Reliability and measurement error of exercise-induced hypoalgesia in pain-free adults and adults with musculoskeletal pain: A systematic review
Bibliographic record
Abstract
OBJECTIVES: We systematically reviewed the reliability and measurement error of exercise-induced hypoalgesia (EIH) in pain-free adults and in adults with musculoskeletal (MSK) pain. METHODS: We searched EMBASE, PUBMED, SCOPUS, CINAHL, and PSYCINFO from inception to November 2021 (updated in February 2024). In addition, manual searches of the grey literature were conducted in March 2022, September 2023, and February 2024. The inclusion criteria were as follows: adults - pain-free and with MSK pain - a single bout of exercise (any type) combined with experimental pre-post pain tests, and assessment of the reliability and/or measurement error of EIH. Two independent reviewers selected the studies, assessed their Risk of Bias (RoB) with the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) RoB tool, and graded the individual results (COSMIN modified Grading of Recommendations Assessment, Development, and Evaluation). RESULTS: = 168), which were deemed to have an overall "doubtful" RoB. No study including adults with MSK pain was found. The following ranges of parameters of reliability and measurement error of EIH were reported: intraclass correlation coefficients: 0-0.61; kappa: 0.01-0.46; standard error of measurement: 30.1-105 kPa and 10.4-21%; smallest detectable changes: 83.54-291.1 kPa and 28.83-58.21%. CONCLUSIONS: We concluded, with a very low level of certainty, that the reliability and measurement error of EIH is, in pain-free adults, respectively, "insufficient" and "indeterminate." Future studies should focus on people with MSK pain and could consider using tailored exercises, other test modalities than pressure pain threshold, rater/assessor blinding, and strict control of the sources of variations (e.g., participants' expectations).
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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 | 0.042 | 0.205 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".