A Comparison of Dyadic and Social Network Assessments of Peer Influence.
Ontology highlight
ABSTRACT:
SUBMITTER: DeLay D
PROVIDER: S-EPMC8078849 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Disentangling the effects of selection and influence is one of social science's greatest unsolved puzzles: Do people befriend others who are similar to them, or do they become more similar to their friends over time? Recent advances in stochastic actor-based modeling, combined with self-reported data on a popular online social network site, allow us to address this question with a greater degree of precision than has heretofore been possible. Using data on the Facebook activity of a cohort of college students over 4 years, we find that students who share certain tastes in music and in movies, but not in books, are significantly likely to befriend one another. Meanwhile, we find little evidence for the diffusion of tastes among Facebook friends-except for tastes in classical/jazz music. These findings shed light on the mechanisms responsible for observed network homogeneity; provide a statistically rigorous assessment of the coevolution of cultural tastes and social relationships; and suggest important qualifications to our understanding of both homophily and contagion as generic social processes.
| S-EPMC3252911 | biostudies-literature
Project description:Background and purposeSocial networks influence human health and disease through direct biological and indirect psychosocial mechanisms. They have particular importance in neurologic disease because of support, information, and healthy behavior adoption that circulate in networks. Investigations into social networks as determinants of disease risk and health outcomes have historically relied on summary indices of social support, such as the Lubben Social Network Scale-Revised (LSNS-R) or the Stroke Social Network Scale (SSNS). We compared these 2 survey tools to personal network (PERSNET) mapping tool, a novel social network survey that facilitates detailed mapping of social network structure, extraction of quantitative network structural parameters, and characterization of the demographic and health parameters of each network member.MethodsIn a cohort of inpatient and outpatient stroke survivors, we administered LSNS-R, SSNS, and PERSNET in a randomized order to each patient. We used logistic regression to generate correlation matrices between LSNS-R scores, SSNS scores, and PERSNET's network structure (eg, size and density) and composition metrics (eg, percent kin in network). We also examined the relationship between LSNS-R-derived risk of social isolation with PERSNET-derived network size.ResultsWe analyzed survey responses for 67 participants and found a significant correlation between LSNS-R, SSNS, and PERSNET-derived indices of network structure. We found no correlation between LSNS-R, SSNS, and PERSNET-derived metrics of network composition. Personal network mapping tool structural and compositional variables were also internally correlated. Social isolation defined by LSNS-R corresponded to a network size of <5.ConclusionsPersonal network mapping tool is a valid index of social network structure, with a significant correlation to validated indices of perceived social support. Personal network mapping tool also captures a novel range of health behavioral data that have not been well characterized by previous network surveys. Therefore, PERSNET offers a comprehensive social network assessment with visualization capabilities that quantifies the social environment in a valid and unique manner.
| S-EPMC8022189 | biostudies-literature
Project description:This study explores the influence of different social reference points and different comparison group sizes on risky decision-making. Participants were presented with a scenario describing an exam, and presented with the opportunity of making a risky decision in the context of different information provided about the performance of their peers. We found that behavior was influenced, not only by comparison with peers, but also by the size of the comparison group. Specifically, the larger the reference group, the more polarized the behavior it prompted. In situations describing social loss, participants were led to make riskier decisions after comparing themselves against larger groups, while in situations describing social gain, they become more risk averse. These results indicate that decision making is influenced both by social comparison and the number of people making up the social reference group.
| S-EPMC4987381 | biostudies-literature
Project description:Based on the serial mergers and acquisitions(M&A) data of Chinese A-share listed companies from 2010 to 2019, this paper discusses whether there are geographical peer effects in serial M&A, and tests its mechanism and influence path. The empirical study shows that geographical peer decision-making has geographical peer effects in the decision-making of serial M&A, and the average number of serial M&A of geographical peers has a significant positive impact on the serial M&A decision-making of focal firms. Social learning and director networks are essential to produce geographical peer effects in serial M&A. The external learning mechanism shows that the geographical peer effect of serial M&A decision-making is partly caused by backward firms' social learning to the leading peer firms' decision-making, but vice versa. The director network relationship of focal firms can positively moderate the relationship between the geographical peer firms' average serial M&A decision-making and the focal firm's serial M&A decision-making. This paper reveals the mechanism of geographical peer effect in serial M&A decision-making and provides a new perspective to understand the motivation of serial M&A decision-making. These empirical findings not only provide important empirical evidence on serial M&A from developing countries such as China, but also provide a valuable reference for decision-makers and researchers of serial M&A in the future.
| S-EPMC10735032 | biostudies-literature
Project description:Studies show that online mentoring is an effective measure to support girls in STEM (science, technology, engineering, and mathematics), especially if it also allows for networking with other participants on the mentoring platform. However, research is missing on peer influence. This topic seems especially crucial in programs for adolescents as peer influence plays an important role at this age. In our study, we investigated peer influence on mentoring outcomes - confidence in own STEM abilities and STEM-related activities - in an online mentoring program in STEM for secondary school girls (N = 124, M = 14.3 years, SD = 2.2 years, age range: 11-19 years). The program provides girls with at least 1 year of one-on-one interaction with a personal female mentor who has a college degree in a STEM subject. Participants can also interact with other participants on the platform. We used a longitudinal social network analysis approach to examine peer influence on mentoring outcomes. Our results indicate that both mentoring outcomes - mentees' confidence in own STEM abilities and STEM-related activities - are influenced by peers moderated by the mentees' own age. Younger mentees tended to become more similar to their peers regarding confidence in own STEM abilities and STEM-related activities, whereas older mentees tended to become more dissimilar over time. In addition, peer group size had a positive effect on confidence in own STEM abilities, but not on STEM-related activities. This effect was moderated by the mentee's age. Overall, peers have a positive influence on the measured mentoring outcomes, especially for young mentees.
| S-EPMC7456988 | biostudies-literature
Project description:INTRODUCTION:Adolescent and young adult binge drinking is strongly associated with perceived social norms and the drinking behavior that occurs within peer networks. The extent to which an individual is influenced by the behavior of others may depend upon that individual's resistance to peer influence (RPI). METHODS:Students in their first semester of college (N=1323; 54.7% female, 57% White, 15.1% Hispanic) reported on their own binge drinking, and the perceived binge drinking of up to 10 important peers in the first-year class. Using network autocorrelation models, we investigated cross-sectional relationships between participant's binge drinking frequency and the perceived and actual binge drinking frequency of important peers. We then tested the moderating role of RPI, expecting that greater RPI would weaken the relationship between perceived and actual peer binge drinking on participant binge drinking. RESULTS:Perceived and actual peer binge drinking were statistically significant predictors of participant binge drinking frequency in the past month, after controlling for covariates. RPI significantly moderated the association between perceptions of peer binge drinking and participant's own binge drinking; this association was weaker among participants with higher RPI compared to those with lower RPI. RPI did not interact with the actual binge drinking behavior of network peers. CONCLUSIONS:RPI may function to protect individuals from the effect of their perceptions about the binge drinking of peers, but not from the effect of the actual binge drinking of peers.
| S-EPMC6563916 | biostudies-literature
Project description:BackgroundThe influence of social media among adolescent peer groups can be a powerful change agent.ObjectiveOur scoping review aimed to elucidate the ways in which social media use among adolescent peers influences eating behaviors.MethodsA scoping review of the literature of articles published from journal inception to 2019 was performed by searching PubMed (ie, MEDLINE), Embase, CINAHL, PsycINFO, Web of Science, and other databases. The review was conducted in three steps: (1) identification of the research question and clarification of criteria using the population, intervention, comparison, and outcome (PICO) framework; (2) selection of articles from the literature using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines; and (3) charting and summarizing information from selected articles. PubMed's Medical Subject Headings (MeSH) and Embase's Emtree subject headings were reviewed along with specific keywords to construct a comprehensive search strategy. Subject headings and keywords were based on adolescent age groups, social media platforms, and eating behaviors. After screening 1387 peer-reviewed articles, 37 articles were assessed for eligibility. Participant age, gender, study location, social media channels utilized, user volume, and content themes related to findings were extracted from the articles.ResultsSix articles met the final inclusion criteria. A final sample size of 1225 adolescents (aged 10 to 19 years) from the United States, the United Kingdom, Sweden, Norway, Denmark, Portugal, Brazil, and Australia were included in controlled and qualitative studies. Instagram and Facebook were among the most popular social media platforms that influenced healthful eating behaviors (ie, fruit and vegetable intake) as well as unhealthful eating behaviors related to fast food advertising. Online forums served as accessible channels for eating disorder relapse prevention among youth. Social media influence converged around four central themes: (1) visual appeal, (2) content dissemination, (3) socialized digital connections, and (4) adolescent marketer influencers.ConclusionsAdolescent peer influence in social media environments spans the spectrum of healthy eating (ie, pathological) to eating disorders (ie, nonpathological). Strategic network-driven approaches should be considered for engaging adolescents in the promotion of positive dietary behaviors.
| S-EPMC8212626 | biostudies-literature
Project description:IntroductionAlthough technology-assisted tobacco interventions (TATIs) are effective, they are underused due to recruitment challenges. We tested whether we could successfully recruit smokers to a TATI using peer marketing through a social network (Facebook).MethodsWe recruited smokers on Facebook using online advertisements. These recruited smokers (seeds) and subsequent waves of smokers (peer recruits) were provided the Share2Quit peer recruitment Facebook app and other tools. Smokers were incentivized for up to seven successful peer recruitments and had 30 days to recruit from date of registration. Successful peer recruitment was defined as a peer recruited smoker completing the registration on the TATI following a referral. Our primary questions were (1) whether smokers would recruit other smokers and (2) whether peer recruitment would extend the reach of the intervention to harder-to-reach groups, including those not ready to quit and minority smokers.ResultsOverall, 759 smokers were recruited (seeds: 190; peer recruits: 569). Fifteen percent (n = 117) of smokers successfully recruited their peers (seeds: 24.7%; peer recruits: 7.7%) leading to four recruitment waves. Compared to seeds, peer recruits were less likely to be ready to quit (peer recruits 74.2% vs. seeds 95.1%), more likely to be male (67.1% vs. 32.9%), and more likely to be African American (23.8% vs. 10.8%) (p < .01 for all comparisons).ConclusionsPeer marketing quadrupled our engaged smokers and enriched the sample with not-ready-to-quit and African American smokers. Peer recruitment is promising, and our study uncovered several important challenges for future research.ImplicationsThis study demonstrates the successful recruitment of smokers to a TATI using a Facebook-based peer marketing strategy. Smokers on Facebook were willing and able to recruit other smokers to a TATI, yielding a large and diverse population of smokers.
| S-EPMC5896501 | biostudies-literature
Project description:BackgroundOptimizing prescribing practices is important due to the substantial clinical and financial costs of polypharmacy and an increasingly aging population. Prior research shows the importance of social relationships in driving prescribing behaviour. Using social network analysis, we examine the relationship between a physician practices' connectedness to peers and their prescribing performance in two German regions.MethodsWe first mapped physician practice networks using links established between two practices that share 8 or more patients; we calculated network-level (density, average path length) and node-level measures (degree, betweenness, eigenvector). We defined prescribing performance as the total number of inappropriate medications prescribed or appropriate medications not prescribed (PIMs) to senior patients (over the age of 65) during the calendar year 2016. We used FORTA (Fit fOR The Aged) algorithm to classify medication appropriateness. Negative binomial regression models estimate the association between node-level measures and prescribing performance of physician practices controlling for patient comorbidity, provider specialization, percentage of seniors in practice, and region. We conducted two sensitivity analyses to test the robustness of our findings - i) limiting the network mapping to patients younger than 65; ii) limiting the network ties to practices that share more than 25 patients.ResultsWe mapped two patient-sharing networks including 436 and 270 physician practices involving 28,508 and 20,935 patients and consisting of 217,126 and 154,274 claims in the two regions respectively. Regression analyses showed a practice's network connectedness as represented by degree, betweenness, and eigenvector centrality, is significantly negatively associated with prescribing performance (degree-bottom vs. top quartile aRR = 0.04, 95%CI: 0.035,0.045; betweenness-bottom vs. top quartile aRR = 0.063 95%CI: 0.052,0.077; eigenvector-bottom vs. top quartile aRR = 0.039, 95%CI: 0.034,0.044).ConclusionsOur study provides evidence that physician practice prescribing performance is associated with their peer connections and position within their network. We conclude that practices occupying strategic positions at the edge of networks with advantageous access to novel information are associated with better prescribing outcomes, whereas highly connected practices embedded in insulated information environments are associated with poor prescribing performance.
| S-EPMC10613382 | biostudies-literature
Project description:We introduce a model of dyadic social interactions and establish its correspondence with relational models theory (RMT), a theory of human social relationships. RMT posits four elementary models of relationships governing human interactions, singly or in combination: Communal Sharing, Authority Ranking, Equality Matching, and Market Pricing. To these are added the limiting cases of asocial and null interactions, whereby people do not coordinate with reference to any shared principle. Our model is rooted in the observation that each individual in a dyadic interaction can do either the same thing as the other individual, a different thing or nothing at all. To represent these three possibilities, we consider two individuals that can each act in one out of three ways toward the other: perform a social action X or Y, or alternatively do nothing. We demonstrate that the relationships generated by this model aggregate into six exhaustive and disjoint categories. We propose that four of these categories match the four relational models, while the remaining two correspond to the asocial and null interactions defined in RMT. We generalize our results to the presence of N social actions. We infer that the four relational models form an exhaustive set of all possible dyadic relationships based on social coordination. Hence, we contribute to RMT by offering an answer to the question of why there could exist just four relational models. In addition, we discuss how to use our representation to analyze data sets of dyadic social interactions, and how social actions may be valued and matched by the agents.
| S-EPMC4380352 | biostudies-other