Virtual Delivery of Parent Coaching Interventions in Early Childhood Mental Health: A Scoping Review
Bibliographic record
Abstract
Parent-coaching interventions positively impact child development. Virtual delivery of such interventions is supported by literature reviews and a practice guideline, however, none of these focused on children under age six. A scoping review of virtually-delivered parent-coaching interventions for disruptive behaviour, anxiety, and parent-child relationship concerns in children under age six was conducted between Dec. 15, 2020 and April 22, 2021. Iterative searches of the databases PubMed, CINAHL, and PsycINFO were complemented by reference list searches and clinician expert review (N = 1146). After relevance screening and duplicate removal, collaboratively-developed inclusion criteria were applied to records, followed by data extraction from eligible articles (n = 30). Most literature documented behavioural-based interventions targeting disruptive behaviour which were delivered individually, by therapists, to White, non-Hispanic parents. Evidence supports feasibility and efficacy of virtually-delivered parent-coaching interventions to improve child disruptive behaviour (strong), anxiety (moderate), and parent-child relationship (weak). There is a significant gap in the literature regarding the virtual delivery of attachment-based parent-coaching interventions. In sum, virtual parent coaching can be an efficacious approach for children under age six, particularly for behavioural challenges.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".