Physical activity should be the primary intervention for individuals living with chronic pain A position paper from the European Pain Federation (<scp>EFIC</scp>) ‘On the Move’ Task Force
Bibliographic record
Abstract
BACKGROUND: There is clear evidence demonstrating the benefits of physical activity (PA) on pain and overall health, however, PA is challenging for many individuals living with chronic pain. Even non-exercise specialists can (cost) effectively promote PA, but many health professionals report a number of barriers in providing guidance on PA, suggesting that it is not consistently promoted. This expert position paper summarizes the evidence and provides five recommendations for health professionals to assess, advise and support individuals living with any chronic pain condition with a long life expectancy in adopting and sustaining physically active lifestyles. METHODS: This position paper was prepared by the 'On The Move' Task Force of the European Pain Federation EFIC. Final recommendations were endorsed by the European Pain Forum, Pain Alliance Europe and the Executive Board of EFIC. RESULTS: We recommend that all health professionals (1) Take a history of the persons' PA levels, and put PA on the agenda, (2) Advise that PA is important and safe for individuals living with chronic pain, (3) Deliver a brief PA intervention and support individuals living with chronic pain in becoming physically active, (4) Discuss acceptable levels of PA-related soreness and pain and (5) Provide ongoing support in staying physically active. SIGNIFICANCE: Physical activity is safe and offers several advantages, including general health benefits, low risk of side effects, low cost and not requiring access to healthcare. Adoption of these recommendations can improve the quality of care and life of individuals living with chronic pain and reduce their overall health risks.
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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 | 0.037 | 0.075 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.042 | 0.027 |
| Insufficient payload (model declined to judge) | 0.020 | 0.015 |
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".