Promoting physical activity: the general practice agenda
Bibliographic record
Abstract
There is a continued national public health strategic focus on increasing physical activity at a population level 1 and primary care is being called on to play a central role in this drive, 2 with the Royal College of General Practitioners (RCGP) set to appoint the first clinical champion for physical activity.Nationally Public Health England (PHE) 3 and globally the World Health Organization 4 have highlighted the importance of increasing physical activity and reducing sedentary time.Guidelines and recommendations from the Department of Health 5 and the National Institute for Health and Care Excellence 6 also emphasise the importance of physical activity promotion in primary care.GPs' workloads are already ballooning; but with the right knowledge, skills, and support, prioritising physical activity could potentially have a positive impact on our patients health. 7 BENEFITS OF PHYSICAL ACTIVITYPhysical activity is as important as healthy lifestyle choices such as diet, smoking cessation, and sensible alcohol intake.It is estimated that physical inactivity is directly responsible for up to 10% of noncommunicable diseases and another 9% of premature mortalities. 8Daily physical activity totalling 150 minutes of moderate intensity or 75 minutes of vigorous intensity per week 9 can help prevent many noncommunicable diseases: a 20-35% reduction in cardiovascular disease and premature mortality risk with a reduction in the risk of other diseases including type 2 diabetes (35-50%) and breast and colon cancer (20-50%) is hard to ignore. 10Physical activity is also beneficial for most long-term conditions and comparable with pharmacological therapy in outcomes for many conditions such as mortality in stroke, heart failure, and patients with prediabetes 11 with the additional preventative effects on other diseases.There is also evidence for improved morbidity and mortality outcomes in cancer patients. 12Despite this evidence, approximately 40% of UK adults are insufficiently active to enjoy significant health benefits. 13
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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 | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.043 | 0.046 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".