Evidence map›Paper›PMID 40747256›Full record

ArticleFrontiers in psychiatry2025

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

Lei Cao, Jiake Wu, Mengyao Wang, Liang Zhao, Xin Wang, Bowen Yao, Qi Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Lei CaoBeijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing, China.
Jiake WuBeijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing, China.
Mengyao WangBeijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing, China.
Liang ZhaoSchool of Information Management, Key Laboratory of Semantic, Publishing and Knowledge Service of the National Press and Publication Administration, Wuhan University, Wuhan, China.
Xin WangThe Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom.
Bowen YaoSchool of Economics and Management, Beijing Jiaotong University, Beijing, China.
Qi LiBeijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

microblogneural networkpersonalitysemantic understandingsleep

Identifiers

PMID40747256
PMCPMC12310568

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.