Reducing social diabetes distress with a conversational agent support system: a three-week technology feasibility evaluation

BACKGROUND: People with diabetes mellitus not only have to deal with physical health problems, but also with the psycho-social challenges their chronic disease brings. Currently, technological tools that support the psycho-social context of a patient have received little attention. OBJECTIVE: The objective of this work is to determine the feasibility and preliminary efficacy of an automated conversational agent to deliver, to people with diabetes, personalised psycho-education on dealing with (psycho-)social distress related to their chronic illness. METHODS: In a double-blinded between-subject study, 156 crowd-workers with diabetes received a social help program intervention in three sessions over three weeks. They were randomly assigned to receive support from either an interactive conversational support agent ([Formula: see text]) or a self-help text from the book “Diabetes burnout” as a control condition ([Formula: see text]). Participants completed the Diabetes Distress Scale (DDS) before and after the intervention, and after the intervention, the Client Satisfaction Questionnaire (CSQ-8), Feeling of Being Heard (FBH), and System Usability Scale (SUS). RESULTS: Results indicate that people using the conversational agent have a larger reduction in diabetes distress ([Formula: see text] , [Formula: see text]) than the control group ([Formula: see text] , [Formula: see text]) and this difference is statistically significant ([Formula: see text] , [Formula: see text]). A hypothesised mediation effect of “attitude to the social help program” was not observed. CONCLUSIONS: An automated conversational agent can deliver personalised psycho-education on dealing with (psycho-)social distress to people with diabetes and reduce diabetes distress more than a self-help book. ETHICS, STUDY REGISTRATION AND OPEN SCIENCE: This study has been preregistered with the Open Science Foundation (osf.io/yb6vg) and has been accepted by the Human Research Ethics Committee - Delft University of Technology under application number 1130. The data and analysis script are available: https://surfdrive.surf.nl/files/index.php/s/4xSEHCrAu0HsJ4P.