Evidence map›Paper›PMID 40841383›Full record

ArticleScientific reports2025

Assessing the impact of AI tools on mobility and daily assistance for children with down syndrome in Saudi Arabia.

Rayan Alanazi, Adel Sabre Alanazi, Sohil Alqazlan, Houcine Benlaria

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

4 authors.

Rayan AlanaziCollege of Computer and Information Sciences, Jouf University, Sakakah, Saudi Arabia.ORCID http://orcid.org/0009-0006-7774-8190
Adel Sabre AlanaziCollege of Education, Jouf University, Sakakah, Saudi Arabia.ORCID http://orcid.org/0000-0002-6378-1073
Sohil AlqazlanCollege of Education, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia.
Houcine BenlariaCollege of Business, Jouf University, Sakakah, Saudi Arabia. hbenlarir@ju.edu.sa.ORCID http://orcid.org/0000-0001-7108-7068

Funding

King Salman Center for Disability Research KSRG-2024-181
6 · The paper itself

Abstract

This mixed-methods study investigated the impact of AI-powered assistive technology on mobility, communication, and daily living assistance in children with Down syndrome in Saudi Arabia. We looked at information from 123 carers (47 who used AI and 76 who did not) with similar child backgrounds through structured surveys and seven detailed interviews, using careful statistical methods and thorough initial assessments. AI users found it much easier to do things compared to those who didn't use AI, showing a medium improvement in moving around (Cohen's d = 0.65) and communicating (d = 0.72) and a large improvement in household tasks (d = 0.83). Among AI users only, perceived effectiveness was rated moderately high for daily independence (M = 3.85, SD = 0.93) and mobility (M = 3.78, SD = 1.18). Seven interviewed carers reported subjective stress reduction when children used AI tools independently. This secondary benefit extends the impact of AI beyond direct child outcomes to broader family well-being. Primary barriers to adoption included financial constraints (74.46%), insufficient technical support (38.29%), and technology adaptation difficulties (31.91%). Cultural perceptions and the absence of Arabic-localised AI solutions pose additional challenges that align with the global patterns identified in cross-cultural research. Although we did not directly test cross-cultural comparisons, this study suggests that Saudi Arabia's adoption barriers may share similarities with international patterns. Policy recommendations include establishing government subsidies covering 60-80% of AI tool costs, mandating insurance coverage, creating regional AI support centres, and prioritising the development of culturally adapted Arabic language solutions.

Indexed as

Activities of Daily LivingArtificial IntelligenceDown SyndromeSelf-Help DevicesAdolescentAdultCaregiversChildChild, PreschoolFemaleHumansMaleSaudi ArabiaSurveys and QuestionnairesAccessibilityAdoption barriersAI assistive technologiesCommunicationDaily independenceDisability technologyDown syndromeMobilitySaudi arabia

Identifiers

PMID40841383
PMCPMC12370876

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.