2015
DOI: 10.5664/jcsm.4362
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Patterns and Predictors of Sleep Quality Before, During, and After Hospitalization in Older Adults

Abstract: Clinicians should exercise caution in assessing sleep quality in inpatient settings. Alterations in the cutoffs employed may result in discordant clinical classifications of older adults. Pain and depression warrant detailed considerations when working with older adults on inpatient units when poor sleep is a concern.

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Cited by 20 publications
(13 citation statements)
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“…In this meta-analysis depression was associated with subjective sleep disturbances, aspect corroborated by past studies (e.g., Dzierzewski et al, 2015;Maglione et al, 2012;Orhan et al, 2012;Park et al, 2013;Potvin, Lorrain, Belleville, Grenier, & Préville, 2014;Rashid & Tahir, 2015). Given the role of depression on the subjective sleep quality, depression treatment should focus on both mental health and sleep quality (Buysse, 2004;Yao, Yu, Cheng, & Cheng, 2008).…”
Section: Discussionsupporting
confidence: 78%
“…In this meta-analysis depression was associated with subjective sleep disturbances, aspect corroborated by past studies (e.g., Dzierzewski et al, 2015;Maglione et al, 2012;Orhan et al, 2012;Park et al, 2013;Potvin, Lorrain, Belleville, Grenier, & Préville, 2014;Rashid & Tahir, 2015). Given the role of depression on the subjective sleep quality, depression treatment should focus on both mental health and sleep quality (Buysse, 2004;Yao, Yu, Cheng, & Cheng, 2008).…”
Section: Discussionsupporting
confidence: 78%
“…A previous meta-analysis verified that depression was associated with subjective sleep disturbances ( r0 = .42, p < .001; Becker, Jesus, João, Viseu, & Martins, 2016), as well as other works (Dzierzewski et al, 2015, Maglione et al, 2012, Potvin et al, 2014, Rashid and Tahir, 2015). Thus, sleep quality was considered an important variable influencing depression and other variables, such as life quality.…”
Section: Discussionsupporting
confidence: 61%
“…The dataset was subjected to LCA using twelve variables which includes daytime sleepiness, daytime fatigue, worry about sleep, negative thoughts before sleep onset, sleep initiation problem, sleep maintenance problem, early morning awakening, feeling of worthlessness, sleep time variability, association of bed with purposes other than sleep/sex, arousals during sleep (dichotomous levels) and daytime impairments (dichotomous levels). Latent class analysis has been widely used in many sleep-related studies to subgroup the population based on their sleep quality, sleep duration, sleep difficulty and insomnia symptoms [ [34] , [35] , [36] , [37] ].…”
Section: Methodsmentioning
confidence: 99%