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Exploring Antecedent Factor that Influence Dental Hygienist's Job Satisfaction and Turnover Intention

치과위생사의 직무만족과 이직의도에 영향을 미치는 선행요인 탐색

  • Received : 2018.12.07
  • Accepted : 2019.03.08
  • Published : 2019.03.31

Abstract

Advances in the dental medical field now provide high quality medical service, and thus, it has become important to identify the role of dental hygienists. However, the professional status of dental hygienists has not been acknowledged, and this has resulted in problems such as dissatisfaction and high turnover rates at dental hospitals. This study was undertaken to identify factors that influence dental hygienist job satisfaction and turnover rates. To achieve this we used a synthetic approach incorporating individual (optimism), job (professionalism), and organizational (perceived organizational support) characteristics. Our results showed that optimism, professionalism, and perceived organizational support were positively related to job satisfaction. Furthermore, job satisfaction was found to be negatively related to turnover intension and to partially mediate the effect between POS and turnover intention. We believe the results of this study could be used by dental hospitals to address dental hygienist dissatisfaction and high turnover rates.

치과의료에 대한 공급은 갈수록 증가하고 있고 이에 따라 구강보건 전문인력인 치과위생사의 역할은 더욱 중요해지고 있다. 그러나 아직까지 치과위생사의 직업전문성이 의료현장에서 실제로 인정받는다고 보기에는 힘든 상황이며, 이로 인해 치과위생사의 직무불만과 이직의도는 의료기관의 문제로 대두되고 있다. 이에 본 연구에서는 치과위생사의 직무만족과 이직의도에 영향을 미치는 선행요인을 탐색하여 조직유효성을 증진시키는 방법을 모색하고자한다. 선행요인을 보다 다각도로 탐색하게 위해 개인의 특성(낙관성)과 직무와 관련된 특성(직업전문성) 그리고 조직과 관련된 특성(조직지원인식)으로 구분하여 접근하였다. 치과 의료기관에 근무하는 치과위생사들 199명의 자료를 분석한 연구결과, 치과위생사의 낙관성과 직업전문성, 그리고 조직지원인식은 모두 직무만족도를 높여 궁극적으로 이직의도를 낮출 수 있는 것으로 나타났다. 특히 조직지원인식은 이직의도에 대해 직접적인 효과를 미치기도 하지만 직무만족이라는 매개변수에 의해 보다 큰 효과를 미치는 것으로 밝혀졌다. 본 연구의 결과는 치과위생사의 높은 이직률과 직무불만으로 고통받는 치과 의료기관들에게 문제해결을 위한 기초자료를 제공할 수 있을 것으로 기대된다.

Keywords

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Fig. 1. Research Model

Table 1. Results of factor analysis

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Table 2. Results of correlation analysis

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Table 3. Results of hierarchical regression analysis

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