Outline

  • Abstract
  • Background
  • Methods
  • Results
  • Conclusion
  • Keywords
  • 1. Introduction
  • 2. Materials and Methods
  • 2.1. Data Collection
  • 2.2. Survey Instrument
  • 2.3. Measures
  • 2.3.1. Sleep Patterns and Quality
  • 2.3.2. Predictors of Sleep Patterns and Quality
  • 2.4. Statistical Analyses
  • 3. Results
  • 3.1. Demographic Profile of Truckers
  • 3.2. Employment Profile of Truckers
  • 3.3. Work Demands and Patterns of Truckers
  • 3.4. Sleep Patterns of Truckers
  • 3.4.1. Hours of Sleep
  • 3.5. Number and Length of Naps
  • 3.5.1. Sleep Quality
  • 3.6. Effects of Sleep Quality on Truckers' Work Performance
  • 3.7. Effects of Work on Truckers' Sleep Duration and Quality
  • 4. Discussion
  • 4.1. Sleep Hours
  • 4.2. Work Hours
  • 4.3. Irregular Work Schedules
  • 4.4. Miles Driven
  • 4.5. Limitations
  • 5. Conclusion
  • Conflicts of Interest
  • References

رئوس مطالب

  • چکیده
  • کلید واژه ها
  • 1. مقدمه
  • 2. مواد و روش ها
  • 2.1. جمع آوری داده ها
  • 2.2. ابزار پژوهش
  • 2.3. معیارها
  • 2.3.1. الگوها و کیفیت خواب
  • 2.3.2. عوامل پیش بینی کننده الگوها و کیفیت خواب
  • 2.4. تجزیه و تحلیل های آماری
  • 3. نتایج
  • 3.1. نمودار آمارگیری رانندگان کامیون
  • 3.2. نمودار بهره گیری از رانندگان کامیون
  • 3.3. تقاضاها و الگوهای کار و رانندگان کامیون
  • 3.4. الگوهای خواب رانندگان کامیون
  • 3.4.1. ساعات خواب
  • 3.5. تعداد و مدت زمان خواب های نیمروزی
  • 3.5.1. کیفیت خواب
  • 3.6. اثرات کیفیت خواب بر عملکرد کاری رانندگان کامیون
  • 3.7. اثرات کار بر مدت و کیفیت خواب رانندگان کامیون
  • 4. تشریح مطالب
  • 4.1. ساعات خواب
  • 4.2. ساعات کار
  • 4.3. برنامه های زمان بندی نامنظم کاری
  • 4.4. تعداد مایل ها رانندگی شده
  • 4.5. محدودیت ها
  • 5. نتیجه گیری

Abstract

Background

Given the long hours on the road involving multiple and interacting work stressors (i.e., delivery pressures, irregular shifts, ergonomic hazards), commercial drivers face a plethora of health and safety risks. Researchers goal was to determine whether and to what extent long-haul trucker work schedules influence sleep duration and quality.

Methods

Survey and biometric data collected from male long-haul truck drivers at a major truckstop in central North Carolina over a six month period.

Results

Daily hours worked (mean = 11 hours, 55 minutes) and frequency of working over government-mandated daily HOS regulations (23.8% “frequently or always”) were statistically significant predictors of sleep duration. Miles driven per week (mean = 2,812.61), irregular daily hours worked (63.8%), and frequency of working over the daily hour limit (23.8% “frequently or always”) were statistically significant predictors of sleep quality.

Conclusion

Implications of findings suggest a comprehensive review of the regulations and operational conditions for commercial motor vehicle drivers be undertaken.

Keywords: - - - -

Conclusions

As a result of the 1980 industry deregulation, trucking has gradually evolved into what is considered a stressogenic, obesogenic, and often pathogenic work environment [58,59]. In this context, long-haul truckers are afflicted by a plethora of syndemic comorbidities with not only ramifications for their own health but as well for the safety of the driving public [60]. Our findings corroborate that fatigue-inducing factors such as long work hours, irregular work shifts, high number of miles driven, and violation of HOS regulations have had a critical bearing on truckers’ sleep patterns. Despite recent changes in HOS legislation, the implications of these findings suggest that a comprehensive review of the regulations and operational conditions for commercial motor vehicle drivers should be undertaken.

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