This approach has been effectively used in schools, for example, as networks are characterized at the classroom level and diffusion of behaviors measured and intervened upon. Social network data, both sociometric and that limited to directed graphs, provide a global view of a social network and its structure, including multiple members’ perspectives, and thus they have great analytic possibilities. they tend to reflect the behaviors of the individuals describing them). These approaches allow one to measure the actual behavior of shared social network members, rather than just an individual’s perception of shared social network members’ behavior, which is known to be differentially biased (i.e. In the case that a complete network is not sampled, collecting data among multiple members of a social network at least allows for the creation of directed graphs, where there can be directionality in the relationships among members of a shared social network. This process can be carried out successively, for as many waves as are needed until saturation of network members and the ties between them are achieved. an index) and then interviewing the social network members that an individual nominates (i.e. Alternatively, social network data can be collected by interviewing an individual (i.e. bounded), rosters can be used to facilitate selecting the sampling frame and identifying connections between social network members. When a social network of interest is complete (i.e. The most comprehensive approach that researchers use to collect data on social networks is termed a sociometric network approach, which involves interviewing multiple members (ideally all members) of a social network. A fundamental tenet in social network analysis is that it incorporates information about relationships between members of a shared social network. Social network analysis is the term applied to a set of theories and methods used to study social interactions between individuals, and how these social interactions influence various outcomes. being pressured by peers to drink alcohol), suggests that this is an area ripe for investigation. selecting drinking buddies as friends) and be influenced by them (e.g. That alcohol consumption can both influence choice of relationships (e.g. Social network analysis can be used to show how peer drinking behavior and patterns of relationships that connect social actors influence an individuals drinking behavior. In this regard, one step beyond looking at individual risk factors is to consider the influence of social networks on alcohol-related outcomes.
Socio-ecological models point to larger social units, ranging from networks to institutional factors, as potential drivers of alcohol use. these studies have limited their focus to psychological or other individual characteristics of alcohol users. Many studies have identified individual-level determinants of alcohol consumption, but. Excessive alcohol consumption additionally places psychological and financial burdens not only on those who engage in these behaviors, but also their families, friends, coworkers and society as a whole. These recent findings are consistent with the well-demonstrated relationship of excessive alcohol consumption to numerous adverse health consequences, and to increased morbidity and mortality worldwide. Risk of all-cause mortality is positively associated with level of alcohol consumption, such that any level of consumption is potentially harmful. Alcohol use is also a leading cause of global disease burden and health loss. In the US, the prevalence of two forms of excessive alcohol consumption, high-risk drinking and alcohol use disorder, have increased substantially in adults over the past decade, such that 1 in every 8 adults report past-year high-risk drinking and the prevalence of lifetime alcohol use disorder is high. Alcohol consumption is prevalent worldwide, with more than 2.4 billion people (33% of the global population) being current drinkers.