• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Pain Symptom Manage. Author manuscript; available in PMC Aug 1, 2009.
Published in final edited form as:
PMCID: PMC2542506

Methodological Challenges When Using Actigraphy in Research

Ann M. Berger, PhD, RN, AOCN, FAAN, Kimberly K. Wielgus, MSN, APRN, BC, Stacey Young-McCaughan, PhD, RN AOCN, Patricia Fischer, BSN, RN, CCRC, Lynne Farr, PhD, and Kathryn A. Lee, PhD, CBSM, RN, FAAN


Actigraphy has become a valuable clinical and research tool to objectively evaluate sleep, daytime activity, and circadian activity rhythms in healthy individuals as well as persons with primary and co-morbid insomnia. However, procedures used for sampling, data processing, and analysis are not consistently reported in the literature. The wide variability in how actigraphy is reported makes it difficult to compare findings across studies. The procedures and reporting methods from 21 studies that used actigraphs to assess sleep and wake in adult patients with cancer are reviewed to highlight the differences in reporting strategies. Patients with cancer were chosen to illustrate the methodological challenges related to procedures and reporting in one population. The aim of this article is to advance standards of information presented in publications to enable comparisons across research studies that use actigraphy. Specific methodological challenges when using actigraphy in research include instrumentation, selection of pertinent variables, sampling, and data processing and analysis. Procedural decisions are outlined and discussed, and suggestions are made for standardized actigraphy information to include in research reports. More consistent procedures and reporting will advance the science of sleep, daytime activity, and circadian activity rhythms and their association with other health-related variables.

Keywords: Actigraph, sleep, activity, circadian rhythms, methods


Actigraphy involves the use of a portable device the size of a large wristwatch to record movement over time in the form of activity counts (1). Adoption of the device in research was limited until its precision improved in the 1980s (2). Actigraphy is a reliable and valid instrument to assess sleep. Estimates of sleep with actigraphy correlate at approximately 90% agreement with polysomnography, the gold standard for detecting specific sleep and wake states (3). Actigraphy has gained acceptance as a sensitive tool for evaluating sleep-wake and activity rest patterns, and circadian activity rhythms. With its ease of use, as well as acceptance among research participants, actigraphy monitoring can be expected to increase in future research (4, 5).

At issue is the consistency in scoring and wide variability of information in published reports of studies involving actigraphy. The procedural challenges in selection of instruments and pertinent variables, sampling, and data processing and analysis are rarely described. The most recent practice parameters offer recommendations to guide the use of actigraphy in the study of sleep and circadian rhythms (4). However, the scope of these parameters is limited, leaving researchers to independently make many decisions regarding procedures. Advancing standards of information in published results will make possible comparison across studies that use actigraphy and will enhance the testing of interventions to improve activity and sleep rhythms. Therefore, the purpose of this paper is to review the literature on actigraphy in studies with adult patients with cancer to illustrate methodological challenges related to procedures and reporting, and to make recommendations regarding instrumentation, selection of pertinent variables, sampling, and data processing and analysis.

Focused Review of the Literature

Studies of sleep, activity, and circadian rhythms using actigraphy in adult cancer patients were identified by searching Medline, CINAHL, and PsychInfo databases up to December 31, 2006. The searches were constructed by combining the following search terms: cancer and (actigraph* or actiwatch or accelerometer) and (sleep or rest or circadian). More than one term was needed to capture all articles involving actigraphy in adults with cancer. Of the 29 articles found from 1996 to 2006, eight were excluded because they reported only measures of day activity, leaving 21 articles for this review. An extraction form for each article was completed and included information on pertinent variables, instrumentation, sampling procedures, and data processing and analysis.

Selection of Pertinent Variables

No variables obtained from actigraphy (i.e., sleep, activity, or circadian rhythms) were reported consistently in all 21 studies. Of course, each study had different research questions and it may not have been practical or possible to report all the data collected. The majority of studies reporting on actigraphy with early stage cancer patients described sleep and circadian rhythms (610), but several other studies of such patients described only sleep (1113). One study (14) did not include any sleep variables and presented only activity and circadian rhythm results in this population of patients with early stage disease. Of several studies using actigraphy in metastatic colo-rectal cancer patients, one (15) included nighttime and daytime activity in addition to circadian rhythms, but the others included only circadian rhythm parameters (1621). In patients with bone metastasis, sleep and activity, but not circadian rhythms, were reported (22). Only one comprehensive report was found of sleep, activity, and circadian rhythms in adults with metastatic disease; patients had lung cancer (23).Only three studies used actigraphy in cancer survivors. One (24) reported on sleep and activity of breast cancer survivors, another (25) reported these variables in patients with various types of cancer, and a third included sleep and circadian rhythms for adult survivors of childhood cancer (26).

This review illuminates the lack of consistency in reports from actigraph data and the untapped potential for more thorough analysis of sleep, activity, and circadian rhythms. This has resulted in missed opportunities to compare findings between studies and advance our knowledge of sleep-wake patterns by using actigraphy in various cancer populations.

The frequency of reporting specific variables was also determined in the 21 articles. Among the 14 studies that reported sleep variables, the most frequently reported variable was number of awakenings, followed by time in bed (in minutes), total sleep time (in minutes), wake after sleep onset in minutes (WASO-M) if the time in bed was standardized, wake after sleep onset as a percentage (WASO-P) of time after first falling asleep if the time in bed was not consistent, and sleep maintenance (as a percentage of sleep after first falling asleep during time in bed), which is the opposite of WASO-P. The daytime activity variables, included in only eight studies were mean daytime activity, and either total time (in minutes) or percentage of time asleep during the day. In the 12 articles that included circadian rhythm variables, the most commonly reported included mesor, acrophase, amplitude, and a measure of rhythm periodicity such as tau or 24-hour autocorrelation coefficient. This review demonstrates both the wide range of variables that can be reported, as well as the inconsistencies in reporting, resulting in the inability to make comparisons between studies.

Review of Actigraphy Procedures and Reports

Like the variables reported, no one instrument was consistently used. Sampling procedures, as well as data processing (cleaning) and analysis (scoring), varied. Two articles by Mormont and colleagues (18, 19) reported procedures from the same data set; therefore this section discusses variables reported in 20 data sets.


Details related to instrumentation included the device model and manufacturer. Models from one company were used in the majority of the studies (6, 8, 10, 1416, 18, 2025). Four studies used other devices from other companies (11, 13, 17, 26); three studies did not identify the instrument used (7, 9, 12). Placement of the actigraph was most commonly reported as being on the non-dominant wrist.


Sampling procedures were examined to determine if they included the environment of data collection, the data collection period, days of the week sleep and activity were monitored, and epoch recording length. All studies included a description of the environment in which the actigraphy monitoring took place, at primarily the patient’s home. Data collection periods ranged from 2 to 26 days; 16 reports included at least three, consecutive 24-hour periods, as recently recommended (4). One researcher omitted the first several hours of recording while participants were acclimating to the actigraph (25), as described in Blackwell et al. (27). Four studies collected data for at least one week (9, 10, 13, 24). Only two studies collected data on specific weekdays in an attempt to further standardize sleep measures for the sample (23, 25). Statements regarding whether data were from a single night versus the means of multiple nights’ values were not included.

Epoch lengths are pre-set by the program software, but can be adjusted, depending on the preferred memory, battery time, and the level of resolution desired. One-minute epochs were used in the majority of studies, as recently recommended (14); however, one used a 10-second epoch, one used a 6-minute interval (17), and others did not report this information (11, 21, 24, 26). To summarize, considerable variability was found in sampling procedures, except for location and epoch length of recordings.

Data Processing and Analysis

Critical elements of actigraph data processing (cleaning) and analysis (scoring) include setting time intervals, how missing data are handled prior to sleep scoring, determination of the clock time for intention to go to sleep in bed at night and get up out of bed in the morning, procedures to ensure intra-rater and inter-rater reliability, and the software program selected for scoring sleep from the raw actigraph data. The descriptions of data processing (cleaning) and analysis (scoring) were inconsistently reported if at all. Ancoli-Israel and colleagues (6) provided details of their scoring algorithms, but most studies only reported the name and source of software programs used to generate results. Only two studies reported the algorithm used; both used the Cole-Kripke (14, 25).

Suggestions to Overcome Challenges When Using Actigraphy in Research

Consistent publication standards can lead to greater similarity of reports, enabling researchers to compare results across studies. Best practices and recommendations for using accelerometers in the study of physical activity have recently been published (28) and could serve as a guide for improving consistency of methods and reporting for actigraphy in the study of sleep and wake. Based upon this review of the use of actigraphy in patients with cancer and extensive experience using actigraphy in three different research settings, the authors of this paper advise others planning to use actigraphy to carefully consider instrumentation, selection of pertinent variables, sampling, and data processing (cleaning) and analysis (scoring) procedures in the planning stages of their research (Table 1 and Table 2).

Table 1
Decisions When Planning Procedures for Use of Actigraphy in Research
Table 2
Actigraphy Information Suggested for Inclusion in Research Reports


Suggestion 1. When designing a study, consider the resources needed to purchase actigraphs and interface unit

To increase validity for estimating total sleep time, actigraphs with event markers and light sensors may be required. The expense of these features needs to be considered when estimating resources to conduct the study. All actigraphs used in a study, particularly in repeated measures designs, should be the same type, and ideally the same model.

Suggestion 2. In reporting study findings, include all significant product information

Reports should provide the registered trademark name of the device and model, name and location of the manufacturer, and whether the actigraph was placed on the dominant or non-dominant arm or leg. Including “actigraphy” as a key word in articles can aid other researchers in locating articles.

Suggestion 3. Provide clear instructions to participants

Participant-related factors, such as removing the actigraph and forgetting to use the event marker, introduce artifact into the data measurements. Therefore, providing clear instructions and expectations to participants is a necessity. Sleep onset latency and sleep efficiency values from actigraphy are difficult to determine in uncontrolled settings such as the home, unless exact “intent to go to sleep time” can be determined with an event marker and confirmed with a diary log entry.

Selection of Pertinent Variables

Suggestion 1. Include the following five key sleep variables

time in bed (in minutes), total sleep time after sleep onset (in minutes), number of awakenings, minutes awake (WASO-M), and percent wake after sleep onset (WASO-P). Clearly define these variables in publication.

Suggestion 2. Include the following two key day activity variables

mean daytime activity counts and percent time asleep during the day. The number of minutes asleep during the day may be reported if researchers use a consistent day length, such as from 0900 to 2059 hrs. Clearly define these variables in publication.

Suggestion 3. Include the following three key circadian rhythm variables

mesor, acrophase, and amplitude of activity counts. In some studies, such as those including infants, children, adolescents, the elderly, or those with sleep-phase disorders, cycle length (or tau) should be included. Clearly define these variables in publication.


Suggestion 1. Clearly define the aspects of the environment in which data are collected

Important information includes the location of data collection, the duration of recording (number of days the actigraph was worn), whether another person or pet was sharing the bedroom with the participant, and the resulting number of sleep and activity periods included in the analysis.

Suggestion 2. Duration of monitoring is important in order to capture the phenomena of interest

In planning the duration of monitoring for the population of interest, researchers should weigh the potential benefits of more hours of usable data against the potential costs of participant time, battery usage, processing time, and increased risk of missing data, or lost actigraphs. Some individuals may perceive extended periods of continuous data collection as burdensome, which may lead to reduced enrollment of potential participants from which to generalize to the larger population. Time required for delivery and retrieval of the individual actigraphs must also be considered when determining the number of actigraphs needed. Recommendations for at least 72 hours of data collection and 1-minute sampling epochs in adults have been made (4).

Suggestion 3. Selection of days of the week for monitoring needs to be considered

Since sleep and activity patterns usually vary between weekdays and weekends, the days of the week in which monitoring occurs can be kept constant by design, particularly in longitudinal studies with repeated measures at weekly or monthly intervals (27). As much as three weeks of data would be necessary to obtain valid and reliable patterns of activity and sleep that describe weekly or social rhythms. Keeping the days of the week consistent or randomized at each time interval is recommended whenever feasible. Reporting the actual days of the week increases comparability between studies. Additionally, data analysis can be strengthened when days of the week are coded. Results need to clearly state whether a single day or night of data (usually reported as a group mean ± standard deviation) or the mean for more than one day or night (usually reported as a group mean ± standard error of the mean) is reported.

Suggestion 4. The epoch length is important when studying sleep patterns over time

Epoch lengths up to one minute provide sufficient data for analysis of sleep and activity counts for three to five nights (4). However, the epoch length selected should be consistent with that used for validation of the analytic software. In sleep research with polysomnography, epochs are typically 20 or 30 seconds, and actigraphy recordings may be set for these epoch lengths to establish validity. Two- to three-minute epochs may be more useful for analysis of circadian rhythms over long periods of time. In a study comparing polysomnography to actigraphy in participants with insomnia, researchers used a 30-second epoch to match the epoch used with polysomnography and found actigraphy to be valid for number of awakenings, WASO, total sleep time, and sleep efficiency (29). Polysomnography detects both arousals (3–15 seconds of EEG awake brain waves) and awakenings (> 15 seconds of awake brain waves), but actigraphy algorithm criteria for an awake episode vary with the software algorithm used and should be reported.

Suggestion 5. Consider the mode of data collection for each type of monitoring device

Selections include zero-crossing mode (ZCM; a way of counting movements and the primary mode of data collection for sleep estimation), time-above-threshold (TAT; an estimate of movement duration that is more indicative of the vigor of activity and used primarily in daytime monitoring of activity), proportional integrating measure (PIM; an estimate of movement intensity most useful with daytime activity levels and patterns), or TRI-mode (ZCM/TAT/ PIM).

Data Processing and Analysis

One of the most challenging aspects of using actigraphs is the need to dedicate resources to developing expertise in processing (cleaning) and analyzing (scoring) large volumes of data.

Suggestion 1. Plan for and report the name and version of the software used to analyze the data, and the algorithm used for scoring

Software and algorithm selection should be based on the aims of the study. Options can include clinical scoring algorithms as well as research scoring algorithms, each with its advantages and disadvantages. Some software programs perform circadian rhythm analysis, while others do not.

Suggestion 2. Make data editing rules and decisions a priori

Stating these rules clearly in procedures and reports will facilitate analysis and permit comparisons among published studies (28). Data editing includes setting actual time intervals for analysis and handling missing data. A sleep diary is essential to determine start and stop intervals for analysis when event marker and light data are not available. While information from participant diaries may be used to set the day and night intervals (4), diary information is often discordant with the event marker the patients used to indicate bed time and wake time (25, 30). Event markers may also be inaccurate, since participants may push the event marker earlier or later than they actually turn out the lights to go to sleep. Diary entries should be designed with validity in mind, and participants should be given instructions to promote accurate recording of the designated times. Some investigators assess “cascading counts” of progressively less activity until sleep is clearly evident. Decisions need to be made about what constitutes cascading counts and when a change in interval from wake to sleep will be marked. A combination of two or more methods of standardizing interval setting is recommended. Strict data editing rules are essential when preparing many files for analysis to ensure reproducibility of bed time and rise time intervals, and when data are missing or should be excluded from analysis. Some investigators decide a priori not to mark any data as bad, or missing, if it is less than one hour. Other investigators commit the considerable additional time and effort to remove all bad or missing data as a part of cleaning prior to scoring.

Precise analysis of actigraphy data depends on minimizing the errors that may result when procedures lack the details necessary to maximize inter-rater and intra-rater reliability and reproducibility of data editing and handling of missing data. Various alternative approaches may be necessary in some studies where bedtimes are highly variable from night to night. For example, new parents and shift workers may have no predictable sleep periods, and researchers may consider setting a 12-hour day interval (0900 to 2059 hours) and a 12-hour night interval (2100 to 0859 hours) and reporting sleep and wake time during each time frame.

One specific challenge is deciding how to handle evening naps that occur involuntarily prior to bedtime. Many people doze while watching television or reading, and then get up and go to bed. Whether this type of evening sleep prior to bedtime is considered part of the day’s sleep or night’s sleep time is not clear in published reports. One method of handling this situation is to designate the first sleep episode after 2100 hours as first nocturnal sleep episode; if the individual is already asleep at that time, the bed time can be moved earlier to the first epoch of wake prior to sleep onset. Decision rules for determining start and stop times can enhance inter-rater and intra-rater reliability for designating sleep periods for analysis. Regardless of the methods used, it is essential that investigators report how the data were cleaned and scored.

Suggestion 3. Institute consistent procedures for entering individual actigraphy sleep analyses into the master data file

Several factors need to be considered when populating the master data file(s) with individuals’ actigraphy results. Among these are accounting for each day/night of data within the context of the study, and making sure that all sleep results are analyzed using percentage conversions when standardized bed and wake times cannot be employed. When circadian rhythms are also included in the analysis, procedures need to be implemented for equal treatment of files with missing data. When grouping circadian rhythm variables for analysis, the variables must be calculated using the same tau (generally 24 hours or cycle length). In specific studies of circadian rhythms the exact tau should be determined through spectral analysis methods available in some software programs.

Suggestion 4. Plan for staff training

No procedures for training staff in processing actigraphy data have been published. Manufacturers’ manuals outline how to collect data and conduct basic analysis, but do not anticipate or include decision rules that may be particular to the population of interest. Involving a content expert can be highly beneficial and assist in anticipating potential problems.

Sleep and wake epochs are automatically and consistently scored using selected software criteria with no researcher bias in identifying sleep and wake states. Strict written procedures for training staff in consistent handling of missing data and making decisions about time intervals will ensure reproducibility. When these procedures are followed, a high percentage of agreement among trained staff should be achieved.

Suggestion 5. Set a minimum level of inter-rater reliability, and confirm it periodically

Staff training is aimed at developing procedures to promote consistent agreement on all files among scorers. Previous research has achieved agreement by setting day and night time intervals within a predetermined time frame (27), and having a high level of agreement between scorers for all intervals on the file. If one researcher is responsible for editing data files, a method for determining intra-rater reliability is essential. When more than one individual edits data files, a method for determining inter-rater reliability is essential. Once staff training is deemed sufficient for a high rate of agreement, reliability should be confirmed periodically for a random sample of good and poor sleepers, especially in longitudinal studies. Other advanced statistical methods for determining reliability have also been described (27). An 80% or higher agreement within a 15-minute timeframe may be a feasible minimal goal for inter-rater reliability testing 10% of the actigraphy reports in a study.


Many challenging issues related to procedures and reports using actigraphy in research have been described. Recommendations for future research include making careful decisions (Table 1) and including specific actigraphy information to be included in research reports (Table 2). Reporting salient sleep, activity, and circadian rhythm variables, whenever appropriate, will allow for comparisons among reports. Details about software programs used to generate results can lead to guidelines that will assist in comparing results from different devices. As sleep, activity, and circadian rhythm research using actigraphy instrumentation for assessing primary and co-morbid insomnia becomes more standardized, a consensus conference can be organized to develop further practice parameters for using actigraphy in research.

The body of knowledge regarding objective measurement of sleep, activity, and circadian rhythms will grow when researchers plan studies that address the methodological challenges related to procedures and reporting results. This applies to research with healthy individuals and persons with primary and co-morbid insomnia, such as those with cancer. Understanding relationships between subjective sleep measures and objective actigraphy measures of sleep, activity, and circadian rhythms is essential to enhance our understanding of physical and mental health outcomes in various populations of children and adults with sleep disturbances.


Authors wish to disclose the absence of financial support and off-label or investigational use of drugs or devices for this study. Authors Berger and Farr wish to acknowledge funding from the National Institute of Nursing Research NIH (#5R01NR007762-05). The views of author Young-McCaughan are her own and do not purport to reflect the position of the Army Medical Department, Department of the Army, or the Department of Defense.


Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.


1. Ancoli-Israel S, Cole R, Alessi C, et al. The role of actigraphy in the study of sleep and circadian rhythms. Sleep. 2003;26(3):342–392. [PubMed]
2. Cole RJ, Kripke DF, Gruen W, Mullaney DJ, Gillin JC. Automatic sleep/wake identification from wrist activity. Sleep. 1992;15(5):461–469. [PubMed]
3. de Souza L, Benedito-Silva AA, Pires ML, et al. Further validation of actigraphy for sleep studies. Sleep. 2003;26(1):81–85. [PubMed]
4. Littner M, Kushida CA, Anderson WM, et al. Practice parameters for the role of actigraphy in the study of sleep and circadian rhythms: an update for 2002. Sleep. 2003;26(3):337–341. [PubMed]
5. Vallieres A, Morin CM. Actigraphy in the assessment of insomnia. Sleep. 2003;26(7):902–906. [PubMed]
6. Ancoli-Israel S, Liu L, Marler MR, et al. Fatigue, sleep, and circadian rhythms prior to chemotherapy for breast cancer. Support Care Cancer. 2006;14(3):201–209. [PMC free article] [PubMed]
7. Berger AM. Patterns of fatigue and activity and rest during adjuvant breast cancer chemotherapy. Oncol Nurs Forum. 1998;25(1):51–62. [PubMed]
8. Berger AM, Farr L. The influence of daytime inactivity and nighttime restlessness on cancer-related fatigue. Oncol Nurs Forum. 1999;26(10):1663–1671. [PubMed]
9. Berger AM, Higginbotham P. Correlates of fatigue during and following adjuvant breast cancer chemotherapy: a pilot study. Oncol Nurs Forum. 2000;27(9):1443–1448. [PubMed]
10. Berger AM, VonEssen S, Kuhn BR, et al. Feasibility of a sleep intervention during adjuvant breast cancer chemotherapy. Oncol Nurs Forum. 2002;29(10):1431–1441. [PubMed]
11. Kuo HH, Chiu MJ, Liao WC, Hwang SL. Quality of sleep and related factors during chemotherapy in patients with stage I/II breast cancer. J Formos Med Assoc. 2006;105(1):64–69. [PubMed]
12. Payne J, Piper B, Rabinowitz I, Zimmerman B. Biomarkers, fatigue, sleep, and depressive symptoms in women with breast cancer: a pilot study. Oncol Nurs Forum. 2006;33(4):775–783. [PubMed]
13. Rumble ME, Keefe FJ, Edinger JD, Porter LS, Garst JL. A pilot study investigating the utility of the cognitive-behavioral model of insomnia in early-stage lung cancer patients. J Pain Symptom Manage. 2005;30(2):160–169. [PubMed]
14. Roscoe JA, Morrow GR, Hickok JT, et al. Temporal interrelationships among fatigue, circadian rhythm and depression in breast cancer patients undergoing chemotherapy treatment. Support Care Cancer. 2002;10(4):329–336. [PubMed]
15. Mormont MC, De Prins J, Levi F. Study of circadian rhythms of activity by actometry: preliminary results in 30 patients with metastatic colorectal cancer. Pathol Biol (Paris) 1996;44(3):165–171. [PubMed]
16. Chevalier V, Mormont MC, Cure H, Chollet P. Assessment of circadian rhythms by actimetry in healthy subjects and patients with advanced colorectal cancer. Oncol Rep. 2003;10(3):733–737. [PubMed]
17. Minors D, Akerstedt T, Atkinson G, et al. The difference between activity when in bed and out of bed. I. Healthy subjects and selected patients. Chronobiol Int. 1996;13(1):27–34. [PubMed]
18. Mormont MC, Langouet AM, Claustrat B, et al. Marker rhythms of circadian system function: a study of patients with metastatic colorectal cancer and good performance status. Chronobiol Int. 2002;19(1):141–155. [PubMed]
19. Mormont MC, Waterhouse J, Bleuzen P, et al. Marked 24-h rest/activity rhythms are associated with better quality of life, better response, and longer survival in patients with metastatic colorectal cancer and good performance status. Clin Cancer Res. 2000;6(8):3038–3045. [PubMed]
20. Mormont MC, Waterhouse J. Contribution of the rest-activity circadian rhythm to quality of life in cancer patients. Chronobiol Int. 2002;19(1):313–323. [PubMed]
21. Rich T, Innominato PF, Boerner J, et al. Elevated serum cytokines correlated with altered behavior, serum cortisol rhythm, and dampened 24-hour rest-activity patterns in patients with metastatic colorectal cancer. Clin Cancer Res. 2005;11(5):1757–1764. [PubMed]
22. Miaskowski C, Lee KA. Pain, fatigue, and sleep disturbances in oncology outpatients receiving radiation therapy for bone metastasis: a pilot study. J Pain Symptom Manage. 1999;17(5):320–332. [PubMed]
23. Levin RD, Daehler MA, Grutsch JF, et al. Circadian function in patients with advanced non-small-cell lung cancer. Br J Cancer. 2005;93(11):1202–1208. [PMC free article] [PubMed]
24. Berger AM, VonEssen S, Kuhn BR, et al. Adherence, sleep, and fatigue outcomes after adjuvant breast cancer chemotherapy: results of a feasibility intervention study. Oncol Nurs Forum. 2003;30(3):513–522. [PubMed]
25. Young-McCaughan S, Mays MZ, Arzola SM, et al. Research and commentary: change in exercise tolerance, activity and sleep patterns, and quality of life in patients with cancer participating in a structured exercise program. Oncol Nurs Forum. 2003;30(3):441–454. discussion 441–454. [PubMed]
26. Van Someren EJ, Swart-Heikens J, Endert E, et al. Long-term effects of cranial irradiation for childhood malignancy on sleep in adulthood. Eur J Endocrinol. 2004;150(4):503–510. [PubMed]
27. Blackwell T, Ancoli-Israel S, Gehrman PR, et al. Actigraphy scoring reliability in the study of osteoporotic fractures. Sleep. 2005;28(12):1599–1605. [PubMed]
28. Ward DS, Evenson KR, Vaughn A, Rodgers AB, Troiano RP. Accelerometer use in physical activity: best practices and research recommendations. Med Sci Sports Exerc. 2005;37(11 Suppl):S582–S588. [PubMed]
29. Lichstein KL, Stone KC, Donaldson J, et al. Actigraphy validation with insomnia. Sleep. 2006;29(2):232–239. [PubMed]
30. Berger AM, Johnson PJ. Relationship between sleep/wake patterns and fatigue after chemotherapy: A comparison of diary versus actigraphs. Sigma Theta Tau. [Accessed February 11, 2005];
PubReader format: click here to try


Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...


  • PubMed
    PubMed citations for these articles

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...