Criterion Validity Study of the Cervical Range of Motion (CROM) Device for Rotational Range of Motion on Healthy Adults
Bibliographic record
Abstract
STUDY DESIGN: This study compared range of motion (ROM) measurements using a cervical range of motion device (CROM) and an optoelectronic system (OPTOTRAK). OBJECTIVES: To examine the criterion validity of the CROM for the measurement of cervical ROM on healthy adults. BACKGROUND: Whereas measurements of cervical ROM are recognized as part of the assessment of patients with neck pain, few devices are available in clinical settings. Two papers published previously showed excellent criterion validity for measurements of cervical flexion/extension and lateral flexion using the CROM. METHODS AND MEASURES: Subjects performed neck rotation, flexion/extension, and lateral flexion while sitting on a wooden chair. The ROM values were measured by the CROM as well as the OPTOTRAK. RESULTS: The cervical rotational ROM values using the CROM demonstrated a good to excellent linear relationship with those using the OPTOTRAK: right rotation, r = 0.89 (95% confidence interval, 0.81-0.94), and left rotation, r = 0.94 (95% confidence interval, 0.90-0.97). Similar results were also obtained for flexion/extension and lateral flexion ROM values. CONCLUSION: The CROM showed excellent criterion validity for measurements of cervical rotation. We propose using ROM values measured by the CROM as outcome measures for patients with neck pain.
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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 | 0.019 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".