Defining a screening tool for post-traumatic stress disorder in East Africa: a penalized regression approach

• DOI: 10.3389/fpubh.2024.1383171
• Publication Date: 2024-06-14T08:17:18Z
• Authors: Susan M. Meffert; Muthoni A. Mathai; Linnet Ongeri; Thomas C. Neylan; Daniel Mwai; Dickens Onyango; Dickens Akena; Grace Rota; Ammon Otieno; Raymond R. Obura; Josline Wangia; Elizabeth Opiyo; Peter Muchembre; Dennis Oluoch; Raphael Wambura; Anne Mbwayo; James G. Kahn; Craig R. Cohen; David E. Bukusi; Gregory A. Aarons; Rachel L. Burger; Chengshi Jin; Charles E. McCulloch; Simon Njuguna Kah...
• Keywords: Male; Adult; low and middle income countries; Adolescent; low and middle income countries (LMIC); East Africa (Kenya); Stress Disorders, Post-Traumatic; primary care; Young Adult; 03 medical and health sciences; 0302 clinical medicine; Clinical Research; Health Services and Systems; Surveys and Questionnaires; Health Sciences; Health services and systems; Humans; Mass Screening; Stress Disorders; Public health; Prevention; Health Services; Middle Aged; Post-Traumatic Stress Disorder (PTSD); posttraumatic stress disorder (PTSD); screening tools; Anxiety Disorders; Mental Illness; East Africa; Kenya; Brain Disorders; traumatic stress; Mental Health; Good Health and Well Being; posttraumatic stress disorder; Post-Traumatic; Public Health and Health Services; sub Saharan Africa; Regression Analysis; Female; Public Health; Public aspects of medicine; RA1-1270

BackgroundScalable PTSD screening strategies must be brief, accurate and capable of administration by a non-specialized workforce.MethodsWe used PTSD as determined by the structured clinical interview as our gold standard and considered predictors sets of (a) Posttraumatic Stress Checklist-5 (PCL-5), (b) Primary Care PTSD Screen for the DSM-5 (PC-PTSD) and, (c) PCL-5 and PC-PTSD questions to identify the optimal items for PTSD screening for public sector settings in Kenya. A logistic regression model using LASSO was fit by minimizing the average squared error in the validation data. Area under the receiver operating characteristic curve (AUROC) measured discrimination performance.ResultsPenalized regression analysis suggested a screening tool that sums the Likert scale values of two PCL-5 questions—intrusive thoughts of the stressful experience (#1) and insomnia (#21). This had an AUROC of 0.85 (using hold-out test data) for predicting PTSD as evaluated by the MINI, which outperformed the PC-PTSD. The AUROC was similar in subgroups defined by age, sex, and number of categories of trauma experienced (all AUROCs>0.83) except those with no trauma history- AUROC was 0.78.ConclusionIn some East African settings, a 2-item PTSD screening tool may outperform longer screeners and is easily scaled by a non-specialist workforce.