Dissemination of evidence based interventions for pediatric sleep disorders – The Niagara project: process and outcomes
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: This paper describes evidence-based strategies for the dissemination of empirically supported interventions for infant behavioral sleep problems. METHODS: To identify parents' needs, a survey sampled 1022 parents in the Niagara region about use of health resources, tracking occurred of public health nurses' consultations with parents about infant sleep, and nurses obtained sleep workshop evaluation data from 18 parents. A focus group with 10 participants, a survey of Niagara Region Public Health and Emergency Services (NRPH&ES) employees, and consultations with external stakeholders identified gaps in parents' and infants' care and public health nurses' training needs. We developed solutions by creating evidence-based tools and a program for parents and public health nurses. We implemented and disseminated information via sharing tools on the NRPH&ES website, and workshops for community agencies and public health nurses. RESULTS: Seventy childhood educators, support workers, and social and public health professionals attended our community workshop. Twenty-three public health nurses attended our training workshop. In guided discussion, nurses evaluated the workshop as addressing gaps in knowledge and enhancing NRPH&ES interventions to manage infants' behavioral sleep problems. Fifteen parents attended a sleep workshop pilot, with seven parents indicating a preference for follow-up telephone support. Fifty individuals attended our oral presentation at the Ontario Public Health Convention. CONCLUSIONS: For next directions, community and other public health agencies want access to our tools and program components. We received a research grant to design, implement, and evaluate sharing tools and program components with community agencies (daycares and childcare centres).
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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 | 0.101 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".