The relationship between social support and sleep quality in older adults: A review of the evidence

Mediation effect of perceived social support and psychological distress between psychological resilience and sleep quality among Chinese medical staff

Sleep quality is crucial for the personal well-being of healthcare professionals and the health outcomes of their patients. This study aims to explore the relationship between psychological resilience (PR), perceived social support (PSS), psychological distress (comprising anxiety,depression,and stress), and sleep quality. It also examines whether PSS and psychological distress function as chain mediators between PR and sleep quality. A cross-sectional online survey was conducted using a convenient sampling method, with 454 participants included. The survey instruments included the Connor and Davidson Resilience Scale, the Perceived Social Support Scale, the 21-item Depression Anxiety Stress Scale, and the Pittsburgh Sleep Quality Index. Structural equation modeling revealed that PR significantly predicted sleep quality of Chinese medical staff. Psychological distress was identified as a mediating factor between PR and sleep quality. However, PSS did not directly mediate the relationship between PR and sleep quality. Instead, PSS and psychological distress were found to play a chain mediating role in the relationship between PR and sleep quality. This study provides new insights into the impact of PR on sleep quality, highlights the importance of PSS and psychological distress, and suggests practical implications for enhancing sleep quality among medical staff.

Understanding resilience: Lifestyle-based behavioral predictors of mental health and well-being in community-dwelling older adults during the COVID-19 pandemic

BACKGROUND

Changes in sleep, physical activity and mental health were observed in older adults during early stages of the COVID-19 pandemic. Here we describe effects of the COVID-19 pandemic on older adult mental health, wellbeing, and lifestyle behaviors and explore predictors of better mid-pandemic mental health and wellbeing.

METHODS

Participants in the Adult Changes in Thought study completed measures of lifestyle behaviors (e.g., sleep, physical activity) and mental health and wellbeing both pre-pandemic during regular study visits and mid-pandemic via a one-time survey. We used paired t-tests to compare differences in these measures pre- vs. mid-pandemic. Using multivariate linear regression, we further explored demographic, health, and lifestyle predictors of pandemic depressive symptoms, social support, and fatigue. We additionally qualitatively coded free text data from the mid-pandemic survey for related comments.

RESULTS

Participants (N = 896) reported significant changes in mental health and lifestyle behaviors at pre-pandemic vs. mid-pandemic measurements (p < 0.0001). Qualitative findings supported these behavioral and wellbeing changes. Being male, never smoking, and lower pre-pandemic computer time and sleep disturbance were significantly associated with lower pandemic depressive symptoms. Being partnered, female, never smoking, and lower pre-pandemic sleep disturbance were associated with higher pandemic social support. Pre-pandemic employment, more walking, less computer time, and less sleep disturbance were associated with less pandemic fatigue. Participant comments supported these quantitative findings, highlighting gender differences in pandemic mental health, changes in computer usage and physical activity during the pandemic, the value of spousal social support, and links between sleep disturbance and mental health and wellbeing. Qualitative findings also revealed additional factors, such as stresses from personal and family health situations and the country's concurrent political environment, that impacted mental health and wellbeing.

CONCLUSIONS

Several demographic, health, and lifestyle behaviors appeared to buffer the effects of the COVID-19 pandemic and may be key sources of resilience. Interventions and public health measures targeting men and unpartnered individuals could promote social support resilience, and intervening on modifiable behaviors like sleep quality, physical activity and sedentary activities like computer time may promote resilience to fatigue and depressive symptoms during future community stressor events. Further research into these relationships is warranted.

The Influence of Social Dynamics on Biological Aging and the Health of Historically Marginalized Populations: A Biopsychosocial Model for Health Disparities

Historically marginalized populations are susceptible to social isolation resulting from their unique social dynamics; thus, they incur a higher risk of developing chronic diseases across the course of life. Research has suggested that the cumulative effect of aging trajectories per se, across the lifespan, determines later-in-life disease risks. Emerging evidence has shown the biopsychosocial effects of social stress and social support on one's wellbeing in terms of inflammation. Built upon previous multidisciplinary findings, here, we provide an overarching model that explains how the social dynamics of marginalized populations shape their rate of biological aging through the inflammatory process. Under the framework of social stress and social support theories, this model aims to facilitate our understanding of the biopsychosocial impacts of social dynamics on the wellbeing of historically marginalized individuals, with a special emphasis on biological aging. We leverage this model to advance our mechanistic understanding of the health disparity observed in historically marginalized populations and inform future remediation strategies.

Socially-supported sleep in older adults aged 50 and older: a concept analysis

Introduction

The population of older adults is growing disproportionately, constituting 13% of the global population in 2022, and is expected to double by 2050. One of public health's priorities is healthy aging, the maintenance of functional ability aligned with well-being. As many as 50% of older adults report poor sleep quality, leading to an increased risk of morbidity and mortality. The quality and quantity of social relationships may broadly benefit sleep in older adults. However, the concept of socially-supported sleep is underdeveloped as a basis for intervention.

Methods

Existing literature was searched without time restriction in PubMed, CINAHL, PsycINFO, and Scopus ending in August 2022. Thematic analysis was used to determine the defining attributes, antecedents, and consequences of socially-supported sleep guided by Rodgers' evolutionary concept analysis.

Results

Twenty-nine articles written in English, peer-reviewed, and examined social support and sleep in participants aged ≥50 were included. The defining attributes reflect dimensions of sleep quality. The antecedents are safe and secure, belonging and connection, and warmth and comfort. The consequences of socially-supported sleep include improved regulatory capabilities, physical and emotional well-being, and quality of life.

Conclusion

Socially-supported sleep has the potential to inform interventions that promote sleep in older adults. Ongoing research is needed to address the antecedents and mechanisms through which socially-supported sleep may promote sleep quality for healthy aging.