Evidence map›Paper›PMID 41306933›Full record

ArticleFrontiers in digital health2025

Factors influencing perceived benefits and behavioral intention to use mental health chatbots among professional employees: an empirical study.

Gehad Mohammed Ahmed Naji, Foo Yuan, Nurul Azzura, Fajer Danish, Ali Ateeq, Siddig Balal Ibrahim, Halimaton Hakimi, Aziah Binti Abdollah, Yulita Hanum P Iskandar

Abstract read
In one paragraph

Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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  7. 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
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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

9 authors.

Gehad Mohammed Ahmed NajiGraduate School of Business, Universiti Sains Malaysia (USM), Pulau Pinang, Malaysia.
Foo YuanGraduate School of Business, Universiti Sains Malaysia (USM), Pulau Pinang, Malaysia.
Nurul AzzuraGraduate School of Business, Universiti Sains Malaysia (USM), Pulau Pinang, Malaysia.
Fajer DanishRoyal University for Women, Sanad, Bahrain.
Ali AteeqAdministrative Science Department, College of Administrative and Financial Science, Gulf University, Sanad, Bahrain.
Siddig Balal IbrahimAdministrative Science Department, College of Administrative and Financial Science, Gulf University, Sanad, Bahrain.
Halimaton HakimiPositive Computing Research Centre, Universiti Teknologi, Perak, Malaysia.
Aziah Binti AbdollahAsia Pacific University of Technology & Innovation (APU), Kuala Lumpur, Malaysia.
Yulita Hanum P IskandarGraduate School of Business, Universiti Sains Malaysia (USM), Pulau Pinang, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study explores factors influencing Malaysian professionals' intentions to use mental health chatbots by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Theory of Planned Behaviour (TPB). It examines UTAUT factors' direct effects on usage intention and the mediating role of perceived benefits, along with the moderating influence of attitudes towards chatbots. Research design & methodology: The study collects data from 351 professional employees in Malaysia using an online survey and analyses it using structural equation modelling (SEM). Findings: The study outcomes indicate that UTAUT factors significantly influence perceived benefits ( Conclusion: These findings challenge the assumption that perceived benefits alone drive adoption. They suggest a more complex interplay of factors influencing behavioural intention, indicating that trust, privacy, and credibility may play more critical roles in shaping adoption decisions. Implications: The study provides valuable insights for developers and implementers of mental health technologies. While UTAUT factors are crucial in shaping perceived benefits, the lack of a direct link to behavioural intention highlights the need to explore additional psychological and contextual factors. Future research should consider longitudinal designs and probabilistic sampling to enhance generalisability and causal inference.

Indexed as

attitudehealth system accessMalaysiamental health chatbotsperceived benefitsprofessional employeestechnology acceptance

Identifiers

PMID41306933
PMCPMC12644079

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.