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From well-rested to wrecked: identifying college sleep patterns with latent profile analysis.

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Title: From well-rested to wrecked: identifying college sleep patterns with latent profile analysis.
Authors: Peltz, Jack S. (AUTHOR), Rogge, Ronald (AUTHOR)
Source: Journal of American College Health. May2026, Vol. 74 Issue 5, p1391-1402. 12p.
Subjects: Mental depression risk factors, Psychological resilience, Risk assessment, Cross-sectional method, Substance abuse, Health attitudes, Health status indicators, Smartphones, Compulsive behavior, Chronotype, Self-efficacy, Risk-taking behavior, Undergraduates, Mindfulness, Multiple regression analysis, Questionnaires, Psychological adaptation, Structural equation modeling, Descriptive statistics, Chi-squared test, Severity of illness index, Health surveys, Sleep, Health behavior, Analysis of variance, Sociodemographic factors, Student attitudes, Interpersonal relations, Sleep quality, Alcohol drinking in college, Comparative studies, Data analysis software, Psychological tests, Sleep disorders, Sleep hygiene, Disease risk factors
Abstract: 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. [ABSTRACT FROM AUTHOR]
Copyright of Journal of American College Health is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: From well-rested to wrecked: identifying college sleep patterns with latent profile analysis.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+American+College+Health%22">Journal of American College Health</searchLink>. May2026, Vol. 74 Issue 5, p1391-1402. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Mental+depression+risk+factors%22">Mental depression risk factors</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+resilience%22">Psychological resilience</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Cross-sectional+method%22">Cross-sectional method</searchLink><br /><searchLink fieldCode="DE" term="%22Substance+abuse%22">Substance abuse</searchLink><br /><searchLink fieldCode="DE" term="%22Health+attitudes%22">Health attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Health+status+indicators%22">Health status indicators</searchLink><br /><searchLink fieldCode="DE" term="%22Smartphones%22">Smartphones</searchLink><br /><searchLink fieldCode="DE" term="%22Compulsive+behavior%22">Compulsive behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Chronotype%22">Chronotype</searchLink><br /><searchLink fieldCode="DE" term="%22Self-efficacy%22">Self-efficacy</searchLink><br /><searchLink fieldCode="DE" term="%22Risk-taking+behavior%22">Risk-taking behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduates%22">Undergraduates</searchLink><br /><searchLink fieldCode="DE" term="%22Mindfulness%22">Mindfulness</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+regression+analysis%22">Multiple regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Questionnaires%22">Questionnaires</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+adaptation%22">Psychological adaptation</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+equation+modeling%22">Structural equation modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Chi-squared+test%22">Chi-squared test</searchLink><br /><searchLink fieldCode="DE" term="%22Severity+of+illness+index%22">Severity of illness index</searchLink><br /><searchLink fieldCode="DE" term="%22Health+surveys%22">Health surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Sleep%22">Sleep</searchLink><br /><searchLink fieldCode="DE" term="%22Health+behavior%22">Health behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Analysis+of+variance%22">Analysis of variance</searchLink><br /><searchLink fieldCode="DE" term="%22Sociodemographic+factors%22">Sociodemographic factors</searchLink><br /><searchLink fieldCode="DE" term="%22Student+attitudes%22">Student attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Interpersonal+relations%22">Interpersonal relations</searchLink><br /><searchLink fieldCode="DE" term="%22Sleep+quality%22">Sleep quality</searchLink><br /><searchLink fieldCode="DE" term="%22Alcohol+drinking+in+college%22">Alcohol drinking in college</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+studies%22">Comparative studies</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+tests%22">Psychological tests</searchLink><br /><searchLink fieldCode="DE" term="%22Sleep+disorders%22">Sleep disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Sleep+hygiene%22">Sleep hygiene</searchLink><br /><searchLink fieldCode="DE" term="%22Disease+risk+factors%22">Disease risk factors</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of American College Health is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=194393957
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/07448481.2025.2577656
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 1391
    Subjects:
      – SubjectFull: Mental depression risk factors
        Type: general
      – SubjectFull: Psychological resilience
        Type: general
      – SubjectFull: Risk assessment
        Type: general
      – SubjectFull: Cross-sectional method
        Type: general
      – SubjectFull: Substance abuse
        Type: general
      – SubjectFull: Health attitudes
        Type: general
      – SubjectFull: Health status indicators
        Type: general
      – SubjectFull: Smartphones
        Type: general
      – SubjectFull: Compulsive behavior
        Type: general
      – SubjectFull: Chronotype
        Type: general
      – SubjectFull: Self-efficacy
        Type: general
      – SubjectFull: Risk-taking behavior
        Type: general
      – SubjectFull: Undergraduates
        Type: general
      – SubjectFull: Mindfulness
        Type: general
      – SubjectFull: Multiple regression analysis
        Type: general
      – SubjectFull: Questionnaires
        Type: general
      – SubjectFull: Psychological adaptation
        Type: general
      – SubjectFull: Structural equation modeling
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Chi-squared test
        Type: general
      – SubjectFull: Severity of illness index
        Type: general
      – SubjectFull: Health surveys
        Type: general
      – SubjectFull: Sleep
        Type: general
      – SubjectFull: Health behavior
        Type: general
      – SubjectFull: Analysis of variance
        Type: general
      – SubjectFull: Sociodemographic factors
        Type: general
      – SubjectFull: Student attitudes
        Type: general
      – SubjectFull: Interpersonal relations
        Type: general
      – SubjectFull: Sleep quality
        Type: general
      – SubjectFull: Alcohol drinking in college
        Type: general
      – SubjectFull: Comparative studies
        Type: general
      – SubjectFull: Data analysis software
        Type: general
      – SubjectFull: Psychological tests
        Type: general
      – SubjectFull: Sleep disorders
        Type: general
      – SubjectFull: Sleep hygiene
        Type: general
      – SubjectFull: Disease risk factors
        Type: general
    Titles:
      – TitleFull: From well-rested to wrecked: identifying college sleep patterns with latent profile analysis.
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            NameFull: Peltz, Jack S.
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            NameFull: Rogge, Ronald
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            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 74
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            – TitleFull: Journal of American College Health
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