Developing, Implementing, and Evaluating an Artificial Intelligence-Guided Mental Health Resource Navigation Chatbot for Health Care Workers and Their Families During and Following the COVID-19 Pandemic: Protocol for a Cross-sectional Study.
Autor: | Noble JM; Department of Computing Science, University of Alberta, Edmonton, AB, Canada.; Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada., Zamani A; Department of Computing Science, University of Alberta, Edmonton, AB, Canada.; Alberta Machine Intelligence Institute, Edmonton, AB, Canada., Gharaat M; Department of Computing Science, University of Alberta, Edmonton, AB, Canada.; Alberta Machine Intelligence Institute, Edmonton, AB, Canada., Merrick D; Department of Indigenous Studies, University of Saskatchewan, Regina, SK, Canada., Maeda N; Rehabilitation Robotics Lab, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB, Canada., Lambe Foster A; Mood Disorders Society of Canada, Ottawa, ON, Canada., Nikolaidis I; Mood Disorders Society of Canada, Ottawa, ON, Canada., Goud R; Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada., Stroulia E; Department of Computing Science, University of Alberta, Edmonton, AB, Canada., Agyapong VIO; Department of Psychiatry, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada., Greenshaw AJ; Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.; Asia-Pacific Economic Cooperation Digital Hub for Mental Health, Vancouver, BC, Canada., Lambert S; Department of Indigenous Studies, University of Saskatchewan, Regina, SK, Canada.; Network Environments for Indigenous Health Research National Coordinating Centre, Saskatoon, SK, Canada., Gallson D; Mood Disorders Society of Canada, Ottawa, ON, Canada., Porter K; Mood Disorders Society of Canada, Ottawa, ON, Canada., Turner D; Mood Disorders Society of Canada, Ottawa, ON, Canada., Zaiane O; Department of Computing Science, University of Alberta, Edmonton, AB, Canada.; Alberta Machine Intelligence Institute, Edmonton, AB, Canada. |
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Jazyk: | angličtina |
Zdroj: | JMIR research protocols [JMIR Res Protoc] 2022 Jul 25; Vol. 11 (7), pp. e33717. Date of Electronic Publication: 2022 Jul 25. |
DOI: | 10.2196/33717 |
Abstrakt: | Background: Approximately 1 in 3 Canadians will experience an addiction or mental health challenge at some point in their lifetime. Unfortunately, there are multiple barriers to accessing mental health care, including system fragmentation, episodic care, long wait times, and insufficient support for health system navigation. In addition, stigma may further reduce an individual's likelihood of seeking support. Digital technologies present new and exciting opportunities to bridge significant gaps in mental health care service provision, reduce barriers pertaining to stigma, and improve health outcomes for patients and mental health system integration and efficiency. Chatbots (ie, software systems that use artificial intelligence to carry out conversations with people) may be explored to support those in need of information or access to services and present the opportunity to address gaps in traditional, fragmented, or episodic mental health system structures on demand with personalized attention. The recent COVID-19 pandemic has exacerbated even further the need for mental health support among Canadians and called attention to the inefficiencies of our system. As health care workers and their families are at an even greater risk of mental illness and psychological distress during the COVID-19 pandemic, this technology will be first piloted with the goal of supporting this vulnerable group. Objective: This pilot study seeks to evaluate the effectiveness of the Mental Health Intelligent Information Resource Assistant in supporting health care workers and their families in the Canadian provinces of Alberta and Nova Scotia with the provision of appropriate information on mental health issues, services, and programs based on personalized needs. Methods: The effectiveness of the technology will be assessed via voluntary follow-up surveys and an analysis of client interactions and engagement with the chatbot. Client satisfaction with the chatbot will also be assessed. Results: This project was initiated on April 1, 2021. Ethics approval was granted on August 12, 2021, by the University of Alberta Health Research Board (PRO00109148) and on April 21, 2022, by the Nova Scotia Health Authority Research Ethics Board (1027474). Data collection is anticipated to take place from May 2, 2022, to May 2, 2023. Publication of preliminary results will be sought in spring or summer 2022, with a more comprehensive evaluation completed by spring 2023 following the collection of a larger data set. Conclusions: Our findings can be incorporated into public policy and planning around mental health system navigation by Canadian mental health care providers-from large public health authorities to small community-based, not-for-profit organizations. This may serve to support the development of an additional touch point, or point of entry, for individuals to access the appropriate services or care when they need them, wherever they are. International Registered Report Identifier (irrid): PRR1-10.2196/33717. (©Jasmine M Noble, Ali Zamani, MohamadAli Gharaat, Dylan Merrick, Nathanial Maeda, Alex Lambe Foster, Isabella Nikolaidis, Rachel Goud, Eleni Stroulia, Vincent I O Agyapong, Andrew J Greenshaw, Simon Lambert, Dave Gallson, Ken Porter, Debbie Turner, Osmar Zaiane. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 25.07.2022.) |
Databáze: | MEDLINE |
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