Patterns and Predictors of Different Youth Responses to Attachment-Based Parent Intervention
Bibliographic record
Abstract
Objective Few studies have evaluated attachment-based parent interventions for pre-teens and teens, and in particular, differential adolescent trajectories of response. This study examined distinct patterns, and multi-level predictors, of intervention response among youth with serious behavioral and mental health problems whose parents participated in Connect, an attachment- and trauma-informed parent program.Method Participants included 682 parents (Mage = 42.83, 86% mothers) and 487 youth (Mage = 13.95, 53% female, 28.1% ethnic minority) enrolled in a community-based evaluation of Connect. Parents and youth reported on youth externalizing and internalizing problems (EXT and INT) at six time points from baseline through 18-months post-intervention. Demographic and youth and family level predictors were assessed at baseline.Results Growth mixture modeling revealed three distinct trajectory classes in both the parent and youth models based on different patterns of co-occurring EXT and INT and degree of improvement over time. Youth with severe EXT showed the largest and fastest improvement, and, interestingly, were characterized by higher callous-unemotional traits and risk-taking at program entry. Youth with comorbid EXT/INT demonstrated a partial or moderate response to intervention in the parent and youth model, respectively, and were characterized by more attachment anxiety at baseline. Most youth showed relatively moderate/low levels of EXT/INT at baseline which gradually improved. Caregiver strain also predicted trajectory classes.Conclusions These results have significance for tailoring and personalizing interventions for high-risk youth and provide new understanding regarding the profiles of subgroups of youth who show different responses to an attachment-based parent intervention.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".