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Article Abstract

Purpose: Previous epidemiological and psychological studies have assessed the effects of napping on individual performance and health. However, these studies did not distinguish between spontaneous and passive napping due to sleep disorders. Therefore, this study aimed to explore the potential motivation for napping among Chinese college students and to assess the relationship between different nap motivations and sleep.

Patients And Methods: This cross-sectional study was conducted at a university in Shanghai in March 2021 using convenience sampling. A total of 564 Chinese college students with self-reported napping habits participated in this study. Exploratory factor analysis (EFA) was employed to analyze 34 self-rated motivations for napping to derive a potential structural model of napping motivation. Correlation and multiple linear regression analyses were performed to determine the influence of nap motivation on sleep behavior.

Results: Chinese college students mainly take naps to reduce fatigue, usually in the form of frequent and long naps (6.25 ± 1.24 days; 64.62 ± 23.70 min). A structural model of nap motivation named the I-DREAM model was proposed, consisting of six factors: restorative, induced, mindful, appetitive, dysregulative, and exercise naps. There were also sex differences in nap motivation, as women preferred restorative naps and appetitive naps, while men preferred exercise naps ( < 0.01, < 0.05). Furthermore, there was a significant correlation between nap motivation on nap duration, frequency and nighttime sleep quality ( = 2.70-18.9%).

Conclusion: The proposed I-DREAM model implies that there are population differences in napping motivation. Different motivations also have different relationships with napping patterns and nighttime sleep. In understanding the relationship between naps and health status, nap motivation may be an extremely important influencing factor.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9075905PMC
http://dx.doi.org/10.2147/NSS.S349013DOI Listing

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