The interrater reliabilities (intraclass correlation coefficients) of the first seven subscales and interference subscales, determined using data from eight FCGs, were 0.97 and 1.00 (both p < 0.01), respectively. Since these eight FCGs did not differ signifi- cantly in age, education, duration of care (months), and caring time (hours/week) from the other 172 FCGs in the study, we combined these two data sets (N ¬ 180). For hierarchical regression analyses, we used only scores on the first seven subscales because only 48 FCGs reported that their sleep disturbance interfered with their daily life, an insufficient sample for regression analysis. Procedures This study was approved by the institutional review boards of the hospital affiliated with the authors university (Case No. 95-0049B). Consecutive PWDFCG dyads were recruited by purposive sampling from the participating sites by two well-trained research assistants using a standardized interview. The research assistants, one registered nurse with a bachelors degree in nursing and another with a masters degree in gerontological nursing, were trained by a clinical psychiatrist to administer the test battery and by the principal investigator on background knowledge of dementia, dementia care, and community resources for the FCGPWD dyads. Data on outpatient PDWs diagnosis and cognitive status were collected by research assistants from PDWs charts, and this information on community-dwelling PWDs was obtained from their respective physicians. Statistical analysis All analyses were performed using SPSS, version 13.0 (SPSS Inc., Chicago, IL). Data were cleaned using frequency and descriptive statistics to check for outliers. To reduce deviations from normality, all variables were checked for skewness and kurtosis to identify those that could benefit from data transformations. Patients and FCGs demographic and main variables were analyzed by descriptive statistics. Relationships between PWDs neuropsychiatric symptoms, FCGs stressors (caregiving distress, depression, fatigue), and FCGs sleep disturbance scores were explored by Pearson correlation coefficient and hierarchical regression models. The final sample size was 180 dyads. The sample size was estimated for a medium effect size, power of 0.8, a level of 0.05, and analysis of 14 variables: background factors (FCGs gender, age, education [in years], marital status, relationship with PWD, living with PWD [yes/no], having a foreign helper [yes/no]), stressor variables (PWDs neuropsychiatric symptoms and disease severity, FCG caregiving distress and fatigue), FCG depressive symptoms, synergistic effects of depressive symptoms and fatigue, and the main outcome variable (FCG sleep disturbance). This analysis determined that a sample size from 100 to 250 dyads would be sufficient to detect R2 between 21 and 8, with 20 independent variables (Hair, 1988). Of 198 dyads contacted, 189 agreed to participate, for a response rate of 95.24%. Of these 189 participating dyads, nine failed to complete the test battery due to time limitations and schedule conflicts. Results Participants characteristics The 180 PWDs had a mean age of 77.61 years (SD 8.2), a male/female ratio of 89/91, and mean educational level of 8.16 years (SD 5.2). The majority of PWDs was diagnosed with Alzheimers disease (n ¬ 132, 73.3%). Almost half the elders (n ¬ 88, 48.9%) had a CDR score ¬ 1, with 27.8% (n ¬ 50) having a CDR score ¬ 0.05, and 22.4% (n ¬ 42) having a CDR score 2 (CDR ¬ 2, n ¬ 39; CDR ¬ 3, n ¬ 3). Their mean MMSE score was 16.7 (SD ¬ 6.1), meaning moderate global cognitive impairment, while the mean CNPI score was 16.6 (SD ¬ 19.8) (Table 1). The FCGs had a mean age of 56.0 years (SD ¬ 13.8), with more than half 41 to 60 years old (53.3%). The majority of FCGs were female (65%), most were married (90.6%), and they had a mean caring duration of 30.0 months (SD ¬ 40.6), and a mean caring time of 66.2 hours per week (SD ¬ 50.6). The majority of FCGs were PWDs adult children, including sons and daughtersin-law (55.6%), followed by spouses (40.6%) (Table 1). Aging & Mental Health 95 These background characteristics of PWDs and FCGs are similar to those of other Taiwanese FCGPWD dyads (Huang, Shyu, Chen, & Hsu, 2009). Distributions of FCG sleep disturbance FCGs mean GSDS score for the first seven subscales was 46.2 (SD ¬ 28.3). Since the original instrument has not established a cutoff score, we report here the percentage of FCGs with any scores 1 on the first seven subscales. Among 180 FCGs, 109 reported difficulty falling asleep (60.6%), 122 reported waking up during sleep (67.8%), and 110 reported waking up before the end of a sleep cycle (61.1%). With regard to self-perceived sleep quality, 179 FCGs reported worse sleep quality (99.4%); as to sleep quantity, 116 FCGs considered themselves sleeping too much or too little (64.4%). Almost everyone indicated experiences of dozing in the daytime (97.8%), and only 55 claimed they used substances to help them sleep (30.6%). Finally, 51 FCGs reported experiencing unusual sleep disturbance in the past week, and 48 reported that this problem interfered with their lives (26.7%) (Table 2). Relationships between FCGs sleep disturbance and PWDs characteristics FCGs sleep disturbance was not significantly related to PWDs demographic characteristics in Pearson correlation analysis, one-way ANOVA with Scheffes test for post hoc analysis, and independent sample t-tests. However, FCGs sleep disturbance was moderately, positively correlated with PWDs neuropsychiatric symptoms (r ¬ 0.29, p < 0.01) and highly, positively correlated with PWDs depression/bad mood (r ¬ 0.32, p < 0.01) (Table 3). FCGs mean score for caregiving distress toward PWDs neuropsychiatric symptoms was 8.61 (SD 10.56), indicating mild distress (Matsumoto et al., 2007). The results of correlation analysis indicate that FCGs sleep disturbance and interference with daily life were signifi- cantly correlated with distress regarding all but PWD sleep/nighttime activities. Specifically, FCGs sleep disturbance was strongly correlated with their distress towards patients delusions (r ¬ 0.25, p < 0.01), hallucinations (r ¬ 0.22, p < 0.01) and emotion-related behavioral symptoms (including irritation/aggression, Table 1. Demographic and clinical characteristics of PWDs and their FCGs (N ¬ 180). PWDs FCGs Mean (SD) n (%) Mean (SD) n (%) Female 91 (50.6) 117 (65) Age (years) 77.61 (8.2) 56.0(13.8) Education (years) 8.16 (5.2) 11.9(4.1) Caring duration (months) 30.0(40.6) Caring time (hours/week) 66.2(50.6) Relationship Spouse 73 (40.6) Adult children (including in-laws) 100 (55.6) Other 6 (3.3) Missing 1 (0.1) Living with PWD Yes 139 (77.2) No 41 (22.8) Hired foreign helpers Yes 40 (22.2) No 140 (77.8) Diagnosis Alzheimers disease 132 (73.3) Vascular dementia 27 (15.0) Other 21 (11.7) Clinical Dementia Rating 0.5 50 (27.8) 1 88 (48.9) 2 42 (22.4) Mini-Mental State Examination 16.7(6.1) Barthel Index 88.2 (18.8) Chinese Neuropsychiatric Inventory (CNPI) 16.6 (19.8) Geriatric Depression Scale-S (patient version) 52.0 (1.6) CNPI-Caregiver distress 8.6(10.6) CESD-10 6.6 (5.9) Attentional Function Index 129.0 (9.9) Lees Fatigue Scale 28.3(29.1) General Sleep Disturbance Scale First seven GSDS subscales 48.5(25.6) Interference 6.9(13.8) CESD-10, 10-item Center for Epidemiological Studies Depression Scale; GSDS-S, General Sleep Disturbance Scale Short Form. 96 Y.-C. Chiu et al. depression, and anxiety) (Table 3). Overall, FCGs sleep disturbance was strongly, positively correlated with their distress towards patients neuropsychiatric symptoms (r ¬ 0.32, p < 0.01) (Table 3). The relationships between FCGs caregiving distress and different aspects of sleep disturbance were then explored using Pearson correlations. Results indicate moderate and significant positive correlations between FCGs distress and sleep disturbance domains (r ¬ 0.20 0.29, p < 0.01), except for self-perceived sleep quality (reversed question, r ¬ 0.13, p ¬ 0.07). FCGs distress was most significantly correlated with dozing during the daytime (r ¬ 0.25, p ¬ 0.001) and interference with daily life (r ¬ 0.29, p ¬ 0.000). To explore possible significant predictors of FCGs sleep disturbance based on the stress-process model for family caregiving (Pearlin et al., 1990), we used hierarchical multiple regression models. Independent variables included FCGs background factors (age, gender, education, living with PWDs, care duration, care time per week, having a foreign helper, marital status, and relationship with patient), primary stressors (PWDs neuropsychiatric symptoms and disease severity), secondary stressors (FCGs caregiving distress and fatigue), and FCGs depressive symptoms. These independent variables were examined by tolerance tests for collinearity; none of the predictors had a tolerance indicator >0.1, suggesting no collinearity (Shi, 2003).
To avoid multicollinearity when calculating the synergistic effects of depressive symptoms and fatigue indicators, we adopted a mean-centering approach (Aiken, West, & Reno, 1991). The results of five-level hierarchical model analyses showed that only 11.1% of the variance in sleep disturbance was explained by FCGs background factors in the level I model, but the contribution to variance increased to 18.4% after PWDs neuropsychiatric symptoms and disease severity were entered in the level II model. Moreover, the overall explained variance in sleep disturbance increased to 47.5% after FCGs caregiving distress and fatigue indicators were entered, adding 29.0% to the Table 3. Correlations among FCGs sleep disturbance, FCGs distress and PWDs psychiatric symptoms (N ¬ 180). PWDs neuropsychiatric symptoms FCGs distress regarding PWDs neuropsychiatric symptoms FCGs sleep disturbance subscale score FCGs interference subscale score GSDS total score FCGs sleep disturbance subscale score FCGs interference subscale score GSDS total score Delusion .19 .11 .18 .25 .23 .27 Hallucination .15 .11 .15 .22 .19 .22 Agitation/aggression .24 .22 .25 .20 .23 .23 Dysphoria/depression .31 .27 .32 .27 .25 .29 Anxiety .27 .18 .26 .28 .20 .28 Euphoria .16 .05 .13 .07 .13 .10 Apathy .05 .12 .08 .16 .14 .17 Disinhibition .16 .16 .17 .20 .16 .20 Irritability .22 .21 .24 .19 .21 .21 Aberrant motor behavior .09 .22 .15 .16 .26 .21 Sleep & nighttime behavioral change .06 .07 .07 .11 .08 .11 Appetite and eating behavioral change .11 .18 .15 .13 .18 .16 PWDs neuropsychiatric symptoms .34 .32 .30 .37 .26 .32 p < 0.05; p < 0.01. Table 2. Types of sleep disturbance among FCGs (N ¬ 180). Number of FCGs with scores 1 (%) Mean SD Range Sleep disturbance subscale (items) 46.2 28.3 0147 Difficulty falling asleep (1) 109 (60.6) 2.9 3.1 010 Waking up during sleep (1) 122 (67.8) 3.7 3.5 010 Waking up before the end of a sleep cycle (1) 110 (61.1) 3.0 3.2 010 Sleep quality (3) 179 (99.4) 12.9 4.1 027 Sleep quantity (2) 116 (64.4) 4.3 4.2 014 Dozing in daytime (7) 176 (97.8) 19.3 12.0 057 Consumption of sleeping pills (5) 55 (30.6) 2.5 5.1 027 Interference subscale Sleep disturbance interfering with life (7) 48 (26.7) 6.9 13.8 064 Note: One GSDS item with a dichotomized response to measure unusual sleep disturbance in the past week is not listed.
Aging & Mental Health 97 variance, but the predictive effect of PWDs neuropsychiatric symptoms disappeared in the level III model. An additional 9.1% of the variance in sleep disturbance was explained by FCGs depressive symptoms in the level IV model. When the synergistic effect of FCGs depressive symptoms and physical fatigue was entered into the final level V model, this model explained 57.8% of the FCGs sleep disturbance variance.
The hierarchical model analyses suggested that the most important predictors were FCGs physical fatigue and depressive symptoms. Finally, FCGs sleep disturbance was predicted by physical fatigue, rather than mental fatigue, depressive symptoms, and the synergistic effect of depressive symptoms and physical fatigue, explaining 57.8% of the total variance, even though the increased variance of the synergistic effect was not significant (Table 4). Discussion This study shows that, in general, about two-thirds of FCGs of PWDs suffered from various types of sleep disturbance, similar to a review of primarily Western FCGs of PWDs (McCurry et al., 2009) and a study of Taiwanese FCGs of PWDs (Tseng, 2007).
The most prevalent sleep disturbance problems reported by our FCGs included sleep quality problems (99.4%), dozing in daytime (97.8%) and waking up before the sleep cycle ends (67.8%). Despite the sleep disturbances, FCGs of PWDs in our study reported low consumption of sleeping aids. This result might be due to Taiwanese FCGs worrying about addiction and difficulty waking up for night care (Tseng, 2007).
Future investigations are warranted to explore the conditions and reasons for taking sleeping pills in this population, as well as subjective and objective measurements of sleep disturbance to comprehensively understand sleep disturbance problems in Taiwanese FCGs of PWDs. Our results indicate that FCGs sleep disturbance was not significantly correlated with PWDs age, gender, dementia diagnosis, severity of dementia, and overall cogn
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