Prevalence of probable posttraumatic stress disorder and determination of its relationship with everyday functioning in children and adolescents by using generalized estimating equations

Post-traumatic Stress and Depressive Symptoms Among Adolescents After the 2015 Earthquake in Nepal: A Longitudinal Study

Few longitudinal studies have focused on mental health problems among adolescents after earthquakes. We investigated changes in post-traumatic stress symptoms (PTSS) and depressive symptoms from 18 to 31 months after the 2015 earthquake in Nepal and explored potential risk factors associated with the change in psychiatric symptoms. This study comprised of 515 adolescents, aged 11-17 years from two earthquake-affected areas, one severely affected than the other. The psychiatric symptoms were assessed using the standardized Child Post-traumatic Stress Disorder Scale and the Depression Self-Rating Scale. No significant change was observed in the prevalence of PTSS and depressive symptoms from 18 to 31 months after the earthquake. Living in severely affected area and exposure to trauma after the earthquake were associated with adolescents who developed chronic or delayed PTSS and depressive symptoms. The study findings highlight the need for disaster preparedness and early interventions that strengthen support at various levels.

Patterns of Depression and Resilience in Children and Adolescents Exposed to an Earthquake: A Latent Profile Analysis

OBJECTIVE

Depression and resilience are different psychological outcomes caused by experiencing traumatic events. We aimed to 1) explore heterogeneity patterns of co-occurrence between depression symptoms and resilience among children and adolescents exposed to an earthquake and 2) assess covariates (trauma exposure, sex, age, ethnicity, and sleep quality) in identifying the best fitting solution.

METHODS

Latent profile analysis (LPA) was used to examine patterns of self-reported depression and resilience in an epidemiological sample of 2,887 Chinese youth survivors 1 year after the Lushan earthquake.

RESULTS

A suitable 3-class model were identified, which are mild depression/high resilience (65.0%), severe depression/high resilience (22.1%), and severe depression/low resilience (12.9%). Trauma exposure, demographic characteristics and sleep state can be used to identify the different latent classes.

CONCLUSION

Our results contribute to understanding the heterogeneous coexisting patterns of depression and resilience and provide suggestions for identifying high-risk youth survivors and offering effective interventions.

Identifying predictors of probable posttraumatic stress disorder in children and adolescents with earthquake exposure: A longitudinal study using a machine learning approach

BACKGROUND

Evidence has identified risk factors associated with individuals with trauma exposure who develop posttraumatic stress disorder (PTSD). How to combine risk factors to predict probable PTSD in young survivors using machine learning is limited. The study aimed to integrated multiple measures at 2 weeks after the earthquake using machine learning for the prediction of probable PTSD at 3 months after earthquake.

METHODS

A total of 2099 young survivors with earthquake exposure were included. We integrated multiple domains of variables to 'train' a machine learning algorithm (XGBoost). Thirty-one combination types were implemented and evaluated. The resulting XGBoost was utilized in identifying individual participants as either probable PTSD or no PTSD.

RESULTS

Any combination type predicted young survivor probable PTSD, with prediction accuracies ranging between 66%-80% (p < 0.05). In particular, the combination of earthquake experience, everyday functioning, somatic symptoms and sleeping correctly predicted 683 out of 802 cases of probable PTSD, translating to a classical accuracy of 74.476% (85.156% sensitivity and 60.366% specificity) and an area under the curve of 0.80. The most relevant variables (e.g. age, sex, property loss and a sedentary lifestyle) revealed in the present study.

LIMITATIONS

Participants from a specific district might limit the generalizability of our results. Self-report questionnaires and non-standardized measures were used to assess symptoms.

CONCLUSION

Detection of probable PTSD according to self-reported measurement data is feasible, may improve operational efficiencies via enabling targeted intervention, before manifestation of symptoms.

Changes in the network structure of posttraumatic stress disorder symptoms at different time points among youth survivors: A network analysis

BACKGROUND

Despite considerable studies focused on the symptoms of posttraumatic stress disorder (PTSD), little is understood about how symptoms of PTSD change over time. The study aimed to use a network analysis approach to understand the nature of the association between PTSD symptoms at different time points among children and adolescents who experience an earthquake.

METHODS

A longitudinal study enrolled 1623 youth survivors who completed 3 assessments with the Children's Revised Impact of Event Scale at 2 weeks, 3 months and 6 months after the Lushan earthquake. The epicentre was Baoxing Country that located in the Ya'an city (Sichuan Province in China). A network analysis approach was used to investigate how symptom networks change at different time points.

RESULTS

A total of 1623 youth survivors (768 male and 855 female) completed three assessments. Different centrality symptoms existed at different time points. Flashback and upset by reminders were centrality symptoms at 2 weeks, 3 months and 6 months. The overall network connectivity was significantly stronger at 3 months than at 2 weeks (5.663 vs. 5.140, s = 0.523, p = 0.000), and significantly stronger at 6 months than at 2 weeks (6.094 vs. 5.663, s = 0.432, p = 0.020).

LIMITATIONS

Participants from a specific region might limit the generalizability of our results. A self-report questionnaire was used to assess PTSD symptoms.

CONCLUSIONS

Re-experience cluster (flashback and upset by reminders) and their interactions might play a key role in PTSD symptom evolution. Over time, the global connectivity becomes stronger, suggesting that youth survivors are more vulnerable in the chronic phases.