Reliability of a neck strength test in schoolboy rugby players
Bibliographic record
Abstract
BACKGROUND: In rugby union, a bracing mechanism of the neck and trunk is normally adopted in contact situations where high linear and angular forces are produced, which may contribute to the risk for sports-related concussion (SRC). OBJECTIVES: To examine the feasibility of and test-retest reliability, both inter-rater and intra-rater reliability, of a novel neck strength test in schoolboy rugby players and to summarize neck strength values for this cohort, including rugby position-specific estimates. MATERIALS AND METHODS: 52 male schoolboy rugby union players completed the neck strength test protocol twice, eight days apart using a novel device. RESULTS: Intra-class correlation coefficients (ICCs) were good to excellent for test-retest reliability (range from 0.86 to 0.92) in all four directions. Intra-rater (ICCs range from 0.706 to 0.981) and inter-rater (ICCs range from 0.669 to 0.982) ranges were calculated. Significant differences were identified between forwards and backs for non-normalised force measures but no significant difference when normalised to bodyweight. The flexor:extensor ratio was 0.68 (SD 0.2) for forwards, 0.71 (SD 0.16) for backs and 0.67 (SD 0.16) for the cohort. DISCUSSION & CONCLUSION: While there is limited direct evidence to support a direct link between neck strength and SRC risk at present, investigating the relationship of neck strength, stiffness and impact anticipation might be a useful direction for further research. In conclusion, we describe a portable, user-friendly and safe neck strength test with good-to-excellent test-retest reliability, and intra-, inter-rater reliability. Test-retest ICC values compare favourably to gold standard fixed-frame dynamometry and are superior to hand-held dynamometry.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".