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Self-disclosure and relational agents for mental health: a scoping review protocol
Sia Sha1, Kate Loveys2, Isla Francis3
1The London School of Economics and Political Science, London, UK.
Introduction:
Relational agents are an innovative form of Artificial Intelligence (AI) that can help address waiting times for mental health services. They often appear in the form of chatbots that provide responses to patient questions via web or mobile interfaces, and they seek to build long-term relationships with patients. Effective self-disclosure is key for therapeutic outcomes, and we are therefore conducting a scoping review to map the literature on self-disclosure to relational agents for mental health.
Methods:
Our work will follow guidance by the Joanna Briggs Institute and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Extension for Scoping Reviews. We will systematically search Ovid Medline, Ovid Embase, Ovid Emcare, Ovid PsycINFO, Ovid Global Health, EBSCO CINAHL, Scopus, Web of Science and ProQuest Dissertations & Theses Global. Two reviewers will independently screen titles and abstracts as well as full texts of potential studies in Covidence. Both qualitative and quantitative studies from all countries published in English will be eligible. We will then provide a narrative synthesis of the results along with data tables.
Ethics And Dissemination:
Our scoping review does not require ethical approval. We will publish results in a peer-reviewed journal and during conference presentations.
Trial Registration Number:
Open Science Framework (https://osf.io/wf4aq).
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