Exercise as a vital sign: a preliminary pilot study in a chiropractic setting.
Bibliographic record
Abstract
BACKGROUND: The association between physical inactivity and non-communicable disease risk has been well documented in recent literature. An exercise vital sign (EVS) is a measure that can routinely capture vital information about a patient's physical activity behaviour. The objective of this study is to understand if (1) patient exercise minutes per week (EMPW) are being recorded by chiropractic interns, and (2) whether these patients are exceeding, meeting or falling short of the current recommendations provided by the Canadian Physical Activity Guidelines (CPAG). METHODS: Electronic medical records obtained from two Canadian Memorial Chiropractic College (CMCC) teaching clinics for patients seen between August 01, 2015 and January 31, 2017 (N=273). EMPW, age, and gender were used to compare patient files relative to the CPAG. RESULTS: Overall, 86.4% of patient files had recorded data to the question of how many EMPW they perform. The majority (68.8%) of individuals appear to be meeting or exceeding the CPAG, leaving nearly one third (31.2%) of individuals failing to meet these guidelines. CONCLUSIONS: In this pilot study with two sports specialist clinicians an exercise vital sign had been integrated alongside traditional vital signs in order to identify issues of physical inactivity and improve opportunities for continued exercise counselling.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".