Evaluation Of Exercise is Medicine From The Perspective Of Fitness Professionals
Bibliographic record
Abstract
PURPOSE: Exercise is Medicine (EIM) promotes physicians prescribing exercise and referring patients to fitness professionals (FP). Early focus in research has been on improving the knowledge of physicians on how to prescribe exercise and encouraging physicians to refer patients to FPs, however the receiving end of the referral procedure has not been examined. This mixed method pilot study aimed to identify level of awareness for FPs regarding EIM initiatives and whether a brief educational session enhanced that level of awareness. The second aim was to engage FPs in dialogue to indicate barriers to and enablers of the exercise prescription and referral procedure. METHODS: Twelve certified personal trainers employed at a university campus recreation facility with an active EIM on campus group, were recruited to participate in an EIM information session and focus group. Personal trainers completed a pre-information session questionnaire on EIM goals, mission, and contents of the exercise prescription pad. A 15 minute EIM information session was provided and then the same questionnaire was completed again. Immediately after the information session personal trainers participated in a focus group to indicate if problems exist and discuss solutions regarding the EIM goal of engaging FPs and physicians to implement exercise prescription and referrals in the health care system. RESULTS: Average score on the pre-information questionnaire (7 questions) was 30% which significantly improved to 82% (p<0.05) after the information session. Thematic analysis of the focus group identified four suggestions: increase communication opportunities between physicians and FPs, increase promotion of EIM to both physicians and FPs, add progression and follow-up details to the EIM prescription pad and increase educational opportunities about EIM for all staff employed at a recreational facility. CONCLUSION: EIM should consider increasing opportunities to educate FPs about the EIM initiative so they are better prepared to receive patients referred to exercise and can engage with physicians to promote EIM. Furthermore, by incorporating the suggestions of FPs to enhance the exercise prescription and referral procedure, the effectiveness of EIM for increasing physical activity levels in all populations can improve.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".