Attachment & Child Health (ATTACH) pilot trials: Effect of parental reflective function intervention for families affected by toxic stress
Bibliographic record
Abstract
Toxic stressors (e.g., parental violence, depression, low income) place children at risk for insecure attachment. Parental reflective function-parents' capacity to understand their own and their child's mental states and thus regulate their own feelings and behavior toward their child-may buffer the negative effects of toxic stress on attachment. Our objective was to test the effectiveness of the Attachment and Child Health (ATTACH) intervention, focusing on improving reflective function and children's attachment security, for at-risk mothers and children <36 months of age. Three pilot studies were conducted with women and children from an inner city agency serving vulnerable, low-income families and a family violence shelter. Randomized control trial (n = 20, n = 10 at enrollment) and quasi-experimental (n = 10 at enrollment) methods tested the effect of the ATTACH intervention on the primary outcome of reflective function scores, from transcribed Parent Development Interviews. Our secondary outcome was children's attachment patterns from Ainsworth's Strange Situation Procedure. Despite some attrition, mixed methods analysis of covariance and t tests revealed significant differences in maternal, child, and overall reflective function, with moderate effect sizes. While more children whose mothers received the ATTACH program were securely attached posttreatment, as compared with controls, significant differences were not observed, which may be due to missing observations (n = 5 cases). Understanding the effectiveness of programs like the ATTACH intervention contributes to improved programs and services to promote healthy development of children affected by toxic stress.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".