Exploring Applications of Artificial Intelligence in the Crisis Line Sector: Protocol for a Scoping Review (Preprint)

Abstract

<sec> <title>BACKGROUND</title> Crisis helplines are a vital component of a robust public health approach to suicide prevention as they are often free, accessible, and provide immediate support to individuals in distress. Artificial intelligence (AI) presents an opportunity for novel applications to support and improve crisis line services across a variety of functions including suicide risk assessment, issue identification, tracking responder behaviours, prompts and reminders, and more. However, the use of AI in the crisis sector also raises critical questions regarding safety, ethics, privacy, efficacy, feasibility, and acceptability among interest holders. The extent to which AI is currently being explored and implemented in crisis line contexts is unknown. </sec> <sec> <title>OBJECTIVE</title> The objective of this scoping review is to examine how AI is being used in crisis line services and to explore the perspectives of different interest groups regarding its application. </sec> <sec> <title>METHODS</title> This scoping review will be conducted in accordance with Arksey and O’Malley’s methodological framework and reported using the PRISMA Extension for Scoping Reviews (PRISMA-ScR). A comprehensive search strategy will be developed with an experienced health sciences librarian and implemented in multiple databases, including MEDLINE, Embase, PsycINFO, CINAHL, ASSIA, and Web of Science. Searches will be limited to studies published in English. We will include primary research describing AI applications and implementation in the crisis line sector and studies exploring interest holder perspectives. Titles and abstracts and full texts will be screened independently, in duplicate, following a screening calibration process. Disagreements will be resolved through discussion. Expert opinions will be sought as needed to make final determinations on included and excluded sources. A data extraction form will be created and piloted to capture information on study characteristics, study findings and outcomes, AI use cases, and considerations for various concepts relevant to crisis line services (eg, safety, trust, equity, ethics, privacy, etc). Extracted data will be synthesized using descriptive and narrative approaches. </sec> <sec> <title>RESULTS</title> As of March 2026, the search strategy is being finalized and translated across databases. Screening is expected to start in April of 2026. Results from this review will be ready by Winter 2027. </sec> <sec> <title>CONCLUSIONS</title> AI is changing public mental health by creating opportunities for optimizing interventions and care. However, several implementation questions remain when considering AI applications in the crisis sector. This review is a timely and comprehensive exploration into the state of AI in the crisis sector and will identify existing knowledge and evidence gaps to help inform practice, policy, and future research. By systematically mapping current AI applications, interest holder perspectives, and how core domains such as safety, privacy, and equity are addressed, this review will provide a foundational evidence base to guide responsible, person-centered AI integration and a robust research agenda tailored to crisis line contexts. </sec>

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