Skip to main content
SpringerLink
Log in

Feasibility, Acceptability and Preliminary Efficacy of an Online Peer-to-Peer Social Support ART Adherence Intervention

  • Original Paper
  • Published:
AIDS and Behavior Aims and scope Submit manuscript

Abstract

This study describes the results of an online social support intervention, called “Thrive with Me” (TWM), to improve antiretroviral therapy (ART) adherence. HIV-positive gay or bisexually-identified men self-reporting imperfect ART adherence in the past month were randomized to receive usual care (n = 57) or the eight-week TWM intervention (n = 67). Self-reported ART outcome measures (0–100 % in the past month) were collected at baseline, post-intervention, and 1-month follow-up. Follow-up assessment completion rate was 90 %. Participants rated (1–7 scale) the intervention high in information and system quality and overall satisfaction (Means ≥ 5.0). The intervention showed modest effects for the overall sample. However, among current drug-using participants, the TWM (vs. Control) group reported significantly higher overall ART adherence (90.1 vs. 57.5 % at follow-up; difference = 31.1, p = 0.02) and ART taken correctly with food (81.6 vs. 55.7 % at follow-up; difference = 47.9, p = 0.01). The TWM intervention appeared feasible to implement, acceptable to users, and demonstrated greatest benefits for current drug users.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. The Antiretroviral Therapy Cohort Collaboration. Life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies. Lancet. 2008;372(9635):293–9.

    Article  Google Scholar 

  2. Cohen MS, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365(6):493–505.

    Article  PubMed  CAS  Google Scholar 

  3. Prejean J, et al. Estimated HIV incidence in the United States, 2006–2009. PLoS One. 2011;6(8):e17502.

    Article  PubMed  CAS  Google Scholar 

  4. Centers for Disease Control and Prevention, HIV Surveillance Report: Diagnoses of HIV Infection and AIDS in the United States and Dependent Areas, 2010, 2012.

  5. Mills EJ, et al. Adherence to HAART: a systematic review of developed and developing nation patient-reported barriers and facilitators. PLoS Med. 2006;3(11):e438.

    Article  PubMed  Google Scholar 

  6. Mugavero MJ, et al. Failure to establish HIV care: characterizing the “no show” phenomenon. Clin Infect Dis. 2007;45(1):127–30.

    Article  PubMed  Google Scholar 

  7. Simoni J, et al. Efficacy of interventions in improving highly active antiretroviral therapy adherence and HIV-1 RNA viral load. A meta-analytic review of randomized controlled trials. J Acquir Immune Defic Syndr. 2006;43(Suppl 1):S23–35.

    Article  PubMed  Google Scholar 

  8. Simoni J, et al. Antiretroviral adherence interventions: a review of current literature and ongoing studies. Top HIV Med. 2003;11(6):185–98.

    PubMed  Google Scholar 

  9. Thompson MA, et al. Guidelines for improving entry into and retention in care and antiretroviral adherence for persons with HIV: evidence-based recommendations from an international association of physicians in AIDS care panel. Ann Intern Med. 2012;156(11):817–33.

    Article  PubMed  Google Scholar 

  10. Saberi P, Johnson MO. Technology-based self-care methods of improving antiretroviral adherence: a systematic review. PLoS One. 2011;6(11):e27533.

    Article  PubMed  CAS  Google Scholar 

  11. Page TF, et al. A cost analysis of an internet-based medication adherence intervention for people living with HIV. J Acquir Immune Defic Syndr. 2012;60(1):1–4.

    Article  PubMed  Google Scholar 

  12. Pellowski JA, Kalichman SC. Recent advances (2011–2012) in technology-delivered interventions for people living with HIV. Curr HIV/AIDS Rep. 2012;9(4):326–34.

    Article  PubMed  Google Scholar 

  13. Fisher JD, et al. Computer-based intervention in HIV clinical care setting improves antiretroviral adherence: the LifeWindows project. AIDS Behav. 2011;15(8):1635–46.

    Article  PubMed  Google Scholar 

  14. Portnoy DB, et al. Computer-delivered interventions for health promotion and behavioral risk reduction: a meta-analysis of 75 randomized controlled trials, 1988–2007. Prev Med. 2008;47(1):3–16.

    Article  PubMed  Google Scholar 

  15. Noar SM, Black HG, Pierce LB. Efficacy of computer technology-based HIV prevention interventions: a meta-analysis. AIDS. 2009;23(1):107–15.

    Article  PubMed  Google Scholar 

  16. Madden M, Zickuhr K. 65 % of online adults use social networking sites. 2011. http://pewinternet.org/Reports/2011/Social-Networking-Sites.aspx, Pew Research Center: Washington DC.

  17. Fox S. Peer-to-peer healthcare: many people-especially those living with chronic or rare diseases-use online connections to supplement professional medical advice. Washington DC: Pew Research Center’s Internet & American Life Project; 2011.

    Google Scholar 

  18. Horvath K, et al. Technology use and reasons to participate in social networking health websites among people living with HIV in the US. AIDS Behav. 2012;16(4):900–10.

    Article  PubMed  Google Scholar 

  19. Rosser BS, et al. Reducing HIV risk behavior of men who have sex with men through persuasive computing: results of the Men’s INTernet Study-II. AIDS. 2010;24(13):2099–107.

    Article  PubMed  Google Scholar 

  20. Potosky D. The internet knowledge (iKnow) measure. Comput Hum Behav. 2007;23(6):2760–77.

    Article  Google Scholar 

  21. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1992;1:385–401.

    Article  Google Scholar 

  22. Zhang W, et al. Validating a shortened depression scale (10 item CES-D) among HIV-positive people in British Columbia, Canada. PLoS One. 2012;7(7):e40793.

    Article  PubMed  CAS  Google Scholar 

  23. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24:385–96.

    Article  PubMed  CAS  Google Scholar 

  24. Wong MD, et al. The association between life chaos, health care use, and health status among HIV-infected persons. J Gen Intern Med. 2007;22(9):1286–91.

    Article  PubMed  Google Scholar 

  25. Emlet CA. Measuring stigma in older and younger adults with HIV/AIDS: an analysis of an HIV stigma scale and initial exploration of subscales. Res Soc Work Pract. 2005;15:291–300.

    Article  Google Scholar 

  26. Saunders JB, et al. Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption–II. Addiction. 1993;88(6):791–804.

    Article  PubMed  CAS  Google Scholar 

  27. DeLone WH, McLean ER. The DeLone and McLean model of information systems success: a ten-year update. J Manag Inf Syst. 2003;19(4):9–30.

    Google Scholar 

  28. DeLone WH, McLean ER. Information systems success: the quest for the dependent variable. Inf Syst Res. 1992;3(1):60–95.

    Article  Google Scholar 

  29. Simoni J, et al. Self-report measures of antiretroviral therapy adherence: a review with recommendations for HIV research and clinical management. AIDS Behav. 2006;10(3):227–45.

    Article  PubMed  Google Scholar 

  30. Walsh JC, Mandalia S, Gazzard BG. Responses to a 1 month self-report on adherence to antiretroviral therapy are consistent with electronic data and virological treatment outcome. AIDS. 2002;16(2):269–77.

    Article  PubMed  Google Scholar 

  31. Begg C, et al. Improving the quality of reporting of randomized controlled trials. The CONSORT statement. JAMA. 1996;276(8):637–9.

    Article  PubMed  CAS  Google Scholar 

  32. Dimitrov DM, Rumrill PD Jr. Pretest-posttest designs and measurement of change. Work. 2003;20(2):159–65.

    PubMed  Google Scholar 

  33. Gottman JM, Rushe RH. The analysis of change: issues, fallacies, and new ideas. J Consult Clin Psychol. 1993;61(6):907–10.

    Article  PubMed  CAS  Google Scholar 

  34. Bangsberg DR, et al. Non-adherence to highly active antiretroviral therapy predicts progression to AIDS. AIDS. 2001;15(9):1181–3.

    Article  PubMed  CAS  Google Scholar 

  35. Pasternak AO, et al. Modest non-adherence to antiretroviral therapy promotes residual HIV-1 replication in the absence of virological rebound in plasma. J Infect Dis. 2012;206(9):1443–52.

    Article  PubMed  CAS  Google Scholar 

  36. Rivet Amico K, Harman JJ, Johnson BT. Efficacy of antiretroviral therapy adherence interventions: a Research Synthesis of Trials, 1996 to 2004. J Acquir Immune Defic Syndr. 2006;41(3):285–97.

    Article  PubMed  Google Scholar 

  37. Anderson PL, et al. Emtricitabine-tenofovir concentrations and pre-exposure prophylaxis efficacy in men who have sex with men. Sci Transl Med. 2012;4(151):151ra125.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

We wish to thank the participants of this study for their time and effort. We also thank Tony Miles at the Positive Project for allowing us to use segments from their video archive for the purpose of this study. This study was funded by the National Institute of Mental Health (5R34MH083549).

Author information

Authors and Affiliations

  1. Center for AIDS Intervention Research, Medical College of Wisconsin, 2071 N. Summit Ave., Milwaukee, WI, 53202, USA

    Keith J. Horvath

  2. Division of Epidemiology and Community Health Education, University of Minnesota, Minneapolis, MN, USA

    J. Michael Oakes & B. R. Simon Rosser

  3. Xerebral Inc., Minneapolis, MN, USA

    Gene Danilenko

  4. Children’s Hospital of Philadelphia Research Institute, University of Pennsylvania, Philadelphia, PA, USA

    Heather Vezina

  5. Center for Health Intervention and Prevention, University of Connecticut, Storrs, CT, USA

    K. Rivet Amico

  6. Department of Health Policy and Management, Florida International University, Miami, FL, USA

    Mark L. Williams

  7. Department of Psychology, University of Washington, Seattle, WA, USA

    Jane Simoni

Authors
  1. Keith J. Horvath
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Michael Oakes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. B. R. Simon Rosser
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gene Danilenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Heather Vezina
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. K. Rivet Amico
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mark L. Williams
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jane Simoni
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Keith J. Horvath.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Horvath, K.J., Michael Oakes, J., Simon Rosser, B.R. et al. Feasibility, Acceptability and Preliminary Efficacy of an Online Peer-to-Peer Social Support ART Adherence Intervention. AIDS Behav 17, 2031–2044 (2013). https://doi.org/10.1007/s10461-013-0469-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10461-013-0469-1

Keywords

Search

Navigation