Trading likes for sleepless nights: A lifespan investigation of social media and sleep

Sensationalising Sleep: Perspectives and Protocols for Understanding Discourses of Sleep Health in Aotearoa New Zealand

Sufficient sleep is a basic right, vital for functioning and wellbeing. Socioecological disparities in sleep status are increasingly highlighted. However, broader social and cultural factors, including beliefs and practicalities of sleep, are seldom considered. This is particularly important for bicultural countries such as Aotearoa New Zealand, where mainstream discourses and health promotion have been colonised. Media provides a platform for shaping beliefs and attitudes concerning sleep. Media messaging contributes to definitions of 'normal sleep' and sensationalised messages around sleep(lessness) and disease-seldom accounting for nuanced differences across the lifespan or Indigenous knowledge and practises concerning sleep and wellbeing. How messages concerning sleep are delivered, interpreted, and resisted varies and warrants exploring-particularly among populations predisposed to sleep disturbances. This paper provides a narrative review of the social and cultural factors influencing sleep and highlights the paucity of research in this space. Responding to these gaps, a current research agenda is presented concerning sleep-related discourses and practises in Aotearoa New Zealand. This includes explorations of media representations of sleep, key audience interpretations, and the development of a theoretical framework to inform appropriate sleep-related research and health promotion relevant to contemporary Aotearoa New Zealand and beyond.

Mechanisms Linking Social Media Use and Sleep in Emerging Adults in the United States

Social media use is associated with poor sleep outcomes. We aimed to extend previous research by examining how measures of social media use would affect two sleep characteristics: sleep quality and insomnia symptoms. In addition, we tested a serial mediation model linking social media use to sleep through increases in negative social comparison and pre-sleep cognitive arousal. Participants were 830 emerging adults (ages 18-30) who were recruited for an online survey study in February 2024. The sample was 63.1% female, with an average age of 24. We examined three measures of social media use: duration (minutes of daily use), frequency (number of weekly visits to social media platforms), and emotional investment (attachment to and integration of social media into daily life). Consistent with our hypothesis, greater emotional investment in social media and more frequent social media use were associated with poorer sleep quality and greater insomnia severity. We also found evidence supporting our hypothesized serial mediation model: emotional investment in social media and more frequent social media use were associated with increased negative social comparison, which subsequently increased pre-sleep cognitive arousal, which then led to poorer sleep outcomes. Our findings suggest that negative social comparison and pre-sleep cognitive arousal are important mechanisms linking social media use to poor sleep outcomes. Future studies should aim to test this serial mediation model using longitudinal data and experimental methods.

The mediating and moderating effects of psychological distress on the relationship between social media use with perceived social isolation and sleep quality of late middle-aged and older adults

OBJECTIVES

Older adults are more likely to have poor sleep quality and be socially isolated. The present study examined the potential benefits and disadvantages of social media use (SMU) with respect to sleep quality and perceived social isolation among Iranian late-middle-aged and older adults with focus a on both the mediating and moderating role of psychological distress.

METHODS

A population-based cross-sectional study was conducted among 900 older community-dwellers living in Shiraz using a structured questionnaire. Social media use was assessed by estimating the frequency of social networking site visits per week. Data concerning self-rated physical health, chronic medical and mental health conditions, perceived social isolation, sleep quality, and psychological distress were also collected. Multiple linear regression was used to identify independent variables associated with outcomes. Then, mediation and moderation models were used to examine the potential mediating and moderating effects of psychological distress and SMU on their relationships with the study variables.

RESULTS

Higher social media use was associated with better sleep quality and less perceived social isolation. Nevertheless, the relationships between SMU and participants' sleep quality and perceived social isolation were largely mediated by their level of psychological distress. Furthermore, SMU had a significant moderating effect in the relationship between the psychological distress and the levels of perceived social isolation, so that participants with higher frequency of SMU per week felt less loneliness.

CONCLUSIONS

The study findings suggest that SMU has a positive buffering effect regarding late middle-aged and older adults' mental health mainly through moderation of their perceived social isolation. The mediating role of psychological distress in research examining the relationship between SMU and older adults' mental health outcomes should be considered in future research.

Social media use and its impact on adults' mental health and well-being: A scoping review

BACKGROUND

Social media use has grown in importance and prevalence, with its estimated number of users at 4.9 billion worldwide. Social media use research has revealed positive and negative impacts on users' mental health and well-being. However, such impacts among adults have not been examined in any reviews.

METHODS

A scoping review was conducted based on the framework by Arksey and O'Malley and reported based on the PRISMA-ScR guidelines. Eight databases were searched from 2005 to December 2021. Articles were included after being reviewed by three independent teams, with discrepancies resolved through consensus with the senior author. Publication-related information (i.e., authors, year of publication, aims, study population, methodology, interventions, comparisons, outcome measures and key findings) were extracted from each study. Thematic analysis was conducted to answer the research questions.

RESULTS

Among the 114 eligible articles, young adults (69.6%) represented the main age group. Most studies (78.6%) focused on the negative impacts of social media use on mental health and well-being, with nearly a third (32.1%) assessing such impacts on depression. Notably, this scoping review found that more than three-quarters (78.6%) of the included studies revealed that excessive and passive social media use would increases depression, anxiety, mood and loneliness. Nevertheless, a third (33.0%) also reported positive impacts, where positive and purposeful use of social media contributes to improvements in mental health and well-being, such as increased perceived social support and enjoyment.

LINKING EVIDENCE TO ACTION

This review has provided an overview of the existing knowledge on how social media use affects adults and identified areas of research that merit investigation in future studies. More attention should be given to maximizing the positive impacts of social media use on mental health and well-being among adults.

Active Social Media Use and Health Indicators Among Sexual and Gender Minority Adults

Purpose: Sexual and gender minority (SGM) individuals may receive social support through active use of social media (i.e., posting and interacting). This study examined associations between active social media use, social support, and health indicators in a large sample of SGM adults in the United States. Methods: Data were derived from the 2017 wave of The PRIDE Study, a national cohort study of SGM health. SGM-identified adults reporting social media use (N = 5995) completed measures of active social media use, social support, depressive symptoms, cigarette smoking, hazardous drinking, sleep, and physical activity. Regression models examined main and interactive effects of active social media use and social support on health indicators. Results: The sample reported a moderate level of active social media use (mean [M] = 3.2 [1.0], scale = 1-5) and relatively high social support (M = 16.7 [3.3], scale = 4-20); 31.8% reported moderate-to-severe depressive symptoms. Participants with greater active social media use were more likely to experience depressive symptoms (adjusted odds ratio [AOR] = 1.18, 95% confidence interval [CI] = 1.10-1.26), cigarette smoking (AOR = 1.11, 95% CI = 1.01-1.22), insufficient sleep (AOR = 1.13, 95% CI = 1.06-1.21), and physical inactivity (AOR = 1.09, 95% CI = 1.02-1.15) than those with less active social media use. Active social media use did not significantly interact with social support to predict any health indicators (p values >0.159). Conclusions: Among SGM adults, active social media use was associated with several negative health indicators. Active social media use may increase health risks, or SGM adults with poor health may actively use social media to maintain social connections. Moderate active social media use may be compatible with health.

Potential use of large language models for mitigating students' problematic social media use: ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals' daily lives, interpersonal relationships, physical and mental health, and more. Currently, there are few methods and tools to alleviate problematic social media, and their potential is yet to be fully realized. Emerging large language models (LLMs) are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life. In mitigating problematic social media use, LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users, providing personalized information and resources, monitoring and intervening in problematic social media use, and more. In this process, we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT, leveraging their advantages to better address problematic social media use, while also acknowledging the limitations and potential pitfalls of ChatGPT technology, such as errors, limitations in issue resolution, privacy and security concerns, and potential overreliance. When we leverage the advantages of LLMs to address issues in social media usage, we must adopt a cautious and ethical approach, being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

Lifestyle Factors and Sleep Health across the Lifespan

Sleep health, operationalized as a multidimensional construct consisting of sleep regularity, satisfaction, alertness, timing, efficiency, and duration, is an emerging concept in the field of sleep medicine which warrants further investigation. The purpose of the present study was to: (1) compare sleep health across the lifespan, (2) determine lifestyle factors associated with sleep health, and (3) examine whether lifestyle factors associated with sleep health varied between and within age groups. Participants consisted of 3284 individuals (Mean age = 42.70; 45% male) who participated in a cross-sectional online survey of sleep and health. Sleep health was measured using the RU-SATED scale, while demographic and lifestyle factors (e.g., daily social media use, sedentary activity, fast food consumption, etc.) were all self-reported. Sleep health was the highest among older adults (M = 8.09) followed by middle-aged (M = 7.65) and younger adults (M = 7.16). Across age groups, fast-food consumption, daily regularity, and daily TV, social media, or internet use were all negatively correlated with sleep health (ps < 0.05). Few differences in the association between lifestyle factors and sleep health across age groups were found. Overall, these findings may help to inform sleep health promotion efforts by targeting the most pertinent lifestyle factors for promoting sleep health.