Exploration of Barriers and Facilitators to Implementing Best Practice in Exercise Medicine in Primary Pediatric Care—Pediatrician Perspectives
Bibliographic record
Abstract
PURPOSE: Despite the known health benefits of physical activity (PA), few primary care pediatricians discuss, evaluate, or prescribe PA for children. The goal of this study was to examine pediatricians' thoughts and practices related to child PA and the perceived facilitators and barriers to implementing PA evaluation and prescription in pediatric primary care clinics. METHODS: The Consolidated Framework for Implementation Research was used to explore implementation barriers and facilitators. A mixed-method design combined questionnaires and focus groups with 27 pediatricians. RESULTS: Despite the pediatricians' beliefs that PA is important for patients, there was wide practice variability in their approaches to discussing PA. Several perceived barriers to implementing PA evaluation and prescription were identified, including lack of knowledge and training, managing time for PA with multiple demands, the need for a team approach and simple PA tools and resources, support for patient tailoring of PA messaging, and a need for PA best practice champions. CONCLUSION: The identified barriers to implementing evidence in PA suggest several directions for improvement, including a care-team approach; quick, inexpensive, and simple PA tools; community PA partnerships; PA training in medical education; evidence-based strategies; and PA directories for families. These efforts could facilitate the implementation of PA best practices in pediatrics.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".