Evidence map›Paper›PMID 29527356›Full record

ArticleBMJ global health2018

mHealth text and voice communication for monitoring people with chronic diseases in low-resource settings: a realist review.

Jocelyn Anstey Watkins, Jane Goudge, Francesc Xavier Gómez-Olivé, Caroline Huxley, Katherine Dodd, Frances Griffiths

Open access · goldAbstract read
In one paragraph

Article in BMJ global health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
10.7field-weighted citation impact, top 2% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.

  1. Pooled it
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  6. Role of telemedicine in cardiovascular care in low- and middle-income countries (LMICs).American heart journal plus : cardiology research and practice · 2026
    Review
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  17. A new privacy framework for the management of chronic diseases via mHealth in a post-Covid-19 world.Zeitschrift fur Gesundheitswissenschaften = Journal of public health · 2022
    Article
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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

6 authors at 2 institutions in 2 countries.

Jocelyn Anstey WatkinsDivision of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK.ORCID 0000-0003-4984-1057
Jane GoudgeCentre for Health Policy, Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
Francesc Xavier Gómez-OlivéMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Caroline HuxleyDivision of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK.
Katherine DoddDivision of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK.
Frances GriffithsDivision of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK.
University of the Witwatersrand · ZAUniversity of Warwick · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRoutine monitoring by patients and healthcare providers to manage chronic disease is vital, though this can be challenging in low-resourced health systems. Mobile health (mHealth) has been proposed as one way to improve management of chronic diseases. Past mHealth reviews have proposed the need for a greater understanding around how the theoretical constructs in mHealth interventions actually work. In response, we synthesised evidence from primary studies on monitoring of chronic diseases using two-way digital text or voice communication between a patient and health worker. We did this in order to understand the important considerations for the design of mHealth interventions.

methodArticles retrieved were systematically screened and analysed to elicit explanations of mHealth monitoring interventions. These explanations were consolidated into programme theory and compared with existing theory and frameworks. We identified variation in outcomes to understand how context moderates the outcome.

resultsFour articles were identified-monitoring of hypertension and HIV/AIDS from: Kenya, Pakistan, Honduras and Mexico and South Africa. Six components were found in all four interventions: reminders, patient observation of health state, motivational education/advice, provision of support communication, targeted actions and praise and encouragement. Intervention components were mapped to existing frameworks and theory. Variation in outcome identified in subgroup analysis suggests greater impact is achieved with certain patient groups, such as those with low literacy, those with stressful life events or those early in the disease trajectory. There was no other evidence in the included studies of the effect of context on the intervention and outcome.

conclusionmHealth interventions for monitoring chronic disease in low-resource settings, based on existing frameworks and theory, can be effective. A match between what the intervention provides and the needs or social factors relevant to specific patient group increases the effect. It was not possible to understand the impact of context on intervention and outcome beyond these patient-level measures as no evidence was provided in the study reports.

Indexed as

health systemssystematic review

Identifiers

PMID29527356
PMCPMC5841508
OpenAlexW2786306808

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.