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Published in final edited form as: Support Care Cancer. 2010 Dec 21;20(2):245–252. doi: 10.1007/s00520-010-1060-1

Predictors of adherence to a behavioral therapy sleep intervention during breast cancer chemotherapy

Dennis E McChargue 1, Jayashri Sankaranarayanan 2, Constance G Visovsky 3, Ellyn E Matthews 4, Krista B Highland 5, Ann M Berger 6
PMCID: PMC9677574  NIHMSID: NIHMS1836981  PMID: 21174129

Abstract

Background

This study’s purpose was twofold: (1) to establish adherence rates to a behavioral therapy (BT) sleep intervention and (2) to identify psychological and physical symptom predictors of adherence to the intervention in women undergoing breast cancer chemotherapy.

Methods

A randomized controlled trial began 48 h before the first of four chemotherapy treatments. Women with stages I–IIIA breast cancer (n=113) received a BT sleep intervention composed of stimulus control, modified sleep restriction (MSR), relaxation therapy (RT), and sleep hygiene counseling components. A BT plan was developed by a research nurse and each participant, reinforced on day 8, and repeated for chemotherapy cycles 2, 3, and 4. Adherence to the BT plan was measured daily; total adherence score was computed at each chemotherapy cycle by combining adherence estimates of all BT plan components. Psychological and physical symptoms over the past 7 days were measured 2 days prior to and 7 days after each chemotherapy treatment.

Results

Total adherence rates to the BT plan were 51–52% at all four treatments but adherence varied by component. Sleep disturbance, pain, and anxiety significantly decreased whereas depression significantly increased across chemotherapy. Structural equation modeling revealed a good model fit with decreasing sleep disturbances (0.409) and increasing depression (−0.711) contributing to lower total adherence rates. Increasing depression predicted lower MSR adherence (−0.203) and decreasing sleep disturbances predicted lower RT adherence (1.220).

Conclusions

Sleep disturbance and depression significantly impacted adherence rates during chemotherapy. Results warrant attention when promoting adherence to BT sleep interventions during chemotherapy treatment.

Keywords: Adherence, Breast cancer, Oncology, Depression, Sleep disturbance, Behavioral intervention

Introduction

Sleep disturbance is defined as the perceived or actual alterations in night sleep with subsequent daytime impairment without a diagnosed sleep disorder, such as insomnia [1, 2]. Sleep disturbance is highly prevalent in breast cancer patients, i.e., 23–61% [2–4]. Frequent reports of decreased sleep maintenance, increased daytime sleepiness, and poor quality sleep are documented before patients undergo chemotherapy [5], and increased symptom burden (e.g., concentration problems and pain) during treatment compounds prolonged sleep disturbance [6]. Sleep disturbance is also associated with greater fatigue severity [7, 8] and may, at least indirectly, contribute to dose reduction or delay in treatment via its association with fatigue, pain, and/or depression [9, 10]. The increased accidents and psychiatric problems, as well as reduced quality of life and work productivity [11] related to insomnia in the general population, underscore the need for an acceptable, effective therapy for sleep disturbances in breast cancer patients.

Treatment for sleep problems among breast cancer patients has mainly focused on diagnosed insomnia and not sleep disturbance. Behavioral therapy (BT) is endorsed by the American Academy of Sleep Medicine for treating chronic insomnia secondary to comorbid conditions (e.g., cancer), which consists of a variety of therapies, including stimulus control, sleep restriction, relaxation techniques, and sleep hygiene [12]. Among breast cancer patients, BT interventions for insomnia improve sleep and reduce other symptoms across time [13]. BT approaches also avoid the associated habit-forming, cognitive, and psychomotor impairments related to medications [14].

To our knowledge, only one study has tested 1-year outcomes of a BT intervention to improve generalized sleep disturbance outside of a diagnosed sleep disorder [15]. Findings show some improvement in sleep quality, but the average sleep quality scores at 30 days post-treatment remained in the sleep disturbed range [16]. These data suggest that generalized sleep disturbance was difficult to treat during chemotherapy and evoke questions about what factors may have prevented sleep quality from improving to the asymptomatic range.

One of the most important factors that influence sleep outcomes associated with BT sleep interventions in persons with chronic insomnia has been patients’ adherence to the BT plan [15, 17]. Reported rates of adherence have only been 50% for medication usage, and adherence to lifestyle and behaviorally demanding therapies such as a BT sleep intervention is even lower [18]. A quantitative review of 50 years of research also reported that adherence was lowest in pulmonary disease, diabetes, and sleep [19]. Taken together, the overall aim of the present paper was to understand adherence to a BT sleep intervention for generalized sleep disturbance among breast cancer patients receiving chemotherapy.

The concept of adherence or its earlier designation, compliance, was first described as the extent to which a person’s behavior coincides with medical or health advice [20]. The term compliance emphasizes authority of healthcare providers and implies that patients are passive recipients of care. The World Health Organization attempted to change the undertone of paternalism associated with the term compliance by introducing the term adherence. Adherence implies patient agreement with medical or health recommendations and refers to patient’s engagement or participation in a treatment regimen believed to be of therapeutic benefit and is enacted through an essential partnership with providers to successfully complete the prescribed treatment regimen. Despite the relative importance of adherence on BT sleep outcomes during chemotherapy, factors that contribute to poor adherence are not well understood [21]. Identifying such factors may lead to improved sleep outcomes [22].

Although adherence to BT sleep interventions for generalized sleep disturbance has yet to be explored, supportive evidence from insomnia treatment research suggests that a variety of factors (e.g., psychological, physical symptoms, medical, and/or demographic variables) may reduce adherence to BT sleep interventions. For example, with few exceptions [23], psychological status (specifically depression and anxiety) is associated with lower adherence to cognitive-behavioral therapy in insomnia [22, 24, 25]. Other factors that correlate with lower adherence to sleep interventions include older age [26], male gender [25], and greater symptom severity related to sleep disturbance [18]. Studies also report that poor physical health [27], lower self-efficacy for following the BT sleep intervention plan [28], and lower psychosocial functioning [29] were associated with lower adherence, suggesting that physical symptoms and lack of confidence in abilities may decrease adherence [20]. These factors help explain why 11–33% of cancer patients drop out of individual or group cognitive-behavioral therapy for insomnia [30, 31] and may be implicated in adhering to BT treatment targeting generalized sleep disturbance among breast cancer patients.

Our study objectives were twofold. First, we established adherence rates to the BT sleep intervention targeting sleep disturbances without a diagnosed sleep disorder. Second, we examined whether changes in psychological (anxiety, depression) and physical symptoms (sleep disturbance, fatigue, pain, nausea, appearance dissatisfaction, appetite, concentration, and bowel pattern) predicted changes in adherence rates across four chemotherapy treatments. We hypothesize that increased psychological and physical symptoms would predict lower adherence to the BT sleep intervention.

Methods

Design

Secondary adherence data were derived from a clinical trial that randomized women (n=213) undergoing adjuvant breast cancer treatment to either an individualized sleep intervention or a healthy eating control. Further details of the original study’s participant flow, procedures, instruments, and primary findings may be found at [16]. For the purposes of the adherence questions, the sample was restricted to those receiving active BT intervention (n=113) and did not include those from the healthy eating control group.

Sample

Participants were recruited between April 2003 and May 2006 at two cancer centers and ten community oncology clinics in the Midwestern USA. Inclusion criteria were: (1) women aged ≥19, (2) initial diagnosis of stages I–IIIA breast cancer, (3) postoperative for mastectomy or lumpectomy, (4) scheduled to begin four anthracycline-based intravenous chemotherapy treatments with or without four additional taxane treatments, and (5) Karnofsky Performance Scale score >60. Exclusion criteria were: self-reported history of chronic insomnia, chronic fatigue syndrome, unstable heart, lung or neuromuscular disease, insulin-dependent diabetes, sleep apnea, chronic oral steroid therapy prior to entering chemotherapy, and nightshift employment.

Procedures

The present study was approved by the primary site’s institutional review board and 11 participating clinics. Following HIPAA guidelines, a research nurse contacted and enrolled potential participants. A 90–120-min visit with a research nurse was conducted at the participant’s home or another preferred site at least 2 days before the first treatment. After signing an informed consent, participants were randomized to the BT or control group.

Experimental condition

At the first visit, BT group participants negotiated with the research nurse to develop a 12-item Individual Sleep Promotion Plan (ISPP©), hereafter referred to as the BT plan. A sleep psychologist trained the research nurses to deliver the intervention per protocol and monitored treatment fidelity with a review of cases during weekly meetings. As described in more detail elsewhere [16], BT plans were individualized prior to entering chemotherapy and revised before starting another chemotherapy treatment. Women were also encouraged to continue their sleep treatment in between treatments. Researchers and participants discussed barriers to adherence and strategized solutions throughout the protocol.

The 12-item BT plan included four components common to BT for insomnia: stimulus control (SC), modified sleep restriction (MSR), relaxation therapy (RT), and sleep hygiene counseling (SHC). All BT participants received SC and MSR instructions and were allowed to select RT and SHC methods from a list of 17 relaxation and 20 sleep hygiene options. The list of SHC options was tailored to breast cancer patients receiving chemotherapy and focused on managing other symptoms as well as traditional SHC options. A MSR strategy was used in this study because clinical judgment and experience led us to be more lenient. Revisions to the BT plan were made based on sleep diary data and adherence rates at treatment 2. Participants had the opportunity to keep the same or select different RT or SHC techniques. Each clinic managed chemotherapy symptoms per standard guidelines.

Instruments

Adherence

The 12-item BT plan was used to record daily adherence of SC, MSR, RT, and SHC. Women completed the BT plan each morning for 9 days (2 days prior and 7 days after each treatment) by placing #1 in the box for all items used the previous night, #2 in the box for any items they should have used but did not, #3 if only expected one time, and #9 if it did not apply at all. Marks of #3 (it happened once) accounted for less than 0.0001%. Adherence was behaviorally defined as acknowledging the use of treatment recommendations. Thus, adherence estimates were derived for each BT plan component by totaling all #1 responses among items that reflected a particular component. A total adherence score was computed at each treatment (1–4) by combining adherence estimates of all BT plan components.

Psychological Hospital Anxiety and Depression Scale (HADS)

Psychological Hospital Anxiety and Depression Scale (HADS) [32] is a 14-item, multidimensional, self-report scale that was used to screen for anxiety (7 items) and depression (7 items) on a 4-point scale (0 to 3; total 0–21 for each). Alpha reliabilities for the anxiety subscale ranged from 0.83 to 0.93 and for depression subscale from 0.85 to 0.90 in this study. HADS scores were obtained at day −2 [reflecting 7 days before the first treatment] and day +7 after treatments 3 and 4 [reflecting on how they felt the first 7 days after each treatment].

Symptoms The Symptom Experience Scale (SES)

Symptoms The Symptom Experience Scale (SES) is a 24-item scale designed to measure women’s symptoms associated with treatment for breast cancer [33]. Eight physical symptoms or sensations (nausea, pain, fatigue, disturbances in appetite, sleep, bowel pattern, concentration, and appearance) were rated on a 5-point Likert scale in three dimensions (frequency, intensity, and distress) (0= none to 4 maximum; total 0–32). SES scores were obtained at day −2 [reflecting 7 days before the start of each treatment] and day +7 [reflecting the first 7 days after each treatment]. Baseline SES measures were collected at day −2 of the first treatment. When measuring across treatments, SES scores reflect the average for each symptom across day −2 and day +7 time points.

Demographic/medical characteristics

Demographic/medical characteristics were collected before treatment on age, education, marital status, cancer stage, and Karnofsky performance score.

Data analysis

Descriptive statistics were performed to describe the sample’s demographic and medical characteristics. Mean (SE) estimates and repeated measures ANOVA values were run for the psychological and physical symptom variables across chemotherapy treatment. Correlations were performed to determine the relationship between demographic and medical data with adherence rates. A structural equation model (SEM) examined the degree to which change in psychological and physical symptoms influenced patients’ adherence to the BT plan across four chemotherapy treatments. The dependent variables were the rate of change in adherence to the four BT plan components and to total adherence to the BT plan. Our independent variables were the change over time in psychological and physical symptoms. Symptom change scores were derived using two time points: day −2 before the start of any chemotherapy and day +7 following the fourth chemotherapy treatment.

SEM was employed for a number of reasons. First, SEM develops a model of the relations among variables in order to determine causal and associative relationships [34]. In addition, SEM examines the relationship between multiple longitudinal growth curves while controlling for other variables stated in the model. Finally, SEM tests for both linear and non-linear effects on the criterion variables [35] and infers the existence of latent variables from a pattern of correlations among observed variables [36]. Reported psychological and physical symptoms were those that provided the best overall fit.

The model was estimated using M Plus version 5.1. Chi-square test of model fit, comparative fit index (CFI) and standardized root mean square residual (SRMR) were used as the primary criteria of model fit with cutoff values of CFI >0.95, and SRMR <0.06 interpreted to indicate good model fit. Consistent with Duncan et al. [34], good fitting growth curve models illustrate predictors of BT plan intercepts and growth slopes. Intercepts reflect the values of dependent measures at the start of change and growth slopes reflect dependent measures’ rate of change across the four chemotherapy treatments.

Results

Sample description and adherence rates

Seventy-two percent of BT sleep intervention participants were employed full or part-time, 97% were Caucasian, and 63% had household incomes more than $40,000/year [16]. Approximately 42.5% of participants obtained bachelor degrees or higher, 31.9% attended some college/trade school, and 25.7% obtained a high school/equivalent diploma. Many participants were married (69.9%), with 17.7% reported being divorced, 7.1% single, and 5.3% widowed. Medical information indicated that 50.4% of women were postmenopausal, and as a group, they were overweight (BMI=28.11; SE=0.634). Cancer status was as follows: stage I (29%), stage II (57%), and stage IIIA (14%).

Mean (SE) estimates and repeated measures ANOVA values for the psychological and physical symptom variables across chemotherapy treatments 1 through 4 are shown in Table 1. Results showed that a number of symptoms significantly fluctuated across chemotherapy. Systematic changes showed that sleep disturbance, pain, and anxiety significantly decreased as chemotherapy progressed, whereas depression significantly increased across chemotherapy. Differences in BT adherence percentages across chemotherapy treatment are displayed in Table 2. Results show that participants exhibited reduced MSR adherence across treatments with notable differences comparing treatment 1 to treatment 4. Participants’ RT adherence also significantly increased across time, with at treatment 3 substantially higher than at treatment 1. Higher Karnofsky performance score (r=0.23, p<0.05) and more education (r=0.23, p<0.05), but not age, were correlated with higher overall total adherence.

Table 1.

Psychological and symptom variables across chemotherapy (n=113)

Treatment 1, means (SE) Treatment 2, means (SE) Treatment 3, means (SE) Treatment 4, means (SE) Within-subjects effects, F(p)
Sleep disturbance (0–4) 2.09 ad (0.11) 1.81 cd (0.10) 1.74 bc (0.12) 1.50 b (0.11) 8.00 (<0.01)
Fatigue (0–4) 2.29 (0.08) 2.33 (0.09) 2.42 (0.10) 2.44 (0.10) 2.51 (0.06)
Pain (0–4) 1.95 a (0.11) 1.34 b (0.11) 1.27 b (0.11) 1.21 b (0.12) 15.62 (<0.01)
Nausea (0–4) 1.33 (0.09) 1.32 (0.10) 1.27 (0.09) 1.51 (0.12) 2.24 (0.08)
Appearance dissatisfaction (0–4) 0.77 a (0.09) 1.49 b (0.12) 1.30 bc (0.14) 1.17 c (0.12) 12.98 (<0.01)
Appetite (0–4) 1.47 a (.10) 1.23 b (0.10) 1.37 ab (0.10) 1.46 ab (0.12) 3.32 (0.02)
Concentration (0–4) 1.36 (0.10) 1.26 (0.10) 1.48 (0.10) 1.45 (0.11) 2.91 (0.04)
Bowel pattern (0–4) 1.56 (0.11) 1.46 (0.10) 1.65 (0.12) 1.70 (0.13) 2.31 (0.08)
Anxiety (0–21) 6.67 a (0.42) N/A 5.91 ab (0.39) 5.63 b (0.43) 6.65 (<0.01)
Depression (0–21) 3.21 a (0.28) N/A 5.80 b (0.43) 6.06 b (0.42) 53.85 (<0.01)
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Eight symptoms were measured with the Symptom Experience Scale (SES; [35]). Lower scores indicate lower symptoms. SES was filled out on day −2 and day +7 of each treatment, reflecting on the previous 7 days. Results reflect the average of the dimensions across the two time points.Anxiety and depression were measured with the Hospital Anxiety and Depression Scale [34] completed on day +7 after treatments 1, 3, and 4. Significant repeated measures analyses for each psychological and symptom factor are marked with “a–d”

Table 2.

Percentages for BT adherence across chemotherapy treatments (n=113)

BT component Treatment 1 (%) Treatment 2 (%) Treatment 3 (%) Treatment 4 (%) Within-subject effects, F
Stimulus control 35.20 33.10 34.05 32.05 1.33
Modified sleep restriction 50.20a 48.61 45.82 44.93b 3.03*
Relaxation therapy 58.4b 63.14 70.29a 66.23 3.71*
Sleep hygiene counseling 64.70 66.25 66.86 65.64 0.37
Total adherence 51.10 51.82 51.93 51.93 0.45
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Significant repeated measures analyses are marked with an asterisk. Letters a and b indicate significant LSDs between treatments

Psychological and physical symptoms predict growth slopes of adherence

SEM analyses tested the degree to which changes in psychological and physical symptoms affected adherence growth rates across four chemotherapy treatments. Among the viable symptoms, results produced a good model fit for total adherence while entering fatigue, anxiety, sleep disturbance, and depression within the model [Satorra-Bentler χ2 (14, N=113) = 34.661, p=0.0016, CFI=0.952, SRMR=0.036]. No other symptoms contributed to a good model fit and were no longer considered. Illustrated by the growth diagram (Fig. 1), decreased sleep disturbances predicted significant decreases in the total adherence growth slope (B=0.409, SE=0.176, p=0.002), whereas increased depression predicted decreases in total adherence growth slope (B=−0.711, SE=0.138, p<0.001). Changes in fatigue and anxiety did not significantly predict changes in total adherence rates within the model.

Fig. 1.

Fig. 1

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SEM growth diagram for total adherence

When the individual BT plan components (i.e., SC, MSR, RT, and SHC) were modeled separately, two treatment components produced a good model fit (see Figs. 2 and 3): MSR [Satorra-Bentler χ2 (14, N=113) = 18.123, p=0.2013, CFI=0.988, SRMR=0.036] and RT [Satorra-Bentler χ2 (14, N=113) = 20.328, p=0.1201, CFI=0.974, SRMR=0.048]. Increased depression predicted significant decreases in the MSR adherence growth slope (B=−0.203, SE=0.087, p=0.019). Decreased sleep disturbances predicted significant decreases in the RT adherence growth slope (B=1.220, SE=0.397, p=0.002) and lower RT adherence at the start of treatment (growth intercept: B=0.688, SE=0.300, p=0.022). The SHC [Satorra-Bentler χ2 (14, N=113) = 47.866, p<0.001, CFI=0.21, SRMR=0.049] model did not result in a good fit and the SC model demonstrated a complete lack of fit. Because there was a lack of convergence and the number of iterations was exceeded within the SC model, no Satorra-Bentler estimates were available.

Fig. 2.

Fig. 2

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SEM growth diagram for modified sleep restriction

Fig. 3.

Fig. 3

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SEM growth diagram for relaxation therapy

Discussion

To our knowledge, this is the first detailed study of adherence to an individualized BT sleep intervention targeting generalized sleep disturbance during breast cancer chemotherapy. Participants’ psychological and most physical symptoms significantly fluctuated across time. Notably, depression significantly increased while participants’ sleep disturbance, anxiety, and pain showed linear decreases. Participants were also less adherent to MSR and more adherent to RT across chemotherapy treatments. Sleep disturbances and depression significantly impacted adherence growth rates. Specifically, as sleep disturbances improved and depression increased across the four chemotherapy treatments, participants progressively adhered less to the BT plan.

Our first aim was to establish adherence rates to the BT sleep intervention. Adherence rates of 51–52% to the total BT sleep intervention were similar to most reports of adherence to combined behavioral interventions for sleep disturbance [22, 37]. In the present study, participants’ adherence to sleep restriction (45–50%) and stimulus control (32–35%) across four chemotherapy treatments was lower than some studies of primary insomnia [28, 38] and similar to others [39, 40]. Prior studies suggest that suboptimal adherence to sleep restriction may result from fundamentally counterintuitive recommendation to limit sleep, objections to increased daytime sleepiness, complaints of boredom and lack of activities because of delayed bedtime, and resistance to prescribed time out of bed, especially on the weekend [38]. Participants demonstrated higher adherence to relaxation (58–70%) which is similar to other studies [37, 40] and is consistent with the notion that RT may be one of the easiest BT components to incorporate into current lifestyles. Inconsistency in adherence among these studies may be explained in part by sample characteristics (e.g., education, socioeconomic status, primary vs. comorbid insomnia), dissimilar treatment components, and measures of adherence.

Our second aim was to determine whether changes in psychological and physical symptoms predicted changes in adherence rates across four chemotherapy treatments. We hypothesized that exacerbated symptoms would predict lower adherence. Consistent with expectations and prior studies [22, 23, 26], our findings were that as participants’ depressive symptoms increased across time, adherence to the MSR component abated. We also found that as sleep improved across chemotherapy, patients’ adherence to relaxation recommendations diminished. This finding was inconsistent with our initial hypotheses, but in line with other reports in which adherence and completion of BT was associated with pretreatment severity of sleep disturbance [23]. Presumably for certain symptoms, severity at the start of treatment may increase motivation to change behavior, and as symptoms improve, motivation waxes and wanes. Our findings provide further support of this concept with data showing that higher sleep disturbance at the start of treatment may not be as important an indicator of adherence to a BT intervention as how quickly sleep improves during treatment [22, 37, 38].

Despite the promising results, there were a few noted limitations. Although the sample size was smaller than desired, it did not appear to compromise statistical power. Limited diversity of the sample also reduces our ability to generalize findings. Although actigraphic estimates were available, the primary adherence outcome was restricted to self-reported data because accuracy of actigraphic data as an adherence measure is influenced by the degree to which individuals know that the actigraph is being monitored to assess adherence [41]. Within the present study, patients were not informed that the actigraph was used to assess their adherence to the BT plan. As such, demand characteristics are a concern; however, the range of adherence rates mitigates these concerns to some degree. Lastly, because the BT sleep intervention was individualized to each patient, the ability to relate our findings to those from the general population with sleep disturbances is reduced.

With accumulating evidence of the efficacy of behavioral therapy for insomnia, consistency of adherence to this therapy is an important scientific and clinical concern. There are many important unanswered questions related to adherence to BT in comorbid and primary insomnia that the current design cannot address. Overall, further research is needed to understand the mechanisms underlying adherence to BT for sleep disturbances. Our results emphasize the importance of standardized measures of adherence in future investigations. Additional factors need to be incorporated into subsequent investigations, such as treatment expectancies [17], self-efficacy [28], and the quality of therapeutic alliance [42].

Acknowledgments

This study was funded by the National Institutes of Health and the National Institute of Nursing Research (5R01NR007762).

Footnotes

Conflict of interest There are no conflicts of interest (e.g., funding, authorship, etc.) associated with this paper.

Contributor Information

Dennis E. McChargue, Department of Psychology, University of Nebraska–Lincoln, Lincoln, NE, USA

Jayashri Sankaranarayanan, Department of Pharmacy Practice, College of Pharmacy, University of Nebraska Medical Center (UNMC), Omaha, NE, USA.

Constance G. Visovsky, College of Nursing—Omaha Division, University of Nebraska Medical Center (UNMC), Omaha, NE, USA

Ellyn E. Matthews, College of Nursing, University of Colorado Denver, Box C-288-19, Denver, CO, USA

Krista B. Highland, Department of Psychology, University of Nebraska–Lincoln, Lincoln, NE, USA

Ann M. Berger, University of Nebraska Medical Center (UNMC), Omaha, NE, USA

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