School of Nursing, Vanderbilt University, Nashville, TN, USA.
Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA.
J Behav Med. 2024 Apr;47(2):308-319. doi: 10.1007/s10865-023-00461-3. Epub 2023 Nov 28.
Family caregivers are at high risk of psychological distress and low sleep efficiency resulting from their caregiving responsibilities. Although psychological symptoms are associated with sleep efficiency, there is limited knowledge about the association of psychological distress with variations in sleep efficiency. We aimed to characterize the short- and long-term patterns of caregivers' sleep efficiency using Markov chain models and compare these patterns between groups with high and low psychological symptoms (i.e., depression, anxiety, and caregiving stress). Based on 7-day actigraphy data from 33 caregivers, we categorized sleep efficiency into three states, < 75% (S1), 75-84% (S2), and ≥ 85% (S3), and developed Markov chain models. Caregivers were likely to maintain a consistent sleep efficiency state from one night to the next without returning efficiently to a normal state. On average, it took 3.6-5.1 days to return to a night of normal sleep efficiency (S3) from lower states, and the long-term probability of achieving normal sleep was 42%. We observed lower probabilities of transitioning to or remaining in a normal sleep efficiency state (S3) in the high depression and anxiety groups compared to the low symptom groups. The differences in the time required to return to a normal state were inconsistent by symptom levels. The long-term probability of achieving normal sleep efficiency was significantly lower for caregivers with high depression and anxiety compared to the low symptom groups. Caregivers' sleep efficiency appears to remain relatively consistent over time and does not show rapid recovery. Caregivers with higher levels of depression and anxiety may be more vulnerable to sustained suboptimal sleep efficiency.
家庭照顾者由于照顾责任而面临较高的心理困扰和睡眠效率低下的风险。尽管心理症状与睡眠效率有关,但对于心理困扰与睡眠效率变化之间的关联知之甚少。我们旨在使用马尔可夫链模型描述照顾者睡眠效率的短期和长期模式,并比较高和低心理症状(即抑郁、焦虑和照顾压力)组之间的这些模式。基于 33 名照顾者的 7 天活动记录仪数据,我们将睡眠效率分为三个状态,<75%(S1)、75-84%(S2)和≥85%(S3),并开发了马尔可夫链模型。照顾者很可能在下一个晚上保持一致的睡眠效率状态,而不会有效地恢复到正常状态。平均而言,从较低的状态恢复到正常睡眠效率(S3)的夜晚需要 3.6-5.1 天,长期达到正常睡眠的概率为 42%。我们观察到,与低症状组相比,高抑郁和焦虑组更有可能过渡到或保持正常睡眠效率状态(S3)。回到正常状态所需的时间差异因症状水平而异。与低症状组相比,高抑郁和焦虑的照顾者达到正常睡眠效率的长期概率明显较低。照顾者的睡眠效率似乎随着时间的推移相对保持一致,不会迅速恢复。抑郁和焦虑程度较高的照顾者可能更容易出现持续的睡眠效率不佳。