ABSTRACT. Background Time spent on social media has risen rapidly in recent decades. Most psychological research exploring this phenomenon has focused on problematic social media use, frequently exploring posited links with psychopathology and broader health problems. Very few studies, however, have attempted to explore how social media use might also contribute to positive psychological states.

Aims Using a the PERMA framework, this study explored the association between self-reported social media use and psychological wellbeing.

Method Based on data from the 2023 global digital wellbeing survey the study spanned 35 nations (N = 35,000) and seven world regions. Along with other items, participants completed a measure of positive social media use, comprised of five questions assessing positive emotions, engagement, relationships, meaning and achievement (PERMA) in the context of social media use. Participants also completed single-item measures of life satisfaction, autonomy, competence and relatedness.

Results As hypothesized, positive social media use was positively correlated with life satisfaction, autonomy, competence and relatedness. A regression analysis found that this association between positive social media use and wellbeing variables remained even after controlling for demographic factors such as age, gender, education and employment status. Alongside the current focus on cyber-psychopathology and problematic social media use, there is a need for complimentary research exploring the ways in which social media use might actively contribute to wellbeing.

ABSTRACT. Social performance situations, often crucial and expected in today’s work contexts, can be perceived as highly challenging and stressful. Therefore, experiencing anxiety in public speaking situations can have a negative impact on individuals’ working lives and career prospects.

Virtual Reality Environments (VRE) offer novel means to practise public speaking anywhere, safely and privately, and to replace simulations with more dynamic and innovative training environments unavailable in real-life scenarios. Additionally, these innovative tools and methods could also be used during virtually implemented real-life interactions as working conditions are increasingly shifting towards more technology-mediated forms.

This research uses a strictly controlled, between-subject experiment to investigate the potential for a virtual reality (VR) height manipulation (i.e., raised or lowered point-of-view) to influence individuals’ self-statements during a stressful speech task and, subsequently, their personal performance evaluation. The design of the experiment and the associated hypotheses were preregistered in the Open Science Framework (OSF); this work forms the second part of the planned study, with the first part being published in 2023.

The sample (n = 61) consisted of a generally healthy, multicultural group of mainly university students and employees. Participants were randomly assigned to one of two experimental conditions (perceiving themselves shorter or taller) and were required to complete a five-minute speech task in a VRE. Participants completed self-report measures pre- and post-task, while also assessing their own performance after completing the task.

Data was analysed in a two-stage process, first pairwise comparisons were conducted to examine potential differences between experimental conditions, while in the second stage PLS-SEM was used to identify relationships between a range of independent variables and two dependent variables: self-statements during the speech task, and personal performance evaluation of the speech task.

Results of the pairwise comparisons indicate that participants in the tall condition evaluated their speech performance more positively than those in the short condition. The PLS-SEM analysis found that the tall condition displayed a statistically significant, negative relationship with negative self-statements. That is, that the tall condition was associated with less negative self-statements during the speech task.

Overall, the PLS-SEM analysis supported the results of the pairwise comparisons between experimental conditions. A statistically significant, positive correlation was found between the tall condition and performance evaluation, thus supporting the positive effect of the perceived tallness on participants’ personal speech performance assessment. A medium effect size was also detected for all above correlations, further supporting their significance.

In addition to the experimental condition, PSA was found to have statistically significant correlations with the dependent variables. Both trait PSA, as an independent variable, and state PSA, as a mediating variable, displayed positive correlations with negative self-statements, and negative correlations with speech performance evaluation. All correlations were found to have medium to large effect sizes.

These results suggest that a simple, visual first-person perspective manipulation in VRE influences individuals’ personal evaluation of their own performance and potentially helps them improve their task-related cognitive processes. Furthermore, they also add to the growing body of research supporting the use of bodily expansion to positively influence affective response and the production of thoughts during a task-oriented situation. Results suggest that even a bodily expansion replicated through novel VR and 3D technologies can affect task-related cognitive processes and positively influence personal performance evaluation.

The knowledge generated by this study has the potential to be applied to a range of therapeutic and training simulations, and to performance scenarios in VR. Furthermore, it can be used to develop new, innovative tools and methods to manage cognitive processes during personal performance in real-time, virtually implemented work-based tasks or other social interactions and performance situations.

ABSTRACT. Background: Supporting the mental wellbeing of young people is a significant challenge in public health, with half of all life-time mental illnesses developing before age 14 and 75% before age 25. However, most young people do not receive care due to myriad safety and accessibility barriers to treatment, which subsequently increase their likelihood of developing lifelong chronic mental health disorders. Considering internet-connected mobile devices are now ubiquitous among young people, many are increasingly going online for mental health support and information. Social media platforms have become integral to the lives of young people over the past decade, and many with mental health issues use these platforms to find support, acceptance, help-seeking advice, and a sense of community. However, seeking help from strangers and non-experts can expose young people to inaccurate or misleading information, as well as hostile or derogatory comments, which may negatively impact their mental health. yourtown and The University of Sydney have developed an evidence-based solution to address this need: My Circle. My Circle is a purpose-built, scalable social networking platform that provides young people with a pathway to safe, anonymous, clinically guided peer-to-peer support. The platform is safeguarded by clinical moderators to ensure conversations between members are safe, respectful, and based on accurate information. Clinical moderators aim to validate young people’s experiences, break down stigma, normalise help-seeking, and educate. Unlike existing social media platforms, My Circle is designed for safety and wellbeing, and is integrated with yourtown’s Kids Helpline for 24/7 one-on-one support.

Method: This presentation details the findings of the Phase 5 evaluation of My Circle, which was developed and refined over four previous phases using a participatory action research approach (Phase 1 and 2 have been published or presented previously). Phase 5 consisted of a 36-week mixed-method evaluation, during which demographic, psychological distress, platform usage, and qualitative feedback data was collected from almost 2,800 young people aged 13-25 years. The majority of participants identified as women/girls (62.7%), with only 12.4% of the sample identifying as men/boys. Gender-diverse, non-binary and custom gender responses made up 16.7%.

Results: Young people engaging with My Circle reported benefits such as improvements in psychological distress and mental wellbeing from baseline. Engaging with My Circle also reduced perceptions of mental health stigma, increased coping skills, and led to a greater willingness to seek help from mental health/well-being services. Those who entered the service with the most severe psychological distress reported smaller changes in distress levels over time but were more engaged with the service. The longer they accessed the service, the more likely they were to report increased safety, learning coping skills, reductions in help-seeking stigma, and awareness of mental health services. Qualitative feedback indicated that the best aspects of My Circle were connecting with peers, the supportive environment, and having online access to 24/7 support. Young people said the benefits of being able to connect with other young people in similar situations were sharing coping strategies with others, feeling understood, feeling that they aren’t alone, and helping others. Young people liked the ‘community feeling’ of My Circle, which they found to be a much more positive and safer environment than other social media platforms, allowing them to share their feelings and experiences without judgment. Moderators were appreciated for the genuine support and care they provide.

Conclusion: These results provide an evidence base for the efficacy of custom-built online social networking platforms in supporting young people experiencing depression, anxiety, stress, and self-harm behaviours through clinically guided peer-to-peer support. My Circle provides a new digital mental health practice model of care that organisations can adopt to support other vulnerable groups at scale.

ABSTRACT. Background: Concerns about the health impacts of online activities, such as gaming and social media, have led to the development of psychological interventions targeting problematic technology use. The efficacy of these interventions is typically assessed using quantitative metrics, such as decreased screentime and reductions in behavioural addiction or mood disorder symptomatology. However, few studies have examined participants’ subjective evaluations and perceptions of these interventions. Aims: This study explored the experiences of seven young adults who participated in a mindfulness-based digital wellbeing retreat.

Methodology: Semi-structured interviews, focusing on program experience and perceived impact, were subjected to interpretative phenomenological analysis.

Findings: Participants described varied struggles with technology, suggesting the retreat represented a safe space to discuss such issues while exploring alternative ways of being with their digital devices. The experience was valued for providing a connection to a supportive peer group and the natural outdoor environment. Participants also described developing a heightened awareness of their tech-use idiosyncrasies and maladaptive habits, leading to usage characterised by greater intentionality and choice.

Conclusions: Mindfulness-based approaches appear to be valuable and well-appreciated in the context of problematic technology use and the cultivation of healthier relationships with digital technology

ABSTRACT. Problematic smartphone use (PSU) involves excessive use of a smartphone, with adverse effects on daily life activities (i.e., social, work, academic functioning). Theoretical models such as the Interaction of Person-Affect-Cognition-Execution (I-PACE) model suggest that psychopathology is an important cause of excessive internet use such as PSU. Extensive research has examined relations between psychopathology constructs and PSU severity. Reviews and meta-analyses demonstrate that anxiety, and especially depression symptoms, are associated with PSU severity with small and medium effects, respectively. Despite the consistent relationship between depression and PSU severity, prior work has not investigated which aspects or underlying dimensions of depression may be most associated with PSU severity. We recruited 396 college students (in an IRB-approved study) from a Midwestern US public university’s psychology research pool for a web survey in 2023. These data have not been presented or published before. In addition to demographic characteristics, participants also completed a set of psychological scales, including the Patient Health Questionnaire-9 (PHQ-9) for depression, and Smartphone Addiction Scale-Short Version (SAS-SV) for PSU. After data exclusions for substantial missingness, careless responding, and not owning a smartphone, the final sample included 350 participants; 65% were women, and 69% were Caucasian. Average age was 19.99 years (SD = 4.33). We used Mplus 8 software to first estimate separate confirmatory factor analyses for depression and PSU, treating items as ordinal, using a polychoric covariance matrix and weighted least squares estimation with a mean- and variance-adjusted chi-square, and estimating factor loadings with probit regression. A single-factor PSU model fit well overall, robust X2(33) = 185.91, p < .001, CFI = .96, TLI = .94, RMSEA = .12, SRMR = .04. A two-factor intercorrelated depression model of (three) somatic and (six) cognitive-affective symptoms (depression Model 1) fit well, X2(25) = 62.78, p < .001, CFI = .99, TLI = .99, RMSEA = .07, SRMR = .03 (a competing model from the literature with five somatic and four cognitive-affective symptoms, depression Model 2, fit just slightly worse). A combined, intercorrelated model of the PSU factor and depression Model 1’s two factors fit well, X2(148) = 317.26, p < .001, CFI = .97, TLI = .97, RMSEA = .06, SRMR = .05. The PSU factor was significantly associated with both depression’s cognitive-affective factor (r = .39) and somatic factor (r = .35). Using a Wald chi-square test of parameter constraints, PSU was found to correlate more strongly with the cognitive-affective than somatic factor, X2(1) = 5.37, p = .02. An extremely similar finding was obtained when using the alternative depression Model 2 instead of Model 1 and reconducting the Wald test. Results move beyond prior research only examining depression as a whole in relation to PSU severity. Both cognitive-affective and somatic depression symptom dimensions appear fairly robustly related to PSU severity, but the relationship is stronger for depression’s cognitive-affective dimension. Results support theoretical models such as I-PACE that emphasize cognitive-affective processes that may drive some people to overuse their smartphone in an attempt to alleviate poor mood and maladaptive cognitions.

ABSTRACT. A great deal of research has found psychopathology related to increased problematic smartphone use (PSU) severity. Yet little research has examined affective or cognitive regulation variables that may account for this relationship. The I-PACE model is a theoretical framework that explains the processes underlying the development and maintenance of excessive internet use. Couched within the I-PACE model, we present data collected from a medium-sized Midwestern U.S. university. 337 undergraduate psychology students reporting current use of a smartphone completed a cross-sectional web survey in 2023. Participants were recruited from the psychology department’s research pool, for Introductory Psychology course research points. Participants were administered the Patient Health Questionnaire-9 for depression, Generalized Anxiety Disorder Scale-7, Distress Tolerance Scale, and Smartphone Addiction Scale Short Version. Confirmatory factor analyses (using Mplus) were used, treating scales’ items as ordinal, using a polychoric covariance matrix, probit factor loadings, and weighted least squares estimation with a mean- and variance-adjusted chi-square. CFAs for all scales fit well. Then we tested a latent structural equation model using the same estimation approach, in which latent constructs of depression and anxiety were specified to predict distress tolerance, in turn predicting PSU. Age and sex were used as additional covariates of PSU. Mediation was tested using the delta method for computing indirect effect standard errors, using 1000 non-parametric bootstrapped replications. The full structural model fit reasonably well, Chi-Square(853) = 1677.2, p < .001, RMSEA = .05, CFI = .94, TLI = .94, SRMR = .08. Only depression (but not anxiety) was significantly associated with lower distress tolerance (standardized B = -.51, SE = .11, p < .001). Distress tolerance was significantly associated with decreased PSU (B = -.50, SE = .05, p < .001), adjusting for age and sex (neither covariate was significant). Lower levels of distress tolerance significantly mediated relations between depression (but not anxiety) and PSU severity (B = .25, SE = .06, p < .001). Distress tolerance may be an important affective regulation mechanism influencing why some depressed individuals engage in decreased PSU levels. Findings fit within the I-PACE model which theorizes the important intermediary effect of affect regulation in accounting for relations between psychopathology and excessive internet use.

ABSTRACT. Although social media platforms offer numerous benefits to their users, excessive use can potentially lead to problematic and/or maladaptive outcomes. Considering the widespread adoption of social media and its inherently social nature, investigating the correlation between social anxiety, transdiagnostic psychopathology-related factors, and problematic social media use (PSMU) is crucial. Within the I-PACE theoretical model of internet use disorders, psychopathology such as social anxiety serves as a predisposing factor for PSMU, with cognitive and affective elements such as affective states and trait mindfulness potentially mediating this association. In 2023-2024, we recruited 378 college students from a Midwestern US public university’s psychology research pool for a web survey, in an IRB-approved study. In addition to demographic characteristics, study participants also completed a set of psychological scales, including the Social Phobia Inventory (SPIN) for social anxiety, Positive and Negative Affect Scales (PANAS) for positive and negative affect over the past month, Mindful Attention and Awareness Scale (MAAS) for trait mindfulness, and Bergen Social Media Addiction Scale (BSMAS) for PSMU. After data exclusions for substantial missingness, careless responding, and those without a social media account, our final sample included 319 participants; 61% were female, and 60% were white. Average age was 19.75 years (SD = 1.58). Mplus 8 software was used to estimate confirmatory factor analysis (CFA) for PSMU, using maximum likelihood estimation with robust standard errors (MLR), treating items as continuously scaled, thus using a Pearson covariance matrix and linear regression coefficients for estimating factor loadings. We only modeled BSMAS with CFA to preserve power. The BSMAS CFA demonstrated reasonably good fit, Chi-Square(8) = 15.19, p = .055, RMSEA = .05, CFI = .99, TLI = .98, SRMR = .02. We then tested our structural equation model (SEM) with Mplus using MLR estimation. In this model, social anxiety was specified to predict our mediators - mindful awareness, positive and negative affect; our mediators in turn were specified to predict latent PSMU severity, with age and sex specified as covariates. The full structural model demonstrated reasonably good fit, Chi-Square(48) = 113.23, p < .001, RMSEA = .066, CFI = .94, TLI = .92, SRMR = .05. Social anxiety was significantly associated with lower mindfulness (standardized B = -.46 SE = .05, p < .001), lower positive affect (B = -.28 SE = .05, p < .001), and higher negative affect (B = .61, SE = .04, p < .001). Lower trait mindfulness (B = -.21, SE = .07, p = .001) and higher negative affect B = .41, SE = .07, p = .001) were significantly associated with increased PSMU severity, while positive affect was not significantly associated with increased PSMU (B = .07, SE = .06, p = .23), adjusting for age and sex at birth. Female sex at birth was significantly associated with increased PSMU (B = -.18, SE = .05, p = .001). Mediation was tested using the delta method for computing indirect effect standard errors with the maximum likelihood estimator, using 1000 non-parametric bootstrapped replications. In our mediation model, lower levels of mindfulness significantly mediated relations between social anxiety and PSMU severity (B = .10, SE = .04, p = .005). Higher levels of negative (but not positive) affect also significantly mediated this relationship (B = .25, SE = .05, p < .001). Therefore, levels of trait mindfulness and elevated negative affective states may influence whether socially anxious individuals engage in greater PSMU levels. These results fit well within the I-PACE model, with trait mindfulness and negative affect functioning as cognitive/affective variables accounting for the relationship between social anxiety and problematic social media use.

ABSTRACT. Problematic smartphone use (PSU) is commonly conceptualized by the Interaction of Person-Affect-Cognition-Execution (I-PACE) theoretical model, which explains the development of PSU through risk factors such as predisposing, affective, and cognitive variables. Previous research has highlighted psychopathology as a predisposing factor, including symptoms of anxiety, though more research on the role of mediators such as emotion dysregulation and coping style are needed. Data are presented from undergraduate students enrolled in introductory psychology courses (participating for research points) who endorsed current smartphone use at a medium-sized Midwestern US university. From 2023 to 2024, we administered a cross-sectional web survey including the Generalized Anxiety Disorder Scale-7 for general anxiety, Social Interaction Anxiety Scale for social anxiety, Brief Cope for avoidant coping style, Emotion Regulation Questionnaire for expressive emotional suppression (i.e., emotion dysregulation), and Smartphone Addiction Scale-Short Version (i.e., PSU). Confirmatory factor analyses (CFA), structural equation modeling (SEM), and mediation analyses were completed using Mplus. For the PSU CFA, scale items were treated as ordinal; and weighted least squares estimation with a mean- and variance-adjusted chi-square was used to estimate a polychoric covariance matrix and probit factor loadings. We only modeled PSU with CFA (which fit adequately), to preserve power. Next, we tested an SEM with the same estimation approach; only PSU was modeled as a latent factor. Observed variables of general and social anxiety were specified to predict expression suppression and avoidant coping style, which then predicted the PSU CFA; general and social anxiety were also specified to predict the PSU CFA. Some evidence of adequate fit for the model was found, Chi-Square(96) = 313.78, p < .001, CFI = .92, TLI = .90, SRMR = .18, RMSEA = .09 (90% CI = .08 to .10). PSU was significantly associated with avoidant coping (standardized B = .15, SE = .06, p = .01), social anxiety (B = .30, SE = .06, p < .001), and sex (B = .18, SE = .06, p = .01). Avoidant coping was significantly associated with both general and social anxiety (B = .38, SE = .06, p < .001; B = .13, SE = .06, p = .02), and emotional expressive suppression was related to general anxiety (B= .20, SE = .07, p = .01), but not social anxiety (B = .12, SE = .07, p = .06). Next we utilized a mediation approach with the delta method for computing indirect effect standard errors, using 1000 non-parametric bootstrapped replications. However, no significant mediation effects were revealed. Results demonstrate support for some forms of affective processes (avoidant coping, but not expressive suppression), and some types of anxiety (social, but not generalized) in association with PSU severity. Results do not support affective processes as mediators explaining relations between anxiety and PSU severity. Further implications will be discussed.

ABSTRACT. The phenomenon of Problematic Smartphone Use (PSU) is prevalent. PSU literature is far-reaching and profound, demonstrating a complex mixture of antecedents and consequences regarding this problematic behavior. This study aimed to elucidate the complex nature of PSU by examining potential antecedent mental health-related constructs. By analyzing various subscales of each measure, this study investigates whether all or only some characteristics of a construct predict PSU severity. As an innovation, we employed elastic net regression for our analytic strategy, to assess the relationship PSU severity has with scales and subscales of generalized anxiety disorder (GAD), major depressive disorder (MDD) symptoms, distress tolerance, impulsivity, and trait mindfulness. Elastic net regression is a machine learning algorithm that handles multicollinearity by shrinking unreasonably large regression coefficients down toward zero, and even conducts model subset selection by removing variables from the model that are irrelevant to predicting an outcome (shrinking their coefficients to exactly zero). Using Qualtrics, we conducted a web-based survey of undergraduate students attending Introduction to Psychology courses at a public American university (N = 379; 209, 58.54% female; ages 18 – 42 years). The data were collected from January 2023 through October 2023. Using R software (V. 4.3.3) with the glmnet package (V. 4.1-8), we conducted an elastic net regression on the 33-item Smartphone Addiction Scale (SAS; for PSU) total score to discover relationships with the Generalized Anxiety Disorder-7 (GAD-7), and subscale scores on the Patient Health Questionnaire-9 for depression (PHQ-9), Distress Tolerance Scale (DTS), Psychological Mindedness Scale (PMS), and short version of the UPPS Scale for impulsivity. The elastic net regression results demonstrated that the model of predictors accounted for 24% of the variance in PSU severity. Variable importance (VI) values are presented, that are similar to standardized regression coefficients because we standardized our dependent variable and continuously-scaled predictors. Neither sex nor age predicted PSU severity (VIs = 0). However, the absorption (VI = 0.103) and tolerance (VI = 0.061) subscales of the DTS, total score on the GAD-7 (VI = 0.078), (lack of) perseverance on the UPPS (VI = 0.050), and cognitive subscale of the PHQ-9 (VI = 0.013) were found to be important variables in the model. While this study is not generalizable to the public at large, all of the constructs represented by these scales have previously been associated with PSU severity in other studies examining similar samples. These findings demonstrate the need to investigate further how/if the components of these scales and others are related to PSU severity. Future research should continue to examine PSU as a complex issue by performing more holistic studies that examine the interaction between participants’ dispositions, their cognition, and ability to manage their environments.

ABSTRACT. Distraction during augmented reality (AR) immersion is often believed to make the users vulnerable to social engineering (Wang, 2021), including real-time malicious push notifications (Hyun, 2018). While existing studies have emphasized distraction as a vector exploited by threat actors for social engineering using tactics such as communication requests and time-sensitive requests (Cano, 2024), a dearth of research remains as to how extended reality-specific distraction affects user judgment of the legitimacy of objects appearing on screen in real time. Provided the increasing use of augmented reality mobile applications in a workplace setting (Brue, 2023), this two-stage qualitative empirical study aims to assess user susceptibility in order to subsequently propose a hypothetical security solution to help mitigate this threat. Given the existence of peer pressure in a leisure setting and risk of missing a call or message from a manager or co-worker in an employer setting, the hypothesis predicted that the majority of participants in both scenarios would prioritize responding to a communication request over a time-sensitive device update notification.

The methodology involved an in-depth questionnaire administered via email to 70 participants (regular users of augmented reality for both leisure and at the workplace, aged 18-40) regarding interaction with push notifications within an AR simulation. Each participant was presented with a link to an online animation-enhanced simulation centering the following AR mobile interfaces suggested as popular AR apps (Klyagin, 2020) and regularly used by the selected participants: Google Lens, Google Translate, Instagram, Maps, and Pokémon GO. The simulation presented users with the option of engaging with a push notification appearing on screen while using all five applications, with option A denoting a familiarity theme (“Contact calling in”) and option B denoting an urgency theme (“Update now or device will re-start in 5 minutes”). Users were then asked to explain the rationale behind their choices. Collated responses to the questionnaire for both the leisure and workplace settings showed a trending preference for the familiarity theme, with recurring reasoning citing the assumption that a friend or co-worker might be calling in. As predicted by the hypothesis, this sense of obligation tended to supersede the risk of data progress loss upon a forced reboot.

Given this risk to both individual users and organizational reputation, such a threat vector could be mitigated from the developer standpoint. To propose a solution, four experts were consulted in the business, backend, and user experience fields of AR application development to design a hypothetical artificial intelligence (AI) equipped feature that could detect suspicious artifacts entering the user’s line of sight during partial immersion in an AR application at the workplace. Participants included a business partner at an AR firm and a security engineering manager at a top Fortune 500 organization for the market appeal of such a feature; an AI engineer focused on machine learning for a detailed concept of the feature’s functionality, and a user experience (UX) specialist for consideration into potential user-facing setbacks. Interview questions were administered via email, consulting each respective participant regarding the backend structure and UX challenges of an application disrupting real-time social engineering threats, with emphasis on familiarity-based on-screen notifications. This mitigation proposal stage of the study determined that a security application natively implemented into the device could use heuristic analysis of user screen captured activity to assess potentially malicious push notifications in real time. Finally, participant responses revealed that, while necessary for user and organizational security, has not yet been developed due to challenges in balancing application visibility with user privacy. Therefore, future studies could entail a merging of engineering and privacy expertise to devise a realistic framework for such a feature.

ABSTRACT. Geohazards represent a multifaceted array of engineering challenges warranting deeper inquiry and exploration. The complexities inherent in these phenomena demand thorough investigation. For instance, the seismic disturbances triggered by earthquakes manifest as seismic bumps within coal mines, soil liquefaction, and slope collapse, necessitating a comprehensive assessment of various unpredictable factors. Devising solutions for these intricate geotechnical issues involves evaluating numerous variables. Furthermore, the aftermath of natural disasters often leads to significant consequences and losses, underscoring the critical need for proactive measures. Implementing an early warning system emerges as a crucial solution capable of potentially saving numerous lives. Such systems can significantly enhance evacuation efficiency by providing alerts mere seconds to minutes before the onset of disasters, particularly in high-risk locations. Moreover, integrating these systems at the planning stages of projects can substantially minimize the life cycle loss of life, material resources, and effort. This study introduces a groundbreaking approach—an innovative classification system that seamlessly integrates swarm and metaheuristic intelligence designed to yield categorical outputs. Accompanying this system is a meticulously developed graphical user interface (GUI), serving as a valuable tool for engineers and researchers engaged in sophisticated data mining tasks. The efficacy of the proposed system is rigorously validated through its application to various geotechnical case studies. Comparisons with empirical methods and previous works underpin its credibility and robustness. Three pivotal contributions emerge from this investigation: the introduction of a pioneering nature-inspired classification system, the development of an intuitive GUI complementing the classification system, and the demonstration of the system's effectiveness in forecasting geotechnical hazards ahead of time—an invaluable asset in providing early warnings and mitigating impending impacts.

ABSTRACT. Mental health is an established area of importance for healthcare sectors across the world. Social connection has been found to have marked benefits for an individual’s psychological wellbeing (Small, Taft & Brown, 2011). For example, having a support network has been found to increase self-esteem (Williams & Galliher, 2006) and improve individuals’ self-reported quality of life (Levula, Wilson & Harre, 2016). Videogaming has become increasingly popular, with a predicted 3 billion players worldwide in 2020 (Clement, 2023). In the last 15 years, some videogames have advanced to incorporate features for players to interact with each other, providing opportunities to make friends (Gamers Worldwide by Region, 2021). A thorough examination of increased online interaction through gaming is paramount to understand how social connections are formed and how these connections change over time.

Social capital refers to the resources, relationships, and networks that individuals or groups possess within a social structure (Putnam, 2000). It is considered an asset as it facilitates social interactions, enhances social cohesion, and contributes to individual and collective well-being. Gaming may offer opportunities for bonding (creating close relationships within gaming communities) and bridging (establishing connections with individuals from different backgrounds) social capital (Putnam, 2000). Understanding the nature of social capital in gaming contexts can provide insights into the potential benefits and challenges associated with these relationships. This knowledge can inform interventions, policies, and practices aimed at maximising the positive impact of gaming on social connections.

Social capital within the gaming community has been widely researched (Kaczmarek & Drążkowski, 2014; Kowert, Domahidi, & Quandt, 2014, Travaglino et. al., 2020; Tham, Ellithorpe & Mechi, 2020) however, the results are varied as to the effect of gaming on social capital. Some studies suggest that gaming is associated with increased social capital (Kaczmarek & Drążkowski, 2014) with benefits particularly for shy or introverted individuals (Kowert, Domahidi, & Quandt, 2014). Other studies suggest that this is not the case, and relationships through online gaming had no relationship with reduced feelings of loneliness, a component of social capital (Travaglino et. al., 2020). The complex nature of social interactions in gaming communities, influenced by factors such as game genre, community dynamics, and individual preferences (Kowert, Domahidi, & Quandt, 2014; Tham, Ellithorpe & Mechi, 2020), contributes to the lack of a definitive consensus on the impact of online gaming on social capital.

This study aimed to explore this contentious domain of inquiry by conducting a study to consider the relationships individuals have forged through videogames. This research study had two components, a longitudinal study considering the stability of videogaming relationships over time, and a qualitative exploration of the perceived quality of these relationships. This submission will focus on the qualitative component. The study considered individuals over 18 who self-identified as videogamers and spoke English. This research is ongoing, and results will be available for thematic review next month. It is expected that the results will yield themes related to how individuals formed relationships, how they describe their connection to the videogaming community and the best and most challenging things about engaging with other videogame players. Saturation, as defined in the qualitative paradigm, will determine the number of participants reported. It is expected that the results will draw a conclusion on the perspectives of videogamers on their relationship with others.

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ABSTRACT. Objectives: The long-term effects of COVID-19, also referred to as post-covid-19 condition (PCC), may affect emotional state and heart rate variability (HRV), adding to evidence that persistent symptoms of the virus are associated with anxiety, depression, and cardiac and autonomic nervous system (ANS) problems. PCC can significantly disrupt the ANS, adversely affecting both physical and psychological functioning, leading to a decline in quality of life and increased risk of age-related diseases. Multimodal interventions that combine mindfulness practices, cognitive exercises, and physical activities could enhance HRV in individuals experiencing PCC. In addition, the use of cave-based virtual reality (VR) systems, which allow for group settings and remove the need for older adults to wear individual headsets, could improve the engagement of participants in these programs, potentially minimizing dropout rates. This study aims to assess whether there are changes in frequency-based HRV measures in adults with PCC before and after a multimodal intervention using cave-based VR system.

Methods: Nineteen adults over the age of 18 with a diagnosis of PCC (Mage = 47.74 years, SD= 8.65 years; MBMI= 26.09 kg/m2, SD= 4.82 kg/m2) were recruited. Participants had to be fluent in Spanish or Catalan. Exclusion criteria included pre-existing severe cognitive, psychiatric, neurological, or significant sensory and motor disorders that could interfere with the intervention. All participants underwent a multimodal IVR intervention delivered through the CAVE-system MK360 VR technology (Broomx company) in a group session of 5 participants and was facilitated by a psychologist. Each 60-minute program session included three activities: mindfulness, cognitive training, and physical exercise, and sessions were conducted once or twice a week for 12 weeks. Frequency domain HRV measures included very low frequency (VLF), low frequency (LF), and high frequency (HF). HRV assessments were performed at the first and last sessions of the intervention. Each HRV data record was taken immediately after the VR session.

Results: Wilcoxon signed-rank tests, nonparametric alternatives to paired-sample t-tests, were performed to assess differences in HRV measures before and after the intervention. Results did not show any statistically significant differences in VLF (z = -.327, p = .74), LF (z = 1.372, p = .17), and HF (z = -.283, p = .48) before and after the intervention. Overall, there were non-significant increases from pre (LF-Mdn = 1.04, HF-Mdn =.51) to post (LF-Mdn = 1.37, HF-Mdn =.55) assessments. While VLF showed the opposite trend, with a non-significant reduction from pre- (Mdn = .48) to post-assessment (Mdn = .39).

Conclusions: This study represents, as far as we know, the first integration of HRV assessment with immersive VR training in patients with PCC, using a multimodal approach that combines mindfulness-based interventions, cognitive training, and physical activity. Using CAVE-based VR systems, this research enhances traditional interventions for PCC by providing a shared, immersive IVR environment that replicates real-life scenarios without needing individual headsets, thus facilitating greater participant access and adherence. Although we did not observe significant changes in HRV measures, and the study has inherent limitations, such as the small sample and the lack of follow-up data, it remains essential as it provides preliminary insights into the physiological frequency-based HRV activity of adults with PCC before and after the multimodal intervention. These findings enrich our understanding of the physiological and emotional states experienced by patients with PCC, and lay the groundwork for future research in this area.

ABSTRACT. When taking cognitive tests, there is a noticeable change in nervous system activity compared to rest [1, 2]. This change can be observed in electroencephalography (EEG) during typical computer-based tests, two-dimensional computer-based tests, and virtual reality tests. This study aims to investigate the features that distinguish elite athletes from sedentary participants using a novel working memory task in an immersive virtual reality environment. This study is approved by the Ethical Committee Of Marmara University, Faculty of Medicine with the protocol code 09.2022.606/10.05.2022.

Ten elite triathletes and ten age and gender-matched sedentary participants gave written informed consent before data collection. We used Wearable Sensing’s wireless DSI-7 EEG hardware within the NoraVRx digital assessment platform to collect working memory responses via behavioral and electrophysiological data. EEG data was collected with a sampling frequency of 300 Hz from parietal, frontal, and central regions using seven electrodes (Pz, F4, C4, P4, P3, C3, and F3). Specifically, we obtained participants' visuospatial and verbal working memory scores using behavioral responses recorded by NoraVRx. Since the participants used their hands and moved their heads during the experiments, EEG recordings were contaminated with noise. Thus, we applied independent component analysis to each subject's EEG data for the identification of the noise components. Then we removed noisy components and backprojected the data. Finally, conventional spectral band power values were computed from the cleaned EEG data. Preprocessing steps of the EEG were performed using Matlab2023 (3) and Fieldtrip toolbox (4). We applied Mann-Whitney U tests on physiological features and behavioral responses to ascertain the differences between the elite triathletes and the control group.

The behavioral responses of the subjects did not differ significantly between the two groups, while alpha and gamma band power values were found to be the discriminator parameters between the elite athletes and the control group. Elite triathletes were found to have less alpha band event related desynchronization (ERD=[task-baseline]/baseline) of parietal electrodes than the control subjects (Pz: U=11, p<0.001, rsb=0.78; P3: U=10, p<0.002, rsb=0.8; P4: U=13, p<0.004, rsb=0.74). Similarly, the gamma band power value of the Pz electrode was found to differ significantly between the two groups (Pz: U=7, p<0.001, rbs=0.86).

The increased salient brain oscillation in the alpha band power is associated with task-irrelevant cortical areas whereas a decrement is prominent in the task-relevant areas. In this study, we observed this spatial electrophysiological spectral difference during the performance of a novel working memory task in an immersive virtual reality environment. Although the behavioral scores of the two groups did not differ, electrophysiological differences of alpha and gamma bands between the two groups support the neural efficiency hypothesis; namely, athletes showed less alpha ERD values compared to sedentary participants. To conclude, we can propose that immersive virtual reality experiences can be useful in discriminating electrophysiological responses between elite athletes and sedentary participants, even in small sample sizes.

References

1 L.K McEvoy, M.E Smith, A Gevins, Test–retest reliability of cognitive EEG, Clinical Neurophysiology, Volume 111, Issue 3, 2000, pp 457-463, 2 Wolfgang Klimesch, EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis, Brain Research Reviews, Volume 29, Issues 2–3 1999 3 MATLAB Version: 23.2.0.2515942 (R2023b) Update 7 4 Oostenveld, R., Fries, P., Maris, E., Schoffelen, JM (2011). FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data. Computational Intelligence and Neuroscience, Volume 2011 (2011), Article ID 156869, doi:10.1155/2011/156869

ABSTRACT. The rapid evolution of online dating platforms has primarily centered around text-based and 2D visual interactions, which often fail to emulate the depth and dynamism of face-to-face experiences. This research investigates the application of augmented reality (AR) to create shared virtual spaces that offer a more immersive and engaging way for participants in online dating scenarios to interact, potentially deepening emotional connections.

Central to our investigation is the hypothesis that physical co-presence plays a crucial role in relationship dynamics, which AR can simulate through the creation of a three-dimensional, interactive virtual environment. This study develops a prototype AR system that enables users to cohabit and personalize a shared virtual space, thereby fostering a sense of shared daily experiences and presence.

We conducted a series of experiments involving diverse demographic groups to evaluate the impact of immersive virtual environments on the perceived quality of online interactions. Our findings indicate significant improvements in user engagement and emotional investment when interacting in AR-enhanced environments compared to traditional online dating interfaces. The analysis highlights a particularly strong response from users who experience geographical separation barriers, suggesting that AR can effectively bridge the gap caused by physical distance.

Future research will focus on refining the AR interface to improve user intuitiveness and expand accessibility. Additionally, longitudinal studies are planned to assess the long-term effects of continuous AR interactions on relationship stability and satisfaction.

This study contributes to the field by demonstrating the viability of AR technologies in enhancing emotional connections in online dating, suggesting a shift towards more interactive and presence-emulating platforms in the pursuit of meaningful digital romantic relationships.

ABSTRACT. I. INTRODUCTION Extended reality (XR) technologies are often limited to visual and auditory elements. Many XR technologies can provide visual and auditory information in high fidelity, but the quality of other sensory modalities, tends to be limited. Haptic information can be combined with that of other sensory modalities to provide a richer, and more in-depth understanding of objects within virtual environments, and allow for more naturalistic interactions. Non-invasive forms of electrical stimulation of nerves in the upper limb can be used to produce sensations as though they were coming from more distal regions (Kourtesis et al., 2022). Electrical stimulation based techniques allow the user to receive information about touch and, due to the size of the stimulation electrodes, have a limited impact on movement. The ExtendedTouch (xTouch) platform uses electrodes on the surface of the skin to activate peripheral nerves by utilizing an electrical stimulation technique called Channel-Hopping Interleaved Pulse Scheduling (CHIPS; Pena et al., 2021; Shell et al., 2022). CHIPS was created to evoke percepts that feel as though they are coming from the hand by improving current electrical stimulation-based neuro-haptic feedback techniques. Outcomes from XR applications such as performance of tasks can be enhanced by increased immersion (Huang et al., 2021). The current study aimed to examine the potential of the immersiveness of a non-invasive neurostimulation-based haptic feedback XR application to influence participants’ ability to identify characteristics of virtual objects. II. METHODS 16 participants (1 excluded from final sample due to incomplete data) completed a virtual object identification task. After providing informed consent participants completed the Immersive Tendency Questionnaire (ITQ). The ITQ assesses participants’ likelihood to become immersed within virtual environments. Next, all participants performed a stimulation calibration procedure, during which electrodes were placed at the wrist to elicit sensations referred to the hand on electrical stimulation (Pena et al., 2021). Participants were asked to identify characteristics of the virtual objects (VO). Six VOs categorized by combinations of two size, small or large, and three compliance categories, soft, medium, or hard were presented in a randomized order for 36 total presentations (6 per object). A verbal response indicated the identified size and compliance of the object. The Presence Questionnaire (PQ) was administered after completion of the virtual object identification task. III. RESULTS Bayesian analysis indicated that sense of presence (PQ scores) was unlikely to be linked to accuracy of identifying size or compliance of virtual objects; all Bayes Factors (BFs) were approximately 1 or less. However, there was some anecdotal evidence that the ITQ implication subscale and the PQ interface quality and sound subscales were related to the size accuracy (BFs between 1 and 2). Compliance accuracy and overall accuracies were related to the ITQ implication subscale (BFs between 1 and 2). IV. DISCUSSION & CONCLUSION It has been suggested that increases in sense of presence and immersion can lead to enhanced performance within virtual environments; our results did not support this suggestion. Our results indicated that the levels of immersion associated with neuro-haptic feedback alone were unlikely to be related to accuracy in identifying characteristics of VOs. Two factors that may have impacted the results are the relatively small sample size and the fact that we studied neuro-haptic feedback in isolation of visual or auditory feedback, which may not be immersive enough to produce meaningful experiences of sense of presence. While the current study did not find evidence of measures of sense of presence impacting performance in a virtual object identification task, neurostimulation-based haptic feedback in combination with visual and auditory elements may lead to greater levels of sense of presence and potentially more naturalistic interactions within XR applications. REFERENCES [1] Kourtesis, P., Argelaguet, F., Vizcay, S., Marchal, M., & Pacchierotti, C. (2022). Electrotactile feedback applications for hand and arm interactions: A systematic review, meta-analysis, and future directions. IEEE transactions on haptics, 15(3), 479-496. [2] Pena, A. E., Abbas, J. J., & Jung, R. (2021). Channel-hopping during surface electrical neurostimulation elicits selective, comfortable, distally referred sensations. Journal of neural engineering, 18(5), 055004. [3] Shell, A. K., Pena, A. E., Abbas, J. J., & Jung, R. (2022). Novel neurostimulation-based haptic feedback platform for grasp interactions with virtual objects. Frontiers in Virtual Reality, 3, 910379. [4] Huang, W., Roscoe, R. D., Johnson‐Glenberg, M. C., & Craig, S. D. (2021). Motivation, engagement, and performance across multiple virtual reality sessions and levels of immersion. Journal of Computer Assisted Learning, 37(3), 745-758. [5] Diemer, J., Alpers, G. W., Peperkorn, H. M., Shiban, Y., & Mühlberger, A. (2015). The impact of perception and presence on emotional reactions: a review of research in virtual reality. Frontiers in psychology, 6, 26. *Research supported by the University of Arkansas Women’s Giving Circle. AKS, JJA, RJ are with the Department of Biomedical Engineering and the Institute for Integrative and Innovative Research (I3R), JA, AP are with I3R. Fayetteville, AR 72704 USA.

ABSTRACT. Adaptability in virtual environments has gained significant attention in recent years, particularly with the integration of Electroencephalogram (EEG) technology, which enables real-time measurement of cognitive load during various tasks. This research explores the potential of using EEG data to enhance the interactivity and realism of virtual environments, focusing specifically on its application in creating adaptive "Virtual Human" systems for training clinicians. The study investigates how EEG readings can be used to assess a user's emotional and cognitive state, thereby allowing virtual patients to adapt dynamically to the unique needs of each clinician in training. The study involved the development of a "Virtual Patient" apparatus using the Unity game engine, paired with real-time EEG readings captured by the EMOTIV EPOC X device. This EEG device measures cognitive load and emotional states through the monitoring of theta, alpha, beta, and gamma brainwave bands, providing a detailed picture of the user's engagement and mental effort during interactions with the virtual environment. The study utilized the Stroop task, a well-known cognitive test, to evaluate the participants' cognitive load and engagement levels. Results from the study demonstrated that EEG measurements could effectively depict real-time cognitive load and engagement. Across the four Stroop tasks, it was observed that alpha wave patterns, which are associated with lower cognitive load, increased steadily through the first three tasks before decreasing in the fourth task. This decline in alpha wave activity in the final task, coupled with decreases in beta and gamma wave activities, suggested that the fourth Stroop task required a significantly higher cognitive load, leading to lower participant accuracy and longer response times. Furthermore, the study highlighted the importance of considering a user's "flow" state, a condition of peak engagement, when designing adaptive virtual environments. The data suggested that as tasks became more challenging, participants were pulled out of their flow state, resulting in decreased engagement and performance. This finding underscores the need for virtual environments to adapt not only to the cognitive load but also to maintain an optimal level of challenge that keeps users engaged. In addition to the EEG-based assessments, the study also explored the potential of using Large Language Models (LLMs) in conjunction with EEG data to create more realistic and adaptive virtual human interactions. The comparison between virtual and real human interactions revealed that while cognitive load was initially similar, participants became less engaged with the virtual human as limitations in the LLM's conversational abilities became apparent. This insight points to the necessity of further refining LLMs and their integration with EEG data to enhance the realism and effectiveness of virtual training environments. In conclusion, this research demonstrates the viability of using EEG technology to enhance the adaptability of virtual environments, particularly in the context of training clinicians with virtual patients. By leveraging real-time cognitive and emotional assessments, these environments can provide more personalized and effective training experiences, ultimately leading to better-prepared healthcare professionals. Future research should focus on improving the integration of EEG data with LLMs and other AI technologies to further enhance the realism and interactivity of adaptive virtual environments.