Evidence map›Paper›PMID 42600062›Full record

ArticleJMIR research protocols2026

Health Care Professionals' Perspectives on Conversational Mental Health Chatbots: Protocol for a Systematic Review.

Besran Zara Malgir, Yi Jiao Angelina Tian, Emma Herger, Stephen R Milford, David Shaw, Bernice Simone Elger

Abstract read
In one paragraph

Article in JMIR research protocols, 2026. 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

6 authors.

Besran Zara MalgirInstitute for Biomedical Ethics, Faculty of Medicine, University of Basel, Bernoullistrasse 28, Basel, 4056, Switzerland, 41 612071784.ORCID 0009-0005-6507-7548
Yi Jiao Angelina TianInstitute for Biomedical Ethics, Faculty of Medicine, University of Basel, Bernoullistrasse 28, Basel, 4056, Switzerland, 41 612071784.ORCID 0000-0003-2969-9655
Emma HergerUtrecht University, Utrecht, The Netherlands.ORCID 0009-0000-4987-2393
Stephen R MilfordInstitute for Biomedical Ethics, Faculty of Medicine, University of Basel, Bernoullistrasse 28, Basel, 4056, Switzerland, 41 612071784.ORCID 0000-0002-7325-9940
David ShawInstitute for Biomedical Ethics, Faculty of Medicine, University of Basel, Bernoullistrasse 28, Basel, 4056, Switzerland, 41 612071784.ORCID 0000-0001-8180-6927
Bernice Simone ElgerInstitute for Biomedical Ethics, Faculty of Medicine, University of Basel, Bernoullistrasse 28, Basel, 4056, Switzerland, 41 612071784.ORCID 0000-0002-4249-7399

Funding

Swiss National Science Foundation 51NF40_225155
6 · The paper itself

Abstract

Background: Mental health disorders (MHDs) represent a growing global challenge and pose a significant risk to public health. Alongside developments in the field of large language models (LLMs), conversational mental health chatbots (CMHBs) have emerged and are increasingly being used by individuals in self-directed and independent ways for mental health support. Although users' perspectives on CMHBs have been extensively examined and systematically synthesized, relatively little research has focused on how health care professionals (HCPs) perceive these tools. To develop a more comprehensive understanding of the implications of using CMHBs, the perspectives of HCPs should also be considered. As HCPs' views are informed by their clinical expertise and professional responsibility, they may point to underexplored implications related to the safety, ethical use, and implementation of these tools. Objective: This paper presents the protocol for a systematic review that aims to identify, synthesize, and critically appraise the available evidence on HCPs' perspectives regarding the use of CMHBs for mental health support, including perceptions of their therapeutic role, trustworthiness, safety, risks and benefits, ethical concerns, and implementation barriers and facilitators. Where relevant, the completed review will discuss its findings in relation to the existing literature on user perspectives to contextualize possible areas of convergence and divergence. Methods: A systematic review of the literature will be conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Peer-reviewed qualitative, quantitative, and mixed methods studies will be identified through searches of PubMed (MEDLINE), PsycInfo, Embase, CINAHL, Web of Science, and Scopus, with no restrictions on publication date. Study screening will be supported by AI-assisted active learning using ASReview, following the SAFE stopping procedure, with independent quality-assurance (QA) screening by a second reviewer. Data will be synthesized using a convergent integrated mixed methods approach, and the findings will be reported narratively. Methodological quality will be appraised using the Mixed Methods Appraisal Tool (MMAT; version 2018). Results: The search for this review was conducted and completed in late November 2025 and identified 24,905 records before deduplication and 18,535 records after deduplication. The initial title and abstract screening began in January 2026 and is ongoing. Data extraction is expected to be completed by August 2026. Conclusions: This protocol outlines a systematic review that will synthesize the available empirical evidence on HCPs' perspectives on the use of CMHBs for mental health support. The completed review aims to identify aspects such as perceived benefits, barriers and facilitators, and ethical concerns. By integrating qualitative, quantitative, and mixed methods evidence, the review will contribute to a more comprehensive understanding of the implementation and broader implications of CMHBs in mental health care.

Indexed as

Attitude of Health PersonnelHealth PersonnelMental DisordersCommunicationHumansLarge Language ModelsMental HealthMental Health TeletherapySystematic Reviews as TopicAIartificial intelligencechatbotsconversational AIconversational artificial intelligencehealth care professionalsmental health

Identifiers

PMID42600062
PMCPMC13475783

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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.