Influence of TikTok on Body Satisfaction Among Generation Z in Indonesia: Mixed Methods Approach.

BACKGROUND: As social media platforms gain popularity, their usage is increasingly associated with cyberbullying and body shaming, causing devastating effects. OBJECTIVE: This study aims to investigate the impact of social media on Generation Z users' body image satisfaction. More specifically, it examines the impact of TikTok on body image satisfaction among TikTok users aged between 17 years and 26 years in Indonesia. METHODS: The methodology used mixed-method approaches. Quantitative data were obtained from 507 responses to a questionnaire and analyzed using covariance-based structural equation modeling. Qualitative data were obtained from the interviews of 32 respondents and analyzed through content analysis. RESULTS: This study reveals that upward appearance comparison is influenced by video-based activity and appearance motivation. Conversely, thin-ideal internalization is influenced by appearance motivation and social media literacy. Upward appearance comparisons and thin-ideal internalization comparisons detrimentally impact users' body image satisfaction. CONCLUSIONS: The results of this study are expected to provide valuable insights for social media providers, regulators, and educators in their endeavors to establish a positive and healthy social media environment for users.

A framework for integrating neural development and social networks in adolescence.

Adolescence is a developmental period characterized by increasingly complex and influential peer contexts. Concurrently, developmental changes in neural circuits, particularly those related to social cognition, affective salience, and cognitive control, contribute to individuals' social interactions and behaviors. However, while adolescents' behaviors and overall outcomes are influenced by the entirety of their social environments, insights from developmental and social neuroscience often come from studies of individual relationships or specific social actors. By capturing information about both adolescents' individual relations and their larger social contexts, social network analysis offers a powerful opportunity to enhance our understanding of how social factors interact with adolescent development. In this review, we highlight the relevant features of adolescent social and neural development that should be considered when integrating social network analysis and neuroimaging methods. We focus on broad themes of adolescent development, including identity formation, peer sensitivity, and the pursuit of social goals, that serve as potential mechanisms for the relations between neural processes and social network features. With these factors in mind, we review the current research and propose future applications of these methods and theories.

Confidants and Caregivers: Network Multiplexity and Subjective Well-Being of Older Adults.

OBJECTIVES: Older adults rely on personal networks for different types of support. Given shifts in family composition in later adulthood, more work is needed to map network members who can provide multiple aspects of support and the implications for older adults. We explore the phenomenon of having the same network members as both a confidant and a caregiver (multiplexity) and its implications for the well-being of older adults. METHODS: Using the 2011 National Health and Aging Trends Study (NHATS), we describe the prevalence of having someone as both a confidant and a caregiver (henceforth "multiplex helper") for older adults and examine its association with subjective well-being. We also investigate the differences by having whom as multiplex helpers. RESULTS: About three-quarters (76%) of older adults with at least one confidant and one caregiver have at least one multiplex helper. Partnered older adults are more likely to have any multiplex helpers than unpartnered counterparts and usually nominate their partner as a multiplex helper, whereas the unpartnered are more likely to rely on their children to serve multiple roles, especially for widowed older adults. Having a multiplex helper is associated with better subjective well-being. DISCUSSION: Network multiplexity is prevalent and positively associated with the subjective well-being of older adults who have at least one confidant and one caregiver, above and beyond having any confidants or caregivers separately. The baseline patterns established in this study lay the groundwork for future research to further explore support dynamics in older adults' networks.

Evaluating Open Dialogue in Italian mental health services: evidence from a multisite prospective cohort study.

Objective: This longitudinal study aimed to quantitatively document and evaluate the implementation and outcomes of the Open Dialogue (OD) approach within Italian Mental Health Departments (MHDs), focusing on the ratings of OD-network meetings by patients and their families and assessing the clinical outcomes over a span of 12 months. Results: Over the course of the study, 58 patients participated in 517 OD-network meetings, demonstrating a high level of satisfaction with the care received, as evidenced by the Session Rating Scale (SRS) and Outcome Rating Scale (ORS). Clinically, significant improvements were observed in the Global Assessment of Functioning (GAF), Clinical Outcomes in Routine Evaluation (CORE-OM), and the Lubben Social Network Scale (LSNS), indicating enhanced psychological and social functioning. The SRS scores showed that satisfaction with the meetings increased over time, while the ORS indicated that both patients and their social networks perceived gradual improvements throughout the therapy. Conclusion: The OD approach within Italian MHDs was successfully implemented and well-received by patients and their social networks, yielding significant clinical improvements. These findings suggest the feasibility and effectiveness of integrating the OD model into the Italian public mental health system, supporting its potential for broader application in diverse healthcare settings. The study highlights the importance of continuous engagement and evaluation to maintain high standards of practice and suggests that OD can be a valuable addition to existing mental health care practices, promoting recovery through inclusive, dialogue-based interventions.

Social network influence based on SHIR and SLPR propagation models.

The rapid progress of science and technology has revolutionized the dissemination of information, with the Internet playing a crucial role. While it has enhanced the ease of sharing information, it has also hastened the transmission of emotions on social media, sometimes resulting in unintended negative outcomes. This research seeks to tackle this issue by suggesting an innovative technique for analyzing social network influence using the Susceptible Hesitant Infected Removed (SHIR) and Susceptible Latent Propagative Removal (SLPR) propagation models. Through the development of an emotional communication model, we take into account the effects of news and public opinion on the rate of emotional communication among individuals. Furthermore, we investigate the impact of various network structures on user behavior. The findings from experiments demonstrate a notable relationship between changes in the density of emotion spreaders and hesitants and the influence of nodes in different network configurations. Specifically, the analysis reveals that the peaks of hesitators and disseminators were lower when the node influence was reduced. Additionally, we verified the precision and dependability of our model by examining data from the Baidu Index, a tool for big data analysis. The margin of error between the model and the actual data was minimal, underscoring the efficacy of our approach. In essence, the study highlights a direct correlation between the speed and extent of emotional propagation in social networks and the degree of nodes. The results showed that the density changes of emotion spreaders and hesitants were significantly correlated with the influence of nodes in different network settings. In the case of node influence of 0.86, the highest peaks of hesitator H and disseminator I were 0.101 and 0.109 lower than those of influence of 1.25. The data analysis of the Baidu Index showed that the maximum peak error of the model was only 0.04, which verified the accuracy and reliability of the model. This investigation carries significant implications for efficiently managing and steering the dissemination of emotions on social media, thereby promoting a healthier online environment.

Machine learning and natural language processing to assess the emotional impact of influencers' mental health content on Instagram.

Background: This study aims to examine, through artificial intelligence, specifically machine learning, the emotional impact generated by disclosures about mental health on social media. In contrast to previous research, which primarily focused on identifying psychopathologies, our study investigates the emotional response to mental health-related content on Instagram, particularly content created by influencers/celebrities. This platform, especially favored by the youth, is the stage where these influencers exert significant social impact, and where their analysis holds strong relevance. Analyzing mental health with machine learning techniques on Instagram is unprecedented, as all existing research has primarily focused on Twitter. Methods: This research involves creating a new corpus labelled with responses to mental health posts made by influencers/celebrities on Instagram, categorized by emotions such as love/admiration, anger/contempt/mockery, gratitude, identification/empathy, and sadness. The study is complemented by modelling a set of machine learning algorithms to efficiently detect the emotions arising when faced with these mental health disclosures on Instagram, using the previous corpus. Results: Results have shown that machine learning algorithms can effectively detect such emotional responses. Traditional techniques, such as Random Forest, showed decent performance with low computational loads (around 50%), while deep learning and Bidirectional Encoder Representation from Transformers (BERT) algorithms achieved very good results. In particular, the BERT models reached accuracy levels between 86-90%, and the deep learning model achieved 72% accuracy. These results are satisfactory, considering that predicting emotions, especially in social networks, is challenging due to factors such as the subjectivity of emotion interpretation, the variability of emotions between individuals, and the interpretation of emotions in different cultures and communities. Discussion: This cross-cutting research between mental health and artificial intelligence allows us to understand the emotional impact generated by mental health content on social networks, especially content generated by influential celebrities among young people. The application of machine learning allows us to understand the emotional reactions of society to messages related to mental health, which is highly innovative and socially relevant given the importance of the phenomenon in societies. In fact, the proposed algorithms' high accuracy (86-90%) in social contexts like mental health, where detecting negative emotions is crucial, presents a promising research avenue. Achieving such levels of accuracy is highly valuable due to the significant implications of false positives or false negatives in this social context.

Social networks as facilitators and barriers to behavior change among U.S. South Asian adult participants of a culturally adapted, group lifestyle intervention.

OBJECTIVES: This qualitative study aimed to characterize how social networks influence cardiovascular health behaviors among U.S. South Asian adults in a culturally adapted, group lifestyle intervention. METHODS: A purposive sample of participants (n = 24) from the South Asian Healthy Lifestyle Intervention (SAHELI) randomized trial's intervention arm participated in semi-structured process evaluation interviews. Specific open-ended questions were used to probe participants' behavior changes, personal social networks, and social support for behavior change. The team transcribed interviews and identified themes using inductive and deductive coding, based on a theoretical model of social influence. RESULTS: Among 24 participants (67 % female, mean age 50.5 years, 88 % foreign-born, 50 % with limited English proficiency), three themes emerged: 1) SAHELI participants and their family members provided bidirectional social support for behavior change; 2) intervention participants provided social support to one another; and 3) participants faced resistance to change from some community members. CONCLUSIONS: Behavior changes initiated during SAHELI diffused to participants' close family members. Several social network influences varied by participant gender, English language proficiency, and network member type. PRACTICE IMPLICATIONS: Health professionals should ask patients about how their social networks facilitate or hinder behavior changes. Gender and cultural factors may modify how social networks influence behavior change.

Associations of close social connections with smoking and vaping: a population study in England.

INTRODUCTION: Studies consistently demonstrate smoking is a socially contagious behaviour, but less is known about the influence of social connections on vaping. This study examined associations between having close social connections who smoke or vape and relevant smoking and vaping outcomes. METHODS: This was a representative cross-sectional survey of adults (≥16y) in England. Participants (n=1,618) were asked how many people they discuss important matters with (i.e., close social connections) and how many of them smoke/vape. We tested associations between (i) smoking and (ii) vaping among close social connections and participants' own smoking and vaping status; harm perceptions of e-cigarettes (among current smokers); attempts and success in quitting smoking (among past-year smokers); and use of e-cigarettes as a smoking cessation aid (among past-year smokers who tried to quit). RESULTS: Adults with ≥1 close social connection who smoke were more likely than those with none to smoke themselves (32.8% vs. 9.4%; ORadj=7.23[95%CI 4.74-11.0]) and had an uncertain lower likelihood to quit (12.2% vs. 19.8%; ORadj=0.46[0.17-1.23]). Those with ≥1 close social connection who vape were more likely than those with none to vape themselves (29.6% vs. 6.3%; ORadj=5.16[3.15-8.43]) and to use e-cigarettes in their most recent attempt to quit (57.0% vs. 27.9%; ORadj=18.0[1.80-181]), and had an uncertain higher likelihood to perceive e-cigarettes as less harmful than cigarettes (30.8% vs. 12.2%; ORadj=2.37[0.82-6.90]). CONCLUSIONS: In England, we replicated well-established associations with smoking and found similar evidence for vaping. People were much more likely to vape and to use e-cigarettes to quit smoking if they had close social connections who vaped. IMPLICATIONS: The cross-sectional design means it is not clear whether smoking/vaping among close social connections influences people to smoke/vape themselves, or whether people who smoke/vape select to form close social connections with others who similarly smoke/vape. Further research is required to establish causality. If the associations we observed are causal, interventions that encourage smokers to switch to vaping may have positive spillover effects on social connections' perceptions of e-cigarettes and use of these products to support smoking cessation.

Endogenous dynamics of denunciation: Evidence from an inquisitorial trial.

We develop an endogenous approach to the practice of denunciation, as an alternative to exogenous historical and sociological accounts. It analyzes denunciation as a response to increasing pressure, which in turn increases pressure on social contacts. The research context is the trial of Waldensians in Giaveno, Italy, in 1335, headed by the inquisitor Alberto de Castellario. A dynamic network actor model attests that coercive pressure not only raises the rate of denunciation but also compels denouncers to implicate individuals who are socially closer to them. We find that coercive pressure starts yielding diminishing returns relatively quickly, with the degree of redundancy of information escalating as a result of preferential attachment, increasingly targeting those already denounced by others, publicly announced suspects, and those having absconded from the trial.

Framing openness: Exploring Similarities and Differences in Patients' and Their Social Networks' Experiences with Participating in Dialogical Network Meetings Through the Lens of Mattering.

In this qualitative study conducted at a public mental health outpatient clinic in Norway, the integration of patients' social network in treatment was examined. The aim was to explore the experiences of patients and their network during dialogical network meetings and discuss any similarities and differences between the two participant groups. Reflexive thematic analysis was performed on data obtained from fifty-three meetings, resulting in the development of five themes. For patients, there were two themes: "Enhanced trust within our relationships" and "Providing us a safe space to talk openly," and for network members there were three: "Empowered through participation," Being welcomed and taken seriously," and "Provide more clarity to enhance our ability to contribute." Mattering was employed as a conceptual framework to discuss the similarities and differences between the themes of the two participant groups. Both patients and network members placed strong emphasis on the freedom of expression and acknowledged the crucial role of the meeting leaders in facilitating discussions on important and challenging topics. Differences included network members' emphasis on feeling welcome and their need to add value, while patients emphasized strengthened relationships and feeling valued and empowered by being trusted to control the discussion content. Overall, mattering appears to be a valuable tool for understanding the relational dynamics within network meetings.\.

Social network characteristics and their relationships with physical activity in children with multiple sclerosis.

BACKGROUND: Physical activity has been found to associate with improved health outcomes in children with multiple sclerosis (MS). Social networks may facilitate physical activity in children with MS. OBJECTIVES: To estimate associations between social network characteristics and physical activity in children with MS compared to children with monophasic acquired demyelinating syndrome (mono-ADS). METHODS: Children with MS and mono-ADS recruited from the Hospital for Sick Children completed questionnaires on social network and physical activity. Descriptive and inferential analyses estimated differences between cohorts and correlations. RESULTS: Children with MS (n = 16) and mono-ADS (n = 22) did not differ in outcomes. Higher physical activity associated with larger social networks (rs= 0.681, p < 0.01), more Emotional Support (rs= 0.604, p < 0.05), Camaraderie (rs= 0.585, p < 0.05), more social network members with post-secondary education (rs= 0.680, p < 0.05), and members who exercise 3 to 4 times a week (rs= 0.744, p < 0.01). These associations were not found in children with mono-ADS. CONCLUSION: Larger social network size, more emotional support and camaraderie, and more individuals with post-secondary education and who regularly exercise in the social network associated with higher physical activity in children with MS. Social network characteristics may help understand health behaviors in children with MS.

Innovating a Community-driven Enumeration and Needs Assessment of People Experiencing Homelessness: A Network Sampling Approach for the HUD-Mandated Point-in-Time Count.

To enumerate people experiencing homelessness in the U.S., the federal Department of Housing and Urban Development (HUD) mandates its designated local jurisdictions regularly conduct a crude census of this population. This Point-in-Time (PIT) body count, typically conducted on a January night by volunteers with flashlights and clipboards, is often followed by interviews with a separate convenience sample. Here, we propose employing a network-based (peer-referral) respondent-driven sampling (RDS) method to generate a representative sample of unsheltered people, accompanied by a novel method to generate a statistical estimate of the number of unsheltered people in the jurisdiction. First, we develop a power analysis for the sample size of our RDS survey to count unsheltered people experiencing homelessness. Then, we conducted three large-scale population-representative samples in King County, WA (Seattle metro) in 2022, 2023, and 2024. We describe the data collection and the application of our new method, comparing the 2020 PIT count (the last visual PIT count performed in King County) to the new method 2022 and 2024 PIT counts. We conclude with a discussion and future directions.

The contribution of movement to social network structure and spreading dynamics under simple and complex transmission.

The structure of social networks fundamentally influences spreading dynamics. In general, the more contact between individuals, the more opportunity there is for the transmission of information or disease to take place. Yet, contact between individuals, and any resulting transmission events, are determined by a combination of spatial (where individuals choose to move) and social rules (who they choose to interact with or learn from). Here, we examine the effect of the social-spatial interface on spreading dynamics using a simulation model. We quantify the relative effects of different movement rules (localized, semi-localized, nomadic and resource-based movement) and social transmission rules (simple transmission, anti-conformity, proportional, conformity and threshold rules) to both the structure of social networks and spread of a novel behaviour. Localized movement created weakly connected sparse networks, nomadic movement created weakly connected dense networks, and resource-based movement generated strongly connected modular networks. The resulting rate of spreading varied with different combinations of movement and transmission rules, but-importantly-the relative rankings of transmission rules changed when running simulations on static versus dynamic representations of networks. Our results emphasize that individual-level social and spatial behaviours influence emergent network structure, and are of particular consequence for the spread of information under complex transmission rules.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

Interactions between neural representations of the social and spatial environment.

Even in our highly interconnected modern world, geographic factors play an important role in human social connections. Similarly, social relationships influence how and where we travel, and how we think about our spatial world. Here, we review the growing body of neuroscience research that is revealing multiple interactions between social and spatial processes in both humans and non-human animals. We review research on the cognitive and neural representation of spatial and social information, and highlight recent findings suggesting that underlying mechanisms might be common to both. We discuss how spatial factors can influence social behaviour, and how social concepts modify representations of space. In so doing, this review elucidates not only how neural representations of social and spatial information interact but also similarities in how the brain represents and operates on analogous information about its social and spatial surroundings.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

Social network, fair payment, subjective well-being, and general health: a moderation mediation analysis.

Objective: This research aimed to investigate whether subjective general health mediated the relationship between social networks and subjective well-being and whether the perception of fair payment moderated the mediating effect of subjective general health on subjective well-being. Methods: Data were drawn from round 9 of the European Social Survey (ESS), involving 3,843 respondents from 19 countries, with ages ranging from 65 to 90 years (Meanage = 73.88 ± 6.61 years). The participants completed self-reported measures assessing subjective well-being, social networks, subjective general health, and perception of fair payment. Results: Subjective general health played a mediating role in the relationship between social networks and subjective well-being. The perception of fair payment emerged as a moderator in the mediating effect of subjective general health on the association between social networks and subjective well-being. Conclusion: This study suggests that the impact of social networks on both subjective general health and subjective well-being is contingent upon individuals' perceptions of fair payment. These results highlight the significance of social networks in fostering social connections and promoting overall subjective well-being.

Supporting Pre-Exposure Prophylaxis Uptake: Exploring Social Network Characteristics among Black Women and Acceptability of Social Network Strategies.

Black women continue to be disproportionally burdened by HIV. Pre-exposure prophylaxis (PrEP) is an effective HIV prevention option, which is underused by Black women. While social network interventions (SNIs) have been widely researched and implemented among some groups vulnerable to HIV, little is known about social network characteristics among Black women. To learn more about the social networks of Black women vulnerable to HIV and their knowledge of and interest in PrEP, we conducted a cross-sectional survey among 109 Black women aged 18-45 years attending a family planning clinic in Chicago, Illinois. In our study, 44% of women reported that they were moderately to extremely concerned about HIV. Over half of participants (53%) had a small personal network size (i.e., less than two). No statistically significant associations between having larger network sizes and having previously heard of PrEP, having an interest in starting PrEP, or having good PrEP knowledge were detected. Open-ended responses revealed high levels of trust in network connections with matters related to sexual health. Additionally, nearly all (94%) of women reported that SNIs were a good idea to promote PrEP. Future network studies are needed to inform the development of effective intervention strategies for women.

Using confirmatory principal component analysis to uncover the interplay between social and spatial factors among older adults: An exploratory study.

This study examines the complex interplay between social and spatial structures among older adults, emphasizing the interest in considering the social composition of activity spaces and the spatial characteristics of social networks. There is a growing interest in the collection and analysis of both social and daily mobility spatial information to better understand people-place interactions and determinants of health. Yet, few analyses have explored how the social and spatial dimensions of people's lives relate. In this exploratory study, we analyze how social and spatial indicators collected with the VERITAS-Social questionnaire among 98 older adults in Montréal, Canada, relate, using confirmatory principal component analysis. The aim of the article is to provide empirical evidence on the reduction of dimensions of measures related to social networks, activity spaces, and combined socio-spatial structures.

A Return to Biased Nets: New Specifications and Approximate Bayesian Inference.

The biased net paradigm was the first general and empirically tractable scheme for parameterizing complex patterns of dependence in networks, expressing deviations from uniform random graph structure in terms of latent "bias events," whose realizations enhance reciprocity, transitivity, or other structural features. Subsequent developments have introduced local specifications of biased nets, which reduce the need for approximations required in early specifications based on tracing processes. Here, we show that while one such specification leads to inconsistencies, a closely related Markovian specification both evades these difficulties and can be extended to incorporate new types of effects. We introduce the notion of inhibitory bias events, with satiation as an example, which are useful for avoiding degeneracies that can arise from closure bias terms. Although our approach does not lead to a computable likelihood, we provide a strategy for approximate Bayesian inference using random forest prevision. We demonstrate our approach on a network of friendship ties among college students, recapitulating a relationship between the sibling bias and tie strength posited in earlier work by Fararo.

Close Relations, Practitioners or Social Networks: What Affects the Selection of Infant Formula Products?

This study examines which factors influence the preferences of mothers seeking advice on the use of infant formula in feeding practices. The effects of their close social circle, medical professionals and social network forums on feeding choices were evaluated. Data were collected from 638 questionnaires from mothers and were statistically analyzed. Our findings suggest that age may influence the preference to seek advice from a close social circle over consulting with medical professionals (p-value = 0.019 < 0.05). The educational level and the number of children impact the preferences of using infant formula over combining it with breastfeeding (p-value = 0.000 < 0.05 and p-value = 0.004 < 0.05, respectively). The research contributes to the understanding of the complex interplay between various demographic and socioeconomic factors and the decision-making process of mothers based on multiple social and digital sources of influence. The research presents valuable insights for healthcare policymakers and professionals in supporting mothers and providing them with up-to-date information. Feeding information can be distributed through all the communication channels that were examined in this study to benefit different socio-economic groups and to contribute to the well-being of infants in the long-run.

Community Forest Management and the Resilience of Karen Indigenous Knowledge in Northern Thailand.

This study investigates the resilience of indigenous knowledge in five Karen villages, located in Thailand's Chiang Mai, Chiang Rai, and Lampang provinces, that have been recognized for best practices in community forest management (CFM). The CFM model was initiated by local communities to promote forest conservation and community engagement. Data on CFM practices, land-use rights, social networks, and indigenous knowledge were collected through 17 in-depth interviews and 5 focus group meetings. The findings include how these Karen communities have adopted payment for environmental services (PES) to fund conservation projects and social welfare. More specifically, PES generates social capital by facilitating coordination with stakeholders from the private sector, academia, and government. These social networks promote markets for local products and advocate for indigenous land-use rights. The PES model also serves as a tool whereby Indigenous Peoples can shape their identities as innovative forest guardians and legitimize their residence within the forest. Additionally, the study reports on how Karen people have diversified their livelihoods to include hosting academic tourism, handicrafts, and livestock, reducing their dependence on forest resources.