User tendency-based rating scaling in online trading networks.

Social networks often involve the users rating each other based on their beliefs, abilities, and other characteristics. This is particularly common in e-commerce platforms where buyers rate sellers based on their trustworthiness. However, the rating tends to vary between users due to differences in their individual scoring criteria. For example, in a transaction network, a positive user may give a high rating unless the transaction was unsatisfactory while a neutral user may give a mid-rating, consequently giving the same numeric score to different levels of satisfaction. In this paper, we propose a novel method called user tendency-based rating scaling, which adjusts the current rating (its score) based on the pattern of past ratings. We investigate whether this rating scaling method can classify between "good users" and "bad users" in online trade social networks better when compared with using the original rating scores without scaling. Classifying between good users and bad users is especially important for anonymous rating networks like Bitcoin transaction networks, where users' reputations must be recorded to preclude fraudulent and risky users. We evaluate the proposed rating scaling method by performing user classification, link prediction, and clustering tasks, using three real-world online rating network datasets. We use both the original ratings and the scaled ratings as weights of graphs and use a weighted graph embedding method to find node representations that reflect users' positive and negative information. The experimental results showed that using the proposed rating scaling method outperformed using the original (i.e., unscaled) ratings by up to 17% in classification accuracy, and by up to 2.5% in link prediction based on the AUC ROC measure, and by up to 21% in the clustering tasks based on the Dunn-index.

Diversity, integration, and variability of intergenerational relationships in old age: New insights from personal network research.

Relationships between family members from different generations have long been described as a source of solidarity and support in aging populations and, more recently, as a potential risk factor for COVID-19 contagion. Personal or egocentric network research offers a powerful kit of conceptual and methodological tools to study these relationships, but this has not yet been employed to its full potential in the literature. We investigate the heterogeneity, social integration, and individual correlates of intergenerational relationships in old age analyzing highly granular data on the personal networks of 230 older adults (2747 social ties) from a local survey in one of the areas of the world at the forefront of global aging trends (northern Italy). Using information on different layers in broad egocentric networks and on the structure of connectivity among the social contacts of aging people, we propose multiple conceptualizations and measures of intergenerational connectedness. Results show that intergenerational relationships are strongly integrated, but also highly diverse and variable, in older adults' social networks. Different types of intergenerational ties exist in different network layers, with various relational roles, degrees of tie strength, and patterns of association with individual and tie characteristics. We discuss how new and existing personal network data can be leveraged to consider novel questions and hypotheses about intergenerational relationships in contemporary aging families.

Antecedents of social media addiction in high and low relational mobility societies: Motivation to expand social network and fear of reputational damage.

Contrary to previous studies on the antecedent factors of social media addiction, we focused on the social environmental factor of relational mobility (i.e., the ease of constructing new interpersonal relationships) and investigated its relationship with social media addiction. People in low relational mobility societies have fewer opportunities to select new relationship partners and consequently feel a stronger need to maintain their reputation. We hypothesized that (1) people in low relational mobility societies are more strongly addicted to social media because they estimate that greater reputational damage will be caused by ignoring messages and (2) people in low relational mobility societies estimate greater reputational damage than actual damage. We conducted two online experiments with 715 and 1,826 participants. Our results demonstrated that (1) there is no relationship between relational mobility and social media addiction and (2) people in both high and low relational mobility societies overestimate reputational damage. Furthermore, we demonstrated that the social media addiction mechanism differs between societies: (3) people in low relational mobility societies estimate greater reputational damage, whereas (4) people in high relational mobility societies are more motivated to expand their social networks; both mechanisms strengthen their social media addiction. Based on these results, we propose interventions for moderating social media addiction in both high and low relational mobility societies.

NBCAL violation of products that compete with breastfeeding on the social network Instagram. / Violação à NBCAL de produtos que competem com a amamentação na rede social Instagram.

The article aims to identify NBCAL violations and analyze the content of messages posted on the Instagram social network. This qualitative-quantitative study consisted of a convenience sample of profiles identified through specific terms preceded by the hashtag symbol (#). Data were collected for two months by trained researchers using a structured questionnaire. We calculated the product promotion frequency that characterized violation of the NBCAL per category and manufacturer. The messages were analyzed using the content analysis technique. We identified 64 personal accounts of mothers with violations in 89 products, mainly food (n = 72), dairy compounds (54.2%), and infant formulas (45.8%) were the most publicized. Two thematic categories emerged from the posted texts, one related to the quality of the products and the other about breastfeeding difficulty, especially low milk production. The study identified NBCAL violations on the Instagram social network, alerting the need to recognize digital marketing to include it in the rules imposed by the Norm in the virtual context, considering the capillarity of social networks in disseminating information to the public in question.

O artigo objetiva identificar infrações à NBCAL e analisar o conteúdo das mensagens postadas na rede social Instagram. Estudo de abordagem quali-quantitativa, com amostra de conveniência composta por perfis identificados por meio de termos específicos, precedidos do símbolo hashtag (#). A coleta de dados foi realizada durante dois meses por pesquisadores treinados, por meio de questionário estruturado. Calculou-se a frequência de promoção de produtos que caracterizava violação à NBCAL, segundo categoria e fabricante. As mensagens foram analisadas por meio da técnica de análise de conteúdo. Foram identificadas 64 contas pessoais de mulheres mães com infrações em 89 produtos, a maioria alimentos (n = 72), sendo os compostos lácteos (54,2%) e as fórmulas infantis para lactentes (45,8%) os mais divulgados. Duas categorias temáticas emergiram dos textos postados, uma relativa à qualidade dos produtos e a outra sobre a dificuldade com a amamentação, especialmente a baixa produção de leite. O estudo identificou violações à NBCAL na rede social Instagram, alertando para a necessidade do reconhecimento do marketing digital para incluí-lo nas regras impostas pela norma no contexto virtual, considerando a capilaridade das redes sociais na divulgação de informações para o público em questão.

How do social networks, perception of social isolation, and loneliness affect depressive symptoms among Japanese adults?

OBJECTIVE: This study aims to elucidate the complex relationship among social isolation, loneliness, and perception of social isolation and its influence on depressive symptoms by evaluating a hypothetical model. This understanding is essential for the formulation of effective intervention strategies. METHODS: We conducted an online survey on Japanese adults (N = 3,315) and used the six-item Lubben Social Network Scale to assess the size of their social networks. We employed a single question to gauge their perception of social isolation. Loneliness was assessed using the three-item UCLA Loneliness Scale, and depressive symptoms were examined using the Patient Health Questionnaire-9. Structural equation modeling was employed to test the hypothesized model. RESULTS: The final model demonstrated satisfactory fit with data (χ2 (1) = 3.73; not significant; RMSEA = 0.03; CFI = 1.00; TLI = 1.00). The size of social network demonstrated a weak negative path to loneliness and depressive symptoms (ß = -.13 to -.04). Notably, a strong positive association existed between perception of social isolation and loneliness (ß = .66) and depressive symptoms (ß = .27). Additionally, a significant positive relationship was found between loneliness and depressive symptoms (ß = .40). Mediation analysis indicated that perception of social isolation and loneliness significantly intensified the relationships between social networks and depressive symptoms. CONCLUSIONS: Results indicate that interventions of psychological approaches, such as cognitive-behavioral therapy, are effective in reducing the perception of social isolation and loneliness, which may lead to the prevention of depressive symptoms. Future longitudinal studies are expected to refine and strengthen the proposed model.

A social image recommendation system based on deep reinforcement learning.

Today, due to the expansion of the Internet and social networks, people are faced with a vast amount of dynamic information. To mitigate the issue of information overload, recommender systems have become pivotal by analyzing users' activity histories to discern their interests and preferences. However, most available social image recommender systems utilize a static strategy, meaning they do not adapt to changes in user preferences. To overcome this challenge, our paper introduces a dynamic image recommender system that leverages a deep reinforcement learning (DRL) framework, enriched with a novel set of features including emotion, style, and personality. These features, uncommon in existing systems, are instrumental in crafting a user's characteristic vector, offering a personalized recommendation experience. Additionally, we overcome the challenge of state representation definition in reinforcement learning by introducing a new state representation. The experimental results show that our proposed method, compared to some related works, significantly improves Recall@k and Precision@k by approximately 7%-10% (for the top 100 images recommended) for personalized image recommendation.

Care complexity, perceptions of complexity and preferences for interprofessional collaboration: an analysis of relationships and social networks in paediatrics.

BACKGROUND: In the context of increasingly intricate healthcare systems, professionals are compelled to collaborate within dynamically changing interprofessional teams. Moreover, they must adapt these collaborative processes to effectively and efficiently manage the evolving complexity of care needs. It remains unclear how professionals determine care complexity and relate this complexity to their preferences for interprofessional collaboration (IPC). This study investigated the relationships between care complexity, professionals' perceived complexity and IPC preferences, and examined the variation in individual and team characteristics of IPC-practices across different levels of complexity in paediatric care. METHODS: In an online questionnaire, 123 healthcare professionals working at an academic tertiary children's hospital scored their perceptions of complexity and preferences for IPC. They also selected family and various professions as members of the interprofessional (IP-) team based on thirteen patient cases. We employed conjoint analysis to systematically model the complexity of case descriptions across the five domains of the International Classification of Functioning, Disability and Health (ICF). Additionally, we applied social network analysis to identify important professions, crucial connectors and influential professions in the IP-team, and to describe the cohesiveness of IP-teams. RESULTS: Modelled case complexity, professionals' perceived complexity and IPC preferences were positively associated. We found large inter-individual variations in the degree of these associations. Social network analysis revealed that the importance and influence of professions was more equally distributed when case complexity increased. Depending on the context and complexity of the case, different professions (e.g. medical doctors, social professionals, extramural professionals) were considered to be more crucial connectors within the IP-team. Furthermore, team cohesion was positively associated with modelled and perceived care complexity. CONCLUSIONS: In conclusion, our study contributes to the existing knowledge by integrating task-specific insights and broadening the use of conjoint and social network analysis in the context of IPC. The findings substantiate the contingency theory that relates characteristics of IPC to care complexity, offering quantified insights into how IP-teams adapt to situational needs. This understanding of relationships and variations within IPC holds crucial implications for designing targeted interventions in both clinical and health profession education contexts. Consequently, it contributes to advancements in healthcare systems.

Shaping opinions in social networks with shadow banning.

The proliferation of harmful content and misinformation on social networks necessitates content moderation policies to maintain platform health. One such policy is shadow banning, which limits content visibility. The danger of shadow banning is that it can be misused by social media platforms to manipulate opinions. Here we present an optimization based approach to shadow banning that can shape opinions into a desired distribution and scale to large networks. Simulations on real network topologies show that our shadow banning policies can shift opinions and increase or decrease opinion polarization. We find that if one shadow bans with the aim of shifting opinions in a certain direction, the resulting shadow banning policy can appear neutral. This shows the potential for social media platforms to misuse shadow banning without being detected. Our results demonstrate the power and danger of shadow banning for opinion manipulation in social networks.

PROGRESO-II: Developing Culturally Tailored Materials for a Social Network-Based Intervention to Promote HIV Pre-Exposure Prophylaxis Initiation Among Latina Seasonal Farmworkers.

Latina Seasonal Farmworkers (LSFW) in South Florida are a community affected by human immunodeficiency virus (HIV) due to cultural barriers, stigma, and lack of awareness of pre-exposure prophylaxis (PrEP). Building on the PROGRESO study, this study sought to: (1) develop and pre-test scientifically supported and culturally tailored PrEP materials for PROGRESO and (2) assess the acceptability of these PrEP materials by LSFW who use alcohol and/or drugs. PrEP messages were selected based on a literature review, feedback from experts working on PrEP programs, and recommendations from a four-member scientific expert panel through a two-level Delphi method. A culturally tailored PrEP presentation was developed and presented to sixteen LSFW, who engaged in four focus groups. Materials were modified based on participants' suggestions. Thematic analysis was used to assess the acceptability and usability of these materials in the LSFW community. Participants responded positively to the PrEP messages and understood their importance for Latinx communities. Participants felt empowered and comfortable enough with the information to distribute the messages to partners, children, and friends with the aid of a physical pamphlet or flyer. A strong cultural context of familialismo and confianza was present in comments made by our participants. This study has the potential to increase LSFW's PrEP awareness and initiation. Future studies may implement a hybrid-interview approach, allowing individuals to self-select into a virtual or in-person focus group. Such flexibility may increase participation and discussion by allowing participants to attend in a format they are most comfortable with, as noted by participants in this study.

How adolescents lose control over social networks: A process-based approach to problematic social network use.

Social networks (SNs) are immensely popular, especially among teenagers, yet our understanding of problematic SNs remains limited. Understanding motivations and patterns of use is crucial given the current prevalence of problematic SNs use. Perarles et al. (2020) distinguish two behavioral control modes: Model-Free Control, where actions are characterized by actions driven by immediate gratification without reflective consideration for long-term consequences, and Model-Based Control, enabling planned and goal-directed actions. Both control modes can lead to problematic social network use. This study aims to delve into problematic SNs use and the underlying motives behind adolescents' participation in SNs, drawing upon the theoretical proposal by Perales et al. (2020). We conducted four focus groups with adolescents aged 13-17 (50 % female; Mage = 14.5, SD = 1.75), comprising two public school and two Catholic private school groups. Thematic analysis using Atlas.ti software revealed three themes. The first uncovers characteristics of problematic SNs use, including withdrawal, increased usage time, impaired control, behavioral salience and attentional capture and cognitive hijacking. The second spotlights motives, emphasizing emotional regulation, finding out what is going on, and social interaction. The third theme explores consequences such as compromised academic performance and physical harm. In conclusion, addressing both motives and problematic behaviors present a more effective approach to confronting SNs use challenges and fostering healthier online experiences for adolescents.

The mediating effect of social network identity management on the relationship between personality traits and social media addiction among pre-service teachers.

BACKGROUND: The use of social media has become an important part individuals' daily lives and is used in many daily life activities, such as social interaction, education, and shopping. However, with the increase in the use of social media, a minority of individuals can experience problematic use (and in extreme cases, 'social media addiction'). The purpose of the present study was to examine the effect of personality traits on social media addiction and the mediating role of social network identity management in this relationship among preservice teachers. METHODS: The data were collected from 275 pre-service teachers at a university in Türkiye. The survey included the Big Five Inventory-10 (BFI-10), the Social Network Identity Management Scale, the Bergen Social Media Addiction Scale, and a personal information form. RESULTS: The findings of the study indicated that there was a relationship between personality traits, social network identity management, and social media addiction. Specifically, neuroticism was positively associated with social media addiction, whereas extraversion, agreeableness and conscientiousness were negatively associated. The results also indicated that social network identity management mediated the effect of personality traits on social media addiction. CONCLUSION: Given that the present investigation was only a preliminary study, further research is needed to examine whether social network identity management is an important determinant in understanding the relationship between personality traits and social media addiction.

Perceived social support and characteristics of social networks of families with children with special healthcare needs following the COVID-19 pandemic.

Background: Children with special healthcare needs (CSHCN) require more support than the average of their peers. Support systems for CSHCN were particularly affected by pandemic control measures. Perceived social support is a resource for health and wellbeing for CSHCN and their families. Associations of social support, mental health and socioeconomic status (SES) have been described. This study aims to (1) assess perceived social support in families with and without CSHCN; (2) describe structure and types of social networks of families with and without CSHCN; and (3) explore associations between perceived social support, disease complexity, child and caregiver mental health, and SES. Methods: This is the third of a sequential series of cross-sectional online surveys conducted among caregivers of children ≤ 18 years in Germany since the beginning of the COVID-19 pandemic, administered between 1st December 2022 and 10 March 2023. The Brief Social Support Scale (BS6) assessed perceived social support. Child and parental mental health were assessed using the Strengths and Difficulties Questionnaire (SDQ) and WHO-5 Wellbeing index. The CSHCN-Screener identified CSHCN. Descriptive statistics and linear regression modeling assessed associations between perceived social support, parent-reported child mental health problems, disease complexity, caregiver mental wellbeing and SES. Results: The final sample included 381 participants, among them 76.6% (n = 292) CSHCN. 46.2% (n = 176) of caregivers reported moderate, i.e., at least occasional social support. Social support was largely provided by informal social networks consisting of partners, relatives and neighbors/friends. Linear regression modeling revealed associations of lower perceived social support with higher disease complexity of the child, lower caregiver mental wellbeing, lower SES and increasing caregiver age. Conclusion: The results of this study describe inequalities in perceived social support according to disease complexity of the child, caregiver mental health and socioeconomic status. They highlight the importance of social support and support networks as a resource for wellbeing of caregivers and CSHCN. Moving on from the COVID-19 pandemic, recovery strategies should focus on low-threshold interventions based in the community to improve social support for families with CSHCN and actively involve caregivers in identifying needs and co-creating new approaches.

Effectiveness of contact tracing on networks with cliques.

Contact tracing, the practice of isolating individuals who have been in contact with infected individuals, is an effective and practical way of containing disease spread. Here we show that this strategy is particularly effective in the presence of social groups: Once the disease enters a group, contact tracing not only cuts direct infection paths but can also pre-emptively quarantine group members such that it will cut indirect spreading routes. We show these results by using a deliberately stylized model that allows us to isolate the effect of contact tracing within the clique structure of the network where the contagion is spreading. This will enable us to derive mean-field approximations and epidemic thresholds to demonstrate the efficiency of contact tracing in social networks with small groups. This analysis shows that contact tracing in networks with groups is more efficient the larger the groups are. We show how these results can be understood by approximating the combination of disease spreading and contact tracing with a complex contagion process where every failed infection attempt will lead to a lower infection probability in the following attempts. Our results illustrate how contact tracing in real-world settings can be more efficient than predicted by models that treat the system as fully mixed or the network structure as locally treelike.

From an election to an insurrection: Investigating differential engagement and sentiment in the #defundthepolice and #defendthepolice network on Twitter.

Social movements and their respective countermovements have evolved to use online social media platforms to recruit followers, share pertinent information, discuss relevant issues, and draw the attention of political figures. Movements' strategic use of Twitter has increasingly been studied, though there are relatively few studies that compare social movements and their corresponding countermovements simultaneously. We examine engagement in the #DefundthePolice social movement and #DefendthePolice countermovement in a Twitter network comprised of retweets using both hashtags from August 2020 to January 2021. Text and sentiment analysis as well as a content analysis of a random sample of retweets in the network's 20 largest subgroups reveal four key patterns. First, information commonly communicated in historical social movements is communicated in the online, Twitter network. Second, the use of movement and countermovement hashtags to criticize is common, suggesting Twitter engagement with the movement/countermovement is not a sufficient indicator of support for the movement. Third, social movements are inextricably embedded in politics, with political discourse present in all the 20 largest subgroups. Finally, though we do not include geo-tagged tweets in the analysis, physical geography is key theme in multiple subgroups. Broadly, our findings demonstrate the breadth of topics communicated within movement networks and highlight the importance of qualitatively examining Twitter data in the study of social movements.

Revisiting the Modularity-Disease transmission Link: Uncovering the importance of intra-modular structure.

Studies have shown that the internal structure of modules is hardly important for the spread of epidemics. However, most of these studies have assumed that intra-module connectivity and inter-module connectivity do not affect each other. In reality, changes in the internal structure of modules may affect inter-module links and thus change the modularity of the entire network. Therefore, we have developed a theoretical network model with adjustable modularity to investigate the impact of this situation on disease transmission. Our findings indicate that the intra-module structure plays a crucial role in disease outbreaks. Changes in intra-module structure lead to significant numerical changes in peak prevalence and duration of disease. This implies that the potential impact of changes in exposure patterns within modules should also be considered when investigating the exact impact of modular social networks on disease burden.

"Unlinked lives": Elaboration of a concept and its significance for the life course.

This article introduces the concept of "unlinked lives" and illustrates its significance for scholarship on the life course. There are many lessons to be learned about human interdependence by focusing not on relationships that are formed and then maintained, but instead on relationships that are lost or ended by choice or circumstance, such as through changes in institutional affiliations, social status and positions or places. Unlinked lives carry important social meanings, are embedded in complex social processes, and bring consequences for the wellbeing of individuals, families, and societies. To develop this concept, we put forward nine key propositions related to when and how unlinkings happen as processes, as well as some of the consequences of being unlinked as a status or outcome. The coupling of "unlinked lives" with "linked lives" offers a crucial avenue for advancing life course theories and research, integrating scholarship across multiple life periods and transitions, and bridging the two now-distinct traditions of intellectual inquiry on the life course and on social networks.

Modelling social networks for children of parents with severe and enduring mental illness: an evidence based modification to the network episode model.

The Network Episode Model (NEM) is a well utilised model conceptualising how social networks, valuable resources which can positively impact wellbeing and functional outcomes, are responsive to the needs of people with physical and mental health difficulties. Children of parents with severe and enduring mental illness (COPMI) are impacted by these illnesses through the intersecting roles of kin relation, informal carer, and dependent. However, it is not clear that social networks effectively respond in kind to the child's episodic need.We draw upon qualitative data to propose a new multi-factorial conceptual model (COPMI-NEM), triangulating parental mental illness, child's developmental stage and social ties to theorise how social networks do respond and adapt to children's needs.The model illustrates how networks are typically flexible and responsive to visible age-related needs, but less reactive to more obscured needs. Successful network navigation and negotiation of support relies on multiple factors including the child's ability to successfully activate social ties and the availability of formal networks. We propose a new theoretically and empirically informed NEM model also available for testing, refinement and validation in other young carer populations exposed to episodic parental health needs. Findings from this study could be used to generate network informed interventions for this and comparable populations.

Unlocking the power of virtual networking for early-career researchers.

Many successful researchers in the biomedical sciences have benefitted from mentors and networks earlier in their career. However, early-career researchers from minoritized and underrepresented groups do not have the same access to potential mentors and networks as many of their peers. In this article we describe how 'cold emails' and social media platforms - notably Twitter/X and LinkedIn - can be used to build virtual networks, and stress the need to invest in maintaining networks once they have been established.

Social network tie functions of social support and social influence and adult smoking abstinence.

Adults' social network ties serve multiple functions and play prominently in quitting smoking. We examined three types of adults' egocentric social networks, including family, friends, and friends online to investigate how two network characteristics with major relevance to health behavior, network size and tie closeness, related to the emotional and confidant support and to pro- and anti-smoking social influence these ties may transmit. We also examine whether the social support and social influence constructs related to smoking abstinence. We utilized baseline and 7-day abstinence survey data from 123 adult current smokers attempting to quit prior to the start of a randomized controlled quit-smoking trial of a social support intervention for quitting smoking on Twitter. To examine study relationships, we estimated Negative Binomial Regression models and Logistic Regression models. For all networks, network size and tie closeness related positively to most of the social support and social influence constructs, with tie closeness related most strongly, especially for online friends. Family pro-smoking social influence related negatively to smoking abstinence, and there were marginally negative relationships for family emotional support and family confidant support. Online friend emotional support had a marginally positive relationship with smoking abstinence. Overall, our findings indicated the importance of the social support and social influence functions of each type of network tie, with larger networks and closer ties related to higher levels of social support and social influence. Moreover, family network pro-smoking social influence may compromise abstinence while emotional support from online friend network ties may reinforce it.

Exploring the Types of Social Support Exchanged by Survivors of Pediatric Stroke and Their Families in an Online Peer Support Community: Qualitative Thematic Analysis.

BACKGROUND: Pediatric stroke is relatively rare and underresearched, and there is little awareness of its occurrence in wider society. There is a paucity of literature on the effectiveness of interventions to improve rehabilitation and the services available to survivors. Access to online health communities through the internet may be a means of support for patients with pediatric stroke and their families during recovery; however, little research has been done in this area. OBJECTIVE: This study aims to identify the types of social support provided by an online peer support group to survivors of pediatric stroke and their families. METHODS: This was a qualitative thematic analysis of posts from a pediatric stroke population on a UK online stroke community active between 2004 and 2011. The population was split into 2 groups based on whether stroke survivors were aged ≤18 years or aged >18 years at the time of posting. The posts were read by 2 authors who used the adapted Social Support Behavior Code to analyze the types of social support exchanged. RESULTS: A total of 52 participants who experienced a pediatric stroke were identified, who posted a total of 425 messages to the community. About 41 survivors were aged ≤18 years at the time of posting and were written about by others (31/35 were mothers), while 11 were aged >18 years and were writing about themselves. Survivors and their families joined together in discussion threads. Support was offered and received by all participants, regardless of age. Of all 425 posts, 193 (45.4%) contained at least 1 instance of social support. All 5 types of social support were identified: informational, emotional, network, esteem support, and tangible aid. Informational and emotional support were most commonly exchanged. Emotional support was offered more often than informational support among participants aged ≤18 years at the time of posting; this finding was reversed in the group aged >18 years. Network support and esteem support were less commonly exchanged. Notably, the access subcategory of network support was not exchanged with the community. Tangible aid was the least commonly offered type of support. The exchanged social support provided insight into rehabilitation interventions and the unmet needs of pediatric stroke survivors. CONCLUSIONS: We found evidence of engagement of childhood stroke survivors and their families in an online stroke community, with peer support being exchanged between both long- and short-term survivors of pediatric stroke. Engagement of long-term survivors of pediatric stroke through the online community was key, as they were able to offer informational support from lived experience. Further interventional research is needed to assess health and rehabilitation outcomes from engagement with online support groups. Research is also needed to ensure safe, nurturing online communities.