The CASA Trauma and Attachment Group (TAG) Program for Children who have Attachment Issues Following Early Developmental Trauma.
Bibliographic record
Abstract
OBJECTIVE: There is relatively little research about effective therapeutic approaches for children in middle childhood who have attachment related diagnoses as a result of experiencing significant, early developmental trauma. This study describes findings from an intensive, dyad-based intervention, aimed at stabilizing attachment relationships with primary caregivers, increasing caregiver reflective function skills, and reducing children's trauma-related behavioural sequelae. METHOD: We analyzed retrospective data from 51 caregiver/child dyads who participated in the Trauma and Attachment Group (TAG) Program from September 2011-December 2014. This data included pre- and post-intervention scores retrieved from the Parenting Relationship Questionnaire (PRQ), the Parent Report of Post-Traumatic Stress Symptoms (PROPS), and the Parental Reflective Functioning Questionnaire (PRFQ-1). RESULTS: The preliminary findings show statistically significant improvements in attachment, communication, discipline practices, involvement, and relational frustration. Additionally there were statistically significant improvements in parental reflective functioning, and a trend towards a reduction in symptoms typical of post-traumatic stress disorder. CONCLUSION: Poor quality or inconsistent interactions with early caregivers can lead to life-long impairments in physical and mental health. This intensive program shows potential as a way to improve longer-term outcomes for children exposed to early developmental trauma. Longer-term research is required to further substantiate outcomes, appraise cost analysis, as well as to consider evaluation with appropriate comparison groups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".