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Understanding of Rehabilitation Nursing based on Academic Big Data Analysis
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학술 빅데이터 분석에 기반한 재활간호의 이해

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Type
Academic journal
Author
Bae, Jung-Ho (백석문화대학교) Burm, Eun-Ae (백석문화대학교)
Journal
Korean Academic Society Of Rehabiltation Nursing The Korean Journal of Rehabilitation Nursing Vol.23 No.2 KCI Accredited Journals
Published
2020.12
Pages
105 - 111 (7page)
DOI
10.7587/kjrehn.2020.105

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Topic
본 연구의 주제는 국내 재활간호에 대한 학술 빅데이터 분석을 통해 질 높은 재활간호 방안을 마련하는 것이다.
📖
Background
재활 간호는 만성 질환과 노령화로 인해 그 필요성이 증가하고 있으며, 재활간호에 대한 사회적 인식 개선과 지식 기반 강화를 통한 재활 간호의 질 향상이 시급하다.
🔬
Method
이 연구는 1980년부터 2020년까지 '재활간호'와 관련된 모든 학술 자료를 수집하고, R과 Python 프로그램을 사용하여 텍스트 분석 및 시각화를 통해 연구를 진행하였다.
🏆
Result
분석 결과, 재활간호에 대한 연구는 1990년대 중반부터 급격히 증가하였고, 주요 주제어로는 환자, 뇌졸중, 가족 등이 나타났다. 연구에서 부정적인 감성어가 긍정적인 감성어 보다 약 6배 이상 높은 것으로 나타났다.
Understanding of Rehabilitation Nursing based on Academic Big Data Analysis
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Abstract· Keywords

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Purpose: The purpose of this study was to provide high-quality rehabilitation nursing through the analysis of academic big data in domestic rehabilitation nursing and to provide basic data for preparing a plan for supporting families who perform rehabilitation nursing. Methods: This study is a literature review to explore research trends in rehabilitation nursing. We collected quantitative and qualitative data in the educational and academic information database (RISS) defined as the big data, and extracted keywords by the "rehabilitation", and "rehabilitation nursing". The data were analyzed by’R’ Program. Word cloud and social network analysis were performed. Results: In the field of domestic rehabilitation nursing study, the main keywords were patient, stroke, family, old man, depression, stress, and quality of life. As a result of sentiment analysis with the main keywords in domestic rehabilitation nursing, negative emotional words appeared 6 times higher than positive emotional words. Conclusion: We suggested that it is also necessary to prepare emotional support plans for patients, family and nurses who are targeted for rehabilitation nursing.
#Academic big data #Big data analysis #Rehabilitation nursing #Sentiment analysis #학술 빅데이터 #빅데이터 분석 #재활 간호 #감성분석

AI Summary

Topic

본 연구의 주제는 국내 재활간호에 대한 학술 빅데이터 분석을 통해 질 높은 재활간호 방안을 마련하는 것이다.

Background

재활 간호는 만성 질환과 노령화로 인해 그 필요성이 증가하고 있으며, 재활간호에 대한 사회적 인식 개선과 지식 기반 강화를 통한 재활 간호의 질 향상이 시급하다.

Method

이 연구는 1980년부터 2020년까지 '재활간호'와 관련된 모든 학술 자료를 수집하고, R과 Python 프로그램을 사용하여 텍스트 분석 및 시각화를 통해 연구를 진행하였다.

Result

분석 결과, 재활간호에 대한 연구는 1990년대 중반부터 급격히 증가하였고, 주요 주제어로는 환자, 뇌졸중, 가족 등이 나타났다. 연구에서 부정적인 감성어가 긍정적인 감성어 보다 약 6배 이상 높은 것으로 나타났다.

주요내용

Contents

서론
연구방법
연구결과
논의
결론 및 제언
REFERENCES

References (20)

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Bae, J / 2019 / Big data analysis: Medical accident / Medico-Legal Update 19(1):646~652 google schola Bae, J / 2020 / Big data analysis for child well-being on academic research / Medico Legal Update 20(1):2058~2062 google schola Burton, C. R. / 2000 / A description of the nursing role in stroke rehabilitation / Journal of Advanced Nursing 32(1):174~181 Crossref Burton, C. / 2005 / Expanding the role of the stroke nurse : A pragmatic clinical trial / Journal of Advanced Nursing 52(6):640~650 Crossref 최연희 / 2015 / 지역사회 역량강화 전략을 이용한 재가 허약여성노인의 운동유지 프로그램 개발 / 재활간호학회지 18(2):153~164 dbpia

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