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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Patient Educ Couns. Author manuscript; available in PMC Feb 1, 2009.
Published in final edited form as:
PMCID: PMC2324068
NIHMSID: NIHMS39529

Meta-Analysis of Patient Education Interventions to Increase Physical Activity among Chronically Ill Adults

Abstract

Objective

This meta-analysis integrates primary research testing the effect of patient education to increase physical activity (PA) on behavior outcomes among adults with diverse chronic illnesses.

Methods

Extensive literature searching strategies located published and unpublished intervention studies that measured PA behavior outcomes. Primary study results were coded. Fixed- and random-effects meta-analytic procedures included moderator analyses.

Results

Data were synthesized across 22,527 subjects from 213 samples in 163 reports. The overall mean weighted effect size for two-group comparisons was 0.45 (higher mean for treatment than control). This effect size is consistent with a difference of 48 minutes of PA per week or 945 steps per day. Preliminary moderator analyses suggest interventions were most effective when they targeted only PA behavior, used behavioral strategies (vs. cognitive strategies), and encouraged PA self-monitoring. Differences among chronic illnesses were documented. Individual strategies unrelated to PA outcomes included supervised exercise sessions, exercise prescription, fitness testing, goal setting, contracting, problem solving, barriers management, and stimulus/cues. PA outcomes were unrelated to gender, age, ethnicity, or socioeconomic distribution among samples.

Conclusion

These findings suggest that some patient education interventions to increase PA are effective, despite considerable heterogeneity in the magnitude of intervention effect.

Practice Implications

Moderator analyses are preliminary and provide suggestive evidence for further testing of interventions to inform practice.

Keywords: patient education, exercise, meta-analysis, health behavior change

1. Introduction

Health care providers routinely recommend physical activity (PA) to many adults with chronic illnesses. Despite widespread recognition of potential health and well-being benefits of PA, most adults with chronic illnesses remain sedentary. Numerous primary studies have tested diverse patient education interventions to increase PA, and many authors have reviewed these investigations. Most reviews, including meta-analyses, have focused on benefits of PA. The many narrative reviews focused on PA behavior outcomes have examined limited domains of this broad literature, such as computer-tailored interventions [1]; primary care-based interventions [2-5]; environmental interventions [6,7]; mass media-delivered interventions [8]; interventions designed to increase ‘lifestyle’ PA (versus episodic exercise) [9,10]; interventions targeting older adults [11,12]; studies addressing subpopulations such as African-Americans [13-19]; and intervention studies based on particular theoretical models [20]. Narrative reviews discussing PA behavior outcomes often address very few of the available studies [21-24]. Narrative reviews often rely heavily on previous reviews [19], perhaps because it is difficult to conduct a narrative summary across many studies. Narrative reviews generally do not offer conclusions about the efficacy of interventions because evidence that appears contradictory is difficult to synthesize without quantitative integration [25,26]. This quantitative synthesis meets the current pressing need to integrate this large body of research to inform future research and facilitate behavior change theory development.

Few meta-analyses have examined PA outcomes following patient education interventions. Hillsdon, Foster, and Thorogood [27] synthesized across only 11 primary studies with healthy adults that reported PA outcomes. Conn et al. [11] synthesized intervention studies conducted with healthy and chronically ill aging adults. Ashworth, Chad, Harrison, Reeder, and Marshall [28] further limited their meta-analysis of studies conducted with older adults to comparisons between home- versus center-based interventions. Over a decade ago, Dishman and Buckworth [29] conducted the broadest meta-analysis across 127 studies of healthy and chronically ill adults and children. Fewer than 20% of the studies included in that study focused on persons with chronic illness. The authors reported that intervention effects sizes (ESs) were smaller among studies with chronically ill subjects than in studies with healthy subjects. In contrast, Conn et al. [11] reported that among studies of older adults, interventions targeting samples with specific chronic illnesses reported larger ESs than studies with diverse older adults. No comprehensive meta-analyses have been reported that address PA behavior following patient education interventions among adults with diverse chronic illnesses. This meta-analysis was designed to integrate primary study findings from interventions designed to increase PA behavior among adults with chronic illnesses.

This synthesis addressed the following questions (1) What are the overall effects of interventions to increase PA on PA behavior after interventions? (2) Do interventions' effects on PA behavior vary depending on characteristics of interventions, sample, or methodology? (3) For controlled trials, do control groups' post-test outcome measures different significantly from pre-test values?

2. Methods

We used standard quantitative review methods to identify and retrieve potential primary studies, determine study eligibility, reliably code data, synthesize results across primary studies, and interpret findings [30-35].

2.1 Inclusion Criteria

English-language reports of PA interventions among chronically ill subjects more than 18 years old were eligible for inclusion. We included studies with both an explicit intervention to increase PA and a measure of PA behavior following the intervention reported with adequate detail to calculate ESs. We included interventions broadly defined as patient education, that is planned activities which could include teaching, counseling, behavior modification, and exercise practice sessions which could influence subsequent PA behavior. We operationalized PA as any bodily movement that results in elevated energy expenditure beyond basal levels. Exercise, a subset of PA, was defined as structured, planned, and repetitive movement intended to increase fitness. A few studies addressed the broader construct of PA, though most targeted exercise.

Both published and unpublished studies were included. Meta-analyses that only include published studies are likely to overestimate the overall ES because the most consistent difference between published and unpublished studies is the statistical significance of the findings [36]. Small-sample studies were included to synthesize across the broad scope of investigations. Although these studies may lack statistical power, they can contribute important information from difficult-to-recruit subjects or innovative interventions [37]. We weighted studies so that smaller studies had proportionally less impact on aggregate findings. Pre-experimental studies with pre-intervention and post-intervention data to calculate ESs were included because some investigators find it unethical to withhold potentially beneficial treatments, and because novel interventions may be tested initially in these designs [38,39]. These pre-experimental studies were analyzed separately from two group comparisons. We were able to include a broader variety of studies by including studies with multiple designs.

2.2 Search Strategies

We used multiple search strategies to ensure a comprehensive search and widen the scope of studies beyond those identified in previously published reviews [36]. The broad searching was an important technique to avoid the bias resulting from narrow searches [37]. An experienced reference librarian conducted searches in MEDLINE, PsycINFO, EMBASE, CINAHL, Cochrane Controlled Trials Register, Database of Abstracts of Reviews of Effectiveness, Healthstar, Combined Health Information Database, Sport Discus, Dissertation Abstracts International, and Educational Resources Information Center. We searched the National Institutes of Health Computer Retrieval of Information on Scientific Projects (CRISP) data of funded studies back to 1973. To ensure comprehensive searches of computerized databases, we employed broad search terms for intervention (adherence, behavior therapy, clinical trial, compliance, counseling, evaluation, evaluation study, evidence-based medicine, health care evaluation, health behavior, health education, health promotion, intervention, outcome & process assessment, patient education, program, program development, program evaluation, self care, treatment outcome, validation study) and PA (exercise, physical activity, physical fitness, exertion, exercise therapy, physical education & training, walking). Computerized author database searches were conducted on principal investigators of funded studies and all authors of eligible studies. Senior authors of eligible studies were contacted to solicit additional papers. Ancestry searches were conducted on all eligible studies and previous reviews. We conducted hand searches for articles from 1970 (or initial year of publication) through 2004 in 215 journals where eligible studies were published, review papers were retrieved, or research team members suggested primary studies might be published. Internet searches were conducted but did not yield any primary studies not located through other mechanisms.

2.3 Data Coding

We developed, pilot tested, and refined a coding frame to record results of primary studies and characteristics of sources, study participants, study methods, and interventions. Source characteristics include presence of funding, dissemination vehicle, and year of distribution. Gender, minority, age, socio-economic status, and medical diagnoses were coded to describe subjects. Interventions could include motivational/educational sessions and/or supervised exercise sessions. Because supervised exercise sessions are a common health behavior change intervention with chronically ill adults, details of supervised exercise sessions were coded as available in study reports (intensity, duration, frequency per week, weeks of supervised exercise). Coded intervention attributes include intervention social context (group vs. individual), weeks over which the intervention was delivered, behavioral target (PA only vs. multiple health behaviors including PA), recommended duration of exercise sessions, recommended exercise frequency per week, recommended form of exercise, and several intervention content attributes (Table 1). We coded data at a micro-level with very specific details to enhance coder reliability. Coding specific details was appropriate because universal definitions of broad categories of interventions (e.g. self-management) are not available. We recorded PA behavior only if the PA measure clearly was separated from any intervention supervised exercise sessions (e.g. cardiac rehabilitation participation). The most distal data collection point was used to calculate ESs since enduring PA behavior changes will most likely lead to health benefits. To establish reliability, two extensively trained coders independently extracted all data. The senior author or other member of the research team resolved any coding discrepancies.

Table 1
Intervention Content Reported by More than 10 of the Studies*

2.4 Data Management and Analyses

We used standard meta-analytic approaches for data calculations. We calculated a standardized mean difference (d) as each comparison's ES. More favorable outcome scores for treatment groups or at post-test are reflected in a positive d. We analyzed single treatment group pre- and post-intervention ESs separately from two-group ESs, but expressed both types of ESs in the raw-score metric to facilitate comparisons. Although both random- and fixed-effects analyses were conducted, we present only random-effects analyses. See Table 2 for details of statistical analyses.

Table 2
Statistical Management of Data

Between-study ES homogeneity was assessed using a conventional heterogeneity statistic (Q). Heterogeneity was expected because it is very common among studies of educational and behavior interventions and in studies with diverse methodologies [40]. Recent Cochrane reviews of behavioral interventions have accepted heterogeneity and reported management strategies consistent with our approach [40-43]. We emphasize the random-effects analyses because it is a heterogeneous model that takes into account heterogeneity not fully explained by moderators. The random-effects analyses present a location parameter (mean ES) and quantify residual heterogeneity in a variance component [44]. We explored potential study-level moderators to understand potential sources of heterogeneity [41,44-48]. Finally, we interpreted our findings in the context of heterogeneity discovered. Interpreting the extent to which heterogeneity affects conclusions is more valuable than merely testing for the presence of heterogeneity [45]. Interested readers may consult Conn, Hafdahl, Mehr, LeMaster, Brown, and Nielsen [30] for a more detailed rationale for synthesizing across heterogeneous studies.

We conducted exploratory moderator analyses for two-group comparisons. Moderators were selected based on availability in primary reports and our ability to reliably code the attribute. We could not analyze many of the intriguing potential moderators because primary studies reported them infrequently. For example, we could not effectively analyze the impact of interventions based on social cognitive theory because reports provide too little information about conceptual frameworks and papers that claim to be based on particular theories often provide little evidence that the intervention is consistent with the theory. We grouped interventions into behavior and cognitive categories but did not make other groupings, such as self-management training, because universal definitions are not available and studies often provide insufficient information to accurately categorize studies. Because little previous research has provided a foundation for confirmatory hypothesis testing, the moderator analyses are intended as a hypothesis-generating contribution.

3. Results

A total of 213 samples including 22,557 subjects from 163 reports were eligible for the meta-analysis (numbers of subjects should be considered close approximations, given vagaries of primary-study reporting) [55-217]. We calculated independent groups ESs for 17,147 subjects in 129 samples from 105 reports. Pre-post treatment group comparisons were calculated for 146 samples, which included 9,275 subjects from 107 reports. A total of 3,218 subjects from 59 samples reported in 56 papers were included in the pre-post analysis of control subjects. Most reports were published articles, though some dissertations or theses (s=18) were included as well as a few presentation reports (s=4) and one book chapter (s=number reports, k=number comparisons). Most reported on studies with financial support (s=111). Only 21 reports appeared before 1990, and 73 were disseminated in 2000 or more recently.

Studies recruited samples with diverse chronic illnesses: mixed medically and surgically managed cardiac diseases (s=22), hypertension (s=10), peripheral vascular disease (s=11), myocardial infarction (s=10), coronary artery disease (s=12), coronary artery bypass graft (s=6), heart failure (s=6), mixed medically managed cardiac diseases (s=2), coronary angioplasty (s=1), type 2 diabetes (s=22), type 1 diabetes (s=6), mixed diabetes subjects (s=4), rheumatoid arthritis (s=9), osteoarthritis (s=8), heterogeneous arthritis (s=9), osteoporosis (s=5), breast cancer (s=4), gastrointestinal cancer (s=1), renal disease (s=2), chronic obstructive pulmonary disease (s=2), Parkinson's disease (s=1), multiple sclerosis (s=1), fibromyalgia (s=1), chronic fatigue syndrome (s=1), chronic back problems (s=1), mixed unspecific musculoskeletal diseases (s=1), hypopituitarism (s=1), and mixed chronic illnesses (s=15). Although not well reported, many studies did not exclude subjects with the co-morbidities commonly associated with the chronic illness target population. Further details about subjects with diabetes, cancer, arthritis, and cardiac disease are available in previous publications reporting on health outcomes among these studies [30,31,35,218-220].

Plots depicting ESs of PA versus sampling variance suggested the absence of studies with low or negative ESs for treatment group versus control group comparisons and for treatment group pre-post comparisons. Although this is consistent with a publication bias against non-significant or negative results, it may also arise from phenomena such as certain patterns of heterogeneity [221]. There was no evidence of publication bias for comparison group pre-post ES plots.

3.1 Primary study characteristics

Descriptive statistics for primary study characteristics are displayed in Table 3. Sample size varied extensively from 4 to 1173 subjects, with a median of 62 subjects. The median value for mean age was 59 years. Typically, almost half of the subjects were women, among studies that reported gender distribution. Minority inclusion was often not reported: 33 reports indicated including African Americans, 10 included Hispanics, and 2 included Native Americans. Only four papers reported on predominantly (50% or more) African-American subjects, only one on predominantly Hispanic subjects, and none on predominantly Native-American subjects. A few studies experienced significant attrition, though losses were typically modest and were similar between treatment and control groups.

Table 3
Characteristics of Primary Studies Included in Combined-Illness Physical Activity Meta-Analyses

Tables 1 and and33 include intervention attributes. Supervised exercise was the most common PA behavior change strategy among the studies (s=88). Typical attributes among studies with supervised exercise included 2 weekly 60-minute sessions over 12 weeks. Fifty-four studies included some form of mediated motivational or educational intervention delivery (e.g. telephone, mail, Internet), and 13 used only mediated intervention delivery. Several studies asked subjects to monitor their PA behavior (s=66) as a strategy to increase PA. Fitness testing (s=57) and individualized exercise prescription (s=65) were common intervention components. Modeling, either by research staff members (s=33) or by people similar to subjects (s=40), was very common. Many studies asked subjects to generate specific PA behavioral goals (s=55) in an effort to change behavior. Fifty studies either taught problem-solving skills to subjects or included problem solving during contacts with the research staff. Monitoring of PA behavior by research staff was also common (s=39). Forty-three studies provided explicit feedback to subjects about their PA behavior. Twenty-eight studies either provided rewards for subjects for increasing PA or taught subjects to reward themselves for PA. Thirty-five studies attempted to increase social support for PA. Thirty-nine studies specifically dealt with barriers to PA as a strategy to increase activity. Strategies less frequently reported include stimulus/cues to PA (s=14), relapse prevention education (s=14), health risk appraisal (s=14), symptom monitoring and management (s=16), and contracting (s=16). Intervention content reported by 10 or fewer studies included decision making (s=9), commitment activities (s=8), thought restructuring (s=7), values clarification (s=7), exercise variation (s=5), cognitive modification (s=4), decisional balance (s=3), personal trainer (s=2), shaping (s=2), community development (s=1), emotional arousal (s=1), imagery (s=1), and motivational interviewing (s=1). Most studies delivered the same interventions to all subjects, only six interventions were individually tailored (intervention content to motivate PA behavior change individually modified in systematic manner), and only two were targeted (different interventions for subsets of samples).

3.2 Effect of Patient Education Interventions on PA Outcomes

Table 4 presents the overall effects of interventions. The overall mean effect in two-group studies was 0.45. The treatment group pre- vs. post-test mean ESs were 0.41 (ρ12=0.80) and 0.51 (ρ12=0.00). The treatment group versus control group comparison and both treatment group pre- vs. post-test comparisons demonstrated significant ES heterogeneity according to the homogeneity test (Q in table 3). These findings document that although intervention effects were highly variable, interventions resulted in improved PA behavior scores on average. In contrast, control subjects generally experienced no improvement, with ES estimates of 0 that yielded 95% confidence intervals between -0.07 and 0.07.

Table 4
Random-Effects Physical Activity Behavior Outcome Estimates and Tests

To enhance interpretability, mean ESs were transformed to minutes of PA per week and steps per day, using results from appropriate reference groups pooled across available studies. The mean effect in terms of the pooled treatment and control SD (106.7) is a raw mean difference of 48.0 (0.45 × 106.7) PA minutes per week. Relative to the pooled post-test mean of 116.4 minutes for control subjects, this translates to a mean of 164.4 minutes of PA per week among treatment subjects. For single-group pre-post comparisons, the minutes per week raw mean difference is 38.4 minutes (ρ12=0.80 assumption); relative to the pooled mean baseline of 92.5 minutes per week this translates into mean outcome 130.9 minutes per week. For steps per day, the mean effect in terms of the pooled treatment and control SD (2101) is a steps-per-day raw mean difference of 945 (2101 × .45). Relative to the pooled post-test mean of 6108 steps for control subjects, this translates to a mean of 7053 steps per day among treatment subjects for the two-group comparison. For single-group pre-post comparisons, the steps per day raw mean difference is 870 steps (ρ12=0.80 assumption); relative to the pooled mean baseline of 4254 steps this translates into mean outcome 5124 steps per day. The CLES for the two-group comparisons was 0.62, indicating that 62% of the time, a random treatment subject would have higher PA scores than a random control subject. For single-group comparisons the random-effects estimates would be translated to CLES of .64 and .74 for assumptions of a low and high pre-post association, respectively. The CLES for control subjects was .50 indicating these subjects were no more likely to have higher PA scores after interventions than before interventions.

3.3 Moderator Analyses

The results from the dichotomous and continuous moderator analyses for two-group comparisons are presented in Tables 5 and and6.6. Studies reported more recently yielded slightly smaller ESs than studies distributed earlier (β^1=-.009). Studies published in journals did not report significantly different ESs as compared to unpublished studies. Studies with funding reported significantly lower ESs (.41) than studies without funding (.60). Gender distribution, ethnic minority proportion, sample age, and socioeconomic characteristics of samples were unrelated to ESs. Neither random assignment of subjects, attrition, nor the length of the follow-up period between intervention completion and PA outcome measurement were related to ESs.

Table 5
Independent-Groups Post-test Comparisons: Dichotomous Moderator Analyses
Table 6
Linear Continuous Mixed-Effects Moderator Analyses for Physical Activity

Interventions that targeted only PA behavior (.57) reported larger ESs than those attempting to change multiple behaviors such as PA and diet (.38). Interventions with supervised exercise sessions were no more effective in changing PA than those that relied exclusively on educational or motivational sessions. Individually tailored interventions were not associated with larger ES than more traditional interventions where all subjects receive the same content. The presence of mediated delivery (e.g. telephone, mail) was unrelated to ESs. Interventions were similarly effective regardless of whether they were delivered to individuals or groups.

Interventions based on social cognitive theory, the most commonly reported conceptual foundation for interventions, were unrelated to ESs. Studies of interventions based on the transtheoretical model reported significantly smaller ESs (.22) than studies that did not use this framework (.48). Studies that used any behavioral strategy (e.g. consequences, contracting, feedback, goal setting, self-monitoring, stimulus/cues, personal trainer) to increase PA reported larger ESs (.51) than studies that did not use any behavioral strategies. Studies that used exclusively behavioral strategies (.53) reported larger ESs than studies that did not consist entirely of behavioral intervention (.40). In contrast, the presence or absence of cognitive strategies (barriers management, decisional balance, motivational counseling, problem solving, social cognitive theory) was not associated with ESs. The difference between studies using only cognitive strategies (.10) versus those using cognitive strategies plus other strategies (.47) did not achieve statistical significance. Neither the number of cognitive strategies nor the number of behavioral strategies in interventions was related to ESs. Studies that directed subjects to self-monitor their PA behavior reported significantly larger ESs (.56) than studies that did not promote self-monitoring (.40). Other intervention content potential moderators were unrelated to ESs: barriers management, consequences, contracting, exercise prescription, feedback, fitness testing, goal setting, problem solving, and stimulus/cues. The number of strategies in the intervention did not predict ESs. Neither the weeks over which the intervention was delivered nor the amount of contact time between intervention staff and subject were related to the ESs of PA. The nature of the PA recommended to subjects (specific forms, intensities, minutes/week) was unrelated to PA behavior outcomes. Contact the senior author for information about associations among moderators and moderator analyses of treatment group pre-post comparisons.

The moderators reported above and in Tables 5 and and66 all involve single-df moderator effects. Multiple-df moderator analyses were conducted on a few moderator variables for independent group ESs. This entailed testing either one moderator with more than two levels or two dichotomous moderators, the latter of which permits examining moderator interactions. The ESs of PA differed significantly by type of chronic illness (Qbetween=9.1). The largest ES was for arthritis (.61), followed by diabetes (.49) and cardiac (.40). The smallest ES was among studies of cancer patients (-.03). The single moderator analyses we report for behavioral and cognitive strategies was supported in a multiple moderator analyses (Qbetween=10.5). The analyses found the largest ES for studies with only behavioral strategies (.53) followed by studies with both behavioral and cognitive intervention (.50). ESs were smallest among studies with cognitive strategies and no behavioral intervention (.10).

4. Discussion and Conclusion

4.1 Discussion

This is the first meta-analysis to examine PA behavior following patient education interventions designed to increase PA among diverse chronically ill populations. Our extensive search strategies successfully located a sizable and diverse literature. A moderate overall ES was calculated. The overall ES is between the values previously reported for older adults and for predominantly healthy adults [11,29]. In subgroup analyses, Dishman and Buckworth reported considerably smaller ESs for the few studies they included of people with cardiac disease. These differences probably reflect population differences among the primary studies. Few primary studies included in this meta-analysis were included in the previously reported syntheses.

The calculated differences in PA minutes per week (164.4 vs. 116.4) and in steps per day (7053 vs. 6108) are clinically meaningful for adults with many chronic illnesses. Although the treatment subjects generally did not achieve the 10,000 steps/day commonly recommended for healthy adults [222,223], the PA dose necessary to achieve health outcomes has not been definitively documented for adults with chronic illness. It is unclear whether people gain the greatest health benefits from initial increases in PA above sedentary rates or from moving from moderate levels of PA to more active levels. The amount of increase is clear evidence that some interventions are effective in changing PA behavior. The extent of heterogeneity documents that not all interventions are equally effective.

Our exploratory moderator analyses documented some intriguing findings. Since the moderator analyses were designed to be hypothesis generating, these findings should be explored in further primary research. The largest ESs came from patient education interventions that were designed exclusively to change PA behavior, as compared to those focused on multiple health behaviors. These findings about effectiveness of PA-only interventions are consistent with a previous meta-analysis of interventions to increase PA among healthy and chronically ill older adults [11]. It may be easier to change one behavior at a time. Chronically ill adults may feel overwhelmed when asked to make multiple changes simultaneously. This finding is for PA behavior outcomes and may not extend to health outcomes. For example, a study of adults with type 1 diabetes found better metabolic control outcomes when interventions focused on multiple diabetes-related health behaviors [218]. In contrast, a previous meta-analysis of people with type 2 diabetes found better metabolic control outcomes when interventions targeted only PA behavior [30]. Attempts to change multiple behaviors may be appropriate when the health benefits of some combination of behavior changes are more important than changes achieved by changing only one behavior. We need further primary research which examines both behavior change and health outcomes of interventions which target single behaviors as compared to those which encourage changing multiple behaviors [224].

The moderator analyses provide evidence that patient education interventions were similarly effective regardless of gender, age, minority, and socioeconomic status. Differences in the ESs of PA among the major categories of chronic illnesses were interesting. Subjects recruited because they had arthritis were the most likely to increase their PA, despite possible immediate arthritis-related physical discomfort associated with doing so. It is possible that arthritis symptoms improve after establishing a PA program, which reinforced PA behavior. People recruited because they had diabetes and cardiac disease improved their PA, though less dramatically. With increased PA, people with diabetes may experience improved blood glucose levels and people with cardiac disease may increase fitness while delaying progression of cardiac disease. These objective health outcomes are clearly important, but they may be less perceptible and persuasive thus providing less motivation to continue PA. Further primary research which tests behavior changes, symptom outcomes, and health consequences of interventions is needed. These findings should be interpreted with the understanding that most studies in this meta-analysis did not exclude subjects with co-morbidities. Subjects recruited for a specific illness often had other diseases as well (e.g. diabetes and cardiac disease is a common combination). Co-morbidities were too infrequently reported to be included in the analyses.

Supervised exercise was the most common intervention strategy, but our moderator analyses revealed that it worked no better than educational/motivational sessions. These findings are consistent with previous meta-analyses of older adults and predominantly healthy adults [11,29]. Supervised exercise is an expensive intervention because it requires specialized facilities and equipment as well as highly trained personnel. For some chronically ill populations or subpopulations (e.g. severe heart failure), supervised exercise may be useful for safety or other reasons.

In our moderator analyses, self-monitoring of PA behavior was associated with larger ESs. A previous meta-analysis of interventions with older adults also found self-monitoring an effective strategy [11]. Self-monitoring provides subjects with real-time information and may increase their awareness of existing behavior as well as changes in behavior. Self-monitoring is an inexpensive strategy. Most other single intervention strategies were not associated with differences in ESs.

The findings regarding behavioral versus cognitive categories of interventions were interesting in light of previous research. These findings are consistent with two previous meta-analyses of healthy and older adults that reported behavior strategies were effective in changing PA [11,29]. Mass media attention to the importance of PA may have raised subjects' consciousness of its value. People may need more behavior change strategies to successfully change PA behavior. Interventions which were found to be effective included varying combinations of goal setting, contracting, feedback, consequences, self-monitoring, and/or prompts. Intervention content that this meta-analysis found to be unrelated to PA behavior change includes decisional balance activities, problem solving, barriers management, motivational counseling, or an emphasis on self-efficacy and outcome expectancy. Future intervention tests that directly compare combinations of behavioral and cognitive strategies are necessary to provide direction for practice. Further primary research which examines mediators of behavior change would help clarify the links between intervention components and outcomes. When considerably more primary research is available, future meta-analyses may be able to address the specific constellation of intervention components that when grouped together make the largest changes in PA behavior.

We were unable to directly address specific theoretical frameworks for several reasons. First, studies often use selected components or language commonly associated with particular theories but fail to name the theory or cite theorists. Thus decisions about including these studies would rely on considerable coder attribution that may not be justified. Conceptual frameworks that address health behavior change have many overlapping constructs. For example, self-efficacy constructs are found in social cognitive theory, the theory of planned behavior, and the transtheoretical model. Some primary reports describe interventions as based on multiple theories. Interventions often only partially implement theoretical frameworks. For example, some studies claim social cognitive theory origins but do not address the sources of self-efficacy. Setting criteria for when interventions are based on the theoretical model would depend entirely on research team opinions and would be difficult to operationalize (e.g. does an intervention need to address three of the four sources of self-efficacy to be based on social cognitive theory?). Given current reporting practices, it is unclear if future quantitative syntheses will be able to fully address conceptual frameworks.

We conducted the first reported analyses of joint moderators and found that this may be effective for discovering patterns among studies (e.g. exercise prescription and fitness testing; age and weeks of intervention, interactions between random allocation and other moderators). Relationships among moderators may be complex. Unfortunately, too little is understood about PA behavior change to suggest meaningful directions for these analyses at this time. This will be an important strategy, after many more primary studies are available, to detect the grouping of intervention strategies that combine to make the most effective intervention.

The methodological findings provide a context for interpreting future studies. ESs were similar between single- and two-group comparisons, though there are many reasons to prefer findings from two-group studies. Previous meta-analyses have not reported ESs for control groups. We found that, on average, the PA behavior of control subjects did not change. Thus, researcher used methods for collecting PA data and delivering information to controls generally did not change PA behavior. We were somewhat surprised to find that attrition was unrelated to ESs, given the folk wisdom that subjects who are not exercising are the most likely to drop out of PA studies. Since no previous meta-analysis has examined attrition, future quantitative syntheses should address this whenever examining health behavior change outcomes. The finding that unfunded studies reported larger ESs is interesting. Unfunded studies may differ in ways other than funding status. For example, unfunded studies may include particularly powerful or novel interventions that researchers pilot tested prior to requesting funding.

These findings should be interpreted within the limitations of this meta-analysis. Funnel plots suggested potential publication bias. It remains unclear whether investigators do not attempt to publish or are unable to publish findings from studies without statistically significant intervention effects [37]. We expected the findings of considerable heterogeneity. These should stimulate continued research to determine which primary study features (e.g. sample, intervention, or design attributes) account for differences among studies. Findings of moderator analyses must be interpreted cautiously in the presence of significant heterogeneity. We do not know the extent to which primary study samples represent populations of chronically ill adults. It is possible that, with safety in mind, investigators recruited participants who were less ill and perhaps more physically active [225]. It is also possible that less active subjects were purposefully recruited [225]. Many important features of studies, such as treatment fidelity, were unreported and thus we could not analyze them. Important potential subject characteristic moderators could not be analyzed because they were infrequently reported. For example, co-morbid medical conditions and mental health issues (e.g. depression) are infrequently reported in primary research but could be important moderators of intervention effects. Systematic testing of findings from moderator analyses from future studies will be important.

4.2 Conclusion

Overall, our quantitative synthesis documented moderate PA behavior effects following diverse patient educational interventions. PA is especially important for adults with chronic illnesses because it may delay progression of some chronic illnesses and manage symptoms of others. Our exploratory moderator analyses have suggested directions for future research. In order to increase knowledge about effective patient education interventions, it is essential to continue conducting new primary research studies as well as quantitative syntheses.

4.3 Practice Implications

Our findings document that patient education intervention can increase PA but that not all interventions are effective. Careful outcome assessments of programs are essential. Patient education programs may be effective across gender, age, and income varied subjects, though adults with diabetes or cardiac disease may be less likely to change their behavior than those with arthritis. The suggestive moderator analyses found associations between PA behavior change and interventions that target only PA behavior, include self-monitoring, and emphasize behavioral strategies such as goal setting, contracting, feedback, consequences, and/or cues. The analyses found that interventions that do not include supervised exercise were as effective as interventions with this more costly component. The importance of increasing PA among many chronically ill adults justifies continuing to develop diverse patient education efforts.

Acknowledgments

Financial support provided by a grant from the National Institutes of Health (R01NR07870) to Vicki Conn, principal investigator.

Footnotes

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Contributor Information

Vicki S. Conn, University of Missouri, Columbia, MO, USA 65211.

Adam R. Hafdahl, Washington University.

Sharon A. Brown, University of Texas.

Lori M. Brown, University of Missouri.

References

1. Kroeze W, Werkman A, Brug J. A systematic review of randomized trials on the effectiveness of computer-tailored education on physical activity and dietary behaviors. Ann Behav Med. 2006;31:205–23. [PubMed]
2. Eakin EG, Glasgow RE, Riley KM. Review of primary care-based physical activity intervention studies: effectiveness and implications for practice and future research. J Fam Practice. 2000;49:158–68. [PubMed]
3. Eden KB, Orleans CT, Mulrow CD, Pender NJ, Teutsch SM. Does counseling by clinicians improve physical activity? A summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2002;137:208E–215E. [PubMed]
4. Lawlor DA, Hanratty B. The effect of physical activity advice given in routine primary care consultations: A systematic review. J Public Health Med. 2001;23:219–26. [PubMed]
5. Morey MC, Sullivan RJ. Medical assessment for health advocacy and practical strategies for exercise initiation. Am J Prev Med. 2003;25(3) 2:204–8. [PubMed]
6. Humpel N, Owen N, Leslie E. Environmental factors associated with adults' participation in physical activity: A review. Am J Prev Med. 2002;22:188–99. [PubMed]
7. Li F, Bauman A, Ory MG, Chodzko-Zajko W. Neighborhood influences on physical activity in middle-aged and older adults: A multilevel perspective. J Aging Phys Activ. 2005;13:87–114. [PubMed]
8. Marcus BH, Owen N, Forsyth LH, Cavill NA, Firdinger F. Physical activity interventions using mass media, print media, and information technology. Am J Prev Med. 1998;15:362–78. [PubMed]
9. Dunn AL, Andersen RE, Jakicic JM. Lifestyle physical activity interventions. History, short- and long-term effects, and recommendations. Am J Prev Med. 1998;15:398–412. [PubMed]
10. Matson-Koffman DM, Brownstein JN, Neiner JA, Greaney ML. A site-specific literature review of policy and environmental interventions that promote physical activity and nutrition for cardiovascular health: What works? Am J Health Promot. 2005;19:167–93. [PubMed]
11. Conn V, Valentine J, Cooper H. Interventions to increase physical activity among aging adults: A meta-analysis. Ann Behav Med. 2002;24:190–200. [PubMed]
12. Van Der Bij AK, Laurant MG, Wensing M. Effectiveness of physical activity interventions for older adults: A review. Am J Prev Med. 2002;22:120–33. [PubMed]
13. American College of Sports Medicine. Physical activity programs and behavior counseling in older adult populations. Med Sci Sport Exer. 2004;36:1997–2003. [PubMed]
14. Banks-Wallace J, Conn V. Interventions to promote physical activity among African American women. Public Health Nurs. 2002;19:321–35. [PubMed]
15. Burnet DL, Elliott LD, Quinn MT, Plaut AJ, Schwartz MA, Chin MH. Preventing diabetes in the clinical setting. J Gen Intern Med. 2006;21:84–93. [PMC free article] [PubMed]
16. Coble JD, Rhodes RE. Physical activity and Native Americans: A review. Am J Prev Med. 2006;31:36–46. [PubMed]
17. Cress ME, Buchner DM, Prohaska T, Rimmer J, Brown M, Macera C, Dipietro L, Chodzko-Zajko W. Best practices for physical activity programs and behavior counseling in older adult populations. J Aging Phys Activ. 2005;13:61–74. [PubMed]
18. Cunningham GO, Michael YL. Concepts guiding the study of the impact of the built environment on physical activity for older adults: A review of the literature. Am J Health Promot. 2004;18:435–43. [PMC free article] [PubMed]
19. Marcus BH, Williams DM, Dubbert PM, Sallis JF, King AC, Yancey AK, Franklin BA, Buchner D, Daniels SR, Clayton RP. Physical Activity Intervention Studies, what we know and what we need to know. A scientific statement from the American Heart Association Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity); Council on Cardiovascular Disease in the Young; and the Interdisciplinary Working Group on Quality of Care and Outcomes Research. Circulation. 2006;114:2739–52. [PubMed]
20. Adams J, White M. Are activity promotion interventions based on the transtheoretical model effective? A critical review. Brit J Sport Med. 2003;37:106–114. [PMC free article] [PubMed]
21. Epstein LH, Roemmich JN. Reducing sedentary behavior: Role in modifying physical activity. Exerc Sport Sci Rev. 2001;29:103–8. [PubMed]
22. Laitakari J, Miilunpalo S. How can physical activity be changed--basic concepts and general principles in the promotion of health-related physical activity. Patient Educ Couns. 1998;33(1 Suppl):47S–49S. [PubMed]
23. Nupponen R. What is counseling all about--basics in the counseling of health-related physical activity. Patient Educ Couns. 1998;33(1 Suppl):61S–67S. [PubMed]
24. Rinne M, Toropainen E. How to lead a group--practical principles and experiences of conducting a promotional group in health-related physical activity. Patient Educ Couns. 1998;33(1 Suppl):69S–76S. [PubMed]
25. Dunn AL. Getting started--a review of physical activity adoption studies. Brit J Sport Med. 1996;30:193–9. [PMC free article] [PubMed]
26. Kahn EB, Ramsey LT, Brownson RC, Heath GW. The effectiveness of interventions to increase physical activity. A systematic review. Am J Prev Med. 2002;22(4 Suppl):73–107. [PubMed]
27. Hillsdon M, Foster C, Thorogood M. Interventions for promoting physical activity. Cochrane Db Syst Rev. 2005;(1):CD003180. [PubMed]
28. Ashworth NL, Chad KE, Harrison EL, Reeder BA, Marshall SC. Home versus center based physical activity programs in older adults. Cochrane Db Syst Rev. 2005;(1):CD00401. [PubMed]
29. Dishman RK, Buckworth J. Increasing physical activity: A quantitative synthesis. Med Sci Sport Exer. 1996;28:706–19. [PubMed]
30. Conn V, Hafdahl A, Mehr D, LeMaster J, Brown S, Nielsen P. Meta-analysis of metabolic effects of interventions to increase exercise among adults with type 2 diabetes. Diabetologia. 2007;50:913–21. [PubMed]
31. Conn V, Hafdahl A, Porock D, McDaniel R, Nielsen P. A meta-analysis of exercise interventions among people treated for cancer. Support Care Cancer. 2006;14:699–712. [PubMed]
32. Cooper H, Hedges L, editors. The handbook of research synthesis. New York: Russell Sage Foundation; 1994.
33. Hedges L, Olkin I. Statistical methods for meta-analysis. Orlando: Academic Press; 1985.
34. Morris SB. Distribution of the standardized mean change effect size for meta-analysis on repeated measures. Brit J Math Stat Psy. 2000;53:17–29. [PubMed]
35. Nielsen P, Hafdahl A, Conn V, LeMaster J, Brown S. Meta-analysis of the effect of exercise interventions on fitness outcomes among adults with type 1 and type 2 diabetes. Diabetes Res Clin Pr. 2006;74:111–20. [PubMed]
36. Conn V, Isamaralai S, Rath S, Jantarakupt P, Wadhawan R, Dash Y. Beyond MEDLINE for literature searches. J Nurs Scholarsh. 2003;35:177–82. [PubMed]
37. Conn V, Valentine J, Cooper H, Rantz M. Grey literature in meta-analyses. Nurs Res. 2003;52:256–61. [PubMed]
38. Brown SA, Upchurch S, Anding R, Winter M. Promoting weight loss in type II diabetes. Diabetes Care. 1996;19:613–24. [PubMed]
39. Dusseldorp E, Van Elderen T, Maes S, Meulman J, Kraaij V. A meta-analysis of psychoeducational programs for coronary heart disease patients. Health Psychol. 1999;18:506–19. [PubMed]
40. Little JH, Popa M, Forsythe B. Multisystemic therapy for social, emotional, and behavioral problems in youth aged 10-17. Cochrane Db Syst Rev. 2005;(3):CD004797. [PubMed]
41. Merry S, McDowell H, Hetrick S, Bir J, Muller N. Psychological and/or educational interventions for the prevention of depression in children and adolescents. Cochrane Db Syst Rev. 2004;(1):CD003380. [PubMed]
42. Norris SL, Zhang X, Avenell A, Gregg E, Schmid CH, Lau J. Long-term non-pharmacological weight loss interventions for adults with prediabetes. Cochrane Db Syst Rev. 2005;(2):CD005270. [PubMed]
43. Royal ST, Kendrick D, Coleman T. Non-legislative interventions for the promotion of cycle helmet wearing by children. Cochrane Db Syst Rev. 2005;(2):CD003985. [PubMed]
44. Colditz GA, Burdick E, Mosteller F. Heterogeneity in meta-analysis of data from epidemiologic studies: A commentary. Am J Epidemiol. 1995;142:371–82. [PubMed]
45. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analysis. Brit Med J. 2003;327:557–60. [PMC free article] [PubMed]
46. Berlin JA. Invited commentary: Benefits of heterogeneity in meta-analysis of data from epidemiologic studies. Am J Epidemiol. 1995;142:383–7. [PubMed]
47. Lipsey M, Wilson D. Practical meta-analysis. Thousand Oaks: Sage; 2001.
48. Lipsey M, Wilson D. The way in which intervention studies have “personality” and why it is important to meta-analysis. Eval Health Prof. 2001;24:236–54. [PubMed]
49. Morris SB, DeShon RP. Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs. Psychol Methods. 2002;2:105–125. [PubMed]
50. Gleser LJ, Olkin I. Stochastically dependent effect sizes. In: Cooper H, Hedges L, editors. The handbook of research synthesis. New York: Russell Sage Foundation; 1994. pp. 339–355.
51. Vevea JL, Hedges LV. A general linear model for estimating effect size in the presence of publication bias. Psychometrika. 1995;60:419–435.
52. Kline RB. Beyond significance testing: reforming data analysis methods in behavioral research. Washington, DC: American Psychological Association; 2004.
53. Hedges L. Fixed effects models. In: Cooper H, Hedges L, editors. The handbook of research synthesis. New York: Russell Sage Foundation; 1994. pp. 285–299.
54. Raudenbush SW. Random effects models. In: Cooper H, Hedges L, editors. The handbook of research synthesis. New York: Russell Sage Foundation; 1994. pp. 301–321.
55. Agurs-Collins TD, Kumanyika SK, Ten Have TR, Adams-Campbell LL. A randomized controlled trial of weight reduction and exercise for diabetes management in older African-American subjects. Diabetes Care. 1997;20:1503–1511. [PubMed]
56. Allen J. Coronary risk factor modification in women after coronary artery bypass surgery. Nurs Res. 1996;45:260–265. [PubMed]
57. Allison MJ. The effect of a social cognitive theory-based intervention on self-efficacy and physical activity in older adults post coronary event [Dissertation] San Antonio, TX: University of Texas; 2000.
58. Allison T, Farkouh M, Smars P, Evans R, Squires R, Gabriel S, Kopecky S, Gibbons R, Reeder G. Management of coronary risk factors by registered nurses versus usual care in patients with unstable angina pectoris. Am J Cardiol. 2000;86:133–138. [PubMed]
59. Allison TG, Squires RW, Johnson BD, Gau GT. Achieving National Cholesterol Education Program goals for low-density lipoprotein cholesterol in cardiac patients: importance of diet, exercise, weight control, and drug therapy. Mayo Clin Proc. 1999;74:466–473. [PubMed]
60. Appel LJ, Champagne CM, Harsha DW, Cooper LS, Oberzanek E, Elmer PJ, Stevens VJ, Vollmer WM, Lin PH, Svetkey LP, Stedman SW, Young DR. Effects of comprehensive lifestyle modification on blood pressure control: main results of the PREMIER clinical trial. JAMA. 2003;289:2083–2093. [PubMed]
61. Arroll B, Beaglehole R. Salt restriction and physical activity in treated hypertensives. N Z Med J. 1995;108:266–268. [PubMed]
62. Baker KR, Nelson ME, Felson DT, Layne JE, Sarno R, Roubenoff R. The efficacy of home based progressive strength training in older adults with knee osteoarthritis: a randomized controlled trial. J Rheumatol. 2001;28:1655–1665. [PubMed]
63. Barlow JH, Turner AP, Wright CC. A randomized controlled study of the Arthritis Self-Management Programme in the UK. Health Educ Res. 2000;15:665–680. [PubMed]
64. Barnason S, Zimmerman L, Nieveen J, Schmaderer M, Carranza B, Reilly S. Impact of a home communication intervention for coronary artery bypass graft patients with ischemic heart failure on self-efficacy, coronary disease risk factor modification, and functioning. Heart Lung. 2003;32:147–158. [PubMed]
65. Beebe C, Fischer B, McCracken S. Lifestyle change: a new approach to treatment of obese type II diabetes? Diabetes. 1984;24 6A
66. Bengtsson K. Rehabilitation after myocardial infarction. A controlled study. Scand J Rehabil Med. 1983;15:1–9. [PubMed]
67. Bennett R, Burckhardt C, Clark S, O'Reilly C, Wiens A, Campbell S. Group treatment for fibromyalgia: a 6 month outpatient program. J Rheumatol. 1996;23:521–528. [PubMed]
68. Bielamowicz M, Miller W, Elkins E, Ladeqig H. Monitoring behavioral changes in diabetes care with the diabetes self-management record. Diabetes Educ. 1995;21:426–431. [PubMed]
69. Bock BC, Carmona-Barros RE, Esler JL, Tilkemeier PL. Program participation and physical activity maintenance after cardiac rehabilitation. Behav Modif. 2003;27:37–53. [PubMed]
70. Bock B, Albrecht A, Traficante R, Clark M, Pinto B, Tilkemeier P, Marcus B. Predictors of exercise adherence following participation in a cardiac rehabilitation program. Int J Behav Med. 1997;4:60–75. [PubMed]
71. Brus HL, van de Laar M, Taal E, Rasker J, Wiegman O. Effects of patient education on compliance with basic treatment regimens and health in recent onset active rheumatoid arthritis. Ann Rheum Dis. 1998;57:146–151. [PMC free article] [PubMed]
72. Burge MR, Hewes H, Araiza P, Gashytewa C. Efficacy of a pedometer based physical activity program on parameters of diabetes control in type 2 diabetes; American Diabetes Association Scientific Session; Boston. 2002. [PubMed]
73. Campbell NC, Ritchie LD, Thain J, Deans HG, Rawles JM, Squair JL. Secondary prevention in coronary heart disease: a randomised trial of nurse led clinics in primary care. Heart. 1998;80:447–452. [PMC free article] [PubMed]
74. Cantagallo A, Cignetti A, Garbuio B, Giancotta V. How long does the efficacy of therapeutic education last? Four-year-follow up; Paper presented at the 18th International Diabetes Federation Congress; 2003.
75. Carlsson R, Lindberg G, Westin L, Israelsson B. Influence of coronary nursing management follow up on lifestyle after acute myocardial infarction. Heart. 1997;77:256–259. [PMC free article] [PubMed]
76. Castaneda C, Layne JE, Munoz-Orians L, Gordon PL, Walsmith J, Foldvari M, Roubenoff R, Tucker K, Nelson M. A randomized controlled trial of progressive resistance exercise training to improve glycemic control in older adults with type 2 diabetes. Diabetes Care. 2002;25:2335–2341. [PubMed]
77. Clark M, Hampson SE, Avery L, Simpson R. Effects of a tailored lifestyle self-management intervention in patients with Type 2 diabetes. Br J Health Psychol. 2004;9:365–379. [PubMed]
78. Conn V, Burks K, Minor M, Mehr D. Randomized trial of two interventions to increase older women's exercise. Am J Health Behav. 2003;27:380–388. [PubMed]
79. Courneya KS, Friedenreich CM, Quinney HA, Fields AL, Jones LW, Fairey AS. A randomized trial of exercise and quality of life in colorectal cancer survivors. Eur J Cancer Care. 2003;12:347–357. [PubMed]
80. Cox N, Hendricks J, Binkhorst R, van Herwaarden C. A pulmonary rehabilitation program for patients with asthma and mild chronic obstructive pulmonary disease. Lung. 1993;171:235–244. [PubMed]
81. Cupples ME, McKnight A. Randomised controlled trial of health promotion in general practice for patients at high cardiovascular risk. Br Med J. 1994;309:993–996. [PMC free article] [PubMed]
82. DeVellis BM, Blalock SJ, Hahn PM, DeVellis RF, Hochbaum G. Evaluation of a problem-solving intervention for patients with arthritis. Patient Educ Couns. 1988;11:29–42.
83. Dilsen G, Berker C, Oral A, Varan G. The role of physical exercise in prevention and management of osteoporosis. Clin Rheumatol. 1989;8:70–75. [PubMed]
84. Djuric Z, DiLaura NM, Bradley E, Hryniuk W. Weight loss intervention in African American breast cancer survivors. Presented at Amer Soc Prev Oncolog; 2003.
85. Dolansky MA. Effects of cardiac rehabilitation on older adults' recovery outcomes following coronary artery bypass surgery [Dissertation] Cleveland, OH: Case Western Reserve University; 2001.
86. Dubbert P, Cooper K, Kirchner K, Meydrech E, Bilbrew D. Effects of nurse counseling on walking for exercise in elderly primary care patients. J Gerontol. 2002;57A:M733–M740. [PubMed]
87. Duncan K, Pozehl B. Effects of an exercise adherence intervention on outcomes in patients with heart failure. Rehabil Nurs. 2003;28:117–122. [PubMed]
88. Dunstan DW, Daly RM, Owen N, Jolley D, De Courten M, Shaw J, Zimmet P. High-intensity resistance training improves glycemic control in older patients with type 2 diabetes. Diabetes Care. 2002;25:1729–1736. [PubMed]
89. Engelhart M, Kondrup J, Hoie LH, Andersen V, Kristensen JH, Heitmann BL. Weight reduction in obese patients with rheumatoid arthritis, with preservation of body cell mass and improvement of physical fitness. Clin Exp Rheumatol. 1996;14:289–293. [PubMed]
90. Erdman R, Duivenvoordent H, Verhage F. Predictability of beneficial effects in cardiac rehabilitation: a randomized clinical trial of psychosocial variables. J Cardiopulm Rehabil. 1986;6:206–213.
91. Ersek M, Turner J, McCurry S, Gibbons L, Kraybill B. Efficacy of a self-management group intervention for elderly persons with chronic pain. Clin J Pain. 2003;19:156–167. [PubMed]
92. French SL. The self-management of osteoarthritis in older women: a study of the efficacy of the Arthritis Self-Management Program and of the factors influencing outcomes. Queen's University; Kingston, Ontario: 1996.
93. Fries JF, Carey C, McShane DJ. Patient education in arthritis: randomized controlled trial of a mail-delivered program. J Rheumatol. 1997;24:1378–1383. [PubMed]
94. Gaede P, Beck M, Vedel P, Petersen O. Limited impact of lifestyle education in patients with Type 2 diabetes mellitus and microalbuminuria: results from a randomized intervention study. Diabet Med. 2001;18:104–108. [PubMed]
95. Gardner AW, Katzel LI, Sorkin JD, Killewich L, Ryan A, Flinn W, Goldberg A. Improved functional outcomes following exercise rehabilitation in patients with intermittent claudication. J Gerontol. 2000;55A:M570–M577. [PubMed]
96. Gardner AW, Katzel LI, Sorkin JD, Golderg AP. Effects of long-term exercise rehabilitation on claudication distances in patients with peripheral arterial disease: a randomized controlled trial. J Cardiopulm Rehabil. 2002;22:192–198. [PubMed]
97. Gardner AW, Killewich LA, Montgomery PS, Katzel LI. Response to exercise rehabilitation in smoking and nonsmoking patients with intermittent claudication. J Vasc Surg. 2004;39:531–538. [PubMed]
98. Gardner AW, Pillai SB, Sieminski DJ, Muir J, Cowell LL, Montgomery PS. Daily physical activity of peripheral arterial disease patients is increased following exercise rehabilitation; Paper presented at the American College of Sports Medicine: Minneapolis; Minnesota. 2001.
99. Gary TL, Bone LR, Hill M, Levine D, McGuire M, Saudek C, Brancati F. A randomized controlled trial of the effects of nurse case manager and community health worker team interventions in urban African-Americans with type 2 diabetes. Prev Med. 2003;37:23–32. [PubMed]
100. Giese H, Helgo Schomer H. Life-style changes and mood profile of cardiac patients after an exercise rehabilitation program. J Cardiopulm Rehabil. 1986;6:30–37.
101. Glasgow RE, Toobert DJ, Hampson SE, Brown JE, Lewinsohn PM, Donnelly J. Improving self-care among older patients with Type II diabetes: the “Sixty Something” study. Patient Educ Couns. 1992;19:61–74. [PubMed]
102. Goodwin P, Esplen MJ, Butler K, Winocur J, Pritchard K, Brazel S, Gao J, Miller A. Multidisciplinary weight management in locoregional breast cancer: results of a phase II study. Breast Cancer Res Treat. 1998;48:53–64. [PubMed]
103. Guare JC. Response of obese nondiabetic and diabetic women to behavioral weight loss therapy (Diabetes Mellitus, Weight Loss) [Dissertation] Pittsburgh, PA: University of Pittsburgh;
104. Gulanick M. Is phase 2 cardiac rehabilitation necessary for early recovery of patients with cardiac disease? A randomized, controlled study. Heart Lung. 1991;20:9–15. [PubMed]
105. Haber D, Lacy M. Evaluation of a socio-behavioral intervention for changing health behaviors of older adults. Behavior, Health, and Aging. 1993;3:73–85.
106. Hakkinen A, Sokka T, Hannonen P. A home-based two-year strength training period in early rheumatoid arthritis led to good long-term compliance: a five-year followup. Arthritis Rheum. 2004;51:56–62. [PubMed]
107. Haldorsen E, Kronholm K, Skouen J, Ursin H. Multimodal cognitive behavioral treatment for patients sicklisted for musculoskeletal pain. Scand J Rheumatol. 1998;27:16–25. [PubMed]
108. Hall JL. Psychological interventions for exercise and dietary behavior change with breast cancer survivors. Philadelphia, PA: Temple University; 1999.
109. Hambrecht R, Niebauer J, Fiehn E, Kalberer B, Offner B, Hauer K, Riede U, Schlierf G, Kubler W, Schuler G. Physical training in patients with stable chronic heart failure: effects on cardiorespiratory fitness and ultrastructural abnormalities of leg muscles. J Am Coll Cardiol. 1995;25:1239–1249. [PubMed]
110. Hambrecht R, Niebauer J, Marburger C, Grunze M, Kalberer B, Hauer K, Schlierf G, Kubler W, Schuler G. Various intensities of leisure time physical activity in patients with coronary artery disease: effects on cardiorespiratory fitness and progression of coronary atherosclerotic lesions. J Am Coll Cardiol. 1993;22:468–477. [PubMed]
111. Handberg-Thurmond EM. Effect of home exercise intervention on functional capacity and quality of life in decompensated heart failure [Dissertation] Gainesville, FL: University of Florida; 1998.
112. Hanefeld M, Fischer S, Schmechel H, Rothe G, Schultze J, Dude H, Schwanebeck U, Julius U. Diabetes intervention study: multi-intervention trial in newly diagnosed NIDDM. Diabetes Care. 1991;14:308–317. [PubMed]
113. Haskell W, Alderman E, Fair J. Effects of intensive multiple risk factor reduction on coronary artherosclerosis and clinical cardiac events in men and women with coronary artery disease. The Stanford Coronary Risk Intervention Project (SCRIP) Circulation. 1994;89:975–990. [PubMed]
114. Hasler T, Fisher B, MacIntyre N. Exercise consultation and physical activity in patients with type 1 diabetes. Pract Diab Int. 2000;17:44–48.
115. Heath G, Maloney P, Fure C. Group exercise versus home exercise in coronary artery bypass graft patients: effects on physical activity habits. J Cardiopulm Rehabil. 1987;7:190–195.
116. Helboastad J, Sletvoid O, Moe-Nilssen R. Home training with and without additional group training in physically frail old people living at home: effect on health-related quality of life and ambulation. Clin Rehabil. 2004;18:498–5008. [PubMed]
117. Heller RF, Knapp JC, Valenti LA, Dobson AJ. Secondary prevention after acute myocardial infarction. Am J Cardiol. 1993;72:759–762. [PubMed]
118. Himeno E, Nishimo K, Okazaki T, Nanri H, Ikeda M. A weight reduction and weight maintenance program with long-lasting improvement in left ventricular mass and blood pressure. Am J Hypertens. 1999;12:682–690. [PubMed]
119. Hogue C, Cullinan S. Exercise training for frail rural elderly. In: Funk SG, Tornquist ET, Champagne MT, Wiese R, editors. Key aspects of caring for the chronically ill: hospital and home. New York: Springer; 1993. pp. 202–211.
120. Hopper DL. The effects of telephone contact on the exercise adherence of cardiac patients [Dissertation] Denver, CO: University of Denver; 1995.
121. Hughes SL, Seymour RB, Campbell R, Pollak N, Huber G, Sharma L. Impact of the fit and strong intervention on older adults with osteoarthritis. Gerontologist. 2004;44:217–228. [PubMed]
122. Irvine A, Mitchell C. Impact of community-based diabetes education on program attenders and nonattenders. Diabetes Educ. 1992;18:29–33. [PubMed]
123. Iwamoto J, Takeda T, Ichimura S. Effect of exercise training and detraining on bone mineral density in postmenopausal women with osteoporosis. J Orthop Sci. 2001;6:128–132. [PubMed]
124. Jerant AF, Azari R, Martinez C, Nesbitt TS. A randomized trial of telenursing to reduce hospitalization for heart failure: patient-centered outcomes and nursing indicators. Home Health Care Serv Q. 2003;22:1–20. [PubMed]
125. Johnson R. The effect of contingency contracting on compliance to the medical regimen in hypertensive black females [Thesis] Denton, TX: Texas Woman's University; 1993.
126. Kamwendo K, Tingstrom P, Bergdahl B, Svensson E. Effect of problem-based learning on stages of change for exercise behaviour in patients with coronary artery disease. Physiother Res Int. 2004;9:24–32. [PubMed]
127. Karlovich I, Kholodova H, Mokhort T. Rehabilitation of Type 1 diabetic patients: the experience of rehabilitation diabetologic centre in Belarus; Paper presented at the 18th International Diabetes Federation Congress; Paris-France. 2003.
128. Kentala E. Physical fitness and feasibility of physical rehabilitation after myocardial infarction in men of working age. Ann Clin Res. 1972;4 9:1–84. [PubMed]
129. Ketelaars C, Abu-Saad H, Halfens R, Schlosser M, Mostert R, Wounters E. Effects of specialized community nursing care in patients with chronic obstructive pulmonary disease. Heart Lung. 1998;27:109–120. [PubMed]
130. Keyserling TC, Samuel-Hodge CD, Ammerman AS, Ainsworth BE, Henriquez-Roldan CF, Elasy TA, Skelly AH, Johnston LF, Bangdiwala SI. A randomized trial of an intervention to improve self-care behaviors of African-American women with type 2 diabetes: impact on physical activity. Diabetes Care. 2002;25:1576–1583. [PubMed]
131. Kochevar A, Smith K, Bernard M. Effects of a community-based intervention to increase activity in American Indian elders. J Okla State Med Assoc. 2001;94:455–460. [PubMed]
132. Koertge J, Weidner G, Elliott-Eller M, Scherwitz L, Merritt-Worden TA, Marlin R, Lipsenthal L, Guarneri M, Finkel R, Saunders DE, Jr, McCormac P, Scheer JM, Collins RE, Ornish D. Improvement in medical risk factors and quality of life in women and men with coronary artery disease in the Multicenter Lifestyle Demonstration Project. Am J Cardiol. 2003;91:1316–1322. [PubMed]
133. Laaksonen DE, Atalay M, Niskanen L, Mustonen J, Sen S, Lakka T, Uusitupa M. Aerobic exercise and the lipid profile in type 1 diabetic men: a randomized controlled trial. Med Sci Sport Exerc. 2000;32:1541–1548. [PubMed]
134. Lear SA, Ignaszewski A, Laquer EA, Pritchard PH, Frohlich JJ. Extensive lifestyle management intervention following cardiac rehabilitation: pilot study. Rehabil Nurs. 2001;26:227–232. [PubMed]
135. Lear SA, Ignaszewski A, Linden W, Brozic A, Kiess M, Spinelli JJ, Haydn Pritchard P, Frohlich JJ. The Extensive Lifestyle Management Intervention (ELMI) following cardiac rehabilitation trial. Eur Heart J. 2003;24:1920–1927. [PubMed]
136. Lehmann R, Kaplan V, Bingisser R, Block K, Spinas G. Impact of physical activity on cardiovascular risk factors in IDDM. Diabetes Care. 1997;20:1603–1611. [PubMed]
137. Lehmann R, Engler H, Honegger R, Riesen W, Spinas GA. Alterations of lipolytic enzymes and high-density lipoprotein subfractions induced by physical activity in type 2 diabetes mellitus. Eur J of Clin Invest. 2001;31:37–44. [PubMed]
138. Lehmann R, Vokac A, Niedermann K, Agosti K, Spinas GA. Loss of abdominal fat and improvement of the cardiovascular risk profile by regular moderate exercise training in patients with NIDDM. Diabetologia. 1995;38:1313–1319. [PubMed]
139. Lemozy-Cadroy S, Crognier S, Gourdy P, Chauchard M, Chale J, Tauber J, Hanaire-Broutin H. Intensified treatment of type 1 diabetes: prospective evaluation at one year of a therapeutic patient education programme. Diabetes Metab. 2002;28:287–294. [PubMed]
140. Leveille S, Wagner E, Davis ZC, Grothaus L, Wallace J, LoGerfo M, Kent D. Preventing disability and managing chronic illness in frail older adults: a randomized trial of a community-based partnership with primary care. J Am Geriatr Soc. 1998;46:1191–1198. [PubMed]
141. Ligtenberg PC, Hoekstra JB, Bol E, Zonderland ML, Erkelens DW. Effects of physical training on metabolic control in elderly type 2 diabetes mellitus patients. Clin Sci. 1997;93:127–135. [PubMed]
142. Lindroth Y, Bauman A, Barnes C, McCredie M, Brooks PM. A controlled evaluation of arthritis education. Br J Rheumatol. 1989;28:7–12. [PubMed]
143. Linton S, Hellsing A, Bergstrom G. Exercise for workers with musculoskeletal pain: does enhancing compliance decrease pain? J Occup Rehabil. 1996;6:177–190. [PubMed]
144. Lisspers J, Hofman-Bang C, Nordlander R, Ryden L, Sundin O, Ohman A, Nygren A. Multifactorial evaluation of a program for lifestyle behavior change in rehabilitation and secondary prevention of coronary artery disease. Scand Cardiovasc J. 1999;33:9–16. [PubMed]
145. Lloys A, Hickie I, Brockman A, Hickie C, Wilson A, Dwyer J, Wakefield D. Immunologic and psychologic therapy for patients with chronic fatigue syndrome: a double-blind, placebo-controlled trial. Am J Med. 1993;94:197–203. [PubMed]
146. Loreto C, Fanelli C, Lucidi P, Murdolo G, DeCicco A, Parlanti N, Santeusanio F, Brunetti P, De Feo P. Validation of a counseling strategy to promote the adoption and the maintenance of physical activity by type 2 diabetic subjects. Diabetes Care. 2003;26:404–408. [PubMed]
147. Lorig KR, Sobel DS, Stewart AL, Brown BW, Jr, Bandura A, Ritter P, Gonzalez VM, Laurent DD, Holman HR. Evidence suggesting that a chronic disease self-management program can improve health status while reducing hospitalization: a randomized trial. Med Care. 1999;37:5–14. [PubMed]
148. Lorig KR, Feigenbaum P, Regan C, Ung E, Chastain RL, Holman HR. A comparison of lay-taught and professional-taught arthritis self-management courses. J Rheumatol. 1986;13:763–767. [PubMed]
149. Lorig K, Gonzalez VM, Ritter P. Community-based Spanish language arthritis education program: a randomized trial. Med Care. 1999;37:957–963. [PubMed]
150. Lorig K, Gonzalez VM, Laurent DD, Morgan L, Laris BA. Arthritis self-management program variations: three studies. Arthritis Care Res. 1998;11:448–454. [PubMed]
151. Lorig K, Lubeck D, Kraines R, Seleznick M, Holman H. Outcomes of self-help education for patients with arthritis. Arthritis Rheum. 1985;28:680–685. [PubMed]
152. Lorig K, Seleznick M, Lubeck D, Ung E, Chastain RL, Holman HR. The beneficial outcomes of the arthritis self-management course are not adequately explained by behavior change. Arthritis Rheum. 1989;32:91–95. [PubMed]
153. Lorig K, Sobel D, Ritter P, Laurent D, Hobbs M. Effect of a self-management program on patients with chronic disease. Eff Clin Pract. 2001;4:256–262. [PubMed]
154. Maeland JG, Havik OE. The effects of an in-hospital educational programme for myocardial infarction patients. Scand J Rehabil Med. 1997;19:57–65. [PubMed]
155. Mahler HI, Kulik JA, Tarazi RY. Effects of a videotape information intervention at discharge on diet and exercise compliance after coronary bypass surgery. J Cardiopulm Rehabil. 1999;19:170–177. [PubMed]
156. Marshall AL, Booth ML, Bauman AE. Promoting physical activity in Australian general practices: a randomised trial of health promotion advice versus hypertension management. Patient Educ Couns. 2005;56:283–290. [PubMed]
157. Mattila R, Malmivaara A, Kastarinen M, Kivela SL, Nissinen A. Effectiveness of multidisciplinary lifestyle intervention for hypertension: a randomised controlled trial. J Hum Hypertens. 2003;17:199–205. [PubMed]
158. Maxwell A, Bastani R, Vida P, Warda U. Physical activity among older Filipino-American women. Women Health. 2002;36:67–79. [PMC free article] [PubMed]
159. Mayou R. A controlled trial of early rehabilitation after myocardial infarction. J Cardiopulm Rehabil. 1983;3:397–402.
160. McGilley BM. Influence of exercise rehabilitation on coronary patients: a six-year follow-up evaluation [Dissertation] Lawrence, KS: University of Kansas; 1987.
161. Mersebach H, Klose M, Svendsen O, Astrup A, Feldt-Rasmussen U. Combined dietary and pharmacological weight management in obese hypopituitary patients. Obes Res. 2004;12:1835–1843. [PubMed]
162. Montgomery E, Lieberman A, Singh G, Fries J. Patient education and health promotion can be effective in Parkinson's disease: a randomized controlled trial. Am J Med. 1994;97:429–435. [PubMed]
163. Moore SM, Charvat JM. Using the CHANGE intervention to enhance long-term exercise. Nurs Clin North Am. 2002;37:273–283. [PubMed]
164. Morrin L, Black S, Reid R. Impact of duration in a cardiac rehabilitation program on coronary risk profile and health-related quality of life outcomes. J Cardiopulm Rehabil. 2000;20:115–121. [PubMed]
165. Mostert S, Kesselring J. Effects of a short-term exercise training program on aerobic fitness, fatigue, health perception, and activity level of subjects with multiple sclerosis. Mult Scler. 2002;8:161–168. [PubMed]
166. Murchie P, Campbell NC, Ritchie LD, Simplson JA, Thain J. Secondary prevention clinics for coronary heart disease: four year follow up of a randomized controlled trial in primary care. Br Med J. 2003;326:84–89. [PMC free article] [PubMed]
167. Neuberger GB, Smith KV, Black SO, Hassanein R. Promoting self-care in clients with arthritis. Arthritis Care Res. 1993;6:141–148. [PubMed]
168. Oh H, Seo W. Decreasing pain and depression in a health promotion program for people with rheumatoid arthritis. J Nurs Sch. 2003;35:127–132. [PubMed]
169. Ornish D, Schewitz L, Billings J, Brown S, Gould K, Merritt T, Sparier S, Armstrong W, Ports T, Kirkeside R, Hogeboom C, Brand R. Intensive lifestyle changes for reversal of coronary heart diseases. JAMA. 1998;23:2001–2007. [PubMed]
170. Painter P, Carlson L, Carey S, Paul S, Myll J. Physical functioning and health-related quality-of-life changes with exercise training in hemodialysis patients. Am J Kidney Dis. 2000;35:482–492. [PubMed]
171. Painter Pl, Hector L, Ray K, Lynes L, Paul S, Dodd M, Tomlanovich S, Ascher N. Effects of exercise training in coronary heart disease risk factors in renal transplant recipients. Am J Kidney Dis. 2003;42:362–369. [PubMed]
172. Penckofer S, Llewellyn J. Adherences to risk-factor instructions one year following coronary artery bypass surgery. J Cardiovasc Nurs. 1989;3:10–24. [PubMed]
173. Petrella RJ, Bartha C. Home based exercise therapy for older patients with knee osteoarthritis: a randomized clinical trial. J Rheumatol. 2000;27:2215–2221. [PubMed]
174. Powell KW. Strategy to improve blood pressure control and medication adherence [Dissertation] Chicago, IL: Rush University; 2002.
175. Prince R, Smith M, Dick I, Price R, Webb P, Henderson N, Harris M. Prevention of postmenopausal osteoporosis: a comparative study of exercise, calcium supplementation, and hormone-replacement therapy. N Engl J Med. 1991;325:1189–1195. [PubMed]
176. Regensteiner JG, Steiner JF, Hiatt WR. Exercise training improves functional status in patients with peripheral arterial disease. J Vasc Surg. 1996;23:104–115. [PubMed]
177. Rejeski W, Brawley L, Ambrosius W, Brubaker P, Focht B, Foy C, Fox L. Older adults with chronic disease: benefits of group-mediated counseling in the promotion of physically active lifestyles. Health Psychol. 2003;22:414–423. [PubMed]
178. Riemsma RP, Taal E, Rasker JJ. Group education for patients with rheumatoid arthritis and their partners. Arthritis Care Res. 2003;49:556–566. [PubMed]
179. Rippey RM, Bill D, Abeles M, Day J, Downing DS, Pfeiffer CA, Thal S, Wetstone S. Computer-based patient education for older persons with osteoarthritis. Arthritis Rheum. 1987;30:932–935. [PubMed]
180. Rubin RR, Peyrot M, Saudek CD. Effect of diabetes education on self-care, metabolic control, and emotional well-being. Diabetes Care. 1989;10:673–679. [PubMed]
181. Samaras K, Ashwell S, Mackintosh AM, Fleury AC, Campbell LV, Chisholm DJ. Will older sedentary people with non-insulin-dependent diabetes mellitus start exercising? A health promotion model. Diabetes Res Clin Pract. 1997;37:121–128. [PubMed]
182. Sanderson CD. Functional capacity and adherence patterns in coronary patients participating in supervised versus unsupervised exercise training [Dissertation] Gainesville, FL: University of Florida; 1990.
183. Scales R. Motivational interviewing and skills-based counseling in cardiac rehabilitation: the Cardiovascular Health Initiative and Lifestyle Education (Chile) study [Dissertation] Albuquerque, NM: University of New Mexico; 1998.
184. Schaperclaus G, de Greef M, Rispens P, de Calonne D, Landsman M, Lie K. Participation in sports groups for patients with cardiac problems: an experimental study. Adapted Phys Act Q. 1997;14:275–284.
185. Scholten C, Brodowicz T, Graninger W, Gardavsky I, Pils K, Pesau B, Eggl-Tyl E, Wanivenhaus A, Zielinski C. Persistent functional and social benefit 5 years after a multidisciplinary arthritis training program. Arch Phys Med Rehabil. 1999;80:1282–1287. [PubMed]
186. Schuster PM, Wright C, Tomich P. Gender differences in the outcomes of participants in home programs compared to those in structured cardiac rehabilitation programs. Rehabil Nurs. 1995;20:93–101. [PubMed]
187. Sharazand S, Canfield J, Kuschner W. Improved quality of life among patients completing a pulmonary rehabilitation program: one center's early experience. Respir Care. 2001;46:595–600. [PubMed]
188. Singh RB, Rastogi V, Rastogi SS, Niaz MA, Beegom R. Effect of diet and moderate exercise on central obesity and associated disturbances, myocardial infarction and mortality in patients with and without coronary artery disease. J Am Coll Nutr. 1996;15:592–601. [PubMed]
189. Song R, Lee H. Effects of a 12-week cardiac rehabilitation exercise program on motivation and health-promoting lifestyle. Heart Lung. 2001;30:200–209. [PubMed]
190. Southard BH, Southard DR, Nuckolls J. Clinical trial of an internet-based case management system for secondary prevention of heart disease. J Cardiopulm Rehabil. 2003;23:341–348. [PubMed]
191. Stanton JM, Arroll B. The effect of moderate exercise on mood in mildly hypertensive volunteers: a randomized controlled trial. J Psychosom Res. 1996;40:637–642. [PubMed]
192. Stenlund T, Lindstrom B, Granlund M, Burell G. Cardiac rehabilitation for the elderly: Qi Gong and group discussions. Eur J Cardiovasc Prev Rehabil. 2005;12:5–11. [PubMed]
193. Stenstrom CH, Lindell B, Swanberg E, Swanberg P, Harms-Ringdahl K, Nordemar R. Intensive dynamic training in water for rheumatoid arthritis functional class II--a long-term study of effects. Scand J Rheumatol. 1991;20:358–365. [PubMed]
194. Sullivan T, Allegrante JP, Peterson MG, Kovar PA, MacKenzie C. One-year followup of patients with osteoarthritis of the knee who participated in a program of supervised fitness walking and supportive patient education. Arthritis Care Res. 1998;11:228–233. [PubMed]
195. Sward K. Effects of resistance exercise training on muscular strength, functional fitness, physical self-perception, and quality of life in the elderly [Dissertation] Pittsburgh, PA: University of Pittsburgh; 2001.
196. Talbot LA, Gaines JM, Huynh TN, Metter EJ. A home-based pedometer-driven walking program to increase physical activity in older adults with osteoarthritis of the knee: a preliminary study. J Am Geriatr Soc. 2003;51:387–392. [PubMed]
197. Tapanya S. A biopsychosocial intervention program to improve medical regimen adherence and glycemic control in type ll diabetic patients [Dissertation] New Brunswick, Canada: University of New Brunswick; 1996.
198. Toda Y. The effect of energy restriction, walking, and exercise on lower extremity lean body mass in obese women with osteoarthritis of the knee. J Orthop Sci. 2001;6:148–154. [PubMed]
199. Toobert DJ, Glasgow RE, Radcliffe JL. Physiologic and related behavioral outcomes from the Women's Lifestyle Heart Trial. Ann Behav Med. 2000;22:1–9. [PubMed]
200. Trofimuk-Thomas G. The effectiveness of standardized vs individualized teaching, in combination with a counseling and exercise program, for clients in cardiac rehabilitation programs, in relation to the reduction of coronary risk factors [Dissertation] DeKalb, IL: Northern Illinois University; 1986.
201. Tudor-Locke CE. Development, implementation and evaluation of a daily physical activity intervention for individuals with Type 2 diabetes [Dissertation] Ontario, Canada: University of Waterloo; 1999.
202. Tudor-Locke C, Bell RC, Myers AM, Harris SB, Ecclestone NA, Lauzon N, Rodger NW. Controlled outcome evaluation of the First Step Program: a daily physical activity intervention for individuals with type II diabetes. Int J Obes Relat Metab Disord. 2004;28:113–119. [PubMed]
203. Van den Arend I, Stolk R, Rutten G, Schrijvers G. Education integrated into structured general practice care for Type 2 diabetic patients results in sustained improvement in disease knowledge and self-care. Diabet Med. 2000;17:190–197. [PubMed]
204. van Elderen-van Kemenade T, Maes S, van den Broek Y. Effects of a health education programme with telephone follow-up during cardiac rehabilitation. Br J Clin Psycho. 1994;33:367–378. [PubMed]
205. Vestfold Heartcare Study Group. Influence on lifestyle measures and five-year coronary risk by a comprehensive lifestyle intervention programme in patients with coronary heart disease. Eur J Cardiovasc Prev Rehabil. 2003;10:429–437. [PubMed]
206. Wallner S, Watzinger N, Lindschinger M, Smolle KH, Toplak H, Eber B, Dittrich P, Elmadfa I, Klein W, Krejs GJ, Wascher TC. Effects of intensified lifestyle modification on the need for further revascularization after coronary angioplasty. Eur Journal Clin Invest. 1999;29:372–379. [PubMed]
207. Wdowik M, Kendall P, Harris M, Kelm K. Development and evaluation of an intervention program: control on campus. Diabetes Educ. 2000;26:95–104. [PubMed]
208. Welty FK, Stuart E, O'Meara M, Huddleston J. Effect of addition of exercise to therapeutic lifestyle changes diet in enabling women and men with coronary heart disease to reach Adult Treatment Panel III low-density lipoprotein cholesterol goal without lowering high-density lipoprotein cholesterol. Am J Cardiol. 2002;89:1201–1204. [PubMed]
209. Whittemore R, Chase S, Mandle CL, Roy SC. The content, integrity, and efficacy of a nurse coaching intervention in type 2 diabetes. Diabetes Educ. 2001;27:887–898. [PubMed]
210. Wiggam J, French R, Henderson H. The effects of a token economy on distance walked by senior citizens in a retirement center. Am Correct Ther J. 1986;40:6–12.
211. Willenheimer R, Rydberg E, Cline C, Broms K, Hillberger B, Oberg L, Erhardt L. Effects on quality of life, symptoms and daily activity 6 months after termination of an exercise training programme in heart failure patients. Int J Cardiol. 2001;77:25–31. [PubMed]
212. Wing RR, Marcus M, Epstein L, Jawad A. A “Family-Based” approach to the treatment of obese type II diabetic patients. J Consult Clin Psychol. 1991;59:156–162. [PubMed]
213. Wisnewski CA. A study of the health-promoting behavioral effects of an exercise educational intervention in adult diabetics [Dissertation] Denton, TX: Texas Woman's University; 1996.
214. Worcester MU, Stojcevski Z, Murphy B, Goble AJ. Long-term behavioral outcomes after attendance at a secondary prevention clinic for cardiac patients. J Cardiopulm Rehabil. 2003;23:415–422. [PubMed]
215. Yates BC, Anderson T, Hertzog M, Ott C, Williams J. Effectiveness of follow-up booster sessions in improving physical status after cardiac rehabilitation: health, behavioral, and clinical outcomes. Appl Nurs Res. 2005;18:59–62. [PubMed]
216. Young DR, Appel LJ, Jee S, Miller E. The effects of aerobic exercise and Tai Chi on blood pressure in older people: results of a randomized trial. J Am Geriatr Soc. 1999;47:277–284. [PubMed]
217. Young D, Kittke T, McCall M, Blume D. A prospective controlled study of in-hospital myocardial infarction rehabilitation. Journal of Cardiac Rehabilitation. 1982;2:32–40.
218. Conn V, Hafdah A, LeMaster J, Ruppar T, Cochran J, Nielsen P. Interventions to improve self-management among adults with type 1 diabetes: Meta-analysis of metabolic outcomes. Am J Health Behav. In press.
219. Conn V, Hafdahl A, Minor M, Nielsen P. Physical activity interventions among adults with arthritis: Meta-analysis of outcomes. Semin Arthritis Rheum. In press. [PubMed]
220. Conn V, Hafdahl A, Moore S, Nielsen P, Brown L. Meta-analysis of interventions to increase physical activity among adults with cardiovascular disease. Int J Cardiol. In review.
221. Vevea JL, Woods CM. Publication bias in research synthesis: Sensitivity analysis using a priori weight functions. Psychol Methods. 2005;10:428–43. [PubMed]
222. Le Masurier GC, Sidman CL, Corbin CB. Accumulating 10,000 steps: does this meet current physical activity guidelines? Res Q Exercise Sport. 2003;74:389–94. [PubMed]
223. Tudor-Locke C, Bassett DR. How many steps/day are enough? Preliminary pedometer indices for public health. Sports Med. 2004;34:1–8. [PubMed]
224. Obarazanek E, Vollme WM, Lin PW, Cooper LS, Young DR, Ard JK, Stevens FJ, Simons-Morton DG, Svetkey LP, Harsha DW, Elmer PJ, Appel LJ. Effects of individual components of multiple behavior changes: The PREMIER trial. Am J Health Behav. 2007;31:545–560. [PubMed]
225. Clark AM, Hartline L, Vandermeer B, McAlister FA. Quantitative synthesis documenting importance of secondary prevention. Ann Intern Med. 2005;143:659–72. [PubMed]
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