Learning Spinal Manipulation: Objective and Subjective Assessment of Performance
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to investigate associations between objective spinal manipulation therapy (SMT) biomechanical parameters and subjective assessments provided by patients, clinicians, and expert assessors. METHODS: Chiropractic students (N = 137) and expert instructors (N = 14) were recruited. Students were asked to perform a thoracic SMT alternately on each other on a force-sensing table while being observed by an expert instructor. Students who performed (clinicians) and received (patients) SMT, and expert instructors, independently scored each SMT performance using visual analog scales. Correlations between these subjective scores and SMT biomechanical parameters were calculated. The following parameters were evaluated: peak force, preload force, thrust duration, and drop in preload force. Spinal manipulation therapy comfort was also assessed by patients, clinicians, and expert instructors. RESULTS: Results of the study indicate that thrust duration assessed by instructors and patients was the only parameters significantly correlated with the table data (r = .37; P < .001 and r = .26; P = .002). Comfort assessed by clinicians was significantly correlated with their own assessments of thrust duration (r = .37; P < .001) and preload force (r = .23; P = .007), whereas comfort assessed by instructors was significantly correlated with their own assessment of thrust duration (r = .27; P = .002) and drop in preload force (r = -.34; P < .001). Objective biomechanical parameters of performance did not predict perceived comfort. CONCLUSIONS: Overall, the results from the subjective assessments of SMT performance are weakly correlated with objective measures of SMT performance. Only the thrust duration evaluated by expert instructors and patients was associated with scores obtained from the table. Perceived comfort of the procedure seems to be associated mostly with perceived thrust duration and preload characteristics.
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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 | 0.011 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".