Risk factors associated with work-preventing musculoskeletal discomfort in the upper extremities of bovine practitioners
Bibliographic record
Abstract
OBJECTIVE: To identify risk factors associated with work-preventing musculoskeletal discomfort (MSKD) in the upper extremities (defined as neck, shoulders, upper back, arms, elbows, wrists, and hands) of bovine practitioners. SAMPLE: 116 members of the Western Canadian Association of Bovine Practitioners. PROCEDURES: Data from a previously described cross-sectional survey of western Canadian bovine practitioners underwent further analysis. The survey, developed to glean information about MSKD in bovine practitioners, was a modified standardized Nordic questionnaire that included questions regarding personal and work characteristics and incidence and location of MSKD during the preceding 12 months along with perceptions about most physically demanding tasks. Logistic regression was used to identify factors associated with work-preventing upper extremity MSKD. RESULTS: 18 of 116 (15.5%) respondents indicated they had experienced work-preventing upper extremity MSKD during the preceding 12 months. The final multivariable regression model indicated that practice type (mixed animal vs primarily [> 50%] bovine; OR, 3.20; 95% CI, 0.96 to 10.67), practitioner height (OR, 0.93; 95% CI, 0.87 to 0.99), and number of veterinarians in the practice (OR, 1.32; 95% CI, 1.05 to 1.66) were significantly associated with the odds of work-preventing upper extremity MSKD. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that reproductive examination of cattle was not a significant risk factor for upper extremity MSKD in bovine practitioners. Further research into the effects of biomechanical, organizational, and psychosocial workplace factors on the development of MSKD in bovine practitioners is necessary to help inform prevention strategies to foster career longevity in this increasingly diverse practitioner group.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".