Pain, medication, and injury in older farmers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Agricultural work continues to be a dangerous occupation. Older farmers experience high risks for work-related injury. The purpose of this research was to determine if there is a relationship between medication use and injury among older male farmers in Alberta. METHODS: Using probabilistic linkage between an Alberta Agriculture government registry of farm operators and the Alberta Health Plan registry file, older farmers (aged 66 and older) were identified. Farm related injuries were identified using an E-code search of both hospitalization and emergency department separations for a 3-year period. Cases were matched to controls on age, geographic health region, and index injury date at a ratio of 1:5. Co-morbidity and medication use for each of the cases and controls were derived from population based health system utilization files. Conditional logistic regression was used to determine which medications were related to injury. RESULTS: Overall, a total of 282 farm related injuries were suffered by the linked group. Controlling for co-morbidity, farmers who had stopped taking narcotic pain killers (OR = 9.37 [95% CI:4.95, 17.72]) and non-steroidal anti-inflammatories (OR = 2.40 [95% CI:1.43, 4.03]) 30 days prior to the date of injury were at risk of injury. Those farmers taking sedatives up until the date of injury were also at risk (OR = 3.01 [95 CI:1.39, 6.52]). In addition, those suffering from incontinence/urinary tract disorders (OR = 2.95 [95% CI:1.30, 6.71]), and prior injury (OR = 1.42 [95% CI:1.04, 1.95]) were also at greater risk of injury. CONCLUSIONS: The relationship of medication use and injury in this population is different from those observed in studies of falls in older persons. We hypothesize that distraction from either pain or co-morbidity may play an important role in the etiology of injuries suffered in this active older working population. Further investigations in this area are required to confirm these findings.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 it