Low back pain in junior Australian Rules football: a cross-sectional survey of elite juniors, non-elite juniors and non-football playing controls
Post-publication record
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Bibliographic record
Abstract
BACKGROUND: Low back pain in junior Australian Rules footballers has not been investigated despite findings that back pain is more prevalent, severe and frequent in senior footballers than non-athletic controls and findings that adolescent back pain is a strong predictor for adult back pain. The aim of this study was to determine the prevalence, intensity, quality and frequency of low back pain in junior Australian Rules footballers and a control group and to compare this data between groups. METHODS: A cross-sectional survey of male non-elite junior (n = 60) and elite junior players (n = 102) was conducted along with a convenience sample of non-footballers (school children) (n = 100). Subjects completed a self-reported questionnaire on low back pain incorporating the Quadruple Visual Analogue Scale and McGill Pain Questionnaire (short form), along with additional questions adapted from an Australian epidemiological study. Linear Mixed Model (Residual Maximum Likelihood) methods were used to compare differences between groups. Log-linear models were used in the analysis of contingency tables. RESULTS: For current, average and best low back pain levels, elite junior players had higher pain levels (p < 0.001), with no difference noted between non-elite juniors and controls for average and best low back pain. For low back pain at worst, there were significant differences in the mean pain scores. The difference between elite juniors and non-elite juniors (p = 0.040) and between elite juniors and controls (p < 0.001) was significant, but not between non-elite juniors and controls. The chance of suffering low back pain increases from 45% for controls, through 55% for non-elite juniors to 66.7% for elite juniors. The chance that a pain sufferer experiences chronic pain is 16% for controls and 41% for non-elite junior and elite junior players. Elite junior players experienced low back pain more frequently (p = 0.002), with no difference in frequency noted between non-elite juniors and controls. Over 25% of elite junior and non-elite junior players reported that back pain impacted their performance some of the time or greater. CONCLUSIONS: This study demonstrated that when compared with non-elite junior players and non-footballers of a similar age, elite junior players experience back pain more severely and frequently and have higher prevalence and chronicity rates.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".