Profiles of Subjective Daytime Sleepiness through Cluster Analysis
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Sleepiness propensity and sleepiness perception are two relevant dimensions of the general multidimensional sleepiness construct. In the current study, the aim was to identify eventual homogeneous subgroups when sleepiness propensity and sleepiness perception measures are combined. Data from 678 undergraduate students (aged 17 to 24 years) from a medical school were analyzed. A Two-Step Cluster Analysis was performed taken into consideration sleepiness propensity and sleepiness perception measures as clustering variables. Four different clusters were identified. Additionally, the two groups comprising higher levels of sleepiness perception (i.e., “high perception, low propensity” and “high subjective daytime sleepiness” clusters) had the most compromised results in some of the sleep-related variables examined – sleep needs, sleep latency, sleep quality, sleep sufficiency, self-reported insomnia, sleep reactivity to stress, and cognitive arousal – and in some of non-sleep related variables, such as neuroticism and affect. As to non-sleep variables, those groups reported higher scores in neuroticism, arousability, self-reported mental health and affective states. The identification of distinct groups concerning self-reported sleepiness may bring new avenues for research and understanding of the specific and differential role of sleepiness and its dimensions in sleep health and sleep disturbances, in particular, insomnia disorder.
KeywordsSleepiness Epworth sleepiness scale (ESS) Daytime sleepiness perception scale (DSPS-4) Clusters Profiles
We are grateful to professors and students who participated in this study.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
This article does not contain any studies with animals performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
- 6.Johns M. What is excessive daytime sleepiness? In: Fulke P, Vaughan S, editors. Sleep deprivation: causes, effects and treatment. New York: Nova Science Publishers, Inc.; 2009. p. 59–94.Google Scholar
- 11.Rosmaninho, J., Lopes, M., Quintal, J., Soares, M. J., Maia, B., Marques, M., ... Azevedo, M. H. (2010). Daytime sleepiness in medical students. Journal of Sleep Research, 19(supp. 2), e178. https://doi.org/10.1111/j.1365-2869.2010.00868.x
- 15.Eysenck, H. J., & Eysenck, S. G. (1964). Manual of the Eysenck Personality Inventory. London, UK: University of London Press.Google Scholar
- 17.Marques D, Gomes A, Drake C, Roth T, Azevedo MH. Assessing stress-induced sleep reactivity in college students: the European Portuguese version of the ford insomnia response to stress test (FIRST). Behav Sleep Med. 2018a;16(4):337–46. https://doi.org/10.1080/15402002.2016.1210151.CrossRefPubMedGoogle Scholar
- 23.Silva, C. F., Azevedo, M. H., & Dias, M. R. (1994). Estudo padronizado do trabalho por turnos. Versão Experimental. Instituto de Psicologia Médica da Faculdade de Medicina, Universidade de Coimbra.Google Scholar
- 27.McNair DM, Lorr M, Droppleman LF. Edits manual for the profile of mood states. San Diego: Educational and Industrial Testing Service; 1971.Google Scholar
- 28.Azevedo MH, Silva C, Dias M. O "perfil dos estados de humor": Adaptação à população portuguesa. Psiquiatria Clínica. 1991;12:187–93.Google Scholar
- 29.Mooi E, Sarstedt M. A concise guide to market research: the process, data, and methods using IBM SPSS statistics. 2nd ed. Berlin: Springer; 2014.Google Scholar
- 33.Cohen J. Statistical power analysis for the behavioral sciences. New York, NY: Routledge Academic; 1988.Google Scholar
- 35.Marques, D., Gomes, A., Drake, C., Roth, T., Morin, C., & Azevedo, M. H. (2017). Typologies of individuals vulnerable to insomnia: A two-step cluster analysis. Manuscript submitted for publication.Google Scholar
- 41.Kyle S, Miller C, Rogers Z, Siriwardena A, MacMahon K, Espie C. Sleep restriction therapy for insomnia is associated with reduced objective total sleep time, increased daytime somnolence, and objectively impaired vigilance: implications for the clinical management of insomnia disorder. Sleep. 2014;37(2):229–37. https://doi.org/10.5665/sleep.3386.CrossRefPubMedPubMedCentralGoogle Scholar
- 42.Field A. Discovering statistics using IBM SPSS statistics. 4th ed. London: Sage Publications; 2013.Google Scholar