Factors associated with recording the exercise vital sign (EVS) in the electronic health records of patients in chiropractic teaching clinics.
Bibliographic record
Abstract
Objective: We set out to identify factors associated with recording of exercise minutes per week in electronic patient files at chiropractic teaching clinics to better understand whether this important health determinant - exercise vital sign (EVS) - is captured or not. Methods: Patient files (4018) from 23 clinicians eligible for inclusion underwent multilevel logistic regression modeling to explore the association between a recorded EVS and the following: patients' age, sex, comorbidities and interns nested within clinicians. Results: EVS discussion was documented in 81.2% of patient files, whereas 44.9% had exercise minutes recorded numerically. Clinicians and interns explained 1.7% and 25.5% of the variance in the EVS outcome. Conclusion: To enhance EVS recording, clinic directors and clinicians should better educate the interns on the importance of exercise is medicine and appropriate record keeping, as they explained the largest portion of variability in recording exercise in minutes per week.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".