Evidence map›Paper›PMID 31710302›Full record

ArticleJMIR mHealth and uHealth2019

Iterative Adaptation of a Mobile Nutrition Video-Based Intervention Across Countries Using Human-Centered Design: Qualitative Study.

Jasmin Isler, N Hélène Sawadogo, Guy Harling, Till Bärnighausen, Maya Adam, Moubassira Kagoné, Ali Sié, Merlin Greuel, Shannon A McMahon

Erratum issuedAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 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.

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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  17. Novel methods for health intervention research.Journal of health monitoring · 2020
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Jasmin IslerHeidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-0294-9469
N Hélène SawadogoNouna Health Research Center, Nouna, Nouna, Burkina Faso.ORCID 0000-0002-5708-2364
Guy HarlingInstitute for Global Health, University College London, London, United Kingdom.ORCID 0000-0001-6604-491X
Till BärnighausenHeidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-4182-4212
Maya AdamStanford Center for Health Education, Stanford School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0001-5563-421X
Moubassira KagonéNouna Health Research Center, Nouna, Nouna, Burkina Faso.ORCID 0000-0002-7297-0810
Ali SiéNouna Health Research Center, Nouna, Nouna, Burkina Faso.ORCID 0000-0002-3959-2520
Merlin GreuelHeidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-7430-7051
Shannon A McMahonHeidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-8634-9283

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile health (mHealth) video interventions are often transferred across settings. Although the outcomes of these transferred interventions are frequently published, the process of adapting such videos is less described, particularly within and across lower-income contexts. This study fills a gap in the literature by outlining experiences and priorities adapting a suite of South African maternal nutrition videos to the context of rural Burkina Faso.

objectiveThe objective of this study was to determine the key components in adapting a suite of maternal nutrition mHealth videos across settings.

methodsGuided by the principles of human-centered design, this qualitative study included 10 focus group discussions, 30 in-depth interviews, and 30 observations. We first used focus group discussions to capture insights on local nutrition and impressions of the original (South African) videos. After making rapid adjustments based on these focus group discussions, we used additional methods (focus group discussions, in-depth interviews, and observations) to identify challenges, essential video refinements, and preferences in terms of content delivery. All data were collected in French or Dioula, recorded, transcribed, and translated as necessary into French before being thematically coded by two authors.

resultsWe propose a 3-pronged Video Adaptation Framework that places the aim of video adaptation at the center of a triangle framed by end recipients, health workers, and the environment. End recipients (here, pregnant or lactating mothers) directed us to (1) align the appearance, priorities, and practices of the video's protagonist to those of Burkinabe women; (2) be mindful of local realities whether economic, health-related, or educational; and (3) identify and routinely reiterate key points throughout videos and via reminder cards. Health workers (here, Community Health Workers and Mentor Mothers delivering the videos) guided us to (1) improve technology training, (2) simplify language and images, and (3) increase the frequency of their engagements with end recipients. In terms of the environment, respondents guided us to localize climate, vegetation, diction, and how foods are depicted.

conclusionsDesign research provided valuable insights in terms of developing a framework for video adaptation across settings, which other interventionists and scholars can use to guide adaptations of similar interventions.

Indexed as

AdolescentAdultFemaleFocus GroupsHumansMaternal Health ServicesMaternal Nutritional Physiological PhenomenaMother-Child RelationsPregnancyQualitative ResearchSouth AfricaUniversal DesignVideotape RecordingBurkina FasoCommunity Health Workersdgital healthdietmHealthmotherspregnancy

Identifiers

PMID31710302
PMCPMC6878105

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.