The Role of Self-Concept in a Community-Based Study of the Effectiveness of Trauma-Focused Cognitive Behavioural Therapy with Trauma-Exposed Children
Bibliographic record
Abstract
Trauma-Focused Cognitive Behavioural Therapy (TF-CBT) is a widely used treatment model for trauma (Cohen, Mannarino, & Deblinger, 2006). The Healthy Coping Program was a multi-site community-based study which evaluated the effectiveness of TF-CBT with trauma-exposed school-aged children in a diverse Canadian city (Muller & DiPaolo, 2008). Using data from the Healthy Coping Program, the role of children’s self-concept, and its relationship to posttraumatic stress (PTS) symptoms were examined. Self-report data were collected from a total of 111 trauma-exposed children referred for a trauma-focused intervention (assessment and TF-CBT). Children’s self-concept was measured using the short form version of the Tennessee Self-Concept Scale – Second Edition (Fitts & Warren, 1996). Children’s PTS was measured using the Trauma Symptom Checklist for Children (Briere, 1996). Trauma-exposed children’s self-concept was found to have a decreasingly significant negative relationship with PTS symptoms over the course of assessment and TF-CBT. Self-concept was significantly more dysfunctional amongst trauma-exposed children compared to a normative sample of children. Significant improvements in trauma-exposed children’s self-concept were observed after receiving trauma-focused intervention. Trauma-exposed children’s self-concept moved from a clinically dysfunctional range to the clinically functional range over the course of the assessment and continued to improve during TF-CBT. Further, these improvements were maintained at a six-month follow-up. These findings support the effectiveness of TF-CBT in improving trauma-exposed children’s self-concept and underscore the importance of considering how children view themselves after trauma. Clinical implications are discussed.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".