Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Jun 1;19(6):e190.
doi: 10.2196/jmir.6631.

Mobile Text Messaging to Improve Medication Adherence and Viral Load in a Vulnerable Canadian Population Living With Human Immunodeficiency Virus: A Repeated Measures Study

Elizabeth King  1 , Karen Kinvig  2 , Jonathan Steif  3 , Annie Q Qiu  2 , Evelyn J Maan  2 , Arianne Yk Albert  4 , Neora Pick  2   4   5 , Ariane Alimenti  2   6 , Mary H Kestler  2   5 , Deborah M Money  2   4   7 , Richard T Lester  5 , Melanie Caroline Margaret Murray  2   4   5
Affiliations

Mobile Text Messaging to Improve Medication Adherence and Viral Load in a Vulnerable Canadian Population Living With Human Immunodeficiency Virus: A Repeated Measures Study

Elizabeth King et al. J Med Internet Res. .

Abstract

Background: Combination antiretroviral therapy (cART) as treatment for human immunodeficiency virus (HIV) infection is effective and available, but poor medication adherence limits benefits, particularly in vulnerable populations. In a Kenyan randomized controlled trial, a weekly text-messaging intervention (WelTel) improved cART adherence and HIV viral load (VL). Despite growing evidence for short message service (SMS) text-message interventions in HIV care, there is a paucity of data utilizing these interventions in marginalized or female cohorts.

Objective: This study was undertaken to assess whether the standardized WelTel SMS text-message intervention applied to a vulnerable, predominantly female, population improved cART adherence and VL.

Methods: We conducted a repeated measures study of the WelTel intervention in high-risk HIV-positive persons by measuring change in VL, CD4 count, and self-reported adherence 12 months before and 12 months after the WelTel intervention was introduced. Inclusion criteria included VL ≥200 copies/mL, indication for treatment, and meeting vulnerability criteria. Participants were given a mobile phone with unlimited texting (where required), and weekly check-in text messages were sent for one year from the WelTel computer platform. Clinical data were collected for control and intervention years. Participants were followed by a multidisciplinary team in a clinical setting. Outcomes were assessed using Wilcoxon signed ranks tests for change in CD4 and VL from control year to study end and mixed-effects logistic regressions for change in cART adherence and appointment attendance. A secondary analysis was conducted to assess the effect of response rate on the outcome by modeling final log10 VL by number of responses while controlling for mean log10 VL in the control year.

Results: Eighty-five participants enrolled in the study, but 5 withdrew (final N=80). Participants were predominantly female (90%, 72/80) with a variety of vulnerabilities. Mean VL decreased from 1098 copies/mL in the control year to 439 copies/mL at study end (P=.004). Adherence to cART significantly improved (OR 1.14, IQR 1.10-1.18; P<.001), whereas appointment attendance decreased slightly with the intervention (OR 0.81, IQR 0.67-0.99; P=.03). A response was received for 46.57% (1753/3764) of messages sent and 9.62% (362/3764) of text messages sent were replied to with a problem. An outcome analysis examining relationship between reply rate and VL did not meet statistical significance (P=.07), but may be worthy of investigating further in a larger study.

Conclusions: WelTel may be an effective tool for improving cART adherence and reducing VLs among high-risk, vulnerable HIV-positive persons.

Trial registration: Clinicaltrials.gov NCT02603536; https://clinicaltrials.gov/ct2/show/NCT02603536 (Archived by WebCite at http://www.webcitation.org/6qK57zCwv).

Keywords: HIV; engagement; female; mHealth; medication adherence; mobile phone; viral load; vulnerable.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: Dr Richard Lester is the founder of WelTel, the text-messaging platform used in this study. The technology platform was developed by a nonprofit organization, WelTel mHealth Society, and a private company, WelTel Incorporated. Dr Richard Lester has financial as well as professional interests in both organizations. All other authors declare no conflict of interest.

Figures

Figure 1
Figure 1
CONSORT flow diagram of trial.
Figure 2
Figure 2
Boxplot of mean log10 VL in the control year compared to the log10 VL at study end. The black bars indicate the medians; boxes indicate the interquartile range and the whiskers extend to 1.5× the interquartile range. There was a significant decrease in log10 VL after the intervention (P=.004).
Figure 3
Figure 3
Boxplot of the mean CD4 in the control year compared to the mean CD4 at the study end. The black bars indicate the medians; boxes indicate the interquartile range and the whiskers extend to 1.5× the interquartile range. There was no significant change in CD4 after study intervention.
Figure 4
Figure 4
Rate of health care provider involvement for all “problems” identified by SMS text message after assessment by study nurse.
Figure 5
Figure 5
Proportion of weekly SMS text-message response types throughout the intervention.
Figure 6
Figure 6
Final log10 VL by number of SMS text-message responses in the intervention year. The solid line indicates predictions from the regression for median control year log10 VL (median 2.88). The dashed lines indicate the 95% CI around the regression estimate.
See this image and copyright information in PMC

References

    1. Public Health Agency of Canada . Summary: Estimates of HIV Incidence, Prevalence and Prorportion Undiagnosed in Canada, 2014. Ottawa, ON: Public Health Agency of Canada; 2015. Nov, [2017-02-26]. http://www.catie.ca/sites/default/files/2014-HIV-Estimates-in-Canada-EN.pdf 6oYWkC4PM.
    1. Montaner JS, Hogg R, Wood E, Kerr T, Tyndall M, Levy AR, Harrigan PR. The case for expanding access to highly active antiretroviral therapy to curb the growth of the HIV epidemic. Lancet. 2006 Aug 5;368(9534):531–536. doi: 10.1016/S0140-6736(06)69162-9. - DOI - PubMed
    1. Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, Hakim JG, Kumwenda J, Grinsztejn B, Pilotto JH, Godbole SV, Mehendale S, Chariyalertsak S, Santos BR, Mayer KH, Hoffman IF, Eshleman SH, Piwowar-Manning E, Wang L, Makhema J, Mills LA, de Bruyn G, Sanne I, Eron J, Gallant J, Havlir D, Swindells S, Ribaudo H, Elharrar V, Burns D, Taha TE, Nielsen-Saines K, Celentano D, Essex M, Fleming TR, HPTN 052 Study Team Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011 Aug 11;365(6):493–505. doi: 10.1056/NEJMoa1105243. http://europepmc.org/abstract/MED/21767103 - DOI - PMC - PubMed
    1. Dube S, Boily M, Mugurungi O, Mahomva A, Chikhata F, Gregson S. Estimating vertically acquired HIV infections and the impact of the prevention of mother-to-child transmission program in Zimbabwe: insights from decision analysis models. J Acquir Immune Defic Syndr. 2008 May 1;48(1):72–81. doi: 10.1097/QAI.0b013e31816bcdbb. - DOI - PubMed
    1. Bangsberg DR, Perry S, Charlebois ED, Clark RA, Roberston M, Zolopa AR, Moss A. Non-adherence to highly active antiretroviral therapy predicts progression to AIDS. AIDS. 2001 Jun 15;15(9):1181–1183. - PubMed

Associated data