Psychometric testing of the British‐English Long‐Term Conditions Job Strain Scale, Long‐Term Conditions Work Spillover Scale and Work‐Health‐Personal Life Perceptions Scale in four rheumatic and musculoskeletal conditions
Bibliographic record
Abstract
Abstract Objective The aims were to validate linguistically British‐English versions of the Long‐Term Conditions Job Strain Scale (LTCJSS), Long‐Term Conditions Work Spillover Scale (LTCWSS) and Work‐Health‐Personal Life Perceptions Scale (WHPLPS) in rheumatoid arthritis, axial spondyloarthritis, osteoarthritis and fibromyalgia (FM). Methods The three scales were forward translated and reviewed by an expert panel prior to cognitive debriefing interviews. Participants completed a postal questionnaire. Construct validity was assessed using Rasch analysis. Concurrent validity included testing between the three scales and work (e.g., Workplace Activity Limitations Scale [WALS]) and condition‐specific health scales. Two weeks later, participants were mailed a second questionnaire to measure test‐retest reliability. Results The questionnaire was completed by 831 employed participants: 68% women, 53.5 (SD 8.9) years of age, with condition duration 7.7 (SD 8.0) years. The LTCJSS, LTCWSS and WHPLPS Parts 1 and 2 satisfied Rasch model requirements, but Part 3 did not. A Rasch transformation scale and Reference Metric equating scales with the WALS were created. Concurrent validity was generally good (rs = 0.41–0.85) for the three scales, except the WHPLPS Part 3. Internal consistency (Person Separation Index values) was consistent with group use in all conditions, and individual use except for the LTCWSS and WHPLSP Parts 1 and 2 in FM. Test‐retest reliability was excellent, with intraclass coefficients (2,1) of 0.80–0.96 for the three scales in the four conditions. Discussion Reliable, valid versions of the British‐English LTCJSS, LTCWSS and WHPLPS Parts 1 and 2 are now available for use in the UK.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".