Daily Stress and Affect Across Adulthood: The Role of Social Interactions via Different Communication Modes

Social Media Use and Daily Well-Being: The Role of Quantity and Quality of Social Support

There have been mixed findings on whether social media use is positively or negatively related to well-being. Using the Midlife in the United States Refresher study (N = 782, age 25-75), multilevel structural equation modeling examined social support quantity (time giving and receiving) and quality of as mediators at both the within- (intraindividual) and between-person (interindividual) levels. Giving support significantly mediated at within- and between-person levels: more social media use was associated with more time giving support and worse well-being. Receiving support significantly mediated at the between-person level: more social media use was associated with more time receiving support and worse well-being. When examining social support quality as a mediator, findings showed that more social media use to contact family/friends was related to better social support quality and better well-being. Results added to our understanding of the relationship between social media use and well-being by considering the role of social support quantity/quality.

Diversity of network communication mode and interpersonal interactions: Relationship with social support and well-being

Social interactions today expand beyond in-person interactions. Therefore, it is important to recognize that social interactions can occur with social network members across multiple communication modes (in-person, phone, and online). The current study explored the role that social support plays in the relationship between mode frequency (in-person, phone, and online), network communication mode diversity (breadth and evenness of communicating with network members via different communication modes), and well-being (positive affect, stress, and loneliness) from the 3-year UCNET (UC Berkley Social Networks Study, N = 1159) dataset. The study contained samples for two age groups (cohorts) - 21-31 year-olds and 50-70 year-olds, which also allowed for an exploration of age differences in these relationships. Longitudinal random-intercept cross-lagged panel models (RI-CLPM) showed a high degree of stability over the 3 years for all variables. Cross-sectional structural equation mediation models showed that social support mediated the relationships of mode frequency (in-person, phone, and online) and network communication mode diversity with well-being (more positive affect and less loneliness and stress). Age differences were found in the relationship between frequency of communication modes and social support, in that the frequency of communication mode was positively related to social support for younger adults, but not for middle-aged/older adults. Current findings provided future research directions geared toward further understanding of the mode frequency and network communication mode diversity constructs and how they relate to various psychosocial outcomes.

Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review

BACKGROUND

Social interactions are important for well-being, and therefore, researchers are increasingly attempting to capture people's social environment. Many different disciplines have developed tools to measure the social environment, which can be highly variable over time. The experience sampling method (ESM) is often used in psychology to study the dynamics within a person and the social environment. In addition, passive sensing is often used to capture social behavior via sensors from smartphones or other wearable devices. Furthermore, sociologists use egocentric networks to track how social relationships are changing. Each of these methods is likely to tap into different but important parts of people's social environment. Thus far, the development and implementation of these methods have occurred mostly separately from each other.

OBJECTIVE

Our aim was to synthesize the literature on how these methods are currently used to capture the changing social environment in relation to well-being and assess how to best combine these methods to study well-being.

METHODS

We conducted a scoping review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

We included 275 studies. In total, 3 important points follow from our review. First, each method captures a different but important part of the social environment at a different temporal resolution. Second, measures are rarely validated (>70% of ESM studies and 50% of passive sensing studies were not validated), which undermines the robustness of the conclusions drawn. Third, a combination of methods is currently lacking (only 15/275, 5.5% of the studies combined ESM and passive sensing, and no studies combined all 3 methods) but is essential in understanding well-being.

CONCLUSIONS

We highlight that the practice of using poorly validated measures hampers progress in understanding the relationship between the changing social environment and well-being. We conclude that different methods should be combined more often to reduce the participants' burden and form a holistic perspective on the social environment.

The COVID-19 pandemic: Electronic media use and health among US College students

Objective: To explore differences before and during the COVID-19 pandemic in electronic media use (i.e. TV watching, social media use, screen time), health (i.e. physical, behavioral, social, mental), and the relationship between them among college students. Participants: Nine hundred sixty-five United States college students with 367 participating before and 598 during the pandemic (after March 2020). Methods: Using a multiple cross-sectional design, participants completed an online self-report questionnaire and biometric data was gathered in-person for the Pre-COVID group. Results: During the pandemic, time spent watching TV and social media was 14% higher and total screen time was 30% higher (d = .39). Health variations were mixed with both adverse and beneficial differences. Most correlations between electronic media use and health variables were lower in strength during the pandemic. Conclusions: Differences between electronic media use and health before and during the pandemic suggest potential mixed effects of the pandemic on college student media use and health.