A brief screening tool for assessing psychological trauma in clinical practice: development and validation of the New York PTSD Risk Score

• Published in: General hospital psychiatry 2011-09, Vol.33 (5), p.489-500
• Main Authors: Boscarino, Joseph A., Ph.D., M.P.H, Kirchner, H. Lester, Ph.D, Hoffman, Stuart N., D.O, Sartorius, Jennifer, M.S, Adams, Richard E., Ph.D, Figley, Charles R., Ph.D
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Area under receiver operating characteristic (ROC) curve; Biological and medical sciences; Chronic Disease; Depressive Disorder; Diagnostic testing; Female; Health Services Accessibility; Humans; Male; Medical sciences; Middle Aged; New York City - epidemiology; Pain - psychology; Patient screening; Pennsylvania; Posttraumatic stress disorder; Psychiatric Status Rating Scales - standards; Psychiatry; Psychological Trauma; Psychology. Psychoanalysis. Psychiatry; Psychometrics. Diagnostic aid systems; Psychopathology. Psychiatry; Risk Assessment - methods; ROC Curve; Sensitivity and Specificity; September 11 Terrorist Attacks; Sleep Wake Disorders - psychology; Stress Disorders, Post-Traumatic - diagnosis; Stress Disorders, Post-Traumatic - epidemiology; Stress Disorders, Post-Traumatic - psychology; Techniques and methods; Trauma Centers; Young Adult
• ISSN: 0163-8343; 1873-7714
• DOI: 10.1016/j.genhosppsych.2011.06.001

Abstract Objective The objective was to develop a brief posttraumatic stress disorder (PTSD) screening instrument that is useful in clinical practice, similar to the Framingham Risk Score used in cardiovascular medicine. Methods We used data collected in New York City after the World Trade Center disaster (WTCD) and other trauma data to develop a new PTSD prediction tool — the New York PTSD Risk Score. We used diagnostic test methods to examine different clinical domains, including PTSD symptoms, trauma exposures, sleep disturbances, suicidal thoughts, depression symptoms, demographic factors and other measures to assess different PTSD prediction models. Results Using receiver operating curve (ROC) and bootstrap methods, five prediction domains, including core PTSD symptoms, sleep disturbance, access to care status, depression symptoms and trauma history, and five demographic variables, including gender, age, education, race and ethnicity, were identified. For the best prediction model, the area under the ROC curve (AUC) was 0.880 for the Primary Care PTSD Screen alone (specificity=82.2%, sensitivity=93.7%). Adding care status, sleep disturbance, depression and trauma exposure increased the AUC to 0.943 (specificity=85.7%, sensitivity=93.1%), a significant ROC improvement ( P