Understanding the Impact of Upper Extremity Musculoskeletal and Comorbid Health Conditions on Physical and Mental Health and Quality of Life in 956 Adults Aged 50 to 65
Bibliographic record
Abstract
The objective of the study was to examine the relationship and impact of comorbidity, pain, and function on quality of life in people aged 50-65 with upper extremity musculoskeletal disorders (UED), controlling for sex, occupational status, and age. This was a cross-sectional study. We performed hierarchical linear regression models to assess the extent that comorbidity and injury-related pain and disability affected overall health-related quality of life measured by the SF-36. We included 956 patients, of whom 601 were female. Physical and mental disability were associated significantly with lower levels of UE functional capacity (effect physical health = 0.24, SE = 0.10, P < 0.001; effect mental health = 0.17, SE = 0.09, P < 0.05). Comorbidity, pain, and occupational status have indirect relationships with UED, such that greater pain, a larger burden of comorbid health conditions, and less participation in the workforce, is associated with poorer physical and mental health. Mobility is key in promoting health and quality of life while contributing towards a successful transition into retirement.
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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 | 0.003 |
| 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) | 0.001 | 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".