Mining latent information in PTSD psychometrics with fuzziness for effective diagnoses

The Contributing Factors of Delayed-Onset Post-traumatic Stress Disorder Symptoms: A Nested Case-Control Study Conducted After the 2008 Wenchuan Earthquake

Background: Delayed-onset post-traumatic stress disorder after catastrophes is a major public health issue. However, good designs for identifying post-traumatic stress disorder (PTSD) among earthquake survivors are rare. This is the first nested case-control study to explore the possible factors associated with delayed-onset PTSD symptoms. Methods: A nested case-control study was conducted. The baseline (2011) and follow-up (2018) surveys were utilized to collect data. A total of 361 survivors of the Wenchuan earthquake were investigated and 340 survivors underwent follow-up. The survivors, from the hardest-hit areas, who met the criteria for PTSD were included in the case group, and PTSD-free survivors from the same area, matched for age, were included in the control group, with a ratio of one to four. Conditional logistic regression was used to evaluate the variables' odds ratio (OR). Results: The overall prevalence of delayed-onset PTSD symptoms in survivors of the Wenchuan earthquake was 9.7% (33/340). The unemployed earthquake survivors had a higher risk of developing delayed-onset PTSD symptoms (OR = 4.731, 95% CI = 1.408-15.901), while higher perceived social support was a protective factor against delayed-onset PTSD symptoms (OR = 0.172, 95% CI = 0.052-0.568). Conclusion: Delayed-onset PTSD symptoms, after a disaster, should not be ignored. Active social support and the provision of stable jobs can contribute to the earthquake survivors' mental health.

The symptoms and factors associated with post-traumatic stress disorder for burns nurses: a cross-sectional study from Guangdong province in China

BACKGROUND

The symptoms of post-traumatic stress disorder (PTSD) among medical staff has become a significant issue. Environments related to burns are highly stressful for nurses and can lead to PTSD, thus affecting their mental health. It is vital to consider that the quality of burns care, and the outcomes of such treatments, may be threatened if nurses experience PTSD. We evaluated PTSD symptoms in burns nurses and explored the correlations between demographic characteristics, work-related characteristics, professional identity, turnover intention, and PTSD symptoms.

METHODS

This was a cross-sectional study involving 273 nurses working in burns unit from Guangdong, China, between July and August 2019. Nurses were recruited from 30 hospitals and completed three validated psychological questionnaires: Post-traumatic Stress Disorder Checklist-Civilian Version (PCL-C), Professional Identity Scale for Nurses (PIS), and Turnover Intention Questionnaire (TIQ). We also collated information relating to socio-demographic and work-related characteristics.

RESULTS

The cut-off point for the PCL-C was defined as 38 points; 17.22% (n=47) of participants scored higher than or equal to 38. The PCL-C score was negatively correlated with professional identity level (P < 0.01) and positively correlated with turnover intention (P < 0.01). The workplace, mean monthly income, experience of workplace violence, and professional identity level, were important factors and all associated with the severity of PTSD.

CONCLUSION

PTSD symptoms were common in burns nurses. Attention should be paid to the mental wellbeing of these staff. Screening processes need to be initiated to identify individuals suffering from PTSD and take appropriate early interventional action.

Association between childhood parental rearing, sexual partnerships, social support and posttraumatic stress disorders (PTSD) among young HIV-positive MSM

We aimed to assess the effect of childhood parental rearing on post-traumatic stress disorder (PTSD) among young HIV-positive men who have sex with men (MSM), as well as the mediation effect of social support on this association. A convenient sampling method and questionnaire-based survey were used to recruit eligible participants from the Wuhan Medical Treatment Center from 20 December 2018 to 28 February 2019. Bivariate analyses were used to investigate the correlations between PTSD and childhood parental rearing, the number of sexual partners and social support. Mediation analyses were used to investigate the mediation of social support. Totally, 142 eligible MSM participated in our study, with prevalence of PTSD being 33.10%. It was found that maternal warmth (M1) and maternal favoring (M5) were positively correlated with social support. Paternal rejection (F5) was positively correlated with PTSD. The effects of M1 and M5 on PTSD were completely mediated by social support. The effects of paternal favoring (F4) and M5 on PTSD were completely mediated by subjective social support, and the effects of F5 and M1 were completely mediated by social support utility. Social support was an important mediator between parental rearing and PTSD.

The Effect of Signaling Latencies and Node Refractory States on the Dynamics of Networks

We describe the construction and theoretical analysis of a framework derived from canonical neurophysiological principles that model the competing dynamics of incident signals into nodes along directed edges in a network. The framework describes the dynamics between the offset in the latencies of propagating signals, which reflect the geometry of the edges and conduction velocities, and the internal refractory dynamics and processing times of the downstream node receiving the signals. This framework naturally extends to the construction of a perceptron model that takes into account such dynamic geometric considerations. We first describe the model in detail, culminating with the model of a geometric dynamic perceptron. We then derive upper and lower bounds for a notion of optimal efficient signaling between vertex pairs based on the structure of the framework. Efficient signaling in the context of the framework we develop here means that there needs to be a temporal match between the arrival time of the signals relative to how quickly nodes can internally process signals. These bounds reflect numerical constraints on the compensation of the timing of signaling events of upstream nodes attempting to activate downstream nodes they connect into that preserve this notion of efficiency. When a mismatch between signal arrival times and the internal states of activated nodes occurs, it can cause a breakdown in the signaling dynamics of the network. In contrast to essentially all of the current state of the art in machine learning, this work provides a theoretical foundation for machine learning and intelligence architectures based on the timing of node activations and their abilities to respond rather than necessary changes in synaptic weights. At the same time, the theoretical ideas we developed are guiding the discovery of experimentally testable new structure-function principles in the biological brain.