2023 Fiscal Year Final Research Report

"Validation of Corrective Lifestyle Patterns through Survey and AI Analysis of Circadian Rhythms among Shift Working Nurses"

Research Project

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Project/Area Number	19H03925
Research Category	Grant-in-Aid for Scientific Research (B)
Allocation Type	Single-year Grants
Section	一般
Review Section	Basic Section 58050:Fundamental of nursing-related
Research Institution	Osaka Metropolitan University (2022-2023) Osaka City University (2019-2021)
Principal Investigator	Yamaguchi Yoko 大阪公立大学, 大学院看護学研究科, 教授 (50381918)
Co-Investigator(Kenkyū-buntansha)	山田真介大阪公立大学, 大学院医学研究科, 准教授 (00623810) 中島智晴大阪公立大学, 大学院情報学研究科, 教授 (20326276) 藤田寿一大阪公立大学, 大学院看護学研究科, 准教授 (30212187) 若村智子京都大学, 医学研究科, 教授 (40240452) 森木ゆう子大阪公立大学, 大学院看護学研究科, 准教授 (70374163) 岩崎賢一大阪公立大学, 大学院看護学研究科, 特任講師 (70912046)
Project Period (FY)	2019-04-01 – 2023-03-31
Keywords	睡眠と代謝 / 概日リズムの乱れ / シフト勤務者
Outline of Final Research Achievements	This study predicted lifestyle patterns that could correct circadian rhythms through AI analysis based on the investigation of lifestyle patterns and sleep of shift-working nurses. The participants, 37 in total, were mostly women around 30 years old. The PSQI scores did not show significant changes, but there were variations in sleep efficiency and sleep duration, and an increase in calorie intake was observed on night shift days. During the study period, the social circumstances caused by the COVID-19 pandemic made it difficult to recruit participants and collect data as initially planned. Consequently, there was insufficient data on lifestyle patterns for AI analysis. Therefore, no clear correlation was found between AI analysis and clock genes, and it was not possible to predict lifestyle patterns that could correct circadian rhythms.
Free Research Field	成人看護学
Academic Significance and Societal Importance of the Research Achievements	本研究は、シフト勤務を行う看護師の生活パターンと概日リズムの乱れを多角的に調査し、AIによる解析を行った点で学術的意義がある。具体的には、睡眠状況、血糖変動、食事内容、時計遺伝子多型などのデータを収集し、機械学習を活用して複雑なパターンや相関関係を検討した。また、COVID-19パンデミック中の柔軟な対応を通じて、実践的な課題と改善点の知見を提供した。これにより、今後の研究に向けた効果的なデータ収集や解析方法の確立に貢献するとともに、シフト勤務看護師の健康管理や勤務改善策の策定に寄与する可能性がある。