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Toward understanding the impact of mHealth features for people with HIV: a latent class analysis of PositiveLinks usage.

ABSTRACT: PositiveLinks (PL) is a multi-feature smartphone-based platform to improve engagement-in-care and viral suppression (VS) among clinic patients living with HIV. Features include medication reminders, mood/stress check-ins, a community board, and secure provider messaging. Our goal was to examine how PL users interact with the app and determine whether usage patterns correlate with clinical outcomes. Patients (N = 83) at a university-based Ryan White clinic enrolled in PL from June 2016 to March 2017 and were followed for up to 12 months. A subset (N = 49) completed interviews after 3 weeks of enrollment to explore their experiences with and opinions of PL. We differentiated PL members based on 6-month usage of app features using latent class analysis. We explored characteristics associated with class membership, compared reported needs and preferences by class, and examined association between class and VS. The sample of 83 PL members fell into four classes. "Maximizers" used all app features frequently (27%); "Check-in Users" tended to interact only with daily queries (22%); "Moderate All-Feature Users" used all features occasionally (33%); and "As-Needed Communicators" interacted with the app minimally (19%). VS improved or remained high among all classes after 6 months. VS remained high at 12 months among Maximizers (baseline and 12-month VS: 100%, 94%), Check-in Users (82%, 100%), and Moderate All-Feature Users (73%, 94%) but not among As-Needed Communicators (69%, 60%). This mixed-methods study identified four classes based on PL usage patterns that were distinct in characteristics and clinical outcomes. Identifying and characterizing mHealth user classes offers opportunities to tailor interventions appropriately based on patient needs and preferences as well as to provide targeted alternative support to achieve clinical goals.

SUBMITTER: Canan CE

PROVIDER: S-EPMC7877298 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Toward understanding the impact of mHealth features for people with HIV: a latent class analysis of PositiveLinks usage.

Canan Chelsea E CE Flickinger Tabor E TE Waselewski Marika M Tabackman Alexa A Baker Logan L Eger Samuel S Waldman Ava Lena D ALD Ingersoll Karen K Dillingham Rebecca R

Translational behavioral medicine 20210201 1

PositiveLinks (PL) is a multi-feature smartphone-based platform to improve engagement-in-care and viral suppression (VS) among clinic patients living with HIV. Features include medication reminders, mood/stress check-ins, a community board, and secure provider messaging. Our goal was to examine how PL users interact with the app and determine whether usage patterns correlate with clinical outcomes. Patients (N = 83) at a university-based Ryan White clinic enrolled in PL from June 2016 to March 2 ...[more]

PMID: 31816017

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Project description:BackgroundMobile communication has been found to improve antiretroviral therapy (ART) adherence among people living with HIV. In an ongoing randomized clinical trial, 2 mobile communication strategies (ie, sending SMS text messages and real-time medication monitoring [RTMM]) were used to improve adherence to ART among people living with HIV in Tanzania. We noticed remarkable discrepancies between self-reported adherence and adherence recorded by SMS text messaging or RTMM among some of the first trial participants.ObjectiveOur objective was to describe these cases and the observed discrepancies in more detail, to serve as a useful illustration of some of the challenges in using mobile health in resource-limited settings.MethodsIn an ongoing randomized trial, adults living with HIV from two HIV treatment centers in Tanzania who were suspected of low levels of adherence were randomly assigned in a 1:1:1 ratio to receive (1) SMS text message reminders, (2) an RTMM device, or (3) no additional intervention to standard HIV care. During bimonthly study visits, the participants self-reported their level of adherence, received feedback about their level of adherence based on SMS text messaging or RTMM, and discussed strategies to overcome adherence problems with nurses providing HIV care. For the purpose of this report, we selected people living with HIV who had completed 5 follow-up visits and consistently reported more than 95% adherence, while SMS text messaging or RTMM recorded lower than 75% adherence. The participants were invited for a short, face-to-face in-depth interview to explore reasons for this discrepancy.ResultsAt the time of this analysis, 26 participants had completed follow-up. Six of these evidenced the above-mentioned discrepancies, with an average adherence of 46% based on SMS text messaging or RTMM, while self-reported adherence was 98%. Five of these 6 participants insisted that their adherence to ART was good, with 4 reporting that their adherence to properly using the monitoring device was low. Three participants mentioned concerns about involuntary disclosure of HIV status as a main reason for low adherence to using the device. Two participants were still depending on other reminder cues despite receiving SMS text message or RTMM reminders. Poor network coverage caused low adherence in 1 participant.ConclusionsPsychosocial barriers were reported as importantly contributing to low adherence, both with respect to use of ART and proper use of the adherence-monitoring device. This case series illustrates that when introducing new digital adherence monitoring technology, researchers should consider psychosocial barriers and distinguish between adherence to device use and adherence to treatment.Trial registrationPan African Clinical Trials Registry PACTR201712002844286; https://tinyurl.com/y98q4p3l.

Project description:IntroductionWithin many sub-Saharan African countries including Malawi, HIV prevalence varies widely between regions. This variability may be related to the distribution of population groups with specific sociobehavioural characteristics that influence the transmission of HIV and the uptake of prevention. In this study, we intended to identify groups of people in Malawi with similar risk profiles.MethodsWe used data from the Demographic and Health Survey in Malawi (2015 to 2016), and stratified the analysis by sex. We considered demographic, socio-behavioural and HIV-related variables. Using Latent Class Analysis (LCA), we identified groups of people sharing common sociobehavioural characteristics. The optimal number of classes (groups) was selected based on the Bayesian information criterion. We compared the proportions of individuals belonging to the different groups across the three regions and 28 districts of Malawi.ResultsWe found nine groups of women and six groups of men. Most women in the groups with highest risk of being HIV positive were living in female-headed households and were formerly married or in a union. Among men, older men had the highest risk of being HIV positive, followed by young (20 to 25) single men. Generally, low HIV testing uptake correlated with lower risk of having HIV. However, rural adolescent girls had a low probability of being tested (48.7%) despite a relatively high HIV prevalence. Urban districts and the Southern region had a higher percentage of high-prevalence and less tested groups of individuals than other areas.ConclusionsLCA is an efficient method to find groups of people sharing common HIV risk profiles, identify particularly vulnerable sub-populations, and plan targeted interventions focusing on these groups. Tailored support, prevention and HIV testing programmes should focus particularly on female household heads, adolescent girls living in rural areas, older married men and young men who have never been married.

Dataset Information

Toward understanding the impact of mHealth features for people with HIV: a latent class analysis of PositiveLinks usage.

Publications

Toward understanding the impact of mHealth features for people with HIV: a latent class analysis of PositiveLinks usage.

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