Interrelationships Between Pain, Disability, General Health, and Quality of Life and Associations With Work-Related and Individual Factors
Bibliographic record
Abstract
In Brief Study Design. A cross-sectional study. Objectives. To measure interrelationships among pain, functional disability, general health, and overall quality of life for workers on sickness absence for 2 to 6 weeks due to musculoskeletal complaints, and to assess the impact of work-related and individual characteristics on these different health dimensions. The results of this study will contribute to a better understanding of the relationship between health and functional disability. Summary of Background Data. When choosing a patient-based outcome measure, different health dimensions must be considered. For musculoskeletal complaints, four health dimensions are important: pain, disability, general health, and overall quality of life. Improvement at one dimension does not necessarily correlate with better health on another dimension. Moreover, correlations between different dimensions may be influenced by individual and environmental factors. However, it is not known whether these factors influence different health dimensions differently. Methods. A total of 218 workers on sickness absence for 2 to 6 weeks due to musculoskeletal complaints completed a questionnaire on four different health dimensions and work-related and environmental factors. Results. Moderate correlations (r < 0.50) among measures of pain, disability, general health, and quality of life were found. These health dimensions were not influenced by work-related physical and psychosocial workload, suggesting no impact of recall bias in studies for work-related musculoskeletal complaints. Self-perceived ability to return to work within 6 weeks explained 21% to 26% of the outcomes on pain and disability and contributed less to the generic measures of health. Conclusion. Within a population of workers on sickness absence for 2 to 6 weeks, specific dimensions of pain and disability seem to be more appropriate measures of health than generic instruments of general health and quality of life. Workers on sickness absence for 2 to 6 weeks due to musculoskeletal complaints completed a questionnaire about pain, disability, general health, and quality of life and about work-related and environmental factors. The health dimensions and were moderately interrelated were not influenced by work-related factors. Self-perceived ability to return to work explained a substantial part of the variance in pain and disability.
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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 | 0.003 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".