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dc.contributor.authorTakadaa, Sae
dc.contributor.authorNyakato, Viola
dc.contributor.authorNishi, Akihiro
dc.contributor.authorO'Malley, A. James
dc.contributor.authorKakuhikire, Bernard
dc.contributor.authorPerkins, Jessica M.
dc.contributor.authorBangsbergh, David R.
dc.contributor.authorChristakisi, Nicholas A.
dc.contributor.authorTsai, Alexander C.
dc.date.accessioned2021-06-02T07:12:33Z
dc.date.available2021-06-02T07:12:33Z
dc.date.issued2019
dc.identifier.citationTakada, S., Nyakato, V., Nishi, A., O'Malley, A. J., Kakuhikire, B., Perkins, J. M., ... & Tsai, A. C. (2019). The social network context of HIV stigma: Population-based, sociocentric network study in rural Uganda. Social Science & Medicine, 233, 229-236.en_US
dc.identifier.urihttp://ir.must.ac.ug/xmlui/handle/123456789/899
dc.description.abstractRationale: HIV-related stigma profoundly affects the physical and social wellbeing of people living with HIV, as well as the community’s engagement with testing, treatment, and prevention. Based on theories of stigma elaborating how it arises from the relationships between the stigmatized and the stigmatizer as well as within the general community, we hypothesized that social networks can shape HIV-related stigma. Objective: To estimate social network correlates of HIV-related stigma. Methods: During 2011-2012, we collected complete social network data from a community of 1669 adults (“egos”) in Mbarara, Uganda using six culturally-adapted name generators to elicit different types of social ties (“alters”). We measured HIV-related stigma using the 9-item AIDS-Related Stigma Scale. HIV serostatus was based on self-report. We fitted linear regression models that account for network autocorrelation to estimate the association between egos’ HIV-related stigma, alters’ HIV-related stigma and alters’ self-reported HIV serostatus, while adjusting for egos’ HIV serostatus, network centrality, village size, perceived HIV prevalence, and sociodemographic characteristics. Results: The average AIDS-Related Stigma Score was 0.79 (Standard Deviation=0.50). In the population 116 (7%) egos reported being HIV-positive, and 757 (46%) reported an HIV-positive alter. In the multivariable model, we found that egos’ own HIV-related stigma was positively correlated with their alters’ average stigma score (b=0.53; 95% confidence interval [CI] 0.42-0.63) and negatively correlated with having one or more HIV-positive alters (b=-0.05; 95% CI -0.10 to -0.003). Conclusion: Stigma-reduction interventions should be targeted not only at the level of the individual but also at the level of the network. Directed and meaningful contact with people living with HIV may also reduce HIV-related stigmaen_US
dc.language.isoen_USen_US
dc.publisherSocial Science & Medicineen_US
dc.subjectPopulation-baseden_US
dc.subjectNetworken_US
dc.subjectHIV stigmaen_US
dc.subjectUgandaen_US
dc.titleThe social network context of HIV stigma: Population-based, sociocentric network study in rural Ugandaen_US
dc.typeArticleen_US


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