Posttraumatic stress symptom severity is associated with impaired processing of emotional faces in a large international sample.
Lauren A RutterColton LindJacqueline HowardPrabhvir LakhanLaura T GerminePublished in: Journal of traumatic stress (2022)
Trauma exposure and posttraumatic stress symptoms (PTSS) are associated with biases in emotional face processing. Existing research has utilized a variety of methodological techniques to demonstrate hyperreactivity to threatening cues in posttraumatic stress disorder (PTSD; i.e., fearful faces), but studies to date have shown conflicting findings, including both increased and decreased time fixating on fearful faces. Moreover, the impact of PTSS severity on emotional face processing in the general population is unknown, as the generalizability of prior work is limited. The current study aimed to examine the associations between PTSS and sensitivity to detecting differences in fearful, angry, and happy faces in a large international sample. Participants were 1,182 visitors (M age = 31.13 years, SD = 13.57, range: 18-85 years) to TestMyBrain.org who completed three emotion sensitivity tasks and the PTSD Checklist for DSM-5. The results indicated that higher PTSS scores were associated with poorer performance in detecting happiness, fear, and anger, ps < .001, with the largest effect for fear, f 2 = .06, controlling for age and gender. Participants who experienced more recent and more direct trauma exposure displayed higher levels of PTSS, with a small but significant effect whereby more direct trauma exposure was associated with higher (i.e., better) scores for anger and fear, f 2 s = .02. Women showed heightened sensitivity to detecting fear compared to men, d = 0.17. The present findings underscore the value of citizen science initiatives that allow researchers to obtain clinical data from diverse samples with a high degree of PTSS variability.
Keyphrases
- posttraumatic stress disorder
- prefrontal cortex
- trauma patients
- public health
- autism spectrum disorder
- depressive symptoms
- electronic health record
- mental health
- stress induced
- machine learning
- metabolic syndrome
- quality improvement
- working memory
- physical activity
- artificial intelligence
- case control
- middle aged
- data analysis
- deep learning