Predicting Posttraumatic Stress Disorder Among Survivors of Recent Interpersonal Violence

A substantial minority of women who experience interpersonal violence will develop posttraumatic stress disorder (PTSD). One critical challenge for preventing PTSD is predicting whose acute posttraumatic stress symptoms will worsen to a clinically significant degree. This 6-month longitudinal study...

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Bibliographic Details
Published in:Journal of interpersonal violence Vol. 37; no. 13-14; pp. NP11460 - NP11489
Main Authors: Morris, Matthew C., Sanchez-Sáez, Francisco, Bailey, Brooklynn, Hellman, Natalie, Williams, Amber, Schumacher, Julie A., Rao, Uma
Format: Journal Article
Language:English
Published: Los Angeles, CA SAGE Publications 01.07.2022
SAGE PUBLICATIONS, INC
Subjects:
Adolescent
Adult
Anxiety
Anxiety disorders
Blame
Childhood
Clinical significance
Disorders
Domestic violence
Female
Generalized anxiety disorder
Humans
Longitudinal Studies
Machine learning
Occupational stress
Post traumatic stress disorder
Posttraumatic Stress Disorder
Predictions
Prevention programs
Selfblame
Severity
Sex crimes
Sex Offenses
Stress Disorders, Post-Traumatic - psychology
Survivor
Survivors - psychology
Symptoms
Trauma
Violence
Violence - psychology
Women
Young Adult
Young women
PTSD
prediction
assault
interpersonal violence
longitudinal
women
ISSN:0886-2605, 1552-6518, 1552-6518
Online Access:Get full text
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Summary:A substantial minority of women who experience interpersonal violence will develop posttraumatic stress disorder (PTSD). One critical challenge for preventing PTSD is predicting whose acute posttraumatic stress symptoms will worsen to a clinically significant degree. This 6-month longitudinal study adopted multilevel modeling and exploratory machine learning (ML) methods to predict PTSD onset in 58 young women, ages 18 to 30, who experienced an incident of physical and/or sexual assault in the three months prior to baseline assessment. Women completed baseline assessments of theory-driven cognitive and neurobiological predictors and interview-based measures of PTSD diagnostic status and symptom severity at 1-, 3-, and 6-month follow-ups. Higher levels of self-blame, generalized anxiety disorder severity, childhood trauma exposure, and impairment across multiple domains were associated with a pattern of high and stable posttraumatic stress symptom severity over time. Predictive performance for PTSD onset was similarly strong for a gradient boosting machine learning model including all predictors and a logistic regression model including only baseline posttraumatic stress symptom severity. The present findings provide directions for future work on PTSD prediction among interpersonal violence survivors that could enhance early risk detection and potentially inform targeted prevention programs.
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ISSN:0886-2605
1552-6518
1552-6518
DOI:10.1177/0886260520978195