Evidence map›Paper›PMID 41963506›Full record

ArticleScientific reports2026

Factors influencing large language model adoption among dental students: a cross-sectional study.

Angel M Joseph, Rahaf E Almutairi, Wejdan A Alrashidi, Reem M Almutairi, Yahya Theeban, Sami Aldhuwayhi, Ahmed Altuwalah, Mohammed Z Mustafa, Amar A Thakare, Saikarthik Jayakumar and 2 more

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In one paragraph

Article in Scientific reports, 2026. 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

12 authors.

Angel M JosephDepartment of Restorative Dentistry and Prosthodontics, College of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia. angel@mu.edu.sa.
Rahaf E AlmutairiCollege of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia.
Wejdan A AlrashidiCollege of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia.
Reem M AlmutairiDepartment of Restorative Dentistry and Prosthodontics, College of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia.
Yahya TheebanDepartment of Restorative Dentistry and Prosthodontics, College of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia.
Sami AldhuwayhiDepartment of Restorative Dentistry and Prosthodontics, College of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia.
Ahmed AltuwalahDepartment of Restorative Dentistry and Prosthodontics, College of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia.
Mohammed Z MustafaDepartment of Restorative Dentistry and Prosthodontics, College of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia.
Amar A ThakareDepartment of Restorative Dentistry and Prosthodontics, College of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia.
Saikarthik JayakumarDepartment of Maxillofacial Surgery and Diagnostic Sciences, College of Dentistry, Majmaah University, 11952, Al-Majmaah, Saudi Arabia.
Ashwin JosephECHS Polyclinic, Manarcadu, Kottayam, Kerala, 686019, India.
Sreekanth K MallineniDepartment of Pediatric Dentistry, Dr. Sulaiman Al Habib Medical Group, Ar Rayyan, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research evaluates the factors influencing the behavioural intention (BI) to adopt large language models (LLMs) among dental students in education, clinical decision support (CDS), and research, using the original unified theory of acceptance and use of technology (UTAUT) model, representing the first application of this model in this specific context. LLM adoption among Saudi dental students is unstructured and unregulated, making empirical evidence on adoption factors an educational and governance priority. A cross-sectional, web-based survey using convenience sampling was conducted among 700 students from six universities in central Saudi Arabia (60.71% aged 18-22 years; 58.71% female; 74% undergraduate). The UTAUT constructs: performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC), were assessed using a five-point Likert scale. Measurement equivalence across English and Arabic language questionnaire versions were confirmed. All UTAUT constructs showed borderline acceptable to excellent internal consistency (α = 0.678-0.907). Structural equation modelling (SEM) with bootstrapped 95% confidence intervals (CI) was used for statistical analysis. Hierarchical multiple regression was used for post-hoc sensitivity analysis to examine the moderating effects of demographic variables. The model accounted for 44.1% of the variance in BI (SEM-derived R

Indexed as

Students, DentalAdolescentCross-Sectional StudiesFemaleHumansLarge Language ModelsMaleSaudi ArabiaSurveys and QuestionnairesYoung AdultArtificial intelligenceClinical decision supportDental educationMachine learningNatural language processing

Identifiers

PMID41963506
PMCPMC13230515

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.