Heidi Nieminen, Anna‐Kaisa Vartiainen, Raymond Bond, Emilia Laukkanen, Maurice Mulvenna, Lauri Kuosmanen
{"title":"Recommendations for Mental Health Chatbot Conversations: An Integrative Review","authors":"Heidi Nieminen, Anna‐Kaisa Vartiainen, Raymond Bond, Emilia Laukkanen, Maurice Mulvenna, Lauri Kuosmanen","doi":"10.1111/jan.16762","DOIUrl":null,"url":null,"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 sourcesPrimary 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 CareMental health professionals participating in chatbot development can utilise this review. The results can also inform technical development teams not involving healthcare professionals directly.ImpactKnowledge 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 ContributionNo patient or public contribution.","PeriodicalId":54897,"journal":{"name":"Journal of Advanced Nursing","volume":"45 1","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Advanced Nursing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/jan.16762","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
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 sourcesPrimary 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 CareMental health professionals participating in chatbot development can utilise this review. The results can also inform technical development teams not involving healthcare professionals directly.ImpactKnowledge 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 ContributionNo patient or public contribution.
期刊介绍:
The Journal of Advanced Nursing (JAN) contributes to the advancement of evidence-based nursing, midwifery and healthcare by disseminating high quality research and scholarship of contemporary relevance and with potential to advance knowledge for practice, education, management or policy.
All JAN papers are required to have a sound scientific, evidential, theoretical or philosophical base and to be critical, questioning and scholarly in approach. As an international journal, JAN promotes diversity of research and scholarship in terms of culture, paradigm and healthcare context. For JAN’s worldwide readership, authors are expected to make clear the wider international relevance of their work and to demonstrate sensitivity to cultural considerations and differences.