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      How "Community" Matters for How People Interact With Information: Mixed Methods Study of Young Men Who Have Sex With Other Men

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          Abstract

          Background

          We lack a systematic portrait of the relationship between community involvement and how people interact with information. Young men who have sex with men (YMSM) are a population for which these relationships are especially salient: their gay community involvement varies and their information technology use is high. YMSM under age 24 are also one of the US populations with the highest risk of HIV/AIDS.

          Objective

          To develop, test, and refine a model of gay community involvement (GCI) factors in human-information interaction (HII) as applied to HIV/AIDS information among YMSM, specifically examining the role of Internet use in GCI and HII.

          Methods

          Mixed methods included: 1) online questionnaire with 194 YMSM; and 2) qualitative interviews with 19 YMSM with high GCI levels. Recruitment utilized social media, dating websites, health clinics, bars/clubs, and public postings. The survey included questions regarding HIV/AIDS–related information acquisition and use patterns, gay community involvement, risk behaviors, and technology use. For survey data, we tested multiple linear regression models using a series of community- and information-related variables as dependent variables. Independent variables included community- and information-related variables and demographic covariates. We then conducted a recursive path analysis in order to estimate a final model, which we refined through a grounded theory analysis of qualitative interview data.

          Results

          Four community-related variables significantly predicted how people interact with information (HII variables): 1) gay community involvement (GCI), 2) social costs of information seeking, 3) network expertise accessibility, and 4) community relevance. GCI was associated with significantly lower perceived social costs of HIV/AIDS information seeking ( R 2 =0.07). GCI and social costs significantly predicted network expertise accessibility ( R 2 =0.14). GCI predicted 14% of the variance in community relevance and 9% of the variance in information seeking frequency. Incidental HIV/AIDS information acquisition (IIA) was also significantly predicted by GCI ( R 2 =0.16). 28% of the variance in HIV/AIDS information use was explained by community relevance, network expertise access, and both IIA and information seeking. The final path model showed good fit: the RSMEA was 0.054 (90% CI: .000-.101); the Chi-square was non-significant (χ 2(11)=17.105; P=.105); and the CFI was 0.967. Qualitative findings suggest that the model may be enhanced by including information sharing: organizing events, disseminating messages, encouraging safety, and referring and recommending. Information sharing emerged under conditions of pro-social community value enactment and may have consequences for further HII. YMSM with greater GCI generally used the Internet more, although they chatted online less.

          Conclusions

          HIV/AIDS–related HII and associated technology uses are community-embedded processes. The model provides theoretical mediators that may serve as a focus for intervention: 1) valuing HIV/AIDS information, through believing it is relevant to one’s group, and 2) supportive and knowledgeable network members with whom to talk about HIV/AIDS. Pro-social community value endorsement and information sharing may also be important theoretical mediators. Our model could open possibilities for considering how informatics interventions can also be designed as community-level interventions and vice versa.

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          Most cited references 95

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          Constructing grounded theory—A practical guide through qualitative analysis

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            Content analysis: An introduction to its methodology

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              Estimated HIV Incidence in the United States, 2006–2009

              Background The estimated number of new HIV infections in the United States reflects the leading edge of the epidemic. Previously, CDC estimated HIV incidence in the United States in 2006 as 56,300 (95% CI: 48,200–64,500). We updated the 2006 estimate and calculated incidence for 2007–2009 using improved methodology. Methodology We estimated incidence using incidence surveillance data from 16 states and 2 cities and a modification of our previously described stratified extrapolation method based on a sample survey approach with multiple imputation, stratification, and extrapolation to account for missing data and heterogeneity of HIV testing behavior among population groups. Principal Findings Estimated HIV incidence among persons aged 13 years and older was 48,600 (95% CI: 42,400–54,700) in 2006, 56,000 (95% CI: 49,100–62,900) in 2007, 47,800 (95% CI: 41,800–53,800) in 2008 and 48,100 (95% CI: 42,200–54,000) in 2009. From 2006 to 2009 incidence did not change significantly overall or among specific race/ethnicity or risk groups. However, there was a 21% (95% CI:1.9%–39.8%; p = 0.017) increase in incidence for people aged 13–29 years, driven by a 34% (95% CI: 8.4%–60.4%) increase in young men who have sex with men (MSM). There was a 48% increase among young black/African American MSM (12.3%–83.0%; p<0.001). Among people aged 13–29, only MSM experienced significant increases in incidence, and among 13–29 year-old MSM, incidence increased significantly among young, black/African American MSM. In 2009, MSM accounted for 61% of new infections, heterosexual contact 27%, injection drug use (IDU) 9%, and MSM/IDU 3%. Conclusions/Significance Overall, HIV incidence in the United States was relatively stable 2006–2009; however, among young MSM, particularly black/African American MSM, incidence increased. HIV continues to be a major public health burden, disproportionately affecting several populations in the United States, especially MSM and racial and ethnic minorities. Expanded, improved, and targeted prevention is necessary to reduce HIV incidence.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                Gunther Eysenbach (JMIR Publications Inc., Toronto, Canada )
                1439-4456
                1438-8871
                February 2013
                21 February 2013
                : 15
                : 2
                Affiliations
                1School of Information University of Michigan Ann Arbor, MIUnited States
                2Department of Health Behavior and Health Education School of Public Health University of Michigan Ann Arbor, MIUnited States
                3HIV/AIDS Resource Center Ypsilanti, MIUnited States
                Author notes
                Corresponding Author: Tiffany Christine Veinot tveinot@ 123456umich.edu
                Article
                v15i2e33
                10.2196/jmir.2370
                3636252
                23428825
                ©Tiffany Christine Veinot, Chrysta Cathleen Meadowbrooke, Jimena Loveluck, Andrew Hickok, Jose Artruro Bauermeister. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 21.02.2013.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

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