英文摘要
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The main purpose of this study was to investigate the related factors of traumas of motorcycle traffic accidents survivors and injury severity among young adults-namely 15 to 24-year-olds-in Taipei City using the cross-sectional survey. Subjects of our study were made up of 164 teenagers who underwent motorcycle accident-related emergency treatment at three municipal hospitals in Taipei, and we itemized the information we gleaned for immediate and retrospective data registers. The major findings of this study were as follows:
1. As for research subjects' social demography, the variables such as gender, age, identity have salient correlation with the injured degree of motorcycle accident.
2. As for research subjects' contemporary situation of accident, the variables such as the weather situations, doing what activity and injured place have salient correlation with the injured degree of motorcycle accident.
3. As for the injured situations and locations of research subjects, the variables such as the injured location is head/neck and the injured situation is fracture have salient correlation with the injured degree of motorcycle accident.
4. As for the research subjects' motorcycle riding behavior, the variables such as role of motorcycle, whether having motorcycle driver's license, speed of motorcycle, whether losing of helmet, whether the behavior is neglecting and whether complying with traffic signals and lines have salient correlation with the injured degree of motorcycle accident.
5. While exploring the predictive ability of social demography, contemporary situation of accident, injured locations and situations, motorcycle riding behavior towards the injured degree of motorcycle accident, the correlation strength coefficient of overall model is Nagelkerke R2=.546 showing that there exists medium relationship between dependent variable and in dependent variable. In view of the salience indicators of individual parameter, ”age”, ”identity”, ”doing what activity”, ”injured place” which are the main factors for predicting the research subjects' injured degree of motorcycle accident, among them, ”identity” has the strongest predictive ability.
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