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P37 Behavioural factors of poor sleep in a University student population
  1. Alice Morley1,
  2. Poh Wang1,
  3. Suleyman Noordeen1,
  4. Civia Chen1,
  5. Charles Oulton1,
  6. Yizhou Yu1,
  7. Humairaa Duad3,
  8. Samia Zarin3,
  9. Ellen Ndoro3,
  10. Umaymah Mansoor3,
  11. George Browne3,
  12. Ben Bowers3,
  13. Gabriela Sloma3,
  14. Ben Cusack3,
  15. Anah Karim3,
  16. Brioni Chin Yu Leung4,
  17. Shin Chen4,
  18. Yihan Yue4 and
  19. Wantang Yang4
  1. 1International Sleep Charity, Southampton, UK
  2. 2School of Public Health, Faculty of Medicine, Imperial College London, London, UK
  3. 3University of Leicester Psychology Department, Leicester, UK
  4. 4University of Cambridge Psychology Department, Cambridge, UK
  5. 5Department of Medicine, Cambridge University, Cambridge, UK

Abstract

Introduction Sleep disturbance among students has become a growing concern because of its adverse effects on cognitive function, mental health, and quality of life. Previous research showed that University students report significantly poorer sleep hygiene compared to the general population (Hershner, 2020).1 However, the sleep hygiene and quality of UK university students remain unclear. Here, we explore the specific behavioural factors associated with poor sleep among University students in the UK.

Methods A cross-sectional survey design was employed to collect data from university students, including questions regarding sleep patterns, sleep quality, and sleep hygiene. Participants were recruited through University societies, and data were analyzed using descriptive statistics, unsupervised machine learning and regression analysis.

Results Our data included 892 students, (71.4% female, 24.3% male and 4.3% other), mainly from the Universities of Leicester (68.5%) and Cambridge (12.9%). Most students (60.4%), aged between 18 and 21 years old, slept for an average of 8.08 (s.d. = 2.1) hours and reported a tiredness score of 6.24 (s.d. = 1.71). We found that the sleep hygiene index was significantly correlated with self-reported tiredness (𝛽 =0.09, s.e. = 0.02, P < 0.0001), while accounting for covariates. We then used unsupervised learning to identify the main features of sleep hygiene linked to poor sleep, and found that irregular sleep patterns were the main features of poor sleep. The second most important component of poor sleep hygiene in this cohort was linked to stress.

Discussion Our results highlight the importance of providing guidance on regular sleep schedules and stress related interventions for students. We are currently evaluating the effectiveness of interventions targeting these behavioural factors to improve sleep outcomes in the student population.

Reference

  1. Hershner S. Sleep and academic performance: Measuring the impact of sleep. Current Opinion in Behavioral Sciences, 2020;33:51–56.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

http://dx.doi.org/10.1136/bmjresp-2023-BSSconf.48

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