Understanding health needs of professional truck drivers to inform health services: a pre-implementation qualitative study in a Canadian Province
Bibliographic record
Abstract
OBJECTIVES: Long-haul truck drivers experience multiple challenges, including increased health risks. A large percentage of professional truck drivers (PTDs) suffer from numerous chronic physical health conditions such as obesity, hypertension, diabetes, heart disease, sleep disorders, etc.) as well as poor mental health and social challenges. Furthermore, this population experiences numerous barriers related to accessing health care services including primary care and resources to improve their health. PTDs living in rural and remote areas are at higher risk. The objective of this study is to understand the views of PTDs and the trucking industry on health and personalized healthcare interventions and services. METHODS: In-depth semi-structured interviews were conducted with twenty-six individuals with contextual knowledge and experience in the trucking ecosystem, to better understand the needs, expectations, and preferences of PTDs based in New Brunswick (Canada), related to their health (physical, mental, and social). Analysis of the audiotape recording was conducted using thematic content analysis. RESULTS: Three major themes emerged from the qualitative analysis describing PTDs' health needs, existing health and preventive services, as well as recommendations for personalized healthcare interventions and services to be implemented: (1) "My life as a trucker!" Understanding needs and challenges, (2) "Taking care of myself, do you think it is easy while you're on the road?" Describing drivers and motivators for better health, and (3) "Can you hear what we need?" Translating needs into recommendations for tailored health services and preventative services. CONCLUSION: A highly demanding work environment and lack of timely access to integrated primary care negatively affect PTDs' health. Results of this study shed light on how to tailor primary care to improve its responsiveness and adequacy to PTDs' needs and realities. PTDs-sensitive integrated services, including multicomponent interventions (health education, coaching for lifestyle changes, and social support), are still lacking within the New Brunswick health system.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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 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".