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An Analysis of Research Trends about Good Death in Korea

좋은 죽음에 대한 국내 연구동향 분석

  • Received : 2022.04.08
  • Accepted : 2022.06.20
  • Published : 2022.06.28

Abstract

This study was attempted to suggest a direction for future research on good death by analyzing and synthesizing research trends on good death. For this purpose, 66 articles related to good death published in academic journals in Korea from 2011 to 2021 were analyzed based on the analysis frame of references. As a result, the year with the most good death studies was 2019 (18.2%). In the analysis by research design, 52 articles (78.8%) were the most quantitative studies, and 36 studies (54.5%) were survey studies. In the field of research, nursing studies were the most researched with 47 articles (71.2%), but multidisciplinary studies were three articles (4.5%). The subjects of the good death study were mainly the aged in the community and nursing students, each of which was 13 (19.7%), but the studies for patients were published only four articles (6.1%). The most used tool was the perception of a good death and conducted in in 38 articles (73.1%). The main research variables were the the perception of good death and hospice palliative and end-of-life care, and family support was used as mediating variables. Therefore, not only multidisciplinary research but also development research for vaious good death instruments may be suggested to comprehensively understand good death.

본 연구는 좋은 죽음에 관한 연구 동향을 분석하고 종합하여 향후 좋은 죽음에 관한 연구의 방향을 제시하고자 시도되었다. 이를 위해 2011년부터 2021년까지 국내학술지에 발표된 좋은 죽음 관련 66편의 논문을 분석준거틀에 근거하여 분석하였다. 그 결과 좋은 죽음 연구가 가장 많이 이루어진 년도는 2019년(18.2%)이었다. 연구설계별 분석에서는 양적 연구가 52편(78.8%)으로 가장 많았고, 그 중 조사연구가 36편(54.5%)으로 나타났다. 연구분야에서는 간호학 논문이 47편(71.2%)으로 가장 많이 연구되었고, 다학제간 연구는 3편(4.5%)이었다. 좋은 죽음 연구대상자는 주로 지역사회 노인과 간호대학생으로 이 각각 13편(19.7%)으로 나타났고, 환자 대상연구는 4편(6.1%)으로 나타났다. 연구도구는 좋은 죽음 인식도구가 38편(73.1%)에서 사용되었다. 주요 연구 변인은 좋은 죽음 인식과호스피스완화의료 및 임종간호였고, 가족지지는 매개변인으로 사용되었다. 따라서 좋은 죽음을 종합적으로 이해하기 위해 다학제 연구와 다양하게 좋은 죽음을 측정할 수 있는 도구 개발을 제언한다.

Keywords

Acknowledgement

This Research was supported by Kyungwoon University Research Grants 2022.

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