Preliminary Evidence for Feasibility, Use, and Acceptability of Individualized Texting for Adherence Building for Antiretroviral Adherence and Substance Use Assessment among HIV-Infected Methamphetamine Users

David J Moore, Jessica L Montoya, Kaitlin Blackstone, Alexandra Rooney, Ben Gouaux, Shereen Georges, Colin A Depp, J Hampton Atkinson, The Tmarc Group, David J Moore, Jessica L Montoya, Kaitlin Blackstone, Alexandra Rooney, Ben Gouaux, Shereen Georges, Colin A Depp, J Hampton Atkinson, The Tmarc Group

Abstract

The feasibility, use, and acceptability of text messages to track methamphetamine use and promote antiretroviral treatment (ART) adherence among HIV-infected methamphetamine users was examined. From an ongoing randomized controlled trial, 30-day text response rates of participants assigned to the intervention (individualized texting for adherence building (iTAB), n = 20) were compared to those in the active comparison condition (n = 9). Both groups received daily texts assessing methamphetamine use, and the iTAB group additionally received personalized daily ART adherence reminder texts. Response rate for methamphetamine use texts was 72.9% with methamphetamine use endorsed 14.7% of the time. Text-derived methamphetamine use data was correlated with data from a structured substance use interview covering the same time period (P < 0.05). The iTAB group responded to 69.0% of adherence reminder texts; among those responses, 81.8% endorsed taking ART medication. Standardized feedback questionnaire responses indicated little difficulty with the texts, satisfaction with the study, and beliefs that future text-based interventions would be helpful. Moreover, most participants believed the intervention reduced methamphetamine use and improved adherence. Qualitative feedback regarding the intervention was positive. Future studies will refine and improve iTAB for optimal acceptability and efficacy. This trial is registered with ClinicalTrials.gov NCT01317277.

Figures

Figure 1
Figure 1
Response patterns for (a) medication adherence reminder text messages and (b) methamphetamine-use text messages. Note: ∗ Sample size represents number of messages sent to participants not the number of participants on study.

References

    1. Kaplan RM, Stone AA. Bringing the laboratory and clinic to the community: mobile technologies for health promotion and disease prevention. Annual Review of Psychology. 2013;64:471–498.
    1. Heron KE, Smyth JM. Ecological momentary interventions: Incorporating mobile technology into psychosocial and health behaviour treatments. British Journal of Health Psychology. 2010;15(1):1–39.
    1. Krishna S, Boren SA, Balas EA. Healthcare via cell phones: a systematic review. Telemedicine and e-Health. 2009;15(3):231–240.
    1. Free C, Whittaker R, Knight R, Abramsky T, Rodgers A, Roberts IG. Txt2stop: a pilot randomised controlled trial of mobile phone-based smoking cessation support. Tobacco Control. 2009;18(2):88–91.
    1. Rodgers A, Corbett T, Bramley D, et al. Do u smoke after txt? Results of a randomised trial of smoking cessation using mobile phone text messaging. Tobacco Control. 2005;14(4):255–261.
    1. Nachega JB, Hislop M, Dowdy DW, Chaisson RE, Regensberg L, Maartens G. Adherence to nonnucleoside reverse transcriptase inhibitor-based HIV therapy and virologic outcomes. Annals of Internal Medicine. 2007;146(8):564–573.
    1. Perienti J-J, Massari V, Descamps D, et al. Predictors of virologic failure and resistance in HIV-infected patients treated with nevirapine- or efavirenz-based antiretroviral therapy. Clinical Infectious Diseases. 2004;38(9):1311–1316.
    1. Hardy H, Kumar V, Doros G, et al. Randomized controlled trial of a personalized cellular phone reminder system to enhance adherence to antiretroviral therapy. AIDS Patient Care and STDs. 2011;25(3):153–161.
    1. Lester RT, Ritvo P, Mills EJ, et al. Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial. The Lancet. 2010;376(9755):1838–1845.
    1. Pop-Eleches C, Thirumurthy H, Habyarimana JP, et al. Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a randomized controlled trial of text message reminders. AIDS. 2011;25(6):825–834.
    1. Ybarra ML, Bull SS. Current trends in Internet-and cell phone-based HIV prevention and intervention programs. Current HIV/AIDS Reports. 2007;4(4):201–207.
    1. Hinkin CH, Barclay TR, Castellon SA, et al. Drug use and medication adherence among HIV-1 infected individuals. AIDS and Behavior. 2007;11(2):185–194.
    1. Marquez C, Mitchell SJ, Hare CB, John M, Klausner JD. Methamphetamine use, sexual activity, patient-provider communication, and medication adherence among HIV-infected patients in care, San Francisco 2004–2006. AIDS Care. 2009;21(5):575–582.
    1. McClure EA, Acquavita SP, Harding E, Stitzer ML. Utilization of communication technology by patients enrolled in substance abuse treatment. Drug and Alcohol Dependence. 2013;129(1-2):145–150.
    1. Marsch LA, Dallery J. Advances in the psychosocial treatment of addiction: the role of technology in the delivery of evidence-based psychosocial treatment. Psychiatric Clinics of North America. 2012;35(2):481–493.
    1. Boyer EW, Smelson D, Fletcher R, Ziedonis D, Picard RW. Wireless technologies, ubiquitous computing and mobile health: application to drug abuse treatment and compliance with HIV therapies. Journal of Medical Toxicology. 2010;6(2):212–216.
    1. Colfax G, Shoptaw S. The methamphetamine epidemic: implications for HIV prevention and treatment. Current HIV/AIDS Reports. 2005;2(4):194–199.
    1. Gibson DR, Leamon MH, Flynn N. Epidemiology and public health consequences of methamphetamine use in California’s Central Valley. Journal of Psychoactive Drugs. 2002;34(3):313–319.
    1. Halkitis PN, Green KA, Carragher DJ. Methamphetamine use, sexual behavior, and HIV seroconversion. Journal of Gay and Lesbian Psychotherapy. 2006;10(3-4):95–109.
    1. Hinkin CH, Hardy DJ, Mason KI, et al. Medication adherence in HIV-infected adults: effect of patient age, cognitive status, and substance abuse. AIDS. 2004;18(supplement 1):S19–S25.
    1. Ellis RJ, Childers ME, Cherner M, Lazzaretto D, Letendre S, Grant I. Increased human immunodeficiency virus loads in active methamphetamine users are explained by reduced effectiveness of antiretroviral therapy. Journal of Infectious Diseases. 2003;188(12):1820–1826.
    1. Moore DJ, Blackstone K, Woods SP, et al. Methamphetamine use and neuropsychiatric factors are associated with antiretroviral non-adherence. AIDS Care. 2012;24(12):1504–1513.
    1. Gifford AL, Bormann JE, Shively MJ, Wright BC, Richman DD, Bozzette SA. Predictors of self-reported adherence and plasma HIV concentrations in patients on multidrug antiretroviral regimens. Journal of Acquired Immune Deficiency Syndromes. 2000;23(5):386–395.
    1. Hinkin CH, Castellon SA, Durvasula RS, et al. Medication adherence among HIV+ adults: effects of cognitive dysfunction and regimen complexity. Neurology. 2002;59(12):1944–1950.
    1. Hirsch MS, Brun-Vézinet F, D’Aquila RT, et al. Antiretroviral drug resistance testing in adult HIV-1 infection: recommendations of an international AIDS society-USA panel. Journal of the American Medical Association. 2000;283(18):2417–2426.
    1. Collins LM, Murphy SA, Strecher V. The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. American Journal of Preventive Medicine. 2007;32(5, supplement):S112–S118.
    1. Collins LM, Murphy SA, Nair VN, Strecher VJ. A strategy for optimizing and evaluating behavioral interventions. Annals of Behavioral Medicine. 2005;30(1):65–73.
    1. Riley WT, Glasgow RE, Etheredge L, Abernethy AP. Rapid, responsive, relevant (R3) research: a call for a rapid learning health research enterprise. Clinical and Translational Medicine. 2013;2(1):p. 10.
    1. World Health Organization. Composite International Diagnostic Interview (CIDI, Version 2.1) Geneva, Switzerland: World Health Organization; 1997.
    1. Moore DJ, Posada C, Parikh M, et al. HIV-infected individuals with co-occurring bipolar disorder evidence poor antiretroviral and psychiatric medication adherence. AIDS and Behavior. 2012;16(8):2257–2266.
    1. Montoya JL, Georges S, Poquette A, Depp CA, Atkinson JH, Moore DJ. Developing content for a mobile medication adherence intervention for HIV+ methamphetamine users. (under review)
    1. Johnson MO, Catz SL, Remien RH, et al. Theory-guided, empirically supported avenues for intervention on HIV medication nonadherence: findings from the Healthy Living Project. AIDS Patient Care and STDs. 2003;17(12):645–656.
    1. Roberts KJ. Barriers to and facilitators of HIV-positive patients’ adherence to antiretroviral treatment regimens. AIDS Patient Care and STDs. 2000;14(3):155–168.
    1. Hser Y-I, Anglin MD, Chou C-P. Reliability of retrospective self-report by narcotics addicts. Psychological Assessment. 1992;4(2):207–213.
    1. Phillips KA, Epstein DH, Preston KL. Daily temporal patterns of heroin and cocaine use and craving: relationship with business hours regardless of actual employment status. Addictive Behaviors. 2013;38(10):2485–2491.
    1. Rippeth JD, Heaton RK, Carey CL, et al. Methamphetamine dependence increases risk of neuropsychological impairment in HIV infected persons. Journal of the International Neuropsychological Society. 2004;10(1):1–14.
    1. Thirumurthy H, Lester RT. M-health for health behaviour change in resource-limited settings: applications to HIV care and beyond. Bulletin of the World Health Organization. 2012;90(5):390–392.
    1. Yang X, Li J, Shoptaw S. Imputation-based strategies for clinical trial longitudinal data with nonignorable missing values. Statistics in Medicine. 2008;27(15):2826–2849.

Source: PubMed

Szponzorok és közreműködők

Egészségi állapot

Kábítószer-beavatkozások

3
Iratkozz fel