Evidence map›Paper›PMID 41070110›Full record

ArticleF1000Research2025

New Horizons in Higher Education: Examining the Mental Well-Being of Medical & Health Sciences Students Through the Use of Artificial Intelligence Based Chatbot Platforms in the United Arab Emirates - A Cross-Sectional Comparative Study.

Eman Abdelaziz Rashad Dabou, Fatma Magdi Ibrahim, Mustafa Faisal Haimour, Aya Saleh, Richard Mottershead

Abstract readComparative Study
In one paragraph

Article in F1000Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Eman Abdelaziz Rashad DabouRAK College of Nursing,, Ras Al Khaimah Medical and Health Sciences University, Ras Al Khaimah, United Arab Emirates.ORCID https://orcid.org/0000-0002-2105-5073
Fatma Magdi IbrahimRAK College of Nursing,, Ras Al Khaimah Medical and Health Sciences University, Ras Al Khaimah, United Arab Emirates.
Mustafa Faisal HaimourRAK College of Nursing,, Ras Al Khaimah Medical and Health Sciences University, Ras Al Khaimah, United Arab Emirates.
Aya SalehRAK College of Nursing,, Ras Al Khaimah Medical and Health Sciences University, Ras Al Khaimah, United Arab Emirates.
Richard MottersheadFaculty of Nursing, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Barriers to mental-health care include limited resources and workforce, access constraints, and stigma. Artificial-intelligence (AI)-enabled chatbots may offer low-threshold support. Methods: Cross-sectional correlational (comparative) study in one private health-sciences university in the UAE. Proportional stratified random sampling across four colleges yielded Results: 206/298 (69.1%) had ever used an AI chatbot; most used Snapchat AI (76.9%), followed by ChatGPT/Bard (23.4% each). Overall, 57.0% had moderate-to-extremely-severe depression, 68.5% anxiety, and 33.6% stress. Users had higher odds of moderate-to-extremely-severe anxiety and depression than non-users. In multivariable models, higher depression (OR = 1.022; 95% CI 1.01-1.085; Conclusion: Among UAE health-sciences students, AI-chatbot use is common and associated with higher depression/anxiety severity; this likely reflects help-seeking rather than causation. Universities should integrate early, stigma-sensitive supports, potentially including regulated, evidence-based chatbot tools-within stepped-care services.

Indexed as

Artificial IntelligenceMental HealthStudentsStudents, MedicalAdolescentAdultAnxietyCross-Sectional StudiesDepressionFemaleGenerative Artificial IntelligenceHumansMaleSurveys and QuestionnairesUnited Arab EmiratesUniversitiesArtificial IntelligenceChatbotMental Health & Well-BeingStudents

Identifiers

PMID41070110
PMCPMC12504930

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.