Journal of Education and Health Promotion

Factor structure and psychometric properties of the Persian versions of the Pediatric Daytime Sleepiness Scale and Morningness–Eveningness Scale for Children

Document Type : Original Article

Authors

. Ali Nouri 1
. Fattaneh Esmaeili 2
. Heliya Seyedi 2
. Sahba Rezaeian 3
. Sareh Panjeh 4
. Hugo Cogo‑Moreira 5
. Sabine Pompeia 6

1 Department of Educational Sciences, Malayer University, Malayer, Iran, 2 M.A. in Mind, Brain and Education Science, Independent Researcher, Tehran, Iran

2 M.A. in Mind, Brain and Education Science, Independent Researcher, Tehran, Iran

3 Ph.D. in Higher Education Management, Independent Researcher, Tehran, Iran

4 Deparment of Psychiatry, Universidade Federal de São Paulo, São Paulo, SP, Brazil

5 Deparment of Psychiatry, Universidade Federal de São Paulo, São Paulo, SP, Brazil, 5 School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam School of Public Health, University of Hong Kong, Hong Kong, China

6 Deparment of Psychobiology, Universidade Federal de São Paulo, São Paulo, SP, Brazi

Abstract
BACKGROUND: The Pediatric Daytime Sleepiness Scale (PDSS) and the Morningness–Eveningness
Scale for Children (MESC) are widely used to measure two important facets of sleep patterns, but
neither have been adapted and validated for use in Iran. The purpose of this study was to examine
the psychometric properties and factor structure of the Persian versions of the PDSS and the MESC
in a sample of Iranian adolescents.
MATERIALS AND METHODS: The Persian versions of PDSS and MESC were translated and
administered to a representative sample (n = 407) of Iranian early adolescents, aged 9–15 years,
who attended school in morning shifts. The factor structure of both scales, found in prior studies,
was tested using Confirmatory Factor Analyses to assess their validity and reliability.
RESULTS: The results revealed that the model fit indices of the one factor solution of the PDSS
and the two factor solution of the MESC were acceptable to good. A high Pearson correlation was
found between raw and latent factor scores for the PDSS and the two factors derived from the
MESC (i.e., Morningness and Planning). Furthermore, the higher the PDSS score (more daytime
sleepiness), the lower the MESC scores (more eveningness), indicating criterion validity of the scales
showing the expected increase in daytime sleepiness in evening oriented adolescents who wake
up early for attending school.
CONCLUSION: The Persian versions of the PDSS and the MESC can be considered reliable and
valid tools for evaluating, respectively, daytime sleepiness and morningness‑eveningness in the
adolescent population of Iran.

Keywords

Adolescence
circadian preference
confirmatory factor analyses
daytime sleepiness
factorial structure
psychometric properties
sleep measures
  1. Spear LP. The adolescent brain and age‑related behavioral
    manifestations. Neurosci Biobehav Rev 2000; 24:417‑63.
    2. Crowley SJ, Wolfson AR, Tarokh L, Carskadon MA. An update
    on adolescent sleep: New evidence informing the perfect storm
    model. J Adolesc 2018;67:55‑65.
    3. Kelley P, Lockley SW, Foster RG, Kelley J. Synchronizing
    education to adolescent biology: ‘Let teens sleep, start school
    later’. Learn Media Technol 2015;40:210‑26.
    4. Sigman M, Peña M, Goldin AP, Ribeiro S. Neuroscience and
    education: Prime time to build the bridge. Nat Neurosci
    2014;17:497‑502.
    5. Akbaraly TN, JaussentI, BessetA, BertrandM, Barberger‑GateauP,
    Ritchie K, et al. Sleep complaints and metabolic syndrome in an
    elderly population: The three‑city study. Am J Geriatr Psychiatry
    2015;23:818‑28.
    6. Ohayon MM, Vecchierini MF. Daytime sleepiness and cognitive
    impairment in the elderly population. Arch Intern Med
    2002;162:201‑8.
    7. Drake C, Nickel C, Burduvali E, Roth T, Jefferson C, Pietro B.
    The pediatric daytime sleepiness scale (PDSS): Sleep habits and
    school outcomes in middle‑school children. Sleep 2003;26:455‑8.
    8. Kim SY, Sim S, Kim SG, Choi HG. Sleep deprivation is associated
    with bicycle accidents and slip and fall injuries in Korean
    adolescents. PLoS One 2015;10:e0135753.
    9. Owens J. Adolescent Sleep Working Group ASW, Committee
    on Adolescence CO. Insufficient sleep in adolescents and young
    adults: An update on causes and consequences. Pediatrics
    2014;134:e921‑32.
    10. Carskadon MA, Vieira C, Acebo C. Association between puberty
    and delayed phase preference. Sleep 1993;16:258‑62.
    11. Giannotti F, Cortesi F, Sebastiani T, Ottaviano S. Circadian
    preference, sleep and daytime behaviour in adolescence. J Sleep
    Res 2002;11:191‑9.
    12. Díaz‑Morales JF. Morningness–eveningness scale for
    children (MESC): Spanish normative data and factorial invariance
    according to sex and age. Pers Individ Dif 2015;87:116‑20.
    13. Schmidt C, Collette F, Cajochen C, Peigneux P. A time to think:
    Circadian rhythms in human cognition. Cogn Neuropsychol
    2007;24:755‑89.
    14. Dolsen MR, Wyatt JK, Harvey AG. Sleep, circadian rhythms,
    and risk across health domains in adolescents with an evening
    circadian preference. J Clin Child Adolesc Psychol 2019;48:480‑90.
    15. Shahid A, Wilkinson K, Marcu S, Shapiro CM, editors. STOP,
    THAT and one hundred other sleep scales. New York: Springer
    Science & Business Media; 2012.
    16. Rhie S, Lee S, Chae KY. Sleep patterns and school performance
    of Korean adolescents assessed using a Korean version of the
    pediatric daytime sleepiness scale. Korean J Pediatr 2011;54:29‑35.
    17. Felden ÉP, Carniel JD, Andrade RD, Pelegrini A, Anacleto TS,
    Louzada FM. Translation and validation of the pediatric daytime
    sleepiness scale (PDSS) into Brazilian Portuguese. J Pediatr
    2016;92:168‑73.
    18. McNeish D. Thanks coefficient alpha, we’ll take it from here.
    Psychol Methods 2018;23:412‑33.
    19. Bektas M, Bektas I, Ayar D, Selekoglu Y, Ayar U, Kudubes AA,
    et al. Psychometric properties of Turkish version of pediatric
    daytime sleepiness scale (PDSS‑T). Asian Nurs Res (Korean Soc
    Nurs Sci) 2016;10:62‑7.
    20. Ferrari Junior GJ, Drake CL, Barbosa DG, Diego Andrade R,
    Santos Silva DA, Érico Pereira GF. Factor structure of the Brazilian
    version of pediatric daytime sleepiness scale. Chronobiol Int
    2018;35:1088‑94.
    21. Randler C, Kolomeichuk SN, Morozov AV, Petrashova DA,
    Pozharskaya VV, Martynova AA, et al. Psychometric properties
    of the Russian version of the pediatric daytime sleepiness
    scale (PDSS). Heliyon 2019;5:e02134.
    22. Smith CS, Reilly C, Midkiff K. Evaluation of three circadian
    rhythm questionnaires with suggestions for an improved measure
    of morningness. J Appl Psychol 1989;74:728‑38.
    23. Díaz‐Morales JF, de Leon MC, Sorroche MG. Validity of the
    morningness‐eveningness scale for children among Spanish
    adolescents. Chronobiol Int 2007;24:435‑47.
    24. Finimundi M, Barin I, Bandeira D, Souza DO. Validity of a
    circadian rhythm scale ‑ sleep/wake cycle for adolescents. Rev
    Paul Pediatr 2012;30:409‑14.
    25. Gau SF, Soong WT. The transition of sleep‑wake patterns in early
    adolescence. Sleep 2003;26:449‑54.
    26. Kim S, Dueker GL, Hasher L, Goldstein D. Children’s time of
    day preference: Age, gender and ethnic differences. Pers Individ
    Differ 2002;33:1083‑90.
  2. 27. Önder İ, Beşoluk Ş. Adaptation of the morningness eveningness
    scale for children into Turkish. Biol Rhythm Res 2013;44:313‑23.
    28. Tonetti L, Adan A, Di Milia L, Randler C, Natale V. Measures of
    circadian preference in childhood and adolescence: A review. Eur
    Psychiatry 2015;30:576‑82.
    29. Díaz‑Morales JF. Morningness‑eveningness in adolescents.
    Spanish J Psychol 2008;11:201‑6.
    30. Caci H, Robert P, Dossios C, Boyer P. Morningness–Eveningness
    for Children Scale: Psychometric properties and month of
    birth effect. Encephale. 2005b; 31:56–64. [Article in French]
    DOI: 10.1016/s0013‑7006(05)82372‑3.
    31. Bandalos DL. Measurement theory and applications for the social
    sciences. New York: Guilford Publications; 2018.
    32. Brown TA. Confirmatory Factor Analysis for Applied Research.
    New York: Guilford Publications; 2015.
    33. Li CH. Confirmatory factor analysis with ordinal data: Comparing
    robust maximum likelihood and diagonally weighted least
    squares. Behav Res Methods 2016;48:936‑49.
    34. Schermelleh‑Engel K, Moosbrugger H, Müller H. Evaluating
    the fit of structural equation models: Tests of significance and
    descriptive goodness‑of‑fit measures. Methods Psychol Res
    Online 2003;8:23‑74.
    35. Schreiber JB, Nora A, Stage FK, Barlow EA, King J. Reporting
    structural equation modeling and confirmatory factor analysis
    results: A review. J Educ Res 2006;99:323‑38.
    36. Tanaka JS. “How big is big enough?” Sample size and goodness
    of fit in structural equation models with latent variables. Child
    Dev 1987;1:134‑46.
    37. DeVellis RF. Scale Development: Theory and Applications.
    Thousand Oaks: Sage Publications; 2016.
    38. Carskadon MA. Sleep in adolescents: The perfect storm. Pediatr
    Clin North Am 2011;58:637‑47. 
Journal of Education and Health Promotion
Volume 11, Issue 8
September 2021
Pages 1-9

Home

Guide for Authors

Submit Manuscript

Reviewers

Contact Us