Measurement properties of cervical joint position error in people with and without neck pain: a systematic review and narrative synthesis
Bibliographic record
Abstract
INTRODUCTION: Proprioception can be impaired in people with neck pain. The cervical joint position sense test, which measures joint position error (JPE), is the most common test used to assess neck proprioception. The aim of this systematic review was to assess the measurement properties of this test for the assessment of people with and without neck pain. METHODS: This systematic review was registered prospectively on Prospero (CRD42020188715). It was designed using the COSMIN guidelines and reported in line with the PRISMA checklist. Two reviewers independently searched Medline, Embase, SportDiscus, and CINAHL Plus databases from inception to the 24th July 2022 with an update of the search conducted until 14th of October 2023. The COSMIN risk of bias checklist was used to assess the risk of bias in each study. The updated criteria for good measurement properties were used to rate individual studies and then the overall pooled results. The level of evidence was rated by two reviewers independently using a modified GRADE approach. RESULTS: Fifteen studies were included in this review, 13 reporting absolute JPE and 2 reporting constant JPE. The measurement properties assessed were reliability, measurement error, and validity. The measurement of JPE showed sufficient reliability and validity, however, the level of evidence was low/very low for both measurement properties, apart from convergent validity of the constant JPE, which was high. CONCLUSION: The measure of cervical JPE showed sufficient reliability and validity but with low/very low levels of evidence. Further studies are required to investigate the reliability and validity of this test as well as the responsiveness of the measure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".