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The Tsunami of the Sunda Strait in December 2018 resulted in many losses, fatalities, and infrastructure. The psychological impact that often occurs during a catastrophic event is Post Traumatic Stress Disorder (PTSD) and if a teenager experiences it will have an impact on life in the future. The purpose of this study was to analyse the social determinants associated with PTSD in post-Tsunami Banten. This research is a quantitative study with a cross-sectional study design with a sample size of 125. The sampling technique uses Proportional to Size (PPS) and Simple Random Sampling. Data analysis using Fisher's Exact test. Factors related to the risk of Post Traumatic Stress Disorder (PTSD) are family support (p-value 0,0420,05) and peer support (p-value 0,0210,05) significantly related to the risk of Post Traumatic Stress Disorder in adolescents in SMPN 2 Labuan. However, volunteer support and support of religious leaders do not have a significant relationship with the risk of Post Traumatic Stress Disorder (PTSD). Support of family and friends are risk factors PTSD in adolescents at SMPN 2 Labuan after the Sunda Strait tsunami disaster in December 2018. There needs to be socialization related to post-disaster mental health management to parents and peers.

Background: The likelihood of developing Posttraumatic Stress Disorder (PTSD) depends on the interaction of individual risk factors and cumulative traumatic experiences. Hence, the identification of individual susceptibility factors warrants precise quantification of trauma exposure. Previous research indicated that some traumatic events may have more severe influences on mental health than others; thus, the assessment of traumatic load may be improved by weighting event list items rather than calculating the simple sum score. Objective: We compared two statistical methods, Random Forests using Conditional Interference (RF-CI) and Least Absolute Shrinkage and Selection Operator (LASSO), based on their ability to rank traumatic experiences according to their importance for predicting lifetime PTSD. Methods: Statistical models were initially fitted in a sample of N1 = 441 survivors of the Northern Ugandan rebel war. The ability to correctly predict lifetime PTSD was then tested in an independent sample of N2 = 211, and subsequently compared with predictions by the simple sum score of different traumatic event types experienced. Results: Results indicate that RF-CI and LASSO allow for a ranking of traumatic events according to their predictive importance for lifetime PTSD. Moreover, RF-CI showed slightly better prediction accuracy than the simple sum score, followed by LASSO when comparing prediction results in the validation sample. Conclusion: Given the expense in time and calculation effort by RF-CI and LASSO, and the relatively low increase in prediction accuracy by RF-CI, we recommend using the simple sum score to measure the environmental factor traumatic load, e.g., in analyses of gene × environment interactions.

Background: The likelihood of developing Posttraumatic Stress Disorder (PTSD) depends on the interaction of individual risk factors and cumulative traumatic experiences. Hence, the identification of individual susceptibility factors warrants precise quantification of trauma exposure. Previous research indicated that some traumatic events may have more severe influences on mental health than others; thus, the assessment of traumatic load may be improved by weighting event list items rather than calculating the simple sum score. Objective: We compared two statistical methods, Random Forests using Conditional Interference (RF-CI) and Least Absolute Shrinkage and Selection Operator (LASSO), based on their ability to rank traumatic experiences according to their importance for predicting lifetime PTSD. Methods: Statistical models were initially fitted in a sample ofN1 = 441 survivors of the Northern Ugandan rebel war. The ability to correctly predict lifetime PTSD was then tested in an independent sample ofN2 = 211, and subsequently compared with predictions by the simple sum score of different traumatic event types experienced. Results: Results indicate that RF-CI and LASSO allow for a ranking of traumatic events according to their predictive importance for lifetime PTSD. Moreover, RF-CI showed slightly better prediction accuracy than the simple sum score, followed by LASSO when comparing prediction results in the validation sample. Conclusion: Given the expense in time and calculation effort by RF-CI and LASSO, and the relatively low increase in prediction accuracy by RF-CI, we recommend using the simple sum score to measure the environmental factor traumatic load, e.g., in analyses of gene × environment interactions. [ABSTRACT FROM AUTHOR]