Taewan Kim

Research promotion enables researchers to share advanced knowledge with pertinent academic communities. The question-and-answer (QA) style articles are effective for researchers to promote their research by enabling readers to understand research on complex subjects. Recent advances in large language models (LLMs) have opened avenues for supporting researchers in creating QA-style articles for research promotion. However, without the authors’ involvement, these models may only partially capture the researcher’s intention and voice. We developed AQUA, a research probe that enables researchers to co-create QA-style articles with LLMs to promote their research papers. A user study (n=12) reveals that LLMs reduced authors’ burden and helped them understand the readers’ perspectives. Nevertheless, LLMs failed to capture the unique intent of the authors, and their automated generation discouraged authors from carefully revising their answers. Based on our findings, we discuss human-LLM interaction design to enable authors to create QA-style articles that reflect their intention.

Large Language Models (LLMs) offer promising opportunities in mental health domains, although their inherent complexity and low controllability elicit concern regarding their applicability in clinical settings. We present MindfulDiary, an LLM-driven journaling app that helps psychiatric patients document daily experiences through conversation. Designed in collaboration with mental health professionals, MindfulDiary takes a state-based approach to safely comply with the experts’ guidelines while carrying on free-form conversations. Through a four-week field study involving 28 patients with major depressive disorder and five psychiatrists, we examined how MindfulDiary facilitates patients’ journaling practice and clinical care. The study revealed that MindfulDiary supported patients in consistently enriching their daily records and helped clinicians better empathize with their patients through an understanding of their thoughts and daily contexts. Drawing on these findings, we discuss the implications of leveraging LLMs in the mental health domain, bridging the technical feasibility and their integration into clinical settings.

With their generative capabilities, large language models (LLMs) have transformed the role of technological writing assistants from simple editors to writing collaborators. Such a transition emphasizes the need for understanding user perception and experience, such as balancing user intent and the involvement of LLMs across various writing domains in designing writing assistants. In this study, we delve into the less explored domain of personal writing, focusing on the use of LLMs in introspective activities. Specifically, we designed DiaryMate, a system that assists users in journal writing with LLM. Through a 10-day field study (N=24), we observed that participants used the diverse sentences generated by the LLM to reflect on their past experiences from multiple perspectives. However, we also observed that they are over-relying on the LLM, often prioritizing its emotional expressions over their own. Drawing from these findings, we discuss design considerations when leveraging LLMs in a personal writing practice.

Background: Individuals with autism often experience heightened anxiety in workplace environments because of challenges in communication and sensory overload. As these experiences can result in negative self-image, promoting their self-efficacy in the workplace is crucial. Virtual reality (VR) systems have emerged as promising tools for enhancing the self-efficacy of individuals with autism in navigating social scenarios, aiding in the identification of anxiety-inducing situations, and preparing for real-world interactions. However, there is limited research exploring the potential of VR to enhance self-efficacy by facilitating an understanding of emotional and physiological states during social skills practice. Objective: This study aims to develop and evaluate a VR system that enabled users to experience simulated work-related social scenarios and reflect on their behavioral and physiological data through data visualizations. We intended to investigate how these data, combined with the simulations, can support individuals with autism in building their self-efficacy in social skills. Methods: We developed WorkplaceVR, a comprehensive VR system designed for engagement in simulated work-related social scenarios, supplemented with data-driven reflections of users’ behavioral and physiological responses. A within-subject deployment study was subsequently conducted with 14 young adults with autism to examine WorkplaceVR’s feasibility. A mixed methods approach was used, compassing pre- and postsystem use assessments of participants’ self-efficacy perceptions. Results: The study results revealed WorkplaceVR’s effectiveness in enhancing social skills and self-efficacy among individuals with autism. First, participants exhibited a statistically significant increase in perceived self-efficacy following their engagement with the VR system (P=.02). Second, thematic analysis of the interview data confirmed that the VR system and reflections on the data fostered increased self-awareness among participants about social situations that trigger their anxiety, as well as the behaviors they exhibit during anxious moments. This increased self-awareness prompted the participants to recollect their related experiences in the real world and articulate anxiety management strategies. Furthermore, the insights uncovered motivated participants to engage in self-advocacy, as they wanted to share the insights with others. Conclusions: This study highlights the potential of VR simulations enriched with physiological and behavioral sensing as a valuable tool for augmenting self-efficacy in workplace social interactions for individuals with autism. Data reflection facilitated by physiological sensors helped participants with autism become more self-aware of their emotions and behaviors, advocate for their characteristics, and develop positive self-beliefs.

BACKGROUND Individuals with autism often experience heightened anxiety in workplace environments because of challenges in communication and sensory overload. As these experiences can result in negative self-image, promoting their self-efficacy in the workplace is crucial. Virtual reality (VR) systems have emerged as promising tools for enhancing the self-efficacy of individuals with autism in navigating social scenarios, aiding in the identification of anxiety-inducing situations, and preparing for real-world interactions. However, there is limited research exploring the potential of VR to enhance self-efficacy by facilitating an understanding of emotional and physiological states during social skills practice. OBJECTIVE This study aims to develop and evaluate a VR system that enabled users to experience simulated work-related social scenarios and reflect on their behavioral and physiological data through data visualizations. We intended to investigate how these data, combined with the simulations, can support individuals with autism in building their self-efficacy in social skills. METHODS We developed WorkplaceVR, a comprehensive VR system designed for engagement in simulated work-related social scenarios, supplemented with data-driven reflections of users’ behavioral and physiological responses. A within-subject deployment study was subsequently conducted with 14 young adults with autism to examine WorkplaceVR’s feasibility. A mixed methods approach was used, compassing pre- and postsystem use assessments of participants’ self-efficacy perceptions. RESULTS The study results revealed WorkplaceVR’s effectiveness in enhancing social skills and self-efficacy among individuals with autism. First, participants exhibited a statistically significant increase in perceived self-efficacy following their engagement with the VR system (P=.02). Second, thematic analysis of the interview data confirmed that the VR system and reflections on the data fostered increased self-awareness among participants about social situations that trigger their anxiety, as well as the behaviors they exhibit during anxious moments. This increased self-awareness prompted the participants to recollect their related experiences in the real world and articulate anxiety management strategies. Furthermore, the insights uncovered motivated participants to engage in self-advocacy, as they wanted to share the insights with others. CONCLUSIONS This study highlights the potential of VR simulations enriched with physiological and behavioral sensing as a valuable tool for augmenting self-efficacy in workplace social interactions for individuals with autism. Data reflection facilitated by physiological sensors helped participants with autism become more self-aware of their emotions and behaviors, advocate for their characteristics, and develop positive self-beliefs.

Pervasive symptoms of people with autism spectrum disorder (ASD), such as a lack of social and communication skills, are major challenges to be embraced in the workplace. Although much research has proposed VR training programs, their effectiveness is somewhat unclear, since they provide limited, one-sided interactions through fixed scenarios or do not sufficiently reflect the characteristics of people with ASD (e.g., preference for predictable interfaces, sensory issues). In this paper, we present VISTA, a VR-based interactive social skill training system for people with ASD. We ran a user study with 10 people with ASD and 10 neurotypical people to evaluate user experience in VR training and to examine the characteristics of people with ASD based on their physical responses generated by sensor data. The results showed that ASD participants were highly engaged with VISTA and improved self-efficacy after experiencing VISTA. The two groups showed significant differences in sensor signals as the task complexity increased, which demonstrates the importance of considering task complexity in eliciting the characteristics of people with ASD in VR training. Our findings not only extend findings (e.g., low ROI ratio, EDA increase) in previous studies but also provide new insights (e.g., high utterance rate, large variation of pupil diameter), broadening our quantitative understanding of people with ASD.

Background: College students’ mental health is at an all-time low. Students are increasingly disclosing their vulnerable, stigmatizing experiences on online social networking sites (SNSs). Peer support facilitated by SNSs can play a crucial role for the students in coping with mental health–related problems. Thus, it is imperative to understand how university students form perceptions, attitudes, and behaviors toward their peers who are dealing with mental health problems. Objective: This study aimed to provide a better understanding of how college students recognize, perceive, and react to signs of mental health problems in their peers on SNSs. Our ultimate goal in this study was to inform the design of SNSs that can facilitate online peer support. Methods: We conducted surveys with 226 students as well as semistructured interviews with 20 students at six universities in South Korea. Results: Of the 226 survey respondents, 150 (66.4%) reported that they recognized signs of a mental health problem on their friends’ SNS posts. However, a considerable number of respondents (62/150, 41.3%) were reluctant to offer support, even when they had identified friends who were at risk; this reluctance was due to a lack of knowledge or confidence and their desire to maintain a distance from at-risk peers to save their identity from stigmatization and to avoid emotional contagion online. Conclusions: Drawing on these results, we provide implications that could explain the construction of students’ perceptions regarding their peers’ mental health problems. We also provide design proposals for SNSs to serve as platforms that facilitate just-in-time and adaptive support exchanges among peers while mitigating stigma-related concerns.

BACKGROUND College students’ mental health is at an all-time low. Students are increasingly disclosing their vulnerable, stigmatizing experiences on online social networking sites (SNSs). Peer support facilitated by SNSs can play a crucial role for the students in coping with mental health–related problems. Thus, it is imperative to understand how university students form perceptions, attitudes, and behaviors toward their peers who are dealing with mental health problems. OBJECTIVE This study aimed to provide a better understanding of how college students recognize, perceive, and react to signs of mental health problems in their peers on SNSs. Our ultimate goal in this study was to inform the design of SNSs that can facilitate online peer support. METHODS We conducted surveys with 226 students as well as semistructured interviews with 20 students at six universities in South Korea. RESULTS Of the 226 survey respondents, 150 (66.4%) reported that they recognized signs of a mental health problem on their friends’ SNS posts. However, a considerable number of respondents (62/150, 41.3%) were reluctant to offer support, even when they had identified friends who were at risk; this reluctance was due to a lack of knowledge or confidence and their desire to maintain a distance from at-risk peers to save their identity from stigmatization and to avoid emotional contagion online. CONCLUSIONS Drawing on these results, we provide implications that could explain the construction of students’ perceptions regarding their peers’ mental health problems. We also provide design proposals for SNSs to serve as platforms that facilitate just-in-time and adaptive support exchanges among peers while mitigating stigma-related concerns.