Personal and psychosocial variables in workers with a previous history of LBP: 16-month follow-up
Bibliographic record
Abstract
A 16-month longitudinal study was made of workers who perform physically demanding jobs. In a previous study some of these workers were found to have a history of low back disorders sufficient to miss work, and others not. All were asymptomatic at that time. To further quantify the association between various personal and psychosocial parameters that linger due to a history of low back disorders and how they may change after another 16 months of work. Originally, 72 workers were recruited from heavy industry; 26 of whom had a history of disabling low back disorders sufficient to miss work. In the follow-up study, 46 responded all of whom remained at work injury free, 13 belonged to the 'history of back disorders' category. While the earlier study suggested that having a history of low back disorders is associated with a larger waist girth, a greater chronicity potential as predicted from psychosocial questionnaires, perturbed flexion to extension strength and endurance ratios, and widespread motor control deficits across a variety of tasks some of which resulted in high back loads, the follow-up showed no difference in reported physical symptoms, or perceived pain over the 16 months. Both groups changed their responses from the original data collection to the 16-month follow-up with the net result of psychosocial distinguishing traits, in those with a history, diminishing. It was concluded that time and work appear to be healing.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".