Accepted for/Published in: JMIR Human Factors
Date Submitted: Feb 5, 2024
Open Peer Review Period: Feb 8, 2024 - Apr 4, 2024
Date Accepted: May 24, 2024
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Chatbot for social needs screening and resource sharing with vulnerable families: Iterative design and evaluation study
ABSTRACT
Background:
Health outcomes are significantly influenced by unmet social needs. Although screening for unmet social needs has become common in healthcare settings, there is often poor linkage to resources after needs are identified. The structural barriers (e.g., staffing, time, space) to helping address social needs could be overcome by a technology-based solution.
Objective:
This study presents the design and evaluation of a chatbot, DAPHNE©, that screens for social needs and links patients to resources.
Methods:
This study used a two-step approach: (1) iterative design with interdisciplinary stakeholder groups and (2) feasibility and usability assessment. Virtual sessions were held with an interdisciplinary group of stakeholders (n=10) using thematic and content analysis to inform the chatbot's design and development. Evaluation included an online survey, focus group interviews, and scenario-based usability testing with community health workers (family advocates) (n=4) and social workers (n=9).
Results:
The stakeholders emphasized the importance of provider-technology collaboration, inclusive conversational design, and user education. Users found the chatbot's capabilities met expectations and the chatbot was easy to use (System Usability Scale score=72). The stakeholders raised concerns about accuracy of suggested resources, electronic health record integration, and trust with a chatbot.
Conclusions:
Chatbots can provide personalized feedback platforms for families to identify and meet social needs. Our study highlights the importance of user-centered iterative design and development of chatbots for social needs. Future research should examine efficacy, cost-effectiveness, and scalability of chatbot interventions to address social needs.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.