Evidence map›Paper›PMID 42879324›Full record

ArticlePLOS digital health2026

Contribution of artificial intelligence research to the development of inclusive applications for people with disabilities: A scoping review (2015-2025).

Soutongnoma Safiata Kaboré, Azadeh Bayani, Léandre Parfait Epoh Ewane, Davllyn Santos Oliveira Dos Anjos, Jean Noel Nikiéma, Muriel Mac-Seing

Abstract read
In one paragraph

Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Soutongnoma Safiata KaboréÉcole d'optométrie, Université de Montréal, Montréal, Québec, Canada.
Azadeh BayaniCentre de recherche en santé publique, Montréal, Québec, Canada.ORCID https://orcid.org/0009-0002-7707-9602
Léandre Parfait Epoh EwaneCentre de recherche en santé publique, Montréal, Québec, Canada.
Davllyn Santos Oliveira Dos AnjosCentre de recherche en santé publique, Montréal, Québec, Canada.
Jean Noel NikiémaCentre de recherche en santé publique, Montréal, Québec, Canada.
Muriel Mac-SeingCentre de recherche en santé publique, Montréal, Québec, Canada.ORCID https://orcid.org/0000-0001-5966-6702

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is rapidly transforming healthcare. Yet people with disabilities (PWD), representing 16% of the global population, remain disproportionately excluded from these advances. This exclusion is driven by algorithmic bias, non-representative datasets, and limited involvement of PWD in the design, development, and evaluation of AI applications. This scoping review examines the extent to which AI research in health contributes to the development of inclusive technologies for PWD, focusing on equity considerations. It identifies current trends, methodological gaps, and opportunities for socially responsive innovation. We conducted a systematic search across MEDLINE, Embase, Web of Science, and CINAHL for the 2015-2025 period, following Arksey and O'Malley's five-stage scoping review methodology and the PRISMA-ScR guidelines. Data were extracted and synthesized thematically using the Population-Concept-Context approach. Of 4,233 references retrieved, 93 studies were included. Most studies originated from high-income countries, particularly in North America (45.2%) and Europe (26.9%). AI applications addressed motor, sensory, cognitive, communication-related, and psychosocial disabilities, with emphasis on prediction/diagnosis, assistive technologies, and personalized care. While about 60% of studies referenced equity, only 12 (12.9%) implemented concrete measures (e.g., adapting tools for vulnerable groups or ensuring sample diversity), and only six (6.5%) actively involved PWD through co-design or user validation. AI holds significant potential to enhance autonomy, access, and quality of life for PWD. Realizing this promise will require moving beyond technical optimization to embrace inclusive design, participatory methods, and equity-driven frameworks aligned with responsible AI development and use.

Identifiers

PMID42879324
PMCPMC13671530

What OpenQuestion holds

Textmetadata
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.