Early positive approaches to support for family carers of young children with developmental disabilities: adaptation and piloting in Quebec public services
Bibliographic record
Abstract
Background: This paper presents the participative research undertaken to adapt and pilot the Early Positive Approaches to Support (E-PAtS) program, originally developed and evaluated in English for use in the United-Kingdom, for implementation within Québec's public health and social services. E-PAtS supports family carers of young children with developmental disabilities by promoting their well-being and adjustment early in their services trajectory. Method: The program was translated into French and iteratively adapted based on feedback from six pilot cohorts conducted across four diverse clinical settings: a rural service center, an urban center, a specialized pediatric hospital, and a diagnostic clinic. These sites were selected to ensure demographic and geographic representativity of Québec's population, and participating families also reflected a range of backgrounds. The adaptation process was grounded in community-based participatory research principles, actively involving parents, practitioners, managers, and researchers. Changes to the program's content and delivery were made according to partner recommendations. Evaluation focused on social validity, effectiveness, feasibility, and fidelity of implementation. Results: Participating parents completed questionnaires and interviews, reporting improved well-being and greater confidence in self-care, indicating the program's relevance and positive impact. Fidelity of implementation was assessed using the E-PAtS fidelity checklist, and feasibility was evaluated through session attendance logs. Both indicators were considered strong, despite the challenges posed by the COVID-19 pandemic. Conclusion: Findings support the adapted E-PAtS program's suitability for Québec's public services, with further refinements recommended for broader dissemination. This study highlights the value of participatory approaches in adapting evidence-based interventions across cultural and service delivery contexts.
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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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".