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간호사 대상 한국어판 인간중심돌봄 측정도구의 타당도와 신뢰도

Validity and Reliability of the Korean Version of Person-Centered Practice Inventory-Staff for Nurses

  • 김소현 (서울대학교 간호대학) ;
  • 탁성희 (서울대학교 간호대학.간호과학연구소)
  • Kim, Sohyun (College of Nursing, Seoul National University) ;
  • Tak, Sunghee H (The Research Institute of Nursing Science.College of Nursing, Seoul National University)
  • 투고 : 2021.02.15
  • 심사 : 2021.04.21
  • 발행 : 2021.06.30

초록

Purpose: The purpose of this study was to evaluate the validity and reliability of the Korean version of Person-Centered Practice Inventory-Staff (PCPI-S) for nurses. Methods: The English PCPI-S was translated into Korean with forward and backward translation. Data were collected from 338 nurses at one general hospital in Korea. Construct validity was evaluated with confirmatory factor analysis, convergent validity, and discriminant validity. Known-group validity was also evaluated. Cronbach's α was used to assess the reliability. Results: The PCPI-S Korean version consisted of 51 items in three areas: prerequisites, the care environment, and person-centered process. The comparative fit index (CFI) and values of person-centered care process were improved after engagement and having sympathetic presence items were combined as one component. The construct validity of PCPI-S Korean version was verified using four-factor structures (.05 < RMSEA < .10, AGFI > .70, CFI > .70, and AIC). The convergent validity and discriminant validity of the entire PCPI-S question were verified using a two-factor structures (AVE > .50, construct reliability > .70). There was an acceptable known-group validity with a significant correlation between the PCPI-S level and the degree of person-centered care awareness and education. Internal consistency was reliable with Cronbach's α .95. Conclusion: The Korean version of PCPI-S is valid and reliable. It can be used as a standardized Korean version of person-centered care measurement tool. Abbreviation: RMSEA = root mean square error of approximation; AGFI = adjusted goodness of fit index; AIC = Akaike information criterion; AVE = average variance extracted.

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참고문헌

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