Current Posttraumatic Stress Symptoms Mediate the Relationship Between Adverse Childhood Experiences and Executive Functions
Bibliographic record
Abstract
Adverse childhood experiences (ACEs) and posttraumatic stress disorder (PTSD) are both associated with lower performances on executive function tasks. However, few researchers have evaluated ACEs, posttraumatic stress (PTS) symptoms, and executive function difficulties in conjunction. Using an online micropayment service, the current study assessed whether PTS symptoms mediated the relationship between ACEs and executive functions. In total, 83 participants (54.2% female, age: M = 28.86, SD = 7.71) were administered the ACE questionnaire, PTSD Checklist for DSM-5 (PCL-5), and the Executive Function Index (EFI). A higher number of reported ACEs was related to greater PTS symptom severity ( β = .40, p < .001) and worse self-rated executive functions ( β = –.32, p = .002). Controlling for the number of reported ACEs, current PTS symptom severity was related to worse executive functions ( β = –.45, p < .001). A bootstrapped 95% confidence interval (CI) indicated a significant indirect effect, β = –.18 (95% CI: –.30, –.08), by which current PTS symptoms mediated the relationship between the number of reported ACEs and executive functions. These results suggest that psychological interventions targeting PTS symptoms, in the context of a history of childhood trauma, may concurrently improve executive functions in adult populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".