Conversational Agents in Health Care: Scoping Review and Conceptual Analysis
Descripción general
Resumen del artículo
This review examined the use of conversational agents (chatbots) in healthcare. The findings indicate that most chatbots are text-based, delivered through smartphone apps, and use machine learning. The most common chatbot applications are treatment monitoring, health service support, and patient education. Despite generally positive findings on their effectiveness and acceptability, there is a need for more robust evaluations, especially in LMICs, and a standardized evaluation framework.
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Scientists found that talking apps on phones can help people with their health, like remembering medicine or learning about being healthy. They seem useful, but we need to check if they work well for everyone.
Posibles conflictos de intereses
One author (TK) is affiliated with the Center for Digital Health Interventions, which is partly funded by a health insurer (CSS), and is also a cofounder of Pathmate Technologies, a company that creates digital clinical pathways.
Limitaciones identificadas
Explicación de la calificación
This scoping review provides a valuable overview of the current state of conversational agents in healthcare. It highlights the potential benefits and identifies key areas for future research. The limitations mentioned do not detract significantly from the review's overall quality. The identified COI was acknowledged and likely did not significantly affect the results of the review, warranting a rating of 4.
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