Evidence map›Paper›PMID 37649024›Full record

ArticleBMC health services research2023

Assessing the acceptability of technological health innovations in sub-Saharan Africa: a scoping review and a best fit framework synthesis.

Sarah Louart, Gildas Boris Hedible, Valéry Ridde

Abstract readScoping Review
In one paragraph

Article in BMC health services research, 2023. 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.

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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

3 authors.

Sarah LouartUniv. Lille, CNRS, UMR 8019 - CLERSE - Centre Lillois d'Etudes Et de Recherches Sociologiques Et Economiques, 59000, Lille, France. sarah.louart@gmail.com.
Gildas Boris HedibleCERPOP- UMR 1295 - Inserm, Université Paul Sabatier 3, Toulouse, France.
Valéry RiddeUniversité Paris Cité, IRD, INSERM, Ceped, 75006, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acceptability is a key concept used to analyze the introduction of a health innovation in a specific setting. However, there seems to be a lack of clarity in this notion, both conceptually and practically. In low and middle-income countries, programs to support the diffusion of new technological tools are multiplying. They face challenges and difficulties that need to be understood with an in-depth analysis of the acceptability of these innovations. We performed a scoping review to explore the theories, methods and conceptual frameworks that have been used to measure and understand the acceptability of technological health innovations in sub-Saharan Africa. The review confirmed the lack of common definitions, conceptualizations and practical tools addressing the acceptability of health innovations. To synthesize and combine evidence, both theoretically and empirically, we then used the "best fit framework synthesis" method. Based on five conceptual and theoretical frameworks from scientific literature and evidence from 33 empirical studies, we built a conceptual framework in order to understand the acceptability of technological health innovations. This framework comprises 6 determinants (compatibility, social influence, personal emotions, perceived disadvantages, perceived advantages and perceived complexity) and two moderating factors (intervention and context). This knowledge synthesis work has also enabled us to propose a chronology of the different stages of acceptability.

Indexed as

Attitude of Health PersonnelBiomedical TechnologyInventionsPhysician-Patient RelationsAfrica South of the SaharaHumansAcceptabilityBest fit framework synthesisHealthInnovationScoping reviewSub-Saharan Africa

Identifiers

PMID37649024
PMCPMC10469465

What OpenQuestion holds

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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.