Evidence map›Paper›PMID 27930610›Full record

ArticleJournal of acquired immune deficiency syndromes (1999)2017

Using mHealth for HIV/TB Treatment Support in Lesotho: Enhancing Patient-Provider Communication in the START Study.

Yael Hirsch-Moverman, Amrita Daftary, Katharine A Yuengling, Suzue Saito, Moeketsi Ntoane, Koen Frederix, Llang B Maama, Andrea A Howard

Registry-linked trialAbstract read
In one paragraph

Article in Journal of acquired immune deficiency syndromes (1999), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05633056 (Adaptive Evaluation of mHealth and Conventional Adherence Support Interventions to Optimize Outcome With New Treatment Regimens for Drug-resistant Tuberculosis and HIV in South Africa), which is not on this map. Cited by 62 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 9 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05633056 narecruitingnot on this mapstarted 2023, after this paper: background citation

Adaptive Evaluation of mHealth and Conventional Adherence Support Interventions to Optimize Outcome With New Treatment Regimens for Drug-resistant Tuberculosis and HIV in South Africa

TypeinterventionalSponsorColumbia UniversityRan2023 to 2029Enrolled360ConditionsMulti Drug Resistant Tuberculosis, HIV InfectionsArmsAdherence support intevention
3 · Its place in the literature

Who cites it

62 citing papers in PubMed, 9 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. eHealth in TB clinical management.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
    Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Trial
  11. Trial
  12. Trial
  13. Trial
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

2 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yael Hirsch-Moverman*ICAP, Mailman School of Public Health, Columbia University, New York, NY; †Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY; ‡McGill International TB Centre, McGill University, Montreal, Quebec, Canada; §CAPRISA MRC HIV-TB Pathogenesis and Treatment Research Unit, University of KwaZulu-Natal, Durban, South Africa; and ‖National Tuberculosis Program, Lesotho Ministry of Health, Maseru, Lesotho.
Amrita Daftary
Katharine A Yuengling
Suzue Saito
Moeketsi Ntoane
Koen Frederix
Llang B Maama
Andrea A Howard

Funding

PEPFAR
6 · The paper itself

Abstract

backgroundmHealth is a promising means of supporting adherence to treatment. The Start TB patients on ART and Retain on Treatment (START) study included real-time adherence support using short-text messaging service (SMS) text messaging and trained village health workers (VHWs). We describe the use and acceptability of mHealth by patients with HIV/tuberculosis and health care providers.

methodsPatients and treatment supporters received automated, coded medication and appointment reminders at their preferred time and frequency, using their own phones, and $3.70 in monthly airtime. Facility-based VHWs were trained to log patient information and text message preferences into a mobile application and were given a password-protected mobile phone and airtime to communicate with community-based VHWs. The use of mHealth tools was analyzed from process data over the study course. Acceptability was evaluated during monthly follow-up interviews with all participants and during qualitative interviews with a subset of 30 patients and 30 health care providers at intervention sites. Use and acceptability were contextualized by monthly adherence data.

findingsFrom April 2013 to August 2015, the automated SMS system successfully delivered 39,528 messages to 835 individuals, including 633 patients and 202 treatment supporters. Uptake of the SMS intervention was high, with 92.1% of 713 eligible patients choosing to receive SMS messages. Patient and provider interviews yielded insight into barriers and facilitators to mHealth utilization. The intervention improved the quality of health communication between patients, treatment supporters, and providers. HIV-related stigma and technical challenges were identified as potential barriers.

conclusionsThe mHealth intervention for HIV/tuberculosis treatment support in Lesotho was found to be a low-tech, user-friendly intervention, which was acceptable to patients and health care providers.

Indexed as

TelemedicineAdultAppointments and SchedulesCell PhoneFemaleHealth CommunicationHIV InfectionsHumansLesothoMaleMiddle AgedPatient ComplianceReminder SystemsSocial StigmaText MessagingTuberculosis

Identifiers

PMID27930610
PMCPMC5147041

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.