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Experiences of a Motivational Interview Delivered by a Robot: Qualitative Study
Author(s) -
Joana Galvão Gomes da Silva,
David J. Kavanagh,
Tony Belpaeme,
Lloyd A. Taylor,
Konna Beeson,
Jackie Andrade
Publication year - 2018
Publication title -
journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/jmir.7737
Subject(s) - applied psychology , psychology , social robot , robot , usability , human–robot interaction , motivational interviewing , interview , human–computer interaction , humanoid robot , intervention (counseling) , social psychology , computer science , artificial intelligence , robot control , mobile robot , psychiatry , political science , law
Background Motivational interviewing is an effective intervention for supporting behavior change but traditionally depends on face-to-face dialogue with a human counselor. This study addressed a key challenge for the goal of developing social robotic motivational interviewers: creating an interview protocol, within the constraints of current artificial intelligence, which participants will find engaging and helpful. Objective The aim of this study was to explore participants’ qualitative experiences of a motivational interview delivered by a social robot, including their evaluation of usability of the robot during the interaction and its impact on their motivation. Methods NAO robots are humanoid, child-sized social robots. We programmed a NAO robot with Choregraphe software to deliver a scripted motivational interview focused on increasing physical activity. The interview was designed to be comprehensible even without an empathetic response from the robot. Robot breathing and face-tracking functions were used to give an impression of attentiveness. A total of 20 participants took part in the robot-delivered motivational interview and evaluated it after 1 week by responding to a series of written open-ended questions. Each participant was left alone to speak aloud with the robot, advancing through a series of questions by tapping the robot’s head sensor. Evaluations were content-analyzed utilizing Boyatzis’ steps: (1) sampling and design, (2) developing themes and codes, and (3) validating and applying the codes. Results Themes focused on interaction with the robot, motivation, change in physical activity, and overall evaluation of the intervention. Participants found the instructions clear and the navigation easy to use. Most enjoyed the interaction but also found it was restricted by the lack of individualized response from the robot. Many positively appraised the nonjudgmental aspect of the interview and how it gave space to articulate their motivation for change. Some participants felt that the intervention increased their physical activity levels. Conclusions Social robots can achieve a fundamental objective of motivational interviewing, encouraging participants to articulate their goals and dilemmas aloud. Because they are perceived as nonjudgmental, robots may have advantages over more humanoid avatars for delivering virtual support for behavioral change.

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