A Multilingual Digital Mental Health and Well-Being Chatbot (ChatPal): Pre-Post Multicenter Intervention Study

Author:

Potts CourtneyORCID,Lindström FridaORCID,Bond RaymondORCID,Mulvenna MauriceORCID,Booth FrederickORCID,Ennis EdelORCID,Parding KarolinaORCID,Kostenius CatrineORCID,Broderick ThomasORCID,Boyd KyleORCID,Vartiainen Anna-KaisaORCID,Nieminen HeidiORCID,Burns ConORCID,Bickerdike AndreaORCID,Kuosmanen LauriORCID,Dhanapala IndikaORCID,Vakaloudis AlexORCID,Cahill BrianORCID,MacInnes MarionORCID,Malcolm MartinORCID,O'Neill SiobhanORCID

Abstract

Background In recent years, advances in technology have led to an influx of mental health apps, in particular the development of mental health and well-being chatbots, which have already shown promise in terms of their efficacy, availability, and accessibility. The ChatPal chatbot was developed to promote positive mental well-being among citizens living in rural areas. ChatPal is a multilingual chatbot, available in English, Scottish Gaelic, Swedish, and Finnish, containing psychoeducational content and exercises such as mindfulness and breathing, mood logging, gratitude, and thought diaries. Objective The primary objective of this study is to evaluate a multilingual mental health and well-being chatbot (ChatPal) to establish if it has an effect on mental well-being. Secondary objectives include investigating the characteristics of individuals that showed improvements in well-being along with those with worsening well-being and applying thematic analysis to user feedback. Methods A pre-post intervention study was conducted where participants were recruited to use the intervention (ChatPal) for a 12-week period. Recruitment took place across 5 regions: Northern Ireland, Scotland, the Republic of Ireland, Sweden, and Finland. Outcome measures included the Short Warwick-Edinburgh Mental Well-Being Scale, the World Health Organization-Five Well-Being Index, and the Satisfaction with Life Scale, which were evaluated at baseline, midpoint, and end point. Written feedback was collected from participants and subjected to qualitative analysis to identify themes. Results A total of 348 people were recruited to the study (n=254, 73% female; n=94, 27% male) aged between 18 and 73 (mean 30) years. The well-being scores of participants improved from baseline to midpoint and from baseline to end point; however, improvement in scores was not statistically significant on the Short Warwick-Edinburgh Mental Well-Being Scale (P=.42), the World Health Organization-Five Well-Being Index (P=.52), or the Satisfaction With Life Scale (P=.81). Individuals that had improved well-being scores (n=16) interacted more with the chatbot and were significantly younger compared to those whose well-being declined over the study (P=.03). Three themes were identified from user feedback, including “positive experiences,” “mixed or neutral experiences,” and “negative experiences.” Positive experiences included enjoying exercises provided by the chatbot, while most of the mixed, neutral, or negative experiences mentioned liking the chatbot overall, but there were some barriers, such as technical or performance errors, that needed to be overcome. Conclusions Marginal improvements in mental well-being were seen in those who used ChatPal, albeit nonsignificant. We propose that the chatbot could be used along with other service offerings to complement different digital or face-to-face services, although further research should be carried out to confirm the effectiveness of this approach. Nonetheless, this paper highlights the need for blended service offerings in mental health care.

Publisher

JMIR Publications Inc.

Subject

Health Informatics

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Conversational and generative artificial intelligence and human–chatbot interaction in education and research;International Transactions in Operational Research;2024-07-31

2. Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review;Journal of Medical Internet Research;2024-07-23

3. Using Large Language Models for Robot-Assisted Therapeutic Role-Play: Factuality is not enough!;ACM Conversational User Interfaces 2024;2024-07-08

4. Young peoples’ reflections about using a chatbot to promote their mental wellbeing in northern periphery areas - a qualitative study;International Journal of Circumpolar Health;2024-06-24

5. Mental Health Chatbot;2024 IEEE Students Conference on Engineering and Systems (SCES);2024-06-21

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3