Swipe om te navigeren naar een ander artikel
Theories of health behavior change suggest that perceived susceptibility to illness precedes health-protective behavior. We used a cross-lagged panel design to explore the relationship between perceived susceptibility to AIDS, and HIV risk behavior pre-incarceration and post-release in a sample of 499 jail inmates, a group at high risk for HIV. We also explored moderators of this relationship. HIV risk was calculated with a Bernoulli mathematical process model. Controlling for pre-incarceration HIV risk, perceived susceptibility to AIDS predicted less post-release HIV risk; the reverse relationship was not supported. Consistent with health behavior change theories, perceived susceptibility seemed to partially guide behavior. However, this relationship was not true for everyone. African-Americans and individuals high in borderline personality features exhibited no relationship between perceived susceptibility and changes in HIV risk. This suggests that targeted interventions are needed to use information about risk level to prevent HIV contraction.
Log in om toegang te krijgen
Met onderstaand(e) abonnement(en) heeft u direct toegang:
Adams, L. M., Kendall, S., Smith, A., Quigley, E., Stuewig, J. B., & Tangney, J. P. (2011). HIV risk behaviors of male and female jail inmates prior to incarceration and one year post-release. AIDS and Behavior. doi: 10.1007/s10461-011-9990-2.
Becker, M. H. (1974). The health belief model and personal health behavior. Health Education Monographs,2, 324–508.
Carvajal, S. C., Clair, S. D., Nash, S. G., & Evans, R. I. (1998). Relating optimism, hope, and self-esteem to social influences in deterring substance use in adolescents. Journal of Social and Clinical Psychology, 17, 443–465.
Centers for Disease Control and Prevention. (2011). HIV in the United States: An overview.
Centers for Disease Control and Prevention. (2012a). Estimated HIV incidence in the United States, 2007-2010. HIV Surveillance Supplemental Report 2012. (CDC Publication Vol 17, No. 4). Retrieved from http://www.cdc.gov/hiv/surveillance/resources/reports/2010supp_vol17no4/.
Centers for Disease Control and Prevention. (2012b). HIV transmission risk. Retrieved from http://www.cdc.gov/hiv/law/transmission.htm.
Chandler, R. K., Fletcher, B. W., & Volkow, N. D. (2009). Treating drug abuse and addiction in the criminal justice system: Improving public health and safety. Journal of the American Medical Association, 301, 183–190.
Cohen, D. J., & Bruce, K. E. (1997). Sex and mortality: Real risk and perceived vulnerability. Journal of Sex Research, 34, 279–291.
Conn, C., Warden, R., Stuewig, J., Kim, E. H., Harty, L., Hastings, M., & Tangney, J. P. (2010). Borderline Personality Disorder among jail inmates: How common, and how distinct? Corrections Compendium, 4, 6–13.
Enders, C.K., & Bandalos, D.L. (2001). The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Structural Equation Modeling: A Multidisciplinary Journal.
Freudenberg, N. (2006). Coming home from jail: A review of health and social problems facing US jail populations and opportunities for reentry interventions. Washington, DC: Urban Institute.
Hare, R. D. (2003). The hare psychopathy checklist—Revised manual (2nd ed.). Toronto: Multi-Health Systems.
Hart, S. D., Cox, D. N., & Hare, R. D. (1995). The Hare psychopathy checklist: Screening version. Toronto: Multi-Health Systems.
Holtgrave, D. R., Leviton, L., Wagstaff, D. A., & Pinkerton, S. D. (1997). Cumulative probability of HIV infection: A summary risk measure for HIV prevention intervention studies. AIDS and Behavior,1, 169–172. CrossRef
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling,6, 1–55. CrossRef
Jackson, R., Wernicke, R., & Haaga, D. A. F. (2003). Hope as a predictor of entering substance abuse treatment. Addictive Behaviors, 28, 13–28.
Klatt, E.C. (2010). Pathology of AIDS, version 21 (monograph online). Savannah, GA: Mercer University School of Medicine, 2010. Available from: http://library.med.utah.edu/WebPath/TUTORIAL/AIDS/HIV.html.
Margolis, A. D., MacGowan, R., Grinstead, O., Sosman, J., Kashif, I., Flanigan, T. P., & the Project START Study Group. (2006). Unprotected sex with multiple partners: Implications for HIV prevention among young men with a history of incarceration. Sexual Transmitted Diseases, 33, 175–180.
Maruschak, L. M. (2010). Bureau of Justice Statistics Bulletin: HIV in Prisons, 2007–2008. Washington, DC: U.S. Department of Justice.
Morey, L. C. (1991). Personality assessment inventory professional manual. Odessa, FL: Psychological Assessment Resources.
Morrow, K. M., Eldridge, G., Nealey-Moore, J., Grinstead, O., & the Project START Study Group. (2007). HIV, STD, and hepatitis risk in the week following release from prison: An event-level analysis. Journal of Correctional Health Care, 13, 27–38.
Muthén, L. K., & Muthén, B. O. (2010). Mplus user’s guide (6th ed.). Los Angeles, CA: Muthén & Muthén.
Peterson, C., & Seligman, M. E. P. (2003). The values in action (VIA) classification of strengths. Washington, DC: American Psychological Association.
Pinkerton, S. D., & Abramson, P. R. (1993). Evaluating the risks: A Bernoulli process model of HIV infection and risk reduction. Evaluation Review,17, 504–528. CrossRef
Seal, D. W., Eldridge, G. D., Zack, B., & Sosman, J. (2010). HIV testing and treatment within correctional populations: People, not prisoners. Journal of Health Care for the Poor and Underserved, 21, 977–985.
Simpson, D. D. (1997). The measurement of HIV risk behavior. Fort Worth: Texas Christian University, Institute of Behavioral Research.
Simpson, D. D., & Knight, K. (1998). TCU data collection forms for correctional residential treatment. Fort Worth: Texas Christian University, Institute of Behavioral Research.
Singer, M., Dai, H., Weeks, M. R., & Malave, D. (1998). AIDS risk perception among women drug users in Hartford, CT. Women, Drug Use, and HIV Infection,27, 67–85.
Spielberg, F., Branson, B. M., Goldbaum, G. M., Lockhart, D., Kurth, A., Celum, C. L., Rossini, A., Critchlow, C. W., & Wood, R. W. (2003). Overcoming barriers to HIV testing: Preference for new strategies among clients of a needle exchange, a sexually transmitted disease clinic, and sex venues for men who have sex with men. Journal of Acquired Immune Deficiency Syndrome, 32, 318–327.
SPSS for Windows, Version 16.0. (2008). Chicago, IL: SPSS, Inc.
Tempalski, B., Lieb, S., Cleland, C. M., Cooper, H., Brady, J. E., & Friedman, S. R. (2009). HIV prevalence rates among injection drug users in 96 large US metropolitan areas, 1992–2002. Journal of Urban Health, 86, 132–154.
Wood, E., Li, K., Miller, C. L., Hogg, R. S., Montaner, J. S. G., Schechter, M. T. (2005). Baseline self-perceived risk of HIV infection independently predicts the rate of HIV seroconversion in a prospective cohort of injection drug users. International Journal of Epidemiology,34, 152–158. PubMedCrossRef
- Perceived susceptibility to AIDS predicts subsequent HIV risk: a longitudinal evaluation of jail inmates
Leah M. Adams
Jeffrey B. Stuewig
June P. Tangney
Todd B. Kashdan
- Springer US