Improving truck stop environments to support long-haul truck driver safety and health: A scoping review
Bibliographic record
Abstract
• Long-haul truckers depend on truck stop amenities for basic daily needs. • Truck stops do not support safety, health, and well-being of long-haul truckers. • Parking and basic amenity improvements should inform designs of truck stops. • Various stakeholders should inform truck stop policies and infrastructures. • Numerous avenues of future research are needed to transform truck stop amenities. Long-haul truck drivers (LHTD) are required to drive long distances to transport essential goods and products in a timely manner, which can lead to roadway safety risks, an unbalanced lifestyle, and poor health and wellbeing. While truck stops are designed for LHTD to park, refuel, eat, shower, and sleep, the lack of amenities (e.g., unavailable parking, poor food choices) contributes to poor safety and health outcomes. This scoping review synthesized the evidence on the current amenities offered at truck stops and how they can be improved to support LHTD safety and health. Research databases (e.g., EMBASE, Global Health, Medline) and online sources (e.g., transportation research websites) were searched for publications in English from 2006 to 2023. A total of 5,377 unique sources were identified. Two reviewers independently screened the 5,377 titles and abstracts and then the full texts of 59 sources. Three sources were included through searching reference lists of 13 full-texts included, totaling 16 sources included in the scoping review. Parking and basic truck stop amenities (e.g., fuel, food, restrooms, and showers) are most important to LHTD. However, there is currently a lack of available, accessible, affordable, or safe parking at truck stops which preclude LHTD from parking overnight. There is also a lack of food options to meet LHTD preferences for different cuisines, healthier choices, and options that accommodate food allergies. Moreover, LHTD expect parking, restrooms, and showers to be free when purchasing fuel. The current state of parking and basic truck-stop amenities should be improved to prevent safety-adverse LHTD behaviors (e.g., driving beyond their hours of service and increasing their risk of driving fatigued, falling asleep, or getting into an accident). There is a high demand among LHTD to improve and expand the availability, accessibility, security, and cost of these truck stop amenities. Improvements to truck stop amenities may improve the resilience of supply chains and constitute public health interventions to reduce longstanding safety and health disparities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".