Psychological Distress and Emotional Expression on Facebook

The self online: When meaning-making is outsourced to the cyber audience

This study examines the cyber audience's perception of social media users' persona based on their online posts from a cognitive meaning-making perspective. Participants (N = 158) answered questions about their personal characteristics and provided their 20 most recent Facebook status updates. Two groups of viewers, who viewed either the text-only or multimedia version of the status updates, answered questions about the Facebook users' personal characteristics. The viewers' perceptions of Facebook users deviated from the users' self-perceptions, although user characteristics that serve social motives were more accurately perceived. Multimedia viewers were more accurate than text viewers, whereas the latter showed a greater consensus. Gender and ethnic differences of Facebook users also emerged in online person perceptions, in line with gendered and cultured characteristics. These findings shed critical light on the dynamic interplay between social media users and the cyber audience in the co-construction of a digitally extended self.

Problematic Smartphone Use Mediates the Pathway from Suicidal Ideation to Positive Psychotic Experiences: a Large Cross-Sectional, Population-Based Study

The present study followed the newly hypothesized "suicidal drive for psychosis" suggesting that psychosis may be consequential to suicidal ideation (SI) and behavior and attempted to explain parts of the pathway between these variables. To this end, we aimed to test whether problematic smartphone use (PSU) has an indirect mediating effect in the cross-sectional relationship between SI and positive psychotic experiences (PEs). Lebanese community young adults (N=4158; 64.4% females; mean age 21.91±3.79) have been invited to participate to a cross-sectional, web-based study in the period from June to September 2022. After adjusting for potential confounders (i.e., the living situation, marital status, household crowding index, economic pressure, cannabis use, other drugs use, and past history of mental illness other than psychosis), we found that higher levels of suicidal ideation was significantly associated with greater PSU, which was also positively and significantly associated with more positive PEs. Finally, greater suicidal ideation was significantly and directly associated with more positive PEs. Our findings suggest that SPU may be regarded as a potential target for prevention and intervention in psychosis. Clinicians, educators, and school administrators ought to give greater attention to PSU among vulnerable young people who present with SI.

Self-disclosure, social support and postpartum depressive mood in online social networks: a social penetration theory perspective

Purpose

The purpose of this research is to investigate how postpartum mothers conduct self-disclosure on social media may obtain social support and therefore improve their depressive mood.

Design/methodology/approach

The authors extract variables of self-disclosure by manual coding postpartum mothers' 835 posts from a parenting social media in China. The ordinary least squares model and the binary logistic regression model are used to test the proposed hypotheses.

Findings

The study suggests that both mothers' superficial level disclosure and personal level disclosure positively affect online social support received, and the effect of personal level disclosure on social support is much greater than that of superficial level disclosure. Online social support received is related to the content of the post and reduces mothers' depressive mood. The authors further find that the association between personal level disclosure and depressive mood is fully mediated by social support.

Research limitations/implications

The data are collected from a parenting social network. Although it is the major parenting social media with the most users in China, the generalizability of this model and the findings to other social media need additional research.

Practical implications

This study offers implications for researchers and practitioners with regard to social media uses and impacts, which also has important implications for policy and interventions for the mental health of mothers.

Originality/value

This paper makes theoretical contributions to the literature of social penetration theory and social support by (1) dividing self-disclosure into superficial level disclosure and personal level disclosure according to the intimacy of self-disclosure; (2) empirically investigating the direct effect of online self-disclosure on social support and the mediating effect of social support between online self-disclosure and mothers' depressive mood.

Investigating Self-injury Support Solicitations and Responses on a Mobile Peer Support Application

Online informal support networks may provide a critical source of support for young people who self-injure. While these platforms are often intended to mitigate digital harm, there is limited understanding of how individuals use peer support venues to seek self-injury related support and the specific contingencies of supportive exchanges. The present mixed-methods study was designed to explore the types of concerns members express on a mobile peer support application and the types of responses that they receive. Specifically, our aims were to (1) understand the prevalence of peer support types exchanged and (2) surface more nuanced themes within these categories of support. We also explore the relationship between support sought through posts and received through comments. Findings have important theoretical implications for understanding support seeking and provision through a mobile peer support app, which can help guide the design and optimization of peer-driven platforms for individuals who self-injure.

Mapping gender transition sentiment patterns via social media data: toward decreasing transgender mental health disparities

Objective

Transgender people face substantial mental health disparities, and this population’s emotional well-being can be particularly volatile during gender transition. Understanding gender transition sentiment patterns can positively impact transgender people by enabling them to anticipate, and put support in place for, particularly difficult time periods. Yet, tracking sentiment over time throughout gender transition is challenging using traditional research methods. This study’s objective was to use social media data to understand average gender transition sentiment patterns.

Materials and Methods

Computational sentiment analysis and statistics were used to analyze 41 066 posts from 240 Tumblr transition blogs (online spaces where transgender people document gender transitions) to understand sentiment patterns over time and quantify relationships between transgender identity disclosures, sentiment, and social support.

Results

Findings suggest that sentiment increases over time on average throughout gender transition, particularly when people receive supportive responses to transgender identity disclosures. However, after disclosures to family members, people experienced temporary increased negative sentiment, followed by increased positive sentiment in the long term. After transgender identity disclosures on Facebook, an important means of mass disclosure, those with supportive networks experienced increased positive sentiment.

Conclusions

With foreknowledge of sentiment patterns likely to occur during gender transition, transgender people and their mental healthcare professionals can prepare with proper support in place throughout the gender transition process. Social media are a novel data source for understanding transgender people’s sentiment patterns, which can help reduce mental health disparities for this marginalized population during a particularly difficult time.

Prospective Physician Awareness of the Associations Between Social Media and Mental Health

OBJECTIVE

Recently, studies have cited negative, positive, and an absence of impact on mental health with social media use. However, there has been little studied regarding the level of awareness and training of clinicians in screening and identifying for these associations. For this reason, the authors designed a study to assess the awareness of prospective physicians, or current medical students, on the associations between mental health and social media.

METHODS

The study was in the form of a 12-question survey. The questions aimed at assessing the awareness through past experiences with social media, education of its use and potential impacts, and self-reported ability to screen, identify, and counsel patients on these associations. The survey was sent to a total of 634 medical students and included all classes from MS1-MS4. A total of 148 students completed this survey (23.3% response rate).

RESULTS

The majority of medical students reported first social media use between the ages of 13 and 18, with the most common occurrence of bullying identified in this age group as well. The majority percentage of students believed there could be both positive and negative effects of social media on mental health; however, only a small percentage of students reported being aware of specific patterns of social media use that are associated with mental health. Moreover, only a few students reported feeling adequate in their ability to screen, educate, and counsel patients on these associations.

CONCLUSIONS

Findings from this study suggest the need for educational resources to train future physicians in screening, identifying, and counseling patients on associations between social media and mental health. The small numbers in this study are a limiting factor for the validity of result interpretation.

The Language of LGBTQ+ Minority Stress Experiences on Social Media

LGBTQ+ (lesbian, gay, bisexual, transgender, queer) individuals are at significantly higher risk for mental health challenges than the general population. Social media and online communities provide avenues for LGBTQ+ individuals to have safe, candid, semi-anonymous discussions about their struggles and experiences. We study minority stress through the language of disclosures and self-experiences on the r/lgbt Reddit community. Drawing on Meyer's minority stress theory, and adopting a combined qualitative and computational approach, we make three primary contributions, 1) a theoretically grounded codebook to identify minority stressors across three types of minority stress-prejudice events, perceived stigma, and internalized LGBTphobia, 2) a machine learning classifier to scalably identify social media posts describing minority stress experiences, that achieves an AUC of 0.80, and 3) a lexicon of linguistic markers, along with their contextualization in the minority stress theory. Our results bear implications to influence public health policy and contribute to improving knowledge relating to the mental health disparities of LGBTQ+ populations. We also discuss the potential of our approach to enable designing online tools sensitive to the needs of LGBTQ+ individuals.

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.

Neighborhood disadvantage, residents' distress, and online social communication: Harnessing Twitter data to examine neighborhood effects

This study aims to examine the role of place-based online social communications in buffering the relationship between neighborhood disadvantage and psychological distress using geo-located Twitter feeds. We collected 1,981,802 geo-tagged tweets posted within the physical boundaries of 78 neighborhoods located in Pittsburgh for 16 consecutive months, beginning July 15, 2013. Psychological distress was measured using sentiments expressed in tweets, and within- and between-neighborhood online social communications were assessed using users' Twitter activity. This study reveals differential effects of within- and between-neighborhood online social communications. More online social communications within a neighborhood were associated with increased psychological sadness, anxiety, and distress in high-poverty neighborhoods; a relationship that was not found in low-poverty neighborhoods. This study suggests the buffering effects of online social communications may follow the same patterns as off-line social support in disadvantaged neighborhoods. Considering the interactions between online spaces and neighborhoods may be important for planning and implementing neighborhood-level interventions.