Say it aloud: Measuring change talk and user perceptions in an automated, technology-delivered adaptation of motivational interviewing delivered by video-counsellor.

Motivational Interviewing is a widely used counselling technique. A fundamental principle of this technique is that hearing oneself argue for change strengthens motivation. This study presents the first analysis of participants' dialogue with an automated motivational interviewer. The objective was to explore communication with, and perceptions of, a technology-delivered adaptation of motivational interviewing (TAMI) delivered by a pre-recorded video-counsellor. Eighteen participants undertook the video interview and evaluated it after one week. Interviews were scored for change and sustain talk. Participants' written evaluations were subjected to thematic analysis. Interviews lasted 10 min 30s (SD 3 min 0 s). Change talk was observed in a mean of 16 of 25 responses (SD 3.35, range 11-21). Sustain talk was less frequent (mean = 3.4 replies, SD = 2.5, range 0 to 8). Participants disliked seeing their own image in the webcam and desired a personalised interaction where each question depended on the answer given to the previous one. Positive appraisals included space to think about motivation and plans, and hearing themselves voicing goals. A brief, generic, automated TAMI elicited change talk and was perceived as motivating.

Experiences of a Motivational Interview Delivered by a Robot: Qualitative Study.

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.

Generation and the subjective feeling of "aha!" are independently related to learning from insight.

It has been proposed that sudden insight into the solutions of problems can enhance long-term memory for those solutions. However, the nature of insight has been operationalized differently across studies. Here, we examined two main aspects of insight problem-solving-the generation of a solution and the subjective "aha!" experience-and experimentally evaluated their respective relationships to long-term memory formation (encoding). Our results suggest that generation (generated solution vs. presented solution) and the "aha!" experience ("aha!" vs. no "aha!") are independently related to learning from insight, as well as to the emotional response towards understanding the solution during encoding. Moreover, we analyzed the relationship between generation and the "aha!" experience and two different kinds of later memory tests, direct (intentional) and indirect (incidental). Here, we found that the generation effect was larger for indirect testing, reflecting more automatic retrieval processes, while the relationship with the occurrence of an "aha!" experience was somewhat larger for direct testing. Our results suggest that both the generation of a solution and the subjective experience of "aha!" indicate processes that benefit long-term memory formation, though differently. This beneficial effect is possibly due to the intrinsic reward associated with sudden comprehension and the detection of schema-consistency, i.e., that novel information can be easily integrated into existing knowledge.