Within-session test-retest reliability of pressure pain threshold and mechanical temporal summation in healthy subjects
Bibliographic record
Abstract
OBJECTIVE: To determine the absolute and relative intra-rater within-session test-retest reliability of pressure pain threshold (PPT) and mechanical temporal summation of pain (TSP) at the low back and the forearm in healthy participants and to test the influence of the number and sequence of measurements on reliability metrics. METHODS: In 24 participants, three PPT and TSP measures were assessed at four sites (2 at the low back, 2 at the forearm) in two blocks of measurements separated by 20 minutes. The standard error of measurement, the minimal detectable change (MDC) and the intraclass correlation coefficient (ICC) were investigated for five different sequences of measurements (e.g. measurement 1, 1-2, 1-2-3). RESULTS: The MDC for the group (MDCgr) for PPT ranged from 28.71 to 50.56 kPa across the sites tested, whereas MDCgr for TSP varied from 0.33 to 0.57 out of 10 (numeric scale). Almost all ICC showed an excellent relative reliability (between 0.80 and 0.97), except when only the first measurement was considered (moderate). Although minimal differences in absolute PPT reliability were present between the different sequences, in general, using only the first measurement increase measurement error. Three TSP measures reduced the measurement error. DISCUSSION: We established that two measurements of PPT and three of TSP reduced the measurement error and demonstrated an excellent relative reliability. Our results could be used in future pain research to confirm the presence of true hypo/hyperalgesia for paradigms such as conditioned pain modulation or exercise-induced hypoalgesia, indicated by a change exceeding the measurement variability.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".