Potentially traumatic events in foster youth, and association with DSM-5 trauma- and stressor related symptoms
Bibliographic record
Abstract
BACKGROUND: In DSM 5, three disorders are related to trauma and/or maltreatment: Post-traumatic Stress Disorder (PTSD), Reactive Attachment Disorder (RAD) and Disinhibited Social Engagement Disorder (DSED) but how these disorders relate to each other and to traumatic events is unknown. OBJECTIVE: We examined 1. Prevalence of Potentially Traumatic Events (PTEs) and poly-victimization for youths in foster care. 2. Associations between single/multiple PTEs and PTSD, DSED, and the two symptom-clusters that constitute RAD: Failure to seek/accept comfort (RAD A), and Low social-emotional responsiveness/ emotion dysregulation (RAD B). PARTICIPANTS, SETTING AND METHODS: Foster youth 11-17 years (N = 303) in Norway completed The Child and Adolescent Trauma Screen. Foster parents completed the RAD and DSED Assessment interview. RESULTS: Foster youth reported experiencing, on average, 3.44 PTEs each (range 0-15, SD 3.33), and 52.9 % reported PTSD symptoms at or above clinical cut off. The PTE sum score was associated with the latent factors PTSD (r = .66, p < 0.001), RAD cluster B symptoms (Low social-emotional responsiveness / emotion dysregulation, r = .28, p < 0.001) and DSED (r = .11, p = 0.046), but not with RAD cluster A symptoms (Failure to seek/accept comfort). CONCLUSIONS: These findings raise new questions about the nature, mechanisms and timing of development of RAD and DSED. Maltreatment assessment needs to encompass a wide range of PTEs, and consider poly-victimization.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".