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Walking Improves Sleep in Individuals With Cancer: A Meta-Analysis of Randomized, Controlled Trials

Hsiao-Yean Chiu

Hui-Chuan Huang

Pin-Yuan Chen


Wen-Hsuan Hou

Pei-Shan Tsai

sleep, walking, exercise
ONF 2015, 42(2), E54-E62. DOI: 10.1188/15.ONF.E54-E62

Purpose/Objectives: To evaluate the effectiveness of walking exercise on sleep in people with cancer.

Data Sources: Databases searched included China Knowledge Resource Integrated Database, CINAHL®, Cochrane Central Register of Controlled Trials, EMBASE, PsycINFO®, PubMed, Wanfang Data, and Web of Science.

Data Synthesis: Nine randomized, controlled trials involving 599 patients were included. Most of the studies used moderate-intensity walking exercise. Overall, walking exercise significantly improved sleep in people with cancer (Hedges’ g = –0.52). Moderator analyses showed that walking exercise alone and walking exercise combined with other forms of interventions yielded comparable effects on sleep improvement, and that the effect size did not differ among participants who were at different stages of cancer. The effect sizes for studies involving individuals with breast cancer and for studies including individuals with other types of cancer were similar.

Conclusions: Moderate-intensity walking exercise is effective in improving sleep in individuals with cancer.

Implications for Nursing: The authors’ findings support the inclusion of walking exercise into the multimodal approaches to managing sleep in people with cancer. Healthcare providers must convey the benefits of walking exercise to individuals with cancer who are suffering from sleep problems.

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    Early cancer diagnosis and treatment programs can prolong the lives of individuals with cancer. However, disturbed sleep is common among people with cancer, and many frequently report experiencing daily sleep disturbance following primary treatment (Davidson, MacLean, Brundage, & Schulze, 2002; Mercadante, Girelli, & Casuccio, 2004; Sela, Watanabe, & Nekolaichuk, 2005). Disturbed sleep may affect mental health, physical functioning, and health-related quality of life (Koopman et al., 2002; Le Guen et al., 2007; Romito et al., 2014).

    Pharmacologic treatments and cognitive behavioral therapy for insomnia (CBT-I) are commonly used to treat sleep problems in survivors (Espie et al., 2008; Savard, Simard, Ivers, & Morin, 2005; Vena, Parker, Cunningham, Clark, & McMillan, 2004). However, because of the adverse effects of medications (Kripke, 2000) and the problem of accessibility to CBT-I (Unbehaun, Spiegelhalder, Hirscher, & Riemann, 2010), many survivors may seek alternative sleep-management approaches that have minimal adverse effects and easy access.

    Exercise has been shown to improve sleep through physiologic mechanisms that include the regulation of immune-inflammatory response (Besedovsky, Lange, & Born, 2012; Lorton et al., 2006), core body temperature (Kunstetter et al., 2014; Nybo, 2012), autonomic function (Sandercock, Bromley, & Brodie, 2005), and endocrine function (Reis et al., 2011), as well as through psychological pathways, such as the improvement of mood status (Paluska & Schwenk, 2000; Taso et al., 2014). Walking has great potential to be an accessible, cost-effective, and feasible approach for managing sleep problems in individuals with cancer, particularly when compared to other forms of exercise (e.g., aquatic exercise, yoga, tai chi, Pilates-based exercises). Although some randomized, controlled trials (RCTs) have shown that walking improves sleep in people with cancer (Cheville et al., 2013; Coleman et al., 2012; Donnelly et al., 2011; Mock et al., 1997; Payne, Held, Thorpe, & Shaw, 2008; Tang, Liou, & Lin, 2010; Wang, Boehmke, Wu, Dickerson, & Fisher, 2011), other studies have produced dissimilar findings (Rogers et al., 2014; Sprod et al., 2010). Two meta-analyses (Mishra, Scherer, Geigle, et al., 2012; Mishra, Scherer, Snyder, et al., 2012) investigating the influence of exercise on sleep in survivors and in patients undergoing active cancer-related treatments, respectively, showed that exercise improved sleep in individuals with cancer. However, a close examination of the reviews revealed that the pooled effect-size calculation was based on pre- to-post-test change scores or post-test scores. Combining the two different summary measures to estimate the effect size is methodologically erroneous. A reexamination of the effect of exercise on sleep in people with cancer is warranted. In addition, these meta-analyses included studies that used various types of exercise (e.g., walking programs, aquatic exercise, yoga, tai chi, Pilates-based exercises), which hinders the determination of whether walking exercise alone exerts a distinct effect on sleep disturbance in individuals with cancer. An updated meta-analysis of studies focusing on the effects of walking exercise on sleep among people with cancer is clinically relevant.

    The authors of the current study conducted a meta-analysis of RCTs to determine the effect of walking exercise on sleep in individuals with cancer, and whether intervention components, patient characteristics, and methodologic features modulate the effects of walking exercise on sleep.

    Methods

    Search Strategies

    The authors’ meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher, Liberati, Tetzlaff, & Altman, 2009). Relevant studies were identified through searches of the following databases: China Knowledge Resource Integrated Database, CINAHL®, Cochrane Central Register of Controlled Trials, EMBASE, PsycINFO®, PubMed, Wanfang Data, and Web of Science. The search terms used were “sleep OR sleep disturbance OR sleep quality OR insomnia,” “cancer OR tumour OR tumor OR neoplasm OR chemotherapy OR radiotherapy,” and “home-based walking exercise OR walking exercise.” The date range was from the earliest publication date available in each database to May 2014. To confirm whether any relevant studies were published since the author’s initial search, the search was updated on July 15, 2014.

    Selection Criteria

    Studies involving individuals who had been diagnosed with any type of cancer and were aged 18 years or older were eligible for inclusion in the current study. In addition, studies in which walking had been used as the intervention were included, as were studies that included an alternative treatment group or an inactive control group (e.g., wait list, no treatment, usual care or exercise style).

    Studies that assessed a self-reported sleep outcome using validated scales (e.g., Pittsburgh Sleep Quality Index [PSQI], symptom Numeric Rating Scale, Symptom Assessment Scale, European Organisation for the Research and Treatment of Cancer Quality-of-Life Questionnaire–Core 30 [EORTC QLQ-C30]) were included. The PSQI is a 19-item scale that evaluates sleep quality during a one-month period. It has seven components that can be summed to obtain a global sleep quality score ranging from 0–21. A global PSQI score of greater than 5 is indicative of poor sleep quality. The PSQI exhibits good reliability and validity; the Cronbach alpha is 0.83, and concurrent validity is r = 0.33 (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). The 11-point symptom Numeric Rating Scale is a valid sleep measure, with a concurrent validity of r = 0.85 (Paice & Cohen, 1997). Higher scores indicate better sleep quality. The Symptom Assessment Scale measures sleep using a series of straight 100 mm lines, with higher scores reflecting worse sleep quality (Wewers & Lowe, 1990). The scale is considered to be reliable and valid; the test-retest reliability has been found to be 0.95–0.99, and the criterion-related validity is 0.42–0.91. The EORTC QLQ-C30 comprises five function and nine symptom subscales (one item assesses sleep) measuring sleep quality, with higher scores representing poorer sleep quality. The reliability and validity of the questionnaire have been established; the Cronbach alpha is 0.43–0.68, and the concurrent validity is 0.78–0.81 (Fredheim, Borchgrevink, Saltnes, & Kaasa, 2007; Groenvold, Klee, Sprangers, & Aaronson, 1997). Studies using a prospective RCT design that were published or accepted for publication in English or Chinese by a peer-reviewed journal were included.

    Study Selection

    Two investigators independently screened the titles and abstracts of articles identified using the search strategy previously described. After removing duplicate publications using Thomson Reuters EndNote X7, the remaining articles were reviewed in full. Only studies fulfilling the selection criteria were included in the current meta-analysis.

    Data Extraction and Methodology Quality Assessment

    Two investigators developed a data extraction sheet and independently extracted the data from each study, including (a) characteristics of the selected studies (e.g., authors’ names and year of publication), (b) characteristics of the patient populations (e.g., type of cancer, patient age, number of patients in each group, percentage of women in the sample), (c) characteristics of the intervention (e.g., type, frequency, length, and intensity of exercise), and (d) outcome measures. Quantitative data were extracted to calculate the effect size. When assessment time points were greater than one, the immediate postintervention measure was selected. Discrepancies were rechecked by the corresponding author of the current article and consensus was achieved by discussion.

    The following domains were assessed in relation to their risk of bias (Higgins & Green, 2011): (a) random sequence generation, (b) allocation concealment, (c) blinding of participants and staff, (d) blinding of outcome assessment, (e) incomplete outcome data, and (f) selective reporting. Each domain was rated as having “low,” “unclear,” or “high” risk of bias. Two reviewers independently performed the assessment of potential bias for each study, with a third reviewer serving as the arbitrator.

    Data Analysis

    Quantitative data were entered into Biostat Comprehensive Meta-Analysis, version 2.0. Two-sided p values were calculated, with p < 0.05 set as the level of statistical significance. First, pre- to post-test change scores were derived for the intervention group and control group from each included study. Then, the effect size for the difference between the intervention and control groups was calculated for each study. Hedges’ g was used as the measure of the effect size. It was calculated by finding the difference between the intervention and control group means (d), divided by their pooled standard deviation and multiplied by a factor (J) that corrects for underestimation of the population standard deviation. A forest plot was used to present the effect size of all of the included studies. An inverse variance random-effects model was applied to analyze the data because it is more conservative than a fixed-effects model (DerSimonian & Laird, 1986).

    To establish whether the selected studies differed significantly, the authors of the current study first examined whether the interstudy heterogeneity was statistically significant by evaluating the Cochran Q statistic (Higgins, Thompson, Deeks, & Altman, 2003), with p < 0.05 indicating significant heterogeneity. The magnitude of heterogeneity was measured using the I2 statistic, with I2 of 50% or greater indicating substantial heterogeneity across studies. A sensitivity analysis was also performed by removing the study with the largest effect size to determine its contribution to the overall effect size in the current meta-analysis.

    Subgroup analyses were conducted by dividing the studies into groups according to (a) type of intervention, (b) type of cancer, (c) whether sleep was the primary outcome, (d) stage of cancer treatment at enrollment, (e) whether random sequence generation was appropriately executed (risk of selection bias), and (f) whether allocation concealment was appropriately executed (risk of selection bias). Moderator analyses were performed to explore possible reasons for the observed heterogeneity. To ensure sufficient data for analyses, each moderator analysis was limited to instances in which groups were represented by at least three studies. For categorical moderators, a mixed-effect model was used to compare differences among the effect sizes in each comparison (Lipsey & Wilson, 2001). Metaregression was used for the analyses of continuous moderators (Lipsey & Wilson, 2001).

    Begg’s rank correlation (Begg & Mazumdar, 1994) and Egger’s intercept (Egger, Davey Smith, Schneider, & Minder, 1997) assess potential publication bias, with p > 0.05 indicating significant publication bias. The trim-and-fill method (Duval & Tweedie, 2000) was applied using a funnel plot to further assess potential publication bias. The overall effect size was adjusted by taking into account the estimated effect sizes of missing studies.

    Results

    The literature search initially identified 132 articles. Among these, 76 duplicates were excluded, and 45 articles were excluded because they were not RCTs or because they used patients and interventions that did not satisfy the current authors’ selection criteria. Three of the 12 remaining studies were excluded because they did not provide sufficient data to compute an effect size even after the authors were contacted (Payne et al., 2008; Rogers et al., 2009) or did not examine a self-reported sleep outcome (Coleman et al., 2012). The remaining nine studies were included in the current meta-analysis (Cheville et al., 2013; Donnelly et al., 2011; Mock et al., 1997; Rogers et al., 2014; Sprod et al., 2010; Tang et al., 2010; Wang et al., 2011; Wenzel et al., 2013; Wiskemann et al., 2011). This process is illustrated in Figure 1.

    Study Characteristics

    Patient demographic and disease characteristics are presented in Table 1. Study sample sizes ranged from 16–68 patients, with a total population of 599 randomized patients. Study participants were predominately women (65%). About half of the patients (42%) had a diagnosis of breast cancer. The most frequently used sleep measure was the PSQI.

    Details of the study intervention characteristics are presented in Table 2. In four studies, the interventions consisted solely of walking, whereas five studies used walking combined with other interventions (e.g., other exercise activities, a discussion group). The mean length of intervention was 9.5 weeks. The mean duration of an intervention session was 37.5 minutes, and the mean number of sessions per week was 4.5. The mean total intervention time was 1,602.1 minutes, with total intervention time in each study ranging from 675–2,880 minutes. The intensity of exercise was moderate in most of the studies. One study did not report the intensity of exercise, seven employed moderate-intensity exercise, and one used moderate-to-vigorous exercise. Only one study reported the time of day when the exercise was performed. The average adherence rate to walking exercise was 77%. Six trials did not document any adverse effects. Results of the methodologic quality assessment of the selected studies are shown in Table 3.

    Effects of Walking on Sleep

    The pooled mean effect sizes for the nine selected studies are shown in Tables 4 and 5. The weighted mean effect size was –0.52 (95% confidence interval [CI] [–0.79, –0.25]). No outlier was found because all effect sizes fell within two standard deviations of the mean. A sensitivity analysis was performed by removing the study with the largest effect size (Tang et al., 2010). The effect size of the walking interventions remained statistically significant (k = 8, Hedges’ g = –0.41). The Cochran Q (Q = 20.3, p = 0.009) and I2 statistics (61%) indicated significant heterogeneity across the nine selected studies. Therefore, subgroup analyses, moderator analyses, and metaregression were performed to further explore factors that might have contributed to the heterogeneity.

    Subgroup Analysis

    Walking alone (Hedges’ g = –0.7) and walking combined with other forms of exercise (Hedges’ g = –0.34) significantly improved sleep. Walking significantly improved sleep in individuals with breast cancer or other types of cancer (Hedges’ g = –0.56 and –0.5, respectively). The effect sizes of studies in which sleep was the primary outcome (Hedges’ g = –0.53) and studies in which sleep was the secondary outcome (Hedges’ g = –0.52) were statistically significant. The effect size for both subgroups, divided according to the stage of cancer treatment at enrollment, were statistically significant (Hedges’ g = –0.53 and –0.51, respectively).

    Moderator Analysis and Metaregression

    In terms of the categorical moderators, none of the factors were found to moderate the relationship between walking exercise and sleep improvement (p > 0.05). For the continuous moderators, the overall effect sizes were not significantly associated with age, the percentage of female patients, the duration of each intervention session, and the adherence rate (p = 0.92, 0.22, 0.46, and 0.44, respectively).

    Publication Bias

    According to the Egger’s test, the intercept of the effect size was –2.47, and the t value was 1.02 (two-tailed p = 0.34). In the Begg’s test, Kendall’s tau with continuity correction was –0.03, and the z value was 0.1 (p = 0.92). The results of the Egger’s and Begg’s tests indicated that no evidence of publication bias exists. The funnel plot indicated a potential selection bias. Therefore, the mean effect size was recalculated based on estimates for the missing studies using the trim-and-fill method, yielding an adjusted effect size of –0.58 (95% CI [–0.85, –0.31]).

    Discussion

    To the best of the authors’ knowledge, this is the first meta-analysis entailing the effects of walking on sleep in individuals with cancer. Overall, the authors of the current study found that walking improved sleep, with an effect size of –0.51. Previous meta-analyses could not determine whether exercise programs improve sleep in people with cancer (Mishra, Scherer, Geigle, et al., 2012; Mishra, Scherer, Snyder, et al., 2012), but the current authors’ findings show support for exercise’s ability to improve sleep in individuals with cancer.

    The intensity and timing of workouts are important factors in the sleep-related effects of exercise (Driver & Taylor, 2000). A previous meta-analysis demonstrated that moderate-to-vigorous exercise, rather than mild exercise, resulted in fewer sleep problems in individuals with cancer (Mishra, Scherer, Snyder, et al., 2012). Most studies included in this meta-analysis used moderate-intensity walking exercise. The current authors’ findings and those from previous studies collectively indicate that moderate-intensity exercise should be recommended for improving sleep in individuals with cancer. Unfortunately, most studies included in this meta-analysis did not report the time of day when exercise sessions were performed. Future studies of exercise programs for individuals with cancer should address this factor in their experimental design.

    Moderator analyses of intervention types revealed that walking exercise alone produced a treatment effect similar to that of a combination of walking and other forms of exercise. Therefore, walking alone is sufficient to improve sleep in individuals with cancer. The current authors also found that walking produced a treatment effect in individuals with breast cancer similar to that in patients with other types of cancer. Most of the studies included in this meta-analysis involved individuals with breast cancer; additional RCTs that investigate the beneficial effects of walking in individuals with different types of cancer are warranted. In addition, this meta-analysis revealed that walking significantly improved sleep among individuals with cancer before, during, and after cancer treatment. Although the current authors were unable to perform a meta-analytical analysis of possible harms associated with walking in this patient population, one of the included studies revealed that the adverse effects associated with walking were minimal (Wang et al., 2011). Walking is considered to be a relatively safe and effective approach for improving sleep in individuals with cancer at any treatment period. Healthcare providers must inform the individuals with cancer who are suffering from sleep problems about the benefit of walking as exercise.

    Limitations

    Although some of the studies included in this meta-analysis were less than optimal in terms of internal validity, the risk of bias associated with random sequence generation and allocation concealment did not affect the magnitude of effect size. In addition, certain design features of the current study support the strength of the authors’ findings. First, the meta-analysis used specific inclusion criteria with regard to the type of exercise; it also used a large total sample size. Second, the inclusion of only RCTs greatly increased the internal validity of the meta-analysis. However, several limitations must be taken into consideration. The exclusion of studies based on language might have limited the external validity of findings. In some studies, sleep was not the primary outcome. Two included studies (Donnelly et al., 2011; Wenzel et al., 2013) had fairly low adherence rates (i.e., 32% and 58%), and the overall sample size for included studies was small. In addition, the type and duration of walking were not consistent across studies. Finally, about 43% of participants were individuals with breast cancer, which, again, may limit generalizability of the findings.

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    Implications for Nursing and Conclusions

    The current authors' findings support the idea that walking exercise can be adopted into the multimodal approaches to managing sleep in individuals with cancer. Healthcare providers must convey the effectiveness of walking exercise to individuals with cancer who are facing sleep problems.

    Moderate-intensity walking is a safe and effective approach to improving sleep among individuals with cancer. Based on the findings of the moderator analyses, walking could be adopted by people with different types of cancer across different treatment stages. It could be used as a stand-alone treatment or in combination with other forms of interventions. To avoid the occurrence of adverse effects resulting from exercise, a medical assessment of cardiovascular and pulmonary functions may be needed beforehand.

    References

    Begg, C.B., & Mazumdar, M. (1994). Operating characteristics of a rank correlation test for publication bias. Biometrics, 50, 1088–1101.

    Besedovsky, L., Lange, T., & Born, J. (2012). Sleep and immune function. Pflügers Archiv: European Journal of Physiology, 463, 121–137. doi:10.1007/s00424-011-1044-0

    Buysse, D.J., Reynolds, C.F., 3rd, Monk, T.H., Berman, S.R., & Kupfer, D.J. (1989). The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research, 28, 193–213. doi:10.1016/0165-1781(89)90047-4

    Cheville, A.L., Kollasch, J., Vandenberg, J., Shen, T., Grothey, A., Gamble, G., & Basford, J.R. (2013). A home-based exercise program to improve function, fatigue, and sleep quality in patients with stage IV lung and colorectal cancer: A randomized controlled trial. Journal of Pain and Symptom Management, 45, 811–821. doi:10.1016/j.jpainsymman.2012.05.006

    Coleman, E.A., Goodwin, J.A., Kennedy, R., Coon, S.K., Richards, K., Enderlin, C., . . . Anaissie, E.J. (2012). Effects of exercise on fatigue, sleep, and performance: A randomized trial. Oncology Nursing Forum, 39, 468–477. doi:10.1188/12.ONF.468-477

    Davidson, J.R., MacLean, A.W., Brundage, M.D., & Schulze, K. (2002). Sleep disturbance in cancer patients. Social Science and Medicine, 54, 1309–1321. doi:10.1016/s0277-9536(01)00043-0

    DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled Clinical Trials, 7, 177–188. doi:10.1016/0197-2456(86)90046-2

    Donnelly, C.M., Blaney, J.M., Lowe-Strong, A., Rankin, J.P., Campbell, A., McCrum-Gardner, E., & Gracey, J.H. (2011). A randomised controlled trial testing the feasibility and efficacy of a physical activity behavioural change intervention in managing fatigue with gynaecological cancer survivors. Gynecologic Oncology, 122, 618–624. doi:10.1016/j.ygyno.2011.05.029

    Driver, H.S., & Taylor, S.R. (2000). Exercise and sleep. Sleep Medicine Reviews, 4, 387–402. doi:10.1053/smrv.2000.0110

    Duval, S., & Tweedie, R. (2000). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56, 455–463. doi:10.1111/j.0006-341x.2000.00455.x

    Egger, M., Davey Smith, G., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315, 629–634. doi:10.1136/bmj.315.7109.629

    Espie, C.A., Fleming, L., Cassidy, J., Samuel, L., Taylor, L.M., White, C.A., . . . Paul, J. (2008). Randomized controlled clinical effectiveness trial of cognitive behavior therapy compared with treatment as usual for persistent insomnia in patients with cancer. Journal of Clinical Oncology, 26, 4651–4658. doi:10.1200/JCO.2007.13.9006

    Fredheim, O.M., Borchgrevink, P.C., Saltnes, T., & Kaasa, S. (2007). Validation and comparison of the health-related quality-of-life instruments EORTC QLQ-C30 and SF-36 in assessment of patients with chronic nonmalignant pain. Journal of Pain and Symptom Management, 34, 657–665. doi:10.1016/j.jpainsymman.2007.01.011

    Groenvold, M., Klee, M.C., Sprangers, M.A., & Aaronson, N.K. (1997). Validation of the EORTC QLQ-C30 quality of life questionnaire through combined qualitative and quantitative assessment of patient-observer agreement. Journal of Clinical Epidemiology, 50, 441–450. doi:10.1016/s0895-4356(96)00428-3

    Higgins, J.P., & Green, S. (Eds.). (2011). Cochrane handbook for systematic reviews of interventions [v.5.1.0]. Retrieved from http://www.cochrane-handbook.org

    Higgins, J.P., Thompson, S.G., Deeks, J.J., & Altman, D.G. (2003). Measuring inconsistency in meta-analyses. BMJ, 327, 557–560. doi:10.1136/bmj.327.7414.557

    Koopman, C., Nouriani, B., Erickson, V., Anupindi, R., Butler, L.D., Bachmann, M.H., . . . Spiegel, D. (2002). Sleep disturbances in women with metastatic breast cancer. Breast Journal, 8, 362–370. doi:10.10146/j.1524-4741.2002.08606.x

    Kripke, D.F. (2000). Chronic hypnotic use: Deadly risks, doubtful benefit. Sleep Medicine Reviews, 4, 5–20. doi:10.1053/smrv.1999.0076

    Kunstetter, A.C., Wanner, S.P., Madeira, L.G., Wilke, C.F., Rodrigues, L.O., & Lima, N.R. (2014). Association between the increase in brain temperature and physical performance at different exercise intensities and protocols in a temperate environment. Brazilian Journal of Medical and Biological Research, 47, 679–688. doi:10.1590/1414-431x20143561

    Le Guen, Y., Gagnadoux, F., Hureaux, J., Jeanfaivre, T., Meslier, N., Racineux, J.L., & Urban, T. (2007). Sleep disturbances and impaired daytime functioning in outpatients with newly diagnosed lung cancer. Lung Cancer, 58, 139–143. doi:10.1016/j.lungcan.2007.05.021

    Lipsey, M.W., & Wilson, D.B. (2001). Practical meta-analysis. Thousand Oaks, CA: Sage.

    Lorton, D., Lubahn, C.L., Estus, C., Millar, B.A., Carter, J.L., Wood, C.A., & Bellinger, D.L. (2006). Bidirectional communication between the brain and the immune system: Implications for physiological sleep and disorders with disrupted sleep. Neuroimmunomodulation, 13, 357–374. doi:10.1159/000104864

    Mercadante, S., Girelli, D., & Casuccio, A. (2004). Sleep disorders in advanced cancer patients: Prevalence and factors associated. Supportive Care in Cancer, 12, 355–359. doi:10.1007/s00520-004-0623-4

    Mishra, S.I., Scherer, R.W., Geigle, P.M., Berlanstein, D.R., Topaloglu, O., Gotay, C.C., & Snyder, C. (2012). Exercise interventions on health-related quality of life for cancer survivors. Cochrane Database of Systematic Reviews, 8, CD007566. doi:10.1002/14651858.CD007566.pub2

    Mishra, S.I., Scherer, R.W., Snyder, C., Geigle, P.M., Berlanstein, D.R., & Topaloglu, O. (2012). Exercise interventions on health-related quality of life for people with cancer during active treatment. Clinical Otolaryngology, 37, 390–392. doi:10.1111/coa.12015

    Mock, V., Dow, K.H., Meares, C.J., Grimm, P.M., Dienemann, J.A., Haisfield-Wolfe, M.E., . . . Gage, I. (1997). Effects of exercise on fatigue, physical functioning, and emotional distress during radiation therapy for breast cancer. Oncology Nursing Forum, 24, 991–1000.

    Moher, D., Liberati, A., Tetzlaff, J., & Altman, D.G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151, 264–269. doi:10.7326/0003-4819-151-4-200908180-00135

    Nybo, L. (2012). Brain temperature and exercise performance. Experimental Physiology, 97, 333–339. doi:10.1113/expphysiol.2011.062273

    Paice, J.A., & Cohen, F.L. (1997). Validity of a verbally administered numeric rating scale to measure cancer pain intensity. Cancer Nursing, 20, 88–93.

    Paluska, S.A., & Schwenk, T.L. (2000). Physical activity and mental health: Current concepts. Sports Medicine, 29, 167–180. doi:10.2165/00007256-200029030-00003

    Payne, J.K., Held, J., Thorpe, J., & Shaw, H. (2008). Effect of exercise on biomarkers, fatigue, sleep disturbances, and depressive symptoms in older women with breast cancer receiving hormonal therapy. Oncology Nursing Forum, 35, 635–642. doi:10.1188/08.ONF.635-642

    Reis, E.S., Lange, T., Köhl, G., Herrmann, A., Tschulakow, A.V., Naujoks, J., . . . Köhl, J. (2011). Sleep and circadian rhythm regulate circulating complement factors and immunoregulatory properties of C5a. Brain, Behavior, and Immunity, 25, 1416–1426. doi:10.1016/j.bbi.2011.04.011

    Rogers, L.Q., Fogleman, A., Trammell, R., Hopkins-Price, P., Spenner, A., Vicari, S., . . . Verhulst, S. (2014). Inflammation and psychosocial factors mediate exercise effects on sleep quality in breast cancer survivors: Pilot randomized controlled trial. Psycho-Oncology. Advance online publication. doi:10.1002/pon.3594

    Rogers, L.Q., Hopkins-Price, P., Vicari, S., Markwell, S., Pamenter, R., Courneya, K.S., . . . Verhulst, S. (2009). Physical activity and health outcomes three months after completing a physical activity behavior change intervention: Persistent and delayed effects. Cancer Epidemiology, Biomarkers and Prevention, 18, 1410–1418. doi:10.1158/1055-9965.EPI-08-1045

    Romito, F., Cormio, C., De Padova, S., Lorusso, V., Berio, M.A., Fimiani, F., . . . Mattioli, V. (2014). Patients attitudes towards sleep disturbances during chemotherapy. European Journal of Cancer Care, 23, 385–393. doi:10.1111/ecc.12106

    Sandercock, G.R., Bromley, P.D., & Brodie, D.A. (2005). Effects of exercise on heart rate variability: Inferences from meta-analysis. Medicine and Science in Sports and Exercise, 37, 433–439. doi:10.1249/01.mss.0000155388.39002.9d

    Savard, J., Simard, S., Ivers, H., & Morin, C.M. (2005). Randomized study on the efficacy of cognitive-behavioral therapy for insomnia secondary to breast cancer, part I: Sleep and psychological effects. Journal of Clinical Oncology, 23, 6083–6096. doi:10.1200/jco.2005.09.548

    Sela, R.A., Watanabe, S., & Nekolaichuk, C.L. (2005). Sleep disturbances in palliative cancer patients attending a pain and symptom control clinic. Palliative and Supportive Care, 3, 23–31. doi:10.1017/s1478951505050042

    Sprod, L.K., Palesh, O.G., Janelsins, M.C., Peppone, L.J., Heckler, C.E., Adams, M.J., . . . Mustian, K.M. (2010). Exercise, sleep quality, and mediators of sleep in breast and prostate cancer patients receiving radiation therapy. Community Oncology, 7, 463–471. doi:10.1016/s1548-5315(11)70427-2

    Tang, M.F., Liou, T.H., & Lin, C.C. (2010). Improving sleep quality for cancer patients: Benefits of a home-based exercise intervention. Supportive Care in Cancer, 18, 1329–1339. doi:10.1007/s00520-009-0757-5

    Taso, C.J., Lin, H.S., Lin, W.L., Chen, S.M., Huang, W.T., & Chen, S.W. (2014). The effect of yoga exercise on improving depression, anxiety, and fatigue in women with breast cancer: A randomized controlled trial. Journal of Nursing Research, 22, 155–164. doi:10.1097/jnr.0000000000000044

    Unbehaun, T., Spiegelhalder, K., Hirscher, V., & Riemann, D. (2010). Management of insomnia: Update and new approaches. Nature and Science of Sleep, 2, 127–138. doi:10.2147/NSS.S6642

    Vena, C., Parker, K., Cunningham, M., Clark, J., & McMillan, S. (2004). Sleep-wake disturbances in people with cancer part I: An overview of sleep, sleep regulation, and effects of disease and treatment. Oncology Nursing Forum, 31, 735–746. doi:10.1188/04.ONF.735-746

    Wang, Y.J., Boehmke, M., Wu, Y.W., Dickerson, S.S., & Fisher, N. (2011). Effects of a 6-week walking program on Taiwanese women newly diagnosed with early-stage breast cancer. Cancer Nursing, 34, E1–E13. doi:10.1097/NCC.0b013e3181e4588d

    Wenzel, J.A., Griffith, K.A., Shang, J., Thompson, C.B., Hedlin, H., Stewart, K.J., . . . Mock, V. (2013). Impact of a home-based walking intervention on outcomes of sleep quality, emotional distress, and fatigue in patients undergoing treatment for solid tumors. Oncologist, 18, 476–484. doi:10.1634/theoncologist.2012-0278

    Wewers, M.E., & Lowe, N.K. (1990). A critical review of visual analogue scales in the measurement of clinical phenomena. Research in Nursing and Health, 13, 227–236. doi:10.1002/nur.4770130405

    Wiskemann, J., Dreger, P., Schwerdtfeger, R., Bondong, A., Huber, G., Kleindienst, N., . . . Bohus, M. (2011). Effects of a partly self-administered exercise program before, during, and after allogeneic stem cell transplantation. Blood, 117, 2604–2613. doi:10.1182/blood-2010-09-306308

    About the Author(s)

    Hsiao-Yean Chiu, RN, PhD, is an assistant professor in the College of Nursing at Taipei Medical University in Taiwan; Hui-Chuan Huang, RN, PhD, is an assistant professor in the Department of Nursing at Cardinal Tien College of Healthcare and Management in New Taipei City; Pin-Yuan Chen, MD, PhD, is an assistant professor in the School of Medicine at Chang Gung University in Taiwan and an attending physician in the Department of Neurosurgery at Chang Gung Memorial Hospital in Taoyuan; Wen-Hsuan Hou, MD, PhD, is an assistant professor in the Master Program in Long-Term Care, College of Nursing, at Taipei Medical University; and Pei-Shan Tsai, RN, PhD, is a professor in the College of Nursing at Taipei Medical University and a senior investigator at the Sleep Science Center at Taipei Medical University Hospital. This study was supported, in part, by a grant (No. NSC 102-2628-B-038-004-MY3) to Tsai and a fellowship (No. NSC 102-2811-B-038-028) to Chiu, both from the Ministry of Science and Technology. Tsai can be reached at ptsai@tmu.edu.tw, with copy to editor at ONFEditor@ons.org. (Submitted July 2014. Accepted for publication October 1, 2014.)

     

    References

    Begg, C.B., & Mazumdar, M. (1994). Operating characteristics of a rank correlation test for publication bias. Biometrics, 50, 1088–1101.
    Besedovsky, L., Lange, T., & Born, J. (2012). Sleep and immune function. Pflügers Archiv: European Journal of Physiology, 463, 121–137. doi:10.1007/s00424-011-1044-0
    Buysse, D.J., Reynolds, C.F., 3rd, Monk, T.H., Berman, S.R., & Kupfer, D.J. (1989). The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research, 28, 193–213. doi:10.1016/0165-1781(89)90047-4
    Cheville, A.L., Kollasch, J., Vandenberg, J., Shen, T., Grothey, A., Gamble, G., & Basford, J.R. (2013). A home-based exercise program to improve function, fatigue, and sleep quality in patients with stage IV lung and colorectal cancer: A randomized controlled trial. Journal of Pain and Symptom Management, 45, 811–821. doi:10.1016/j.jpainsymman.2012.05.006
    Coleman, E.A., Goodwin, J.A., Kennedy, R., Coon, S.K., Richards, K., Enderlin, C., . . . Anaissie, E.J. (2012). Effects of exercise on fatigue, sleep, and performance: A randomized trial. Oncology Nursing Forum, 39, 468–477. doi:10.1188/12.ONF.468-477
    Davidson, J.R., MacLean, A.W., Brundage, M.D., & Schulze, K. (2002). Sleep disturbance in cancer patients. Social Science and Medicine, 54, 1309–1321. doi:10.1016/s0277-9536(01)00043-0
    DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled Clinical Trials, 7, 177–188. doi:10.1016/0197-2456(86)90046-2
    Donnelly, C.M., Blaney, J.M., Lowe-Strong, A., Rankin, J.P., Campbell, A., McCrum-Gardner, E., & Gracey, J.H. (2011). A randomised controlled trial testing the feasibility and efficacy of a physical activity behavioural change intervention in managing fatigue with gynaecological cancer survivors. Gynecologic Oncology, 122, 618–624. doi:10.1016/j.ygyno.2011.05.029
    Driver, H.S., & Taylor, S.R. (2000). Exercise and sleep. Sleep Medicine Reviews, 4, 387–402. doi:10.1053/smrv.2000.0110
    Duval, S., & Tweedie, R. (2000). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56, 455–463. doi:10.1111/j.0006-341x.2000.00455.x
    Egger, M., Davey Smith, G., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315, 629–634. doi:10.1136/bmj.315.7109.629
    Espie, C.A., Fleming, L., Cassidy, J., Samuel, L., Taylor, L.M., White, C.A., . . . Paul, J. (2008). Randomized controlled clinical effectiveness trial of cognitive behavior therapy compared with treatment as usual for persistent insomnia in patients with cancer. Journal of Clinical Oncology, 26, 4651–4658. doi:10.1200/JCO.2007.13.9006
    Fredheim, O.M., Borchgrevink, P.C., Saltnes, T., & Kaasa, S. (2007). Validation and comparison of the health-related quality-of-life instruments EORTC QLQ-C30 and SF-36 in assessment of patients with chronic nonmalignant pain. Journal of Pain and Symptom Management, 34, 657–665. doi:10.1016/j.jpainsymman.2007.01.011
    Groenvold, M., Klee, M.C., Sprangers, M.A., & Aaronson, N.K. (1997). Validation of the EORTC QLQ-C30 quality of life questionnaire through combined qualitative and quantitative assessment of patient-observer agreement. Journal of Clinical Epidemiology, 50, 441–450. doi:10.1016/s0895-4356(96)00428-3
    Higgins, J.P., & Green, S. (Eds.). (2011). Cochrane handbook for systematic reviews of interventions [v.5.1.0]. Retrieved from http://www.cochrane-handbook.org
    Higgins, J.P., Thompson, S.G., Deeks, J.J., & Altman, D.G. (2003). Measuring inconsistency in meta-analyses. BMJ, 327, 557–560. doi:10.1136/bmj.327.7414.557
    Koopman, C., Nouriani, B., Erickson, V., Anupindi, R., Butler, L.D., Bachmann, M.H., . . . Spiegel, D. (2002). Sleep disturbances in women with metastatic breast cancer. Breast Journal, 8, 362–370. doi:10.10146/j.1524-4741.2002.08606.x
    Kripke, D.F. (2000). Chronic hypnotic use: Deadly risks, doubtful benefit. Sleep Medicine Reviews, 4, 5–20. doi:10.1053/smrv.1999.0076
    Kunstetter, A.C., Wanner, S.P., Madeira, L.G., Wilke, C.F., Rodrigues, L.O., & Lima, N.R. (2014). Association between the increase in brain temperature and physical performance at different exercise intensities and protocols in a temperate environment. Brazilian Journal of Medical and Biological Research, 47, 679–688. doi:10.1590/1414-431x20143561
    Le Guen, Y., Gagnadoux, F., Hureaux, J., Jeanfaivre, T., Meslier, N., Racineux, J.L., & Urban, T. (2007). Sleep disturbances and impaired daytime functioning in outpatients with newly diagnosed lung cancer. Lung Cancer, 58, 139–143. doi:10.1016/j.lungcan.2007.05.021
    Lipsey, M.W., & Wilson, D.B. (2001). Practical meta-analysis. Thousand Oaks, CA: Sage.
    Lorton, D., Lubahn, C.L., Estus, C., Millar, B.A., Carter, J.L., Wood, C.A., & Bellinger, D.L. (2006). Bidirectional communication between the brain and the immune system: Implications for physiological sleep and disorders with disrupted sleep. Neuroimmunomodulation, 13, 357–374. doi:10.1159/000104864
    Mercadante, S., Girelli, D., & Casuccio, A. (2004). Sleep disorders in advanced cancer patients: Prevalence and factors associated. Supportive Care in Cancer, 12, 355–359. doi:10.1007/s00520-004-0623-4
    Mishra, S.I., Scherer, R.W., Geigle, P.M., Berlanstein, D.R., Topaloglu, O., Gotay, C.C., & Snyder, C. (2012). Exercise interventions on health-related quality of life for cancer survivors. Cochrane Database of Systematic Reviews, 8, CD007566. doi:10.1002/14651858.CD007566.pub2
    Mishra, S.I., Scherer, R.W., Snyder, C., Geigle, P.M., Berlanstein, D.R., & Topaloglu, O. (2012). Exercise interventions on health-related quality of life for people with cancer during active treatment. Clinical Otolaryngology, 37, 390–392. doi:10.1111/coa.12015
    Mock, V., Dow, K.H., Meares, C.J., Grimm, P.M., Dienemann, J.A., Haisfield-Wolfe, M.E., . . . Gage, I. (1997). Effects of exercise on fatigue, physical functioning, and emotional distress during radiation therapy for breast cancer. Oncology Nursing Forum, 24, 991–1000.
    Moher, D., Liberati, A., Tetzlaff, J., & Altman, D.G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151, 264–269. doi:10.7326/0003-4819-151-4-200908180-00135
    Nybo, L. (2012). Brain temperature and exercise performance. Experimental Physiology, 97, 333–339. doi:10.1113/expphysiol.2011.062273
    Paice, J.A., & Cohen, F.L. (1997). Validity of a verbally administered numeric rating scale to measure cancer pain intensity. Cancer Nursing, 20, 88–93.
    Paluska, S.A., & Schwenk, T.L. (2000). Physical activity and mental health: Current concepts. Sports Medicine, 29, 167–180. doi:10.2165/00007256-200029030-00003
    Payne, J.K., Held, J., Thorpe, J., & Shaw, H. (2008). Effect of exercise on biomarkers, fatigue, sleep disturbances, and depressive symptoms in older women with breast cancer receiving hormonal therapy. Oncology Nursing Forum, 35, 635–642. doi:10.1188/08.ONF.635-642
    Reis, E.S., Lange, T., Köhl, G., Herrmann, A., Tschulakow, A.V., Naujoks, J., . . . Köhl, J. (2011). Sleep and circadian rhythm regulate circulating complement factors and immunoregulatory properties of C5a. Brain, Behavior, and Immunity, 25, 1416–1426. doi:10.1016/j.bbi.2011.04.011
    Rogers, L.Q., Fogleman, A., Trammell, R., Hopkins-Price, P., Spenner, A., Vicari, S., . . . Verhulst, S. (2014). Inflammation and psychosocial factors mediate exercise effects on sleep quality in breast cancer survivors: Pilot randomized controlled trial. Psycho-Oncology. Advance online publication. doi:10.1002/pon.3594
    Rogers, L.Q., Hopkins-Price, P., Vicari, S., Markwell, S., Pamenter, R., Courneya, K.S., . . . Verhulst, S. (2009). Physical activity and health outcomes three months after completing a physical activity behavior change intervention: Persistent and delayed effects. Cancer Epidemiology, Biomarkers and Prevention, 18, 1410–1418. doi:10.1158/1055-9965.EPI-08-1045
    Romito, F., Cormio, C., De Padova, S., Lorusso, V., Berio, M.A., Fimiani, F., . . . Mattioli, V. (2014). Patients attitudes towards sleep disturbances during chemotherapy. European Journal of Cancer Care, 23, 385–393. doi:10.1111/ecc.12106
    Sandercock, G.R., Bromley, P.D., & Brodie, D.A. (2005). Effects of exercise on heart rate variability: Inferences from meta-analysis. Medicine and Science in Sports and Exercise, 37, 433–439. doi:10.1249/01.mss.0000155388.39002.9d
    Savard, J., Simard, S., Ivers, H., & Morin, C.M. (2005). Randomized study on the efficacy of cognitive-behavioral therapy for insomnia secondary to breast cancer, part I: Sleep and psychological effects. Journal of Clinical Oncology, 23, 6083–6096. doi:10.1200/jco.2005.09.548
    Sela, R.A., Watanabe, S., & Nekolaichuk, C.L. (2005). Sleep disturbances in palliative cancer patients attending a pain and symptom control clinic. Palliative and Supportive Care, 3, 23–31. doi:10.1017/s1478951505050042
    Sprod, L.K., Palesh, O.G., Janelsins, M.C., Peppone, L.J., Heckler, C.E., Adams, M.J., . . . Mustian, K.M. (2010). Exercise, sleep quality, and mediators of sleep in breast and prostate cancer patients receiving radiation therapy. Community Oncology, 7, 463–471. doi:10.1016/s1548-5315(11)70427-2
    Tang, M.F., Liou, T.H., & Lin, C.C. (2010). Improving sleep quality for cancer patients: Benefits of a home-based exercise intervention. Supportive Care in Cancer, 18, 1329–1339. doi:10.1007/s00520-009-0757-5
    Taso, C.J., Lin, H.S., Lin, W.L., Chen, S.M., Huang, W.T., & Chen, S.W. (2014). The effect of yoga exercise on improving depression, anxiety, and fatigue in women with breast cancer: A randomized controlled trial. Journal of Nursing Research, 22, 155–164. doi:10.1097/jnr.0000000000000044
    Unbehaun, T., Spiegelhalder, K., Hirscher, V., & Riemann, D. (2010). Management of insomnia: Update and new approaches. Nature and Science of Sleep, 2, 127–138. doi:10.2147/NSS.S6642
    Vena, C., Parker, K., Cunningham, M., Clark, J., & McMillan, S. (2004). Sleep-wake disturbances in people with cancer part I: An overview of sleep, sleep regulation, and effects of disease and treatment. Oncology Nursing Forum, 31, 735–746. doi:10.1188/04.ONF.735-746
    Wang, Y.J., Boehmke, M., Wu, Y.W., Dickerson, S.S., & Fisher, N. (2011). Effects of a 6-week walking program on Taiwanese women newly diagnosed with early-stage breast cancer. Cancer Nursing, 34, E1–E13. doi:10.1097/NCC.0b013e3181e4588d
    Wenzel, J.A., Griffith, K.A., Shang, J., Thompson, C.B., Hedlin, H., Stewart, K.J., . . . Mock, V. (2013). Impact of a home-based walking intervention on outcomes of sleep quality, emotional distress, and fatigue in patients undergoing treatment for solid tumors. Oncologist, 18, 476–484. doi:10.1634/theoncologist.2012-0278
    Wewers, M.E., & Lowe, N.K. (1990). A critical review of visual analogue scales in the measurement of clinical phenomena. Research in Nursing and Health, 13, 227–236. doi:10.1002/nur.4770130405
    Wiskemann, J., Dreger, P., Schwerdtfeger, R., Bondong, A., Huber, G., Kleindienst, N., . . . Bohus, M. (2011). Effects of a partly self-administered exercise program before, during, and after allogeneic stem cell transplantation. Blood, 117, 2604–2613. doi:10.1182/blood-2010-09-306308