Implementing Exercise Medicine Tools In Primary Pediatric Care - A Call To Action
Bibliographic record
Abstract
PURPOSE: Despite the demonstrated health benefits of physical activity for children and adolescents, surprisingly few primary care pediatricians discuss, evaluate or prescribe physical activity (PA) for children and their families. The aim of this study was to examine pediatricians’ views on child PA in order to inform the development of tools and resources to be implemented in the pediatric primary care clinics. METHODS: 27 pediatricians participated. The Consolidated Framework for Implementation Research was used in a mixed-method design combining qualitative and quantitative data. Qualitative data were collected through focus groups, addressed pediatricians’ current approaches to PA for their patients as well as factors facilitating practice change. Quantitative data were collected (online questionnaire) to explore perceptions implicated in the implementation of PA tools, approaches, or guidelines. RESULTS: Analyses of the qualitative data highlighted that pediatricians and patients and their families strongly believe that PA is important and beneficial. However, there is wide practice variability in current approaches to initiating PA discussions and promotion and identified barriers that included: lack of knowledge and training; managing time and multiple demands; the need for team approach in implementation and adherence; and the need for simple tools and resources. Quantitative data highlighted additional factors including evidence-based, cost-effective tools; tailoring the message to patient needs and resources; access to knowledge and information; and champions to engage, advocate and help implement PA best practices. CONCLUSION: Together, the qualitative and quantitative results begin to facilitate a strategic plan to improve the implementation of PA best practices in pediatric practices. While it is encouraging that both pediatricians and families strongly believe that PA is important for good health across the lifespan, the following key elements are needed: 1) rigorous training in exercise science at the medical school and residency level; 2) effective tools to assess and discuss PA as well as implement and follow up adherence to PA prescription; 3) further, these tools must be inexpensive, minimally burdensome and conform to the time constraints faced by busy pediatricians.
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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 | 0.058 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.009 | 0.013 |
| 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".