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Explore how older patients utilize their social networks to inform prognostic understanding.In a pilot study of adults (≥65 years old) with advanced cancer, 16 patients completed surveys, social network maps, and semi-structured interviews exploring with whom they preferred to communicate about their illness. Interviews were analyzed using open-coding, and codes were categorized into emergent themes. Social network maps and themes were analyzed via mixed-methods social network analysis (MMSNA). Three case examples with diverse network characteristics and communication patterns were selected for further analysis.Three overarching themes (i.e., prognostic understanding, social support, and therapeutic alliance) revealed that patients' prognostic understanding was strongly influenced by the quality of the social support patients perceived from members of their social networks. Patients demonstrated prognostic understanding when they reported close relationships and open communication with their network members. Case examples revealed some ways that patients sought information and had better sense of their prognosis when they had supportive social networks.Findings illustrate how understanding social networks may provide information on how older adults with cancer seek, share, and process prognostic information.

A children's hospital explored the feasibility and utility of social network analysis as a tool for system building in community child health, to identify gaps and opportunities in community partnerships, and to assess its role as a contributor to collective impact.We employed social network analysis with the PARTNER survey to assess relationships among community-based organizations and a children's hospital's community-oriented programs. We utilized a two-stage, snowball sampling strategy to identify community partners. We analyzed social capital, network density, degree centralization, perceived trust, and perceived value. Network mapping depicted the hospital programs' relationships with community partners.Of the 153 contacted potential respondents, 76 responded for a response rate of 50%. Respondents reported a total of 1116 ties, ranging in strength from awareness and cooperation to coordination and integration. Approximately 60% of network members could reach 100 or more members in 2 steps or less. The overall network trust score was 74%. Network mapping indicated that hospital programs enhance bonding relationships within sectors, bridge gaps between partners from different sectors, and provide linkages to resources such as funders. Deficits in bonding, bridging, and access to funding are evident when the hospital's programs are omitted from network maps.Findings support the feasibility and utility of social network analysis as a tool for system building in community child health. The study demonstrates the potential of a children's hospital's programs to provide social capital in the form of bonding, bridging, and linking relationships.

Social networking sites (SNSs) are popular among college-aged adults. The defining characteristic of SNSs is that they are a platform to electronically share content. Most students report posting alcohol-related content (ARC) on SNSs. Little is known concerning these students who consume both alcohol and ARC yet choose not to generate ARC.The purpose of the current study was to compare key characteristics of posters and non-posters and develop a measure assessing reasons for not posting ARC.The researchers recruited a diverse sample of 1063 college students from two universities for an online study.Relative to posters of ARC, non-posters tend to drink less, have fewer alcohol-related problems, and report fewer reasons for drinking. Non-posters also report viewing several positive and negative consequences of drinking on SNSs, but at lower levels than ARC posters. The Reasons Not to Post ARC Scale was correlated with common alcohol measures (drinking motives, drinking problems) and self-monitoring. The scale was not correlated with some other measures (posting and sharing alcohol-related content).Given the dominant echo chamber effects of ARC on SNSs, examining non-posters can provide insight into the cognitions that might prevent others from joining the ARC social media culture.

To investigate the longitudinal prediction of intensity and emotional connection (EC) related to online social networking use at baseline on the risk of incident depression at nine-month follow-up among adolescents.A total of 3196 secondary school students, who were online social networking users and free of depression at baseline, were included in this study. Multilevel logistic regression models were applied to investigate the longitudinal prediction of two dimensions of online social networking use intensity (social function use intensity (SFUI), entertainment function use intensity (EFUI)) and EC scores at baseline on incident depression at follow-up.The incidence of depression was 23.37 per 100-person-years during a nine-month follow-up period. Baseline SFUI and EFUI scores were significantly associated with higher level of incident depression (adjusted OR = 1.017, 95% CI: 1.004-1.029 for SFUI, p = 0.010; adjusted OR = 1.046, 95% CI: 1.012-1.080 for EFUI, p = 0.007), after adjustment of significant background factors and baseline depressive symptom score. The associations of EC at baseline and its interaction with SFUI and EFUI on incident depression were statistically non-significant.Online social networking use seems be a risk factor of depression among adolescents, regardless of its specific functions. Early intervention is recommended to reduce the level of online social networking use intensity as a means of preventing depression among adolescents.

People who are socially isolated or lonely report having lower levels of social support. Supportive social networks help buffer individuals against the deleterious effects of negative events and stressors. Supportive social networks also help individuals maximize the benefits of positive events and accomplishments. In short, those who are socially isolated suffer more when bad things happen and gain less when good things happen than those who are more socially connected.

Human brain networks undergo pronounced changes during development. The emergence of highly connected hub regions that can support integrated brain function is central to this maturational process, with these areas undergoing a particularly protracted period of development that extends into adulthood. The location of cortical network hubs emerges early but connections to and from hubs continue to strengthen throughout childhood and adolescence. Patterns of functional coupling in cortical association hubs are immature and incomplete at birth, but gradually strengthen during development. Early establishment of hub connectivity may provide a stable substrate that is refined by changes in tissue organization and microstructure, resulting in the emergence of complex functional dynamics by adulthood.

It is widely believed that the demands of living in large, complexly bonded social groups played a key role in the evolution of human cognition. This review focuses on a critical but understudied skillset in the social-living toolkit: the ability to acquire, maintain, and use knowledge of the interpersonal relationships among the people around oneself. We provide a multidisciplinary synthesis of a diverse set of relevant findings, including recent work on the neural encoding and cognitive and behavioral consequences of knowledge of real-world social networks, research on how third-party relationship knowledge is tracked and used by children and other highly social primates, and research examining how people's knowledge of their social networks can be leveraged to inform the design of interventions aiming to promote behavior change or to efficiently spread information. We also highlight important unanswered questions and avenues in need of further exploration.

Examine predictors of social media use among a nationally representative sample of adults with children in the household.Data were collected from the Health Information National Trends (HINTS) Survey from 2017 to 2020 (N = 3559). Multivariate logistic regression models assessed the association between sociodemographic variables and social networking site (SNS) use, SNS use to share health information, participation in online forum or support groups for health issues and watching health-related videos on YouTube.Older adults and men were significantly less likely to use social media (p.05). Non-Hispanic African American (aOR: 1.83; 95%CI: 1.30-2.57), Hispanic (aOR: 2.16; 95%CI: 1.56-2.99), and Asian (aOR: 2.82; 95%CI: 1.67-4.75) adults were more likely to watch health-related videos on YouTube.Racial/ethnic minorities with children in the household were more likely to seek health information on YouTube, highlighting opportunities to disseminate culturally relevant, accurate messages on the platform. Effective health communication targeted to specific demographics can help counter misinformation and promote health behavior particularly during public health emergencies.Providers need to foster trust so that patients are comfortable to ask questions in addition to seeking information online. Providers can direct patients to credible resources to counter misinformation exposure and promote healthy behavior.

Background Examine the association of household financial indebtedness with depressive symptoms in old age, and investigate whether social network and support anticipation moderate the association. Methods Data were obtained from Sample Survey on Vulnerable Populations from Poor Families in Urban/Rural China (2018), with a sample of 5 934 older adults included. Center for Epidemiologic Studies Depression Scales was applied to measure depressive symptoms. Household indebtedness was measured in several ways, including whether the household was indebted, the amount of debts, and types of debts. We used the 6-item Lubben Social Network Scale to measure individual's social network. Socio-demographic, socioeconomic status and physical health variables were included as covariates. Results Household indebtedness, in form of being indebted and increased amount of debts, was associated with greater depressive symptoms in the Chinese elderly. The association of indebtedness and depressive symptoms may be driven by consumption and emergency debts. The moderating roles of social network and anticipation of support in the association of household indebtedness and depressive symptoms were found. Among those with household debts, older adults with larger size of social network and/or higher anticipation of being supported in the future reported with less symptoms of depressed. Limitations Due to a lack of information on the duration and debtor of household debt, we were not able to present a precise estimate for the exact impact of household indebtedness on mental health of elderly. Conclusion Familial financial strain was associated with aging mental well-being, increased social networks and social protections benefit aging health.

BACKGROUND AND OBJECTIVES Social networks are a means for disseminating scientific information. Alternative metrics assessing the impact of scientific publications on social networks have been created. Our study aims to assess the correlation between the activity of internal medicine journals on social networks and traditional metrics based on citations. METHODS Internal medicine journals were identified in the SCImago-Scopus database and information on traditional impact metrics was extracted. In addition, alternative metrics of activity were determined for Facebook, Twitter, YouTube, and Instagram. The correlation was assessed through Spearman's correlation coefficient. RESULTS Of 134 Internal Medicine journals, 17 had a presence on the social networks evaluated. The SJR index was higher in journals with a presence on social networks vs. those without (59 vs. 18, p

INTRODUCTION: Stress from negative life events may be an important risk factor for chronic cardiometabolic conditions, which are increasingly prevalent among young adults. Support from personal networks is known to buffer stress from negative life events. Yet, evidence for these relationships among both young and older adults remains unclear. METHODS: Longitudinal data came from the University of California, Berkeley Social Networks study (2015–2018), which followed young (aged 21–30 years) and late middle age adults (aged 50–70 years) over 4 years. Weighted hybrid fixed and random effects models (completed in 2020) were used to examine causal relationships among 4 negative life events, distinct forms of network support (e.g., social companionship, emergency help), and self-reported chronic cardiometabolic disease outcomes (i.e., hypertension, diabetes, or a heart condition). RESULTS: Among young adults, both the death of a close tie (Average Marginal Effect=0.10, p

Social behaviour requires the brain to efficiently integrate multiple social processes, but it is not clear what neural substrates underlie general social behaviour. While psychosis patients and individuals with subclinical symptoms are characterized by social dysfunction, the neural mechanisms underlying social dysfunctions in schizophrenia spectrum disorders remains unclear. We first constructed a general social brain network (SBN) using resting-state functional connectivity (FC) with regions of interest based on the automatic meta-analysis results from NeuroSynth. We then examined the general SBN and its relationship with social network (SN) characteristics in 30 individuals with schizophrenia (SCZ) and 33 individuals with social anhedonia (SA). We found that patients with SCZ exhibited deficits in their SN, while SA individuals did not. SCZ patients showed decreased segregation and functional connectivity in their SBN, while SA individuals showed a reversed pattern with increased segregation and functional connectivity of their SBN. Sparse canonical correlation analysis showed that both SCZ patients and SA individuals exhibited reduced correlation between SBN and SN characteristics compared with their corresponding healthy control groups. These preliminary findings suggest that both SCZ and SA participants exhibit abnormality in segregation and functional connectivity within the general SBN and reduced correlation with SN characteristics. These findings could guide the development of non-pharmacological interventions for social dysfunction in SCZ spectrum disorders.

Background Military nurse scientists are embedded in service-affiliated branches (Army, Navy, Air Force) with different missions, but with the singular purpose of generating and disseminating research impacting the health and well-being of DoD beneficiaries. Purpose This project examines collaboration among TriService Nursing Research Program (TSNRP) members, seeking opportunities to strengthen, diversify, and expand research collaboration. Method Social network analysis (SNA) is the empirical inquiry of relations among social actors at different levels of analysis. An electronic SNA assessment and total enumerative sampling were used to explore current collaborations among PhD-prepared military nurse scientists (N = 136). Findings The TSNRP collaboration network has a complex service-driven structure with high status actors whose advice, knowledge, or skills are sought by others, and who function as connectors or bridges across service branches. Discussion For military scientists, SNA is instrumental in identifying influential individuals, visualizing opportunities for intraservice mentoring, designing responsive policy, and directing career opportunities for novice scientists.

Scientists at all career stages can benefit from building diverse mentoring networks that transcend boundaries and promote inclusion. In this piece, we define mentoring networks, describe examples of how mentoring networks can reinforce scientific identity, and help minority scientists overcome unique challenges to achieve their goals in cancer research.

The purpose of this study was to describe older adults’ social network and support during a physical activity intervention and its association with physical activity. Mixed methods were used for this secondary analysis of existing data from a physical activity intervention. Seventy-three participants who completed a session by telephone on using support comprised the sample. Participants reported on average approximately eight individuals in their social network. Half reported support for physical activity from a spouse/partner, adult child, or friend. Those who perceived support for self-reported physical activity tended to have greater improvements on average from baseline for mean daily minutes of physical activity than those with no perceived support. Four-fifths developed a plan for a spouse/partner, friend, adult child, or sibling to provide physical activity support. Participants reported that the session was helpful and increased their confidence in using support; over one-quarter intended to use support after the intervention ended.

INTRODUCTION: Previous studies have demonstrated cross-sectional associations between social media use and depression, but their temporal and directional associations have not been reported. METHODS: In 2018, participants aged 18–30 years were recruited in proportion to U.S. Census characteristics, including age, sex, race, education, household income, and geographic region. Participants self-reported social media use on the basis of a list of the top 10 social media networks, which represent >95% of social media use. Depression was assessed using the 9-Item Patient Health Questionnaire. A total of 9 relevant sociodemographic covariates were assessed. All measures were assessed at both baseline and 6-month follow-up. RESULTS: Among 990 participants who were not depressed at baseline, 95 (9.6%) developed depression by follow-up. In multivariable analyses conducted in 2020 that controlled for all covariates and included survey weights, there was a significant linear association (p

Objective: To investigate the convergence of individual findings relating to psychological distress, alcohol use and social network (SN) to identify their associated clusters within Australian mineworkers. Methods: This study used cross‐sectional survey data from 3,056 participants across 12 Australian mines. Latent class analysis used the scores of Kessler Psychological Distress Scale, Alcohol Use Disorders Identification Test (AUDIT) and Social Network Index. Results: Class 1 (moderate to very high psychological distress, low SN score and low to moderate AUDIT) included 39% (n=1,178) participants and class 2 (low to moderate psychological distress and AUDIT and very high SN) composed of 61% (n=1,873) participants. Class 1 was associated with younger age (OR=0.65, 95%CI=0.53‐0.81), being a current smoker (OR=1.45, 95%CI=1.18‐1.79), and reporting a history of anxiety (OR=3.00, 95%CI=2.23‐4.05) and/or depression (OR=2.18, 95%CI=1.65‐2.90). Conclusions: These findings highlight the challenges the mining sector faces regarding the welfare of its employees. Implications for public health: Modifiable work factors associated with lower social networks and higher psychological distress need addressing at an individual and industry level through targeted and specifically tailored multi‐component interventions.

Objectives The Japanese prime minister declared a state of emergency on April 7 2020 to combat the outbreak of coronavirus disease 2019 (COVID-19). This declaration was unique in the sense that it was essentially driven by the voluntary restraint of the residents. We examined the change of the infection route by investigating contact experiences with COVID-19–positive cases. Study design This study is a population-level questionnaire-based study using a social networking service (SNS). Methods To assess the impact of the declaration, this study used population-level questionnaire data collected from an SNS with 121,375 respondents (between March 27 and May 5) to assess the change in transmission routes over the study period, which was measured by investigating the association between COVID-19–related symptoms and (self-reported) contact with COVID-19–infected individuals. Results The results of this study show that the declaration prevented infections in the workplace, but increased domestic infections as people stayed at home. However, after April 24, workplace infections started to increase again, driven by the increase in community-acquired infections. Conclusions While careful interpretation is necessary because our data are self-reported from voluntary SNS users, these findings indicate the impact of the declaration on the change in transmission routes of COVID-19 over time in Japan., Highlights • After a weak lockdown, the transmission route of coronavirus disease 2019 (COVID-19)–related symptoms changed. • COVID-19 monitoring responses from more than 120,000 social networking service users in Japan were used for analysis. • The emergency declaration prevented infections in the workplace and increased domestic infections. • Even lockdown with limited enforcement may prevent the spread of infection.

Introduction Community detection, the process of identifying subgroups of highly connected individuals within a network, is an aspect of social network analysis that is relevant but potentially underutilized in prevention research. Guidance on using community detection methods stresses aligning methods with specific research questions but lacks clear operationalization. The Question Alignment approach was developed to help address this gap and promote the high-quality use of community detection methods. Methods A total of 6 community detection methods are discussed: Walktrap, Edge-Betweenness, Infomap, Louvain, Label Propagation, and Spinglass. The Question Alignment approach is described and demonstrated using real-world data collected in 2013. This hypothetical case study was conducted in 2019 and focused on targeting a hand hygiene intervention to high-risk communities to prevent influenza transmission. Results Community detection using the Walktrap method best fit the hypothetical case study. The communities derived using the Walktrap method were quite different from communities derived through the other 5 methods in both the number of communities and individuals within communities. There was evidence to support that the Question Alignment approach can help researchers produce more useful community detection results. Compared to other methods of selecting high-risk groups, the Walktrap produced the most communities that met the hypothetical intervention requirements. Conclusions As prevention research incorporating social networks increases, researchers can use the Question Alignment approach to produce more theoretically meaningful results and potentially more useful results for practice. Future research should focus on assessing whether the Question Alignment approach translates into improved intervention results.

Digital health technologies improve outcomes within many health care fields. They include telemedicine and telehealth, remote patient monitoring, mobile health applications, data analytics, and social networking. Patients, providers, and insurers benefit from digital health, with time and cost savings as well as access to aggregate data, used to predict disease and outcomes and allowing tailored solutions. Some essentials of digital health implementation include champion providers, patients in need, technology, peer support system, understanding laws and regulations, seed funding, and sustainability. Successful programs can and will be established, leading health care into a more value-based future largely focused on direct-to-consumer care.

Summary Background Multisystemic therapy is a manualised treatment programme for young people aged 11–17 years who exhibit antisocial behaviour. To our knowledge, the Systemic Therapy for At Risk Teens (START) trial is the first large-scale randomised controlled trial of multisystemic therapy in the UK. Previous findings reported to 18 months after baseline (START-I study) did not indicate superiority of multisystemic therapy compared with management as usual. Here, we report outcomes of the trial to 60 months (START-II study). Methods In this pragmatic, randomised, controlled, superiority trial, young people (aged 11–17 years) with moderate-to-severe antisocial behaviour were recruited from social services, youth offending teams, schools, child and adolescent mental health services, and voluntary services across England, UK. Participants were eligible if they had at least three severity criteria indicating past difficulties across several settings and one of five general inclusion criteria for antisocial behaviour. Eligible families were randomly assigned (1:1), using stochastic minimisation and stratifying for treatment centre, sex, age at enrolment, and age at onset of antisocial behaviour, to management as usual or 3–5 months of multisystemic therapy followed by management as usual. Research assistants and investigators were masked to treatment allocation; the participants could not be masked. For this extension study, the primary outcome was the proportion of participants with offences with convictions in each group at 60 months after randomisation. This study is registered with ISRCTN, ISRCTN77132214, and is closed to accrual. Findings Between Feb 4, 2010, and Sept 1, 2012, 1076 young people and families were assessed for eligibility and 684 were randomly assigned to management as usual (n=342) or multisystemic therapy (n=342). By 60 months' of follow-up, 188 (55%) of 342 people in the multisystemic therapy group had at least one offence with a criminal conviction, compared with 180 (53%) of 341 in the management-as-usual group (odds ratio 1·13, 95% CI 0·82–1·56; p=0·44). Interpretation The results of the 5-year follow-up show no evidence of longer-term superiority for multisystemic therapy compared with management as usual. Funding National Institute for Health Research Health Services and Delivery Research programme.

Recent studies in adult humans have reported correlations between individual differences in people’s Social Network Index (SNI) and gray matter volume (GMV) across multiple regions of the brain. However, the cortical and subcortical loci identified are inconsistent across studies. These discrepancies might arise because different regions of interest were hypothesized and tested in different studies without controlling for multiple comparisons, and/or from insufficiently large sample sizes to fully protect against statistically unreliable findings. Here we took a data-driven approach in a pre-registered study to comprehensively investigate the relationship between SNI and GMV in every cortical and subcortical region, using three predictive modeling frameworks. We also included psychological predictors such as cognitive and emotional intelligence, personality, and mood. In a sample of healthy adults (n = 92), neither multivariate frameworks (e.g., ridge regression with cross-validation) nor univariate frameworks (e.g., univariate linear regression with cross-validation) showed a significant association between SNI and any GMV or psychological feature after multiple comparison corrections (all R-squared values ≤ 0.1). These results emphasize the importance of large sample sizes and hypothesis-driven studies to derive statistically reliable conclusions, and suggest that future meta-analyses will be needed to more accurately estimate the true effect sizes in this field.

Residential mobility has become a common experience for people in most parts of the world. As the number of people moving to different cities, states, and countries increases, it is critical to understand how this residential mobility affects one's thoughts, emotions, and actions. Psychological research on residential mobility over a decade is such an endeavor. We briefly summarize the earlier research in psychology that demonstrated the importance of residential mobility in understanding important psychological constructs such as self-concepts, social relationships, and well-being. We then review recent evidence in psychology and relevant fields that replicated and extended the earlier research. We discuss what is missing in the current literature and what additional research is needed in the future.

Background Infants too young to be fully vaccinated are vulnerable to potentially deadly influenza and pertussis infections. The cocooning strategy limits this risk by vaccinating those likely to interact with the infant and mother during this vulnerable time, such as close friends and family members. Distribution of accurate and accessible vaccine information through existing social networks could be an important tool in increasing vaccine confidence and coverage. Methods We surveyed 1095 pregnant women from diverse prenatal care practices in Georgia and Colorado. These women were surveyed through a mobile app to assess vaccine intentions, attitudes, beliefs, norms, and levels of trust, and then presented brief individually-tailored educational videos about maternal and infant vaccines and the cocooning strategy. They were then given the opportunity to refer up to six contacts to enroll in the app and receive similar vaccine education. Results Twenty-eight percent of these women referred at least one contact, with an average of 2.67 contacts per referring woman. Most referrals (93%) were partners, parents, siblings, relatives, or close friends. Attitudinal constructs significantly associated with increased likelihood of referring contacts included: intention to receive maternal influenza vaccine, perceived safety of maternal Tdap vaccine, perceived efficacy of maternal influenza vaccine, perceived susceptibility to and severity of influenza during pregnancy, and trust in vaccine information from the Centers for Disease Control and Prevention (CDC) and academic institutions. Uncertainty about infant vaccine intentions was associated with decreased likelihood of referring contacts. Conclusions Pregnant women who valued vaccination and trusted vaccine information from academic institutions were more likely to refer an educational app about vaccines than those who did not. Further research is needed to determine the potential impact of this strategy on vaccine coverage when implemented on a large scale. Trial registration The survey informing this article was part of a randomized controlled trial funded by the National Institutes of Health [clinicaltrials.gov registration number NCT02898688].

Purpose Although social support has been shown to be associated with survival among persons with cardiovascular disease, little research has focused on whether social support, measured before the onset of heart failure, can enhance survival after diagnosis. The objective of this study was to assess the association between prediagnosis social support and postdiagnosis survival among older adults with heart failure. Methods We obtained the data from the Cardiovascular Health Study, which included noninstitutionalized adults aged 65 years or older from four sites in the United States with primary enrollment in 1989–1990. We used two measures of social support, the Lubben Social Network Scale and the Interpersonal Support Evaluation List. The analytic data set included 529 participants with a social support measure within two years before diagnosis of heart failure. Results After adjustment for demographic covariates, cardiovascular risk factors, and general health status, mortality rates were lower among participants in the highest tertile of social network scores (HR 0.74, 95% CI: 0.59, 0.93) and the middle tertile (HR 0.73 [0.58, 0.90]), compared with the lowest tertile. Results with interpersonal support were null. Conclusions These findings suggest that prediagnosis structural social support may modestly buffer heart failure patients from mortality.

Background : Sedentary behavior (SB) may be a risk factor for depression in middle- and old age adults. The aim of this study was to examine cross-sectional and longitudinal relationships between SB and depression in a large national sample of Irish people aged 50 and older taking into account a wide range of previously identified influential factors. Methods : Data from the Irish Longitudinal Study on Ageing survey were analyzed (wave 1: 2009–2011, wave 2: 2012–2013). Depression was assessed with the Center for Epidemiologic Studies Depression scale. Total weekday SB and control variables were self-reported. Multivariable logistic regression and mediation analysis were conducted to assess the associations. Results : The final sample consisted of 6903 individuals aged ≥50 years (63.6 ± 9.2years; 52.1% female). After full adjustment for age, gender, social class, current smoking, physical activity, mobility, pain, cognition, chronic physical conditions, disability, anxiety, loneliness, and social network, the association between SB and depression was not statistically significant (OR=1.06; 95%CI=0.60–1.89). Mediation analysis showed that the association is explained by social network (mediated percentage 23.1%), physical activity (20.3%), loneliness (13.2%), chronic physical conditions (11.1%), and disability (7.9%). Cross-sectional analysis showed that SB is significantly associated with depression even after full adjustment. Limitations : SB was self-reported. Conclusions : Factors closely linked with SB such as social isolation, loneliness, physical inactivity, chronic physical conditions, and disability may play a major role in depression among middle-aged and older people. Lifestyle interventions focusing on reductions in depression in this population need to consider these factors.

As the number of refugees continues to increase globally, so does the number of older adults forced to migrate from their home region to Western countries. Many of these older refugees lose their social networks and support to the events leading to forced migration and may be unable to recreate them once resettled. We used Arksey and O'Malley's (2005) framework to explore how forced migration has diminished the social networks and support of older refugees in Western countries and its impact on their emotional well-being. Eight databases were searched for the review; abstracts were reviewed using Rayyan QCRi(c) before the full-text review. A total of 25 studies were included in the final analysis, and findings revealed that forced migration reduced the quantity of social networks and the quality of social support older refugees received. The reduced social network and support led to social isolation, increased migration-related grief, and mental health challenges. Advances in digital technology are not yet capable of filling the support gap. With this, we hope to inform future research on the social support needs of older refugees and raise awareness of the need for humanitarian support intervention to cushion the impact of the migration-induced loss of social networks and support.

Our objectives were (i) to systematically review how SNA is used in studies investigating adolescent health behaviours (i.e., the purpose of using SNA, methods used for network data collection and analysis), and (ii) to develop methodological guidelines to help researchers use SNA in studies on adolescent health behaviours.Five databases were searched using keywords related to "social network analysis" and "adolescents". We extracted data from included articles pertaining to the choice of methods for network data collection and analysis. We used these data to develop a 5-step decision tree to help researchers make methodological decisions most appropriate to their research objectives.A total of 201 articles were included. Most investigated tobacco (50%) or alcohol use (48%). SNA was used most often to examine processes related to peer selection or influence (37%) and/or to examine the effect of sociometric position on health behaviours (34%). 181 studies (90%) used a sociocentric approach for SNA, 16 studies (8%) used an egocentric approach, and 4 studies (2%) used both. We identified five decision-making steps in SNA including the choice of: (i) network boundary, (ii) SNA approach, (iii) methods for name generators, (iv) methods for name interpreters, and (iv) SNA indicators.This study provides insights and guidance in a 5-step decision tree on practical and methodological considerations in using SNA to explore adolescent health behaviours.

Patient narratives on social networks contain large amounts of objective information, such as the descriptions of examinations and interventions. Sentiment analysis (SA) models are mostly used to evaluate the conveyed sentiments by patients in these narratives to assess positive or negative clinical outcomes or to judge the impact of a drug or a medical condition. To date, many state-of-the-art SA models often result in false assessment coverage due to the natural medical entities recognition deficiency and ambiguity problem. In this work, we propose a semisupervised-based neural sense disambiguation approach that helps to substantially define ambiguities, their levels, and the relational mappings between biomedical targets and dependencies for accurate aspect-based sentiment prediction. Three main modules are proposed: (1) generate a sentiment value based on extracted concepts and their synsets, (2) encode the representations of the contextual senses and sentiment inputs, and (3) estimate an aspect-based sentiment weight based on the context-dependency sentiment units vs. the biomedical sense. Both intrinsic and extrinsic evaluation proved how the proposed method have succeeded in pruning contextual sense feature generation and showed a strong agreement for biomedical data property parameterization and ambiguity type extraction. Thus, the model offers a significant rate of discrimination of biomedical natural concept senses by critically analysing constraints from conjunctions of positive or negative contextual semantics. A total of 21% of the vocabulary is drug names, 11% is a multiword drug reaction expressions, 7% is disease symptoms, and 5% is disease-related concepts such as symptoms and related therapy terms. Furthermore, the experiments on a multisource data from Twitter and health-related forums have overshadowed sentiment assessment and achieved an accuracy of 0.91 regarding concepts-based biomedical aspects. These results provide fresh insights into how to investigate biomedical knowledge, e.g., Medical Subject Headings (MeSH) and PubMed, to clarify the correspondence of various biomedical descriptive entities, definitions, and data properties from shared medication-related content.

Recent evidence indicates use of geosocial networking apps is associated with body image-related issues among gay, bisexual, and other men who have sex with men. The current study aims to elaborate upon these findings by investigating how Grindr, the most widely-used dating app among this population, impacts users' body image and body satisfaction. Using an exploratory, qualitative study design, semi-structured interviews were conducted with 13 current and previous Grindr users and analyzed thematically. Our findings suggest Grindr affects users' body image through three primary mechanisms: weight stigma, sexual objectification, and social comparison. In each case, normative user attitudes and behaviours interact with the app's constitutional elements to affect bodily perceptions in a way that differs in form or intensity from social influence via offline exchanges. These interactions are often enabled by features shared with traditional social networking sites, like asynchronous, text-based communication and technology-assisted appearance augmentation, but certain features unique to Grindr may also play an important role. Moreover, participants identified several protective factors and coping strategies which suggest the relationship between Grindr and body image is dependent on a number of complex interactions between technology, user, and environment. Limitations and suggestions for future research are also discussed.

CONTEXT: Little attention has been given to social environmental factors associated with advance care planning (ACP) among African Americans or persons living with advanced Human Immunodeficiency Virus (PLHIVs). OBJECTIVES: The present study aimed to identify support network factors that affect the likelihood of naming a decision-maker and of talking to family/friends and doctors about ACP among vulnerable PLHIVs. METHODS: PLHIV were recruited from a large urban HIV clinic. A social support network inventory was used to calculate numbers of persons available for various types of support. Characteristics of network members were also collected. Multivariable logistic regression models were fit to examine associations between social network factors and ACP discussion, adjusting for age, sex, education and total number of network members. RESULTS: The sample (N=370) was mostly African American (95%), male (56%) and 48% had less than a high school education. Almost half the sample (48%) had talked to their family/friends or doctor about ACP and 34% had named a medical decision-maker. Adjusted analysis revealed that talking about ACP with family/friends was associated with female sex and a larger, closer support network who provided health information and physical assistance. Talking to doctors about ACP was associated with larger support networks who provided physical assistance but lower numbers from whom emotional support was received. Naming a decision-maker was associated with greater numbers of network members who provided emotional support, health information, and medication adherence reminders. CONCLUSION: The findings revealed aspects of family/ support network structures and caregiving function associated with ACP in a population with often vital yet vulnerable networks.

Background Interaction within mothers’ social networks can theoretically diffuse messages from interventions and campaigns into norms and practices for infant and young child feeding (IYCF). Objectives We hypothesized that mothers’ social networks, diffusion of information, and social norms differed in intensive [intensive interpersonal counseling (IPC), community mobilization (CM), and mass media (MM)] compared with nonintensive (standard IPC and less-intensive CM and MM) intervention areas, were associated with IYCF practices, and partly explained practice improvement. Methods We conducted household surveys at endline in 2014 and follow-up in 2016 (n = ∼2000 each round). We used multiple regression to test differences and changes in networks, diffusion, and norms within intervention areas. We analyzed paths from intervention exposure to IYCF practices through networks, diffusion, and norms. Results Mothers’ networks were larger in intensive than in nonintensive areas in 2014 and increased in both areas over time [25–38 percentage points (pp)]. The prevalence of receipt of IYCF information was high, with no changes over time in intensive areas but an increase in nonintensive areas (8–16 pp). In both areas, more family members and health workers provided IYCF information over time. Sharing of information increased 17–23 pp in intensive and 11–41 pp in nonintensive areas over time. Perceived descriptive norms improved 8–16 pp in intensive and 17–28 pp in nonintensive areas. Perceived injunctive norms were high in both areas. Breastfeeding practices were associated with networks, diffusion, and norms (OR: 1.6–4.4 times larger comparing highest with lowest quartile). Minimum dietary diversity was associated with larger networks and diffusion (OR: 1.5–2.2) but not with social norms. Indirect paths from intervention exposure to practices explained 34–78% of total effects. Conclusions Diffusion of IYCF information through social networks, reinforced by positive social norms for messages promoted over time, will contribute to positive changes in IYCF practices that may be achieved and sustained through large-scale social and behavior change interventions. This trial was registered at clinicaltrials.gov as NCT0274084.

Background In the biopsychosocial formulation of functional neurological (conversion) disorder (FND), little is known about relationships between social behavior and brain anatomy. We hypothesized that social behavior would relate to brain areas implicated in affiliative behaviors and that social network size would correlate with symptom severity and predisposing vulnerabilities in FND. Methods This neuroimaging pilot probed how social network size, as measured by the Social Network Index, related to structural brain profiles in 23 patients with motor FND (15 woman and 8 men). FreeSurfer cortical thickness and subcortical volumetric analyses were performed correcting for multiple comparisons. Stratified analyses compared FND patients with a low social network size to matched healthy controls. Secondary exploratory analyses in an expanded sample of 38 FND patients investigated relationships between social network size, risk factors and patient-reported symptom severity. Results Adjusting for age and gender, neuroimaging analyses showed that social network size positively correlated with left nucleus accumbens and hippocampal volumes in patients with FND; stratified analyses did not show any group-level differences. In individuals with FND, social network size correlated with health-related quality of life, graduating college, working full-time and a non-epileptic seizure diagnosis; social network size inversely related to lifetime trauma burden, post-traumatic stress disorder severity and age. Limitations Only patient-reported scales were used and social network size information was not collected for healthy subjects. Conclusions This neuroimaging pilot adds to the literature linking affiliation network brain areas to pro-social behaviors and enhances the biopsychosocial conceptualization of FND.

Animals, from flies to humans, interact with each other, forming complex relationships and structured social interaction networks. These networks describe patterns of interactions that occur within a group. Social network analysis (SNA) is the statistical analysis of nodes, which represent individuals within a network who are connected by social ties, often called edges, that represent interactions between individuals. Here, we review recent studies on social interaction networks in insects with an emphasis on flies. In flies and other insects, SNA has revealed the contribution of group structure to disease transmission, feeding strategy, fighting, mating, and oviposition. The literature shows that SNAs are useful to understand mechanisms underlying group behavior as well as the evolution of social structure.

In this paper we develop simple and fast multicore parallel algorithms for counting the number of k-cliques in large undirected graphs, for any small constant k ≥ 4. Clique counting is an important problem in a variety of network analytics applications. Differently from existing solutions, which mainly target distributed memory settings (e.g., MapReduce), our algorithms work on off-the-shelf shared-memory multicore platforms. We assess the effectiveness of our approach through an extensive experimental analysis on a variety of real-world graphs, considering different clique sizes and scalability on different numbers of cores. The experimental results show that our parallel algorithms largely outperform the running times of highly optimized sequential solutions and gracefully scale to non-trivial values of k even on medium/large graphs. For instance, computing hundreds of billions of cliques for rather demanding Web graphs and social networks requires about 15 min on a 32-core machine. As a by-product of our experimental analysis, we also compute the exact number of k-cliques with at most 20 nodes in many real-world networks from the SNAP repository.

Social media use is increasing in the United States. Because psychiatrists and physicians are becoming more active online, Twitter is emerging as a leading platform for professional development. Social media can enhance networking, serve as a tool for mentoring trainees and colleagues, introduce journal articles to new readers, and allow psychiatrists and physicians to advocate for health care issues. Psychiatrists and physicians should observe ethical standards for digital citizenship on Twitter and other social media platforms.

Objectives Coordination of multidisciplinary care is critical to address the complex needs of people with neurological disorders; however, quality improvement and research tools to measure coordination of neurological care are not well-developed. This study explored and compared the value of social network analysis (SNA) and relational coordination (RC) in measuring coordination of care in a neurology setting. The Department of Veterans Affairs Healthcare System (VA) established an Epilepsy Centers of Excellence (ECOE) hub and spoke model of care, which provides a setting to measure coordination of care across networks of providers. Methods In a parallel mixed methods approach, we compared coordination of care of VA providers who formally engage the ECOE system to VA providers outside the ECOE system using SNA and RC. Coordination of care scores were compiled from provider teams across 66 VA facilities, and key informant interviews of 80 epilepsy care team members were conducted concurrently to describe the quality of epilepsy care coordinating in the VA healthcare system. Results On average, members of healthcare teams affiliated with the ECOE program rated quality of communication and respect higher than non-ECOE physicians. Connectivity between neurologist and primary care providers as well as between neurologists and mental health providers were higher within ECOE hub facilities compared to spoke referring facilities. Key informant interviews reported the important role of formal and informal programming, social support and social capital, and social influence on epilepsy care networks. Conclusion For quality improvement and research purposes, SNA and RC can be used to measure coordination of neurological care; RC provides a detailed assessment of the quality of communication within and across healthcare teams but is difficult to administer and analyze; SNA provides large scale coordination of care maps and metrics to compare across large healthcare systems. The two measures provide complimentary coordination of care data at a local as well as population level. Interviews describe the mechanisms of developing and sustaining health professional networks that are not captured in either SNA or RC measures.

Increasing evidence suggests that systemic inflammation adversely affects social experiences and behaviors of older adults by changing the functional state of the brain. In this study, we investigated the relationships among systemic inflammation, functional network connectivity (FNC) of the whole brain, and social-network size using complete social-network data of older adults residing in a Korean village. Sixty-one participants were recruited from the Korean Social Life, Health, and Aging Project (KSHAP). Participants underwent a resting-state functional magnetic resonance imaging scan. High sensitivity C-reactive protein (hs-CRP) levels were measured as an inflammation marker. In-degree and out-degree network sizes were calculated based on the total number of intimate social relationships per participant. We demonstrated that hs-CRP levels were associated with decreased frontotemporal FNC. Stronger frontotemporal FNC was significantly correlated with a larger out-degree network size, suggesting that impaired frontotemporal communication in older adults decreases perceived social connectedness with other people. An exploratory mediation analysis supported the observation that increased systemic inflammation contributes to reduced out-degree social-network size among older adults by changing frontotemporal FNC. The present findings provide meaningful insight into the complex relationship between systemic inflammation and social quality of life.

Objective Studies have documented the salience of social networks for a range of health outcomes and behaviors among adolescents, but sleep has received far less attention. We examined whether adolescents' network positions relative to cohesive friendship groups and popularity among peers are associated with their sleep behaviors and whether the associations differ by gender. Methods We analyzed friendship data on 2,550 adolescents from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to identify participants' network group positions (member, isolate, liaison) and popularity (number of friendship nominations received). Respondents provided self-reports of sleep duration, insomnia symptoms, and sleep insufficiency. We evaluated the relationships between respondents' group positions and popularity with their sleep behaviors using linear and Poisson regression, adjusting for socio-demographics, self-rated health, smoking and drinking status, integration in non-peer contexts (school, family, and religion), and friends' sleep. Results Results from the total sample show that liaisons report increased risk of sleep insufficiency compared to group members. Higher popularity status is associated with shorter sleep duration and greater sleep insufficiency. Stratifying by gender, popular girls report shorter sleep duration (β = -2.68 min for each additional friendship nomination; 95% CI [-4.75, -.61]) and greater sleep insufficiency (RR = 1.04; 95% CI [1.01, 1.07]) compared to less popular girls. Girls who are liaisons experience more sleep insufficiency (RR = 1.28; 95% CI [1.07, 1.53]) compared to group member girls. In contrast, isolated boys reported more insomnia symptoms (RR = 2.19; 95% CI [1.20, 3.98]) compared to group members. Conclusion Popularity may have hidden costs for girls' sleep, while social isolation seems to be detrimental for boys' sleep. These results suggest that a social network perspective is valuable for studying sleep health and might inform targeted interventions to improve adolescents' sleep outcomes.

Friends tend to be more similar than non-friends (i.e., exhibit homophily) in body image concerns and disordered eating behaviors. These similarities may be accounted for by similarities in eating disorder risk factors and correlates. The current study sought to replicate findings of homophily for eating pathology using social network analysis and to test if similarity in eating pathology is present above and beyond homophily for eating disorder risk factors and correlates. College students (n = 89) majoring in nutrition completed a social network assessment and measures of eating pathology (i.e., body dissatisfaction, binge eating, restricting, excessive exercise), negative affect, and perfectionism. Homophily for eating pathology, negative affect, and perfectionism were tested as predictors of friendship ties using exponential random graph modeling, adjusting for gender, year in school, and body mass index. Results did not support homophily for eating pathology. However, restricting was associated with a lower likelihood of friendship ties. Homophily was present for perfectionism, but not for negative affect. Results suggest that eating pathology may influence the propensity to form friendships and account for previous findings of homophily in the literature. Homophily for perfectionism may have also driven previous findings for homophily. More longitudinal work using social network analysis is needed to understand the role that personality plays in peer influences on eating pathology.

Improved access to housing and recovery support is a low-cost, high-potential opportunity to help people recovering from alcohol and substance use sustain their recoveries. Oxford House (OH) recovery homes represent a recovery-favorable social environment for at least some people, but it is still unclear which resident characteristics and relational dynamics affect the social integration of residents. In the current study, OH residents in three geographic locations completed a social network instrument and self-rated their quality of life (QOL). The instruments were administered to the current (per wave) residents of 42 OHs at three time points over a period of a year. Findings indicated that those with a higher QOL were more likely to form friendships with those with a lower QOL than with their similar QOL peers, and vice versa. This finding would not have been predicted based on relationship mechanisms typical of broader social contexts, where homophily (similarity-based assortativity) is common. The self-governance model that characterizes OH residences, in which success among residents is necessarily viewed as mutually dependent and therefore mutually beneficial, seems a likely explanation for our result. Specifically, and aligned with current knowledge about what works in peer oriented recovery, our results suggest the governance mechanisms of OH favor relationships between those more stable in their recovery and those who are at a higher risk of dropout or relapse. This study reveals a potential research avenue examining an important ingredient for the effectiveness of OH.

Background: Network-based interventions against epidemic spread are most powerful when the full network structure is known. However, in practice, resource constraints require decisions to be made based on partial network information. We investigated how the accuracy of network data available at individual and village levels affected network-based vaccination effectiveness. Methods: We simulated a Susceptible-Infected-Recovered process on static empirical social networks from 75 rural Indian villages. First, we used regression analysis to predict the percentage of individuals ever infected (cumulative incidence) based on village-level network properties for simulated datasets from 10 representative villages. Second, we simulated vaccinating 10% of each of the 75 empirical village networks at baseline, selecting vaccinees through one of five network-based approaches: random individuals (Random); random contacts of random individuals (Nomination); random high-degree individuals (High Degree); highest degree individuals (Highest Degree); or most central individuals (Central). The first three approaches require only sample data; the latter two require full network data. We also simulated imposing a limit on how many contacts an individual can nominate (Fixed Choice Design, FCD), which reduces the data collection burden but generates only partially observed networks. Results: In regression analysis, we found mean and standard deviation of the degree distribution to strongly predict cumulative incidence. In simulations, the Nomination method reduced cumulative incidence by one-sixth compared to Random vaccination; full network methods reduced infection by two-thirds. The High Degree approach had intermediate effectiveness. Somewhat surprisingly, FCD truncating individuals’ degrees at three was as effective as using complete networks.Conclusions:Using even partial network information to prioritize vaccines at either the village or individual level, i.e. determine the optimal order of communities or individuals within each village, substantially improved epidemic outcomes. Such approaches may be feasible and effective in outbreak settings, and full ascertainment of network structure may not be required. Keywords: Vaccination, Sociocentric networks, Agent-based models

This paper examined the association between friendship and academic networks and how the connections these networks have with academic performance and school misconduct differ when comparing three types of classrooms where students were grouped based on their academic ability (i.e., high-, low-, and mixed-ability). The sample was composed of 528 seventh to ninth graders (Mage = 15; 64.1% girls) from 12 classrooms (four in each category of ability grouping) across two waves in five schools in Chile. The effects of academic performance and school misconduct on receiving academic and friendship nominations were examined, as well as the interplay between academic and friendship relationships. Furthermore, the extent to which similarity in adolescents' academic performance and school misconduct contributed to the formation and maintenance of academic and friendship relationships was examined. Sex, socioeconomic status, and structural network features were also taken into account. Longitudinal social network analyses (RSiena) indicated that (1) in high-ability classrooms students chose high-achieving peers as academic partners; (2) in high-ability classrooms students avoided deviant peers (i.e., those high in school misconduct) as academic partners; and (3) academic relationships led to friendships, and vice versa, in both high- and low-ability classrooms. Whereas the interplay of friendship and academic relationships was similar in high- and low-ability classrooms, the formation and maintenance of academic networks unfolded differently in these two types of classrooms.

Childhood adversities can impact negatively on psychological health across the lifespan. Many military veterans have a history of adverse childhood experiences, which when combined with deployment related traumas, can lead to high levels of psychopathology. Social networks can however be protective. The current study aimed to identify typologies of childhood adversity in U.S. military veterans (n = 3092) and explore relationships between the adversity typologies and PTSD, mood and anxiety disorders, utilising data from the National Epidemiological Survey on Alcohol and Related Conditions-III (NESARC-III). The mediating role of quality and quantity of social networks were examined. Latent class analysis identified four adversity classes; 1) baseline, 2) household dysfunction, 3) maltreatment, and 4) multi-adversity. Individuals in the adversity classes (2–4), especially those who experienced multi-adversity had higher rates of psychopathology. The quality of social networks played an important mediating role, while quantity of networks did not. Those who experienced adversity were less likely to have supportive social networks, therefore adversity had both a direct and indirect impact on psychopathology. The findings highlight the importance of developing and maintaining social networks following military life. Recommendations include interpersonal skills training and programmes which may help them engage back into the community and enhance relationships.

The uneven distribution of medical resources is a serious problem in developing countries. Those seeking timely treatment have difficulty choosing the right hospital. To found sustainable development with medical system, this paper establishes a model of the hospital confidence evaluation index by combining national evaluation and a third-party evaluation. The model is applied to a social network. Users from any region can use the model through APP in IoT, a hospital analysis index query, which selects the best hospital for diagnosis and treatment. The model can locate different personnel characteristics by modifying the control variables. Establishing a medical system with big data provides good model characteristics. Effective data analysis through large data users in the sample is established to provide the most effective hospital recommendation, which is a good solution to the selectivity problem. The contributions in this works are: (1) Models of initial trust and hospital evaluations are established by combining national and third-party assessments; (2) the initial trust evaluation model is modified and optimized by establishing control variables; (3) the trust evaluation mechanism of users in social networks is obtained through big data sampling and model analysis, and the balanced distribution of the medical staff is realized.