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Updated: Jan 12, 2026

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World
Published on: April 7, 2020
From well-rested to wrecked: identifying college sleep patterns with latent profile analysis
1State University of New York (SUNY), Brockport, USA.
Objective:
This study sought to classify the myriad profiles that might exist of undergraduate sleepers by examining diverse sleep and sleep-related indicators.
Methods:
A total of 642 undergraduates (77.3% female; Mage=21.3 years; SD = 2.4) completed measures of sleep disturbance and sleep-related behaviors, in addition to critical sleep correlates (e.g., problematic smartphone use, chronotype) during the Spring 2023 semester.
Results:
Based on latent profile analysis of 19 indicator variables, five unique profiles of undergraduate sleepers were identified: 1) "great" (i.e., high sleep self-efficacy, low sleep disturbance; 22.6%), 2) "average" (34.7%), 3) "poor" (i.e., poor sleep hygiene, high sleep disturbance; 20.1%), 4) "poor, but conscientious" (i.e., moderate sleep hygiene, multiple barriers to quality sleep; 19.2%), and 5) "high-risk behavior" (i.e., poor sleep quality/hygiene, notable substance use; 3.4%).
Conclusions:
This study identifies critical differences amongst types of undergraduate sleepers. These efforts may support more targeted interventions to support their sleep and functioning.
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