Supporting Understanding: Comparing Conversational Interviewing in Chatbot vs Human-Administered Patient-Reported Outcomes for Stroke Survivors

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Authors: Milo Marsfeldt Skovfoged, Kalliopi Mavromati, Lucie Tvrdá, Terence J. Quinn, Felicia Körner, Sabrina Chiesurin, Veronika Némcová, Robert Mikulik, Hendrik Knoche
Cited by: 2
References: 87

Abstract

Hospitals use patient-reported outcome measurements (PROMs) to monitor stroke survivors post-discharge. Unfortunately, PROM items are prone to misinterpretation. Human-administered PROMs mitigate comprehension issues through conversational interviewing (CI), in which facilitators provide real-time clarification. However, chatbots have not yet adopted CI techniques, raising questions about whether CI-enabled chatbots can effectively support PROM administration. We conducted a controlled experiment with 18 stroke survivors comparing two CI clarification techniques —1) additional examples and 2) reflective prompts —against 3) no clarification (control) administered by both a chatbot and a human facilitator. Our findings demonstrate the feasibility of CI-enabled chatbots, as participants’ responses remained consistent across facilitators and clarification types. Participants exhibited better PROM answer behaviour when using the chatbot, with fewer anecdotal digressions and greater adherence to validated response options. Notably, when receiving CI support, participants stopped asking the human facilitator for clarification. Preferences for clarification varied by question type: participants favoured examples for physical activity questions, while no clarification was preferred for mental health–related items.

Fields of Study & Subjects

AI in Service Interactions Stroke Rehabilitation and Recovery Digital Mental Health Interventions

Publication details

Journal / source
ACM Transactions on Computing for Healthcare
Publisher
Association for Computing Machinery (ACM)
Publication date
7 March 2026
Language
EN