COMPARISON OF PREVIOUSLY ESTABLISHED RISK FACTORS IN PREDICTING PTSD SYMPTOM SEVERITY IN THE FIRST SIX MONTHS POST-TRAUMA

This study aims to improve our understanding of the predictive value of previously identified risk factors for the severity of Post-Traumatic Stress Disorder (PTSD) symptoms after a traumatic event. We recruited 178 participants from an Emergency Department and assessed four constructs previously associated with PTSD in the first few weeks after trauma and their relationship to PTSD symptom severity at six-month follow-up. Using structural equation modeling we examined four latent variables as predictors of PTSD symptom severity, cognitive attributions, trauma history, emotion response and regulation, and socioeconomic factors, along with two mediators, sleep quality and self-perceived pain. Our findings indicate that cognitive attributions soon after trauma and a history of trauma are closely linked to the severity of PTSD symptoms six months later. Sleep quality and self-perceived pain partially mediated the relationship between cognitive attributions and PTSD symptom severity, highlighting their significant roles in the progression of PTSD. The study also revealed that emotion responding and regulation, measured shortly after trauma, indirectly influenced PTSD symptom severity at six months through their impact on sleep quality, underscoring the critical role of emotional processes in the trajectory of PTSD development. In addition to providing valuable insights into the mechanisms driving PTSD symptomatology, this research also provides important insights into the development of targeted interventions aimed at mitigating the long-term psychological effects of trauma. Key words: Post-Traumatic Stress Disorder (PTSD), structural equation modeling, cognitive attributions, trauma history, emotion response and regulation, socioeconomic factors, sleep, pai

COMPARISON OF PREVIOUSLY ESTABLISHED RISK FACTORS IN PREDICTING PTSD SYMPTOM SEVERITY IN THE FIRST SIX MONTHS POST-TRAUMA

This study aims to improve our understanding of the predictive value of previously identified risk factors for the severity of Post-Traumatic Stress Disorder (PTSD) symptoms after a traumatic event. We recruited 178 participants from an Emergency Department and assessed four constructs previously associated with PTSD in the first few weeks after trauma and their relationship to PTSD symptom severity at six-month follow-up. Using structural equation modeling we examined four latent variables as predictors of PTSD symptom severity, cognitive attributions, trauma history, emotion response and regulation, and socioeconomic factors, along with two mediators, sleep quality and self-perceived pain. Our findings indicate that cognitive attributions soon after trauma and a history of trauma are closely linked to the severity of PTSD symptoms six months later. Sleep quality and self-perceived pain partially mediated the relationship between cognitive attributions and PTSD symptom severity, highlighting their significant roles in the progression of PTSD. The study also revealed that emotion responding and regulation, measured shortly after trauma, indirectly influenced PTSD symptom severity at six months through their impact on sleep quality, underscoring the critical role of emotional processes in the trajectory of PTSD development. In addition to providing valuable insights into the mechanisms driving PTSD symptomatology, this research also provides important insights into the development of targeted interventions aimed at mitigating the long-term psychological effects of trauma. Key words: Post-Traumatic Stress Disorder (PTSD), structural equation modeling, cognitive attributions, trauma history, emotion response and regulation, socioeconomic factors, sleep, pai

Exploring emotions and perspectives of families with autism spectrum disorder individuals on sports participation: a case study on Weibo using machine learning method

Abstract Background Physical activity is known to have numerous benefits for individuals with autism spectrum disorder (ASD). Understanding family sentiments towards ASD sports participation is crucial for developing interventions that promote physical activity. This study aimed to explore the sentiments of families regarding sports participation for individuals with ASD using longitudinal data from Weibo, a popular Chinese social media platform. Objective This study investigates family sentiments and attitudes toward sports participation by ASD individuals, leveraging longitudinal data from Sina Weibo and machine learning–based sentiment analysis. Methods We collected Weibo posts containing the keyword “autism” from January 2020 to April 2023, filtered for sports‑related content, and divided the dataset into ten four‑month intervals. Using SnowNLP’s Naive Bayes–based sentiment classifier, we labeled each post as positive or negative and analyzed temporal trends. Results Positive sentiments toward sports participation far outnumbered negative sentiments, and the proportion of supportive posts increased steadily over the study period, reflecting growing recognition of sports’ role in enhancing well‑being and development among ASD individuals. Conclusion Families of ASD individuals increasingly acknowledge the multifaceted benefits of physical activity. These insights can guide the design of targeted interventions and inclusive sports programs, ultimately fostering greater participation and improving quality of life within the ASD community