ReviewJournal of advanced nursing2025
Recommendations for Mental Health Chatbot Conversations: An Integrative Review.
Review in Journal of advanced nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- From promise to practice: artificial intelligence in mental health care in the MENA region.Frontiers in psychiatry · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
aimTo identify and synthesise recommendations and guidelines for mental health chatbot conversational design.
designIntegrative review.
methodsSuitable publications presenting recommendations or guidelines for mental health conversational design were included. The quality of included publications was assessed using Joanna Briggs Institute Critical Appraisal Tools. Thematic analysis was conducted. DATA SOURCES: Primary searches limited to last 10 years were conducted in PubMed, Scopus, ACM Digital Library and EBSCO databases including APA PsycINFO, CINAHL, APA PsycArticles and MEDLINE in February 2023 and updated in October 2023. A secondary search was conducted in Google Scholar in May 2023.
resultsOf 1684 articles screened, 16 publications were selected. Three overarching themes were developed: (1) explicit knowledge about chatbot design and domain, (2) knowing your audience and (3) creating a safe space to engage. Results highlight that creating pleasant and effective conversations with a mental health chatbot requires careful and professional planning in advance, defining the target group and working together with it to address its needs and preferences. It is essential to emphasise the pleasant user experience and safety from both technical and psychological perspectives.
conclusionRecommendations for mental health chatbot conversational design have evolved and become more specific in recent years. Recommendations set high standards for mental health chatbots. To meet that, co-design, explicit knowledge of the user needs, domain and conversational design is needed. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Mental health professionals participating in chatbot development can utilise this review. The results can also inform technical development teams not involving healthcare professionals directly. IMPACT: Knowledge of developing mental health chatbot conversations appears scattered. In mental health chatbots, features that enhance the chatbot's ability to meet users' needs and increase safety should be considered. This review is useful for developers of mental health chatbots and other health applications used independently. REPORTING
methodThis integrative review was reported according to PRISMA guidelines, as applicable. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.