Predictors of rural driver self-reported passing behaviors when interacting with farm equipment on the roadway.

Background: Crashes involving farm equipment (FE) are a major safety concern for farmers as well as all other users of the public road system in both rural and urban areas. These crashes often involve passenger vehicle drivers striking the farm equipment from behind or attempting to pass, but little is known about drivers' perceived norms and self-reported passing behaviors. The objective of this study is to examine factors influencing drivers' farm equipment passing frequencies and their perceptions about the passing behaviors of other drivers. Methods: Data were collected via intercept surveys with adult drivers at local gas stations in two small rural towns in Iowa. The survey asked drivers about their demographic information, frequency of passing farm equipment, and perceptions of other drivers' passing behavior in their community and state when approaching farm equipment (proximal and distal descriptive norms). A multinomial logistic regression model was used to estimate the relationship between descriptive norms and self-reported passing behavior. Results: Survey data from 201 adult drivers showed that only 10% of respondents considered farm equipment crashes to be a top road safety concern. Respondents who perceived others passing farm equipment frequently in their community were more likely to report that they also frequently pass farm equipment. The results also showed interactions between gender and experience operating farm equipment in terms of self-reported passing behavior. Conclusions/Implications: Results from this study suggest local and state-level norms and perceptions of those norms may be important targets for intervention to improve individual driving behaviors around farm equipment.

Development of a Checklist to Identify Injury Hazards on Row Crop Farms in the Midwestern United States.

Agriculture is among the most dangerous industries in the U.S., yet routine surveillance of injury hazards is not currently being conducted on a national level. The objectives of this study were to describe a new tool, called the Hazard Assessment Checklist (HAC), to identify and characterize farm hazards that increase injury risk to farmers and farm workers, and (2) report the inter-rater reliability of the new tool when administered on row-crop farms in Iowa. Based on a literature review and a consensus of expert opinion, the HAC included hazards related to self-propelled vehicles, powered portable implements, fixed machinery and equipment, farm buildings and structures, fall risks, and portable equipment associated with fall risk. A scoring metric indicating the extent of compliance with recommended safety guidelines and standards was developed for each item of the HAC, which included compliant, minimal improvement needed, substantial improvement needed, and not compliant. Inter-rater reliability was assessed from data collected by research staff on 52 row crop farms in Iowa. Cohen's weighted Kappa values demonstrated high inter-rater reliability, ranging between 0.86 and 0.94, for all HAC sections. The HAC can be completed in 1.5-2 hours on each farm and requires about three hours of training, two hours of which are spent in field training. The ability to monitor injury-related hazards over time using an empirically driven tool will contribute significantly to injury prevention efforts in an industry with consistently high rates of fatal and nonfatal injury.

Examining the Association Between Age and Tractor Driving Performance Measures Using a High-Fidelity Tractor Driving Simulator.

HIGHLIGHTS This study uses a new tractor driving simulator to examine the impact of age on perception response time in an emergency braking situation. The results demonstrate increased risk for crash among older farm equipment operators. ABSTRACT. Transportation-related incidents are the leading cause of occupational fatalities for all industries in the U.S. In the agriculture industry, where tractor-related incidents are the leading cause of occupational fatality, fatal crashes occur more frequently among senior farm equipment operators (FEOs) than younger FEOs. This study examined the association between age and driving performance among FEOs using a simulated driving environment. We demonstrated that older FEOs have longer perception response times when encountering an incurring semi-truck during a simulated drive than younger FEOs. These results persisted when adjusted for selected medical diagnoses and medications, tractor generation, and tractor horsepower. However, due to the small sample size and limitations of the tractor driving simulator, its use for event perception response time research is questionable. The tractor driving simulator used in this study may be better suited for distracted driving studies and studies comparing the ways in which FEOs drive passenger vehicles compared to tractors.

Examination of Realism in a High-fidelity Tractor Driving Simulator.

Transportation-related incidents are the leading cause of occupational fatalities for all industries in the U.S., including the agricultural industry, which suffers thou- sands of crashes involving farm equipment each year. Simulated driving studies offer a safe and cost-effective way to conduct driving research that would not be feasible in the real world. A tractor driving miniSim was developed and then evaluated for realism at the University of Iowa among 99 Midwestern farm equipment operators. It is important for driving simulators to have a high degree of realism for their results to be applicable to non-simulated driving operations. High-fidelity driving simulators facilitate extrapolations made by driving research but should be re-tested for realism when changes are made to the design of the simulator. The simulator used in this study emulated a tractor cab with realistic controls, three high-resolution screens, and high-fidelity sound. After completing a 10-minute drive, farm equipment operators completed a survey and scored four specific domains assessing specific characteristics (i.e., appearance, user interface, control, and sound) of the tractor simulator's realism using a seven-point Likert scale (from 0 = not at all realistic to 6 = completely realistic). An overall realism score and domain scores were calculated. Farm equipment operators were also asked to provide recommendations for improving the tractor miniSim. Overall, farm equipment operators rated the simulator's realism favorably (i.e., >3 on a scale from 0 to 6) for all individual items and domains. The appearance domain received the highest average realism score (mean = 4.58, SD = 1.03), and the sound domain received the lowest average realism score (mean = 3.86, SD = 1.57). We found no significant differences in realism scores across farm equipment operator characteristics. The most frequently suggested improvements were to tighten the steering wheel (27%), make the front tires visible (19%), and that no improvements were needed to improve the simulator realism (18%). This study demonstrates that the new trac- tor miniSim is a viable approach to studying farm equipment operations and events that can lead to tractor-related crashes. Future studies should incorporate the suggested improvements and seek to validate the simulator as a research and outreach instrument.

Characteristics of Farm Equipment-Related Crashes Associated With Injury in Children and Adolescents on Farm Equipment.

PURPOSE: Operating or riding on farm equipment is one of the leading causes of farm-related injuries and fatalities among children and adolescents. The aim of this study is to examine environment, crash, vehicle, and occupant characteristics and the probability of injury, given a crash, in youth under age 18 on farm equipment. METHOD: Data from the Departments of Transportation on farm equipment-related crashes across 9 Midwestern states from 2005-2010 were used. Odds ratios were calculated using logistic regression to assess the relationship between environment, crash, vehicle, and occupant characteristics and the probability of injury, given a crash. FINDINGS: A total of 434 farm equipment-related crashes involved 505 child or adolescent occupants on farm equipment: 198 passengers and 307 operators. Passengers of farm equipment had 4.1 higher odds of injury than operators. Occupants who used restraints had significantly lower odds of injury than those who did not. Furthermore, occupants on farm equipment that was rear-ended or sideswiped had significantly lower odds of injury compared to occupants on farm equipment involved in noncollision crashes. Likewise, occupants on farm equipment that was impacted while turning had significantly lower odds of injury compared to those on equipment that was impacted while moving straight. CONCLUSION: Precautions should be taken to limit or restrict youth from riding on or operating farm equipment. These findings reiterate the need to enforce policies that improve safety measures for youth involved in or exposed to agricultural tasks.