Prospective prediction of PTSD and depressive symptoms during social unrest and COVID-19 using a brief online tool

Abstract

Large-scale protracted population stressors, such as social unrest and the coronavirus disease 2019 (COVID-19), are associated with increased symptoms of post-traumatic stress disorder (PTSD) and depression. Cost-effective mental health screening is prerequisite for timely intervention. We developed an online tool to identify prospective predictors of PTSD and depressive symptoms in the context of co-occurring social unrest and COVID-19 in Hong Kong. 150 participants completed baseline and follow-up assessments, with a median duration of 29 days. Three logistic regression models were constructed to assess its discriminative power in predicting PTSD and depressive symptoms at one month. Receiver-operating characteristic analysis was performed for each model to determine their optimal decision thresholds. Sensitivity and specificity of the models were 87.1% and 53.8% for probable PTSD, 77.5% and 63.3% for high-risk depressive symptoms, and 44.7% and 96.4% for no significant depressive symptoms. The models performed well in discriminating outcomes (AUCs range: 0.769–0.811). Probable PTSD was predicted by social unrest-related traumatic events, high rumination, and low resilience. Rumination and resilience also predicted high-risk and no significant depressive symptoms, with COVID-19-related events also predicting no significant depression risk. Accessible screening of probable mental health outcomes with good predictive capability may be important for early intervention opportunities.