Chatbot -assisted self-assessment (CASA): Co-designing an AI -powered behaviour change intervention for ethnic minorities.

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Tác giả: Tom Buchanan, Anathoth Bulukungu, Ankit Das, Cynthia Graham, Deborah Husbands, Nicky Knights, Gurpreet Lall, Carrie D Llewellyn, Ian Montgomery, Tom Nadarzynski, Chimeremumma Ogueri, Olabisi Oyebode, Grace Paydon, Damien Ridge, Alejandra Soruco Rodriguez, Evan Rouse, Nidhi Singh, Alexandra Stefan, Nur Yanyali

Ngôn ngữ: eng

Ký hiệu phân loại: 363 Other social problems and services

Thông tin xuất bản: United States : PLOS digital health , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 84808

BACKGROUND: The digitalisation of healthcare has provided new ways to address disparities in sexual health outcomes that particularly affect ethnic and sexual minorities. Conversational artificial intelligence (AI) chatbots can provide personalised health education and refer users for appropriate medical consultations. We aimed to explore design principles of a chatbot-assisted culturally sensitive self-assessment intervention based on the disclosure of health-related information. METHODS: In 2022, an online survey was conducted among an ethnically diverse UK sample (N = 1,287) to identify the level and type of health-related information disclosure to sexual health chatbots, and reactions to chatbots' risk appraisal. Follow-up interviews (N = 41) further explored perceptions of chatbot-led health assessment to identify aspects related to acceptability and utilisation. Datasets were analysed using one-way ANOVAs, linear regression, and thematic analysis. RESULTS: Participants had neutral-to-positive attitudes towards chatbots and were comfortable disclosing demographic and sensitive health information. Chatbot awareness, previous experience and positive attitudes towards chatbots predicted information disclosure. Qualitatively, four main themes were identified: "Chatbot as an artificial health advisor", "Disclosing information to a chatbot", "Ways to facilitate trust and disclosure", and "Acting on self-assessment". CONCLUSION: Chatbots were acceptable for health self-assessment among this sample of ethnically diverse individuals. Most users reported being comfortable disclosing sensitive and personal information, but user anonymity is key to engagement with chatbots. As this technology becomes more advanced and widely available, chatbots could potentially become supplementary tools for health education and screening eligibility assessment. Future research is needed to establish their impact on screening uptake and access to health services among minoritised communities.
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