مطالب

Background: Bangkok's urban landscape features approximately 6,000 high-rise towers housing millions of residents in what was historically considered a seismically stable region. However, the March 28, 2025 magnitude-7.7 Myanmar earthquake triggered widespread psychological distress among Bangkok's vertical communities despite causing minimal structural damage. While existing disaster psychology research demonstrates that individual appraisal processes and coping resources influence distress outcomes, high-density vertical urban environments remain largely unexplored in disaster literature, particularly within Asian megacities where socioeconomic inequities may compound vulnerabilities. Aims: This study aimed to quantify earthquake-related emotional distress changes, evaluate the effectiveness of different coping strategies, examine socioeconomic and disability-related moderators, and test Transactional Model of Stress and Coping pathways among Bangkok's high-rise population. Methods: A cross-sectional web-based survey was conducted two weeks post-earthquake using multistage stratified probability sampling. From 120 randomly selected buildings across Bangkok's districts, 5,200 households received survey invitations, yielding 2,104 completed responses (40.5% response rate). Participants were adults residing at least six months in buildings exceeding eight floors. Validated Thai-adapted instruments included the Kessler-6 for psychological distress, Insomnia Severity Index, and custom scales measuring emergency preparedness, social support-seeking, and self-care behaviors. Statistical analyses employed paired t-tests, ANOVA, MANOVA, and bootstrap mediation procedures with effect size reporting. Results: Clinically significant insomnia prevalence increased from 27.4% to 61.8% post-earthquake. Emergency preparedness behaviors were associated with lower anxiety levels, while social support-seeking correlated with reduced insomnia severity. Significant disparities emerged across housing tenure, income levels, and disability status, with renters demonstrating lower preparedness rates than homeowners (54.6% versus 71.9%). Mediation analyses revealed that preparedness and support-seeking behaviors collectively explained 37.7% of the association between perceived seismic threat and psychological distress outcomes. Conclusion: Perceived earthquake threat, rather than actual structural damage, emerged as the primary driver of psychological distress in Bangkok's high-rise communities. While emergency preparedness and social support provided substantial protective effects against anxiety and insomnia, these resources were inequitably distributed across socioeconomic groups. These findings highlight the critical need for inclusive disaster preparedness policies that address structural barriers affecting vulnerable populations in rapidly urbanizing megacities facing emerging seismic risks.

Introduction: Given the expansion of numerous applications of artificial intelligence in the daily activities of human societies and the ethical obstacles that may arise in this direction, the need for a detailed and comprehensive examination of these issues is felt more than ever. Therefore, this study was developed with the aim of examining the challenges of ethical use of artificial intelligence technology. Material and Methods: This study is applied in terms of purpose and descriptive-survey in terms of data collection. Library methods, searching through electronic sources, and field study were used to collect data. In the field method, a questionnaire was used. The research community is experts and specialists in the field of artificial intelligence, 15 of whom were selected through purposive sampling (snowball sampling). By reviewing the literature, 6 obstacles related to the ethical use of artificial intelligence were identified; the DEMATEL method and Excel and MATLAB software were used to analyze the data and evaluate the cause-and-effect relationships between the obstacles. Results: The results show that among the 6 identified barriers (lack of accountability, lack of transparency, lack of legal regulations, possibility of bias and discrimination, violation of data privacy, and violation of social justice and livelihood of individuals), the barrier of lack of transparency, followed by the lack of legal regulations, are considered to be the most important and influential barriers to the ethical use of AI. Also, the barriers of data privacy violation and violation of social justice and livelihood of individuals were identified as the most influential barriers among the aforementioned barriers. Conclusion: The findings of this study indicate the importance and causal relationships governing the existing barriers to the ethical use of AI and can help experts and managers in this field in designing AI systems and making decisions in order to comply with ethical principles.