Digital media such as smartphones, social media or video games have become primary tools to cope with stress, allowing for the pursuit of different coping strategies. While in research on problematic Internet use, using online media for coping is considered a maladaptive behavior, other findings indicate that online media is an effective way of coping. The transactional theory of stress and coping assumes that effective coping depends on the fit between coping strategy and tool to the stress-inducing instance implying that using digital media for coping can be adaptive and maladaptive. The personality trait of coping flexibility (CF) which can be understood as the ability to adapt coping behaviors based on situational demands, has emerged as important predictor for adaptive coping. CF could therefore also be influential in predicting whether individuals are able to use digital media for coping effectively and people high in CF could give insights into effective media use for coping. We assumed that CF is related to a more flexible use of digital media for coping (using digital media for a higher number of coping strategies) and that CF acts as a moderator in the relationship between using digital media for coping, well-being, and stress.

We conducted a longitudinal survey using a quota sample recruited on Prolific (N = 442) asking participants to report on their perceived stress, subjective well-being, coping using smartphones, social media, and games, and CF. In Wave 1, we examined whether CF is related to a larger number of coping strategies per coping tool. In longitudinal regression analyses, we will assess whether CF (measured at Wave 1) moderates the relationship between coping using digital media (Wave 1 measure) and subjective well-being and stress (Wave 2 measure) for smartphones, social media, and gaming respectively while controlling for Wave 1 stress and subjective well-being.

The prevalence of mental disorders among young people constitutes a pressing global health crisis. Due to barriers and access gaps in professional treatment, individuals are often turning to social media influencers who, by sharing information together with their own experiences and advice, add ”human touch” to mental health topics and, in doing so, can offer companionship and encouragement. Aside from themselves, these healthfluencers often also provide spaces for community exchange, enabling followers to react, tell their own stories, and respond to others. Despite acknowledging benefits, researchers have raised concerns about healthfluencer content (e.g., concerning false or overgeneralized information), which, following cultivation theory, may shape viewers’ beliefs, including stigmata surrounding mental health issues. Beyond beliefs, heavy content engagement can also directly impact young people’s mental health: According to Thoits’ model of self-labeling, perceived behavioral norms are essential preconditions for self-diagnosing with mental illness, implying that engagement with mental healthfluencers and their community could intensify worries about and self-observations of one’s mental health. Social cognitive theory further posits that individuals imitate models they deem similar to themselves. Given that influencers and fellow community members may be perceived as such, heavy engagement could reinforce self-perceived depressive symptoms. Notably, each of these mechanisms may be subject to individual susceptibilities, which is why we considered gender (due to documented associations with mental health) and self-reflection (which has been highlighted as a crucial factor in discerning personalized social media recommendations) as moderators. To examine our hypotheses across geographical regions, we conducted two large-scale quota-representative cross-sectional surveys among emerging adults (i.e., 16-to-25-years olds) from the US (N = 1,922) and Indonesia (N = 2,107). Measures included adapted versions of established self-report scales, translated to Indonesian via translation back-translation procedure. For analysis, we conducted a multi-group path analysis using unit-weighted average scores and maximum likelihood estimation with robust standard errors.

Social Networks Use Disorder (SNUD) describes excessive and poorly controlled social network use, leading to functional impairment in daily life. While not recognized as an independent disorder in the ICD-11, SNUD can be classified under “other specified disorders due to addictive behaviors” (6C5Y). The I-PACE model provides a theoretical framework for understanding its development and maintenance. Despite its high prevalence, treatment options remain limited.

This pilot randomized controlled clinical trial examines the feasibility and preliminary efficacy of an eight-week mindfulness-based program specifically tailored for SNUD. A minimization approach is used to ensure balanced random assignment to an intervention or waitlist control group. After the intervention phase, the waitlist group receives the same program. The primary outcome is the reduction in SNUD severity, assessed pre-intervention, post-intervention, and at a two-month follow-up. Secondary outcomes encompass depression, anxiety, functional impairment, as well as sleep quality and quality of life. Feasibility is evaluated through attendance rates, home practice engagement, and participant satisfaction. Additionally, the study employs Ecological Momentary Assessment (EMA) to capture real-time fluctuations in craving, state mindfulness, and affective well-being, and assesses behavioral patterns, including social network usage frequency and duration.

A power analysis, based on a meta-analytically derived effect size (g = 1.02), indicates a required sample of N = 26 (13 per group) for an adequately powered one-tailed test (1-ß = 0.80). Considering an empirically derived expected attrition rate of 23.8%, a total recruitment of N = 33 is planned but had not been completed at the time of abstract submission. Mindfulness-based programs show promise in mitigating problematic internet-related behaviors. This trial aims to contribute to evidence-based treatment development for SNUD.

Theoretical background: According to the uses-and-gratification approach, individuals consciously use social networks to satisfy specific needs and desires. When the (excessive) use is associated with negative consequences and the experiencing of impairments in everyday life, researchers, however, argue social networks use as potential disorder due to addictive behaviors based on the definition of (Internet) gaming disorder. The I-PACE model outlines that specific predisposing variables (e.g., motives, personality traits, coping strategies) and affective and cognitive mechanisms (e.g., use expectancies) as well as their interactions can contribute to the development and maintenance of problematic social network use (PSNU). Within the current study, the relevance of usage motives, personality traits, coping strategies, use expectancies, and their interactions in individuals with non-problematic, risky, and pathological social network use will be investigated.

Research Questions: We hypothesize that individuals with non-problematic, risky, and pathological use of social networks differ in terms of usage motives, coping strategies, and use expectancies. Secondly, we formulate the hypothesis that the effect of usage motives and personality traits on symptom severity is mediated by the specific use expectancies and that the effect of usage motives on symptom severity is moderated by the specific coping styles.

Methods: In a pre-registered, multi-center study (FOR2974), 290 participants were classified as individuals with non-problematic, risky, and pathological use of social networks using a diagnostic interview based on DSM-5 criteria for gaming disorder (modified for PSNU). Within a laboratory setting, symptom severity of PSNU was measured with the ACSID-11. The Motives for Using Social Media questionnaire recorded different motives for use of social networks. Coping strategies were divided into adaptive and maladaptive strategies using subscales of the BRIEF Cope. The Internet Use Expectancies Scale was used. The hypotheses are analyzed with ANOVAs and a structural equation modelling.

Mobile phones, always and easily accessible, provide individuals with extended behavioral options to cope with stress in daily life. Accordingly, several research lines have proposed that mobile phone use is related to experiencing empowerment missing, however, a systematic look at phone use empowerment experiences (MPEE) as a concept. We define MPEE as the perception that phones have increased an individual's agency and therefore helped individuals in their everyday lives. Building on work on digital equality and smartphone use and well-being, we aimed in this project to explore who is most susceptible to experiencing phone use empowerment in everyday life. As mobile phones were found to be helpful in particular to individuals who experience stress, we assumed that individuals with greater stress in various life domains (e.g., relationships, work/academic performance) would experience phone use empowerment more frequently. Moreover, we assumed that more MPEE in daily life would increase people’s well-being.

As part of a larger data experience sampling study, participants (N = 194) recruited via our institution’s student pool reported their general stress levels (pre-survey), stress experienced in life domains (pre-survey), and subjective well-being (pre- and post-survey). In the experience sampling phase, participants answered four surveys a day for one week sent at pre-defined time points (N = 3069) in which, among other questions, participants indicated their MPEE (“my phone use helped me”). We entered general stress and stress in specific life domains as level-2-predictors into a multilevel model with MPEE as the dependent variable to test who is more susceptible to phone use empowerment experiences. Using two-level structural equation models, we moreover tested whether phone use empowerment experiences led to increased lagged subjective well-being. The preregistration is available at: https://osf.io/me5bn/?view_only=406c6af7b30545edb46bb4f75efe7bff).