A Computational Future for Preventing HIV in Minority Communities
| Autor: | John McManus, Jeanne M. Poduska, Gina M. Wingood, Geoff Sutcliffe, Hilda Pantin, Mitsunori Ogihara, Christopher Mader, Fred Wulczyn, C. Hendricks Brown, Sara J. Czaja, Robert D. Gibbons, David C. Mohr, Juan A. Villamar, Thomas W. Valente, Lawrence A. Palinkas, Carlos Gallo, Sheppard G. Kellam, Christopher Jacobs, Guillermo Prado |
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| Rok vydání: | 2013 |
| Předmět: |
Program evaluation
Knowledge management Computer science Sexual Behavior media_common.quotation_subject Population Psychological intervention Fidelity HIV Infections Health Promotion Computing Methodologies Article Humans Pharmacology (medical) Mobile technology education Social network analysis Minority Groups media_common education.field_of_study business.industry Health Plan Implementation Hispanic or Latino United States Black or African American Intervention (law) Infectious Diseases Systems science business Risk Reduction Behavior Cell Phone Forecasting Program Evaluation |
| Zdroj: | JAIDS Journal of Acquired Immune Deficiency Syndromes. 63:S72-S84 |
| ISSN: | 1525-4135 |
| DOI: | 10.1097/qai.0b013e31829372bd |
| Popis: | African Americans and Hispanics in the U.S. have much higher rates of HIV than non-minorities. There is now strong evidence that a range of behavioral interventions are efficacious in reducing sexual risk behavior in these populations. While a handful of these programs are just beginning to be disseminated widely, we still have not implemented effective programs to a level that would reduce the population incidence of HIV for minorities. We propose that innovative approaches involving computational technologies be explored for their use in both developing new interventions as well as in supporting wide-scale implementation of effective behavioral interventions. Mobile technologies have a place in both of these activities. First, mobile technologies can be used in sensing contexts and interacting to the unique preferences and needs of individuals at times where intervention to reduce risk would be most impactful. Secondly, mobile technologies can be used to improve the delivery of interventions by facilitators and their agencies. Systems science methods, including social network analysis, agent based models, computational linguistics, intelligent data analysis, and systems and software engineering all have strategic roles that can bring about advances in HIV prevention in minority communities. Using an existing mobile technology for depression and three effective HIV prevention programs, we illustrate how eight areas in the intervention/implementation process can use innovative computational approaches to advance intervention adoption, fidelity, and sustainability. |
| Databáze: | OpenAIRE |
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