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Exploring Predictors of Counselors' Acceptance of Virtual Reality Exposure Therapy With Resistance and Job Contexts as Moderators: Cross-Sectional Mixed Methods Study

2025-11-30T15:00:00Z

Title: Exploring Predictors of Counselors' Acceptance of Virtual Reality Exposure Therapy With Resistance and Job Contexts as Moderators: Cross-Sectional Mixed Methods Study Author(s): Kim, Myungsung; Jeon, Min; Lee, Yerin; Lee, Sangil; Kim, Hwang; Jung, Dooyoung Abstract: Background: Exposure therapy effectively treats anxiety disorders but faces implementation barriers, including cost, time constraints, and reluctance from therapists and clients. Virtual reality exposure therapy (VRET) offers a controlled digital alternative addressing these issues. However, adoption remains limited, with previous studies focusing mainly on hospital settings without considering individual or workplace factors. Objective: This study examined factors affecting counselors' VRET acceptance across diverse settings. We used the Unified Theory of Acceptance and Use of Technology (UTAUT) extended with job stress and resistance to change. Open-ended questions provided a deeper understanding of counselors' perspectives on VRET. Methods: A cross-sectional mixed methods study was conducted with 258 certified counselors across various settings, including universities, public institutions, and private clinics. Participants watched a 4-minute VRET introduction video and completed a survey measuring UTAUT variables (performance expectancy, effort expectancy, facilitating conditions, and social influence), resistance to change, and job stress. Stepwise forward selection multiple linear regression with moderation analyses was conducted to identify key predictors and test interaction effects. Open-ended responses (N=257, 290 meaning units) on VRET applicability and improvement suggestions were analyzed using team-based thematic analysis with iterative consensus coding. Results: Performance expectancy (β=.404, 95% CI 0.297-0.512, P<.001) and social influence (β=.387, 95% CI 0.280-0.494, P<.001) significantly predicted VRET adoption intentions (R2=0.494). Moderation analysis revealed that routine seeking weakened performance expectancy impact (β=-.160, 95% CI -0.277 to -0.043, P<.01), low job control strengthened it (β=.162, 95% CI 0.280-0.494, P<.005), and high job demands reduced social influence effects (β=-.150, 95% CI -0.263 to -0.036, P=.01). The narrow confidence intervals indicate precise estimation of these moderation effects. Younger counselors were more sensitive to contextual moderators, while older counselors prioritized performance expectancy. Thematic analysis identified 3 themes: counselor evaluation criteria for VRET, emphasizing content diversity and scientific validation; considerations for promoting and introducing VRET to counselors, addressing implementation challenges; and areas requiring continuous improvement for VRET field implementation, emphasizing professional competence and system reliability. Conclusions: This study advances VRET acceptance research by examining certified counselors across diverse nonhospital settings-unlike prior hospital-focused physician studies-and extending UTAUT with profession-specific moderators. Performance expectancy and social influence emerged as primary predictors, with routine seeking and job context significantly moderating these effects across age groups. Thematic analysis revealed that counselors evaluate VRET as a supplementary tool requiring scientific validation, diverse content, and structured training rather than technological usability alone. Findings inform practical strategies as follows: disseminating effectiveness evidence, leveraging professional networks, addressing work environment barriers for high-demand contexts, and developing age-appropriate approaches. Insights guide content developers, policymakers, and researchers implementing VRET beyond hospital settings. © Myungsung Kim, Min Jeon, Yerin Lee, Sangil Lee, Hwang Kim, Dooyoung Jung. Originally published in the Journal of Medical Internet Research (https://www.jmir.org).

Dynamic Modulation of Emotional Expressions in Social Robots: Effects on Liveliness and Naturalness

2026-05-31T15:00:00Z

Title: Dynamic Modulation of Emotional Expressions in Social Robots: Effects on Liveliness and Naturalness Author(s): Park, Haeun; Hwang, Sun Jun; Kim, Hyojin; Lee, Jiyeon; Lee, Hui Sung Abstract: Humans naturally express emotions with subtle variations, and exaggerated expressions often appear as heightened intensity in facial, bodily, or vocal cues. This paper introduces a method for exaggerating robotic emotional expressions by dynamically adjusting intensity within an emotion dynamics model. By systematically manipulating the damping ratio, we generated five distinct intensity levels for each emotion, thereby producing emotional expressions that exhibited different degrees of overshoot. A user study revealed that liveliness ratings for surprise increased linearly with intensity, suggesting that exaggerated, high-energy dynamics are particularly effective for conveying surprise. In contrast, other emotions exhibited optimal points at intermediate levels, indicating that excessive exaggeration can reduce perceived naturalness. These findings highlight the need for emotion-specific and user-specific calibration of expression intensity, supporting more nuanced and engaging human-robot interactions.

MFCC-Inspired Spectral Feature Extraction for Robust Touch Interaction in Social Robots

2026-05-31T15:00:00Z

Title: MFCC-Inspired Spectral Feature Extraction for Robust Touch Interaction in Social Robots Author(s): Kim, Ji Soo; Hwang, Sun Jun; Kim, Hyojin; Hwang, Dong Joon; Lee, Hui Sung Abstract: Touch is a fundamental modality for conveying emotions and intentions in Human–Robot Interaction. However, conventional approaches to touch pattern recognition often lack robustness to inter-user variability, whereas alternative solutions are frequently bulky or costly. This study proposes a novel feature extraction framework for touch pattern recognition, which adapts MFCC from speech processing to capacitive touch signals. The proposed method preserves the strengths of MFCC—dimensionality reduction and noise robustness—while addressing the physical differences between audio and touch signals by introducing a new frequency reference axis in place of the conventional Mel scale. To evaluate its effectiveness, a representative set of social touch patterns, including gestures traditionally difficult to classify, was defined and analyzed. The proposed framework ensures stable recognition across diverse users while reducing feature dimensionality for efficient operation in lightweight models. This efficiency highlights its suitability for real-time robotic interfaces

Understanding Compliance and Conversion Dynamics in Multi-Agent Collectives

2026-04-12T15:00:00Z

Title: Understanding Compliance and Conversion Dynamics in Multi-Agent Collectives Author(s): Lee, Soohwan; Lee, Kyungho Abstract: Multi-agent AI systems are increasingly prevalent across digital environments, yet their social influence dynamics remain underexplored beyond basic compliance. This study investigates how different multi-agent configurations affect human decision-making through compliance and conversion mechanisms. We conducted a controlled experiment with 127 participants interacting with three LLM-powered agents across three conditions: Majority (all agents opposing participant), Minority (one dissenting agent), and Diffusion (gradual spread of minority position). Participants completed normative and informational tasks while reporting stance and confidence at five time points. Results demonstrate distinct influence conditions by condition and task type. In informational tasks, majority consensus drove largest immediate opinion changes, while minority dissent showed potential for delayed but deeper attitude shifts consistent with conversion-like processes. The diffusion condition revealed how temporal dynamics serve as persuasive signals. These findings extend social psychology theories to human-AI interaction, highlighting risks of synthetic consensus manipulation and opportunities for structured dissent to promote critical thinking.