A Descriptive Study of Pressure Pain Threshold at 2 Standardized Sites in People With Acute or Subacute Neck Pain
Bibliographic record
Abstract
STUDY DESIGN: Cross-sectional convenience sample. OBJECTIVES: To describe the distribution of scores for pressure pain threshold (PPT) at 2 standardized testing sites in people with neck pain of less than 90 days' duration: the angle of the upper trapezius and the belly of the tibialis anterior. A secondary objective was to identify important influences on PPT. BACKGROUND: PPT may be a valuable assessment and prognostic indicator for people with neck pain. However, to facilitate interpretation of scores, knowledge of means and variance for the target population, as well as factors that might influence scores, is needed. METHODS: Participants were recruited from community-based physiotherapy clinics and underwent PPT testing using a digital algometer and standardized protocol. Descriptive statistics (mean, standard deviations, quartiles, skewness, and kurtosis) were calculated for the 2 sites. Simple bivariate tests of association were conducted to explore potential moderators. RESULTS: A positively skewed distribution was described for the 2 standardized sites. Significant moderators were sex (male higher than female), age (r = 0.22), and self-reported pain intensity (r = -0.24). Neither litigation status nor most symptomatic/least symptomatic side influenced PPT. CONCLUSIONS: This manuscript presents information regarding the expected scores for PPT testing in people with acute or subacute neck pain. Clinicians can compare the results of individual patients against these population values, and researchers can incorporate the significant confounders of age, sex, and self-reported pain intensity into future research designs.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".