Prevalence and distribution of musculoskeletal disorders in firefighters are influenced by age and length of service
Bibliographic record
Abstract
Introduction: The objective of this cross-sectional study is to describe the prevalence and severity of self-reported musculoskeletal disorders (MSDs) in firefighters and how these vary by demographics and length of service (LOS). Methods: A cohort of 294 active-duty firefighters completed a body diagram to indicate the location and pain intensity of their MSK complaints. Where painful sites were indicated, they completed the relevant region-specific self-report disability measure – Neck Disability Index (NDI), Roland Morris Disability Questionnaire (RMDQ), Lower Extremity Functional Scale (LEFS), or the Short Form of Disabilities of the Arm, Shoulder and Hand (QuickDASH) – to quantify severity. Prevalence was determined from the body diagrams and severity from the site-specific self-report questionnaires. Differences in MSK severity based on demographics or LOS were determined using ANOVA. Results: The 294 active-duty firefighters had a mean age of 42.6 (SD 9.7) years and mean duration of service of 15.1 (SD 10.1) years. The prevalence of neck, back, upper-limb, and lower-limb complaints was 20%, 33%, 44%, and 45% respectively. Firefighters 42 years or older reported significantly more severe lower-extremity disability (median (IQR) LEFS: 71 (65, 77) vs. 75 (69.5, 78.5), p=0.03) and more severe back disability (median (IQR) RMDQ: 2 (1, 3) vs. 1 (0, 2), p=0.04). Firefighters with 15 years or more of firefighting service reported significantly more severe lower extremity disability (median (IQR) LEFS: 71 (64, 77) vs. 76 (70, 79), p=0.0005). Firefighters reporting >1 MSDs were significantly older than firefighters reporting no MSD ( F(5,285)=3.3, p=0.002). Discussion: The rate of MSDs is high in firefighters, and their severity is elevated with greater age and LOS, suggesting cumulative exposures/injuries and highlighting the need for ongoing assessment of the musculoskeletal system and interventions to reduce injury throughout firefighters' careers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".