Relationship between personality and sleep: a dual validation study combining empirical and big data-driven approaches

Objective Sleep is a vital component of individual health, and personality traits are key factors influencing it. This study aims to investigate the relationship between personality traits and both modelassessed sleep problems and self-reported sleep quality. Methods Using deep semantic understanding technology, we developed three deep learning models based on microblogs. Model 1 and Model 2 identified whether a post indicated a sleep problem, while Model 3 assessed the user’s personality traits based on the Five-Factor Model (FFM). We surveyed a dataset comprising 336 active users and then applied the models to a large-scale microblog dataset containing 4,860,000 posts from 15,251 users. Results Our experimental results revealed that: (1) conscientiousness, agreeableness, and extraversion are associated with better sleep quality, while neuroticism is linked to poorer sleep quality; (2) the relationships between sleep problems and personality traits remained consistent when the model, trained on a small survey dataset with expert annotations, was applied to the large-scale dataset. Conclusions These findings highlight the potential of using deep learning models to analyze the complex relationship between personality traits and sleep, offering valuable insights for future research and interventions.