The digital footprints of adolescent depression, social rejection and victimization of bullying on Facebook

Cultural Dimensions Moderate the Association between Loneliness and Mental Health during Adolescence and Younger Adulthood: A Systematic Review and Meta-Analysis

Cultural factors, such as country or continent, influence the relationship between loneliness and mental health. However, less is known about how cultural dimensions moderate this relationship during adolescence and younger adulthood, even if these dimensions manifest as country or continent differences. This study aims to examine the potential influence of Hofstede's cultural dimensions on this relationship using a three-level meta-analysis approach. A total of 292 studies with 291,946 participants aged 10 to 24 were included in this study. The results indicate that cultural dimensions, such as individualism vs. collectivism, indulgence vs. restraint, power distance, and long-term vs. short-term orientation, moderated the associations between loneliness and social anxiety, stress, Internet overuse, and negative affect. The association between loneliness and mental health was not moderated by cultural dimensions, such as masculinity and uncertainty avoidance. These findings suggest that culture's influence on the association between loneliness and mental health is based on a domain-specific mechanism.

Bored to death: Artificial Intelligence research reveals the role of boredom in suicide behavior

Background

Recent advancements in Artificial Intelligence (AI) contributed significantly to suicide assessment, however, our theoretical understanding of this complex behavior is still limited.

Objective

This study aimed to harness AI methodologies to uncover hidden risk factors that trigger or aggravate suicide behaviors.

Methods

The primary dataset included 228,052 Facebook postings by 1,006 users who completed the gold-standard Columbia Suicide Severity Rating Scale. This dataset was analyzed using a bottom-up research pipeline without a-priory hypotheses and its findings were validated using a top-down analysis of a new dataset. This secondary dataset included responses by 1,062 participants to the same suicide scale as well as to well-validated scales measuring depression and boredom.

Results

An almost fully automated, AI-guided research pipeline resulted in four Facebook topics that predicted the risk of suicide, of which the strongest predictor was boredom. A comprehensive literature review using APA PsycInfo revealed that boredom is rarely perceived as a unique risk factor of suicide. A complementing top-down path analysis of the secondary dataset uncovered an indirect relationship between boredom and suicide, which was mediated by depression. An equivalent mediated relationship was observed in the primary Facebook dataset as well. However, here, a direct relationship between boredom and suicide risk was also observed.

Conclusion

Integrating AI methods allowed the discovery of an under-researched risk factor of suicide. The study signals boredom as a maladaptive 'ingredient' that might trigger suicide behaviors, regardless of depression. Further studies are recommended to direct clinicians' attention to this burdening, and sometimes existential experience.

Affective norms for 501 Chinese words from three emotional dimensions rated by depressive disorder patients

Introduction

Emotional words are often used as stimulus material to explore the cognitive and emotional characteristics of individuals with depressive disorder, while normal individuals mostly rate the scores of affective words. Given that individuals with depressive disorder exhibit a negative cognitive bias, it is possible that their depressive state could influence the ratings of affective words. To enhance the validity of the stimulus material, we specifically recruited patients with depression to provide these ratings.

Methods

This study provided subjective ratings for 501 Chinese affective norms, incorporating 167 negative words selected from depressive disorder patients' Sino Weibo blogs, and 167 neutral words and 167 positive words selected from the Chinese Affective Word System. The norms are based on the assessments made by 91 patients with depressive disorder and 92 normal individuals, by using the paper-and-pencil quiz on a 9-point scale.

Results

Regardless of the group, the results show high reliability and validity. We identified group differences in three dimensions: valence, arousal, and self-relevance: the depression group rated negative words higher, but positive and neutral words lower than the normal control group.

Conclusion

The emotional perception affected the individual's perception of words, to some extent, this database expanded the ratings and provided a reference for exploring norms for individuals with different emotional states.

A scoping review of social media in child, adolescents and young adults: research findings in depression, anxiety and other clinical challenges

BACKGROUND

Social media and other technologies are reshaping communication and health.

AIMS

This review addresses the relationship between social media use, behavioural health conditions and psychological well-being for youth aged <25 years.

METHOD

A scoping review of 11 literature databases from 2000 to 2020 explored research studies in youth in five areas: clinical depression and anxiety, quantitative use, social media mode, engagement and qualitative dimensions and health and well-being.

RESULTS

Out of 2820 potential literature references, 140 met the inclusion criteria. The foci were clinical depression and anxiety disorders (n = 78), clinical challenges (e.g. suicidal ideation, cyberbullying) (n = 34) and psychological well-being (n = 28). Most studies focused on Facebook, Twitter, Instagram and YouTube. Few studies are longitudinal in design (n = 26), had comparison groups (n = 27), were randomised controlled trials (n = 3) or used structured assessments (n = 4). Few focused on different youth and sociodemographic populations, particularly for low-income, equity-seeking and deserving populations. Studies examined association (n = 120; 85.7%), mediating (n = 16; 11.4%) and causal (n = 4; 2.9%) relationships. Prospective, longitudinal studies of depression and anxiety appear to indicate that shorter use (≤3 h/day) and purposeful engagement is associated with better mood and psychological well-being. Depression may predict social media use and reduce perception of support. Findings provide families, teachers and providers ways to engage youth.

CONCLUSIONS

Research opportunities include clinical outcomes from functional perspective on a health continuum, diverse youth and sociodemographic populations, methodology, intervention and privacy issues. More longitudinal studies, comparison designs and effectiveness approaches are also needed. Health systems face clinical, training and professional development challenges.

Analyzing the structure of tourism destination network based on digital footprints: taking Guilin, China as a case

Purpose

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.

Design/methodology/approach

The digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.

Findings

(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.

Originality/value

This research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.

A Systematic review of the validity of screening depression through Facebook, Twitter, Instagram, and Snapchat

BACKGROUND

The aim of this study was to determine the validity of using social media for depression screening.

METHOD

Article searches on PubMed and PsycINFO from database inception to August 20, 2019 were completed with a search string and filters.

RESULTS

15 articles made the inclusion criteria. Facebook, Twitter, and Instagram profiles of depressed people were distinguishable from nondepressed people shown by social media markers. Facebook studies showed that having fewer Facebook friends and mutual friends, posting frequently, and using fewer location tags positively correlated with depressive symptoms. Also, Facebook posts with explicit expression of depressive symptoms, use of personal pronouns, and words related to pain, depressive symptoms, aggressive emotions, and rumination predicted depression. Twitter studies showed that the use of "past focus" words, negative emotions and anger words, and fewer words per Tweet positively correlated with depression. Finally, Instagram studies showed that differences in follower patterns, photo posting and editing, and linguistic features between depressed people and nondepressed people could serve as a marker.

LIMITATIONS

The primary articles analyzed had different methods, which constricts the amount of comparisons that can be made. Further, only four social media platforms were explored.

CONCLUSION

Social media markers like number and content of Facebook messages, linguistic variability in tweets and tweet word count on Twitter, and number of followers, frequency of Instagram use and the content of messages on Instagram differed between depressed people and nondepressed people. Therefore, screening social media profiles on these platforms could be a valid way to detect depression.

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.

Social media use and depression in adolescents: a scoping review

There have been increases in adolescent depression and suicidal behaviour over the last two decades that coincide with the advent of social media (SM) (platforms that allow communication via digital media), which is widely used among adolescents. This scoping review examined the bi-directional association between the use of SM, specifically social networking sites (SNS), and depression and suicidality among adolescents. The studies reviewed yielded four main themes in SM use through thematic analysis: quantity of SM use, quality of SM use, social aspects associated with SM use, and disclosure of mental health symptoms. Research in this field would benefit from use of longitudinal designs, objective and timely measures of SM use, research on the mechanisms of the association between SM use and depression and suicidality, and research in clinical populations to inform clinical practice.

Depression and disclosure behavior via social media: A study of university students in China

Severe stress and depression constitute serious challenges to people in both personal and public health. Numerous university students suffer from depression each year while only fractions of them receive proper and competent treatments. Following the trends of the era, social media has been prevalent among university students and become a new platform to disclose depression references. The purpose of this study is to examine the effects of various stressors and the “Big Five” personality traits towards the intention of disclosing depression. Addition to the disclosure intention, this study also explores if respondents have presented their depression via social media profiles. Over 200 WeChat users were surveyed on their experiences from psychological stress factors under four categories - academy, relationship and practical issues.