OBJECTIVES: The prevalence of depression and loneliness is increasing in Western nations, and both have been shown to cause poor sleep quality, with evidence suggesting that loneliness also predicts depression. The Social Cure perspective can shed light on these relationships and thus informs the present study. Specifically, it was hypothesized that the extent of participants' identification with a significant social group, their family, would positively predict sleep quality and that this relationship would be mediated by loneliness and depression. DESIGN: A two-lave longitudinal online survey was used. METHODS: Participants completed an online survey at T1 (N = 387) and 1 year later at T2 (N = 122) assessing the extent to which they identified with their family. Their loneliness, depressive symptomology, and sleep quality/insomnia severity were also measured. RESULTS: Consistent with predictions, cross-sectional and longitudinal serial mediation models indicated that family identification was a negative predictor of loneliness, which in turn was a positive predictor of depression, which predicted poor sleep quality/insomnia. CONCLUSIONS: This is the first Social Cure study to explore the mediated relationship between social identification and sleep quality. As well as advancing the Social Cure perspective, these results have implications for how health professionals understand, prevent, and treat sleep problems. Statement of contribution What is already known on this subject? The prevalence of depression and loneliness is increasing in Western nations, and both have been shown to cause poor sleep quality. Weak social networks have been shown to predict restless sleep over time, and that depressed mood mediates this relationship. What does this study add? Family identification negatively predicted poor sleep quality cross-sectionally. Depression and loneliness positively predicted poor sleep quality over time. Depression and loneliness mediated the family identification-sleep quality relationship over time.
OBJECTIVES: The prevalence of depression and loneliness is increasing in Western nations, and both have been shown to cause poor sleep quality, with evidence suggesting that loneliness also predicts depression. The Social Cure perspective can shed light on these relationships and thus informs the present study. Specifically, it was hypothesized that the extent of participants' identification with a significant social group, their family, would positively predict sleep quality and that this relationship would be mediated by loneliness and depression. DESIGN: A two-lave longitudinal online survey was used. METHODS:Participants completed an online survey at T1 (N = 387) and 1 year later at T2 (N = 122) assessing the extent to which they identified with their family. Their loneliness, depressive symptomology, and sleep quality/insomnia severity were also measured. RESULTS: Consistent with predictions, cross-sectional and longitudinal serial mediation models indicated that family identification was a negative predictor of loneliness, which in turn was a positive predictor of depression, which predicted poor sleep quality/insomnia. CONCLUSIONS: This is the first Social Cure study to explore the mediated relationship between social identification and sleep quality. As well as advancing the Social Cure perspective, these results have implications for how health professionals understand, prevent, and treat sleep problems. Statement of contribution What is already known on this subject? The prevalence of depression and loneliness is increasing in Western nations, and both have been shown to cause poor sleep quality. Weak social networks have been shown to predict restless sleep over time, and that depressed mood mediates this relationship. What does this study add? Family identification negatively predicted poor sleep quality cross-sectionally. Depression and loneliness positively predicted poor sleep quality over time. Depression and loneliness mediated the family identification-sleep quality relationship over time.
Authors: Frederike T Fellendorf; Eva Z Reininghaus; Michaela Ratzenhofer; Melanie Lenger; Alexander Maget; Martina Platzer; Susanne A Bengesser; Armin Birner; Robert Queissner; Carlo Hamm; Rene Pilz; Nina Dalkner Journal: Brain Behav Date: 2021-08-19 Impact factor: 3.405