Cyberpsychology, behavior and social networking最新文献

Despite the emergence of the dark web more than 20 years ago, little scholarly attention has focused on identifying potential mental health differences between dark web users and surface web users. Yet, given the pseudo-anonymous nature of the dark web and the purported privacy it provides, individuals with mental health vulnerabilities may be inclined to use the dark web. In the present study, we investigate this matter by drawing on survey data collected in 2024 from a national sample of 2,000 U.S. adults. The results of both bivariate and multivariate analyses indicate that dark web users exhibit greater depressive symptoms and have more paranoid thoughts than surface web users. Likewise, dark web users are more likely than surface web users to report suicidal thoughts, nonsuicidal self-injury, and engagement in digital self-harm. Discussion centers on the implications of these findings for practice as well as avenues for future research.

Virtual reality (VR) and biofeedback have emerged as promising tools for mindfulness training. However, their combined effectiveness, compared with Traditional Mindfulness formats, remains understudied. This study investigated the short-term effects of a brief mindfulness intervention delivered via VR, with and without biofeedback, on psychological and physiological outcomes. Seventy-two participants (64.7 percent women; aged 18-57 years, M = 24.0) were randomly assigned to one of three groups (n = 24 per group): mindfulness with VR and biofeedback, mindfulness with VR only, and traditional audio-guided mindfulness. Self-report measures assessed negative emotional symptoms, state anxiety, affect, and present-moment awareness before and after the intervention. Heart rate was recorded as a psychophysiological index of arousal. Results indicated significant reductions in stress, anxiety, and heart rate and an increase in positive affect across all groups. The VR + biofeedback group showed significantly greater improvements in receptive awareness and attentional focus compared with the other conditions. These findings support the use of VR-based mindfulness and suggest that integrating biofeedback may enhance present-moment engagement.

First responders (FRs) are routinely exposed to traumatic events, increasing risk for posttraumatic stress disorder (PTSD). This study compared heart rate variability (HRV) and skin conductance level (SCL) between FRs with and without probable PTSD at baseline and during a virtual reality (VR) task. Eighty-four FRs completed questionnaires and physiological assessments. Participants with probable PTSD showed significantly lower baseline HRV, indicating reduced parasympathetic modulation. No group differences emerged for HRV during VR or for SCL at either point. The results confirm reduced HRV at rest in PTSD, but further work is needed to clarify why this difference was not observed during the task and why SCL showed no group effects. To advance understanding of these results, future studies should include larger samples, longer baselines, recovery phases, and clinical interviews.

While individuals exhibit heightened attentional bias toward social media information, it remains debated whether this reflects a content-specific priority or a broader cognitive adaptation. Using visual search tasks, self-report scales, and the Embedded Figures Test, this study investigated attentional capture by digital icons and the role of cognitive style. Results showed that icons, particularly for field-independent individuals, elicited greater capture, suggesting a generalized digital attentional bias, and cognitive style play a key role in the process.

This study was performed to clarify the relationship between smartphone usage and depression risk among older adults. We also examined smartphone use variations, population heterogeneity, and the mechanisms behind smartphone-related depression symptoms. A total of 10,997 older adults (mean age = 84.31 years) from a national cohort (Chinese Longitudinal Healthy Longevity and Happy Family Study) in China were included. Smartphone use was measured by use status (yes/no) and contents. Among eight dichotomous questions about contents of smartphones, chatting, shopping, traveling, and entertainment were classified as routine-oriented activities. In contrast, health management, financial management, and learning were classified as functional/cognitive-oriented activities. Thus, participants were categorized into four groups, including not using a smartphone, using smartphones both for routine-oriented and functional/cognitive-oriented activities, only for routine-oriented activities, and others. Smartphone users had lower 10-item Center for Epidemiological Studies Depression Scale scores (β = -0.62; p < 0.001) and a reduced depression risk (odds ratio = 0.77; p < 0.001) compared with nonusers. Furthermore, those using smartphones for routine-oriented and functional/cognitive-oriented activities had even lower risks than those using them only for routine-oriented activities. Second, using smartphones was more sensitive to alleviating depression among older adults aged <80 years or living in rural areas. Third, mediation analyses suggested that using smartphones may be associated with depressive symptoms through communicating with children regularly. Our findings suggest that smartphone use may have a positive effect on mental health, particularly among those who engage in diverse routine-oriented and functional/cognitive-oriented activities. Smartphone benefits are more evident in younger seniors and rural residents, indicating a need for targeted interventions for these groups.

While the effects of interpersonal social comparison have been widely explored, the potential consequences of human-machine comparison remain understudied. The present survey research investigates how individuals compare themselves to generative artificial intelligence (GAI), by extending the concept of social comparison orientation to human-GAI interactions. Using a large Chinese sample (N = 1302), we examine the relationships between two subtypes of human-GAI comparison orientation (ability-based and opinion-based), self-esteem, perceived identity threat, anthropocentric beliefs, and personal relative deprivation within the framework of the Rejection-Identification Model. The findings reveal that both ability-based and opinion-based comparisons with GAI positively relate to self-esteem, diverging from relevant findings on interpersonal comparisons. In addition, ability-based comparisons with GAI significantly heighten the perceived identity threat, whereas opinion-based comparisons with GAI may alleviate it. Furthermore, anthropocentric beliefs (i.e., human-first attitudes) suppress the negative effect of identity threat on self-esteem, which is also mediated by personal relative deprivation. In addition, a post hoc exploratory multigroup analysis was conducted based on usage frequency. The present study highlights the importance of investigating human-AI comparison and expands the explanatory power of classical concepts and frameworks from the self and identity domains, contributing to psychological interventions aimed at mitigating the potential adverse effects driven by human-machine relationships.