Psycho-Oncology Psycho-Oncology 24: 1632–1638 (2015) Published online 14 April 2015 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/pon.3816
Sleep disturbances and related factors among family caregivers of patients with advanced cancer Kwo-Chen Lee1,2, Jia-Jean Yiin3, Pi-Chu Lin4 and Shu-Hua Lu1,2* 1
School of Nursing, China Medical University, 91, Hsueh-Shih Road, Taichung, 40402, Taiwan Department of Nursing, China Medical University Hospital, 2, Yude Road, Taichung, 40447, Taiwan 3 Department of Neurosurgery, Neurological Institute, Taichung Veteran General Hospital, 1650 Taiwan Boulevard Sect. 4, Taichung, 40705, Taiwan 4 School of Nursing and Master Program in Long-Term Care, College of Nursing, Taipei Medical University, 250 Wuxing Street, Taipei City, 110, Taiwan 2
*Correspondence to: Abstract School of Nursing, China Medical University, 91, Hsueh-Shih Road, Objective: Sleep disturbances among family caregivers (FCs) are common in advanced cancer. The Taichung 40402, Taiwan. E-mail: comprehensive factors for sleep disturbances among the FCs of patients with cancer have not been investigated in Taiwan. The purposes of this study were to investigate the sleep disturbances [email protected] among the FCs of patients with advanced cancer and to determine predictors of sleep Correction added on 23 disturbance. September 2015, after first Methods: A descriptive, cross-sectional study was conducted among 172 FCs. Data were collected online publication: The citation to using the Pittsburgh Sleep Quality Index and wrist actigraphy. A linear regression model was used the publication of “Lee et al. to identify the predictive factors for sleep quality. 2015. The Burden of Caregiving Results: Seventy-six percent of the FCs experienced some sleep disturbances. Female gender, more and Sleep Disturbance Among fatigue, greater depression, more caregiving burden, and spending over 16 h per day on caregiving Family Caregivers of Advanced tasks were risk factors for sleep disturbances in caregivers. Cancer Patients” was omitted, Conclusions: Sleep disturbances were common among the Taiwanese FCs of patients with advanced and is now added in this version. cancer. FCs with risk factors for sleep disturbances should be identified and provided assistance. Received: 18 May 2014 Copyright © 2015 John Wiley & Sons, Ltd. Revised: 11 February 2015 Accepted: 13 February 2015
Introduction Family caregivers (FCs) are an important support for patients with cancer during the advanced stages of the disease. Sleep disturbances are commonly reported in the FCs of patients with cancer [1–3]. These sleep disturbances may include difficulty getting to sleep, difficulty staying asleep, restless sleep or the feeling that sleep is not refreshing, and sleepiness or the inability to stay awake as desired [4]. The major sleep problems include sleep interruption, difficulty falling asleep, and an inappropriate duration of sleep time in FCs [3,5]. In previous studies, the physiological [6] and psychological [1] state of FCs, their lifestyle, demographics [7], and the symptoms of the associated patients [8] are associated with poor sleep quality. Using the predisposing, precipitating, and perpetuating (PPP) model [9], the causes of sleep disturbances, such as demographics, physical and psychological status, and environment, can be investigated using three categories of factors affecting the quality of sleep. Predisposing factors are the biological, genetic, and demographic traits that increase a person’s risk and susceptibility to insomnia, such as gender and age [7]. Precipitating factors are situations and conditions that, although possibly temporary, trigger insomnia, such as fatigue [10], depression [1], anxiety [11], and caregiving burden [7]. Perpetuating factors are those that Copyright © 2015 John Wiley & Sons, Ltd.
reinforce insomnia over longer time periods, such as poor sleep hygiene and a history of insomnia [4]. In previous studies on sleep disturbances among FCs, the associated patients were in the initial stages of cancer [7,12,13]. Few studies have focused on the FCs of patients with advanced cancer [1,2,5]. In addition, most of these studies did not use large sample sizes (N < 60) [1,5,14] and only used a single assessment tool [1,14]. Most importantly, these studies did not comprehensively consider the factors that influenced the sleep disturbances of FCs, for example, the predisposing, precipitating, and perpetuating factors. Therefore, the primary objectives of this research were to first investigate sleep disturbances in a large sample of FCs of terminally ill patients with cancer in Taiwan and to then examine the potential predictors of sleep disturbances using the framework of the PPP model from the viewpoint of predisposing, precipitating, and perpetuating factors.
Methods Setting and participants This descriptive, cross-sectional survey-based study was conducted from October 2011 to October 2012 [15]. Participants were recruited from the FCs of patients with cancer at medical centers in central Taiwan. The FCs
Sleep disturbance among family caregivers
met the following criteria: a relative with terminal stage cancer as judged by the patient’s physician and identification by the patient as the person most involved in the actual care. FCs diagnosed with a major depressive disorder, insomnia, or heart disease were excluded. The research ethics committee of each study site approved the research protocol. All subjects gave written informed consent.
Measurements Dependent variables
The sleep quality data were collected using subjective and objective parameters. Subjective sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI) [16], where 19 self-rated questions included the following domains: sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction. The global score of these seven components ranged from 0 to 21, with a higher score indicating poorer sleep quality. A global PSQI score of >5 indicated a significant level of sleep disturbances. An appropriately translated Chinese version of the PSQI, which demonstrated good sensitivity, reliability, and validity, is available [17]. In this study, the Cronbach’s alpha was 0.72. Objective data for the sleep–wake parameters were measured through non-invasive monitoring of activity over 48 h using wrist actigraphy (Ambulatory Monitoring, Ardsley, NY). The raw actigraphy data were prepared for analysis using Action 2 software and sleep diaries. Raw actigraphy data displayed good validity with a high correlation with the polysomnographic sleep outcomes [18]. The actigraphy data were reported as the representative scores of duration in nighttime (total time asleep at nighttime), sleep onset latency (time in minutes between bedtime and sleep start), wake after sleep onset (WASO, number of minutes awake or percentage of time awake after sleep onset during the sleep period), napping during the day (total number of minutes of sleep during the daytime), and sleep efficiency (the number of minutes of sleep divided by the total number of minutes in bed, multiplied by 100) [4]. Independent variables
The potential predictors for FC sleep quality were categorized as follows: 1. Predisposing factors These were issues that may increase the risk of insomnia and included age and gender.
2. Precipitating factors These can trigger sleep disturbances and including the following: Copyright © 2015 John Wiley & Sons, Ltd.
1633
(1) Fatigue measured using the previously validated Checklist Individual Strength questionnaire [19]. A higher score indicated a higher degree of fatigue. A score of 76 or more indicates ‘possible fatigue’ in the working population [20]. In this study, the Cronbach’s alpha was 0.82. (2) Depression measured using the Center for Epidemiologic Studies–Depression Scale (CES-D) [21]. Higher scores on CES-D indicated more significant depressive symptoms. A cut-off point of 16 indicated depressive symptoms [21]. The Chinese version of the CES-D has shown good sensitivity, reliability, and validity [22]. The Cronbach’s alpha was 0.93 in this study. (3) Anxiety measured using the State Anxiety Inventory [23], which provided self-report scales for assessing the emotional state of the caregiver. The State Anxiety Inventory’s reliability and validity are established [24]. Higher state anxiety (A-State) total scores indicated higher levels of anxiety. In this study, the Cronbach’s alpha was 0.93. (4) Caregiving burden measured using subjective (feeling of the difficulties or strains of caregiving) and objective (observed negative experiences, including caring tasks) burdens. (A) The subjective caregiving burden was measured using the 24-item Caregiver Reaction Assessment (CRA) [25]. CRA’s reliability and validity are established [26]. Higher scores on the 24-item CRA indicated a heavier caregiving burden. In this study, the Cronbach’s alpha was 0.88 for the total scale. (B) The objective burden was measured using several factors. (a) Patient distress was measured using the Symptom Distress Scale [27], with higher scores indicating greater distress; the Cronbach’s alpha was 0.85. (b) Patient activities of daily living (ADLs) function was measured using the Enforced Social Dependency Scale [28], with higher scores representing poor ADLs in the patient; the Cronbach’s alpha was 0.85 in this study. (c) The amount of assistance provided during caregiving included personal care, homemaking, transportation, and health care, with a composite score of 4–16; higher total scores indicated that the FCs provided more assistance. (d) Time spent caregiving each day was categorized as ≤8, 9–15, and >16 h. (e) The conditions for interaction between the patient and FC were decided using the visit frequency, patients’ willingness to express their symptoms, and understanding the patient’s feelings, with a composite score of 3–15; higher scores indicated that the FCs had more interaction with patients. (5) Caregiving context was measured using the following: (a) financial difficulty for the FC was defined by whether the money earned or saved for medical Psycho-Oncology 24: 1632–1638 (2015) DOI: 10.1002/pon
K.-C. Lee et al.
1634
expenses was sufficient and (b) whether living with the patient and currently employed. 3. Perpetuating factors Perpetuating factors tend to worsen insomnia. Personality anxiety was measured using the Trait Anxiety Inventory (A-Trait) scale. Higher total scores of A-Trait in which there is good reliability and validity indicated higher levels of anxiety [23,24]; the Cronbach’s alpha in this study was 0.91. Sleep problems of the FCs that were already present before taking on the caregiver role, as well as the history of drinking and smoking and exercise habits, were assessed.
Data collection The FCs were interviewed before the patients’ hospital discharge. The FCs wore a wrist actigraphy instrument continuously for 48 h to monitor both nocturnal sleep/rest and daytime wake/activity. They completed questionnaires during interviews following the actigraphy measurement.
Statistical analysis Correlation between the outcome variables and independent variables were examined using the Spearman rank correlation. Simultaneous regression model analysis was conducted for testing the incremental variance by a set of independent variables. For more comprehensive experience, such as sleep quality, daily function, and sleep satisfaction of caregivers, to be investigated, we used the PSQI scores only as dependent variables in the regression analysis by the following steps. (i) Nineteen variables considered clinically and statistically significant based on previous literature and potential predictors of the outcome variables of interest were selected. Univariate analyses were performed to determine potential predictors of change in the sleep quality of FCs, and then we identified 10 relatively important variables. (ii) The aforementioned 10 relatively important variables retained in the final multiple regression analyses contributed to the variance explained by the scores of the PSQI using the simultaneous regression model. Statistical analyses were performed using the SPSS 15.0 Statistical Package (SPSS Inc, Chicago, IL, USA) and a two-tailed probability value of 5 in 76.7% of the FCs (Table 2). The most severe sleep problems were the impact on daytime functioning (mean, 1.68 ± 0.98) and poor sleep quality (mean, 1.58 ± 0.81). Of the objective parameters, the mean duration of sleep at night was 266.37 ± 139.47 min (4.4 ± 2.3 h). For FCs, 59.3% of those with a WASO ratio higher than the normal range (5 represent sleep disturbances) Objective sleep parameters (normal range) Sleep onset latency (420 min) Wake after sleep onset (epoch) (
Sleep disturbances and related factors among family caregivers of patients with advanced cancer Kwo-Chen Lee1,2, Jia-Jean Yiin3, Pi-Chu Lin4 and Shu-Hua Lu1,2* 1
School of Nursing, China Medical University, 91, Hsueh-Shih Road, Taichung, 40402, Taiwan Department of Nursing, China Medical University Hospital, 2, Yude Road, Taichung, 40447, Taiwan 3 Department of Neurosurgery, Neurological Institute, Taichung Veteran General Hospital, 1650 Taiwan Boulevard Sect. 4, Taichung, 40705, Taiwan 4 School of Nursing and Master Program in Long-Term Care, College of Nursing, Taipei Medical University, 250 Wuxing Street, Taipei City, 110, Taiwan 2
*Correspondence to: Abstract School of Nursing, China Medical University, 91, Hsueh-Shih Road, Objective: Sleep disturbances among family caregivers (FCs) are common in advanced cancer. The Taichung 40402, Taiwan. E-mail: comprehensive factors for sleep disturbances among the FCs of patients with cancer have not been investigated in Taiwan. The purposes of this study were to investigate the sleep disturbances [email protected] among the FCs of patients with advanced cancer and to determine predictors of sleep Correction added on 23 disturbance. September 2015, after first Methods: A descriptive, cross-sectional study was conducted among 172 FCs. Data were collected online publication: The citation to using the Pittsburgh Sleep Quality Index and wrist actigraphy. A linear regression model was used the publication of “Lee et al. to identify the predictive factors for sleep quality. 2015. The Burden of Caregiving Results: Seventy-six percent of the FCs experienced some sleep disturbances. Female gender, more and Sleep Disturbance Among fatigue, greater depression, more caregiving burden, and spending over 16 h per day on caregiving Family Caregivers of Advanced tasks were risk factors for sleep disturbances in caregivers. Cancer Patients” was omitted, Conclusions: Sleep disturbances were common among the Taiwanese FCs of patients with advanced and is now added in this version. cancer. FCs with risk factors for sleep disturbances should be identified and provided assistance. Received: 18 May 2014 Copyright © 2015 John Wiley & Sons, Ltd. Revised: 11 February 2015 Accepted: 13 February 2015
Introduction Family caregivers (FCs) are an important support for patients with cancer during the advanced stages of the disease. Sleep disturbances are commonly reported in the FCs of patients with cancer [1–3]. These sleep disturbances may include difficulty getting to sleep, difficulty staying asleep, restless sleep or the feeling that sleep is not refreshing, and sleepiness or the inability to stay awake as desired [4]. The major sleep problems include sleep interruption, difficulty falling asleep, and an inappropriate duration of sleep time in FCs [3,5]. In previous studies, the physiological [6] and psychological [1] state of FCs, their lifestyle, demographics [7], and the symptoms of the associated patients [8] are associated with poor sleep quality. Using the predisposing, precipitating, and perpetuating (PPP) model [9], the causes of sleep disturbances, such as demographics, physical and psychological status, and environment, can be investigated using three categories of factors affecting the quality of sleep. Predisposing factors are the biological, genetic, and demographic traits that increase a person’s risk and susceptibility to insomnia, such as gender and age [7]. Precipitating factors are situations and conditions that, although possibly temporary, trigger insomnia, such as fatigue [10], depression [1], anxiety [11], and caregiving burden [7]. Perpetuating factors are those that Copyright © 2015 John Wiley & Sons, Ltd.
reinforce insomnia over longer time periods, such as poor sleep hygiene and a history of insomnia [4]. In previous studies on sleep disturbances among FCs, the associated patients were in the initial stages of cancer [7,12,13]. Few studies have focused on the FCs of patients with advanced cancer [1,2,5]. In addition, most of these studies did not use large sample sizes (N < 60) [1,5,14] and only used a single assessment tool [1,14]. Most importantly, these studies did not comprehensively consider the factors that influenced the sleep disturbances of FCs, for example, the predisposing, precipitating, and perpetuating factors. Therefore, the primary objectives of this research were to first investigate sleep disturbances in a large sample of FCs of terminally ill patients with cancer in Taiwan and to then examine the potential predictors of sleep disturbances using the framework of the PPP model from the viewpoint of predisposing, precipitating, and perpetuating factors.
Methods Setting and participants This descriptive, cross-sectional survey-based study was conducted from October 2011 to October 2012 [15]. Participants were recruited from the FCs of patients with cancer at medical centers in central Taiwan. The FCs
Sleep disturbance among family caregivers
met the following criteria: a relative with terminal stage cancer as judged by the patient’s physician and identification by the patient as the person most involved in the actual care. FCs diagnosed with a major depressive disorder, insomnia, or heart disease were excluded. The research ethics committee of each study site approved the research protocol. All subjects gave written informed consent.
Measurements Dependent variables
The sleep quality data were collected using subjective and objective parameters. Subjective sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI) [16], where 19 self-rated questions included the following domains: sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction. The global score of these seven components ranged from 0 to 21, with a higher score indicating poorer sleep quality. A global PSQI score of >5 indicated a significant level of sleep disturbances. An appropriately translated Chinese version of the PSQI, which demonstrated good sensitivity, reliability, and validity, is available [17]. In this study, the Cronbach’s alpha was 0.72. Objective data for the sleep–wake parameters were measured through non-invasive monitoring of activity over 48 h using wrist actigraphy (Ambulatory Monitoring, Ardsley, NY). The raw actigraphy data were prepared for analysis using Action 2 software and sleep diaries. Raw actigraphy data displayed good validity with a high correlation with the polysomnographic sleep outcomes [18]. The actigraphy data were reported as the representative scores of duration in nighttime (total time asleep at nighttime), sleep onset latency (time in minutes between bedtime and sleep start), wake after sleep onset (WASO, number of minutes awake or percentage of time awake after sleep onset during the sleep period), napping during the day (total number of minutes of sleep during the daytime), and sleep efficiency (the number of minutes of sleep divided by the total number of minutes in bed, multiplied by 100) [4]. Independent variables
The potential predictors for FC sleep quality were categorized as follows: 1. Predisposing factors These were issues that may increase the risk of insomnia and included age and gender.
2. Precipitating factors These can trigger sleep disturbances and including the following: Copyright © 2015 John Wiley & Sons, Ltd.
1633
(1) Fatigue measured using the previously validated Checklist Individual Strength questionnaire [19]. A higher score indicated a higher degree of fatigue. A score of 76 or more indicates ‘possible fatigue’ in the working population [20]. In this study, the Cronbach’s alpha was 0.82. (2) Depression measured using the Center for Epidemiologic Studies–Depression Scale (CES-D) [21]. Higher scores on CES-D indicated more significant depressive symptoms. A cut-off point of 16 indicated depressive symptoms [21]. The Chinese version of the CES-D has shown good sensitivity, reliability, and validity [22]. The Cronbach’s alpha was 0.93 in this study. (3) Anxiety measured using the State Anxiety Inventory [23], which provided self-report scales for assessing the emotional state of the caregiver. The State Anxiety Inventory’s reliability and validity are established [24]. Higher state anxiety (A-State) total scores indicated higher levels of anxiety. In this study, the Cronbach’s alpha was 0.93. (4) Caregiving burden measured using subjective (feeling of the difficulties or strains of caregiving) and objective (observed negative experiences, including caring tasks) burdens. (A) The subjective caregiving burden was measured using the 24-item Caregiver Reaction Assessment (CRA) [25]. CRA’s reliability and validity are established [26]. Higher scores on the 24-item CRA indicated a heavier caregiving burden. In this study, the Cronbach’s alpha was 0.88 for the total scale. (B) The objective burden was measured using several factors. (a) Patient distress was measured using the Symptom Distress Scale [27], with higher scores indicating greater distress; the Cronbach’s alpha was 0.85. (b) Patient activities of daily living (ADLs) function was measured using the Enforced Social Dependency Scale [28], with higher scores representing poor ADLs in the patient; the Cronbach’s alpha was 0.85 in this study. (c) The amount of assistance provided during caregiving included personal care, homemaking, transportation, and health care, with a composite score of 4–16; higher total scores indicated that the FCs provided more assistance. (d) Time spent caregiving each day was categorized as ≤8, 9–15, and >16 h. (e) The conditions for interaction between the patient and FC were decided using the visit frequency, patients’ willingness to express their symptoms, and understanding the patient’s feelings, with a composite score of 3–15; higher scores indicated that the FCs had more interaction with patients. (5) Caregiving context was measured using the following: (a) financial difficulty for the FC was defined by whether the money earned or saved for medical Psycho-Oncology 24: 1632–1638 (2015) DOI: 10.1002/pon
K.-C. Lee et al.
1634
expenses was sufficient and (b) whether living with the patient and currently employed. 3. Perpetuating factors Perpetuating factors tend to worsen insomnia. Personality anxiety was measured using the Trait Anxiety Inventory (A-Trait) scale. Higher total scores of A-Trait in which there is good reliability and validity indicated higher levels of anxiety [23,24]; the Cronbach’s alpha in this study was 0.91. Sleep problems of the FCs that were already present before taking on the caregiver role, as well as the history of drinking and smoking and exercise habits, were assessed.
Data collection The FCs were interviewed before the patients’ hospital discharge. The FCs wore a wrist actigraphy instrument continuously for 48 h to monitor both nocturnal sleep/rest and daytime wake/activity. They completed questionnaires during interviews following the actigraphy measurement.
Statistical analysis Correlation between the outcome variables and independent variables were examined using the Spearman rank correlation. Simultaneous regression model analysis was conducted for testing the incremental variance by a set of independent variables. For more comprehensive experience, such as sleep quality, daily function, and sleep satisfaction of caregivers, to be investigated, we used the PSQI scores only as dependent variables in the regression analysis by the following steps. (i) Nineteen variables considered clinically and statistically significant based on previous literature and potential predictors of the outcome variables of interest were selected. Univariate analyses were performed to determine potential predictors of change in the sleep quality of FCs, and then we identified 10 relatively important variables. (ii) The aforementioned 10 relatively important variables retained in the final multiple regression analyses contributed to the variance explained by the scores of the PSQI using the simultaneous regression model. Statistical analyses were performed using the SPSS 15.0 Statistical Package (SPSS Inc, Chicago, IL, USA) and a two-tailed probability value of 5 in 76.7% of the FCs (Table 2). The most severe sleep problems were the impact on daytime functioning (mean, 1.68 ± 0.98) and poor sleep quality (mean, 1.58 ± 0.81). Of the objective parameters, the mean duration of sleep at night was 266.37 ± 139.47 min (4.4 ± 2.3 h). For FCs, 59.3% of those with a WASO ratio higher than the normal range (5 represent sleep disturbances) Objective sleep parameters (normal range) Sleep onset latency (420 min) Wake after sleep onset (epoch) (
