Evidence map›Paper›PMID 33966607›Full record

Trial reportGlobal public health2022

Learning from a diabetes mHealth intervention in rural Bangladesh: what worked, what did not and what next?

Joanna Morrison, Kohenour Akter, Hannah Jennings, Naveed Ahmed, Sanjit Kumer Shaha, Abdul Kuddus, Tasmin Nahar, Carina King, Hassan Haghparast-Bidgoli, A K Azad Khan and 3 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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.

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

10 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. 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

13 authors.

Joanna MorrisonInstitute for Global Health, University College London, London, UK.
Kohenour AkterDiabetic Association of Bangladesh, Dhaka, Bangladesh.
Hannah JenningsUniversity of York.
Naveed AhmedDiabetic Association of Bangladesh, Dhaka, Bangladesh.
Sanjit Kumer ShahaDiabetic Association of Bangladesh, Dhaka, Bangladesh.
Abdul KuddusDiabetic Association of Bangladesh, Dhaka, Bangladesh.
Tasmin NaharDiabetic Association of Bangladesh, Dhaka, Bangladesh.
Carina KingDepartment of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
Hassan Haghparast-BidgoliInstitute for Global Health, University College London, London, UK.ORCID 0000-0001-6365-2944
A K Azad KhanDiabetic Association of Bangladesh, Dhaka, Bangladesh.
Anthony CostelloInstitute for Global Health, University College London, London, UK.
Kishwar AzadDiabetic Association of Bangladesh, Dhaka, Bangladesh.
Edward FottrellInstitute for Global Health, University College London, London, UK.

Funding

Medical Research Council MR/M016501/1
6 · The paper itself

Abstract

There is an urgent need for population-based interventions to slow the growth of the diabetes epidemic in low-and middle-income countries. We tested the effectiveness of a population-based mHealth voice messaging intervention for T2DM prevention and control in rural Bangladesh through a cluster randomised controlled trial. mHealth improved knowledge and awareness about T2DM but there was no detectable effect on T2DM occurrence. We conducted mixed-methods research to understand this result. Exposure to messages was limited by technological faults, high frequency of mobile phone number changes, message fatigue and (mis)perceptions that messages were only for those who had T2DM. Persistent social norms, habits and desires made behaviour change challenging, and participants felt they would be more motivated by group discussions than mHealth messaging alone. Engagement with mHealth messages for T2DM prevention and control can be increased by (1) sending identifiable messages from a trusted source (2) using participatory design of mHealth messages to inform modelling of behaviours and increase relevance to the general population (3) enabling interactive messaging. mHealth messaging is likely to be most successful if implemented as part of a multi-sectoral, multi-component approach to address T2DM and non-communicable disease risk factors.

Indexed as

Cell PhoneDiabetes Mellitus, Type 2TelemedicineBangladeshHumansRural Populationdiabetesmhealthnon-communicable diseasesprocess evaluation

Identifiers

PMID33966607
PMCPMC9487863

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.