Risk Factors for Depressive Symptoms in Long-Haul Truck Drivers
Bibliographic record
Abstract
Work-related stress is a salient risk factor for depression. While long-haul truck drivers (LHTDs) face a myriad of occupational pressures and demands, little research has examined predictors of depressive symptoms in this occupational group. The purpose of this study was to identify predictors of depressive symptoms in LHTDs. A cross-sectional study was used to examine depressive symptoms, health and working conditions in a sample of 107 LHTDs (mean age of 50.7 ± 12.3; 95.6% were men) at truck stops from five Western Canadian cities. The findings show that 44% of LHTDs reported symptoms of depression in the past 12 months. Severe work-related stress, the use of psychiatric medications and broken sleep were significant predictors of depressive symptomology accounting for 41% of the variance. The findings suggest that LHTDs experience a host of occupational stressors that are embedded within the transportation industry that may increase the risk for depressive symptoms. Mental health promotion efforts that improve sleep quality, decrease work-related demands and pressures, and increase the use of psychiatric medication may reduce rates of depressive symptoms among LHTDs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| 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".