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강지연 ( Kang Ji-Yeon ) - 동아대학교 간호학과
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Abstract
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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.
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KeyWords
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중환자실, 생존자, 감성분석, 감정, 인공지능
Artificial intelligence, Critical illness, Emotions, Intensive care units, Survivors
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원문 및 링크아웃 정보
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등재저널 정보
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