The Building Regulation in Dual-Generations Program (BRIDGE): A Mixed-Methods Feasibility Pilot of a Parenting Program for Depressed Mothers of Preschoolers, Matched with Dialectical Behavior Therapy Skills
Bibliographic record
Abstract
Early exposure to maternal depression is a key risk factor for child mental illness (MI), but there are limited programs that interrupt intergenerational transmission. The BRIDGE "Building Regulation in Dual Generations" Program treats maternal MI using Dialectical Behavior Therapy Skills with a paired curriculum that promotes non-reactive and emotionally validating parenting designed to improve child mental health and ultimately prevent MI. The pilot feasibility trial (n = 28 dyads) included mothers and their preschool-aged children. The 20-week program was completed in a group-based format using mixed methods questionnaires and interviews. Results indicate high feasibility and acceptability (86% retention). Consistent improvements were seen across program targets and outcomes including maternal depression (d = 1.02) and child mental health (d = 1.08), with clinically significant symptom reductions for 85% of clients. Mothers with higher adversity exhibited greater reductions in parenting stress. Qualitative results highlighted efficacy in promoting positive parent-child relationships, rewarding parenting experiences, competence, and child development. Evidence suggests high feasibility and accessibility for BRIDGE in addressing intergenerational mental health needs. There was strong satisfaction with the program material and efficacy across key outcomes. BRIDGE holds promise for offering a transdiagnostic approach to preventing child MI in families of at-risk preschool aged children.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".