Preliminary efficacy of a novel online parenting skills program for caregivers of preterm children with behavioral challenges
Bibliographic record
Abstract
OBJECTIVE: Report results of a single-arm pilot trial examining the efficacy of I-InTERACT Preterm (I2P), an accessible, eHealth parenting skills intervention adapted for the special needs of parents of children born very preterm (VPT). METHODS: We recruited caregivers of children ages 3-8 who were born at <32 weeks gestational age and exhibited behavioral challenges (e.g. noncompliance, emotion dysregulation). Measures of parent-child interaction (Dyadic Parent-Child Interaction Coding System) and child behavior problems (Child Behavior Checklist; Eyberg Child Behavior Inventory) were assessed pre- and post-intervention. I2P includes seven online modules providing parent-skills training and psychoeducation paired with live coaching with a therapist. Exploratory brain MRI scans collected volumetric and graph theoretical data. RESULTS: Fourteen children and 11 parents completed the intervention. Findings indicated significant increases in positive parenting behavior and significant decreases in negative parenting behavior. Improvements in child outcomes were more evident in children who displayed at least modestly elevated behavior problems at baseline. Neuroimaging showed a slight decrease in white matter hyperintensity volume, although this was not significant. CONCLUSIONS: Preliminary findings suggest potential efficacy in strengthening parenting behaviors and reducing child behavior problems for families of VPT children. I2P can be adaptable to different populations with neuropsychological needs, pointing to the necessity for larger-scale trials. Further research is needed on the neural underpinnings of behavioral change in this population.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".