Morningness–eveningness preferences in Portuguese adolescents: Adaptation and psychometric validity of the H&amp;O questionnaire

Rodrigues, Pedro; Pandeirada, Josefa N. S.; Marinho, Patrícia I.; Bem-Haja, Pedro; Silva, Carlos Fernandes da; Ribeiro, Lígia Maria; Fernandes, Natália Lisandra

doi:10.1016/j.paid.2015.08.048

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…Psychometric studies of particular interest are those that developed normative values or clinical/community cutoff scores for widespread usage, of which there were overall 18. Norms have been developed for CAS-15 (17), ESS (51, 52), JSQ (58,59), SDSC (120,121), CSHQ and CRSP (25,34), CSRQ (47), MEQ (64,65), NARQoL-21 (70), OSPQ (83), PSQ (108), SNAKE (129), Comic (138), and YSIS (140) (refer to Table 2).…”

Section: Tools With Norm Scoresmentioning

confidence: 99%

Pediatric Sleep Tools: An Updated Literature Review

Sen

Spruyt

2020

Front. Psychiatry

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Since a thorough review in 2011 by Spruyt, into the integral pitfalls of pediatric questionnaires in sleep, sleep researchers worldwide have further evaluated many existing tools. This systematic review aims to comprehensively evaluate and summarize the tools currently in circulation and provide recommendations for potential evolving avenues of pediatric sleep interest. 144 "tool"-studies (70 tools) have been published aiming at investigating sleep in primarily 6-18 years old per parental report. Although 27 new tools were discovered, most of the studies translated or evaluated the psychometric properties of existing tools. Some form of normative values has been established in 18 studies. More than half of the tools queried general sleep problems. Extra efforts in tool development are still needed for tools that assess children outside the 6-to-12-year-old age range, as well as for tools examining sleep-related aspects beyond sleep problems/disorders. Especially assessing the validity of tools has been pursued vis-à-vis fulfillment of psychometric criteria. While the Spruyt et al. review provided a rigorous step-by-step guide into the development and validation of such tools, a pattern of steps continue to be overlooked. As these instruments are potentially valuable in assisting in the development of a clinical diagnosis into pediatric sleep pathologies, it is required that while they are primary subjective measures, they behave as objective measures. More tools for specific populations (e.g., in terms of ages, developmental disabilities, and sleep pathologies) are still needed.

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Section: Tools With Norm Scoresmentioning

confidence: 99%

Pediatric Sleep Tools: An Updated Literature Review

Sen

Spruyt

2020

Front. Psychiatry

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“…Other questionnaires like the Morningness–Eveningness Questionnaire (MEQ) 9 , that looks into the sleep/wake time preferences of the individuals instead of their actual sleep/wake timings have also been used in this context. These survey studies have been used worldwide and in different populations to study the changes in sleep-wake behaviour across age groups (adolescents, adults, and others) 5 , 17 , as well as in different social and psychological settings 18 . Individuals are found to be of early chronotypes in adolescent stages of their lives and gradually changing to late chronotypes through their teenage years reaching a maximum around 20 years of age.…”

Section: Introductionmentioning

confidence: 99%

Morningness–eveningness assessment from mobile phone communication analysis

Roy

Monsivais

Bhattacharya

et al. 2021

Sci Rep

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Human behaviour follows a 24-h rhythm and is known to be governed by the individual chronotypes. Due to the widespread use of technology in our daily lives, it is possible to record the activities of individuals through their different digital traces. In the present study we utilise a large mobile phone communication dataset containing time stamps of calls and text messages to study the circadian rhythms of anonymous users in a European country. After removing the effect of the synchronization of East-West sun progression with the calling activity, we used two closely related approaches to heuristically compute the chronotypes of the individuals in the dataset, to identify them as morning persons or “larks” and evening persons or “owls”. Using the computed chronotypes we showed how the chronotype is largely dependent on age with younger cohorts being more likely to be owls than older cohorts. Moreover, our analysis showed how on average females have distinctly different chronotypes from males. Younger females are more larkish than males while older females are more owlish. Finally, we also studied the period of low calling activity for each of the users which is considered as a marker of their sleep period during the night. We found that while “extreme larks” tend to sleep more than “extreme owls” on the weekends, we do not observe much variation between them on weekdays. In addition, we have observed that women tend to sleep even less than males on weekdays while there is not much difference between them on the weekends.

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