SOS on SNS: Adolescent distress on social network sites

Social media and partnership jointly alleviate caregivers' psychological distress: exploring the effects of online and offline connectedness

BACKGROUND

The prevalence of caregiving in the United States has increased from 16.6% to 19.2% during the period between 2015 and 2020. Caregivers play a critical public health role post-pandemic and as the population ages. However, caregiving can be detrimental to the health of caregivers. Many studies have shown that communication and connectedness are effective forms of health intervention for caregivers, but how this can be achieved requires further investigation.

OBJECTIVE

This study aimed to investigate the indirect effect of caregiving on problems of alcohol drinking through psychological distress. Moreover, this study aimed to provide initial evidence of the distinct effects of online and offline communication and connectedness on caregivers' well-being.

METHODS

The predictions were evaluated by examining responses to the Health Information National Trends Survey 2020 (n = 3,865). A mediation analysis was conducted to test the mediating effect of psychological distress on the association between caregiving and alcohol drinking. A second-level moderation analysis was performed. The online communication and connectedness, social media use for health, and the offline type, marital or romantic partnership, were tested as moderators to lessen the psychological distress of caregiving.

RESULTS

A competitive mediation was identified. We found a positive indirect effect from caregiving to alcohol drinking mediated by psychological distress (bp = .0017, p < .05) but a negative direct effect from caregiving to alcohol drinking (bp = -.0340, p < .05). Furthermore, the study reported a strongly positive effect of moderated moderation on the linkage from caregiving to psychological distress. The negative impact of caregiving on mental distress was greater among those who used social media less, particularly those without a romantic or marital partner.

CONCLUSIONS

The findings indicate that caregivers experience more mental distress, which leads to risky behavior. This study highlights the crucial role of both online and offline connectedness in mitigating the adverse consequences of caregiving.

Longitudinal relationship between social media and e-cigarette use among adolescents: the roles of internalizing problems and academic performance

BACKGROUND

Prior research has investigated the influence of social media on e-cigarette use among adolescents, predominantly through the display of e-cigarette content and advertisements. However, the psychological mechanism underlying this relationship remains underexplored. This study aims to address the mediating effect of youths internalizing problems and elucidate the moderating effect of academic performance from a longitudinal perspective.

METHODS

Panel data from the Public Assessment of Tobacco and Health (PATH) Study Waves 3-5 (2015-2019) were utilized in this study. The sample consisted of 3,975 youths between the ages of 12 and 17 years old. A moderated mediation model was utilized for analyses.

RESULTS

Adolescents using social media more frequently in Wave 3 reported higher odds of internalizing problems in Wave 4 (bp = 0.061, p < .01), which led to more e-cigarette use in Wave 5 (bp = 0.029, p < .01). A negative moderating effect of academic performance was found in the association between internalizing problems and e-cigarette use (bp=-0.088, p < .05).

CONCLUSIONS

Frequent social media use among young individuals leads to an increase in e-cigarette use through enhanced internalizing problems. However, adolescents who perform well academically exhibit higher resistance to e-cigarette use. Based on our findings, we recommend that tailored anti-e-cigarette campaigns and mental health interventions be used to target frequent social media users and academically struggling adolescents to prevent adverse health outcomes.

Sexualized Images on Social Media and Adolescent Girls' Mental Health: Qualitative Insights from Parents, School Support Service Staff and Youth Mental Health Service Providers

This research explored adults' perceptions of how sexualized images typically found on social media might influence adolescent girls' mental health, what support girls might need should they experience mental health difficulties, and how such difficulties could be prevented or reduced. Qualitative data were collected using semi-structured in-depth interviews with parents of adolescent girls (n = 11) and those who provide support to them: school support service staff (n = 7) and youth mental health service providers (n = 10) located in Perth, Western Australia. All three participant groups perceived sexualized images typically found on social media as exacerbating poor mental health among adolescent girls. Two interrelated themes, emerged with participants describing the 'potential for comparison' and 'pressure to conform' they believed girls encounter on social media that influences their mental health. Participants also explained how they perceived 'counteracting negative influences' related to sexualized images on social media could prevent or reduce the potential for mental health harms among girls, and the importance of adults and services 'keeping up to date' and being 'approachable and trustworthy' when describing the support they believed girls might need. The findings of this study have important implications for the development of health promotion programs focused on social media use and mental health among adolescent girls.

How compulsive WeChat use and information overload affect social media fatigue and well-being during the COVID-19 pandemic? A stressor-strain-outcome perspective

Social media has been increasingly utilized as an effective avenue for individuals to obtain needed social support and health-related information, especially during the on-going global COVID-19 pandemic. However, surprisingly few empirical studies have concentrated on the detrimental impact of social media adoption on young adults' psychosocial well-being and mental health. Drawing upon previous stressor-strain-outcome theoretical paradigm (SSO), the present research investigates how psychosocial well-being assessments, especially compulsive WeChat use and information overload could trigger social media fatigue and, furthermore, how social media fatigue would ultimately result in emotional stress and social anxiety. This article utilized the cross-sectional design whereby statistical data were collected from 566 young people to test the conceptual research model. This research results demonstrate that perceived information overload through WeChat could significantly trigger social media fatigue among young people. Moreover, perceived information overload could indirectly predict emotional stress and social anxiety through the mediation of social media fatigue. This present work has vital theoretical and practical implications for widespread adoption of newly emerging communication technologies to enhance mental health and well-being among younger generation during recent public health crises.

OMG, R U OK? Therapeutic Relationships between Caregivers and Youth at Risk on Social Media

The rising of social media has opened new opportunities for forming therapeutic relationships with youth at risk who have little faith in institutionalized interventions. The goal of this study is to examine whether and how youth care workers utilize social media communications for reaching out to detached adolescents and providing them emotional support. Qualitative in-depth interviews (N = 17) were conducted with counselors, social workers, and clinical psychologists who work with youth at risk. A thematic analysis of the interviews revealed three principal psychosocial usages of social media: (1) Reaching out and maintaining reciprocal and meaningful therapeutic relationships with youth at risk over time; (2) Identifying risks and emotional distress; and (3) "stepping in" and providing psychosocial assistance, when needed. These beneficial practices are made possible through the high accessibility and the sense of secured mediation that characterize social media communication and that complement the psychosocial needs of youth at risk. Alongside these advantages, the analysis yielded several significant challenges in social media therapeutic relationships, including privacy dilemmas and blurring of authority and boundaries. Given that social media communication is a relatively new phenomenon, the applied psychosocial practices are shaped through a process of trial and error, intuitive decisions, and peer learning. Although the main conclusion from this study supports the notion that the advantages of social media therapeutic relationships with youth at risk outweigh their problematic aspects, future research is recommended to establish clear guidelines for youth caregivers who wish to integrate the new media in their daily psychosocial work.

Deep neural networks detect suicide risk from textual facebook posts

Detection of suicide risk is a highly prioritized, yet complicated task. Five decades of research have produced predictions slightly better than chance (AUCs = 0.56–0.58). In this study, Artificial Neural Network (ANN) models were constructed to predict suicide risk from everyday language of social media users. The dataset included 83,292 postings authored by 1002 authenticated Facebook users, alongside valid psychosocial information about the users. Using Deep Contextualized Word Embeddings for text representation, two models were constructed: A Single Task Model (STM), to predict suicide risk from Facebook postings directly (Facebook texts → suicide) and a Multi-Task Model (MTM), which included hierarchical, multilayered sets of theory-driven risk factors (Facebook texts → personality traits → psychosocial risks → psychiatric disorders → suicide). Compared with the STM predictions (0.621 ≤ AUC ≤ 0.629), the MTM produced significantly improved prediction accuracy (0.697 ≤ AUC ≤ 0.746), with substantially larger effect sizes (0.729 ≤ d ≤ 0.936). Subsequent content analyses suggested that predictions did not rely on explicit suicide-related themes, but on a range of text features. The findings suggest that machine learning based analyses of everyday social media activity can improve suicide risk predictions and contribute to the development of practical detection tools.

The use of social media by Australian preadolescents and its links with mental health

OBJECTIVES

Preadolescent social media use is normative and could influence mental health. This study investigated: (a) Differences between preadolescent users and non-users of various social media platforms on mental health, (b) unique links between time spent on those platforms, appearance-based activities on social media, and mental health, and (c) the moderating role of biological sex on those relationships.

METHOD

Preadolescent youth (N = 528; 50.9% male) completed online surveys.

RESULTS

Users of YouTube, Instagram, and Snapchat reported more body image concerns and eating pathology than non-users, but did not differ on depressive symptoms or social anxiety. Appearance investment uniquely predicted depressive symptoms. Appearance comparisons uniquely predicted all aspects of mental health, with some associations stronger for females than males.

CONCLUSIONS

Preadolescents could be encouraged to reduce their opportunities to make appearance comparisons and to invest less in their appearance on social media. Preadolescents may benefit from social media intervention programs.

Distress, Suicidality, and Affective Disorders at the Time of Social Networks

PURPOSE OF REVIEW

We reviewed how scholars recently addressed the complex relationship that binds distress, affective disorders, and suicidal behaviors on the one hand and social networking on the other. We considered the latest machine learning performances in detecting affective-related outcomes from social media data, and reviewed understandings of how, why, and with what consequences distressed individuals use social network sites. Finally, we examined how these insights may concretely instantiate on the individual level with a qualitative case series.

RECENT FINDINGS

Machine learning classifiers are progressively stabilizing with moderate to high performances in detecting affective-related diagnosis, symptoms, and risks from social media linguistic markers. Qualitatively, such markers appear to translate ambivalent and socially constrained motivations such as self-disclosure, passive support seeking, and connectedness reinforcement. Binding data science and psychosocial research appears as the unique condition to ground a translational web-clinic for treating and preventing affective-related issues on social media.

Exploring the dominant features of social media for depression detection

Recently, social media have been used by researchers to detect depressive symptoms in individuals using linguistic data from users’ posts. In this study, we propose a framework to identify social information as a significant predictor of depression. Using the proposed framework, we develop an application called the Socially Mediated Patient Portal (SMPP), which detects depression-related markers in Facebook users by applying a data-driven approach with machine learning classification techniques. We examined a data set of 4350 users who were evaluated for depression using the Center for Epidemiological Studies Depression (CES-D) scale. From this analysis, we identified a set of features that can distinguish between individuals with and without depression. Finally, we identified the dominant features that adequately assess individuals with and without depression on social media. The model trained on these features will be helpful to physicians in diagnosing mental diseases and psychiatrists in analysing patient behaviour.

Association Between Specific Internet Activities and Life Satisfaction: The Mediating Effects of Loneliness and Depression

The current study examined the associations between specific Internet activities (online shopping, pornography use, social networking site use, and Internet gaming), life satisfaction, and the mediating effects of loneliness and depression for these associations. Participants were 5,215 students (2,303 male participants, Mage = 16.20 years; ranging in age from 10 to 23 years) from various school types (546 elementary school students, 1710 junior high school students, 688 senior high school students, and 2271 university students) who provided self-report data on demographic variables, online shopping, pornography use, social networking site use, loneliness, depression, and life satisfaction. The results indicated that after controlling for demographic variables (gender and age) (a) loneliness and depression had fully positive mediating effects on the association between social networking site use and life satisfaction; (b) loneliness and depression played fully negative mediating effects on life satisfaction associations with online shopping, pornography use, and Internet gaming. Therefore, loneliness and depression were the underlying mechanisms that caused life satisfaction to be affected by online shopping, pornography use, social networking site use, and Internet gaming.