Post-traumatic Stress Risk Factor in Fire Fighters

다국어 초록 (Multilingual Abstract)

As technical civilization took place, material abundance got increased, but life became in a state where it is more insecure and precarious in which now anxiety is increasing. Since the collapse of Sampoong Department Store 20 years ago, until nowadays as Sewol Ferry Disaster, danger is lurking everywhere, and as more disasters occur, the more attention on safety is increasing. Fire Fighters, due to the instability of scene, are exposed to various stress and often experience a post-traumatic stress (PTS). PTS reduces concentration on job and its satisfaction, and causing turnover urge, causes a negative consequences on reducing the result of the organization. This study was to identify which variables are most important risky factor in fire fighters' PTS, progressed simple and multiple logistic regression. The risk factors of PTS of fire fighters are, age, period of working experience, current affairs, current job performance period, frequency of mobilization of past 1 year, the main stress-inducing tasks, group requiring no consultation, psychotherapy and any needs, and the group who hasn't used mental health service. Statistically significant predictor of post-traumatic stress were found to be frequency of mobilization of past 1year, group requiring no consultation, psychotherapy and any needs, and the group who hasn't used mental health service. As conclusion, Fire fighter’s PTS can be decreased by Putting fire fighters who has experienced traumatic events as targets, should discover a high-risk group in advance. It is necessary to develop a Critical incident Stress Debriefing (CISD) program. Through the linkage with the experts in the workplace, should maintain prevention and management on PTS.

목차 (Table of Contents)

• Abstract
• Introduction
• Methods
• Research design
• Subject and data collection
• Result
• 1) The general characteristics of subjects
• 2) PTS high risk group of fire fighters
• 3) Simple logistic regression
• 4) Multiple logistic regression
• Discussion & Conclusion
• References