Factors influencing patient engagement in mental health chatbots: A thematic analysis of findings from a systematic review of reviews
Introduction Mental health disorders affect millions of people worldwide. Chatbots are a new technology that can help users with mental health issues by providing innovative features. This article aimed to conduct a systematic review of reviews on chatbots in mental health services and synthesized t...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2024-04-01
|
| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076241247983 |
| _version_ | 1797197325411549184 |
|---|---|
| author | Mohsen Khosravi Ghazaleh Azar |
| author_facet | Mohsen Khosravi Ghazaleh Azar |
| author_sort | Mohsen Khosravi |
| collection | DOAJ |
| description | Introduction Mental health disorders affect millions of people worldwide. Chatbots are a new technology that can help users with mental health issues by providing innovative features. This article aimed to conduct a systematic review of reviews on chatbots in mental health services and synthesized the evidence on the factors influencing patient engagement with chatbots. Methods This study reviewed the literature from 2000 to 2024 using qualitative analysis. The authors conducted a systematic search of several databases, such as PubMed, Scopus, ProQuest, and Cochrane database of systematic reviews, to identify relevant studies on the topic. The quality of the selected studies was assessed using the Critical Appraisal Skills Programme appraisal checklist and the data obtained from the systematic review were subjected to a thematic analysis utilizing the Boyatzis's code development approach. Results The database search resulted in 1494 papers, of which 10 were included in the study after the screening process. The quality assessment of the included studies scored the papers within a moderate level. The thematic analysis revealed four main themes: chatbot design, chatbot outcomes, user perceptions, and user characteristics. Conclusion The research proposed some ways to use color and music in chatbot design. It also provided a systematic and multidimensional analysis of the factors, offered some insights for chatbot developers and researchers, and highlighted the potential of chatbots to improve patient-centered and person-centered care in mental health services. |
| first_indexed | 2024-04-24T06:42:10Z |
| format | Article |
| id | doaj.art-5e610cc254714fdf9ca157e8a8718e8a |
| institution | Directory Open Access Journal |
| issn | 2055-2076 |
| language | English |
| last_indexed | 2024-04-24T06:42:10Z |
| publishDate | 2024-04-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Digital Health |
| spelling | doaj.art-5e610cc254714fdf9ca157e8a8718e8a2024-04-23T01:04:16ZengSAGE PublishingDigital Health2055-20762024-04-011010.1177/20552076241247983Factors influencing patient engagement in mental health chatbots: A thematic analysis of findings from a systematic review of reviewsMohsen Khosravi0Ghazaleh Azar1 Department of Healthcare Management, School of Management and Medical Informatics, , Shiraz, Iran Department of Consultation and Mental Health, , Yasuj, IranIntroduction Mental health disorders affect millions of people worldwide. Chatbots are a new technology that can help users with mental health issues by providing innovative features. This article aimed to conduct a systematic review of reviews on chatbots in mental health services and synthesized the evidence on the factors influencing patient engagement with chatbots. Methods This study reviewed the literature from 2000 to 2024 using qualitative analysis. The authors conducted a systematic search of several databases, such as PubMed, Scopus, ProQuest, and Cochrane database of systematic reviews, to identify relevant studies on the topic. The quality of the selected studies was assessed using the Critical Appraisal Skills Programme appraisal checklist and the data obtained from the systematic review were subjected to a thematic analysis utilizing the Boyatzis's code development approach. Results The database search resulted in 1494 papers, of which 10 were included in the study after the screening process. The quality assessment of the included studies scored the papers within a moderate level. The thematic analysis revealed four main themes: chatbot design, chatbot outcomes, user perceptions, and user characteristics. Conclusion The research proposed some ways to use color and music in chatbot design. It also provided a systematic and multidimensional analysis of the factors, offered some insights for chatbot developers and researchers, and highlighted the potential of chatbots to improve patient-centered and person-centered care in mental health services.https://doi.org/10.1177/20552076241247983 |
| spellingShingle | Mohsen Khosravi Ghazaleh Azar Factors influencing patient engagement in mental health chatbots: A thematic analysis of findings from a systematic review of reviews Digital Health |
| title | Factors influencing patient engagement in mental health chatbots: A thematic analysis
of findings from a systematic review of reviews |
| title_full | Factors influencing patient engagement in mental health chatbots: A thematic analysis
of findings from a systematic review of reviews |
| title_fullStr | Factors influencing patient engagement in mental health chatbots: A thematic analysis
of findings from a systematic review of reviews |
| title_full_unstemmed | Factors influencing patient engagement in mental health chatbots: A thematic analysis
of findings from a systematic review of reviews |
| title_short | Factors influencing patient engagement in mental health chatbots: A thematic analysis
of findings from a systematic review of reviews |
| title_sort | factors influencing patient engagement in mental health chatbots a thematic analysis of findings from a systematic review of reviews |
| url | https://doi.org/10.1177/20552076241247983 |
| work_keys_str_mv | AT mohsenkhosravi factorsinfluencingpatientengagementinmentalhealthchatbotsathematicanalysisoffindingsfromasystematicreviewofreviews AT ghazalehazar factorsinfluencingpatientengagementinmentalhealthchatbotsathematicanalysisoffindingsfromasystematicreviewofreviews |