Evidence map›Paper›PMID 41067756›Full record

ArticleBMJ open2025

Students' perceptions of AI mental health chatbots: an exploratory qualitative study at Sultan Qaboos University.

Ahmed Mohammed AlMaskari, Tamadhir Al-Mahrouqi, Abdullah Al Lawati, Hamood Al Aufi, Qaiser Al Riyami, Hamed Al-Sinawi

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Development and Validation of AI Help-Seeking Behavior Scale Among Undergraduate University Students.European journal of investigation in health, psychology and education · 2026
    Article
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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.

Ahmed Mohammed AlMaskariBehavioral Medicine, College of Medicine and Health Sciences, Sultan Qaboos University, Seeb, Oman.ORCID http://orcid.org/0009-0002-3131-6203
Tamadhir Al-MahrouqiDepartment of Behavioral Medicine, College of Medicine and Health Sciences, Sultan Qaboos University, Sultan Qaboos University Hospital, Seeb, Oman.
Abdullah Al LawatiBehavioral Medicine, College of Medicine and Health Sciences, Sultan Qaboos University, Seeb, Oman.
Hamood Al AufiBehavioral Medicine, College of Medicine and Health Sciences, Sultan Qaboos University, Seeb, Oman.
Qaiser Al RiyamiBehavioral Medicine, College of Medicine and Health Sciences, Sultan Qaboos University, Seeb, Oman S127549@student.squ.edu.om.
Hamed Al-SinawiDepartment of Behavioral Medicine, College of Medicine and Health Sciences, Sultan Qaboos University, Sultan Qaboos University Hospital, Seeb, Oman.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aim of this study is to explore the perceptions, attitudes and previous experiences of Sultan Qaboos University (SQU) students towards artificial intelligence (AI) mental health chatbots.

designThe study was conducted as an exploratory qualitative study, involving focus group discussions (FGDs).

settingThe study was conducted at SQU. All FGDs were conducted via Google Meet.

participantsA total of 60 students were recruited through convenience sampling. Both male and female students from different colleges were enrolled in the study. 10 FGDs were conducted.

resultsThe interview findings revealed that most students were open to using AI mental health chatbots, with many already having used similar applications. Participants listed several benefits that such applications could have, including increased availability, reduced stigma and behaviour tracking. The participants also raised some concerns about such applications, including data security, cultural sensitivity and various ethical issues.

conclusionThe future of AI chatbots for mental health is promising, as they have the potential to enhance mental healthcare services. Now that we know the disadvantages and limitations that may be associated with the use of such apps, it would be easier to design suitable apps that can properly triage mental health issues and provide supportive mental health.

Indexed as

Artificial IntelligenceMental HealthStudentsAdolescentAdultFemaleFocus GroupsGenerative Artificial IntelligenceHumansMaleQualitative ResearchUniversitiesYoung AdultCommunity-Based Participatory ResearchCross-Sectional StudiesEducation, MedicalHealthMENTAL HEALTHPSYCHIATRY

Identifiers

PMID41067756
PMCPMC12516975

What OpenQuestion holds

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LicenceCC BY-NC
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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.