes below $15,000. Of the 39 studies, 25 provided information about participants' level of education.50,52-54,57-59,61-75,77,84,86 The majority of participants in each of these 19 studies had at least a high school education, except for three studies.54,58,73 No study targeted a DA intervention for a specific education level. Ethnicity of participants was reported in 11 studies.50,52,54,55,59,62-64,68,75,86 In all of these studies, the majority of participants were Caucasian, except for the study by Gramlich, et al.75 This study was conducted in Hawaii, and approximately 50 percent of the participants were from an Asian ethnic group (Japanese, Chinese, Filipino, or Korean). In no study was the DA intervention designed to target a particular ethnic group.
Only one study assessed a DA in a special population. In this case series, Sandison, et al.83 explored whether women aged 70 and over with breast cancer would elect to choose their own treatment from four options or ask their surgeon to decide. In addition to the normal consultation, the DA consisted of individual counseling with a nurse and take-home information. Of the 50 women studied, 38 decided to choose their own treatment. The majority of these women (n=34) opted for breast conservation (plus radiation therapy and tamoxifen or tamoxifen only). The authors reported that at 1-year followup only two patients who chose their own treatment were unhappy with their decision. Lerman, et al.50 conducted a study that compared two DA interventions designed to help women at low to moderate risk for breast cancer decide whether to undergo BRCA1 gene testing. The authors reported results from a post hoc analysis that assessed ethnic differences in motivation for BRCA1 genetic testing in Lerman et al.89 The authors concluded that, in low to moderate risk African-American women, the DA intervention consisting of education plus counseling may increase BRCA1 testing.
A variety of outcomes were investigated in the 39 effectiveness studies identified. All but two studies assessed patient decisions (either actual choice or stated preference).57,60 "Knowledge" (including the measurement of knowledge, understanding, or recall) was the second most frequently measured outcome. Knowledge was assessed in 12 of the 16 RCTs,50-52,54,55,57,59-62,64,65 in four out of six controlled trials and nonconcurrent cohort studies66,67,70,71 and in 4 of the 17 case series.72-74,77 Overall, anxiety and/or depression were measured in nine studies: seven RCTs51,53,56-58,60,65 and two case series.76,82 Patients' decision burden, decision uncertainty, or decisional conflict were measured in two RCTs53,65 and three case series.72,73,77 Acceptability of the decision aid intervention was assessed in six RCTs,51,52,56,58,60,61 one nonconcurrent cohort study,71 and four case series.75,77-79 Patient satisfaction with the decision aid, the decisionmaking process, or the actual decision was assessed in two RCTs,56,57 two controlled trials,68,69 one nonconcurrent cohort study,71 and 10 case series.74,75,79,81-87 Refer to Tables 26, 27, and 28 for further information on outcomes measured.
Of the 16 RCTs, 8 compared one DA intervention to another DA intervention.50,54,55,59,61,62,64,65 Of these eight studies, four had a third comparison group.50,52,57,64 The study by Lerman, et al.50 also compared the two DA interventions to a wait list control group, while the three other studies compared the two DA interventions to the medical care that patients would typically receive (usual care).52,57,64 There were eight RCT studies that compared a DA intervention to usual care.51,53-56,58,60,63 Of the four nonrandomized controlled trials, one compared a DA intervention to another DA,68 and three compared a DA intervention to usual care.66,67,69 Both of the nonconcurrent cohort studies compared a DA intervention to usual care.70,71 Refer to Tables 20 and 21 for further details of the types of comparisons made.
| Author (year) | Reporting (Maximum score: 9) | External Validity (Maximum score: 3) | Internal Validity: Bias (Maximum score: 6) | Internal Validity: Confounding (Maximum score: 6) | FINAL SCORE (Maximum score: 24) |
| Maslin, 1998 | 3 | 1 | 1 | 3 | 8 |
| North, 1992 | 5 | 0 | 1 | 3 | 8 |
| Inglehart, 1998 | 4 | 2 | 1 | 3 | 10 |
| Watson, 1998 | 4 | 1 | 2 | 3 | 10 |
| Hack, 1999 | 3 | 2 | 3 | 3 | 11 |
| Shapira, 2000 | 5 | 2 | 2 | 3 | 12 |
| Irwin, 1999 | 6 | 2 | 2 | 3 | 13 |
| Davison, 1999 | 6 | 2 | 3 | 3 | 14 |
| Street, 1995 | 7 | 1 | 3 | 3 | 14 |
| Wolf, 2000 | 7 | 2 | 2 | 3 | 14 |
| Davison, 1997 | 6 | 2 | 4 | 3 | 15 |
| Lerman, 1997 | 8 | 2 | 2 | 3 | 15 |
| Wolf, 1996 | 7 | 2 | 2 | 4 | 15 |
| Volk, 1999 | 7 | 2 | 3 | 4 | 16 |
| Pignione, 2000 | 9 | 2 | 3 | 4 | 18 |
| Goel, 2001 | 9 | 3 | 3 | 5 | 20 |
| Davison, 1997 | 6 | 2 | 4 | 3 | 15 |
| Davison, 1999 | 6 | 2 | 3 | 3 | 14 |
| Goel, 2001 | 9 | 3 | 3 | 5 | 20 |
| Hack, 1999 | 3 | 2 | 3 | 3 | 11 |
| Inglehart, 1998 | 4 | 2 | 1 | 3 | 10 |
| Irwin, 1999 | 6 | 2 | 2 | 3 | 13 |
| Lerman, 1997 | 8 | 2 | 2 | 3 | 15 |
| Maslin, 1998 | 3 | 1 | 1 | 3 | 8 |
| North, 1992 | 5 | 0 | 1 | 3 | 8 |
| Pignione, 2000 | 9 | 2 | 3 | 4 | 18 |
| Shapira, 2000 | 5 | 2 | 2 | 3 | 12 |
| Street, 1995 | 7 | 1 | 3 | 3 | 14 |
| Volk, 1999 | 7 | 2 | 3 | 4 | 16 |
| Watson, 1998 | 4 | 1 | 2 | 3 | 10 |
| Wolf, 2000 | 7 | 2 | 2 | 3 | 14 |
| Wolf, 1996 | 7 | 2 | 2 | 4 | 15 |
| Author (year) | Reporting (Maximum score: 9) | External Validity (Maximum score: 3) | Internal Validity: Bias (Maximum score: 6) | Internal Validity: Confounding (Maximum score: 4) | FINAL SCORE (Maximum score: 22) |
| Flood, 1996 a Study 1 | 8 | 0 | 2 | 2 | 12 |
| Sepucha, 2000 b | 5 | 2 | 3 | 2 | 12 |
| Whelan, 1995 b | 7 | 2 | 2 | 1 | 12 |
| Flood, 1996 a Study 2 | 7 | 2 | 2 | 2 | 13 |
| Whelan, 1999 b | 7 | 2 | 3 | 1 | 13 |
| Molenaar, 2001 a | 9 | 2 | 3 | 3 | 17 |
Controlled trial
Nonconcurrent cohort
| Author (Year) | Reporting (Maximum score: 8) | External Validity (Maximum score: 3) | Internal Validity: Bias (Maximum score: 6) | Internal Validity: Confounding (Maximum score: 2) | FINAL SCORE (Maximum score: 19) |
| Adler (1999) | 4 | 2 | 2 | 1 | 9 |
| Ashcroft (1985) | 5 | 2 | 3 | 0 | 10 |
| Brundage (2000) | 8 | 1 | 3 | 2 | 14 |
| Cassileth (1989) | 5 | 3 | 2 | 1 | 11 |
| Cotton (1991) | 7 | 3 | 2 | 2 | 14 |
| Cotton (1995) | 3 | 1 | 2 | 2 | 8 |
| Fiset (2000) | 8 | 1 | 3 | 2 | 14 |
| Gramlich (1998) | 2 | 1 | 2 | 1 | 6 |
| Klass (1992) | 6 | 0 | 2 | 1 | 9 |
| Levine (1992) | 5 | 1 | 2 | 2 | 10 |
| Okamoto (1999) | 4 | 0 | 2 | 1 | 7 |
| Onel (1998) | 5 | 0 | 2 | 2 | 9 |
| Protiere (2000) | 7 | 3 | 2 | 2 | 14 |
| Sandison (1996) | 6 | 2 | 2 | 2 | 12 |
| Stalmeier (1999) | 8 | 1 | 2 | 2 | 13 |
| Wilson (1988) | 5 | 3 | 2 | 1 | 11 |
| Wolberg (1987) | 5 | 2 | 3 | 0 | 10 |
All three of the quality scales used to assess the RCTs yielded similar findings. Overall, 13 of these studies were rated as low methodological quality across all three scales. Only three studies52,63,65 were found to be of high quality. The results of the quality assessment highlighted several common areas of weakness among the RCTs. Most of the studies had satisfactory scores on the reporting subscale; however, many of the RCTs did not fully describe the DA intervention, nor did many of the studies report the number of patients lost to followup. On the internal validity (bias) subscale, all of the studies with the exception of the study by Davison58 had low scores. Only one study used a blinded assessment of the outcome measures,63 but there was no blinding among the included subjects or in statistical analyses in any of the RCTs. Only four studies54,61 reported reliability and/or validity of the intervention (DA). The outcome measures used were valid and reliable in 8 of the 16 studies.52,53,53,56,56,57,57,58,58,59,59,60,60,65 Compliance with the intervention was described in only two studies.51,51,58 On the internal validity (confounding) subscale, only five studies52,53,53,58,58,65,90 gave a complete description of the method used for random assignment; furthermore, none of the studies discussed whether there was randomization concealment.
The studies in this section are organized by the mode of delivery and degree of interaction of the DA intervention. In most studies, the DA intervention was supplemented by some form of usual care. In some studies, it was difficult to disentangle distinct components of the DA intervention, and we recognize that our categorization of the type of intervention may be arbitrary. We made a careful distinction between general information pamphlets and DA brochures. In DA brochures, screening or treatment options were clearly identified, along with associated risks and benefits, and the objective was to support decisionmaking. In this section, we discuss DA interventions in the following order: DA brochure, educational script, audiotape, videotape, interactive computer program, counseling, DB, and complex interventions (more than one component). Within each category, RCT studies are reported first, followed by nonrandomized controlled trials and then case series. For each study, we report the type and stage of cancer, the type of decision and options, the DA intervention, and primary outcome data. Details of each study are reported in their respective evidence tables.
Eight studies assessed the use of DA brochures (four RCTs and four case series).
Schapira and colleagues55 compared the use of a DA brochure to an information pamphlet. They tested the effect of an illustrated 8-page DA brochure on screening decisions (prostate specific antigen test [PSA] or digital rectal examination [DRE]) of men aged 50 to 80 who had attended an outpatient visit at a Department of Veterans Affairs Hospital. Men in the intervention group (n=122) received an 8-page illustrated pamphlet containing basic prostate cancer information and balanced descriptions of the quantitative and qualitative outcomes regarding risks and benefits of screening with DRE and PSA test. A research assistant was present to answer questions and a followup visit was scheduled. Menin the control group(n = 135)received a 5-page pamphlet containing basic prostate cancer information (i.e., epidemiology, symptoms of prostate cancer) as well as the other components (i.e., research assistant and followup visit).
Iglehart and colleagues62 published preliminary results of an RCT that compared two DA brochures designed to assist women at high risk of carrying a breast/ovarian cancer mutation in deciding whether to undergo genetic testing. One group of participants received a DA brochure that was individually tailored to each participant's education level, carrier probability, and preference for quantitative or qualitative risk estimates. The other group received a DA brochure containing generic information on genetic testing and breast and ovarian genetics. After receiving the DA brochures, all participants had the option of attending free genetic counseling and testing. The purpose of the study was to determine the effect of the individualized DA brochure compared to the generic DA brochure on participants' decisions, attitudes, and knowledge. To date, three interim papers have been published: the first two report baseline data62,91 and the third details the mutations identified and provides some preliminary results.92 In all three studies, the only data presented has been combined for two intervention groups. The authors report that the trial is now closed and participants are in the process of finishing genetic counseling, making genetic testing decisions, and entering the followup phase. Refer to Evidence Tables 5.2a and b for details of the outcomes measured.
Two RCTs compared DA brochures to another type of DA intervention. Goel and colleagues65 compared a DA brochure to an audiotape workbook. Refer to the Audiotape section for a discussion of this study. Street and colleagues59 compared a DA brochure to an interactive computer program. Refer to the Interactive Computer section for further details.
Schapira and colleagues55 found that the DA did not influence decisions regarding screening uptake (p=0.60).
They also assessed knowledge between the groups. They used an 18-item closed-ended questionnaire that was developed and pretested before its application. There were no baseline differences in the scores between the groups. After the intervention, both groups increased their scores, but those in the DA brochure group were statistically higher than those in the informational pamphlet group (p < 0.01).
They also assessed men's beliefs using a prostate cancer belief-assessment survey consisting of 10 closed-ended items that was previously pilot-tested. Domains in the belief assessment included natural history, intentions to use screening, intentions to follow physician advice, perceptions of test characteristics, and how well informed participants felt. Postintervention beliefs were compared between groups; men in the intervention group provided more accurate responses in 2 of the 10 items (p < 0.01, and p < 0.05, respectively).
Four case series evaluated written information provided to patients as DA interventions.84-87 In three studies a DA brochure was used, and in one study no detail about the material was provided.
Two of the studies dealt with adjuvant breast cancer treatment options.84,85 In Adler,85 the intervention consisted of education by a team (oncologist and oncology nurses) about the differences between two chemotherapy regimens including side effects, duration, administration, and number of needles. In addition, women were given take-home information (details not specified). Forty-one women with early stage breast cancer were given a choice between two types of adjuvant chemotherapy: doxorubicin/cyclophosphamide (AC) and cyclosphosphamide/methotrexate/fluorouracil (CMF). Protière and colleagues84 offered 64 breast cancer patients with nonmetastatic disease a choice of receiving their adjuvant chemotherapy and radiation therapy either sequentially or concomitantly. The intervention consisted of a consultation based upon a DA brochure. Patients were given the DA brochure to take home.
The two other case series evaluated DA brochures for advanced prostate cancer treatment options. Cassileth and colleagues86 gave men (n=159) the choice between surgical and hormonal castration. After discussing treatment choices with their physicians, patients took home a 2-page DA brochure. Klass and colleagues87 also gave men (n=101) the choice between surgical and hormonal castration. Following the oncology consultation, participants were provided with a DA brochure that they could takehome to review.
In the study by Adler,85 41 women were given the choice between two types of chemotherapy and 36 women answered a questionnaire after completing their selected treatment. Two women stated they did not remember being given a choice, 22 chose AC, and 12 opted for CMF chemotherapy. In Protière and colleagues,84 41 breast cancer patients elected to have the shorter concomitant treatment, while 23 patients decided to have their adjuvant treatment sequentially. In the Cassileth and colleagues86 study with advanced prostate cancer patients, surgical castration was chosen by 32 patients, while the majority of patients (115/147) chose hormonal castration. In the other prostate cancer study, Klass and colleagues87 reported that an equal number of patients chose surgical castration (n=46) and hormonal castration (n=46). Five patients in this study could not decide between the two options.
In Adler's study85 investigating choice between two types of adjuvant chemotherapy, 27 women felt that being given the chance to decide their treatment was beneficial, while 7 reported being unsure whether choosing their treatment was beneficial. Protière and colleagues84 reported that 51 of 57 patients were "fully satisfied" with participating in the selection of their adjuvant treatment schedule.
In Klass and colleagues,87 all 46 patients who selected surgical castration reported being at least reasonably satisfied with their choice. Of the 46 patients who opted for hormonal castration, only 1 patient responded that he was not at all satisfied with his choice.
In Alder's study,85 5 of the 34 women studied felt that "they were not given enough information to make an informed choice."
In Adler's study,85 women were asked whether "in hindsight they wish they had chosen the alternate treatment." One hundred percent of the AC group said no, compared with 33 percent of the CMF patients having stated they wished they had chosen AC. Three months after choosing either surgical or hormonal castration, men were asked if they would make the same treatment decision again. Of the patients available for followup, all 22 who had surgical castration said they would choose surgery again.86 Similarly, 88 of 89 men who chose hormonal treatment would again choose the same option.
In Protière and colleagues,84 quality of life was measured both pre- and postadjuvant treatment for breast cancer. Global quality of life at the end of treatment was significantly better among patients who decided to have treatment sequentially compared to patients who chose concomitant treatment (p<0.05).
Two RCTs were conducted using educational script DA interventions, both of which were conducted by Wolf.54,64 In the first study, Wolf and colleagues54 determined the impact of a scripted educational intervention on patients' interest in undergoing PSA screening. Men older than 50 years visiting their primary care physicians were included in the study and randomly assigned to one of two groups. In the intervention group (n = 103), the research assistant (RA) read aloud the script that contained information related to known risk factors for developing prostate cancer, the ability of the PSA test to detect early symptomatic cancer, the uncertain outcome of early intervention, and a brief description of treatment options for early prostate cancer and their complications. In the control group (n = 102), the RA read aloud a brief statement that a blood test known as the PSA is available that can sometimes detect early prostate cancer before it is otherwise apparent.
In the second study, Wolf and colleagues64 compared the impact of two scripted educational interventions on patients' interest in undergoing colorectal screening. Patients 65 years or older attending a routine visit with their primary care physician were included in the study. Participants were randomly assigned to one of three groups. In the first intervention group (n = 130), an RA read aloud a relative risk reduction script that contained information describing two colorectal screening tests; the evidence regarding mortality reduction was presented as a relative risk reduction. In the second intervention group (n = 136), the RA read aloud an absolute risk reduction script that contained the same information describing two colorectal screening tests; however, the evidence regarding mortality reduction was presented as an absolute risk reduction. In the control group (n = 133), an RA read aloud a brief description of the two colorectal screening tests.
In the first study, Wolf and colleagues54 measured the interest in PSA screening on a 5-point Likert scale. The results showed that men in the experimental group were less interested in PSA testing (p < 0.001). In a subsequent analysis,93 the authors evaluated the intervention in a subsample (control group, n = 48; intervention group, n = 56) of men > 65 years old. Again, participants in the intervention group were significantly less interested in screening (p = 0.006).
In the second study, Wolf and colleagues64 used a 5-point Likert scale to measure interest in colorectal screening. No statistically significant difference in colorectal screening interest was found between the three groups. Participants were also asked about their intent to have colorectal screening. Again, no statistically significant difference was observed between the three groups.
In the colorectal screening study, participants were asked about the positive predictive value of the fecal occult blood test. No significant difference was found between the two intervention groups. However, significantly more intervention group subjects (combined data) answered the question correctly compared to the control group subjects (p=0.0007).
In the prostate cancer study, participants were queried regarding potential predictors of interest derived from the Health Belief Model. The authors reported that there was no significant difference between groups in perceived susceptibility to prostate cancer and in the perceived seriousness of an abnormal PSA test. They also reported that the intervention group considered the PSA test to be less efficacious, and the control group was more willing to accept prostate cancer treatment risks. No raw data were provided, however. Among participants > 65 years, authors reported that men in the intervention group considered PSA screening to be significantly less efficacious than did the control group (p = 0.004). Again, no raw data were reported.
The authors assessed factors associated with the interest in PSA screening using an ordinal logistic regression model. The informational script (p < 0.001) and advancing age (p = 0.04) were associated with decreased interest in PSA testing. On the other hand, family history of prostate cancer was associated with increased interest in screening (p = 0.005).
Wolf and colleagues64 also assessed the perceived efficacy of screening in the colorectal cancer study. Participants were asked whether screening reduced the risk of dying from cancer "a great deal," "somewhat," or "very little." The perceived efficacy was highest in the control group, followed by the relative risk reduction script group, and lowest in the absolute risk reduction script group (p=0.0002).
Five studies assessed the use of audiotape interventions (four RCTs and one case series).
Four RCTs evaluated the use of audiotapes as DA interventions, three assessed the use of audiotapes of consultations,51,57,60 and one investigated the effect of an audiotape workbook.65 Watson et al.51 studied the effectiveness of a DA in women who had a family history of breast cancer. The intervention group (n = 60) received the standard consultation (which included genetic counseling, physical examination, and a summary letter of the consultation) plus an audiotape of the consultation. The control group (n = 55) received only the standard consultation. The outcome measures were women's recall of risk information, cancer-related worry, and uptake of risk management methods postintervention (i.e., mammography, breast self examination [BSE], tamoxifen, prophylactic mastectomy).
Hack and colleagues57 examined the efficacy of offering patients with an initial diagnosis of breast cancer (n = 18) or prostate cancer (n = 18) an audiotape of their primary oncology consultation. The options available to the patients were not reported. Of those with breast cancer, most had early disease, and the stage of prostate cancer was not specified. Cancer patients were randomly assigned to one of three groups: one group did not receive the audiotape, patients in the second group received the audiotape, and participants in the third group were given the choice of receiving or not receiving an audiotape. The authors did not report the number of patients included in each group. Most of the outcomes were reported by type of cancer (prostate or breast), rather than by intervention group, so it was not possible to describe the effectiveness of the DA. Only one outcome (knowledge) was reported by group, and these results are described in the outcome section below.
In North and colleagues,60 authors randomly tape-recorded the initial oncologist consultation in 34 consecutive new skin, gastric, lung, ovary, and pancreatic cancer patients with advanced disease in a medical oncology outpatient clinic. The treatment options were not reported. The consultant oncologist used a checklist to ensure that both groups received the same topics and facts during the consultation. All patients in the intervention group (n = 18) took home the tape recording, while those in the control group (n = 16) received nothing in addition to the consultation.
Goel and colleagues65 studied 136 women with early breast cancer making decisions about mastectomy or lumpectomy plus radiation therapy. They compared the use of an audiotape workbook (n=86) to a DA brochure (n=50). The audiotape workbook intervention consisted of an audiotape that reviewed the advantages and disadvantages of each treatment option plus an accompanying workbook containing color photographs and graphics. The intervention incorporated a 3-step values clarification exercise in which, after reviewing the pros and cons of each option, a patient assigned a value to each advantage or disadvantage, then examined the values assigned to determine which option was favored. The DA brochure contained identical information as the audiotape workbook, with the exception that it did not contain numbers, photographs, graphics, or a values clarification exercise.
Watson and colleagues51 reported that there were no differences in the uptake of prevention/screening options between the groups; however, no raw data for each group were provided. The various options included mammograms, breast examination (self or clinical), cervical smears and other screening, prophylactic surgery, and taking tamoxifen. North and colleagues60 reported that the audiotape aided decisionmaking regarding treatment in 11 of 18 (61 percent) patients. No control group data were reported. Goel and colleagues65 only reported the initial treatment preference measured at the baseline survey pre-intervention.
One month after the intervention, Watson and colleagues51 asked women to recall risk information provided by the clinical geneticist during the consultation. Accuracy of recalling their risk of developing cancer was not statistically significant between the intervention and control groups (p = 0.15). More women in the intervention group (64 percent vs. 42 percent) were able to remember correctly whether they had been given information on risk before age 50; this finding was statistically significant (p < 0.05). There were no differences between groups in the other five items assessed. Hack and colleagues57 reported that patients with prostate cancer who received the audiotape by choice (Group 3 -- all patients chose to receive the tape) recalled a more thorough consultation than did patients who were given the audiotape (Group 2) and those patients who were not given the audiotape (Group 1) (p < .05). No data were reported for those with breast cancer. North and colleagues60 asked patients to recall information discussed during the consultation, such as treatment options and prognosis. After the consultation, both groups recalled about the same amount the information. One week after the consultation, patients in the intervention group were able to recall significantly more information than were those in the control group (p < 0.0001).
Goel and colleagues65 measured knowledge approximately 3 days postintervention using the Breast Cancer Information Test -- Revised (BCIT -- R). This test consists of 18 true/false questions. No significant difference in breast cancer knowledge was observed between the audiotape workbook intervention group and the DA brochure group.
Watson and colleagues51 also assessed concerns about developing cancer and the impact of cancer worry on daily functioning, using the Cancer Worry Scale (Lerman et al., 1991).94 The authors reported that the intervention group scores significantly decreased from baseline at 1 and 6 months postconsultation; however, postintervention control group scores were not provided. Using the Hospital Anxiety and Depression scale, North and colleagues60 evaluated anxiety scores before and after the intervention. Baseline scores were similar in both groups. After the intervention, scores in both groups decreased, but the reduction was statistically significant in the intervention grouponly (p < 0.001).
Goel and colleagues65 measured anxiety at three points (pre-intervention, postintervention, and at 6-month followup) using the State component of the State-Trait Anxiety Inventory. Pre-intervention, there was no statistically significant difference between the audiotape workbook intervention group and the DA brochure group. The mean anxiety in both groups was high (greater than 50 points). Two to 3 days postintervention (pre-operatively), the mean anxiety score in both groups continued to be high, with no significant difference between the groups. At 6-month followup, the mean anxiety score in both groups decreased to approximately 35 points, which was within the normal range. Again, no significant difference was observed between intervention groups.
Watson and colleagues51 rated the usefulness of the information on a visual analogue scale (VAS), from 1 = not useful to 10 = very useful. The authors reported that there were no statistically significant differences between the groups; however, no raw data were provided. The audiotape was rated on a VAS (1 = not very helpful, 10 = extremely helpful); and the median score was 8.3 (range 0.2-10). Of 60 women, 8 expressed satisfaction with having the audiotape at home, 5 found it useful for clarifying what the doctor had said, and 4 found it reassuring. Three other women said that the audiotape reinforced their memory of the visit and the information given. Other women said that it helped them to explain information to relatives. North and colleagues60 asked patients to express their opinion about using the tape. Seventeen of 18 expressed "very positive feelings." Only one patient reported being "mildly upset" by the audiotape. They also reported that 5 of the 18 patients with the audiotape said it enabled other family members to listen to the interview. The authors also reported that "...several used the tape to explain to their family and at least three patients played the tapes to, and discussed them with, their general practitioners."
Goel and colleagues65 measured decision conflict using the O'Connor Decisional Conflict Scale48 2 to 3 days postintervention. There was no significant difference in decision conflict between the audiotape workbook group and the DA brochure group. In a posthoc subgroup analysis, the audiotape workbook reduced decision conflict in women whose initial treatment preference (pre-intervention) was either uncertain or favoring mastectomy (statistical analysis was not reported).
Goel and colleagues65 measured decisional regret at 6-month followup. Participants were asked whether they regretted their treatment choice and whether the decision did them a lot of harm. There was no significant difference in decisional regret between the audiotape workbook group and the DA brochure group.
Goel and colleagues65 asked participants at 6-month followup whether they would choose the same treatment again, whether it was the right decision, and whether the decision was a wise one. There was no significant difference in responses between the audiotape workbook group and the DA brochure group.
Hack and colleagues57 reported that more patients who chose to receive the tape (Group 3) listened to a portion of the tape than those who were given the tape (Group 2) (83 percent vs. 55 percent, p= NS).
Fiset and colleagues77 evaluated an audiotape workbook intervention for patients (n=20) with stage IV lung cancer making the decision whether to have chemotherapy in addition to supportive care and radiation therapy.
Participants were asked about their chemotherapy preference pre- and post-intervention. Pre-intervention, 13 patients preferred chemotherapy, 1 patient preferred supportive care, and 6 patients were unsure. Postintervention, 14 patients preferred chemotherapy, 4 preferred supportive care, and 2 patients remained uncertain.
Knowledge was assessed both pre- and postintervention using 16 true/false/unsure items based on information contained in the audiotape workbook intervention. There was a significant improvement in knowledge postintervention (p<0.001).
Decision conflict was measured both pre- and postintervention using two of the subscales from the O'Connor Decision Conflict Scale.48 A significant decrease in decision conflict was observed postintervention (p<0.001).
All 20 participants found the audiotape workbook intervention helpful and would recommend it to others. Sixteen of the participants reported being satisfied with the amount and clarity of information presented. Fifteen participants thought the information was balanced. Four participants reported that they found the survival information upsetting.
There were six studies that examined the effectiveness of a videotape as a DA. There were two RCTs, two nonrandomized controlled trials, and two case series.
One RCT52 addressed the effectiveness of videotapes in the prostate cancer screening decisionmaking context. Volk and colleagues52 included asymptomatic primary care patients who were assigned to one of three groups. One of the intervention groups (n = 40) viewed the videotape, "The PSA Decision: What YOU Should Know," developed by The Foundation for Informed Medical Decision Making, Inc., prior to their office visit. Participants in the other intervention group, after viewing the same videotape, had a utility assessment and then the office visit (n = 40). Patients in the control group only attended their office visit (n = 80). The authors reported that both intervention groups did not differ significantly on any of the sociodemographic indicators, previous PSA testing, or any outcome measure, so the two intervention groups were collapsed into one for further analysis.
Pignone and colleagues63 evaluated the impact of a DA videotape plus accompanying DA brochure on colorectal screening decisions of patients 50 to 75 years of age who were attending a visit with their primary care physician. Participants in the intervention group (n=125) viewed a DA videotape that provided information regarding susceptibility to colon cancer and the availability of effective screening tests. After watching the DA videotape, participants were asked to select the color-coded brochure that best reflected their interest in colorectal screening. Each type of DA brochure reinforced the information contained in the DA videotape. Participants in the control group (n=124) viewed an videotape about car safety and then received a car safety information pamphlet.
Volk and colleagues52 assessed participants' preferences for PSA testing. After the intervention, men who received the DA were less likely to want PSA testing in comparison with men who did not receive the videotape (62 percent vs. 80 percent, p = 0.009). Among intervention group participants, there was a statistically significant decrease from baseline in the percentage (79 percent vs. 62 percent, p = 0.01 of participants wanting PSA testing);no significant change was observed in the control group (78 percent vs. 80 percent).
Pignone and colleagues63 assessed participants' decisions to have colorectal screening in two ways. First, they asked participants whether a screening test had been ordered during the visit with their primary care physician immediately following the intervention. Second, they conducted a followup chart review at 6 months postintervention. Significantly more participants in the intervention group reported ordering colorectal screening tests compared to the control group (no p value provided). The results of the chart review were: (1) significantly more colorectal screening tests had been ordered for the intervention group participants compared to the control group (no p value provided), and (2) significantly more colorectal screening tests had been completed for participants in the intervention group compared to the control group (no p value provided).
Volk and colleagues52 developed a 10-item instrument that included domains related to the videotape content (i.e., prostate cancer epidemiology, screening accuracy, treatment effectiveness) to evaluate prostate cancer knowledge. Two weeks after the intervention, more participants in the intervention group answered at least 5 out of 10 questions correctly compared to control participants (62 percent vs. 31 percent, p=0.001). The intervention groups' score compared to baseline was also significantly improved (p = 0.001).
In the study by Volk and colleagues,52 the intervention group was asked to rate the videotape. Ninety-two percent reported that they would recommend its use to other patients, 79 percent considered the information was about right, and 86 percent felt that the videotape length was about right. Eighty-six percent rated the issues as clearly presented, and 79 percent rated the presentation as completely balanced. The perceived influence of the DA on their decisions was expressed as "a great deal" by 35 percent, "quite a bit" by 28 percent, "a moderate amount" by 20 percent, "not much" by 11 percent; and "not at all" by 7 percent of the subjects in the intervention groups.
Flood and colleagues performed two studies66,67 to evaluate educational videotapes designed to inform men about the uncertainty surrounding PSA screening. Both studies were reported in the same article. In the first study,66 the authors included men attending a clinic that was offering free prostate screening examinations and evaluated two different videotapes. The control group (n = 203), enrolled on day 1, viewed a videotape that advocated the utilization of PSA testing ("Shering Video"), while men in the intervention group (n = 206), enrolled on day 2, viewed the "Prostate-PORT Video" that was specifically developed for the study. This videotape was designed to encourage patients to participate in the decision to screen for prostate cancer, presenting not only the pros and cons of the screening, but also the uncertainty surrounding the effectiveness of treatment and the complications that may occur. After the intervention, men were invited to receive a DRE and a PSA test. The authors also asked about treatment preferences for prostate cancer: radical prostatectomy, radiation therapy, or watchful waiting.
In the second study,67 Flood and colleagues included men older than 50 years who were scheduled for a routine physical examination (RPE) or nonurgent followup at a general internal medicine clinic. The trial consisted of viewing the "Prostate-PORT Video," its associated brochure, and the RPE (experimental group, n = 120); or only receiving the RPE (control group, n = 102). After the physicians were informed of the study, the authors began to enroll the participants. The control group was completed first, and afterwards the authors began the intervention group recruitment. The physicians were not told the dates of recruitment initiation, when the intervention started, or the ending of the study. The options in the second study were the same as in the first.
In the first study, there was no statistically significant difference between the intervention and control groups in the proportion of men who actually had a PSA test (98.4 vs. 100 percent, p = 0.07), although the only three patients that refused the test were from the intervention group. When men indicated their likelihood of having another PSA test within the next 2 years, there was a significant difference between the groups. After viewing the video, more control group men rated the chances of having the test within the next 2 years as "high" (89.7 vs. 73.9 percent, p = 0.002).
When asked about preferences for prostate cancer treatment (radical prostatectomy, radiation therapy, or watchful waiting), there were statistically significant differences between the groups. Sixty-three percent of the intervention group preferred watchful waiting, and 51.2 percent of the control group preferred radical prostatectomy (p = 0.0000).
In the second study, the proportion of men in the intervention group who actually had a PSA test was significantly lower than the proportion of men in the control group (11.7 percent vs. 22.6 percent, p = 0.041). Also, more men in the intervention group estimated the chances of having a PSA within the next 2 years as "low" (30.4 percent vs. 67.0 percent, p = 0.0000). After the intervention, most intervention group men preferred watchful waiting (85.9 percent), whereas most men in the control group preferred either radical prostatectomy (40.7 percent) or watchful waiting (39.5 percent). This difference was statistically significant (p = 0.0000).
In both studies, the authors compared correct responses to three questions: one was about the PSA test predictive value and the natural history of prostate cancer, the second corresponded to prostate cancer treatment efficacy, and the third was related to the prostate cancer treatment efficacy. In the first study, a significantly higher proportion of men in the intervention group answered all three questions accurately (50.3 vs. 71.7 percent, p = 0.0002; 61.0 vs. 11.4 percent, p = 0.0000; and 64.2 vs. 30.5 percent, p = 0.0000, respectively). Similar results were found in the second study: the proportion of more accurate responses for each question was higher in the intervention group (92.9, 69.9, and 71.8 percent) than in the control group (40.9, 23.7, and 14.5 percent). For all the questions, the differences were statistically significant (p value = 0.000 for the three proportions).
Men with localized prostate cancer viewed a DA videotape (one of six versions, each identical except for variations in risk factors that were adjusted according to patient age and Gleason score) prior to an oncology consultation in which they decided among four treatment options (radical surgery, radiation therapy, watchful waiting, hormonal treatment).74 In another case series, women less than 65 years of age with early stage breast cancer viewed tape-slide presentations (one for mastectomy and one for lumpectomy plus radiation therapy) to assist them in deciding between the two treatment options.81 The women in this study also received counseling from the oncology staff.
In the Onel and colleagues study,74 of the 95 men included, 32 chose radical surgery, 33 selected radiation therapy, 22 opted for watchful waiting, and 8 decided to have hormonal treatment. In Wilson and colleagues,81 of 153 women, 99 chose mastectomy and 54 opted for lumpectomy plus radiation.
Onel and colleagues74 asked men with prostate cancer to rate their knowledge of the disease at three points: pre-DA, post-DA and post-DA+consultation. According to the authors, their data suggest that the DA (videotape) greatly increased patients' knowledge of prostate cancer (no statistical analysis reported).
Wilson and colleagues81 reported they were aware of only 1 woman out of 153 who regretted her decision. This patient had chosen mastectomy instead of lumpectomy plus radiation therapy. In the study by Onel and colleagues,74 men with prostate cancer were asked if they would choose the same treatment again: 55 percent of men who chose radiation therapy, 66 percent of radical prostatectomy patients, 68 percent of watchful waiting patients, and 71 percent of men on hormonal treatment said "yes."
In the study by Wilson and colleagues,81 28 of the 153 women offered a choice between mastectomy and lumpectomy were interviewed 2 years post-surgery. Two of the 28 women reported that, in retrospect, they were unhappy with having had to choose their treatment. Two prostate cancer patients in the Onel study74 reported they would have preferred the doctor to make the treatment decision; the remaining 95 patients said they were pleased to have participated in the decisionmaking. It is surprising, given the relatively low number of participants who would choose the same treatment again in Onel and colleagues,74 that 93 percent of the men reported being either "delighted," "pleased," or "mostly satisfied" with their decision.
Four studies evaluated the use of interactive computer program interventions (two RCTs, one nonrandomized controlled trial, and one case series).
Two RCT studies56,59 about interactive computer programs were reviewed. Maslin and colleagues56 evaluated the usefulness of an interactive video disk system (IVDS) in women with early breast cancer considering surgical and adjuvant treatment options. One hundred patients were randomized to receive either standard care based on information they were given from a multidisciplinary team (n = 49) or to receive the IVDS in addition to the standard care (n = 51). The IVDS consisted of two parts. Initially, the patient's own details such as age and tumor size were entered. In the second section, the patient could choose to go forward or backward within the IVDS to review pertinent information at their discretion. The system offered information based on a current overview of RCTs as well as on current areas of debate and a rationale for treatment options. The system recognized that patients have values and preferences that may influence their choice of local or systemic treatment. For this study, raw data pertaining to choices were reported as bar graphs, making it difficult to extract the results of the study.
Street and colleagues59 studied 60 women with early breast cancer who were making decisions about mastectomy or lumpectomy and radiation therapy. They compared an interactive multimedia program (IMP) (n = 30) to an eight-page DA brochure that described treatment options (n = 30). The IMP was called "Options for Treating Breast Cancer" and was operated on an Apple computer with a touch screen monitor. The program consisted of text, graphic display, audio narration, and audiovisual clips divided into four sections: Introduction, Understanding the Problem, Treatment Options, and Experiences of Other Women.
For the Maslin study,56 we could not extract the results of the treatment that women chose (surgery, chemotherapy and/or radiation therapy) from each group, although the authors reported: "The women's treatment option choice showed no statistically significant difference, p = 0.8...." Street and colleagues59 compared the proportion of women selecting breast conservation and breast removal in both experimental conditions; 76 percent of the IMP group and 58 percent of the DA brochure group chose breast conservation. The authors did not find any significant differences between the groups.
Street and colleagues59 assessed knowledge about breast cancer treatment with an 11-item questionnaire. This outcome was measured before and after the intervention and after the consultations with physicians. Scores in both groups showed a statistically significant increase from baseline after receiving the intervention (p < 0.001). No difference was detected between the groups (p = 0.07).
Maslin and colleagues56 asked women in the intervention group to give their opinion about the IVDS. Fifty-four percent stated that the IVDS had not influenced their ultimate decision, and 30 percent felt it had influenced their treatment decision. Ninety-six percent found the IVDS interesting, 92 percent easy or very easy to understand, and 82 percent just about the right length; 72 percent felt they had gained a much clearer idea about breast cancer; and 92 percent would recommend the IVDS to someone else with the disease.
Maslin and colleagues56 assessed anxiety, depression, and satisfaction with decision, reporting the results by group. Street and colleagues59 expected that breast cancer patients would express more optimism about the future after using the IMP in comparison with those who used pamphlets. Optimism was measured with a previously developed eight-item instrument. The results did not confirm their hypothesis; scores in both groups were almost the same before and after the DA as well as after the consultation (p = 0.78). Comparison of optimism scores between groups did not reach statistical significance, p = 0.34.
Molenaar and colleagues69 assessed the effect of an interactive computer program designed to assist women with early stage breast cancer in deciding between mastectomy and lumpectomy plus radiation. Participants in the intervention group (n=92) used the interactive computer program after attending their surgical oncology consultation. Participants in the control group (n=88) received an information pamphlet (designed to promote recall and further deliberation of their preliminary treatment choice) after their surgical oncology consultation. The purpose of the study was to determine whether the interactive computer program affected participants' treatment decisions, satisfaction, and quality of life.
There was no significant difference between the intervention and control groups in actual decision. In the intervention group, 69 women chose lumpectomy plus radiation therapy, and 23 women opted for mastectomy. In the control group, 60 women chose lumpectomy plus radiation therapy, and 28 women decided to have a mastectomy.
The O'Connor Decisional Conflict Scale48 was used to measure decision conflict pre-intervention. Baseline decision conflict was significantly greater in the intervention group compared to the control group. The authors reported that they added decision conflict as a covariate for all subsequent statistical analyses.
The authors measured several aspects of satisfaction at both 3- and 9-month followup. At 9-month followup, intervention group participants were significantly more satisfied than were control group participants in all of the areas assessed: (1) satisfaction with general information (p<0.01), (2) satisfaction with treatment-specific information (p=0.03), (3) satisfaction with the decisionmaking process (p=0.02), (4) satisfaction with decision (p=0.03), and (5) satisfaction with care (p=0.04).
The authors measured both generic and breast cancer specific quality of life at baseline and then at 3- and 9-month followup. Generic quality of life was assessed using the Medical Outcomes Study 20. Breast cancer specific quality of life was measured using the European Organization for Research and Treatment of Cancer Quality of Life Breast Cancer scale. At baseline, there was no significant difference in quality of life between the intervention and control groups. At 9-month followup, however, intervention group participants reported significantly greater quality of life (both generic, p<0.01, and breast cancer specific, p<0.05) compared to control group participants.
One case series evaluated an interactive videodisk DA designed to help early breast cancer patients with both primary and adjuvant treatment decisions.75 The videodisk was developed by the Foundation for Informed Medical Decision Making. It is not clear how many women viewed the primary surgery DA program or the adjuvant program or both.
The authors reported the primary treatment preference of 49 women with breast cancer before and after viewing the surgery program.75 Of the 17 women who preferred mastectomy pre-DA, 14 retained this preference post-DA, and 3 women stated they had no treatment preference post-DA. There were 27 women who expressed a preference for lumpectomy plus radiation pre-DA; all 27 retained this preference post-DA. Of the five women who expressed no treatment preference pre-DA, four of them stated a preference for lumpectomy and radiation post-DA, and one woman still did not have a preference.
Gramlich and colleagues75 also reported that 98 percent of patients (N=83) rated the clarity of the surgery program as "excellent" or "very good."
In this study, patients were asked at 6 months post-DA how satisfied they were with their decisions. Pooled data were reported for the surgery and adjuvant interactive videodisks. Of the 57 patients available for followup, 82 percent rated their satisfaction as "excellent" or "very good."
Ninety-five percent of patients who participated in the interactive videodisk DA study by Gramlich and colleagues75 felt "very positive" or "generally positive" about other patients viewing the program.
Five studies, one RCT and four case series, evaluated counseling interventions.
Davison and colleagues53 explored whether providing men with additional information about screening for prostate cancer would enable them to assume more active roles in decisionmaking with their family physicians. Men in the control group (n = 50) talked with the investigator about general issues prior to their medical appointment, while those in the intervention group (n = 50) were provided with verbal and written information about controversies surrounding screening for prostate cancer and the pros and cons of having a DRE and/or a PSA test. Men were encouraged to discuss screening issues with their family doctor.
After the intervention, the authors reported that 49 percent of men were screened with a DRE and PSA test: 21 percent from the control group and 28 percent from the intervention group (no statistical analysis was reported). According to Degner's Control Preference Scale,95 no significant differences were found between role preferences for the two groups before the intervention (p = 0.398). After the intervention, more men in the intervention group assumed an active role in decisionmaking during the consultation compared to men in the control group (p = 0.00002).
Davison53 measured the state of anxiety by Spielberg's State Trait Inventory. Before and after the intervention, there were no significant differences in the anxiety scores between the intervention and control groups (p value not reported).
Based on O'Connor's Decisional Conflict Scale (O'Connor48), Davison and colleagues53 evaluated the degree to which men experienced decisional conflict in making prostate screening decisions after the intervention. Men in the intervention group had statistically significant lower levels of decisional conflict (p = 0.0001).
Three of the four case series explored the use of individual counseling by oncology nurses to help breast cancer patients make primary treatment decisions.79,80,83 Two of the studies investigated the surgical choice of mastectomy versus lumpectomy (plus radiation therapy).79,80 In both studies, patients were also given information pamphlets to take home. Cotton79 studied 20 women with "screen-detected breast cancer," and Cotton and colleagues80 studied 91 women with primary operable breast cancer. In the third case series, Sandison and colleagues83 presented older women with four primary treatment options (tamoxifen alone; complete local excision and tamoxifen; modified radical mastectomy and tamoxifen; and complete local excision, radiation therapy, and tamoxifen). In this study, 50 women aged 70 years or older were given individual counseling and a take-home information sheet in addition to the usual oncology consultation.
In the fourth case series, conducted in Japan, Okamato and colleagues88 evaluated a physician-administered counseling intervention. The intervention was designed to assist patients (n=57) diagnosed with hypopharyngeal cancer (including all stages) in deciding whether to have chemoradiotherapy or surgery. At the initial oncology consultation, the physician described the type and stage of the tumor and outlined the two treatment options available using visual aids. The physician continued to provide each participant with additional counseling sessions to review the risks and benefits of each treatment option until the participant reached a decision.
Cotton and colleagues80 reported that, of the 91 patients studied, 50 chose mastectomy and 41 elected to have lumpectomy plus radiation therapy. Cotton also published a similar study in 1995, in which 10 of the 20 women studied chose mastectomy, 9 decided to have lumpectomy plus radiation therapy, and 1 woman did not perceive she was given a choice.79 In the study by Sandison and colleagues,83 after the DA intervention, 38 women elected to choose their own treatment and 12 asked the surgeon to decide. Of the 38 women who chose their own treatment, 33 selected lumpectomy (31 with tamoxifen plus radiation therapy and 2 with tamoxifen), 4 women chose mastectomy plus tamoxifen, and 1 patient opted for tamoxifen only.
Okamato and colleagues88 reported that, of the 57 hypopharyngeal cancer patients studied, 43 chose chemoradiotherapy, 11 decided on surgery, 2 requested to be transferred to another hospital, and 1 decided not to be treated.
Cotton79 reported that 14 of the breast cancer patients were "glad to make a decision on their own treatment," while 5 patients were "not glad to have a say in the choice of treatment." In the Sandison and colleagues83 study of older women with breast cancer, 36 of 38 patients who elected to choose their own treatment reported that they had made the right choice.
Cotton79 reported that, of the 19 patients studied, 1 found "discussions with the breast-care nurse" unhelpful, 7 stated they did not read the literature provided until after surgery, and 2 found the "material upsetting."
In Cotton's study,79 3 of the 19 women interviewed 12 months post-breast-cancer surgery stated that they would not make the same choice again. All three of these patients had chosen to have mastectomies.
Okamato and colleagues88 compared the length of time between participants' initial oncology consultation to start of treatment with the duration from initial visit to start of treatment for the 60 hypopharyngeal cancer patients treated before the intervention was implemented. The authors reported that the counseling intervention increased the time to treatment (no statistical analysis was provided).
Okamato and colleagues88 reported that there was no significant difference in the crude 3-year survival rate of intervention participants compared to the 60 patients seen before the intervention was implemented (no statistical analysis was provided).
Ashcroft and colleagues76 conducted a large study with women who presented to a clinic with breast problems. All of the women completed a battery of psychological measures at multiple points. Within this group, 43 women were diagnosed with breast cancer. In 25 of these patients, a specific medical treatment was indicated. The remaining 18 women were offered the choice of mastectomy, lumpectomy with radiation therapy, or entry into a clinical trial where they would be randomly assigned to one of the two treatments. Four women entered the clinical trial, and 14 women elected to chose their own treatment. An informal decision analysis procedure was used to help these women decide which treatment they would prefer.
Of the 14 breast cancer patients who elected to chose their own treatment, 6 decided on mastectomy and 8 opted for lumpectomy and radiation therapy.76
In the study by Ashcroft and colleagues,76 anxiety and depression were measured at multiple times, both before and after breast cancer surgery, in women who decided their own treatment with the assistance of informal decision analysis. Unfortunately, these results were presented pooled with data from women who were not offered a choice because their condition necessitated a specific treatment.
Ashcroft and colleagues76 also measured body satisfaction, social adaptability, martial adjustment, and self-esteem. Like the anxiety and depression data, this information was not reported separately for those women who received the DA intervention and made their own choice. Ashcroft and colleagues76 stated that patients' scores on these tests were comparable to those of the normal population.
Refer to Chapter 4 for a complete description of DB instruments. Four studies evaluated DB interventions (one RCT, two nonconcurrent cohort studies, and one case series).
Irwin and colleagues61 tested the hypothesis that a different order of presentation of information would influence the choices of breast cancer patients. They developed and evaluated a DB to objectively educate patients about the benefits and risks of adjuvant chemotherapy. There were two options, Adriamycin + Cyclophosphamide (AC) or Cyclophosphamide + Methotrexate + 5-Fluorouracil (CMF). Women were allocated to one of the two versions of the DB; one version displayed CMF first and then AC (n = 23). The other version displayed AC first, followed by CMF (n = 23).
After the intervention, the proportion of women who chose AC or CMF was similar between groups. Ten of 23 (43.4 percent) women who were presented with CMF first chose AC, 12 (52.1 percent) chose CMF, and one (4.3 percent) chose no treatment. For women in the other group, 13/23 (56.5 percent) chose AC, 9 (39.1 percent) chose CMF, and 1 (4.3 percent) chose no treatment. The authors reported that there were no significant differences, but no statistical analysis was given.
Irwin and colleagues61 evaluated learning and comprehension after patients used the DB. They asked women to answer eight multiple-choice questions with three options and quantified the percentages of correct answers. The authors reported responses as pooled data, rather than by intervention group.
The authors asked the women with breast cancer to rate the DA. Ninety-eight percent rated it "quite helpful" or "very helpful." Difficulty with decisionmaking was assessed with a 5-point scale, from "very much" to "not at all." Thirty-two percent of the women considered the decisionmaking "not at all" difficult; the rest of the participants indicated some level of difficulty. The data reported also are pooled.
Two studies compared the use of a DB in women with breast cancer for treatment decisionmaking among cohorts recruited in consecutive periods of time. Comparisons of the outcomes were performed before and after the DB implementation. Whelan and colleagues70 compared the frequency of choosing breast irradiation after lumpectomy in three groups. The cohorts were gathered in consecutive phases. The first cohort was assembled after a standard clinical radiation oncologist consultation (n = 23); the second consisted of women who attended the consultation, but where physicians had a checklist to standardize the content of information they provided (n = 29). The last cohort included breast cancer patients who were exposed to a DB during the consultation (n = 30). In the second study, Whelan and colleagues71 determined the proportion of women with breast cancer who chose mastectomy or lumpectomy plus radiation therapy before and after the introduction of a DB. The historical cohort consisted of patients who underwent surgery in the 18-month period before the introduction of the DB (n = 194); women in the intervention cohort (n = 175) were recruited during the following 18-month period.
In the first study,70 Whelan et al. (1995) found that most patients in the three cohorts chose breast irradiation. The proportions of women who made this choice were 96, 97, and 93 percent, respectively; no statistical analysis was reported for this outcome. Results of the second study71 showed a significantly lower proportion of women who underwent lumpectomy in the DB cohort (73 percent) than in the historical cohort (88 percent), (p = 0.001).
Based on 10 true or false statements regarding information about breast irradiation, Whelan and colleagues70 compared patient comprehension among the three cohorts. One statement was significantly different among the groups, and more women in the DB cohort answered this item correctly (p < 0.0001). Whelan and colleagues71 also assessed patient comprehension; however, only the DB cohort answered this questionnaire.
Whelan and colleagues71 assessed satisfaction in the DB cohort only. Ninety-seven percent of the women were satisfied with the information received, and 95 percent with the decisionmaking process.
Whelan and colleagues70 asked 27/30 women of the DB cohort about their perceptions of the DA. All women reported that it was easy to understand, 22 said that it helped them to make a decision and to think of further questions to ask, and 20 patients recommended that the DB be used for other patients. In the study by Whelan and colleagues,71 they evaluated this outcome only in women exposed to the DB. The authors reported that 98 percent of the patients found it easy to understand and would recommend its use with other patients. Eighty-one percent said that the DB helped them to make a decision, and 64 percent indicated that it helped them think of questions to ask.
This study70 also compared reasons for choosing breast irradiation across groups. The authors measured this outcome with a six-item questionnaire; patients were asked to score each item from 1 to 5 according to its perceived importance. All but one of the mean importance scores were similar. The DB cohort had the significantly lowest score for the physicians' irradiation recommendation in comparison with the other two groups' scores. Patients also reported that radiation oncologists were less likely to make a formal recommendation when the DB was used (p<0.0001; comparison group not reported). The authors also reported that women's perceptions of having been offered a choice was significantly different: 97 percent of the DB cohort versus 70 percent of the other two cohorts (p = 0.02).
Whelan and colleagues71 used the Degner's Control Preference Scale.95 The DB cohort women were asked about their decisionmaking role postintervention. Fifty-one percent preferred an active role, 36 percent a collaborative role, and 12 percent a passive role.
Levine and colleagues78 explored the use of a DB intervention to help women with node-negative breast cancer decide whether to have adjuvant chemotherapy.
Of the 37 women who used the DB, 34 chose to have adjuvant chemotherapy.
Of the 30 women who were asked, 15 patients stated that the DB "definitely helped" them to decide whether to have adjuvant chemotherapy, 11 patients felt the DB "helped," and four patients felt "it did not help."78
Levine and colleagues78 asked patients whether they found the DB easy to understand. Of the 30 patients surveyed, 19 found the DB was "very easy," 10 patients said it was "easy," and 1 patient reported that the DB was "difficult to understand." The authors also reported that 29 of the 30 patients would recommend that the DB be used with other breast cancer patients. They asked 30 patients if the DB helped them think of further questions to ask the nurse or doctor. Nine responded that the DB "definitely helped," 15 said it "helped," 5 said the DB "did not help," and 1 patient did not answer. In this DB study, patients were also asked if they had shown the take-home version of the DB to anyone else. Twenty-four of the 30 patients studied had shown the DB to someone. In this subset, 10 patients stated that the DB "definitely helped describe treatment choices," 11 said the DB "helped," two stated that the DB did not help, and 1 patient did not answer.
In this section, since the DA interventions consisted of several different components, each study and its outcomes are reported separately. As in previous sections, RCTs will be described first, followed by controlled trials, and then case series.
There were two RCTs50,58 that included two or more primary components in their DA.
In this study, two forms of BRCA1 pretest education -- "an educational or informative" approach and a "counseling or interpretative approach" -- were compared. The informative approach was based on the standard medical model of patient decisionmaking and consisted of a DA educational session + printed handouts (n = 114). The other group received the same DA educational session and handouts as well as "nondirective" genetic counseling that was based on behavioral models of decisionmaking (n = 122). Both groups were compared to a nonintervention group (waiting list [n = 164]). The main outcomes were knowledge, perceived risk of having a BRCA1 mutation, perceived benefits, limitations and risks of testing, the intention to undergo a BRCA1 genetic test, and the provision of a blood sample.
Among the three groups, there were no differences in the proportion of participants wanting to undergo a genetic test in the education group, the counseling group, or the wait list control group (57 percent, 61 percent, and 53 percent, respectively). The proportion of women who provided a blood sample was similar in both the education and counseling groups (50.8 percent vs. 51.6 percent). This outcome was not evaluated in the control group.
Breast cancer and BRCA1 testing knowledge were assessed in this study at baseline and 1 month after the intervention. The outcome measure was developed based on previously published instruments. Both intervention groups showed increased knowledge from baseline after the DA. No difference was found between intervention groups, but both were statistically different from the control group (p = 0.0001).
They also evaluated the perceived personal risk of having a BRCA1 mutation and perceived limitations and risks of the test. There was no demonstrative impact of the interventions on perceived personal risk of having a BRCA1 mutation. However, both interventions improved patient understanding regarding limitations and risks of BRCA1 testing, and the education plus counseling intervention appeared to be better than the educational intervention alone (p < 0.05).
..In the other RCT study, Davison and colleagues evaluated a method to assist men newly diagnosed with prostate cancer to obtain information. There were two groups. Men in the control group (n = 30) were provided five DA brochures containing various types of information about prostate cancer (i.e., disease process, treatment options). They were told that it might be helpful to read the information before or after the initial treatment consultation. Men in the intervention group (n = 30) received the DA brochures and then were asked to think about the type of information they needed to assist in deciding the best treatment for them. A list of questions was reviewed with the patients to give them an idea of the types of questions they could ask their physician. Additional questions were added to the list, and a final list was generated. Men were provided with a blank audiotape, and patients were free to tape the consultation. They were also encouraged to participate in the decisionmaking process.
To elicit patients' preferences, the Degner Control Preference Scale95 was used before the intervention and after the consultation. No significant differences were found in the proportion of the preferred roles (active, collaborative, and passive) before the intervention (p = 0.113). Five to 6 weeks after the consultation, a significantly higher proportion of men in the intervention groups assumed a more active role in treatment decisionmaking (p < 0.001). Two men in the intervention group reported that the audiotape assisted them in making their treatment decision.
Using the Speilberger State-Trait Anxiety Inventory, the authors measured anxiety before the intervention and 5 to 6 weeks after the consultation. They reported that men in the intervention group had significantly higher levels of anxiety prior to the intervention. After the intervention, there were no significant differences between groups (p value was not reported). Men in the intervention group had significantly lower levels of anxiety after the intervention (p < 0.005) compared to baseline; this finding was not seen in the control group.
The authors assessed depression with the Center for Epidemiologic Studies Depression Scale (CES-D). The authors reported that there were no significant differences between or within groups before and after the intervention (p value was not reported).
Davison and colleagues58 asked participants to evaluate the intervention. Four of the 30 participants did not tape their consultation. Of the 26 men who taped the consultation, 22 listened to the tape. The authors reported that 50 percent used the audiotape to review the information provided during the consultation and to share information with their family. In relation to the question list, the majority of men reported that it was helpful in formulating questions to ask their physicians. Several men asked the doctors to answer all of the questions on the list. Regarding the written material, 6 of 30 in the control group did not read the material compared to 3 of 30 in the intervention group. Twenty-two men ranked the three components of the intervention in order of usefulness: the audiotape was ranked as the most useful, the written information package second, and the question list third. Nevertheless, the majority stated that it was difficult to rank them, as all were important to have and one complemented the other.
In this sequential controlled trial study, two DA interventions designed to improve the quality of treatment decisions, the quality of communication, and the satisfaction of patients and physicians were tested in a group of early breast cancer patients. The authors assigned 12 women into one of the two interventions; both interventions consisted of the usual consultation with a surgeon or a medical oncologist and preconsultation planning. For 30 minutes, patients were prepared for the medical consultation by the researcher, who created a flowchart of patients' questions and concerns. Afterward during the consultation, the researcher performed a "consultation recording" in the intervention group; this five-step intervention (contracting, creating an agenda, mapping, commitments, and debriefing) was intended to help physicians and patients to facilitate their communication. In the control group, the researcher observed the consultation without participation.
To evaluate the intervention, the authors used the Decision Quality Scale, the MD Decision scale, and the University of California at San Francisco Satisfaction with Consultation Scale. The quality of the decision was measured before the intervention, after the consultation planning, and after the consultation. The authors reported the before- and after-the-consultation planning results as pooled data.
The scores increased after the consultation in both groups, and the intervention group achieved a significantly higher score in decision quality assessment than did the control group (p = 0.008).
The authors did not find any statistically significant differences between groups related to their satisfaction with the consultation (p = 0.073); however the authors reported that, since the intervention group scores were higher, these patients were more satisfied than the control group.
There were three case series that investigated the use of complex DAs.72,73,82 In a one-group pretest/posttest design, Stalmeier and colleagues72 explored the use of a DA designed to support women (n= 51), at high risk of carrying a breast cancer susceptibility gene in deciding between PM or BCS (semiannual clinical breast examination and annual mammography).72 The DA intervention consisted of individual counseling, a videotape, a DA brochure, and multiple utility assessments. The second study82 studied a series of 250 women with primary breast cancer and no evidence of metastatic disease and used a complex DA to assist in deciding between mastectomy and lumpectomy plus radiation therapy. The DA intervention consisted of individual counseling, a videotape, and a bottom-line sheet. The third study73 also used a pretest/posttest design to evaluate the use of a treatment tradeoff DA in patients with locally advanced non-small-cell lung cancer (n= 25) in deciding between combined-modality treatment and radiation therapy.
See previous section for a description of the study.
Of the 12 women identified as carriers of a breast cancer susceptibility gene, 8 chose to undergo PM, and 4 opted to have BSC. The authors also asked an additional 36 women who had used the DA, but whose genetic testing results were not yet available, to make a hypothetical decision assuming a positive carrier status. Under these conditions, 21 women said they would choose PM, 11 women would have BCS, 2 women could not decide, and 2 women did not answer. A hypothetical choice was not elicited from three women who found out during the study that they were noncarriers.
Knowledge was assessed by asking all of the women to rate their knowledge of both PM and BCS before and after the DA (10-point scales). Patients rated their knowledge of both PM and BCS significantly higher post-DA (p < 0.001 for PM; and p < 0.01 for BCS).
All 51 women who completed the intervention rated how much of a burden they felt the choice between PM and BCS was both pre- and post-DA (7-point scale). Decision burden was significantly lower post-DA (p < 0.01).
All 51 women were asked both before and after the DA intervention how certain they were about their choice (7-point scale). The authors reported that decision uncertainty was significantly lower post-DA (p < 0.05).
In this study, a complex DA was used to assist breast cancer patients in deciding between mastectomy and lumpectomy plus radiation therapy. The DA intervention consisted of individual counseling, a slide-tape presentation, and a bottom-line sheet.
Wolberg and colleagues82 reported that, of the 250 women given a choice, 128 decided on mastectomy and 122 opted for lumpectomy plus radiation therapy.
Wolberg and colleagues82 used the Profile of Mood States (POMS) to measure patients' moods pre- and post-DA. The authors reported that women who chose mastectomy were more anxious (p < 0.01) and felt more depressed (p<0.05) than those who selected lumpectomy with radiation.
When Wolberg and colleagues82 interviewed women 2 weeks after undergoing breast-cancer surgery, 20 of the 22 women said they had participated "as much as they desired" in making the treatment decision.
Wolberg and colleagues82 measured baseline psychosexual adjustment prior to patients' deciding between mastectomy and lumpectomy plus radiation therapy. Women who chose mastectomy reported significantly more predecision problems with sexual relationships than did women who elected to have lumpectomy with radiation therapy (p<0.05).
In the third case series study, a complex DA was used to assist patients with advanced non-small-cell lung cancer in deciding between combined-modality treatment (CMT) and radiation therapy only. The DA intervention consisted of the usual oncology consultation plus a structured individual interview using a display board and treatment-trade-off exercises, as well as a take-home DA information package.
Of the 18 patients who used the DA, 16 decided on CMT and 2 patients opted for radiation therapy only.
The authors also measured the patients' knowledge of the two treatment options before and after the DA in 13 of the 18 patients. They reported that the number of patients correctly answering questions about the direction and magnitude of survival benefit increased post-DA (raw data; no statistical analysis reported).
All of the lung cancer patients who used the DA to decide on treatment for advanced cancer either "strongly agreed" or "agreed" that the decision support was useful in making the decision. The authors also measured patients' treatment preferences before and after the DA. Three patients who reported no preference at baseline all chose CMT after the DA. In 5 patients, the DA increased the strength of their treatment preference and, in the remaining 10 patients, the DA did not alter the strength of their treatment preference. The 13 lung cancer patients who used the DA to decide on treatment for advanced cancer and who completed the followup questionnaire either "strongly agreed" or "agreed" that the decision support should be used with other patients.
The authors also measured decision uncertainty (a subscale of the Decision Conflict Scale) in 13 of 18 lung cancer patients both before and after DA. Post-DA, decision uncertainty decreased in 12 patients and increased in 1 patient.
The authors asked physicians to evaluate the decision support. In 12 of 13 cases, the physicians reported that the DA was useful in helping the patient understand the risks and benefits of each treatment. None of the physicians felt that the DA interfered with their relationship with the patient.
This chapter summarized 39 published studies that evaluated DAs to assist cancer patients to make prevention, screening, or treatment decisions. The majority of the studies involved decisions related to treatment rather than prevention or screening and focused on breast or prostate cancer. All studies were conducted with adult patients from developed countries. Most of the included patients were Caucasian with more than 12 years of education. The DAs that were evaluated varied from DA brochures and educational scripts to interactive computerized programs. Few studies directly compared different types or modes of DA delivery (i.e., DA brochure vs. interactive computer program). There were relatively few studies involving novel approaches such as computer-based applications.
Only 20 of the 39 evaluations used study designs involving a concurrent comparison group. Quality assessment scores across all the studies were low, but studies published in recent years achieved higher scores. Inadequate randomization, lack of blinding of outcome assessors, and lack of adequate followup were the most common methodological problems.
Few studies reported the development process of the DA. Of the 16 RCTs that evaluated the effectiveness of a DA in a clinical context with actual patients, only 3 studies reported the details of the developmental process. Two other studies reported that the DA had been pretested, but the results were not published.
We attempted to classify the models or frameworks of decisionmaking used in each study by independently assessing the information presented by the authors. Since our assessment often differed from the framework stated, we attribute this disparity to lack of available details in the published report and differences in definitions. The lack of consistency in frameworks might explain the variability in the selection of the primary outcome measures across studies. The outcome measures reported most frequently were the decision itself, knowledge (and recall), acceptability of the DA, satisfaction, anxiety, and depression. However, for many of the outcome measures, their psychometric properties (reliability and validity) were not reported, making it difficult to judge the impact of the DA.
If we consider the results of studies that included a concurrent comparison, some similarities emerged. For example, DAs appeared to increase knowledge (about the disease and the pros and cons of different options), did not increase anxiety, decreased decisional conflict or uncertainty, and increased satisfaction with the decision. In general, all DAs seemed to be acceptable to the users. Regarding decisionmaking, in some studies the DA clearly influenced peoples' decisions by changing their choice after the intervention or by helping them feel more comfortable with their choice. However, in other studies, the DA did not seem to influence decisionmaking.
Prostate cancer screening DAs seemed to help men (especially among older men) to choose not to have the PSA test. Studies about breast cancer treatment DAs showed that (younger) women chose breast conservation rather than radical surgery. Among women at risk of breast and ovarian cancer who faced genetic testing, the DA seemed to be more useful than was the standard genetic counseling.
For decisions about prevention or screening, DAs appear to be a useful addition to standard practice, but there is insufficient evidence to indicate which type of decision aid might be more effective. With respect to decisions involving treatment, at the present time there is insufficient evidence about the effectiveness of DAs.
Decision aids have been developed to improve communication between patients and health professionals, to help patients become involved in the decisionmaking process, and to incorporate their values in health care decisions. The area of cancer-related decisions has been found to be particularly problematic with respect to health professional/patient communication and decisionmaking for a number of reasons, including difficulties in sharing information about poor prognoses, the understandable anxiety connected with a life-threatening illness, and the modest benefits and severity of side effects associated with available treatments.
Recent reviews have suggested that decision aids may be effective in supporting general health care decisions. The objective of this systematic review was to determine the impact of decision aids for cancer prevention, screening, and treatment decisions. We identified specific criteria for study eligibility and performed an extensive search of the literature. We purposely used a broad definition of decision aids to be inclusive. While we identified 61 studies of cancer-related decision aids, our review was generally disappointing. The majority of the studies were case series. Only a minority (23) were comparative studies with a concurrent control group, including 18 RCTs. The state of research in this area is perhaps understandable given its relative newness, our still poor understanding of how patients and clinicians make decisions, the labor-intensive process of developing decision aids, and the difficulties (logistical, methodological, and ethical) in conducting research in this area. Even for the studies identified, interpretation was limited by a lack of adequate reporting, small sample sizes, and significant risk of bias and confounding. Interpretation was also hampered by the lack of any uniform widely accepted conceptual framework for decisionmaking between clinicians and patients. As a result, a number of different outcomes were evaluated inconsistently between studies.
In this summary section, we provide the best evidence available to support the questions posed. For the most part, information from the effectiveness randomized trials (n = 16) was used (Chapter Five). Where relevant, data from studies of other designs are included.
What conceptual framework for decisionmaking (e.g., informed, shared) underpin decision aids that have been used?
What has been the mode of delivery (e.g., print, interactive video)?
Sixty-one studies reported the development (22) or evaluation of a DA (39). We identified a number of different conceptual frameworks or models for the type of interaction and process of decisionmaking. Of the 61 studies, 22 referred to "shared" decisionmaking, 5 to an "informed" model, and 1 to an "empowerment" model, although there was often insufficient description of any of these processes. Over half the studies reviewed did not report any conceptual framework or model. The type of interaction described in some instances did not seem congruent with the model of interaction reported. This was felt to relate to a number of factors, including poor reporting and disagreement in definition. The lack of a widely accepted uniform conceptual framework for clinician-patient decisionmaking is seen as a potential barrier to progress in our understanding of how decision aids work and what are the important outcomes to measure. An extensive range of decision aids have been developed and evaluated for cancer patients. We identified over 10 different types of decision aids, including brochures, audiotapes, videotapes, interactive computer programs, educational scripts or sessions, decision boards, time tradeoff visual aids, counseling, and informal decision analysis. A number of studies reported using a combination of different instruments (e.g., workbook and audiotape or educational sessions and counseling).
What clinical contexts (e.g., prevention, screening, and treatment) have been investigated?
What has been the clinical focus of the decision aids (e.g., type of cancer and extent of disease)?
Of the 22 studies describing the development of a decision aid, there were 3 studies of prevention or screening and 19 of treatment. There were 14 studies involving breast cancer patients; 2 each of prostate, ovarian, and lung cancer; and 1 study each of colon cancer and leukemia.
Of the 39 studies evaluating a decision aid, the topics included all areas along the cancer care continuum. Instruments were evaluated for choices regarding genetic testing (2 studies), prevention versus increased surveillance (2 studies), screening (8 studies), and treatment (27 studies). The most common areas were primary surgical treatment and adjuvant therapy. Few instruments were developed for the treatment of metastatic disease. Instruments were applied to a limited number of disease sites. The most common were breast (23 studies) and prostate (11 studies).
What is the effectiveness of decision aids?
What is the effectiveness of decision aids in different clinical contexts?
What is the effectiveness of different modes of delivery?
Despite the many different instruments developed, few studies have been reported that critically evaluated the effectiveness of these instruments. Despite potential logistical difficulties, randomized studies remain the best study design with the least chance of bias to evaluate effectiveness. Sixteen randomized trials assessing effectiveness were identified. In total, there were 22 comparisons (three of the trials had three arms). Unfortunately, the quality of the randomized trials was poor, primarily because of incomplete reporting and small patient numbers.
An interesting contrast was seen. The minority of decision aids developed for prevention/screening decisions were represented more frequently in randomized studies, while the majority of decision aids developed for treatment decisions were rarely evaluated in randomized studies. This probably reflects the early stage of development of this field and the difficulty in performing these types of studies for cancer patients at the treatment decision point.
| Decision | Comparison | Patient Number | Treatment Chosen | Anxiety | Knowledge | Role in DM a | Satisfaction | Other | |
|---|---|---|---|---|---|---|---|---|---|
| Decision Aids vs. Usual Care (UC) (Screening/Prevention) | |||||||||
| Schapira, 2000 | Prostate Screening | DA brochure vs. UC | 257 | ND b | -- | ↑ | -- | -- | -- |
| Wolf, 1996 | Prostate Screening | Education script vs. UC | 205 | ↓ | --↓ | -- | -- | -- | -- |
| Volk, 1999 | Prostate Screening | Videotape vs. UC | 160 | ↓ | -- | ↑ | -- | -- | -- |
| Davison, 1999 | Prostate Screening | Counseling vs. UC | 100 | ND | ND | -- | ↑ | -- | ↓ Decisional conflict |
| Wolf, 2000 | Colorectal Screening | Education Script (relative risk reduction) vs. UC | 169 | ND | -- | ↑ | -- | -- | -- |
| Wolf, 2000 | Colorectal Screening | Education Script (absolute risk reduction) vs. UC | 166 | ND | -- | ↑ | -- | -- | -- |
| Pignone 2000 | Colorectal Screening | Videotape + DA brochure vs. UC | 249 | ↑ | -- | -- | -- | -- | -- |
| Watson, 1998 | Breast Cancer Prevention | Audiotape vs. UC | 115 | ND | ND | ND | -- | -- | -- |
| Lerman, 1997 | BRCA1 testing | Education session vs. Wait List Control | 278 | ND | -- | ↑ | -- | -- | -- |
| Lerman, 1997 | BRCA1 testing | Educational session + counseling vs. Wait List Control | 286 | ND | -- | ↑ | -- | -- | -- |
| Decision Aids vs. UC (Treatment) | |||||||||
| North, 1992 | Not stated | Audiotape vs. UC | 34 | -- | ↓ | ↑ | -- | -- | -- |
| Hack, 1999 | Not stated | Audiotape vs. UC | 24 | -- | NE c | NRD d | -- | NE | -- |
| Hack, 1999 | Not stated | Audiotape by choice vs. UC | 24 | -- | NE c | NRD d | -- | NE | -- |
| Maslin, 1998 | Breast cancer (surgery and adjuvant therapy) | Computer program vs. UC | 100 | NE | NE | NRD | -- | -- | Depression NE |
| Davison 1997 | Prostate cancer (primary treatment; options not reported) | Counseling + audio tape+ info pamphlet vs. UC + info pamphlet | 60 | -- | ND | -- | ↑ | -- | Depression ND |
| Decision Aids vs. Decision Aids | |||||||||
| Lerman, 1997 | BRCA1 testing | Educational session + counseling vs. Educational session | 236 | ND | -- | ↑ | -- | -- | -- |
| Street, 1995 | Breast Cancer Surgery | Computer program vs. DA brochure | 60 | ND | -- | ND | -- | -- | Optimism ND |
| Goel, 2000 | Breast Cancer Surgery | Audiotape workbook + values clarification vs. DA brochure | 136 | ND | ND | ND | -- | -- | Decisional Conflict ND |
| Wolf, 2000 | Colorectal Screening | Educational Script (relative) vs. Educational Script (absolute) | 166 | ND | -- | ND | -- | -- | -- |
| Irwin,1999 | Breast Cancer adjuvant treatment | Decision board vs. Decision board | 46 | ND | -- | -- | -- | -- | -- |
| Miron 2000) | Genetic Testing for women with breast or ovarian cancer | DA brochure (individualized) + vs. DA brochure + genetic counseling | 420 (at baseline) | ||||||
| Hack, 1999 | Not stated (treatment) | Audiotape vs. Audiotape by choice | 24 | -- | -- | NE e | -- | -- | -- |
Decisionmaking
ND= No difference
NE= Not extractable
NRD= No raw data
The authors reported that "patients who received the audiotape by choice recalled more thorough consultation...," however data were provided by type of cancer group rather than intervention group.
↓↑Decrease/increase
To answer the question of effectiveness, we first examined the 12 RCTs (15 comparisons) that compared a decision aid plus usual care versus usual care. Of the 15 comparisons identified, 10 were in prevention/screening and 5 were in treatment.
Studies in prevention/screening were generally larger studies (n = 100 to 286 patients). These included four studies evaluating decision aids for prostate screening methods, two studies of colon cancer screening methods, one study of preventive practices for women at high risk of breast cancer, and one study looking at a woman's wish to have BRCA1 testing. A variety of decision aids were evaluated, including a decision aid brochure, educational scripts, audiotapes, videotapes, counseling, educational session ± counseling. The treatment chosen was reported in all 10 comparisons. Three comparisons indicated that patients who used the decision aid were less likely to opt for screening practice (two for PSA screening and one for colon cancer screening). Knowledge was increased with the use of the decision aid in six of seven comparisons. Patient role in decisionmaking was reported in only one study. In this trial, patients who used the decision aid assumed a more active role. Anxiety was evaluated in only two studies; no increase in anxiety was demonstrated in these studies. Patient satisfaction was not reported in any of these studies. One study reported a decrease in decisional conflict.
These results support that decision aids are effective for cancer-related screening decisions, particularly for PSA screening, colorectal screening techniques, and BRCA testing. In all studies, decision aids improved knowledge about screening and, in a number of instances, affected the intention to be screened. Data regarding decision aids for cancer-related treatment decisions are very limited, and no definitive conclusions can be made.
What is the effectiveness of different modes of delivery?
The best way to compare different instruments is through a direct randomized comparison. However, in this review, it is difficult to compare different instruments in view of the limited number of studies. Eight studies involved a randomized comparison of different types of decision aids. In a number of the studies, there was a trend for knowledge to be improved with the more intensive decision aid, but in only one study did this reach statistical significance. Again, the majority of these studies may have been underpowered. No difference in treatment decisions were noted, but interesting trends were observed.64
A second less satisfactory way to compare different instruments is to compare their relative effectiveness in different studies. Again, in view of the limited number of studies and poor reporting, it was difficult to make even indirect comparisons. Our results demonstrate that a number of different instruments have been used and shown to be effective at least in terms of increased knowledge, including decision aid brochures, audiotapes, videotapes, and educational sessions ± counseling. None appear to be more effective than another.
On what populations has research been conducted?
We reviewed all 39 of the effectiveness studies. In seven studies, the eligibility criteria limited the sample to a certain age range. Five studies of prostate cancer screening and one of colorectal screening restricted their samples to middle or older age people (lower age limit varied from 45 to 50 years; upper limit from 70 years to no limit). One study investigated breast cancer treatment decisionmaking in women age 70 years or older. Only four studies reported information regarding income level. None of the studies targeted a particular SES class. However, in the prostate cancer screening study by Wolf and colleagues,54 more than 50 percent of the participants had annual incomes below $15,000 (U.S.). Of the 39 studies, 19 provided information about participants' level of education. The majority of participants in each of these 19 studies had at least a high school education, except for three studies. No study targeted a DA intervention for a specific education level. Ethnicity of participants was reported in eight studies. In all of these studies, the majority of participants were Caucasian, except for one study. This study was conducted in Hawaii, and approximately 50 percent of the participants were from an Asian ethnic group (Japanese, Chinese, Filipino, or Korean).
Are decision aids used by members of special populations (e.g., the elderly or minorities)?
What is the effectiveness of decision aids on special populations?
Of the 22 developmental studies, two specifically studied a DA for special populations. McTavish and colleagues39 assessed an interactive computer program, the CHESS, in eight African-American breast cancer patients from impoverished neighborhoods. As well, Lawrence and colleagues35 developed a DB to encourage the use of breast cancer screening among European-American and Mexican-American women in the United States. This was not a randomized trial, but the instrument appeared to be well accepted by the minority groups.
Few randomized studies have been performed in members of special populations. One study by Wolf and colleagues54 evaluated a DA for men at risk of prostate cancer by looking at options for prostate cancer screening. The investigators demonstrated that the instrument was effective for both younger and older men. Another study by the same author for the elderly deciding on colorectal cancer screening reported improvements in knowledge but no effect on the treatment chosen.
The evaluation of a number of decision aids also included patients with less than a high school education. However, we were unable to identify a decision aid targeted to patients with less than a high school education or that specifically reported results in this group of patients.
What outcomes have been evaluated?
Variability was observed both in the outcomes measured and the results observed. Different outcomes were reported in different studies, reflecting the different decisionmaking frameworks or lack of identified frameworks on which the decision aids were developed. For the effectiveness of randomized studies, the most common outcomes evaluated were knowledge and the treatment chosen (16 of 22 comparisons). Patients' role in decisionmaking was reported in only 2 out of 22 comparisons, and satisfaction with decisionmaking was reported only once. Patient anxiety was reported in 8 out of 22 comparison studies. Other outcomes such as decisional conflict (two comparisons) and depression (two comparisons) were reported.
Are there characteristics of decision aids related to key outcomes?
Characteristics and context of the decision aids varied substantially (in terms of type, qualitative versus quantitative, and amount of information presented). It is difficult to attribute impact on treatment chosen to any key characteristic. Few properly reported trials are available for decision aids related to cancer treatment decisions. Again, the framework for decisionmaking was so poorly described, it was impossible to make any comment on the impact this might have on effectiveness. Further work is necessary to determine the characteristics of decision aids related to different outcomes.
In essence, our review is limited by the newness of this field and early development with respect to cancer-related decision aids. We did identify increasing data supporting that decision aids are useful and effective for prevention or screening situations. Unfortunately, we found little data to support their effectiveness in the treatment situation.
Research in this area appears to be hampered by the lack of a widely accepted or used conceptual framework for clinician-patient decisionmaking. This is understandable given our rather "black box" understanding of clinician-patient interaction and processes in decisionmaking. As a result, it is difficult to identify quality decisionmaking and, following from this, the important outcomes to determine whether a decision aid is actually helping the process. A related problem is the lack of uniform, reliable, valid, and sensitive measures of outcome to evaluate decision aids. Investigators often use instruments that have not been psychometrically evaluated. Much more work is needed in this area to identify the important outcomes, to get agreement amongst investigators to develop psychometrically appropriate instruments, and to use them consistently.
Many investigators evaluated knowledge in recognition of the previous problems identified with communication between clinicians and patients and the primary importance of information in decisionmaking. In addition, most investigators evaluated the treatment chosen. However, other outcomes regarding the processes of decisionmaking, such as patient involvement in decisionmaking or satisfaction with the process, were inconsistently assessed.
The vagueness of understanding of decisionmaking also appears to have resulted in quite a number of different decision aids. These interventions vary not only in their mode of delivery (e.g., print or videotape), but also in their application. Some interventions may be used by the patient alone, before or after meeting with the clinician; by the clinician-patient dyad; by the clinician-patient-and-significant-other triad; and for single use only or for repeated use.
We attempted to categorize studies according to type of interaction (paternalistic, shared, or informed). This was unsuccessful, owing to a limited description of this feature in the studies evaluated; again underlining the lack of attention to conceptual models for decisionmaking.
More studies that investigate the actual interaction between cancer patients and clinicians when decisions are being made and determine from both parties important attributes of quality decisionmaking will help to better elucidate how treatment decisionmaking occurs, how we can help it, and the important outcomes to judge effectiveness.
Also noticeably missing from the literature was taking the development of a decision aid to its formal evaluation. Many different aids were developed, but few were evaluated in well-designed studies. Again, this may relate to the newness of the field. Formal evaluation of decision aids should not be underestimated. Concern has been raised about the slow adoption of available instruments into practice. Lack of knowledge about instruments and concerns about effectiveness and required resources are likely to remain barriers to the use of decision aids in practice. Instruments with proven efficacy that require limited resources are certainly more likely to be accepted into clinical practice.
Another important limitation of studies reviewed was the lack of clear reporting, including a description of the decisionmaking situation studied, the aid itself, allocation of the intervention, baseline characteristics of study groups, description of outcomes measured, and breakdown of outcomes by treatment group. Such reporting severely limits interpretation of study results and suggests that more rigor needs to be applied to the design and reporting of studies.
Our results support that decision aids are helpful for a number of cancer screening decisions. In these situations, instruments can increase knowledge, do not increase a person's anxiety, and can influence a person's decision. In contrast, there is very little data available evaluating decision aids for cancer-treatment-related decisions. Unfortunately, further evidence is still needed before making specific conclusions regarding decision aids in this situation.
In the last several years, five systematic reviews14,15,17-19 and one summary of decision aids, including one limited to cancer, have been performed.20 To date, three of the five systematic reviews have been published in peer-reviewed journals. O'Connor and colleagues14 comprehensively reviewed published and unpublished randomized trials of patient decision aids in various health conditions. Seventeen studies were identified. The review included six studies (five trials and one nonrandomized study) that were included in our review, including four studies in prevention/screening and two studies involving cancer treatment decisions. A meta-analysis was performed for some of the outcomes evaluated. Patient knowledge was reported in 8 out of 17 (47 percent) studies. Knowledge was statistically improved in four studies, and the meta-analysis supported that it was improved overall. Fourteen studies assessed the effect of decision aids on decisions made by the participants. Decisions were affected in only 3 out of the 14 studies. In a meta-analysis, a trend was observed that decision aids increased the likelihood for patients facing major surgery to prefer the less intensive option. Three studies reported that decision aids increased the proportion of patients assuming a more active role in decisionmaking. Four studies showed that decision aids did not affect patient anxiety, and the impact on patient satisfaction was variable. Our results complement the findings of this study and are consistent.
O'Connor and colleagues15 also published the results of a systematic review of decision aids that included both before/after studies and RCTs. While the focus of the review was cancer-related, the inclusion criteria did not limit to cancer-related decision aids due to the small number of studies assessing the efficacy of DA interventions. In total, 39 studies of DA interventions were identified, 19 of which were cancer-related. The results reported by O'Connor and colleagues are consistent with the findings of our review.
Molenaar and colleagues19 conducted a comprehensive review of decision aids that included all study designs (controlled and noncontrolled). The review included 30 studies, 18 of which were cancer-related (seven RCTs, two nonrandomized controlled trials, and nine one-group-only studies). Decision aids were found to be feasible, acceptable, and to increase patient knowledge of available options. Modest beneficial effects of DAs on decision uncertainty and satisfaction were reported. These results are consistent with the findings of our systematic review.
Our systematic review of cancer-related decision aids included 61 studies (22 development and 39 effectiveness). Of the 39 studies assessing the effectiveness of cancer-related DA interventions, there were 16 RCTs, 4 nonrandomized controlled trials, 2 nonconcurrent cohort studies, and 17 one-group-only studies.
Qualifications of our study should be noted. Abstracts and unpublished studies were not included in this review in view of the need to critically appraise each study. While such limitations may potentially result in some selection bias, this was not perceived to be a problem in view of the early development in this area and because a number of negative studies have been published.
In addition, the findings and conclusions of this Task Order are based on information that was available in the published reports and studies included. Additional information obtained directly from the authors could have overcome some of the reporting limitations described above. The contact with authors also could have led to a reduction in any likelihood of publication by bias through the identification of unpublished studies. The budget and timeline available, however, were insufficient to permit us to communicate with authors. The interpretability of the data included in most of the tables of the evidence report is limited because a number of different outcome measures were used, often with limited descriptions.
The strengths of our systematic review are that it was extensive and involved a critical appraisal of each included study. The review is limited to cancer-related health decisions because of the many reported problems and concerns with information exchange and decisionmaking in this stressful situation. Our results are consistent with systematic reviews performed in other health conditions; that is, at least for cancer screening decisions, these instruments can improve knowledge, do not increase anxiety, and may on occasion impact the final decision. Perhaps, like all good research, our review raises more questions than answers. Most of the initial questions we posed were not fully answered by the available literature, and further research is needed in this important area. It is hoped that this review will serve as an important background for researchers, health care providers, and consumers interested in resolving these questions and determining the appropriate role of decision aids in cancer control (see Chapter 7: Directions for Future Research).
The early stage of development of this field and the gaps in our knowledge outlined in this systematic review underline the need for further research. A number of different areas were identified. Future research efforts should consider:
Developing a better understanding of how decisionmaking happens in the real world. Who is involved-clinician, patient, or others? To what degree are they involved? When does decisionmaking happen-at the clinical encounter, before, or afterward?
Identifying the processes involved and when they occur. Presumably, information transfer is the first step, but what are the stages of deliberation and how do patients and clinicians interact at each stage? How do they ultimately make a decision?
Investigators need to determine the key features of quality decisionmaking from patients and clinicians. Such information will have a number of important benefits to help investigators develop instruments to facilitate quality decisionmaking and, perhaps most importantly, to identify and prioritize outcomes of effectiveness.
Determining patients' understanding of numerical estimates of risk. Is it meaningful for them? What is the impact of framing in real life decisions? Is there a substantial influence?
Much more work is needed to determine if decision aids are effective for cancer-related treatment decisions. Research in other disease sites besides breast and prostate cancer and in the metastatic setting is also necessary. The latter may be particularly challenging in terms of explicit discussion of benefits and risks of proposed treatments.
Future research should also focus on which components of a decision aid are necessary and effective. For example, besides exchanging information, is counseling helpful? How should it be instituted?
Are different types of decision aids more effective than others?
Is decisionmaking regarding cancer really different from decisionmaking in other chronic medical illnesses? In view of the life-threatening nature of this disease, are special approaches necessary here (e.g., psychosocial support techniques, patient support groups or teleconferences, use of repetition)?
What patient, clinician, or decisionmaking factors affect the effectiveness of decision aids? Are decision aids more or less useful in particular situations (i.e., do decision aids facilitate communication for less interactive clinicians)? Or, visa versa, do decision aids impede communication in a more interactive clinician-patient relationship? Are there particular groups of patients who benefit from decision aids? Who are they (e.g., patients having difficulty making a decision)? Can they be identified a priori?
Are decision aids useful for members of special populations (e.g., the elderly, ethnic groups, or people with low levels of education)? Should decision aids be modified for these populations, and how should this be done?
In addition to focusing on these areas, our future research efforts should consider:
Multicenter collaboration to formally set a research agenda. From our review, there appeared to be poor integration of different research efforts in the field. National or international collaboration would permit development of consensus about important basic concepts regarding decisionmaking, what a decision aid is, and important outcomes.
Development of an accepted conceptual framework for decisionmaking, standardized definitions of a decision aid, and a core set of outcomes. These would have important benefits for patients, clinicians, and policymakers. Outcomes should be important to all parties and could include knowledge, patient and clinician satisfaction or comfort with decisionmaking, patient and clinician involvement in decisionmaking, resources utilized both for the decisionmaking and the decision, and the treatment chosen.
With respect to evaluation, larger studies with more rigorous design, more comprehensive reports, and longer-term followup are needed to clearly establish the effectiveness and adverse effects (if any) of decision aids, especially for cancer-related treatment decisions. Ideal studies would include evaluation of decision aids developed based on sound principles compared to usual practice with random allocation of intervention. Cluster randomization may be necessary to avoid contamination. Appropriate outcomes should be assessed using sensitive instruments soon after administration of the intervention and with long followup to determine any latent effects. Studies should be powered large enough to detect important differences and to look at factors predictive of effect. Multicentered collaboration is likely to facilitate this process and may have additional benefits in terms of increasing opportunities for dissemination of research results.
Institution of collaborative efforts, such as workshops; development of practice guidelines by policymakers, clinicians, and patients; and other methods to improve dissemination and implementation of decision aids.
Increased involvement of consumer groups in helping to set the agenda, advocate for funding, facilitate the development of research studies, and disseminate research results.
Procurement of funding from government and industry to support research.
In summary, the study of cancer-related decision aids will respond to the needs of clinicians and patients to improve communication and involve patients more in decisions about their care. This is a vital area of research that has important implications for the well being of patients and their families, and also for society as a whole in terms of appropriate utilization of medical therapies. This is a new and growing area of research. Some work has been done, as reported in this review, and some is ongoing. Much more is needed.
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Development of Decision Aids
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT Design
Studies of Effectiveness of Decision Aids: RCT Design
Studies of Effectiveness of Decision Aids: RCT Design
Studies of Effectiveness of Decision Aids: RCT Design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: Nonrandomized controlled trial design
Studies of Effectiveness of Decision Aids: Nonrandomized controlled trial design
Studies of Effectiveness of Decision Aids: Nonrandomized controlled trial design
Studies of Effectiveness of Decision Aids: Nonrandomized controlled trial design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: Nonrandomized controlled trial
Studies of Effectiveness of Decision Aids: Nonrandomized controlled trial
Studies of Effectiveness of Decision Aids for Treatment: Case series design
Studies of Effectiveness of Decision Aids for Treatment: Case series design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: RCT design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids: Case series design
Studies of Effectiveness of Decision Aids for Treatment: RCT design
Studies of Effectiveness of Decision Aids for Treatment: RCT design
Studies of Effectiveness of Decision Aids: Nonconcurrent cohort design
Studies of Effectiveness of Decision Aids: Nonconcurrent cohort design
Studies of Effectiveness of Decision Aids. Nonconcurrent cohort design
Studies of Effectiveness of Decision Aids. Nonconcurrent cohort design
Studies of Effectiveness of Decision Aids. Case series design
Studies of Effectiveness of Decision Aids. Case series design
Studies of Effectiveness of Decision Aids. RCT design
Studies of Effectiveness of Decision Aids. RCT design
Studies of Effectiveness of Decision Aids. RCT design
Studies of Effectiveness of Decision Aids. RCT design
Studies of Effectiveness of Decision Aids. Nonrandomized controlled trial
Studies of Effectiveness of Decision Aids. Nonrandomized controlled trial
Studies of Effectiveness of Decision Aids. Case series design
Studies of Effectiveness of Decision Aids. Case series design
Studies of Effectiveness of Decision Aids. Case series design
Studies of Effectiveness of Decision Aids. Case series design
Studies of Effectiveness of Decision Aids. Case series design
Studies of Effectiveness of Decision Aids. Case series design
Timothy J. Whelan, BM, BCh, MSc (Task Order Leader): Dr. Whelan is an Associate Professor, Department of Medicine, and Associate Member, Department of Clinical Epidemiology & Biostatistics (CE&B), at McMaster University. He is currently Director of the Supportive Cancer Care Research Unit (SCCR) at McMaster University, which is a health system-linked research unit focusing on supportive care needs of cancer patients. He is a practicing radiation oncologist at the Hamilton Regional Cancer Centre and is co-Chair of the Breast Disease Site Group for the National Cancer Institute of Canada, Clinical Trials Group. Dr. Whelan obtained his medical degrees at University of Oxford Medical School and was a recipient of the Rhodes Scholarship and Terry Fox Fellowship for Physician Scientists. Since obtaining his Master's in CE&B, he has been actively involved in research focusing on health services research and clinical trials related to the management of breast cancer. One of his main areas of interest is information exchange and physician-patient decisionmaking. He is currently principal investigator on several projects evaluating the use of treatment decision aids for women with breast cancer.
Mary Ann O'Brien, MSc, BHSc (PT), (Task Order Coordinator): Ms. O'Brien is an Assistant Clinical Professor in the School of Rehabilitation Sciences at McMaster University. She was the Task Order Coordinator for the Management of Chronic Central Neuropathic Pain Following Traumatic Spinal Cord Injury Task Order. Ms. O'Brien has graduate training in the science of conducting systematic reviews and is a licensed physical therapist with extensive clinical experience in rehabilitation. She is a member of the Board of Examiners for the Canadian Physical Therapy Examination. She is also a member of the Cochrane Collaboration Effective Professional Practice and Organization of Care Review Group. Ms. O'Brien has extensive experience in coordinating the production of systematic reviews. Recently, she coordinated the production of 13 systematic reviews of public health interventions for the Ontario government. In addition, she is the author or co-author of 10 systematic reviews in the areas of health professional behavior change, public health, and rehabilitation. She is responsible for the overall coordination of the Task Order, supervision of other research staff, and drafting of the Evidence Report and associated manuscripts.
Cathy Charles, PhD: Dr. Charles is an Associate Professor in the Department of Clinical Epidemiology & Biostatistics; a Member of the Centre for Health Economics & Policy Analysis; and an Associate Member, Department of Sociology at McMaster University. She is also an Investigator in the Supportive Cancer Care Research Unit, which is cosponsored by the Hamilton Regional Cancer Centre and McMaster University. She is an Honorary Research Associate in the Department of Behavioural Sciences, University of Sydney, Sydney, Australia. She received a B.A. and M.A. in Sociology at the University of Toronto and an M.Phil. and Ph.D. in Sociomedical Sciences from Columbia University. Her research interests include: public and patient participation in health care decisionmaking, the use of research information to improve the organization and delivery of health care, the health professions and public policy, and resident classification systems for long-term care. She is currently undertaking a collaborative study, funded by the Canadian Breast Cancer Research Initiative, on shared treatment decisionmaking among women with early stage breast cancer and among physicians who specialize in this area. Dr. Charles has been a health policy consultant to several provincial governments as well as to the federal government.
Amiram Gafni, DSc: Dr. Gafni is a Professor in the Department of CE&B, a member of the Centre for Health Economics and Policy Analysis and the Supportive Cancer Care Research Unit. His research interests are in the areas of economic evaluation of health care programs (both methods development and empirical applications), modeling of consumers' and providers' health care behavior, policy analysis, and risk and decision analysis in health. Dr. Gafni is heavily involved in research in the areas of decision aids and the physician-patient encounter. He is one of the developers of the decision board (DB) approach (i.e., a method for helping patients to reveal their preferences regarding treatment). The method was first applied for the case of adjuvant chemotherapy for early stage breast cancer and since then has been used in several cancer applications. In addition, Dr. Gafni is involved in both conceptual and empirical research regarding the physician-patient encounter. This research has resulted in the first conceptual definition of the shared treatment decisionmaking model as well as a comprehensive conceptual framework to describe all potential types of encounters and their components. He has also published extensively on these topics.
Mark Levine, MD: Dr. Levine is the Director of the new Clinical Research Institute recently established by the Faculty of Health Sciences, McMaster University. He is a Professor of Medicine and Clinical Epidemiology & Biostatistics at McMaster University. He served as CEO of the Cancer Care Ontario Hamilton Regional Cancer Centre between 1992 and 1999. Since 1982, Dr. Levine has been on staff at the Hamilton Regional Cancer Centre and a member of the Faculty of Health Sciences at McMaster University. He received an MD degree from McGill University followed by a Master's degree in health research methods from McMaster University. Dr. Levine completed his residency in internal medicine at McMaster University and his hematology and oncology training at Duke University Medical Centre. He has been an investigator in breast cancer clinical trials and venous thromboembolism clinical trials and has conducted research in quality-of-life issues and treatment decisions in breast cancer. Dr. Levine is on the Steering Committee of the Ontario Practice Guidelines Initiative and chairs the Steering Committee on Clinical Practice Guidelines for Breast Cancer in Canada. He received the 1999 O. Harold Warwick Prize from the National Cancer Institute of Canada in recognition of research excellence in cancer control within the past decade. He was recently appointed as the first recipient of the Buffett Taylor Chair in Breast Cancer Research at McMaster University.
Andy Willan, PhD: Dr. Willan is a statistician and clinical trial methodologist with a wide variety of interests including oncology, ophthalmology, urology, obstetrics, antiemetics, and cardiology. He has held the posts of head of Biometry of the Clinical Trials Programme at the National Cancer Institute of Canada and Head of Clinical Trials and Epidemiology for the Cancer Programme at Sunnybrook Medical Centre. His contributions to statistical methodology include publications in the areas of health economics, management trials, crossover trials, non-nested regression analysis, bivariate response models and meta-analysis. Dr. Willan currently serves on the steering committee for a number of large multicentre clinical trials in obstetrics and is on the data monitoring and safety committee for the National Cancer Institute of Canada Clinical Trials Programme. He also serves on review panels for the National Cancer Institute of Canada and the Medical Research Council of Canada. Dr. Willan plays an active role in the graduate program in Health Research Methodology in the Department of Clinical Epidemiology and Biostatistics.
Melissa Brouwers, PhD: Dr. Brouwers is an Assistant Professor in the Department of Clinical Epidemiology & Biostatistics and an Assistant Director of the Cancer Care Ontario Program in Evidence-based Care, for which she manages a provincially funded program dedicated to bridging the gap between quality cancer care research and current clinical care options with the most up-to-date evidence-based information for patients, families, and health care providers. Her responsibilities include creating and implementing strategic and operational plans, developing a research agenda, coordinating projects, facilitating and maintaining relationships with Program partners, supervising and training Program staff, and administering the Program budget. She is involved with the Cancer Care Ontario Program in Evidence-Based Care Practice Guidelines Coordinating Committee, Disease Site Chairs Committee, and the Methods Work Group. Dr. Brouwers earned a Ph.D. from the University of Western Ontario, London, Ontario, Department of Psychology. Her areas of interest include: program design and evaluation, attitudes and behavior change, research design and measurement, personality styles and cross cultural variations, stress, coping and health, health psychology, social psychology, and abnormal psychology. She has coordinated two federally funded initiatives dedicated to developing evidence-based information tools and to disseminating health care information to various health care consumers, including clients/patients, health care providers, researchers, and policymakers/government.
Anne Snider, MEd, (EPC Coordinator): Ms. Snider, as EPC Coordinator, is responsible for overall coordination of the Task Order. Her responsibilities include staffing; monthly reporting to the AHRQ Contracts Office; financial management; liaison internally at McMaster University with administrative and financial bodies; liaison with external bodies, including technical experts and the AHRQ; and review and editing of the Evidence Report.
Miguel Villasis-Keever, MD, MSc: Dr. Villasis-Keever is a Pediatrician and Clinical Researcher at the Pediatric Hospital of the Mexican Social Security Institute. He received an MD degree from the University of San Luis Potosi, Mexico, followed by a Master's degree in Medical Sciences from the Universidad Nacional Autonoma de Mexico. In June 2000, he started a Fellowship Research year on Systematic Reviews at McMaster University. He has been involved in all the stages of this systematic review.
Paula Robinson, MD, MSc: Dr. Robinson obtained both her medical degree and her Masters of Science (Biology) degree from McMaster University. She has been involved in the screening process, data extraction, and writing of the evidence report.
Aimee Skye, BA, PhD Student in Cognitive Psychology: Ms. Skye graduated from McMaster University in 2000 with a Bachelor's degree in Honors Psychology. She is currently pursuing her Ph.D. in Cognitive Psychology at McMaster University. Aimee's primary area of research concerns the psychology of judgment, reasoning, and decisionmaking, with particular focus on the domains of health and medicine.
Christopher Sigouin, Biostatistician, PhD student: Mr. Sigouin is a Ph.D. student, Health Research Methodology Programme, Faculty of Health Science, McMaster University. He is responsible for database design, data integrity, and data analysis.
Mary Gauld, BA: Ms. Gauld is a Research Coordinator in the Department of Clinical Epidemiology and Biostatistics, McMaster University. She has participated in numerous systematic reviews, including the AHRQ Task Order on the Treatment of Attention-Deficit/ Hyperactivity Disorder.
Fulvia Baldassarre, MSc, BScN: Ms. Baldassarre completed a Bachelor in Nursing at the University of Chieti (Italy) and graduated in June 2000 from McMaster University with a Masters of Science (Nursing) degree. She is a Research Assistant/Coordinator in the Department of Clinical Epidemiology and Biostatistics, McMaster University.
Laura Siminoff, PhD: Dr. Laura Siminoff is an Associate Professor of Internal Medicine and Health Care Research at the Case Western Reserve University School of Medicine and Associate Director of the Behavioral Cancer Control Program at the Ireland Cancer Center, University Hospitals, Cleveland, Ohio. She is also a member of the National Breast Cancer Coalition Action Plan. Dr. Siminoff received her training in public health at the Johns Hopkins University where she completed her Ph.D. She is also a trained anthropologist. Dr. Siminoff has written widely about how breast cancer patients make treatment decisions about adjuvant therapy. She is interested in how to promote informed treatment decisionmaking and patient participation in treatment decisions. Dr. Siminoff has conducted studies examining the treatment decisionmaking process of breast cancer patients and oncologists, how physicians recruit breast cancer patients into clinical trials, and is currently conducting an NCI-funded clinical trial of a decision aid designed to promote joint decisionmaking about adjuvant therapy between stage I-III breast cancer patients and their medical oncologists.
Vikki Entwistle, PhD: Dr. Entwistle is a senior research fellow at the Health Services Research Unit, University of Aberdeen, Scotland. Her research interests include: the development and assessment of consumer health information materials, the measurement and evaluation of participation in clinical decisionmaking, consumer involvement in health care, and media coverage of health and medical issues. Vikki serves on the editorial teams of Health Expectations, an international journal of public participation in health care, and of the Cochrane group on Consumers and Communication.
Carol Sawka, MD: Dr. Sawka is a medical oncologist, CEO of the Toronto-Sunnybrook Regional Cancer Centre and the Cancer Care Ontario Central East Region, and an Associate Professor, Departments of Medicine and Public Health Science at the University of Toronto. She is an Adjunct Senior Scientist at the Institute for Clinical Evaluative Sciences in Ontario, where she has been conducting breast cancer-related health services research. Her research is aimed at improving breast cancer quality of care and outcomes through information provision, shared decisionmaking, and the use of practice guidelines to promote consistent patterns of care. She developed and evaluated a patient decision aid for breast cancer surgery and has conducted a population-based study that evaluated the role of provincewide guidelines in consistency of breast cancer care.
Martin Tattersall, MD, PhD: Dr. Tattersall is a Professor in the Department of Cancer Medicine, University of Sydney, and a cancer physician at the Royal Prince Alfred Hospital in Sydney, Australia. He is a member of the Editorial Board for the journal Cancer Strategy. Regarded as an international clinical cancer expert, Professor Tattersall is Chair of Australia's peak advisory body on drug evaluation, the Australian Drug Evaluation Committee (ADEC). He also has worked on World Health Organization and National Health and Medical Research Council working parties on cancer.
| 1 | exp decision making/ |
| 2 | decision support techniques/ |
| 3 | patient education/ |
| 4 | patient participation/ |
| 5 | exp professional-patient relations/ |
| 6 | 1 or 2 or 3 or 4 or 5 |
| 7 | exp neoplasms/ |
| 8 | 6 and 7 |
| 9 | limit 8 to human |
| 10 | limit 9 to yr=1977-2000 |
| 11 | exp biopsy/ |
| 12 | exp sunscreening agents/ |
| 13 | exp mammography/ |
| 14 | exp tamoxifen/ |
| 15 | tamoxifen.tw. |
| 16 | exp vaginal smears/ |
| 17 | brca1.tw. |
| 18 | brca2.tw. |
| 19 | exp occult blood/ |
| 20 | exp hormone replacement therapy/ |
| 21 | exp prostate-specific antigen/ |
| 22 | 11 or 12 or 13 or 14 or 15 or 16 or 17 or 18 or 19 or 20 or 21 |
| 23 | 22 and 6 |
| 24 | 23 not 8 |
| 25 | limit 24 to human |
| 26 | limit 25 to yr=1977-2000 |
| 27 | 10 or 26 |
| 28 | exp colonoscopy/ |
| 29 | exp bronchoscopy/ |
| 30 | exp sigmoidoscopy/ |
| 31 | exp colposcopy/ |
| 32 | exp conization/ |
| 33 | 28 or 29 or 30 or 31 or 32 |
| 33 | 33 and 6 |
| 34 | 34 not 8 |
| 35 | limit 35 to human |
| 36 | limit 36 to yr=1977-2000 |
| 37 | 27 or 37 |
| 38 | 38 not letter.pt. |
| 40 | 39 not editorial.pt. |
| 41 | 40 not news.pt. |
This search strategy has been slightly modified for the databases different from Medline, according to different indexing of the articles.
| DEFINITION OF A DECISION AID |
|---|
An intervention designed primarily to help patients or patients and clinicians together, with making cancer-related health care decisions when options are available for prevention, screening, and treatment. At a minimum, it should target some component of decision-making (e.g., information exchange, involvement in the decision process).
The following interventions will be excluded:
|
It must be a report of an experiment or investigation of an intervention, or validation of an outcome tool related to an explicit decision-making process.
It must not be a position paper or any type of review.
Tools/Interventions to assist decision-making must have the following characteristics:
Must explicitly present more than one option (of which one can be take no action or maintain status quo).
Must not advocate/advise a particular course of action or present information in a manner biased towards one or another option.
Must target some phase of the decision making process (i.e. structuring the patient-physician encounter, information elicitation or transfer, deliberation, etc.) and occur prior to the actual decision.
Interventions designed to counsel patients to communicate with clinicians will be treated as uncertain and will be retrieved.
Interventions designed to counsel clinicians only will be excluded.
Must be cancer-related, which means the intervention or decision must primarily target the prevention, detection, treatment or management of cancer, unless the article is regarding the development or validation of a decision aid.
Outcome measures must be instruments that would be used to assess decision-making or to evaluate decision-making interventions. For example, a study validating the "Decisional Conflict Scale" would be retrieved because this scale is used to evaluate some decision aid interventions.
Such studies may not be specifically cancer related.
We will retrieve any article for background that meets the following criteria:
| 1) Any review dated 1990 or more current OR |
| 2) Any seminal paper dated 1990 or more current |
| AND |
| If and only if it is clearly cancer related |
| AND |
If and only if it focuses on one of the following topics:
|
| 3) Any literature dated 1995 or more current that investigates or describes the decision-related needs of patient populations, including special patient populations (e.g., children, ethnic minorities, low SES groups, clinical trial participants). We will NOT retrieve general interviews/surveys investigating patients' perceptions or experiences unless they are explicitly related to a decision or the creation of a tool. ALSO, any abstracts or collection thereof from presentations given at cancer meetings or from any meetings relevant to cancer-related decision aids (where relevance can not be established from a title or abstract) will be retrieved if dated 1998 or more current. |
GENERAL NOTES
|
| DEFINITION OF A DECISION AID |
|---|
An intervention designed primarily to help patients or patients and clinicians together, with making cancer-related health care decisions when options are available for prevention, screening, and treatment. At a minimum, it should target some component of decision-making (e.g., information exchange, involvement in the decision process).
The following interventions will be excluded:
|
Primary Study
Must be a report on an experiment or investigation of an intervention, or an outcome measure related to an explicit decision-making process.
It must not be a position paper or any type of review.
Focus of Study
Wherever possible, broad cancer groupings such as "Head & Neck" or "Abdominal" should be delineated into the more specific groups identified on the screening form.
Hodgkin's Disease will be coded as lymphoma.
Uterine and endometrial cancers will be coded as Corpus Uteri.
Skin cancers that are NOT melanoma will be coded as Other & Specify Type.
Decision Aids surrounding genetic screening will be coded as screening decisions.
Part I and Part II MUST be completed in all cases.
Not Specified will be used for articles where the decision is of a general nature and is applicable to 3 or more specific focal diseases (e.g. a decision to take antioxidants or not in the prevention of several types of cancer).
For focal disease, the screener must specify a description when coding "Other" (maximum readable 30 characters).
Type of Study
Tools/Interventions to assist decision making must have the following characteristics:
Must explicitly present more than one option (of which one can be take no action or maintain status quo).
Must not advocate/advise a particular course of action or present information in a manner biased towards one or another option.
Must target some phase of the decision making process (i.e. structuring the patient-physician encounter, information elicitation or transfer, deliberation, etc.) and occur prior to the actual decision.
Outcome measures must be instruments that would be used to assess decision-making or to evaluate decision-making interventions. For example, a study validating the "Decisional Conflict Scale" would be retrieved because this scale is used to evaluate some decision aid interventions.
Interventions or decisions not primarily targeting some aspect of cancer care will be excluded, unless the study describes the development or validation of a decision aid or an outcome measure.
We will exclude interventions or decisions surrounding the management of Benign Prostatic Hyperplasia (BPH).
We will exclude interventions or decisions surrounding Hormone Replacement Therapy unless the sample has cancer presently / had it in the past / or is at HIGH risk for developing it.
Interventions (educational, behavioral, etc) regarding smoking cessation will be excluded, unless the sample has cancer presently/had it in the past/or have additional risk factors for developing it.
The option of "informed consent intervention" should be used to exclude studies only when the intervention is labeled as an informed consent in the article.
Exclusion Codes for Educational Interventions (code all that apply)
| 1.............. | Intervention does not require a specific decision at some point after the intervention |
| 2.............. | Intervention describes only ONE option |
| 3.............. | Intervention advocates a particular course of action; e.g., screening (mammography, PSA, etc.), or prevention (smoking cessation, etc.). |
| 4.............. | Intervention occurs post-decision |
| 5.............. | Intervention is designed to counsel patients about how to communicate with clinicians |
| 6.............. | Other (Specify -maximum readable 10 characters) |
Purpose of the Study
Development of a decision aid
Includes pilot testing of a decision aid/intervention or a part thereof.
Evaluating the intervention
Includes evaluating the intervention with respect to outcome measures or user experience.
Validation of intervention or outcome measure
Includes reliability and validity testing of a decision aid intervention or an outcome measure.
Mathematical Models
Articles about mathematical models and techniques (e.g., utility analysis, probability trade-off techniques) will be excluded if the purpose is general modeling of the decision making process. They will be included if and only if they are applied within the context of an intervention to assist the patient or patient & clinician in making a specific, cancer-related decision.
Characteristics of Sample
Focal Disease is the type of cancer around which the preventative, screening or treatment decision is structured. The level of specificity may vary with each article (e.g., lung cancer or non-small-cell lung cancer). Alternatively, this includes any illness secondary to a) the focal cancer or b) any treatment or screening procedures targeting the focal cancer (e.g. pneumonia secondary to chemotherapy).
Related Non-Focal Disease is a type of cancer which is different from the focal disease.
At Risk Patients - the article should state that the sample studied was at risk for the focal disease.
Any sample of women greater than 40 years will be coded as at risk (regardless of whether stated in the article) when the article is about mammography.
Any sample of men greater than 50 years will be coded as at risk (regardless of whether stated in the article) when the article is about PSA screening.
Any sample of women who are either sexually active or greater than 17 years of age will be coded as at risk when the article is about cervical smear screening.
Any sample of men or women greater than or equal to 50 years of age will be coded as at risk (regardless of whether stated in the article) when the article is about colon cancer screening.
Design of Primary Study (see algorithm attached)
Randomized controlled trial - An epidemiological experiment in which subjects in a population are randomly allocated into groups, usually called study and control groups, to receive or not to receive an experimental preventative or therapeutic procedure, maneuver, or intervention.
Controlled trial (quasi-randomized) - Quasi-Experiment: a situation in which the investigator lacks full control over the allocation and/or timing of the intervention but nonetheless conducts the study as if it were an experiment, allocating subjects to groups. These types of studies must have some form of comparison/reference group.
Controlled before-after designs - Two or more groups of patients or subjects receiving a procedure, maneuver, or intervention; or a control intervention or non-intervention, with outcomes measured at baseline and post-intervention. Allocation to intervention in control groups is not under the control of the investigator.
Case-control - A retrospective study of persons with the disease (or other characteristic of interest), and a suitably matched control (comparison, reference) group of other persons without the disease.
Pre-post intervention - Single group of patients or subjects who receive the same experimental procedure, maneuver, or intervention, with outcomes measured at baseline and post-intervention.
Survey - An investigation in which information is systematically collected (e.g. face-to-face inquiry, by self-completed questionnaires, by telephone, postal service), at one point in time.
Qualitative study - Researchers look for the social context and point of view of the units (subjects, patients). The approach is primarily inductive, and concern is related to discovery and description. Usually the analysis is presented in narrative rather than numeric form.
Case series - Description of a group of subjects that have something in common. These people had received the intervention and the researchers gathered information related to their outcomes.
Case study - A paper that contains the description of one subject or patient related to some condition in particular.
Other - For studies that are not any of the above designs, the screener should code "Other" and specify a description (maximum 30 readable characters).
Hypothetical Decisions
Any situation where the patient is being asked to make an authentic decision which is necessary given their current medical condition is NOT hypothetical.
Situations where the sample is not asked to make a decision during the study period or where the authors use a Background Papers proxy/surrogate outcome measure for the decision (e.g., degree of interest in a screening test) are not necessarily hypothetical. If there is any doubt, the reviewer should code as uncertain and then discuss the issue with the second reviewer when meeting for consensus.
For any article where the focus is about clinical trial entry (real or hypothetical), and the intervention does not clearly fit our criteria for a decision aid; the status should be coded as uncertain.
Codes for decisions that ARE hypothetical:
| 01..........The options considered in the decision are not medically available or real. 02..........The sample is not a member of the target population for the decision. 03..........Both 01 and 02. 04..........Decision is hypothetical only for a portion or subgroups of the total sample. |
Any articles that will be kept as a background paper should be classified according to the following codes, and the screener should check all codes that apply:
Any review (narrative or systematic) dated 1990 or more current, which focuses on:
Decisions aids/interventions
Patients/patients-physicians decision making
Information transfer (patient ← → clinician)
Clinician-patient communication
Decision-related needs of patient populations
Any seminal paper dated (preferably dated 1990 or more current) which focuses on:
Decisions aids/interventions
Patients/patients-physicians decision making
Information transfer (patient ← → clinician)
Clinician-patient communication
Decision-related needs of patient populations
Any literature dated 1995 or more current that investigates or describes the decision-related needs of patient populations, including special patient populations (e.g., children, ethnic minorities, low SES groups, clinical trial participants). We will NOT retrieve general interviews/surveys investigating patients' perceptions or experiences unless they are explicitly related to a decision or the creation of a tool. ALSO, any abstracts or collection thereof from presentations given at cancer meetings or from any meetings relevant to cancer-related decision aids (where relevance can not be established from a title or abstract) will be retrieved if dated 1998 or more current.
Guidelines
Consensus Conference Report
Contains Definitions
Other (Specify - maximum 10 readable characters )
Remember to check the final STATUS box at the top of the page.
If 'Include' AT CONSENSUS, please highlight the reference list for appropriate citations and submit them fr the article retrieval process***Appropriate References to be retrieved must explicitly have the following in the title:
patient OR preferences OR any cancer consumer AND decision making ORAND hit word involvement OR participation OR other decision term
Patricia Huston, MD, MPH. Scientific Communications International, Inc. Ottawa, Ontario, Canada
Angela Coulter, PhD. Chief Executive, Picker Institute Europe, King's Mead House Oxpens Road, United Kingdom
Hanneke de Haes. Department of Medical Psychology, Academic Medical Center, Amsterdam, The Netherlands
Baruch Fischhoff. Department of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania
Neil A. Hagen MD, FRCPC. Tom Baker Cancer Center, Calgary, Canada
Val Lawrence, MD. Ambulatory Care, Audie Murphy VA Hospital, San Antonio, Texas
Jeffrey C. Lerner, PhD. Vice President for Strategic Planning Center Director, AHRQ Evidence-based Practice Center ECRI, a nonprofit agency, Plymouth Meeting, Pittsburgh, Pennsylvania
Arabella Melville, PhD. Bryn Derwen, Cymru/Wales, United Kingdom
Sjaak Molenaar, MA. Department of Medical Psychology, Academic Medical Center, Amsterdam, The Netherlands
Nora Moumjid, GRESAC, Centre L?on B?rard, Lyon, France
Annette O'Connor RN, PhD. Professor, University of Ottawa School of Nursing and Faculty of Medicine, Acting Director, Clinical Epidemiology Unit Loeb Health Research Institute at the Ottawa Hospital, Ottawa, Ontario, Canada
Debra Roter, PhD. Professor and Associate Chair, Department of Health Policy and Management, Johns Hopkins School of Public Health, Baltimore, Maryland
Trevor A Sheldon, Head of Department of Health Studies, University of York Innovation Center, York, United Kingdom
Amanda J. Sowden, Associate Director, NHS Center for Reviews and Dissemination, University of York, York, United Kingdom
Hazel Thornton, Rowhedge, Colchester, United Kingdom
Steven Woloshin, MD, MS, and Lisa Schwartz, VA Outcomes Group, VA Medical Center White River Junction, Vermont
Quality Assessment of Effectiveness RCT Studies with the Validity Component of the Guyatt et al. Scale
| Assignment randomized | Patients entered the trial accounted for at its conclusion | Followup completed | Patients analyzed in the group they were randomized | Patients, health workers, and study personnel blinded to treatment assignment | Groups similar at baseline | Groups treated equally | FINAL SCORE | |
|---|---|---|---|---|---|---|---|---|
| Volk, 1999 | Y | Y | Y | Y | N | Y | Y | 6 |
| Lerman, 1997 | Y | NR | NR | Y | N | Y | Y | 4 |
| Davison, 1997 | Y | Y | NR | Y | N | Y | Y | 5 |
| Davison, 1999 | Y | Y | NR | Y | N | Y | Y | 5 |
| Hack, 1999 | Y | NR | NR | N | N | NR | Y | 2 |
| Watson, 1998 | Y | NR | NR | N | N | NR | Y | 2 |
| Wolf, 1996 | Y | NR | NR | Y | N | Y | Y | 4 |
| Irwin, 1999 | Y | NR | NR | N | N | NR | Y | 2 |
| Street, 1995 | Y | NR | NR | Y | N | Y | Y | 4 |
| Maslin, 1998 | Y | NR | NR | N | N | NR | Y | 2 |
| North, 1992 | Y | NR | NR | Y | N | NR | Y | 3 |
| Shapira, 2000 | Y | NR | NR | Y | N | NR | Y | 3 |
| Goel, 2001 | Y | Y | Y | Y | N | Y | Y | 6 |
| Wolf, 2000 | Y | NR | NR | Y | N | Y | Y | 4 |
| Pignione, 2000 | Y | Y | Y | Y | Y | Y | Y | 7 |
| Inglehart, 1998 | Y | N | N | N | N | NR | Y | 2 |
Quality Assessment of the Effectiveness RCT Studies with the Jadad Scale
| Randomized | Appropriate Randomization | Double-blinded | Appropriately Blinded | Dropouts | Points | Qualification | |
|---|---|---|---|---|---|---|---|
| Volk, 1999 | Y | Y | N | N | Y | 3 | Good |
| Lerman, 1997 | Y | N | N | N | Y | 2 | Poor |
| Davison, 1997 | Y | Y | N | N | N | 2 | Poor |
| Davison, 1999 | Y | Y | N | N | N | 2 | Poor |
| Hack, 1999 | Y | Y | N | N | N | 2 | Poor |
| Watson, 1998 | Y | N | N | N | Y | 2 | Poor |
| Wolf, 1996 | Y | N | N | N | N | 1 | Poor |
| Shapira, 2000 | Y | N | N | N | N | 1 | Poor |
| Irwin, 1999 | Y | N | N | N | N | 1 | Poor |
| Street, 1995 | Y | N | N | N | N | 1 | Poor |
| Maslin, 1998 | Y | N | N | N | N | 1 | Poor |
| North, 1992 | Y | N | N | N | N | 1 | Poor |
| Goel, 2001 | Y | Y | N | N | Y | 3 | Good |
| Wolf, 2000 | Y | N | N | N | N | 1 | Poor |
| Pignione, 2000 | Y | N | N | Y | Y | 3 | Good |
| Inglehart, 1998 | Y | N | N | N | N | 1 | Poor |
Quality Assessment of Effectiveness RCT Studies with the Downs & Black's Checklist: Reporting
| Author (year) | Hypothesis/Aim/Objective | Outcomes measured | Sample characteristics | Intervention | Confounders | Findings | Random variability estimate | Adverse events | Patients lost to followup | Actual probability values |
|---|---|---|---|---|---|---|---|---|---|---|
| Volk, 1999 | Y | Y | Y | N | Y | Y | N | NA | Y | Y |
| Lerman, 1997 | Y | Y | Y | N | Y | Y | Y | NA | Y | Y |
| Davison, 1997 | Y | Y | Y | N | Y | Y | N | NA | N | Y |
| Davison, 1999 | Y | Y | Y | N | Y | Y | N | NA | N | Y |
| Hack, 1999 | Y | Y | N | Y | N | N | N | NA | N | N |
| Watson, 1998 | Y | N | N | N | N | Y | Y | NA | N | Y |
| Wolf, 1996 | Y | Y | Y | Y | Y | Y | N | NA | N | Y |
| Irwin, 1999 | Y | Y | Y | Y | N | N | Y | NA | N | Y |
| Street, 1995 | Y | Y | Y | N | Y | Y | Y | NA | N | Y |
| Maslin, 1998 | Y | Y | N | N | N | N | N | NA | N | Y |
| North, 1992 | Y | Y | N | N | N | Y | Y | NA | N | Y |
| Shapira, 2000 | Y | Y | N | N | Y | Y | Y | NA | N | N |
| Goel, 2001 | Y | Y | Y | Y | Y | Y | Y | NA | Y | Y |
| Wolf, 2000 | Y | Y | Y | Y | Y | Y | N | NA | N | Y |
| Pignione, 2000 | Y | Y | Y | Y | Y | Y | Y | NA | Y | Y |
| Inglehart, 1998 | y | y | y | Y | N | N | N | NA | N | Y |
Quality Assessment of Effectiveness RCT Studies with the Downs & Black's Checklist: External Validity
| Author (year) | Included subjects are representative of the entire population | Characteristics of the sample are similar | Staff, places, and facilities are representative of treatment the majority of patients receive |
|---|---|---|---|
| Volk, 1999 | Y | NC | Y |
| Lerman, 1997 | Y | NC | Y |
| Davison, 1997 | Y | NC | Y |
| Davison, 1999 | Y | NC | Y |
| Hack, 1999 | Y | NC | Y |
| Watson, 1998 | Y | NC | NC |
| Wolf, 1996 | Y | NC | Y |
| Irwin, 1999 | Y | NC | Y |
| Street, 1995 | Y | NC | NC |
| Maslin, 1998 | Y | NC | NC |
| North, 1992 | NC | NC | NC |
| Shapira, 2000 | Y | NC | Y |
| Goel, 2001 | Y | Y | Y |
| Wolf, 2000 | Y | NC | Y |
| Pignione, 2000 | Y | NC | Y |
| Inglehart, 1998 | Y | NC | Y |
Quality Assessment of Effectiveness RCT Studies with the Downs & Black's Checklist: Internal Validity (bias)
| Blinding in included subjects | Blinding in measuring the outcomes | Results based on "data dredging" | Analysis adjusted for different lengths of followup | Statistical analysis appropriate | Compliance with the intervention | Main outcomes accurate | |
|---|---|---|---|---|---|---|---|
| Volk, 1999 | N | N | N | NA | Y | NC | Y |
| Lerman, 1997 | N | N | N | NA | Y | NC | NC |
| Davison, 1997 | N | N | N | NA | Y | Y | Y |
| Davison, 1999 | N | N | N | NA | Y | N | Y |
| Hack, 1999 | N | N | Y | NA | Y | N | Y |
| Watson, 1998 | N | N | NC | NA | Y | Y | NC |
| Wolf, 1996 | N | N | N | NA | Y | NC | NC |
| Irwin, 1999 | N | N | Y | NA | Y | NC | NC |
| Street, 1995 | N | N | N | NA | Y | NC | Y |
| Maslin, 1998 | N | N | NC | NA | NC | NC | Y |
| North, 1992 | N | N | N | NA | Y | NC | Y |
| Shapira, 2000 | N | N | N | NA | Y | NC | NC |
| Goel, 2001 | N | N | N | NA | Y | NC | Y |
| Wolf, 2000 | N | N | N | NA | Y | NC | NC |
| Pignione, 2000 | N | Y | N | NA | Y | NC | NC |
| Inglehart, 1998 | N | N | N | NA | Y | NC | NC |
Quality Assessment of Effectiveness RCT Studies with the Downs & Black's Checklist: Internal Validity (confounding)
| Author (year) | Each intervention group selected from the same population | Included subjects in the same period of time | Included subjects randomized | Randomization concealed | Adjustment of confounders | Losses of patients taken into a count | Power |
|---|---|---|---|---|---|---|---|
| Volk, 1999 | Y | Y | Y | NC | N | Y | |
| Lerman, 1997 | Y | Y | Y | NC | N | NC | |
| Davison, 1997 | Y | Y | Y | NC | N | NC | |
| Davison, 1999 | Y | Y | Y | NC | N | NC | |
| Hack, 1999 | Y | Y | Y | NC | N | NC | |
| Watson, 1998 | Y | Y | Y | NC | N | NC | |
| Wolf, 1996 | Y | Y | Y | NC | Y | NC | |
| Irwin, 1999 | Y | Y | Y | NC | N | NC | |
| Street, 1995 | Y | Y | Y | NC | N | NC | |
| Maslin, 1998 | Y | Y | Y | NC | N | NC | |
| North, 1992 | Y | Y | Y | NC | N | NC | |
| Shapira, 2000 | Y | Y | Y | NC | N | NC | |
| Goel, 2001 | Y | Y | Y | Y | N | Y | (Y) |
| Wolf, 2000 | Y | Y | Y | NC | N | NC | (Y) |
| Pignione, 2000 | Y | Y | Y | NC | N | Y | (Y) |
| Inglehart, 1998 | Y | Y | Y | NC | N | N |
Quality Assessment of Effectiveness RCT Studies with the Downs & Black's Checklist: Overall Evaluation
| Author (year) | Reporting (max: 9) | External validity (max: 3) | Internal validity:Bias (max: 6) | Internal validity:Confounding (max: 6) | FINAL SCORE (max: 24) |
| Volk, 1999 | 7 | 2 | 3 | 4 | 16 |
| Lerman, 1997 | 8 | 2 | 2 | 3 | 15 |
| Davison, 1997 | 6 | 2 | 4 | 3 | 15 |
| Davison, 1999 | 6 | 2 | 3 | 3 | 14 |
| Hack, 1999 | 3 | 2 | 3 | 3 | 11 |
| Watson, 1998 | 4 | 1 | 2 | 3 | 10 |
| Wolf, 1996 | 7 | 2 | 2 | 4 | 15 |
| Irwin, 1999 | 6 | 2 | 2 | 3 | 13 |
| Street, 1995 | 7 | 1 | 3 | 3 | 14 |
| Maslin, 1998 | 3 | 1 | 1 | 3 | 8 |
| North, 1992 | 5 | 0 | 1 | 3 | 8 |
| Shapira, 2000 | 5 | 2 | 2 | 3 | 12 |
| Goel, 2001 | 9 | 3 | 3 | 5 | 20 |
| Wolf, 2000 | 7 | 2 | 2 | 3 | 14 |
| Pignione, 2000 | 9 | 2 | 3 | 4 | 18 |
| Inglehart, 1998 | 4 | 2 | 1 | 3 | 10 |
Quality Assessment of Controlled Trials and Nonconcurrent Cohort Effectiveness Studies with the Downs & Black's Checklist: Reporting
| Author (year) | Hypothesis/Aim/Objective | Outcomes measured | Sample characteristics | Intervention | Confounders | Findings | Random variability estimate | Adverse events | Patients lost to followup | Actual probability values |
|---|---|---|---|---|---|---|---|---|---|---|
| Flood, 1996 a Study 1 | Y | Y | Y | Y | Y | Y | N | NA | Y | Y |
| Flood, 1996a Study 2 | Y | Y | N | Y | Y | Y | N | NA | Y | Y |
| Sepucha, 2000a | Y | Y | N | N | Y | Y | N | NA | N | Y |
| Whelan, 1995 b | Y | Y | Y | Y | Y | Y | N | NA | N | Y |
| Whelan, 1999b | Y | Y | Y | Y | Y | Y | N | NA | N | Y |
| Molenaar, 2001a | Y | Y | Y | Y | Y | Y | Y | NA | Y | Y |
Controlled trial
Nonconcurrent cohort
Quality Assessment of Controlled Trials and Nonconcurrent Cohort Effectiveness Studies with the Downs & Black's Checklist: External Validity
| Author (year) | Included subjects are representative of the entire population | Characteristics of the sample are similar | Staff, places, and facilities are representative of treatment the majority of patients receive |
|---|---|---|---|
| Flood, 1996a Study 1 | N | NC | N |
| Flood, 1996a Study 2 | Y | NC | Y |
| Sepucha, 2000 a | Y | NC | Y |
| Whelan, 1995b | Y | NC | Y |
| Whelan, 1999b | Y | NC | Y |
| Molenaar, 2001 a | Y | NC | Y |
Controlled trial
Nonconcurrent cohort
Quality Assessment of Controlled Trials and Nonconcurrent Cohort Effectiveness Studies with the Downs & Black's Checklist: Internal Validity (bias)
| Author (year) | Blinding in included subjects | Blinding in measuring the outcomes | Results based on "data dredging" | Analysis adjusted for different lengths of followup | Statistical analysis appropriate | Compliance with the intervention | Main outcomes accurate |
|---|---|---|---|---|---|---|---|
| Flood, 1996a Study 1 | N | N | N | NA | Y | N | N |
| Flood, 1996a Study 2 | N | N | N | NA | Y | N | N |
| Sepucha, 2000a | N | N | N | NA | Y | N | Y |
| Whelan, 1995b | N | N | N | NA | Y | N | N |
| Whelan, 1999 b | N | N | N | NA | Y | N | Y |
| Molenaar, 2001a | N | N | N | NA | Y | N | Y |
Controlled trial
Nonconcurrent cohort
Quality Assessment of Controlled Trials and Nonconcurrent Cohort Effectiveness Studies with the Downs & Black's Checklist: Internal Validity (confounding)
| Author (year) | Each intervention group selected from the same population | Included subjects in the same period of time | Included subjects randomized | Randomization concealed | Adjustment of confounders | Loss of patients taken into account | Power |
|---|---|---|---|---|---|---|---|
| Flood, 1996a Study 1 | Y | Y | NA | NA | N | N | |
| Flood, 1996 a Study 2 | Y | Y | NA | NA | N | N | |
| Sepucha, 2000 a | Y | Y | NA | NA | N | N | |
| Whelan, 1995b | Y | N | NA | NA | N | N | |
| Whelan, 1999b | Y | N | NA | NA | N | N | |
| Molenaar, 2001 a | Y | Y | NA | NA | N | Y |
Controlled trial
Nonconcurrent cohort
Quality Assessment of Controlled Trials and Nonconcurrent Cohort Effectiveness Studies with the Downs & Black's Checklist: Overall Evaluation
| Author (year) | Reporting (max: 9) | External validity (max: 3) | Internal validity:Bias (max: 6) | Internal validity:Confounding (max: 4) | FINAL SCORE (max: 22) |
| Flood, 1996a Study 1 | 8 | 0 | 2 | 2 | 12 |
| Flood, 1996a Study 2 | 7 | 2 | 2 | 2 | 13 |
| Sepucha, 2000 b | 5 | 2 | 3 | 2 | 12 |
| Whelan, 1995b | 7 | 2 | 2 | 1 | 12 |
| Whelan, 1999b | 7 | 2 | 3 | 1 | 13 |
| Molenaar, 2001 a | 9 | 2 | 3 | 3 | 17 |
Controlled trial
Nonconcurrent cohort
Quality Assessment of Case Series Effectiveness Studies with the Downs & Black's Checklist: Reporting
| Author (Year) | Hypothesis/Aim/Objective | Outcomes measured | Sample characteristics | Intervention | Confounders | Findings | Random variability estimate | Adverse events | Patients lost to followup | Actual probability values |
|---|---|---|---|---|---|---|---|---|---|---|
| Adler (1999) | Y | N | Y | N | NA | Y | N | NA | Y | N |
| Ashcroft (1985) | Y | Y | Y | Y | NA | N | Y | NA | N | N |
| Brundage (2000) | Y | Y | Y | Y | NA | Y | Y | NA | Y | Y |
| Cassileth (1989) | Y | Y | Y | Y | NA | Y | N | NA | N | N |
| Cotton (1991) | Y | Y | Y | Y | NA | Y | N | NA | Y | Y |
| Cotton (1995) | Y | N | N | N | NA | Y | N | NA | Y | N |
| Gramlich (1998) | Y | N | N | Y | NA | N | N | NA | N | N |
| Levine (1992) | Y | Y | N | Y | NA | Y | N | NA | Y | N |
| Onel (1998) | Y | Y | N | Y | NA | Y | N | NA | Y | N |
| Protiere (2000) | Y | Y | Y | Y | NA | Y | Y | NA | Y | N |
| Sandison (1996) | Y | Y | Y | Y | NA | Y | N | NA | Y | N |
| Stalmeier (1999) | Y | Y | Y | Y | NA | Y | Y | NA | Y | Y |
| Wilson (1988) | Y | Y | Y | N | NA | Y | N | NA | Y | N |
| Wolberg (1987) | Y | Y | Y | N | NA | Y | Y | NA | NC | N |
| Klass (1992) | Y | Y | Y | Y | NA | Y | N | NA | N | Y |
| Okamoto (1999) | N | Y | Y | Y | NA | Y | N | NA | N | N |
| Fiset (2000) | Y | Y | Y | Y | NA | Y | Y | NA | Y | Y |
Quality Assessment of Case Series Effectiveness Studies with the Downs & Black's Checklist: External Validity
| Author (Year) | Included subjects are representative of the entire population | Characteristics of the sample are similar | Staff, places, and facilities are representative of treatment the majority of patients receive |
|---|---|---|---|
| Adler (1999) | Y | NC | Y |
| Ashcroft (1985) | Y | NC | Y |
| Brundage (2000) | NC | NC | Y |
| Cassileth (1989) | Y | Y | Y |
| Cotton (1991) | Y | Y | Y |
| Cotton (1995) | NC | NC | Y |
| Gramlich (1998) | NC | NC | Y |
| Levine (1992) | NC | NC | Y |
| Onel (1998) | NC | NC | NC |
| Protiere (2000) | Y | Y | Y |
| Sandison (1996) | Y | NC | Y |
| Stalmeier (1999) | NC | NC | Y |
| Wilson (1988) | Y | Y | Y |
| Wolberg (1987) | Y | NC | Y |
| Klass (1992) | NC | NC | NC |
| Okamoto (1999) | NC | NC | NC |
| Fiset (2000) | NC | NC | Y |
Quality Assessment of Case Series Effectiveness Studies with the Downs & Black's Checklist: Internal Validity (bias)
| Author (Year) | Blinding in included subjects | Blinding in measuring the outcomes | Results based on "data dredging" | Analysis adjusted for different lengths of followup | Statistical analysis appropriate | Compliance with the intervention | Main outcomes accurate |
|---|---|---|---|---|---|---|---|
| Adler (1999) | N | N | N | NA | Y | N | NC |
| Ashcroft (1985) | N | N | N | NA | Y | N | Y |
| Brundage (2000) | N | N | N | NA | Y | N | NC |
| Cassileth (1989) | N | N | N | NA | Y | N | NC |
| Cotton (1991) | N | N | N | NA | Y | N | NC |
| Cotton (1995) | N | N | N | NA | Y | N | NC |
| Gramlich (1998) | N | N | N | NA | Y | N | NC |
| Levine (1992) | N | N | N | NA | Y | N | NC |
| Onel (1998) | N | N | N | NA | Y | N | NC |
| Protiere (2000) | N | N | N | NA | Y | N | NC |
| Sandison (1996) | N | N | N | NA | Y | N | NC |
| Stalmeier (1999) | N | N | N | NA | Y | N | NC |
| Wilson (1988) | N | N | N | NA | Y | N | NC |
| Wolberg (1987) | N | N | N | NA | Y | N | Y |
| Klass (1992) | N | N | N | NA | Y | N | NC |
| Okamoto (1999) | N | N | N | NA | Y | N | NC |
| Fiset (2000) | N | N | N | NA | Y | N | Y |
Quality Assessment of Case Series Effectiveness Studies with the Downs & Black's Checklist: Internal Validity (confounding)
| Author (Year) | Each intervention group selected from the same population | Included subjects in the same period of time | Included subjects randomized | Randomization concealed | Adjustment of confounders | Loss of patients taken into account | Power |
|---|---|---|---|---|---|---|---|
| Adler (1999) | NA | Y | NA | NA | NA | N | N/A |
| Ashcroft (1985) | NA | N | NA | NA | NA | NC | N/A |
| Brundage (2000) | NA | Y | NA | NA | NA | Y | N/A |
| Cassileth (1989) | NA | Y | NA | NA | NA | N | N/A |
| Cotton (1991) | NA | Y | NA | NA | NA | Y | N/A |
| Cotton (1995) | NA | Y | NA | NA | NA | Y | N/A |
| Gramlich (1998) | NA | Y | NA | NA | NA | N | N/A |
| Levine (1992) | NA | Y | NA | NA | NA | Y | N/A |
| Onel (1998) | NA | Y | NA | NA | NA | Y | N/A |
| Protiere (2000) | NA | Y | NA | NA | NA | Y | N/A |
| Sandison (1996) | NA | Y | NA | NA | NA | Y | N/A |
| Stalmeier (1999) | NA | Y | NA | NA | NA | NC | N/A |
| Wilson (1988) | NA | Y | NA | NA | NA | N | N/A |
| Wolberg (1987) | NA | N | NA | NA | NA | NC | N/A |
| Klass (1992) | NA | Y | NA | NA | NA | NC | N/A |
| Okamoto (1999) | NA | Y | NA | NA | NA | NC | N/A |
| Fiset (2000) | NA | Y | NA | NA | NA | Y | N/A |
Quality Assessment of Case Series Studies with the Downs & Black's Checklist: Overall Evaluation
| Author (Year) | Reporting (max: 8) | External validity (max: 3) | Internal validity:Bias (max: 6) | Internal validity:Confounding (max: 2) | FINAL SCORE (max: 19) |
| Adler (1999) | 4 | 2 | 2 | 1 | 9 |
| Ashcroft (1985) | 5 | 2 | 3 | 0 | 10 |
| Brundage (2000) | 8 | 1 | 3 | 2 | 14 |
| Cassileth (1989) | 5 | 3 | 2 | 1 | 11 |
| Cotton (1991) | 7 | 3 | 2 | 2 | 14 |
| Cotton (1995) | 3 | 1 | 2 | 2 | 8 |
| Gramlich (1998) | 2 | 1 | 2 | 1 | 6 |
| Levine (1992) | 5 | 1 | 2 | 2 | 10 |
| Onel (1998) | 5 | 0 | 2 | 2 | 9 |
| Protiere (2000) | 7 | 3 | 2 | 2 | 14 |
| Sandison (1996) | 6 | 2 | 2 | 2 | 12 |
| Stalmeier (1999) | 8 | 1 | 2 | 2 | 13 |
| Wilson (1988) | 5 | 3 | 2 | 1 | 11 |
| Wolberg (1987) | 5 | 2 | 3 | 0 | 10 |
| Klass (1992) | 6 | 0 | 2 | 1 | 9 |
| Okamoto (1999) | 4 | 0 | 2 | 1 | 7 |
| Fiset (2000) | 8 | 1 | 3 | 2 | 14 |
Quality Assessment of the Development Studies with the Downs & Black's Checklist: Reporting
| Author (year) | Hypothesis/Aim/Objective | Outcomes measured | Sample characteristics | Intervention | Confounders | Findings | Random variability estimate | Adverse events | Patients lost to followup | Actual probability values |
|---|---|---|---|---|---|---|---|---|---|---|
| Shapira, (1997) ID# 123 | Y | Y | N | Y | NA | Y | N | NA | N | NA |
| Gustafson, (1993) ID# 1196Study 1 | Y | N | Y | Y | NA | N | N | NA | N | N |
| Gustafson, (1993) ID# 7538 Study 2 | Y | N | Y | Y | NA | N | N | NA | N | N |
| McTavish, (1995) ID# 5045 | Y | N | N | Y | NA | N | N | NA | N | N |
| Rolnock, (1999) ID# 386 | Y | N | N | N | N | N | N | NA | N | N |
| Dolan, (1995) ID# 4933 | Y | Y | N | Y | NA | Y | N | NA | Y | Y |
| Chapman, (1995) ID# 116 | Y | Y | N | Y | Y | Y | N | NA | N | Y |
| Jenkinson, (1998) ID# 814 | Y | Y | N | Y | NA | Y | N | NA | N | NA |
| Brundage, (1997) ID# 149 | Y | Y | Y | Y | NA | Y | Y | NA | Y | Y |
| Levine, (1992) ID# 7117 | Y | Y | N | Y | NA | Y | N | NA | N | Y |
| Whelan, (1995) ID# 7535 | Y | Y | N | Y | NA | N | N | NA | N | NA |
| Sebban, (1995) ID# 117 | Y | Y | N | Y | NA | Y | Y | NA | Y | Y |
| Elit, (1996) ID# 119 Study 1 | Y | N | N | Y | NA | N | N | NA | Y | Y |
| Elit, (1996) ID# 7539 Study 2 | Y | N | Y | Y | NA | N | N | NA | Y | N |
| Whelan, (1999) ID# 7536 | Y | Y | N | Y | NA | Y | N | NA | N | Y |
| Lawrence, (2000) ID# 5012 | Y | Y | N | Y | NA | Y | Y | NA | N | Y |
| Carrere, (2000) ID# 5013 | Y | Y | Y | Y | NA | Y | Y | NA | N | Y |
| Sawka, (1998) ID# 199 Study 1 | Y | Y | Y | Y | NA | Y | Y | NA | N | NA |
| Sawka, (1998) ID# 7537 Study 2 | Y | Y | Y | Y | NA | Y | Y | NA | N | NA |
| Unic, (1998) ID# 872 | Y | Y | Y | Y | NA | Y | Y | NA | Y | Y |
| Ravdin, (2001) ID# 7852 | Y | Y | N | Y | NA | N | N | NA | N | N |
| Fisset, (2000) ID# 7873 | Y | Y | N | Y | NA | Y | N | NA | N | N |
Quality Assessment of the Development Studies with the Downs & Black's Checklist: External Validity
| Author (Year) | Included subjects are representative of the entire population | Characteristics of the sample are similar | Staff, places, and facilities are representative of treatment the majority of patients receive |
|---|---|---|---|
| Shapira, (1997) ID# 123 | NC | NC | N |
| Gustafson, (1993) ID# 1196 Study 1 | NC | NC | NC |
| Gustafson, (1993) ID# 7538Study 2 | NC | NC | NC |
| McTavish, (1995) ID# 5045 | NC | NC | NC |
| Rolnock, (1999) ID# 386 | NC | NC | NC |
| Dolan, (1995) ID# 4933 | NC | NC | NC |
| Chapman, (1995) ID# 116 | NC | NC | N |
| Jenkinson, (1998) ID# 814 | NC | NC | N |
| Brundage, (1997) ID# 149 | NC | NC | Y |
| Levine, (1992) ID# 7117 | NC | NC | N |
| Whelan, (1995) ID# 7535 | NC | NC | NC |
| Sebban, (1995) ID# 117 | NC | NC | N |
| Elit, (1996) ID# 119 Study 1 | NC | NC | N |
| Elit, (1996) ID# 7539 Study 2 | NC | NC | Y |
| Whelan, (1999) ID# 7536 | NC | NC | N |
| Lawrence, (2000) ID# 5012 | NC | NC | NC |
| Carrere, (2000) ID# 5013 | NC | NC | NC |
| Sawka, (1998) ID# 199 Study 1 | NC | NC | NC |
| Sawka, (1998) ID# 7537 Study 2 | NC | NC | NC |
| Unic, (1998) ID# 872 | NC | NC | Y |
| Ravdin, (2001) ID# 7852 | NC | NC | NC |
| Fisset, (2000) ID# 7873 | NC | NC | NC |
Quality Assessment of Development Studies with the Downs & Black's Checklist: Internal Validity (bias)
| Author (year) | Blinding in included subjects | Blinding in measuring the outcomes | Results based on "data dredging" | Analysis adjusted for different lengths of followup | Statistical analysis appropriate | Compliance with the intervention | Main outcomes accurate |
|---|---|---|---|---|---|---|---|
| Shapira, (1997) ID# 123 | N | N | N | NA | Y | N | N |
| Gustafson, (1993) ID# 1196 Study 1 | N | N | N | N | Y | Y | NC |
| Gustafson, (1993) ID# 7538 Study 2 | N | N | N | N | Y | Y | NC |
| McTavish, (1995) ID# 5045 | N | N | N | N | Y | Y | NC |
| Rolnick, (1999) ID# 386 | N | N | N | Y | Y | Y | NC |
| Dolan, (1995) ID# 4933 | N | N | N | NA | Y | Y | NC |
| Chapman, (1995) ID# 116 | N | N | N | NA | Y | N | NC |
| Jenkinson, (1998) ID# 814 | N | N | N | NA | Y | N | NC |
| Brundage, (1997) ID# 149 | N | N | N | NA | Y | Y | Y |
| Levine, (1992) ID# 7117 | N | N | N | NA | Y | N | Y |
| Whelan, (1995) ID# 7535 | N | N | N | NA | NC | N | N |
| Sebban, (1995) ID# 117 | N | N | N | NA | Y | N | N |
| Elit, (1996) ID# 119 Study 1 | N | N | N | NA | Y | Y | N |
| Elit, (1996) ID# 7539 Study 2 | N | N | N | NA | NC | Y | N |
| Whelan, (1999) ID# 7536 | N | N | N | NA | Y | N | Y |
| Lawrence, (2000) ID# 5012 | N | N | N | NA | Y | N | Y |
| Carrere, (2000) ID# 5013 | N | N | N | NA | Y | N | Y |
| Sawka, (1998) ID# 199 Study 1 | N | N | N | NA | Y | N | Y |
| Sawka, (1998) ID# 7537 Study 2 | N | N | N | NA | Y | N | Y |
| Unic, (1998) ID# 872 | N | N | N | NA | Y | Y | Y |
| Ravdin, (2001) ID# 7852 | N | N | N | NA | NC | N | NC |
| Fisset, (2000) ID# 7873 | N | N | N | NA | NC | N | NC |
Quality Assessment of the Development Studies with the Downs & Black's Checklist: Internal Validity (confounding)
| Author (year) | Each intervention group selected from the same population | Included subjects in the same period of time | Included subjects randomized | Randomization concealed | Adjustment of confounders | Loss of patients taken into account | Power |
|---|---|---|---|---|---|---|---|
| Shapira, (1997) ID# 123 | NA | Y | NA | NA | NA | N | |
| Gustafson, (1993) ID# 1196 Study 1 | NA | Y | NA | NA | NA | N | |
| Gustafson, (1993) ID# 7538Study 2 | NA | Y | NA | NA | NA | N | |
| McTavish, (1995) ID# 5045 | NA | Y | NA | NA | NA | N | |
| Rolnick, (1999) ID# 386 | NC | Y | Y | NC | N | N | |
| Dolan, (1995) ID# 4933 | NA | Y | NA | NA | NA | Y | |
| Chapman, (1995) ID# 116 | Y | Y | NA | NA | Y | N | |
| Jenkinson, (1998) ID# 814 | NA | Y | NA | NA | NA | N | |
| Brundage, (1997) ID# 149 | NA | Y | NA | NA | NA | Y | |
| Levine, (1992) ID# 7117 | NA | Y | NA | NA | NA | N | |
| Whelan, (1995) ID# 7535 | NA | Y | NA | NA | NA | N | |
| Sebban, (1995) ID# 117 | NA | Y | Y | N | N | Y | |
| Elit, (1996) ID# 119 Study 1 | NA | Y | NA | NA | NA | Y | |
| Elit, (1996) ID# 7539 Study 2 | NA | Y | NA | NA | NA | Y | |
| Whelan, (1999) ID# 7536 | NA | Y | NA | NA | NA | N | |
| Lawrence, (2000) ID# 5012 | NA | Y | NA | NA | NA | N | |
| Carrere, (2000) ID# 5013 | NA | Y | NA | NA | NA | N | |
| Sawka, (1998) ID# 199 Study 1 | NA | Y | NA | NA | NA | N | |
| Sawka, (1998) ID# 7537 Study 2 | NA | Y | NA | NA | NA | N | |
| Unic, (1998) ID# 872 | NA | Y | NA | NA | NA | Y | |
| Ravdin, (2001) ID# 7852 | NC | Y | NA | NA | NA | N | |
| Fisset, (2000) ID# 7873 | NC | Y | NA | NA | NA | N |
Quality Assessment of Development Studies with the Downs & Black's Checklist: Overall Evaluation
| Author (Year) | Reporting | External validity | Internal validity: Bias | Internal validity: Confounding | FINAL SCORE |
|---|---|---|---|---|---|
| Shapira, (1997) ID# 123 | 4/7 (57.1%) | 0/3 (0%) | 2/6 (33.1%) | 1/2 (50%) | 7/18 (38.8%) |
| Gustafson, (1993) ID# 1196 Study 1 | 3/8 (37.5%) | 0/3 (0%) | 3/7 (42.8%) | 1/2 (50%) | 7/20 (35%) |
| Gustafson, (1993) ID# 7538 Study 2 | 3/8 (37.5%) | 0/3 (0%) | 3/7 (42.8%) | 1/2 (50%) | 7/20 (35%) |
| McTavish, (1995) ID# 5045 | 2/8 (25%) | 0/3 (0%) | 3/7 (42.8%) | 1/2 (50%) | 6/20 (30%) |
| Rolnick, (1999) ID# 386 | 1/9 (11.1%) | 0/3 (0%) | 4/7 (57.1%) | 2/5 (40%) | 7/24 (29.1%) |
| Dolan, (1995) ID# 4933 | 5/8 (62.5%) | 0/3 (0%) | 3/6 (50%) | 2/2 (100%) | 10/19 (52.6%) |
| Chapman, (1995) ID# 116 | 6/9 (66.6%) | 0/3 (0%) | 2/6 (33.1%) | 3/4 (75%) | 11/22 (50%) |
| Jenkinson, (1998) ID# 814 | 4/7 (57.1%) | 0/3 (0%) | 2/6 (33.1%) | 1/2 (50%) | 7/18 (38.8%) |
| Brundage, (1997) ID# 149 | 8/8 (100%) | 1/3 (33.3%) | 4/6 (66.6%) | 2/2 (100%) | 15/19 (78.9%) |
| Levine, (1992) ID# 7117 | 5/8 (62.5%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 9/19 (47.3%) |
| Whelan, (1995) ID# 7535 | 3/7 (42.8%) | 0/3 (0%) | 1/6 (16.6%) | 1/2 (50%) | 5/18 (27.7%) |
| Sebban, (1995) ID# 117 | 7/8 (87.5%) | 0/3 (0%) | 2/6 (33.1%) | 3/5 (60%) | 12/22 (54.5%) |
| Elit, (1996) ID# 119 Study 1 | 4/8 (50%) | 0/3 (0%) | 3/6 (50%) | 2/2 (100%) | 9/19 (47.3%) |
| Elit, (1996) ID# 7539 Study 2 | 4/8 (50%) | 1/3 (33.3%) | 2/6 (33.1%) | 1/2 (50%) | 10/19 (52.6%) |
| Whelan, (1999) ID# 7536 | 5/8 (62.5%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 9/19 (47.3%) |
| Lawrence, (2000) ID# 5012 | 6/8 (75%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 10/19 (52.6%) |
| Carrere, (2000) ID# 5013 | 7/8 (87.5%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 11/19 (57.8%) |
| Sawka, (1998) ID# 199 Study 1 | 6/7 (85.7%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 10/18 (55.5%) |
| Sawka, (1998) ID# 7537 Study 2 | 6/7 (85.7%) | 0/3 (0%) | 3/6 (50%) | 1/2 (50%) | 10/18 (55.5%) |
| Unic, 1998 | 8/8 (100%) | 1/3 (33.3%) | 4/6 (66.6%) | 2/2 (100%) | 15/19 (78.9%) |
| Ravdin, (2001) ID# 7852 | 3/8 (37.5%) | 0/3 (0%) | 1/6 (16.6%) | 1/3 (33.3%) | 5/20 (25%) |
| Fisset, (2000) ID# 7873 | 4/8 (50%) | 0/3 (0%) | 1/6 (16.6%) | 1/2 (50%) | 6/19 (31.5%) |
| AC | Adriamycin/Cyclophosphamide |
| AHP | Analytic hierarchy process |
| AHRQ | Agency for Healthcare Research and Quality |
| BCIT | Breast Cancer Information Test |
| BCS | Breast cancer screening |
| BMT | Bone marrow transplant |
| CES-D | Center for Epidemiologic Studies Depression Scale |
| CG | Control group |
| CHESS | Comprehensive Health Enhancement Support System |
| CINAHL | Cumulative Index to Nursing & Allied Health Literature® |
| CI | Confidence interval |
| CMF | Cyclophosphamide/Methotrexate/5-Fluorouracil |
| CMT | Combined treatment modalities |
| CPS | Control preference scale |
| CT | Controlled trial |
| DA | Cancer-related decision aids |
| DB | Decision board |
| DRE | Digital rectal examination |
| DSFI | Derogatis Sexual Function Inventory |
| EMBASE | Excerpta Medica Database |
| GSI | General sheet of information |
| HNPCC | Hereditary nonpolyposis colorectal cancer |
| ICP | Interactive Computer Program |
| IG1 | Intervention group 1 |
| IG2 | Intervention group 2 |
| IG3 | Intervention group 3 |
| IMP | Interactive Multimedia Program |
| IVDS | Interactive Video Disk System |
| MAX | Maximum |
| MCMI | Million Clinical Multiaxial Inventory |
| MOS-SF36 | Medical Outcome Study -- Short form 36 |
| MU-EPC | McMaster University Evidence-based Practice Center |
| NA | Not applicable |
| NC | Not clear |
| NCI | National Cancer Institute |
| NR | Not reported |
| NSCLC | Non-small cell lung cancer |
| PAIS | Psychosocial Adjustment to Illness Scale |
| PHE | Periodic health examination |
| PM | Prophylactic mastectomy |
| POMS | Profile of Mood States |
| PSA | Prostate-Specific Antigen test |
| QPS | Question prompt sheet |
| RA | Research Assistant |
| RCT | Randomized controlled trial |
| RPE | Routine physical examination |
| RS | Rating scale |
| RT | Radiotherapy |
| SAT | Survival advantage threshold |
| SCCR | Supportive Cancer Care Research |
| SCLS | Small-cell lung cancer |
| SD | Standard deviation |
| SES | Socioeconomic status |
| SPD | Shared Decisionmaking Program |
| TEP | Technical Expert Panel |
| TOO | Task Order Officer |
| TTO | Time tradeoff |
| VAS | Visual Analog Scale |
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