Publication Cover
AIDS Care
Psychological and Socio-medical Aspects of AIDS/HIV
Volume 23, 2011 - Issue 5
793
Views
70
CrossRef citations to date
0
Altmetric
ORIGINAL ARTICLES

Computer technology-based interventions in HIV prevention: state of the evidence and future directions for research

Pages 525-533 | Received 27 Apr 2010, Published online: 31 Jan 2011
 

Abstract

Computer technology-based interventions (CBIs) represent a promising area for HIV prevention behavioral intervention research. Such programs are a compelling prevention option given their potential for broad reach, customized content, and low cost delivery. The purpose of the current article is to provide a review of the state of the literature on CBIs. First, we define CBIs in HIV prevention and highlight the many advantages of such interventions. Next, we provide an overview of what is currently known regarding the efficacy of CBIs in HIV prevention, focusing on two recent meta-analyses of this literature. Finally, we propose an agenda for future directions for research in the area of CBIs, using the RE-AIM model as an organizing guide. We conclude that with the continued growth of computer technologies, opportunities to apply such technologies in HIV prevention will continue to blossom. Further research is greatly needed to advance an understanding of not only how and under what circumstances CBIs can be efficacious, but also how the reach, adoption, implementation, and maintenance of such programs in clinical and community settings can be achieved.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 464.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.