Exploring Sleep Duration and Insomnia Among Prospective University Students: A Study with Geographical Data and Machine Learning Techniques.

Firoj Al-Mamun Mohammed A Mamun Md Emran Hasan Moneerah Mohammad ALmerab David Gozal

Published in: Nature and science of sleep (2024)

Sleep disturbances are prevalent among prospective university students and are associated with various factors including gender, test-taking status, mock test satisfaction, and anxiety. Targeted interventions, including sleep education and psychological support, hold promise in ameliorating sleep health and overall well-being among students, potentially enhancing entrance test performance.

Keyphrases

sleep quality
physical activity
machine learning
healthcare
big data
depressive symptoms
mental health
public health
artificial intelligence
electronic health record
health information
cancer therapy
risk assessment
drug delivery
social media
climate change
data analysis
human health