Online interventions and virtual day centres for young people who use drugs: potential for harm reduction?

BACKGROUND

The methodological part of the large-scale study on the psychosocial distress of young people in Slovenia focused on vulnerable young people who use drugs and explored the potential of online interventions in harm reduction programmes. We looked at the needs of young people who, at the time of the research, were attending a virtual Discord day centre hosted by the DrogArt NGO or were involved in the organisation's other programmes. We explored young people's knowledge of online interventions, their satisfaction with them and the opportunities they offer for harm reduction programmes.

METHODS

The study used a qualitative methodology with a combination of deductive and inductive coding, and relied on framework analysis, 18 young people who had used drugs or had stopped using participated in the study. The inclusion criterion was a maximum age of 25 years. In-depth interviews were conducted with the young people, which lasted on average between one and a half and two hours.

RESULTS

The study showed the potential of online interventions, specifically the virtual day centre, which provide a safe and relaxed space for young people in the sample to meet and talk, which is accessible and where they feel welcome. Online interventions have also enabled some of the sample to engage in the 'offline' support types offered within the organisation. The main advantages of online interventions are seen by young people as being more 'geographically' accessible and more available during the COVID-19 epidemic. Online support suits some people because they can leave sessions more quickly and it is more informal, while others prefer it because of specific problems or difficulties, such as social anxiety.

CONCLUSIONS

The results show the relatively high potential of online interventions in harm reduction programmes, as well as more broadly for young people with various psychosocial difficulties and who, for example, do not use drugs. These types of support allow quick contact with a professional or peer and facilitate contact with a support programme. Young people are still poorly informed about the support programmes available in Slovenia and would like more information. Thus, in addition to developing and upgrading the network of programmes, we need to focus on providing information to young people through channels that are close to them and can reach them.

Cross-modal representation of identity in the primate hippocampus

Faces and voices are the dominant social signals used to recognize individuals among primates. Yet, it is not known how these signals are integrated into a cross-modal representation of individual identity in the primate brain. We discovered that, although single neurons in the marmoset hippocampus exhibited selective responses when presented with the face or voice of a specific individual, a parallel mechanism for representing the cross-modal identities for multiple individuals was evident within single neurons and at the population level. Manifold projections likewise showed the separability of individuals as well as clustering for others' families, which suggests that multiple learned social categories are encoded as related dimensions of identity in the hippocampus. Neural representations of identity in the hippocampus are thus both modality independent and reflect the primate social network.

On fear of missing out, social networks use disorder tendencies and meaning in life

Much research has been conducted on the association between social networks use disorder tendencies (SNUD; i.e. problematic social media use) and well-being. In more detail, a meta-analysis and further research suggest an inverse association between higher SNUD tendencies and lower well-being. In existing studies on social media use and well-being, this association has often been investigated by asking participants about their life satisfaction and/or emotional well-being. A path that has only recently been used to shed further light on SNUD tendencies is the assessment of meaning in life. Against this background, the present study aimed to investigate both the search for and presence of meaning in life in the context of SNUD tendencies in 955 participants. To the best of our knowledge and beyond what has been mentioned, this study is the first to investigate the links between meaning in life variables and state/trait fear of missing out (FoMO), with FoMO being a critical variable known to be linked to the overuse of digital technologies. In a structural equation model, we observed that associations between FoMO and meaning in life variables was mediated by SNUD tendencies. Although the present study is of cross-cultural nature and cannot establish causality, it might be the case that proneness to FoMO might trigger SNUD tendencies and as a consequence, results in more search for meaning in life, while hindering presence of meaning in life.

Randomized Clinical Trial Visual Abstract Display and Social Media-Driven Website Traffic

In this study, the authors assessed whether publication of a visual abstract on social media was associated with reader engagement online.

Examining preconditions for integrated care: a comparative social network analysis of the structure and dynamics of strong relations in child service networks

BACKGROUND

To help ensure that children and families get the right support and services at the right time, strong and stable relationships between various child service organizations are vital. Moreover, strong and stable relationships and a key network position for gatekeepers are important preconditions for interprofessional collaboration, the timely and appropriate referral of clients, and improved health outcomes. Gatekeepers are organizations that have specific legal authorizations regarding client referral. However, it is largely unclear how strong relations in child service networks are structured, whether the gatekeepers have strong and stable relationships, and what the critical relations in the overall structure are. The aim of this study is to explore these preconditions for integrated care by examining the internal structure and dynamics of strong relations.

METHODS

A comparative case study approach and social network analysis of three inter-organizational networks consisting of 65 to 135 organizations within the Dutch child service system. Multiple network measures (number of active organizations, isolates, relations, average degree centrality, Lambda sets) were used to examine the strong relation structure and dynamics of the networks. Ucinet was used to analyze the data, with use of the statistical test: Quadratic Assignment Procedure. Visone was used to visualize the graphs of the networks.

RESULTS

This study shows that more than 80% of the organizations in the networks have strong relations. A striking finding is the extremely high number of strong relations that gatekeepers need to maintain. Moreover, the results show that the most important gatekeepers have key positions, and their strong relations are relatively stable. By contrast, considering the whole network, we also found a considerable measure of instability in strong relationships, which means that child service networks must cope with major internal dynamics.

CONCLUSIONS

Our study addressed crucial preconditions for integrated care. The extremely high number of strong relations that particularly gatekeepers need to build and maintain, in combination with the considerable instability of strong relations considering the whole network, is a serious point of concern that need to be managed, in order to enable child service networks to improve internal coordination and integration of service delivery.

Evaluating the Effects of Misinformation on Public Sentiments Surrounding Access to Abortion Through Social Media Sentiment Analytics

As social media use has grown in recent years, ease of access and rapid data collection through online social media has permitted researchers to measure and track sentiments related to emerging public health threats. Herein, we explore the possibilities of examining messaging shared via social media networks for sentiment classification as it relates to women's reproductive healthcare, especially access to abortion. In our previous works, our team has successfully employed various natural language processing (NLP) models for the analysis of social media shared sentiments. This study reports a work-in-progress on the similar use of fine-tuned NLPs (i.e., DistilRoBERTa) to collect/analyze the sentiments of socio-behavioral data shared via social networks to uncover a correlation between reproductive-related misinformation (i.e., access to abortion) and public sentiments/discourse direction.

Stingy bots can improve human welfare in experimental sharing networks

Machines powered by artificial intelligence increasingly permeate social networks with control over resources. However, machine allocation behavior might offer little benefit to human welfare over networks when it ignores the specific network mechanism of social exchange. Here, we perform an online experiment involving simple networks of humans (496 participants in 120 networks) playing a resource-sharing game to which we sometimes add artificial agents (bots). The experiment examines two opposite policies of machine allocation behavior: reciprocal bots, which share all resources reciprocally; and stingy bots, which share no resources at all. We also manipulate the bot's network position. We show that reciprocal bots make little changes in unequal resource distribution among people. On the other hand, stingy bots balance structural power and improve collective welfare in human groups when placed in a specific network position, although they bestow no wealth on people. Our findings highlight the need to incorporate the human nature of reciprocity and relational interdependence in designing machine behavior in sharing networks. Conscientious machines do not always work for human welfare, depending on the network structure where they interact.

Evaluation of Family and Community Social Network Characteristics Among High-Risk Family Members to Improve Cancer-Related Health Behaviors

OBJECTIVES

To evaluate the effects of social network characteristics of individuals with a family history of cancer on the use of cancer-related services (e.g., screening, genetic counseling/testing).

SAMPLE & SETTING

170 family members of individuals with the most common hereditary or familial cancers.

METHODS & VARIABLES

Data collection occurred between March and September 2021 using an online survey.

RESULTS

Having strong within-immediate family relationships and family members who underwent more screening procedures was associated with increased breast cancer screening, and having more family members with cancer was associated with colorectal cancer screening. Having a large family, having family members who underwent screening for more cancers, and having strong social cohesion among families were associated with an increased rate of genetic testing.

IMPLICATIONS FOR NURSING

Nurses working with families affected by cancer should focus on strategies to strengthen relationships among family members to improve knowledge of cancer screening and available genetic services.

Acorn woodpecker movements and social networks change with wildfire smoke

Climate change has contributed to increased wildfires1,2. Wildfire smoke exposes wildlife to hazards and mortality from particulate matter on a scale larger than the area impacted by fire3,4. Using automated radiotelemetry, we illustrate how smoky conditions are associated with changes in behavior of acorn woodpeckers (Melanerpes formicivorus), a flagship species of oak (Quercus spp.) savannas of western North America. On smoky days, birds spent more time at their home territory and reduced visitation to others, especially to distant territories. Associations between birds decreased, and individuals were less assorted by group in co-visitation networks, suggesting less inter-individual coordination on smoky days. We show that between 2016 and 2020, ∼14% of the acorn woodpecker population in the US experienced fire, potentially exposing on average 89.42% of the range to atmospheric smoke annually. These findings highlight how potential effects of smoke on animal behavior may be widespread and exacerbate negative impacts of increasingly common "megafires", even in fire-adapted ecosystems.

Implicit cognitions in problematic social network use

Implicit cognitions may be involved in the development and maintenance of specific Internet use disorders such as problematic social network use (PSNU). In more detail, implicit attitude, attentional biases, approach and avoidance tendencies as well as semantic memory associations are considered relevant in the context of PSNU. This viewpoint article summarizes the available literature on implicit cognitions in PSNU. We systematically reviewed articles of implicit cognitions in PSNU from PubMed, Scopus, Web of Science, and ProQuest databases based on a targeted search strategy and assessed using predefined inclusion and exclusion criteria. The present findings suggest that specific implicit cognitions are important in the context of PSNU and therefore show parallels to other addictive behaviors. However, the empirical evidence is limited to a few studies on this topic. Implicit cognitions in PSNU should be explored in more depth and in the context of other affective and cognitive mechanisms in future work.

Predictors of social networking service addiction

The surge in social network services (SNS) usage has ignited concerns about potential addictive behaviors stemming from excessive engagement. This research focuses on pinpointing the primary determinants of SNS addiction by introducing a theoretical framework centered on flow, perceived enjoyment, and habit. A sample of 282 SNS users from South Korea was surveyed, and the gathered data was assessed through partial least squares structural equation modeling (PLS-SEM). The evaluation revealed that positive affect closely relates to flow and perceived enjoyment, whereas negative affect amplifies flow but diminishes perceived enjoyment. Additionally, the research underscored that social influence significantly shapes habits and affects perceived enjoyment. Notably, flow demonstrated a strong connection to addiction, and perceived enjoyment influenced both flow and habit significantly. Habit was directly linked to addiction. These insights pave the way for more in-depth studies on SNS addiction patterns and offer a foundation for devising effective strategies to mitigate its adverse effects.

Social networks and the mental health among Chinese older adults: the mediating role of loneliness and moderating role of Internet use

Background

Although a large body of research suggests that social networks from family and friends are important factors in protecting the mental health of older adults, we know little about the mediating and moderating mechanisms behind this relationship. Using China as an example, this study aims to investigate a comprehensive model that includes social networks, loneliness, Internet use, and mental health outcomes in the older population.

Methods

We analyzed data from 7,648 Chinese older people over 60 using the 2018 CLASS survey. We studied how various social networks affect their mental health. Using SPSS's PROCESS macro, we first employed descriptive statistics to examine the characteristics of the participants and calculate the correlations of core variables. Then, we assessed whether loneliness mediated this relationship and tested the moderated mediation effect of Internet use. Our findings shed light on these complex dynamics.

Results

The statistics indicate a positive correlation between social networks and mental health. Furthermore, mediation models revealed that loneliness moderates the relationship between social networks and mental health. In addition, moderated mediation models revealed that Internet use played a distinct function in the family networks model compared to the friend networks model. Internet use moderates explicitly the effects of family networks on loneliness and friend networks on mental health.

Conclusion

The findings emphasize the importance of differentiating the types of social networks to understand their impact on older adults well-being, encouraging policymakers, medical professionals, and families to adopt more targeted approaches when devising policy interventions and medical strategies, especially for older individuals with insufficient social support. Additionally, we urge governments to recognize the varying types of social networks among older populations and harness the protective effects of Internet technology on their well-being within a digital society.

Community organization perspectives on COVID-19 vaccine hesitancy and how they increased COVID-19 vaccine confidence: a Canadian Immunization Research Network, social sciences and humanities network study

Background

COVID-19 vaccines play a critical role in reducing the morbidity and mortality associated with SARS-CoV-2 infection and despite vaccine availability, disparities in COVID-19 vaccine uptake among Canadian subgroups exist. Community organizations are uniquely situated to relay important vaccine messaging around all vaccines, understand components of vaccine hesitancy, and facilitate vaccine uptake within the communities they serve. The objective of this research was to solicit community organizations perspectives specific to COVID-19 vaccines and explore strategies of increasing vaccine uptake within their communities.

Methods

A qualitative focus group study was held in the spring of 2021 with 40 community organizations from across the country. Discussions focused on COVID-19 vaccine communication and awareness within their communities, vaccine misinformation, and strategies to increase vaccine acceptance and access. Data were analyzed utilizing thematic and inductive techniques.

Results

Vaccine hesitancy was identified among staff and clients. Vaccine confidence, complacency, convenience, and mistrust in government and authorities were identified as contributors to vaccine hesitancy. Community organizations utilized innovative and novel methods to encourage vaccine uptake and increase vaccine confidence. Leveraging established trusting relationships was key to successful messaging within communities.

Conclusion

Community organizations used innovative methods, built on established trust, to increase vaccine confidence within their communities and among their staff. Community agencies played an important role in COVID-19 vaccine uptake within subgroups of the Canadian population. Community organizations are key public health partners and play a critical role in increasing COVID-19 vaccine confidence.

The Integration of Value Assessment and Social Network Methods for Breast Health Navigation Among African Americans

OBJECTIVES

A major strategy to reduce the impact of breast cancer (BC) among African Americans (AA) is patient navigation, defined here as individualized assistance for reducing barriers to healthcare use. The primary focus of this study was to estimate the added value of incorporating breast health promotion by navigated participants and the subsequent BC screenings that network members may obtain.

METHODS

In this study, we compared the cost-effectiveness of navigation across 2 scenarios. First, we examine the effect of navigation on AA participants (scenario 1). Second, we examine the effect of navigation on AA participants and their networks (scenario 2). We leverage data from multiple studies in South Chicago. Our primary outcome (BC screening) is intermediate, given limited available quantitative data on the long-term benefits of BC screening for AA populations.

RESULTS

When considering participant effects alone (scenario 1), the incremental cost-effectiveness ratio was $3845 per additional screening mammogram. When including participant and network effects (scenario 2), the incremental cost-effectiveness ratio was $1098 per additional screening mammogram.

CONCLUSION

Our findings suggest that inclusion of network effects can contribute to a more precise, comprehensive assessment of interventions for underserved communities.

Algorithm-mediated social learning in online social networks

Human social learning is increasingly occurring on online social platforms, such as Twitter, Facebook, and TikTok. On these platforms, algorithms exploit existing social-learning biases (i.e., towards prestigious, ingroup, moral, and emotional information, or 'PRIME' information) to sustain users' attention and maximize engagement. Here, we synthesize emerging insights into 'algorithm-mediated social learning' and propose a framework that examines its consequences in terms of functional misalignment. We suggest that, when social-learning biases are exploited by algorithms, PRIME information becomes amplified via human-algorithm interactions in the digital social environment in ways that cause social misperceptions and conflict, and spread misinformation. We discuss solutions for reducing functional misalignment, including algorithms promoting bounded diversification and increasing transparency of algorithmic amplification.

Drop edges and adapt: A fairness enforcing fine-tuning for graph neural networks

The rise of graph representation learning as the primary solution for many different network science tasks led to a surge of interest in the fairness of this family of methods. Link prediction, in particular, has a substantial social impact. However, link prediction algorithms tend to increase the segregation in social networks by disfavouring the links between individuals in specific demographic groups. This paper proposes a novel way to enforce fairness on graph neural networks with a fine-tuning strategy. We Drop the unfair Edges and, simultaneously, we Adapt the model's parameters to those modifications, DEA in short. We introduce two covariance-based constraints designed explicitly for the link prediction task. We use these constraints to guide the optimization process responsible for learning the new 'fair' adjacency matrix. One novelty of DEA is that we can use a discrete yet learnable adjacency matrix in our fine-tuning. We demonstrate the effectiveness of our approach on five real-world datasets and show that we can improve both the accuracy and the fairness of the link prediction tasks. In addition, we present an in-depth ablation study demonstrating that our training algorithm for the adjacency matrix can be used to improve link prediction performances during training. Finally, we compute the relevance of each component of our framework to show that the combination of both the constraints and the training of the adjacency matrix leads to optimal performances.

Health Information Sharing via Social Network Sites (SNSs): Integrating Social Support and Socioemotional Selectivity Theory

Despite its prevalence, research on health information sharing via social network sites (SNSs) is mostly descriptive and often lacks a coherent theoretical framework. By integrating social support and socioemotional selectivity theory, the present study takes a uses and gratifications approach to examining what factors affected health information sharing via WeChat, the most widely used SNS in China. Results of an online survey (N = 519) show that emotional and informational support provisions both predicted health information sharing via WeChat. In addition, age moderated the effects of both support provision. While the relationship between emotional support provision and health information sharing was stronger among older adults, the effect of informational support provision was marginally significantly stronger among younger adults. These findings provide additional understanding of health information sharing via SNSs by revealing its emotional meaning and demonstrating different sharing motivations in different age groups, which offers implications on health information design, dissemination, and discussions in different groups.

On exploring node-feature and graph-structure diversities for node drop graph pooling

Graph Neural Networks (GNNs) have been successfully applied to graph-level tasks in various fields such as biology, social networks, computer vision, and natural language processing. For the graph-level representations learning of GNNs, graph pooling plays an essential role. Among many pooling techniques, node drop pooling has garnered significant attention and is considered as a leading approach. However, existing node drop pooling methods, which typically retain the top-k nodes based on their significance scores, often overlook the diversity inherent in node features and graph structures. This limitation leads to suboptimal graph-level representations. To overcome this, we introduce a groundbreaking plug-and-play score scheme, termed MID. MID comprises a Multidimensional score space and two key operations: flIpscore and Dropscore. The multidimensional score space depicts the significance of nodes by multiple criteria; the flipscore process promotes the preservation of distinct node features; the dropscore compels the model to take into account a range of graph structures rather than focusing on local structures. To evaluate the effectiveness of our proposed MID, we have conducted extensive experiments by integrating it with a broad range of recent node drop pooling methods, such as TopKPool, SAGPool, GSAPool, and ASAP. In particular, MID has proven to bring a significant average improvement of approximately 2.8% over the four aforementioned methods when tested on 17 real-world graph classification datasets. Code is available at https://github.com/whuchuang/mid.

Testing the Reciprocal Relationship Between Social Networks and Purpose in Life Among Older Adults: Application of a Random Intercept Cross-Lagged Panel Model

Objectives: The purpose of this study is to examine if there are longitudinal reciprocal effects between social network size and purpose in life among older adults. Methods: Using data from the National Health and Aging Trends Study, the sample included 1485 male and 2058 female adults 65 years and older. We first computed t-tests to assess gender differences in social network size and purpose in life. In order to examine the reciprocal effects between social network size and purpose in life over four time points (2017, 2018, 2019, and 2020), a RI-CLPM (Model 1) was computed. In addition to the main model, two multiple group RI-CLPM analyses (Model 2 and 3) were computed to test the moderated gender effect on the relationship with models estimating unconstrained and constrained cross-lagged parameters. Results: The results of the t-tests denoted significant gender differences in social network size and purpose in life. The results indicated that Model 1 fit the data well. The carry-over effects of social networks and purpose in life and spill-over effect from wave 3 purpose in life on wave 4 social networks were significant. There were no significant differences between the constrained and unconstrained models testing for moderated gender effects. Discussion: The findings of the study highlight the significant carry-over effect of purpose in life and social network size over four years and the positive spill-over effect from purpose in life on social network size at the subsequent wave, which only appeared at the last time point.

The Effect of a Supportive Educational Intervention Through Virtual Social Networks on Sleep Quality and Insomnia of Patients with Cancer

Sleep disturbances are very common among cancer patients, and they need more support in this regard. More access to technology has provided opportunities to use virtual teaching methods to educate and support cancer patients. This study aimed to investigate the effect of supportive educational intervention (SEI) through virtual social networks (VSNs) on the sleep quality and the severity of insomnia of cancer patients. The study was conducted on 66 patients with cancer: intervention (n = 33) and control (n = 33) groups (CONSORT). Intervention group received supportive educational intervention on sleep for 2 months through virtual social networks (VSNs). All participants completed the Pittsburgh Sleep Quality Index and insomnia severity index (ISI) before and after the intervention. The mean scores of sleep quality (p = .001) and insomnia severity (p = .001) in the intervention group had a statistically significant decrease. Moreover, quality, latency, duration, efficiency, disturbances of sleep, and daytime dysfunction showed significant improvement in the intervention group, every two times after the intervention (p < .05). However, the participants' sleep quality deteriorated progressively in the control group (p = .001). Supportive educational intervention (SEI) through VSNs can be an effective method to improve sleep quality and decrease insomnia severity of patients with cancer.Trial registration number: RCT20220528055007N1Date of registration: 2022-08-31(retrospectively registered).

The Role of Family Social Networks in Cardiovascular Health Behaviors Among Asian Americans, Native Hawaiians, and Pacific Islanders

Asian American, Native Hawaiians, and Other Pacific Islander (AANHPI) populations experience significant disparities in cardiovascular health. AANHPI populations also have strong, family-centered social relationships and networks. Since social networks may influence health behaviors, this review aimed to summarize research on the relationship between family social networks and cardiovascular health behaviors among AANHPI individuals. Current evidence suggests that family social network structures may play a particularly important role in smoking, dietary pattern, and physical activity behaviors among AANHPI individuals. Family networks may hinder or promote healthy behaviors through several social network mechanisms including social support, social influence, and social control. These effects vary across different AANHPI subgroups. Recommendations for future research on the role of social networks in health behaviors among AANHPI individuals are provided. Drawing on methodological advances and interventions that leverage social networks in AANHPI populations may be an avenue to improve health and reduce disparities.

The smartphone as a "significant other": interpersonal dependency and attachment in maladaptive smartphone and social networks use

Smartphones are increasingly widespread throughout the world and, although smartphones provide various benefits, excessive and maladaptive use is often reported. Given the penetration of smartphones in the individual's daily life, it is relevant to identify the mechanisms sustaining their use, including the affective bond that the owner may develop with the device. The aim of the current study is to test a novel model to explain smartphone and Social Network Sites (SNS) use from an interpersonal perspective. We hypothesized that adult attachment style and interpersonal patterns (i.e., features of interpersonal dependency) generalize to the emotional bond with the mobile device, interacting with psychological correlates and background factors to predict smartphone and SNS consumption. 341 nonclinical adults (57.2% females; age M = 35.5, SD = 14.6) completed a battery consisting of the Attachment Style Questionnaire, the Relationship Profile Test, the Rosenberg Self-Esteem Scale, the Toronto Alexithymia Scale, the Young Adult Attachment to Phone Scale, and the Social Network Intensity and Social Network Access via Mobile phone Applications. A multi-mediation model supported the hypothesis regarding the influence of interpersonal style in the relationship of the individual with their smartphone and use of SNS. A parallel between attachment style and the emotional bond with the smartphone emerged, with anxious attachment style and destructive overdependence being potential risk factors for maladaptive smartphone use especially in individuals involved in a romantic relationship. Findings are discussed in terms of theoretical implications and intervention strategies towards smartphone dependency.

The spectral underpinnings of pathogen spread on animal networks

Predicting what factors promote or protect populations from infectious disease is a fundamental epidemiological challenge. Social networks, where nodes represent hosts and edges represent direct or indirect contacts between them, are important in quantifying these aspects of infectious disease dynamics. However, how network structure and epidemic parameters interact in empirical networks to promote or protect animal populations from infectious disease remains a challenge. Here we draw on advances in spectral graph theory and machine learning to build predictive models of pathogen spread on a large collection of empirical networks from across the animal kingdom. We show that the spectral features of an animal network are powerful predictors of pathogen spread for a variety of hosts and pathogens and can be a valuable proxy for the vulnerability of animal networks to pathogen spread. We validate our findings using interpretable machine learning techniques and provide a flexible web application for animal health practitioners to assess the vulnerability of a particular network to pathogen spread.

Research on the collaborative evolution process of information in public health emergencies based on complex adaptive system theory and social network analysis: a case study of the COVID-19 pandemic

Introduction

This review aimed to elucidate the significance of information collaboration in the prevention and control of public health emergencies, and its evolutionary pathway guided by the theory of complex adaptive systems.

Methods

The study employed time-slicing techniques and social network analysis to translate the dynamic evolution of information collaboration into a stage-based static representation. Data were collected from January to April 2020, focusing on the COVID-19 pandemic. Python was used to amass data from diverse sources including government portals, public commentary, social organizations, market updates, and healthcare institutions. Post data collection, the structures, collaboration objectives, and participating entities within each time slice were explored using social network analysis.

Results

The findings suggest that the law of evolution for information collaboration in public health emergencies primarily starts with small-scale collaboration, grows to full-scale in the middle phase, and then reverts to small-scale in the final phase. The network's complexity increases initially and then gradually decreases, mirroring changes in collaboration tasks, objectives, and strategies.

Discussion

The dynamic pattern of information collaboration highlighted in this study offers valuable insights for enhancing emergency management capabilities. Recognizing the evolving nature of information collaboration can significantly improve information processing efficiency during public health crises.

Social network, political climate, income inequality, and Americans uptake of monovalent COVID-19 booster

The COVID-19 pandemic has posed an unprecedented impact on Americans for over three years. To control the damage, a booster shot becomes increasingly necessary because the efficacy of the initial vaccine is waning and new variants of the virus are emerging. This study aims to understand factors at both individual and state levels that influence one's decision to take the monovalent booster. We merged data from a national survey administered in the Spring of 2022 with state-level indicators of the political climate, income inequality, and public health conditions. Multilevel logistic regression is adopted for statistical estimation. Findings show contrasting effects of the social network. More vaccinated people in one's network promote booster uptake, while more family members and close friends who contracted the virus in one's network inhibit booster uptake. In addition, residents of states with more votes for the Democratic candidate in the 2020 general election are more likely to take the booster. Meanwhile, residents from states with high income inequality are less likely to become boosted. This study identified multilevel determinants of the individual decision to receive the monovalent COVID-19 booster. The results imply the need to leverage the social network, weaken partisanship salience, and reduce income inequality to encourage booster uptake.

Monitoring the Relationship between Social Network Status and Influenza Based on Social Media Data

BACKGROUND

This article aims to analyze the relationship between user characteristics on social networks and influenza.

METHODS

Three specific research questions are investigated: (1) we classify Weibo updates to recognize influenza-related information based on machine learning algorithms and propose a quantitative model for influenza susceptibility in social networks; (2) we adopt in-degree indicator from complex networks theory as social media status to verify its coefficient correlation with influenza susceptibility; (3) we also apply the LDA topic model to explore users' physical condition from Weibo to further calculate its coefficient correlation with influenza susceptibility. From the perspective of social networking status, we analyze and extract influenza-related information from social media, with many advantages including efficiency, low cost, and real time.

RESULTS

We find a moderate negative correlation between the susceptibility of users to influenza and social network status, while there is a significant positive correlation between physical condition and susceptibility to influenza.

CONCLUSIONS

Our findings reveal the laws behind the phenomenon of online disease transmission, and providing important evidence for analyzing, predicting, and preventing disease transmission. Also, this study provides theoretical and methodological underpinnings for further exploration and measurement of more factors associated with infection control and public health from social networks.

Psychometric properties of the Problematic Use of Social Networks (PUS) scale in Arabic among adolescents

BACKGROUND

The Problematic Use of Social Networks (PUSN) scale assesses for the first time the comparative use of social networks along with addictive tendencies. However, it has only been validated in a Spanish sample. This study aimed to evaluate the psychometric properties of the Arabic version of the PUSN (PUSN-Ar) among Lebanese adolescents.

METHODS

A total of 379 adolescents aged between 15 to 18 years (M = 16.07 years; 64.9% females) participated in this cross-sectional study conducted between January and May 2022. The problematic use of social networks-SNS (PUSN) scale yields of two subscales: addiction-related consequences of SNS use (SNS-ARC) and negative social comparison (SNS-NSC). The Beirut Distress Scale, the Smartphone Addiction Scale and the Jong-Gierveld Loneliness Scale were used to assess psychological distress, smartphone addiction and loneliness respectively.

RESULTS

The PUS-Ar scale exhibited a two-dimensional structure (Comparative Fit Index [CFI] = .97; Root Mean Square Error of Approximation [RMSEA] = .08), consistent with the original scale. Both subscales, Negative Social Comparison (α = .96) and Addictive Consequences (α = .92), demonstrated excellent reliability. Additionally, measurement invariance was verified between males and females at the configural, metric and scalar levels. No significant difference was found between males and females in terms of SNS-NSC (20.75 ± 10.15 vs 21.09 ± 9.51; t(377) = -.32; p = .751) and SNS-ARC (19.08 ± 8.61 vs 19.76 ± 6.77; t(377) = -.79; p = .430). The SNS-ARC subscale was more correlated to smartphone addiction than the SNS-NSC (r = .73; p < .001 vs r = .54; p < .001) whereas both subscales were significantly associated with more stress and more loneliness.

CONCLUSION

The data collected in this study provided support for all the hypotheses formulated. Consequently, the PUS-Ar was deemed a suitable scale to measure problematic SNS among Lebanese adolescents. The PUS-Ar is currently available to researchers for use in evaluating PSNSU in Lebanon. However, it is important to note that further research is needed to explore its applicability and generalizability across different populations and contexts.

Social networking at the microbiome-host interface

Microbial species colonizing host ecosystems in health or disease rarely do so alone. Organisms conglomerate into dynamic heterotypic communities or biofilms in which interspecies and interkingdom interactions drive functional specialization of constituent species and shape community properties, including nososymbiocity or pathogenic potential. Cell-to-cell binding, exchange of signaling molecules, and nutritional codependencies can all contribute to the emergent properties of these communities. Spatial constraints defined by community architecture also determine overall community function. Multilayered interactions thus occur between individual pairs of organisms, and the relative impact can be determined by contextual cues. Host responses to heterotypic communities and impact on host surfaces are also driven by the collective action of the community. Additionally, the range of interspecies interactions can be extended by bacteria utilizing host cells or host diet to indirectly or directly influence the properties of other organisms and the community microenvironment. In contexts where communities transition to a dysbiotic state, their quasi-organismal nature imparts adaptability to nutritional availability and facilitates resistance to immune effectors and, moreover, exploits inflammatory and acidic microenvironments for their persistence.

Analysis of the Usage Context of an mHealth Application for Equestrians

INTRODUCTION

One possibility to support veterinarians in times of a vet shortage is by providing animal owners with a technical decision support for deciding whether their animal needs to be seen by a vet. As the first step in the user-centered development of such an mHealth application for equestrians, an analysis of the context of use was done.

METHODS

The analysis was carried out by reviewing existing literature and conducting an online survey with 100 participants.

RESULTS

Characteristics of the user group and the usage context are presented using an adaptation of the four layers of diversity. Many equestrians are lacking health-related knowledge and competencies as well as social networks supporting them in decision making and gaining further information. This may apply to owners of other animal species in broad ranges as well.

CONCLUSION

The results of the analysis provide information to software developers and researchers on mHealth applications for pet owners in general and equestrians in particular to focus their work on the users' needs and therefore provide efficient results/software.

Unveiling the dynamics of emotions in society through an analysis of online social network conversations

Social networks can provide insights into the emotions expressed by a society. However, the dynamic nature of emotions presents a significant challenge for policymakers, politicians, and communication professionals who seek to understand and respond to changes in emotions over time. To address this challenge, this paper investigates the frequency, duration, and transition of 24 distinct emotions over a 2-year period, analyzing more than 5 million tweets. The study shows that emotions with lower valence but higher dominance and/or arousal are more prevalent in online social networks. Emotions with higher valence and arousal tend to last longer, while dominant emotions tend to have shorter durations. Emotions occupying the conversations predominantly inhibit others with similar valence and dominance, and higher arousal. Over a month, emotions with similar valences tend to prevail in online social network conversations.

Winner-loser effects improve social network efficiency between competitors with equal resource holding power

Animal societies are structured of dominance hierarchy (DH). DH can be viewed as networks and analyzed by graph theory. We study the impact of state-dependent feedback (winner-loser effect) on the emergence of local dominance structures after pairwise contests between initially equal-ranking members (equal resource-holding-power, RHP) of small and large social groups. We simulated pairwise agonistic contests between individuals with and without a priori higher RHP by Monte-Carlo-method. Random pairwise contests between equal-ranking competitors result in random dominance structures ('Null variant') that are low in transitive triads and high in pass along triads; whereas state-dependent feedback ('Winner-loser variant') yields centralized 'star' structured DH that evolve from competitors with initially equal RHP and correspond to hierarchies that evolve from keystone individuals. Monte-Carlo simulated DH following state-dependent feedback show motif patterns very similar to those of a variety of natural DH, suggesting that state-dependent feedback plays a pivotal role in robust self-organizing phenomena that transcend the specifics of the individual. Self-organization based on state-dependent feedback leads to social structures that correspond to those resulting from pre-existing keystone individuals. As the efficiency of centralized social networks benefits both, the individual and the group, centralization of social networks appears to be an important evolutionary goal.

Evaluating the DR-ED Listserv as a Medical Education Networking and Support Tool

The listserv, although considered old technology by some, continues to show benefit for and growth in subscribers. We investigated the roles the DR-ED listserv plays within the medical education community. We asked, Who subscribes? Why do they subscribe? and How do they use the listserv? We conducted a mixed-methods evaluation of the DR-ED listserv based on message content analysis and user surveys. We found the DR-ED listserv fulfills medical educators' need to network collegially; keep current with issues and ideas in the field; share solutions to problems; share resources; and advertise development opportunities. We found two types of listserv engagement: a) one-way engagement by using it as a resource, or two-way engagement by using and sharing resources. Our findings also highlight the value users attribute to virtual resources and the role listservs can play as economical professional development in a time of constrained costs, and our analysis methods can be used to guide future listserv evaluations. We conclude the relatively easy access to a global medical education listserv is one strategy to create a community of practice for medical education practitioners.

Social network analysis: Understanding nurses' advice-seeking interactions

AIM

This study aimed to determine advice-seeking interactions of nurses in a private hospital by using social network analysis.

DESIGN

This study was designed as a cross-sectional descriptive study.

METHODS

The study was conducted in a private hospital with 70 nurses. The data were collected with a social network analysis questionnaire. The social network analysis (SNA) focused on certain values such as network density, component, degree centrality, and betweenness centrality. The SNA was carried out using UCINET, and statistical analyses were performed with SPSS version 23.0.

RESULTS

The network density was reported to be 0.062, and it was composed of three components. It was further noted that nurse Y1 was found to have the highest scores of degree and betweenness centrality. Chi-Square Automatic Interaction Detector (CHAID) analysis indicated that the most common variables that affected degree centrality score were education, department, and position.

CONCLUSION

It was concluded that social network analysis was a useful instrument to delineate strengths and weaknesses of seeking advice relationships among nurses.

IMPLICATIONS FOR NURSING AND HEALTH POLICY

Top- and middle-level nursing managers occupy a significant position in advice-seeking networks. Nursing managers with higher education degrees will absolutely improve advice-seeking networks.

The mediation role of social network size and perception in the association between physical activity and depressive symptoms: a prospective analysis from the SHARE study

OBJECTIVES

To investigate the mediating role of social network size and perceived quality in the associations of physical activity with quality of life and depressive symptoms in middle-aged and older adults.

METHOD

We analyzed information of 10,569 middle-aged and older adults from waves 2 (2006-2007), 4 (2011-2012), and 6 (2015) of the Survey of Health, Ageing, and Retirement in Europe study (SHARE). Data on physical activity (moderate and vigorous intensities), social network (size and quality), depressive symptoms (EURO-D scale), and quality of life (CASP) were self-reported. Sex, age, country of residency, schooling, occupational status, mobility, and baseline values of the outcome were used as covariates. We created mediation models to test the mediating effect of social network size and quality in the association between physical activity and depressive symptoms.

RESULTS

Social network size partly mediated the association between vigorous physical activity and depressive symptoms (7.1%; 95%CI: 1.7-12.6) as well as the association between moderate (9.9%; 1.6-19.7) and vigorous (8.1%; 0.7-15.4) physical activity and quality of life. Social network quality did not mediate any of the associations tested.

CONCLUSION

We conclude that social network's size, but not satisfaction, mediates part of the association of physical activity with depressive symptoms and quality of life in middle-aged and older adults. Future physical activity interventions among middle-aged and older adults should consider increasing social interactions to facilitate benefits for mental health-related outcomes.

Strategy evolution on dynamic networks

Models of strategy evolution on static networks help us understand how population structure can promote the spread of traits like cooperation. One key mechanism is the formation of altruistic spatial clusters, where neighbors of a cooperative individual are likely to reciprocate, which protects prosocial traits from exploitation. However, most real-world interactions are ephemeral and subject to exogenous restructuring, so that social networks change over time. Strategic behavior on dynamic networks is difficult to study, and much less is known about the resulting evolutionary dynamics. Here we provide an analytical treatment of cooperation on dynamic networks, allowing for arbitrary spatial and temporal heterogeneity. We show that transitions among a large class of network structures can favor the spread of cooperation, even if each individual social network would inhibit cooperation when static. Furthermore, we show that spatial heterogeneity tends to inhibit cooperation, whereas temporal heterogeneity tends to promote it. Dynamic networks can have profound effects on the evolution of prosocial traits, even when individuals have no agency over network structures.

RegraphGAN: A graph generative adversarial network model for dynamic network anomaly detection

Due to the wide application of dynamic graph anomaly detection in cybersecurity, social networks, e-commerce, etc., research in this area has received increasing attention. Graph generative adversarial networks can be used in dynamic graph anomaly detection due to their ability to model complex data, but the original graph generative adversarial networks do not have a method to learn reverse mapping and require an expensive process in recovering the potential representation of a given input. Therefore, this paper proposes a novel graph generative adversarial network by adding encoders to map real data to latent space to improve the training efficiency and stability of graph generative adversarial network models, which is named RegraphGAN in this paper. And this paper proposes a dynamic network anomaly edge detection method by combining RegraphGAN with spatiotemporal coding to solve the complex dynamic graph data and the problem of attribute-free node information coding challenges. Meanwhile, anomaly detection experiments are conducted on six real dynamic network datasets, and the results show that the dynamic network anomaly detection method proposed in this paper outperforms other existing methods.

The role of ethical leadership and social networks in the promotion of workplace happiness and quality of care: A cross-sectional study

This study examines the sequential effects of perceived ethical leaders and the strength of social networks among healthcare professionals on the perceived workplace happiness of healthcare professionals and its impacts on the quality of provided care. We conduct a partial least squares (PLS) analysis to estimate the relationship between the variables. Data comes from a survey conducted to 321 healthcare professionals with primary/direct contact with patients working at Portuguese hospitals. We use previously validated scales in the literature for measuring the variables; ethical leadership, social network in the context of the workplace; satisfaction, engagement, and commitment as proxies of workplace happiness, and, quality of care provided to patients (the outcome of the research model). Results show that ethical leadership positively influences social networks, workplace happiness, and quality of provided care. Social networks also have a positive relationship with workplace happiness and quality of provided care. Additionally, the workplace happiness of healthcare professionals positively influences the quality of provided care to patients. Our work addresses a diverse research gap regarding hospitals' ethical and social environment and hospital performance. Specifically, the empirical operationalisation of ethical leadership fights a literature gap in healthcare management. Moreover, we report evidence on the influence of antecedents, but also the performance consequences, of workplace happiness in healthcare environments. Our findings contribute to the literature while providing managerial implications for healthcare settings.

Let families decide: Barriers and enablers to participation in family-assisted therapy for older people in transition care

OBJECTIVE

To understand the barriers and enablers to participation in family-assisted therapy for older people in Transition Care.

METHODS

A qualitative study, underpinned by interpretive description, was conducted at two public health services in Melbourne, Australia. Participants included patients in Transition Care, or their family members, who either participated in or chose not to participate in a family-assisted therapy trial. Semi-structured interviews were conducted, transcribed verbatim and analysed thematically.

RESULTS

Forty-four participants were interviewed (17 patients and 27 family members). The unifying theme was to let families decide about participation in family-assisted therapy. The unifying theme was illustrated by three subthemes. The first, what is possible for the family now, described practical considerations including geography, paid and unpaid work structure and commitments and the presence of fit and willing social networks. The second, what is important to the family now, recognised the role of family priorities in deciding. Physical rehabilitation and extra therapy were of high importance to some families. For others, emotional support or searching for a residential aged care bed were more important at the time. Finally, how the family functions described the complexity of relationships and family history that impacted the decision to participate.

CONCLUSIONS

The decision to participate in family-assisted therapy is complex and is best made by patients and their families. Clinicians offering family-assisted therapy are encouraged to avoid assuming what will or will not work for families and instead, to let families decide.

Social network and mental health of Chinese immigrants in affordable senior housing during the COVID-19 pandemic: a mixed-methods study

OBJECTIVE

Chinese immigrant older adults who live in affordable housing are at high risk of experiencing social isolation during the COVID-19 pandemic, which can affect their mental health. Using a triangulation mixed-methods approach, this study describes Chinese immigrant older adults' social network, mental health status, and their associations during the pandemic.

METHODS

Semi-structured in-depth interviews were conducted with 26 Chinese immigrant older adults from June to August 2021. The structure and characteristics of participants' social networks were assessed with a name-generating approach. Mental health status was self-reported with Geriatric Depression Scale and UCLA loneliness scale.

RESULTS

This sample (mean age = 78.12, 69.23% female), on average, had 5.08 social ties in their network, and 58% were family ties. Participants reported decreased social contact, family and friends interaction patterns specific to immigrants, and constantly being in a low mood and bored. Having closer relationships with others and maintaining the same or higher contact frequency after COVID-19 onset was associated with fewer depressive symptoms. Resilience from religious beliefs, neighbors as role models, and wisdom learned from past experiences were reported.

CONCLUSION

Knowledge built in this study can inform respondence to future crises like the COVID-19 pandemic in affordable housing settings serving older immigrant populations.

Mapping community: A scoping review of clubhouse members' social networks and their impact on recovery in mental illness

OBJECTIVE

Social support is an important component of recovery-based interventions for individuals living with severe mental illness (IWSMI). Clubhouses are local community centers that facilitate the development of meaningful relationships among IWSMI through an empowering structure and engagement with the work-ordered day. This review synthesizes research on social networks in Clubhouses to provide insights on the role of supportive relationships in mental illness recovery, including the size and features of social networks of Clubhouse members, methodological trends and gaps, and the associations between social networks and demographic variables, recovery, health, and perceived social support.

METHOD

Research on social networks within Clubhouses were identified and analyzed following a systematic six-stage scoping review design.

RESULTS

Twelve articles across six studies were included. Results revealed considerable variation in social network interview methods and network size and features. Overall findings suggest that network size is not consistently associated with reported loneliness, social support, recovery, or quality of life. A deep relationship with at least one supportive person, level of perceived affiliation with Clubhouses, or positive comments from network members may be more or equally valuable than a larger network. Some studies found that types of relationships were associated with unique benefits. Stronger peer networks were associated with relationship satisfaction, while increased connections with health care professionals and family were associated with reduced hospitalizations.

CONCLUSIONS AND IMPLICATIONS FOR PRACTICE

Future research should diversify research designs, expand the use of social network analysis and visualization, measure additional outcomes including recovery and health, and increase sample diversity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

How do Gambling Providers Use the Social Network Twitter in Germany? An Explorative Mixed-Methods Topic Modeling Approach

This study examines the social media activities of gambling providers in Germany, focusing on the platform Twitter. A collection of 34.151 tweets from 13 Twitter accounts was made, representing casinos, sports betting, state lotteries, social lotteries and lottery brokers. We apply an explorative mixed-methods approach, integrating a summative content analysis together with a semi-supervised guided topic modeling approach, to analyse frequency, number of followers, interaction and content of Twitter messages, and work out differences among the individual providers. The results show that Twitter does not seem to be particularly important for gambling providers who are active in Germany. Regarding outreach, frequency of tweets and interaction, Twitter plays a much smaller role than, for example, in the UK. The potential for Twitter to be an advertising, marketing and interaction channel has not yet been fully exploited, which would make it a perfect moment for developing an appropriate regulatory framework. Overall, the results of semi-supervised topic modeling show that providers most often use informative content (news) and combine it with other, usually less neutral content. It is alarming that many providers make little or no use of Responsible Gambling messages. Even though the activities are presently on a low level, they contribute to the normalization of gambling, setting incentives for increasing gambling participation. Children and youth form a large segment of Twitter users. Potential harm can arise especially for this group because of the lack of enforcement of any age limit.

Examining the social networks of older adults receiving informal or formal care: a systematic review

PURPOSE

To address the care needs of older adults, it is important to identify and understand the forms of care support older adults received. This systematic review aims to examine the social networks of older adults receiving informal or formal care and the factors that influenced their networks.

METHODS

A systematic review was conducted by searching six databases from inception to January 31, 2023. The review included primary studies focusing on older adults receiving long-term care, encompassing both informal and formal care. To assess the risk of bias in the included studies, validated appraisal tools specifically designed for different study types were utilized. Network analysis was employed to identify the grouping of study concepts, which subsequently formed the foundation for describing themes through narrative synthesis.

RESULTS

We identified 121 studies relating to the formal and informal care of older adults' networks. A variety of social ties were examined by included studies. The most commonly examined sources of care support were family members (such as children and spouses) and friends. Several factors were consistently reported to influence the provision of informal care, including the intensity of networks, reciprocity, and geographical proximity. In terms of formal care utilization, older age and poor health status were found to be associated with increased use of healthcare services. Additionally, physical limitations and cognitive impairment were identified as factors contributing to decreased social engagement.

CONCLUSION

This review found that older people were embedded within a diverse network. The findings of this review emphasize the importance of recognizing and incorporating the diversity of social networks in care plans and policies to enhance the effectiveness of interventions and improve the overall well-being of older adults.

Academic performance and social networks of adolescents in a caribbean city in Colombia

BACKGROUND

Social factors and networks of friends can influence an adolescent's behavior, including academic performance (AP) in school. This study aimed to analyze the relationship between AP and adolescents' social networks in a Caribbean city in Colombia.

METHODS

A cross-sectional study was carried out with 806 schoolchildren from 12 to 17 years old of both sexes (52.7% girls), selected by multi-stage sampling from schools in the rural and urban areas of the city of Montería, Colombia. The AP was obtained from the school records; the sociodemographic variables included the location of the school (rural or urban), family structure, family functioning (Apgar score), and family affluence scale. Social network variables included social activity, popularity, reciprocity, homophily, friends' academic performance, network size, network density, cluster of friends, and centrality.

RESULTS

The AP was inversely associated with the Apgar score in boys. No associations of AP with the school location, family structure, family affluence scale, and age were observed. In social network variables, AP was positively associated with popularity and friends' academic performance in girls and boys, and negatively associated with homophily in boys.

CONCLUSIONS

AP was associated with social network variables. These results could help implement interventions to improve adolescents' social environment and AP.

The COVID-19 related stress and social network addiction among Chinese college students: A moderated mediation model

Based on social cognitive theory and gender differences, this study verified a moderated mediation model to explore the relationship between the COVID-19 related stress (CRS) and social network addiction (SNA) and evaluate the mediating role of fear of missing out (FoMO) and the moderating role of gender. A questionnaire survey was conducted, including 702 Chinese university students.This study used PROCESS to test the hypothesis model.The results showed that the CRS significantly and positively affected the SNA of college students and FoMO played a complementary mediating role. Moreover, the analysis of the moderated mediation model showed that gender moderated the relationship between FoMO and SNA; the effect of FoMO was stronger on the SNA of male college students than that of females. The results not only enhanced our understanding of the internal influencing mechanism of the relationship between CRS and SNA but also considered gender differences. In addition, some suggestions were proposed.

The effectiveness of moderating harmful online content

In 2022, the European Union introduced the Digital Services Act (DSA), a new legislation to report and moderate harmful content from online social networks. Trusted flaggers are mandated to identify harmful content, which platforms must remove within a set delay (currently 24 h). Here, we analyze the likely effectiveness of EU-mandated mechanisms for regulating highly viral online content with short half-lives. We deploy self-exciting point processes to determine the relationship between the regulated moderation delay and the likely harm reduction achieved. We find that harm reduction is achievable for the most harmful content, even for fast-paced platforms such as Twitter. Our method estimates moderation effectiveness for a given platform and provides a rule of thumb for selecting content for investigation and flagging, managing flaggers' workload.

An improved approach for ecological modeling of social phenomena in Blau space

Advances in computation have opened new vistas for modeling of sociodemographic niches and related constructs, enabling us to rectify limitations that unavoidably plagued earlier generations of researchers. This is especially true for Blau space, a sociodemographic niche model used to explore competition between social entities over resources, such as memberships. While this approach has been successful in using probabilistic representations of social networks and resource niches, its modeling framework has remained essentially unchanged for over 40 years, and lacks the ability to make predictions about the future states of sociodemographic space. We present a novel Hybrid Blau space (HBS) model, which utilizes a cellular framework and probabilistic urn models to simulate competition over resources while suffering from fewer limitations. We apply this new model to the General Social Survey, running two sets of models from a series of variables (age, education, income, and sex) and utilize an adjustable range of sociodemographic information for local simulation of organizational competition. We also demonstrate the model's predictive ability, as well as introduce new methods of validation and fit.

Addressing COVID-19 inequities using bidirectional crisis and emergency risk communication and vaccine clinic interventions: a descriptive study

BACKGROUND

Im/migrants (immigrants and migrants, including refugees, asylum seekers, and individuals without legal documentation) experience unique assets and needs in relation to coronavirus disease 2019 (COVID-19). Community-based participatory research (CBPR) is one way to engage im/migrant communities. Rochester Healthy Community Partnership (RHCP) is a CBPR partnership in Rochester, Minnesota. RHCP partners noted that credible COVID-19 information was not available to their communities. In response, RHCP formed a COVID-19 Task Force and adapted the Centers for Disease Control and Prevention's Crisis and Emergency Risk Communication (CERC) framework to create an intervention that prioritized im/migrant groups experiencing health disparities. In the CERC intervention, communication leaders delivered COVID-19 health messages to their social networks and documented related concerns. RHCP relayed these concerns to regional leaders to ensure that im/migrant experiences were included in decision making. Once vaccines were available, RHCP continued to deploy the CERC intervention to promote vaccination equity. The aims of this paper are to (1) describe the implementation of a bidirectional CERC intervention for vaccination equity, and (2) describe a community-engaged and community-based vaccine clinic intervention.

METHODS

First, we surveyed participants (n = 37) to assess COVID-19 experiences, acceptability of the CERC intervention, and motivation to receive a COVID-19 vaccination. Second, we collaborated with community partners to hold vaccine clinics. We report descriptive statistics from each intervention.

RESULTS

When asked about the acceptability of the CERC intervention for vaccine equity, most participants either reported that they 'really liked it' or 'thought it was just ok'. Most participants stated that they would recommend the program to family or friends who have not yet received the COVID-19 vaccine. Almost all participants reported that they felt 'much more' or 'somewhat more' motivated to receive a COVID-19 vaccine after the intervention. We administered 1158 vaccines at the vaccination clinics.

CONCLUSIONS

We found that participants viewed the CERC intervention for vaccination equity as an acceptable way to disseminate COVID-19-related information. Nearly all participants reported that the intervention convinced them to receive a COVID-19 vaccine. In our experience, community-engaged and community-based clinics are a successful way to administer vaccines to im/migrant communities during a pandemic.

Network canvas: an open-source tool for capturing social and contact network data

MOTIVATION

Social influence and contact networks are extremely important for understanding health behaviour and the spread of disease. Yet, most traditional software tools are not optimized to capture these data, making measurement of personal networks challenging. Our team developed Network Canvas to provide an end-to-end workflow with intuitive interfaces to enable researchers to design and conduct network interviews.

IMPLEMENTATION

Network Canvas consists of three applications (Architect, Interviewer and Server). All applications are written in JavaScript and run on Windows, macOS and Linux; Interviewer also runs on Android and iOS.

GENERAL FEATURES

Network Canvas substantially reduces the complexity and technical knowledge required to collect network data via three point-and-click applications. The tool has wide applicability for measuring contact and social influence networks in epidemiology.

AVAILABILITY

Network Canvas is open source and freely available [networkcanvas.com] under the GNU General Public License 3.

The effectiveness of social network interventions for psychiatric patients: A systematic review and meta-analysis

Strengthening social networks is an important goal in mental health treatment. This study aimed to determine the effectiveness of social network interventions for psychiatric patients. A systematic review and meta-analysis was conducted comparing these interventions with control groups on social and mental health-related outcomes in psychiatric patients. PubMed, EMBASE.com, PsycInfo, Scopus, and IBSS were searched for studies until December 21, 2022. Three-level random effects models were used to obtain Cohen's d mean estimates on composite outcomes of social network and secondary mental health outcomes. Heterogeneity was examined with potential moderators. Thirty-three studies were included. Small-to-moderate effects of social network interventions were detected on positive social network (d = 0.115, p = 0.022) and support (d = 0.159; p = 0.007), general functioning (d = 0.127, p = 0.046), mental health treatment adherence (d = 0.332, p = 0.003), days substance use (d = 0.097, p = 0.004), and abstinence (d = 0.254, p = 0.004). Estimates of psychiatric functioning were higher in samples with more females. The quality of evidence was moderate-to-low. This evidence suggests that social network interventions can improve positive social networks, general functioning, mental health treatment adherence, and substance use in psychiatric patients receiving usual care. PROSPERO ID: CRD42019131959.