Comparison of pain‐resilient working individuals to population‐based case controls with/without momentary low back pain
Bibliographic record
Abstract
BACKGROUND: Few studies have examined the 20% of individuals who never experience an episode of low back pain (LBP). To date, no investigation has been undertaken that examines a group who claim to have never experienced LBP in their lifetime in comparison to two population-based case-control groups with and without momentary LBP. This study investigates whether LBP-resilient workers between 50 and 65 years had better general health, demonstrated more positive health behaviour and were better able to achieve routine activities compared with both case-control groups. METHODS: Forty-two LBP-resilient participants completed the same pain assessment questionnaire as a population-based LBP sample from a nationwide, large-scale cross-sectional survey in Switzerland. The LBP-resilient participants were pairwise compared to the propensity score-matched case controls by exploring differences in demographic and work characteristics, and by calculating odds ratios (ORs) and effect sizes. A discriminant analysis explored group differences, while the multiple logistic regression analysis specified single indicators which accounted for group differences. RESULTS: LBP-resilient participants were healthier than the case controls with momentary LBP and achieved routine activities more easily. Compared to controls without momentary LBP, LBP-resilient participants had a higher vitality, a lower workload, a healthier attitude towards health and behaved more healthily by drinking less alcohol. CONCLUSIONS: By demonstrating a difference between LBP-resilient participants and controls without momentary LBP, the question that arises is what additional knowledge can be attained. Three underlying traits seem to be relevant about LBP-resilient participants: personality, favourable work conditions and subjective attitudes/attributions towards health. These rationales have to be considered with respect to LBP prevention.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".