{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T14:14:12Z","timestamp":1788444852699,"version":"build-2803163510"},"reference-count":59,"publisher":"BMJ","issue":"6","license":[{"start":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T00:00:00Z","timestamp":1780444800000},"content-version":"unspecified","delay-in-days":2,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2026,5,14]]},"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Artificial intelligence (AI)-powered chatbots are increasingly integrated into healthcare to support administrative processes, health education and chronic disease management. These systems simulate human dialogue through natural language processing and machine learning, enabling dynamic and context-aware interactions. Despite their rapid adoption, there is limited synthesis of existing research describing how these technologies are applied across different healthcare contexts and what outcomes have been reported. This scoping review aims to map and describe the existing literature on the use of AI-powered chatbots in healthcare with a focus on clinical outcomes, patient satisfaction and operational efficiency. It will identify the types of studies conducted, their key characteristics and existing research gaps to guide future research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and analysis<\/jats:title>\n                    <jats:p>Following the Joanna Briggs Institute methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, a comprehensive search will be conducted across Medline (PubMed), CINAHL, Embase, Web of Science, The Cochrane Library and MedRxiv from database inception to 10 September 2025. Studies published in English, French, Dutch or German, involving AI-powered chatbots in any healthcare context reporting on clinical outcomes and\/or patient satisfaction and\/or operational efficiency will be included. Studies without full-text availability, protocols, trial registrations, reviews and studies conducted solely in educational settings will be excluded. Title and abstract screening will be supported by ASReview LAB, an AI-based active learning tool to enhance efficiency. Screening and data extraction will be conducted independently by two reviewers with disagreements resolved by a third reviewer. Findings will be synthesised narratively and presented using structured evidence tables categorised by chatbot type, clinical healthcare context and reported outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Ethics and dissemination<\/jats:title>\n                    <jats:p>Ethical approval is not required, as this study involves the analysis of published data only. The results of this scoping review will be disseminated through publication in a peer-reviewed journal, presentations at academic conferences and established professional networks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial registration number<\/jats:title>\n                    <jats:p>\n                      Open Science Framework (OSF),\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/doi.org\/10.17605\/OSF.IO\/8UE3B\">https:\/\/doi.org\/10.17605\/OSF.IO\/8UE3B<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  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