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.

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.

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.

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.

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.

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.

Social network shrinking is explained by active and passive effects but not increasing selectivity with age in wild macaques.

Evidence of social disengagement, network narrowing and social selectivity with advancing age in several non-human animals challenges our understanding of the causes of social ageing. Natural animal populations are needed to test whether social ageing and selectivity occur under natural predation and extrinsic mortality pressures, and longitudinal studies are particularly valuable to disentangle the contribution of within-individual ageing from the demographic processes that shape social ageing at the population level. Data on wild Assamese macaques (Macaca assamensis) were collected between 2013 and 2020 at the Phu Khieo Wildlife Sanctuary, Thailand. We investigated the social behaviour of 61 adult females observed for 13 270 h to test several mechanistic hypotheses of social ageing and evaluated the consistency between patterns from mixed-longitudinal and within-individual analyses. With advancing age, females reduced the size of their social network, which could not be explained by an overall increase in the time spent alone, but by an age-related decline in mostly active, but also passive, behaviour, best demonstrated by within-individual analyses. A selective tendency to approach preferred partners was maintained into old age but did not increase. Our results contribute to our understanding of the driver of social ageing in natural animal populations and suggest that social disengagement and selectivity follow independent trajectories during ageing.

Salient beliefs related to secondary distribution of COVID-19 self-test kits within social networks.

Background: Widespread access to testing is critical to public health efforts to control the COVID-19 pandemic. Secondary distribution of COVID-19 self-test kits, where an individual distributes test kits to others in their social networks, is a potential strategy to improve access to testing. In this qualitative study, we identified salient beliefs about distributing and accepting COVID-19 self-test kits within one's social network, as well as ordering COVID-19 self-test kits from the government. Methods: We recruited 61 participants from a randomized controlled trial (NCT04797858) in Philadelphia, Pennsylvania to elicit beliefs about (1) distributing COVID-19 self-test kits within one's social network, (2) receiving test kits from social contacts, and (3) ordering self-test kits from the government. Using validated, open-ended question stems, we identified the most common set of beliefs underlying attitudes, perceived norms (or social referents), and perceived behavioral control (or self-efficacy) toward each of these behaviors. Results: Twenty-seven out of 30 (90%) of participants who received self-test kits reported distributing the kits to social contacts. These participants described altruistic beliefs about giving others access to testing, and felt approval from family members, friends, and others in their social networks. When receiving test kits from social network contacts, participants described advantages of test kit convenience, but some voiced concern about test kit tampering and confusing instructions. Participants also described perceived logistic barriers to distributing and receiving self-test kits, such as delivering or transporting test kits, or finding time to meet. Participants who ordered test kits from the government also described increased convenience of test access, but described different logistic barriers such as delays in test kit delivery, or not receiving test kits at all. Conclusion: In comparison with government-ordered test kits, the secondary distribution of COVID-19 self-test kits raised unique concerns about test kit quality and instructions, as well as distinctive logistic barriers related to distributing self-test kits to network contacts, which were not raised for test kits ordered from the government. This study demonstrates that beliefs may vary depending on the type of testing behavior, and behavioral interventions may benefit from developing messages tailored to specific testing strategies.

General protocol for predicting outbreaks of infectious diseases in social networks.

Epidemic spreading on social networks with quenched connections is strongly influenced by dynamic correlations between connected nodes, posing theoretical challenges in predicting outbreaks of infectious diseases. The quenched connections introduce dynamic correlations, indicating that the infection of one node increases the likelihood of infection among its neighboring nodes. These dynamic correlations pose significant difficulties in developing comprehensive theories for threshold determination. Determining the precise epidemic threshold is pivotal for diseases control. In this study, we propose a general protocol for accurately determining epidemic thresholds by introducing a new set of fundamental conditions, where the number of connections between individuals of each type remains constant in the stationary state, and by devising a rescaling method for infection rates. Our general protocol is applicable to diverse epidemic models, regardless of the number of stages and transmission modes. To validate our protocol's effectiveness, we apply it to two widely recognized standard models, the susceptible-infected-recovered-susceptible model and the contact process model, both of which have eluded precise threshold determination using existing sophisticated theories. Our results offer essential tools to enhance disease control strategies and preparedness in an ever-evolving landscape of infectious diseases.

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.

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.

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.

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.