Evidence map›Paper›PMID 40731042›Full record

ArticleScientific reports2025

Dentists' perception and use of AI and robotics in the care of persons with disabilities.

Najla A Barnawi, Fay A AlAmmar, Sultan A Aldabeis, Salma M Alahmar, Ahmed A Alharthi, Mostafa A Abolfotouh

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.

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. Article
  2. Article
  3. Identifying Measurement Dimensions of Users' Benefit-Risk Perceptions of AI in Healthcare: A Scoping Review.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

6 authors.

Najla A BarnawiKing Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh/Ministry of National Guard Health Affairs, POB 22490, 11426, Riyadh, Saudi Arabia.ORCID http://orcid.org/0000-0001-5259-139X
Fay A AlAmmarKing Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh/Ministry of National Guard Health Affairs, POB 22490, 11426, Riyadh, Saudi Arabia.ORCID http://orcid.org/0009-0007-6241-7273
Sultan A AldabeisKing Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh/Ministry of National Guard Health Affairs, POB 22490, 11426, Riyadh, Saudi Arabia.ORCID http://orcid.org/0009-0004-9276-1778
Salma M AlahmarKing Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh/Ministry of National Guard Health Affairs, POB 22490, 11426, Riyadh, Saudi Arabia.ORCID http://orcid.org/0009-0001-7354-6886
Ahmed A AlharthiKing Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh/Ministry of National Guard Health Affairs, POB 22490, 11426, Riyadh, Saudi Arabia.ORCID http://orcid.org/0009-0006-0006-8138
Mostafa A AbolfotouhKing Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Riyadh/Ministry of National Guard Health Affairs, POB 22490, 11426, Riyadh, Saudi Arabia. mabolfotouh@gmail.com.ORCID http://orcid.org/0000-0003-3787-429X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the growing role of AI and robotics in healthcare, little is known about their integration into dental care for persons with disabilities (PWDs) in Saudi Arabia. This study aimed to assess dentists' perceptions and attitudes towards and use of RT/AI in dentistry and identify the predictors of using RT/AI to care for PWDs in the Saudi context. A cross-sectional study was conducted using a previously validated online self-reported questionnaire via SurveyMonkey, targeting 309 Saudi and non-Saudi licensed dentists and dental/oral health practitioners, to collect data on the following: 1) Personal and work-related characteristics, 2) Perception toward RT/AI use, 3) Attitude toward using AI and RT in dentistry, and 4) Current use of RT and AI. RT/AI use rate was calculated for each clinical aspect and each type of impairment. Logistic regression analysis was used to identify the predictors of dentists' use of RT and AI to provide care for PWDs. Significance was set at p < 0.05. Our study revealed that 59.2% of dentists who worked with PWDs reported utilizing RT/AI in various clinical aspects. Almost one-fourth of dentists reported using RT/AI in clinical examinations (23.9%), managing complications (26.8%), and performing invasive procedures (28.6%). Nearly one-third of respondents reported using RT/AI for taking a history (30%), non-invasive procedures (31.5%), behavioral training sessions (32.9%), health education (36.2%), medical diagnosis (36.6%), diagnostic tests (38%), and treatment planning (43.7%). Over one-half (54.9%) and one-fourth (28.6%) of the dentists reported a positive perception and attitude towards RT/AI use in dentistry. However, after adjusting for possible confounders, only previous RT/AI training remained a significant predictor of RT/AI use among dentists working with PWDs (OR = 9.18, 95% CI 2.92-28.90, p < 0.001). Our study is the first in the Saudi context to investigate the use of RT and AI by dentists caring for PWDs. Previous training was associated with greater use of RT/AI in this context. Potential collaborations between dental institutes and stakeholders in the RT and AI industry are recommended.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelDental Care for Persons with DisabilitiesDentistsPersons with DisabilitiesRoboticsAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedSaudi ArabiaSurveys and QuestionnairesAI/RT utilizationDentistry technologyDisabilityImpairmentOral health educationPerceptionPWDsRobotics

Identifiers

PMID40731042
PMCPMC12307922

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.