Cell phone availability and usage for mobile health and intervention delivery to persons living with HIV in a low-resource setting. (Preprint)

Author:

Adong JulianORCID,Fatch Robin,Emenyonu Nneka,Muyindike Winnie,Ngabirano Christine,Cheng Debbie,Hahn Judith

Abstract

BACKGROUND

HIV/AIDS is now a chronic illness due to effective antiretroviral therapy (ART) and involves routine follow-up care, including regular physical visits to the clinic. In the recent past, and in wake of the COVID-19 pandemic, there has been increased need for virtual care and intervention delivery, a modality known as mHealth, which includes cell phone-delivered services

OBJECTIVE

Here we describe cell phone use and its relationship with alcohol use in a cohort of persons with HIV (PWH) and latent tuberculosis (TB).

METHODS

We performed a cross-sectional analysis of baseline data from a cohort of PWH and latent TB in HIV care in south-western Uganda. We estimated proportions of cell phone and text message use and evaluated their associations with alcohol use, a common modifiable behaviour among PWH. Cell phone use (primary outcome) was defined as owning a cell phone that is turned on at least half of the day. Any alcohol use was defined as any self-reported alcohol use in the prior 3 months, and/or phosphatidylethanol (an alcohol biomarker) ≥8 ng/ml.

RESULTS

A total of 300 participants were included in the analysis, with a median age of 40 years; 48.7% were male. Majority (89.0%) of participants had access to a phone and of these 9.7% shared the phone with someone else. Eighty-seven percent owned a cell phone that is turned on at least half of the time; the majority (89.7%) rarely or never sent text messages, and over two-thirds (66.9%) rarely or never received text messages. 71.3% had any alcohol use. In adjusted analyses, any alcohol use was not significantly associated with cell phone use (adjusted OR [aOR]: 0.48, 95% confidence interval [CI]: 0.18-1.25, p-value=.13), or sending (aOR: 0.82, 95% CI: 0.28-2.37, p-value=.71) or receiving (aOR: 1.31, 95% CI: 0.70-2.47, p-value= .40) of text messages.

CONCLUSIONS

There is hope that mHealth interventions in this population can be carried out using cell phones due to their popularity; however, the interventions may need to employ methods that do not rely on the sending and receiving of text messages only.

CLINICALTRIAL

NCT 03302299

Publisher

JMIR Publications Inc.

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