Evidence map›Paper›PMID 40627090›Full record

ArticleJournal of autism and developmental disorders2025

Perceptions of Special Education Professionals in the Kingdom of Saudi Arabia Regarding the Integration of Artificial Intelligence in Diagnosing Autism Spectrum Disorder.

Reda Ebrahim Mohamed El-Ashram, Ohud Abdulrahman Aldaghmi, Sanaa Mostafa Mohammed

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In one paragraph

Article in Journal of autism and developmental disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Reda Ebrahim Mohamed El-AshramCollege of Education, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia.ORCID http://orcid.org/0000-0002-8001-0852
Ohud Abdulrahman AldaghmiDepartment of Special Education, College of Education, Jouf University, Sakakah, Saudi Arabia.ORCID http://orcid.org/0000-0001-8556-2907
Sanaa Mostafa MohammedDepartment of Business Administration, College of Business, Jouf University, Sakakah, Saudi Arabia. smostafa@ju.edu.sa.ORCID http://orcid.org/0000-0001-8257-6414

Funding

the King Salman Center for Disability Research for funding this work through grant number KSRG-2023-039 KSRG-2023-039
6 · The paper itself

Abstract

Autism spectrum disorder (ASD) diagnosis often presents challenges due to its complexity and reliance on subjective clinical assessments, potentially leading to delays in identification and intervention. Artificial intelligence (AI) holds significant promise for transforming healthcare, including the potential to improve the accuracy, efficiency, and timeliness of ASD diagnosis. This study investigated the perspectives of 423 specialists in special education across the Kingdom of Saudi Arabia (KSA) on the requirements and challenges associated with integrating AI technologies into the ASD diagnostic process. Utilizing a descriptive survey methodology and a authors-developed questionnaire, we explored specialists' perceptions of AI implementation's financial, human, and regulatory aspects. According to our research, financial, human, and regulatory resources are seen to be crucial for a successful AI integration. However, a major barrier identified was the lack of awareness among specialists regarding the potential benefits and applications of AI in ASD diagnosis. These findings underscore the need for targeted interventions, including strategic investment in training programs, infrastructure development, and awareness campaigns, to facilitate the seamless integration of AI into the ASD diagnostic landscape in KSA. By addressing these requirements and challenges, we can pave the way for more accurate, efficient, and timely ASD diagnosis, ultimately resulting in better results for families and people with ASD.

Indexed as

Artificial intelligenceAutism spectrum disorderDiagnosingSpecial educationSpecialists

Identifiers

What OpenQuestion holds

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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.