Ma Zijuan, Chen Xiao-Yan, Wang Dongfang, Zhu Zhiyi, Niu Haiquan, Huang Shuiqing, Zhou Xiuzhu, Yang Zheng, Fan Fang
School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China.
Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Guangzhou, China.
J Sleep Res. 2022 Oct;31(5):e13552. doi: 10.1111/jsr.13552. Epub 2022 Feb 2.
Few studies have assessed the overall nature and profiles of subjective sleep inertia (SI) within the general population. This study was designed to identify subjective SI profiles and examine the associations between profiles of subjective SI with sociodemographic and sleep-related characteristics. A total of 11 colleges and universities were surveyed from May 30 to June 17, 2021, by convenience sampling. A total of 1,240 participants provided usable data regarding sociodemographic information, Sleep Inertia Questionnaire, and sleep-related characteristics via an online platform. Latent profile analysis was utilised to identify profiles of SI. Multinomial logistic regression was further performed to examine the predisposing factors of profiles of SI. Four profiles of SI were identified: (1) "Low SI", 20%; (2) "Mild SI", 31%; (3) "Moderate SI", 33%; and (4) "Severe SI", 16%. Compared to a Low SI profile, younger, individuals with an evening chronotype, and individuals who had <6 h sleep/night, experienced poor sleep quality, and moderate-to-severe sleep disturbance were at increased risk of experiencing severe SI. Individuals with more languid types tended to show more severe SI, while individuals reporting greater flexibility experienced less SI. This study is the first effort to examine the profiles of subjective SI using latent profile analysis and identified four profiles of SI in the general population. This effort may contribute to a greater understanding of SI, including the development of a screening tool and interventions to reduce SI.
很少有研究评估普通人群中主观睡眠惯性（SI）的总体性质和特征。本研究旨在识别主观SI特征，并检验主观SI特征与社会人口学及睡眠相关特征之间的关联。2021年5月30日至6月17日，通过便利抽样对11所高校进行了调查。共有1240名参与者通过在线平台提供了有关社会人口学信息、睡眠惯性问卷和睡眠相关特征的可用数据。采用潜在类别分析来识别SI特征。进一步进行多项逻辑回归以检验SI特征的 predisposing因素。识别出了四种SI特征：（1）“低SI”，20%；（2）“轻度SI”，31%；（3）“中度SI”，33%；（4）“重度SI”，16%。与低SI特征相比，年龄较小、具有夜型生物钟的个体，以及每晚睡眠<6小时、睡眠质量差且有中度至重度睡眠障碍的个体，经历重度SI的风险增加。性格较为慵懒的个体往往表现出更严重的SI，而报告灵活性更高的个体经历的SI较少。本研究是首次使用潜在类别分析来检验主观SI特征，并在普通人群中识别出四种SI特征。这一成果可能有助于更深入地理解SI，包括开发筛查工具和减少SI的干预措施。
