Recurrence of Work-Related Low Back Pain and Disability
Bibliographic record
Abstract
In Brief Study Design. Retrospective cohort. Objective. To explore the ability to capture low back pain (LBP) recurrence using wage-replacement (WR) data. Summary of Background Data. LBP can be a recurrent, fluctuating, and disabling condition. Because of its largely nonspecific and subjective nature, the condition poses challenges for research and clinical management, as speaking directly with the affected individuals is not always practical. Little information is available on how indicators of LBP recurrence that can be extracted from administrative databases relate to patients' self-report. Methods. Participants with a compensated claim for work-related LBP (N = 90) were interviewed regarding their LBP-related experiences after their initial return to work. Interview data were compared with WR data, which was provided by the participants' workers' compensation provider. Results. Concordance was observed between WR-based indicators and self-reports of additional time off due to LBP. The best performing WR-based indicator reflected a payment history that began with more than 7 consecutive days of initial WR payments, followed by a gap in WR payments of more than 7 consecutive days, followed by another WR payment period of more than 7 consecutive days (sensitivity = 55%, specificity = 73%, overall accuracy = 69%). Although concordance was observed between the 2 measures of additional time off, the best performing WR indicator was not related to participants' other self-reports of post–return-to-work LBP recurrence which included LBP being significantly worse usual; LBP experiences; seeking health care for LBP; and the experience of difficulties related to the back condition. Conclusion. Results indicate that compensation data can be used to capture what a claimant would self-report as additional time off after their initial return to work due to their LBP condition. However, the use of self-report recurrence indicators is recommended if there is a desire to capture a fuller extent of workers' ongoing pain and/or disability experiences. Level of Evidence: N/A Workers' compensation claimants (N = 90) were interviewed about their post-return-to-work low back pain (LBP) experiences. Interview data were linked with wage-replacement (WR) data and compared for concordance. Although WR-based indicators were found to relate to self-reports of additional time off, no signifi cant relationship was observed when the best performing WR-based indicator was compared with other self-report indicators of LBP recurrence.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".