Evidence mapPaperPMID 40648640Full record

ArticleHealthcare (Basel, Switzerland)2025

Enhancing Healthcare for People with Disabilities Through Artificial Intelligence: Evidence from Saudi Arabia.

Adel Saber Alanazi, Abdullah Salah Alanazi, Houcine Benlaria

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Digital Inclusion for Neurodiverse and Vulnerable Communities in the Global South: A Policy Analysis Study.Inquiry : a journal of medical care organization, provision and financing
    Article
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.

Adel Saber AlanaziCollege of Education, Jouf University, Sakakah 72388, Saudi Arabia.
Abdullah Salah AlanaziKing Salman Center for Disability Research, Riyadh 11614, Saudi Arabia.ORCID 0000-0002-8120-4018
Houcine BenlariaKing Salman Center for Disability Research, Riyadh 11614, Saudi Arabia.ORCID 0000-0001-7108-7068

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesArtificial intelligence (AI) offers opportunities to enhance healthcare accessibility for people with disabilities (PwDs). However, their application in Saudi Arabia remains limited. This study explores PwDs' experiences with AI technologies within the Kingdom's Vision 2030 digital health framework to inform inclusive healthcare innovation strategies.

methodsSemi-structured interviews were conducted with nine PwDs across Riyadh, Al-Jouf, and the Northern Border region between January and February 2025. Participants used various AI-enabled technologies, including smart home assistants, mobile health applications, communication aids, and automated scheduling systems. Thematic analysis following Braun and Clarke's six-phase framework was employed to identify key themes and patterns.

resultsFour major themes emerged: (1) accessibility and usability challenges, including voice recognition difficulties and interface barriers; (2) personalization and autonomy through AI-assisted daily living tasks and medication management; (3) technological barriers such as connectivity issues and maintenance gaps; and (4) psychological acceptance influenced by family support and cultural integration. Participants noted infrastructure gaps in rural areas, financial constraints, limited disability-specific design, and digital literacy barriers while expressing optimism regarding AI's potential to enhance independence and health outcomes.

conclusionsRealizing the benefits of AI for disability healthcare in Saudi Arabia requires culturally adapted designs, improved infrastructure investment in rural regions, inclusive policymaking, and targeted digital literacy programs. These findings support inclusive healthcare innovation aligned with Saudi Vision 2030 goals and provide evidence-based recommendations for implementing AI healthcare technologies for PwDs in similar cultural contexts.

Indexed as

artificial intelligenceassistive technologiesdigital healthdisabilityhealthcare accessibilitySaudi ArabiaVision 2030

Identifiers

PMID40648640
PMCPMC12250346

What Socratic holds

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LicenceCC BY
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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 Socratic graph.