UNASSIGNED: Electronic health (eHealth) has been widely adopted in chronic disease management. Prior studies focused on time-based reminders as a cue to facilitate behavior change intentions, ignoring the development of automatic cue-behavior associations via other cue types.
UNASSIGNED: Hence, this study utilized avatar appearance as a visual-based cue to help establish the automatic association between appearance transformation and health behavior to form habits without intention.
UNASSIGNED: To better understand users\' attitudes and experiences toward applying changes in avatar appearance to develop cue-behavior associations for hypertensive patients. Fifteen participants were recruited in a 14-day experiment. After excluding one participant who dropped out of the experiment, others were randomly assigned to two groups. One group consisted of a visual-based cue (a virtual plant) and basic behavior change techniques (BCTs). The other group only included basic BCTs. Attitudes and experience outcomes were collected by interview, and qualitative data were analyzed using thematic analysis.
UNASSIGNED: 57% of participants had been diagnosed with hypertension for more than five years, and more than 50% of participants have experience using mobile apps or wearables. 66% of participants did physical activity more than three times every week. The result shows that tailored time-based reminders, blood pressure monitoring, and daily dietary intake were the most attractive features. Additionally, hypertensive participants have positive attitudes toward avatar appearance as a visual-based cue to develop cue-behavior association, which enhances self-management motivation.
UNASSIGNED: This study proposes a visual-based cue design for habit formation and conducts a qualitative method to explore hypertensive patients\' perceptions. The findings offer insights from user\'s perspectives into hypertensive patients\' attitudes toward visual-based cues and perception of the connection between avatar appearance and health behavior for self-management. Subsequent discussions present eHealth design guidelines of habit formation from intention, automatic cue-behavior association, and self-management perspectives.

The term Proteus effect refers to the changes in attitudes and behavior induced by the characteristics of an embodied virtual agent. Whether the effect can extend to the moral sphere is currently unknown. To deal with this issue, we investigated if embodying virtual agents (i.e., avatars) with different characteristics modulate people\'s moral standards differentially. Participants were requested to embody an avatar resembling the Christian God in His anthropomorphic appearance or a control human avatar and to perform a text-based version of incidental and instrumental dilemmas in a virtual environment. For each participant, we recorded (1) chosen options (deontological vs. utilitarian), (2) decision times, (3) postdecision feelings, and (4) physiological reactions (skin conductance response and heart rate). We found that embodying God vs. a control avatar did not change the performance in the moral dilemma task, indicating that no strong Proteus effect was at play in our experimental conditions. We interpreted this result by examining the constraints and limitations of our task, reasoning about the necessary conditions for eliciting the Proteus effect, and discussing future developments and advances in the field. Moreover, we presented compelling effects concerning dilemma type, chosen option, personality traits, and religion affiliation, thus supporting and extending literature on decision making in moral dilemmas.

In recent years, due to the prevalence of virtual reality (VR) and human-computer interaction (HCI) research, along with the expectation that understanding the process of establishing sense of ownership, sense of agency, and limb heaviness (in this study, limb heaviness is replaced with comfort level) will contribute to the development of various medical rehabilitation, various studies have been actively conducted in these fields. Previous studies have indicated that each perceptual characteristics decrease in response to positive delay. However, it is still unclear how each perceptual characteristic changes in response to negative delay. Therefore, the purpose of this study was to deduce how changes occur in the perceptual characteristics when certain settings are manipulated using the avatar developed in this study. This study conducted experiments using an avatar system developed for this research that uses electromyography as the interface. Two separate experiments involved twelve participants: a preliminary experiment and a main experiment. As observed in the previous study, it was confirmed that each perceptual characteristics decreased for positive delay. In addition, the range of the preliminary experiment was insufficient for the purpose of this study, which was to confirm the perceptual characteristics for negative delay, thus confirming the validity of conducting this experiment. Meanwhile, the main experiment showed that the sense of ownership, sense of agency, and comfort level decreased gradually as delay time decreased, (i.e., this event is prior to action with intention, which could not be examined in the previous study). This suggests that control by the brain-machine interface is difficult to use when it is too fast. In addition, the distribution of the most strongly perceived settings in human perceptual characteristics was wider in regions with larger delays, suggesting this may lead to the evaluation of an internal model believed to exist in the human cerebellum. The avatar developed for this study may have the potential to create a new experimental paradigm for perceptual characteristics.

This research explores the significance of avatar communication in the virtual world, where individuals can create new identities and establish relationships beyond real-world limitations. Avatar users engage in virtual interactions to fulfill their desires, enjoy entertainment, and experience surrogate satisfaction. This study integrates the Expectation Confirmation Model (ECM) and Impression Management Theory (IMT) to investigate the impact of various avatar ego types on communication satisfaction and continued intention to use. Two surveys (n = 600) were administered using South Korean and American samples. The results suggest a significant relationship between expectancy confirmation and perceived usefulness. Specifically, high perceived usefulness leads to increased communication satisfaction. Also, when pre-experience expectancy confirmation is low, it positively affects communication satisfaction. In addition, the study highlights differences between Western and Eastern cultural contexts in avatar ego type\'s expression. This study contributes to the understanding of virtual interactions, offering theoretical insights through the integration of ECM and IMT. Theoretical and practical implications are discussed.

A person with impaired emotion recognition is not able to correctly identify facial expressions represented by other individuals. The aim of the present study is to assess eyes gaze and facial emotion recognition in a healthy population using dynamic avatars in immersive virtual reality (IVR). For the first time, the viewing of each area of interest of the face in IVR is studied by gender and age. This work in healthy people is conducted to assess the future usefulness of IVR in patients with deficits in the recognition of facial expressions. Seventy-four healthy volunteers participated in the study. The materials used were a laptop computer, a game controller, and a head-mounted display. Dynamic virtual faces randomly representing the six basic emotions plus neutral expression were used as stimuli. After the virtual human represented an emotion, a response panel was displayed with the seven possible options. Besides storing the hits and misses, the software program internally divided the faces into different areas of interest (AOIs) and recorded how long participants looked at each AOI. As regards the overall accuracy of the participants\' responses, hits decreased from the youngest to the middle-aged and older adults. Also, all three groups spent the highest percentage of time looking at the eyes, but younger adults had the highest percentage. It is also noteworthy that attention to the face compared to the background decreased with age. Moreover, the hits between women and men were remarkably similar and, in fact, there were no statistically significant differences between them. In general, men paid more attention to the eyes than women, but women paid more attention to the forehead and mouth. In contrast to previous work, our study indicates that there are no differences between men and women in facial emotion recognition. Moreover, in line with previous work, the percentage of face viewing time for younger adults is higher than for older adults. However, contrary to earlier studies, older adults look more at the eyes than at the mouth.Consistent with other studies, the eyes are the AOI with the highest percentage of viewing time. For men the most viewed AOI is the eyes for all emotions in both hits and misses. Women look more at the eyes for all emotions, except for joy, fear, and anger on hits. On misses, they look more into the eyes for almost all emotions except surprise and fear.

OBJECTIVE: Aversive emotions toward food and the consequences of eating are at the core of anorexia nervosa. Exposure therapy is effective to reduce anxiety and avoidance toward feared stimuli. Based on the inhibitory learning framework, this study examined the feasibility to induce social support or positive mood to enhance the impact of a single session virtual food exposure on food-related anxiety in anorexia nervosa.
METHODS: One hundred and forty-five patients were randomized to: (1) virtual food exposure (i.e., baseline condition), (2) virtual food exposure plus positive mood induction (i.e., positive mood condition), or (3) virtual food exposure plus social support (i.e., social support condition). They completed self-report assessments of anxiety toward virtual foods, general anxiety, positive mood, social support, and hunger, before and after virtual food exposure. Number of eye gazes and touches toward foods were recorded during the virtual reality exposure.
RESULTS: Patients had lower levels of anxiety toward virtual foods in the positive mood condition, compared to the baseline condition [F(2,141)  = 4.36, p = .015; medium effect size]. They also touched food items more often in the baseline condition. No other significant changes were found.
CONCLUSIONS: Virtual food exposure enhanced by positive mood induction seems a feasible approach to strengthen the impact of food exposure in anorexia nervosa.
UNASSIGNED: This research contributes to the understanding of how patients with anorexia nervosa can be supported to overcome fear and anxiety around food. Virtual reality enables patients to expose themselves to difficult situations (e.g., kitchen with foods of various calorie contents) while experiencing positive stimuli, such as a loving and kind pet or a supportive avatar.

BACKGROUND: In response to the serious lack of physical activity among young adults, recent attempts have been made to encourage young people to exercise through exercise video distribution. However, merely distributing videos does not lead to improved physical activity levels. Metaverse space, which enables web-based interaction through avatars, allows users to watch exercise videos in the same space as other avatars.
OBJECTIVE: This study explored whether exercise video distribution using metaverse space is effective in improving physical activity levels, along with mental health and locomotive function, among young people.
METHODS: In this parallel-group randomized controlled trial participants were recruited using printed poster displays. A total of 48 young adults aged between 18 and 30 years were assigned to 3 groups of 16 each: the metaverse, YouTube, and control group. To encourage exercise, the metaverse group was given an exercise video each week with a load of around 4-8 metabolic equivalents of tasks (METs) for 8 videos delivered in the metaverse space. The YouTube group was sent a URL on YouTube every week to view exercise videos with the same content as the metaverse group. The control group was given no special instructions. The intervention period was 8 weeks. Pre- and postintervention physical activity, well-being, locomotive syndrome risk tests, and social capital were measured. Although this study was not blinded to the participants, the measurers did not know to which group the participants belonged. Mixed model repeated-measures analyses and a post hoc Wilcoxon signed rank sum test were performed to detect the effects of the intervention in all groups.
RESULTS: The results of the mixed model repeated-measures analyses showed a significant interaction between groups and before and after the intervention for total physical activity (metaverse group: pre 737.1, SD 609.5 METs/week, post 1575.4, SD 1071.8 METs/week; YouTube group: pre 661.7, SD 710.7 METs/week, post 911.9, SD 1103.3 METs/week; and control group: pre 930.6, SD 665.1 METs/week, post 844.7, SD 701.8 METs/week; P=.04) but none for the indicators of well-being (P=.40), locomotive function scale (P=.17), and social capital (P=.23). A post hoc test showed a significant increase in physical activity in the metaverse group before and after the intervention (P=.006).
CONCLUSIONS: This study is the first to show that delivering exercise videos through metaverse space can increase physical activity in young adults by providing a gathering space for individuals similarly motivated for exercise practice. This way, the sense of isolation during exercise is reduced compared with merely distributing videos on YouTube. The use of metaverse space in health promotion is likely to spread, and this study provides a useful reference for its exploration.
BACKGROUND: ClinicalTrials.gov NCT06019156; https://ichgcp.net/clinical-trials-registry/NCT06019156.

Research has shown a link between depression risk and how gamers form relationships with their in-game figure of representation, called avatar. This is reinforced by literature supporting that a gamer\'s connection to their avatar may provide broader insight into their mental health. Therefore, it has been argued that if properly examined, the bond between a person and their avatar may reveal information about their current or potential struggles with depression offline. To examine whether the connection with an individuals\' avatars may reveal their risk for depression, longitudinal data from 565 adults/adolescents (Mage = 29.3 years, SD = 10.6) were evaluated twice (six months apart). Participants completed the User-Avatar-Bond [UAB] scale and Depression Anxiety Stress Scale to measure avatar bond and depression risk. A series of tuned and untuned artificial intelligence [AI] classifiers analyzed their responses concurrently and prospectively. This allowed the examination of whether user-avatar bond can provide cross-sectional and predictive information about depression risk. Findings revealed that AI models can learn to accurately and automatically identify depression risk cases, based on gamers\' reported UAB, age, and length of gaming involvement, both at present and six months later. In particular, random forests outperformed all other AIs, while avatar immersion was shown to be the strongest training predictor. Study outcomes demonstrate that UAB can be translated into accurate, concurrent, and future, depression risk predictions via trained AI classifiers. Assessment, prevention, and practice implications are discussed in the light of these results.

Conversation is a time-pressured environment. Recognizing a social action (the \'\'speech act,\'\' such as a question requesting information) early is crucial in conversation to quickly understand the intended message and plan a timely response. Fast turns between interlocutors are especially relevant for responses to questions since a long gap may be meaningful by itself. Human language is multimodal, involving speech as well as visual signals from the body, including the face. But little is known about how conversational facial signals contribute to the communication of social actions. Some of the most prominent facial signals in conversation are eyebrow movements. Previous studies found links between eyebrow movements and questions, suggesting that these facial signals could contribute to the rapid recognition of questions. Therefore, we aimed to investigate whether early eyebrow movements (eyebrow frown or raise vs. no eyebrow movement) facilitate question identification. Participants were instructed to view videos of avatars where the presence of eyebrow movements accompanying questions was manipulated. Their task was to indicate whether the utterance was a question or a statement as accurately and quickly as possible. Data were collected using the online testing platform Gorilla. Results showed higher accuracies and faster response times for questions with eyebrow frowns, suggesting a facilitative role of eyebrow frowns for question identification. This means that facial signals can critically contribute to the communication of social actions in conversation by signaling social action-specific visual information and providing visual cues to speakers\' intentions.

UNASSIGNED: Gaming disorder [GD] risk has been associated with the way gamers bond with their visual representation (i.e., avatar) in the game-world. More specifically, a gamer\'s relationship with their avatar has been shown to provide reliable mental health information about the user in their offline life, such as their current and prospective GD risk, if appropriately decoded.
UNASSIGNED: To contribute to the paucity of knowledge in this area, 565 gamers (Mage = 29.3 years; SD =10.6) were assessed twice, six months apart, using the User-Avatar-Bond Scale (UABS) and the Gaming Disorder Test. A series of tuned and untuned artificial intelligence [AI] classifiers analysed concurrently and prospectively their responses.
UNASSIGNED: Findings showed that AI models learned to accurately and automatically identify GD risk cases, based on gamers\' reported UABS score, age, and length of gaming involvement, both concurrently and longitudinally (i.e., six months later). Random forests outperformed all other AIs, while avatar immersion was shown to be the strongest training predictor.
UNASSIGNED: Study outcomes demonstrated that the user-avatar bond can be translated into accurate, concurrent and future GD risk predictions using trained AI classifiers. Assessment, prevention, and practice implications are discussed in the light of these findings.