Comparison of Forces Exerted by a Chiropractor on Children and Adults During High-Speed, Low-Amplitude Spinal Manipulations: A Feasibility Study
Bibliographic record
Abstract
Objective The aim of this study was to demonstrate that quantification of the forces exerted by a single chiropractor on children and adults during high-velocity, low-amplitude spinal manipulations and the correlation of forces to age was feasible. Methods The force-time profiles of high-velocity, low-amplitude spinal manipulations were measured in 48 children (109 manipulations) ranging from 14 weeks to 17 years of age, and 20 adults (49 manipulations) in a clinical setting. The measurements were taken using a thin, flexible pressure pad. Outcome variables (peak forces, preload forces, thrust forces, thrust durations, rates of force application, and thrust impulses) were quantified and compared across age groups using Kruskal-Wallis testing with Dunn post hoc analysis. Outcome variables were fitted with best-fitting linear regressions with age as the dependent variable. The level of significance for all statistical tests was set a priori at α = 0.05. Results Most outcome variables increased with the age of the patient. Specifically, peak forces, thrust forces, and the rate of force application were positively correlated with age, while thrust durations remained constant across all ages and preload forces decreased slightly with patient age for cervical spine manipulations. Conclusion For this single chiropractor in private practice, the forces he used increased with the age of the patient, and he thus used lower forces in children than adults. This study shows that measuring the forces used by a chiropractor in clinical practice on patients with a range of ages was feasible.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".