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Community norms for HIV risk behaviors among men in a South African township. 2011

Kate B Carey, and Lori A J Scott-Sheldon, and Michael P Carey, and Demetria Cain, and Regina Mlobeli, and Redwaan Vermaak, and Jacqueline Mthembu, and Leickness C Simbayi, and Seth C Kalichman
Center for Health and Behavior, Syracuse University, 430 Huntington Hall, Syracuse, NY 13244-2340, USA.

We investigated alcohol-related sexual risk behavior from the perspective of social norms theory. Adults (N = 895, 62% men) residing in a South African township completed street-intercept surveys that assessed risk and protective behaviors (e.g., multiple partners, drinking before sex, meeting sex partners in shebeens, condom use) and corresponding norms. Men consistently overestimated the actual frequency of risky behaviors, as reported by the sample, and underestimated the frequency of condom use. Relative to actual attitudes, men believed that other men were more approving of risk behavior and less approving of condom use. Both behavioral and attitudinal norms predicted the respondents' self-reported risk behavior. These findings indicate that correcting inaccurate norms in HIV-risk reduction efforts is worthwhile.

UI MeSH Term Description Entries
D007722 Health Knowledge, Attitudes, Practice Knowledge, attitudes, and associated behaviors which pertain to health-related topics such as PATHOLOGIC PROCESSES or diseases, their prevention, and treatment. This term refers to non-health workers and health workers (HEALTH PERSONNEL). Knowledge, Attitudes, Practice
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000293 Adolescent A person 13 to 18 years of age. Adolescence,Youth,Adolescents,Adolescents, Female,Adolescents, Male,Teenagers,Teens,Adolescent, Female,Adolescent, Male,Female Adolescent,Female Adolescents,Male Adolescent,Male Adolescents,Teen,Teenager,Youths
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly

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