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US adolescents' friendship networks and health risk behaviors: a systematic review of studies using social network analysis and Add Health data.

ABSTRACT: Background. Documented trends in health-related risk behaviors among US adolescents have remained high over time. Studies indicate relationships among mutual friends are a major influence on adolescents' risky behaviors. Social Network Analysis (SNA) can help understand friendship ties affecting individual adolescents' engagement in these behaviors. Moreover, a systematic literature review can synthesize findings from a range of studies using SNA, as well as assess these studies' methodological quality. Review findings also can help health educators and promoters develop more effective programs. Objective. This review systematically examined studies of the influence of friendship networks on adolescents' risk behaviors, which utilized SNA and the Add Health data (a nationally representative sample). Methods. We employed the Matrix Method to synthesize and evaluate 15 published studies that met our inclusion and exclusion criteria, retrieved from the Add Health website and 3 major databases (Medline, Eric, and PsycINFO). Moreover, we assigned each study a methodological quality score (MQS). Results. In all studies, friendship networks among adolescents promoted their risky behaviors, including drinking alcohol, smoking, sexual intercourse, and marijuana use. The average MQS was 4.6, an indicator of methodological rigor (scale: 1-9). Conclusion. Better understanding of risky behaviors influenced by friends can be useful for health educators and promoters, as programs targeting friendships might be more effective. Additionally, the overall MQ of these reviewed studies was good, as average scores fell above the scale's mid-point.

SUBMITTER: Jeon KC

PROVIDER: S-EPMC4493707 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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US adolescents' friendship networks and health risk behaviors: a systematic review of studies using social network analysis and Add Health data.

Jeon Kwon Chan KC Goodson Patricia P

PeerJ 20150630

Background. Documented trends in health-related risk behaviors among US adolescents have remained high over time. Studies indicate relationships among mutual friends are a major influence on adolescents' risky behaviors. Social Network Analysis (SNA) can help understand friendship ties affecting individual adolescents' engagement in these behaviors. Moreover, a systematic literature review can synthesize findings from a range of studies using SNA, as well as assess these studies' methodological ...[more]

PMID: 26157622

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Project description:In low- and middle-income countries (LMICs), naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various resources. Understanding how social network structure, and influential individuals within the network, may amplify the effects of interventions in LMICs, by creating, for example, cascade effects to non-targeted participants, presents an opportunity to improve the efficiency and effectiveness of public health interventions in such settings. We conducted a systematic review of PubMed, Econlit, Sociological Abstracts, and PsycINFO to identify a sample of 17 sociocentric network papers (arising from 10 studies) that specifically examined health issues in LMICs. We also separately selected to review 19 sociocentric network papers (arising from 10 other studies) on development topics related to wellbeing in LMICs. First, to provide a methodological resource, we discuss the sociocentric network study designs employed in the selected papers, and then provide a catalog of 105 name generator questions used to measure social ties across all the LMIC network papers (including both ego- and sociocentric network papers) cited in this review. Second, we show that network composition, individual network centrality, and network structure are associated with important health behaviors and health and development outcomes in different contexts across multiple levels of analysis and across distinct network types. Lastly, we highlight the opportunities for health researchers and practitioners in LMICs to 1) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure, 2) measure the spread of outcomes or intervention externalities, and 3) enhance the effectiveness and efficiency of aid based on knowledge of social structure. In summary, human health and wellbeing are connected through complex webs of dynamic social relationships. Harnessing such information may be especially important in contexts where resources are limited and people depend on their direct and indirect connections for support.

Project description:Although the structural properties of online social networks have attracted much attention, the properties of the close-knit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzing the data of four large-scale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented by the distributions of close-knit friendship structures also exhibit a similar scaling law. The degree correlation is very weak over a wide range of the degrees. We propose a simple directed network model that captures the observed properties. The model incorporates two mechanisms: reciprocation and preferential attachment. Through rate equation analysis of our model, the local-scale and mesoscale structural properties are derived. In the local-scale, the same scaling behavior of indegree and outdegree distributions stems from indegree and outdegree of nodes both growing as the same function of the introduction time, and the reciprocal degree distribution also shows the same power-law due to the linear relationship between the reciprocal degree and in/outdegree of nodes. In the mesoscale, the distributions of four closed triples representing close-knit friendship structures are found to exhibit identical power-laws, a behavior attributed to the negligible degree correlations. Intriguingly, all the power-law exponents of the distributions in the local-scale and mesoscale depend only on one global parameter, the mean in/outdegree, while both the mean in/outdegree and the reciprocity together determine the ratio of the reciprocal degree of a node to its in/outdegree. Structural properties of numerical simulated networks are analyzed and compared with each of the four real networks. This work helps understand the interplay between structures on different scales in online social networks.

Project description:BackgroundPhysical activity in children is associated with better physical and mental health but many children do not meet physical activity guidelines. Friendship groups are potentially an important influence on children's physical activity and sedentary time. This paper examines the association between children of physical activity and sedentary time in school-based same-sex friendship networks, for both moderate-to-vigorous intensity physical activity (MVPA) and sedentary time. Moreover, considering the methodological challenges of conducting and interpreting these analyses, we provide examples of how to analyse these data and interpret results to encourage further work in the area.MethodsAccelerometer data for 1223 children, aged 8-9 years, were collected in 2015-2016 and analysed in 2017. Mean accelerometer minutes of MVPA and sedentary time were calculated. Children named up to four school friends and same-sex school-based friendship networks were constructed. Network models, which include correlation between friends, were fitted by sex.ResultsBoth MVPA and sedentary time were found to be associated via the friendship networks, for both boys and girls. The network autocorrelation was 0.21 (95% CI: 0.15 to 0.26) for boys' MVPA, and 0.14 (95% CI: 0.07 to 0.21) for sedentary time. Network autocorrelation between girls was weaker, with 0.13 (95% CI: 0.06 to 0.19) for MVPA and 0.11 (95% CI: 0.05 to 0.17) for sedentary time.ConclusionsPhysical activity and sedentary time of boys and girls are associated with the physical activity and sedentary time respectively of others within same-sex friendship networks, and these associations are comparable to other known factors. In this study, the correlation between friends was stronger for boys than girls, and stronger for MVPA than for sedentary time. These findings suggest that friendship networks play a part in understanding children's physical activity and sedentary time and could play a valuable role in developing effective interventions.

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US adolescents' friendship networks and health risk behaviors: a systematic review of studies using social network analysis and Add Health data.

Publications

US adolescents' friendship networks and health risk behaviors: a systematic review of studies using social network analysis and Add Health data.

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