Increasing Parental Access to Pediatric Pain-related Knowledge
Bibliographic record
Abstract
OBJECTIVES: Parents can play an integral role in managing their child's pain, yet many parents remain unaware of evidence-based strategies to support their child during painful experiences. Recent advances in knowledge translation research, which include dissemination and implementation studies, have resulted in programs geared towards parents to offset this knowledge gap. The nature of these programs and the degree to which parents find them useful remains unclear. Our goal was to systematically review programs aimed as disseminating and implementing evidence-based pain-related knowledge to parents. MATERIALS AND METHODS: Systematic searches of PubMed, Web of Science, CINAHL, and PsycInfo were completed. Articles in which information was disseminated to parents with the goal of assessing dissemination and implementation outcomes were retained. Information was extracted to identify study characteristics, primary outcomes, and quality of evidence. RESULTS: A total of 24,291 abstracts were screened and 12 articles describing programs were retained. Programs were positively rated by parents in terms of the appropriateness of formats selected, presentation of information, and helpfulness of content. The majority of research has been focused in the area of procedural pain among infants. Although several implementation domains are reported by researchers, certain areas have been overlooked to date, including the cost and sustainability of programs. The majority of reports presented with methodological limitations and bias. DISCUSSION: Knowledge translation research in pediatric pain is in its infancy. Development of theories and guidelines to increase the utility and quality of evidence are needed.
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".