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Journal of Korean Critical Care Nursing 2018;11(1):1-14.
Published online February 28, 2018.

질적연구 진술문을 이용한 중환자실 생존자의 감성분석
강지연
동아대학교 간호학과
Sentiment Analysis of the Quotations of Intensive Care Unit Survivors in Qualitative Studies
Jiyeon Kang
Professor, Department of Nursing, Dong-A University, Korea. jykang@dau.ac.kr
Abstract
PURPOSE
As the intensive care unit (ICU) survival rate increases, interest in the lives of ICU survivors has also been increasing. The purpose of this study was to identify the sentiment of ICU survivors.
METHOD
The author analyzed the quotations from previous qualitative studies related to ICU survivors; a total of 1,074 sentences comprising 429 quotations from 25 relevant studies were analyzed. A word cloud created in the R program was utilized to identify the most frequent adjectives used, and sentiment and emotional scores were calculated using the Artificial Intelligence (AI) program.
RESULTS
The 10 adjectives that appeared the most in the quotations were ‘difficult’, ‘different’, ‘normal’, ‘able’, ‘hard’, ‘bad’, ‘ill’, ‘better’, ‘weak’, and ‘afraid’, in order of decreasing occurrence. The mean sentiment score was negative (-.31±.23), and the three emotions with the highest score were ‘sadness’(.52±.13), ‘joy’(.35±.22), and ‘fear’(.30±.25).
CONCLUSION
The natural language processing of AI used in this study is a relatively new method. As such, it is necessary to refine the methodology through repeated research in various nursing fields. In addition, further studies on nursing interventions that improve the coherency of ICU memory of survivors and familial support for the ICU survivors are needed.
Key Words: Artificial intelligence, Critical illness, Emotions, Intensive care units, Survivors


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