Norms, Network, HIV Risk Behaviors in Thailand and U.S - Research Proposal Example

NORMS, NETWORK, HIV RISK BEHAVIORS IN THAILAND AND U.S SUMMARY Social Norms, Social Network Characteristics, and HIV Risk Behaviors in Thailand and the United States: Summary [Insert Your First and Last Names] [Insert Name of University] NORMS, NETWORK, HIV RISK BEHAVIORS IN THAILAND AND U.S.: SUMMARY 2 Abstract This presentation is a summary of a study supported by HIV Prevention Trials Network and sponsored by National Institute of Allergy and Infectious Diseases, U.S. Department of Health and others on social norms, network characteristics, and HIV risk behaviors in Thailand and the United States as well as a personal reflection on study’s impact on author’s thinking about human sexuality and /or sexuality education. NORMS, NETWORK, HIV RISK BEHAVIORS IN THAILAND AND U.S.: SUMMARY 3 Social Norms, Social Network Characteristics, and HIV Risk Behaviors in Thailand and the United States: Summary Reference This presentation is a summary of: Latkin, C., Donnell, D., Celentano, D. D., Aramrattna, A., Liu, T-Y, Vongchak, T., Wiboonatakul, K., Vogel, A., & Metzger, D. (2009). Social norms, social network characteristics, and HIV risk behaviors in Thailand and the United States. Health Psychology, 28(3), 323-329. Purpose This study purports to examine structures of social norms pertaining to HIV risk behaviors within social networks and relationship between norms and risk behaviors. Social norms – and change thereof – are instrumental for changes in a number of health behaviors. Still, few studies have examined social structure of norms with an aim to introduce changes in health behaviors. This study examines relationship between norms as perceived by reference group members, associated risk behaviors, and actual norms within drug networks based on a cross-sectional study of injection drug users (IDUs) in Thailand and the United States. Cultural differences are also accounted for. In an attempt to address health behavior change – a change carried out from an individual level to group level – a number of approaches are first discussed. Social diffusion is a health behavior change approach by which “early adaptors” (i.e. individuals who lead behavior change) diffuse new behavior into wider community. Though proving successful in so far as HIV risk reduction is concerned, change leaders approach has not proven significant for behavior change, not to mention identification of involved social networks. A second approach to health behavior change is an introduction of descriptive data on group’s social norms to target audience. Arguably, one critical question pertaining to interventions intended for health behavior change is whether individual perceptions of social norms shape reference group health behavior or reference group’s actual social norms influence individual behaviors. This approach would require individual-based or group-based behavior change interventions depending on which impacts on which, individual or group. In either case, identification of most influential reference group is paramount for social network analysis, a critical tool for examination of structures of social norms. Moreover, certain reference group members are more influential than other group members and hence effectual in health behavior change. Significantly, a network’s structure is fundamental, according to mathematical models, to behavior change. NORMS, NETWORK, HIV RISK BEHAVIORS IN THAILAND AND U.S.: SUMMARY 4 Method Data collection and pool were based on HIV Prevention Trials Network protocol 037. Prior to conduction of study approval of protocols and procedures by Institutional Review Boards at Johns Hopkins University, University of Pennsylvania, the Royal Thai Ministry of Public Health and Chaing Mai University had been secured. An independent advisory board for each site checked on outcomes and consequences. In addition, independent monitors checked and verified regularly on compliance with approved protocols and procedures. Community outreach was used as a means to recruit subjects in both sites. Subjects were compensated $25.00 and $8.50 respectively in Philadelphia and Thailand. “Index” participants were used in recruiting further network members. The latter was not used for recruitment of further participants. General eligibility for participation in study included: age more than 18, a 12-time injection frequency in past 3 months, not enrolled in methadone maintenance treatment in past 3 months, HIV negative, and willingness to identify more network members (for index participants). Participants responded to four descriptive norm questions: (a) “How many of your friends who short drugs use a needle after someone else, without bleaching or clearing?” (b) “How many of your friends who shoot drugs use a cooker that someone else has already used?” (c) “How many of your friends who shoot drugs use filter cotton that someone else has already used?” (d) “How many of your friends who shoot drugs use drugs that are front-loaded or back-loaded with a shared syringe?” Social norms were answered on a 5-point Likort scale ranging from 1 (none) to 5 (all). Separately, participants were asked to respond to four risk behavior questions each dichotomized into any and none: (a) “Did you use a needle after someone else in the last month?” (b) “In the last month, how many times did you use a cooker that others had used?” (c) “In the last month, how many times did you use cotton that others had used?” (d) “In the last month, how many times did you use a front-/back-loaded syringe?” NORMS, NETWORK, HIV RISK BEHAVIORS IN THAILAND AND U.S.: SUMMARY 5 Further, an issue of interest was to weigh social norms of network index against network members. In order to perform such a correlation in both sites (first separately and then combined), two hierarchical models were fit together where in one relationship between network members’ social norms and associated risk behaviors was established and in second indexes’ social norms were incorporated into first model in order to examine which impacts which: individual or group. In both sites, sampling started at 1088 participants but further adjusted at 993 participants upon restricting sample to IDUs by which network members who, exclusively, had sex with index were excluded. Results Compared to Philadelphia participants, participants in Chiang Mai were (significantly) likely to be younger, married, and employed. Overall, study suggests social norms are clustered within social networks of IDUs. Conclusion Significantly, given social norms being clustered within social networks, groups of individuals who encourage risk behaviors should be identified for adequate risk behavior interventions. Further, representative members, by virtue of credibility amongst network members, could be vehicles for behavior change. Descriptive norms within networks were examined. However, impact of prescriptive norms on behavior change remains unknown. Interestingly, association between indexes’ social norms and network members’ syringe sharing was found significant in Philadelphia site compared to lack of association in Thailand, probably due to disruption of injection networks as a result of war on drugs. By way of limitations, study findings are limited by cross-sectional study design and sampling strategy via which not all network members were recruited. Ideally, all network members such as in bounded networks (e.g. classrooms) should be included in any examination of social norms within a specific network. Finally, a greater understanding of social structuring of norms would lead to a design of effective network-based and community-based interventions as well as a sustainable behavior change. NORMS, NETWORK, HIV RISK BEHAVIORS IN THAILAND AND U.S.: SUMMARY 6 Personal Reflection Personally, author believes peer pressure and social networks are not only eye openers to socially stigmatizing diseases such as HIV but are also effective tools for risk behavior change. By extension, similar approached could be considered as regards other sexual diseases since social norms, as study showed, are embedded in social networks and are influential over network members. NORMS, NETWORK, HIV RISK BEHAVIORS IN THAILAND AND U.S.: SUMMARY 7 References Latkin, C., Donnell, D., Celentano, D. D., Aramrattna, A., Liu, T-Y, Vongchak, T., Wiboonatakul, K., Vogel, A., & Metzger, D. (2009). Social norms, social network characteristics, and HIV risk behaviors in Thailand and the United States. Health Psychology, 28(3), 323-329. Read More