• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.118-127
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• 2009

This study tries to develop model in order to assess personal factors of senior traffic accidents that are widely recognized as one of the social problems. For the current practice. it gathers data (Simulation & Questionnaire Survey) of KOTSA and conducts Poisson and Negative Binomial Regression Analysis to develop traffic accident severity model. The results show that elderly drivers' accidents are mainly affected by attentiveness selection, velocity prediction ability and attentiveness distribution ability in a positive(+) way. Second, non-senior drivers' accidents are also positively(+) influenced by attentiveness selection, velocity prediction, distance perception, attentiveness distribution ability and attentiveness diversion ability. Therefore, influencing factors of senior and non-senior drivers to vehicle accidents are different. This eventually poses a indication that preliminary education for car accident prevention should be implemented based up[n the distinction between senior drivers and non-senior drivers.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.37-46
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• 2012

The number of traffic accidents caused by elderly drivers over the age of 65 has surged over the past ten years from 37,000 to 274,000 cases. The proportion of elderly drivers' accidents has jumped 3.1 times from 1.2% to 3.7% out of all traffic accidents, and traffic safety organizations are pursuing diverse measures to address the situation. Above all, connecting safety measures with an in-depth research on behavioral and physical characteristics of elderly drivers will prove vital. This study conducted an empirical research linking the driving characteristics and traffic accidents by elderly drivers based on the Driving Aptitude Test items and traffic accident data, which enabled the measurement of behavioral characteristics of elderly drivers. In developing the Influence Model, we applied the zero-inflated Poisson (ZIP) regression model and selected an accident prediction model based on the Bayesian Influence in regards to the ZIP regression model and the zero-inflated negative binomial (ZINB) regression model. According to the results of the AAE analysis, the ZIP regression model was more appropriate and it was found that three variables? prediction of velocity, diversion, and cognitive ability? had a relation of influence with traffic accidents caused by elderly drivers.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.622-635
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• 2022

Purpose: Due to the change of demography, the ratio of senior drivers has increased and the transition to a super-aged society is expected to make more seniors drive in the future. Method: In this research, we analyzed medical characteristics of the driver's age-specific decline in body function and saw that both the function of the physical as well as mental capacities deteriorates as people age. Among them, various functions are precipitously weakened after reaching 70, implying that those over the age of 70 are classified as seniors in a medical sense. In this context, we also could identify that based on such age criteria, various safety policies for senior drivers should be developed and set up in Korea. Result: We could find a steep fall in the physical function of body after reaching 70 from the chronological change of cognitive function and judgment ability. In particular, it is revealed that the driving license institution and aptitude test for drivers over 70 should be thoroughly examined, as physical functions necessary for driving such as eyesight and hearing ability is not strong enough in many drivers over 70. Conclusion: Focusing on the physical capacity to drive, we tried to find the hazardous age bracket of senior drivers which might influence driving behaviors. Going forward, we expect this work would help to understand the policies for senior drivers and drivers' physical differences.

• The Korean Journal of Emergency Medical Services
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• v.15 no.1
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• pp.65-78
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• 2011

Purpose : We investigated the career choice and the employment preparation of emergency medical technology (EMT) students. The results of study will provide the base information about the consciousness for career choice and employment of the EMT students. Method : We conducted 1,586 surveys from 665 students at six four-year colleges and 921 students at seven three-year colleges, from Aug. 27th to Oct. 31st in 2010. The result was analyzed by SPSS 18.0 using description statistics, t-test, ANOVA, Scheffe and Pearson correlation coefficient. Result : The general characteristics showed male 50.2% and female 49.8%, and first grade 34.6%, second grade 27.4%, third grade 28.2%, and fourth grade 9.8%. The 53.9% of students had experienced the hospital training and the 44.8% did the fire station training. For the choice of job, there were the 61.8% student who hope to enter the employ in fire station or public service, while 25.7% students hope to be employed in hospitals. The reason for a wish job were 'majors-related job' in 18.2% students, 'employment stability' in 17.2% and 'hit on the aptitude and talent' in 16.7%, 'appropriate salaries' in 15.9%. In the questionnaire of the University what to assist you for job preparation, they chose the 'support for get major related license', 'support for officer exam preparation' and 'support of foreign language study' in 34.6%, 16.8% and 16.6%, respectively. For achieved licence, they had a driver's license in 53.9%, BLS (basic life support) provider in 20.3%, life guard in 16.2% and scuba in 8.8%. The statistically significant correlation was identified between the awareness of University that provides job information and one's career awareness (r= .203, p<.000), the awareness that University provide job information and one's confidence in employment (r= .236, p<.000), and one's career awareness and one's confidence in employment (r = .356, p = .000). Conclusion : The most of EMT Students are well conscious of the their future employment and has prepared career to be employed their preference job.