Factors associated with excessive daytime sleepiness in medical students of a higher education institution of Bucaramanga

García, Jorge Andrés Niño; Vergel, María Fernanda Barragán; Labrador, Jorge Andrés Ortiz; Vera, Miguel Enrique Ochoa; Olaya, Hilda Leonor González

doi:10.1016/j.rcpeng.2017.12.012

Cited by 3 publications

(8 citation statements)

References 23 publications

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“…For sleep‐related characteristics, a higher probability of EDS was found among students with poor sleep quality, corroborating other studies carried out with university students (Nino Garcia et al, 2019). However, the effect measures verified in the present study were smaller than the other studies, which may have been related to a greater number of potential confounding factors in their multivariate analyses.…”

Section: Discussionsupporting

confidence: 89%

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Prevalence and factors associated with excessive and severe daytime sleepiness among healthcare university students in the Brazilian Midwest

Silva

Garcez

Pattussi

et al. 2021

Journal of Sleep Research

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Summary The present study aimed to determine the prevalence of, and factors associated with excessive and severe daytime sleepiness in healthcare university students. A cross‐sectional university‐based study was conducted with 1,779 students from a university located in the Brazilian Midwest State of Goiás, Brazil, in 2018. Daytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS) and classified as excessive daytime sleepiness (EDS; cut‐off ESS score ≥10) and severe EDS (S‐EDS; cut‐off ESS score ≥16). Associated factors included sociodemographic, behavioural, academic, nutritional status, and sleep‐related and perceived health characteristics. Poisson regression was used for the data analysis. The mean (SD) age of the sample was 22.5 (3.84) years. The prevalence of EDS was 54.4% (95% confidence interval [CI] 51.9–56.1) and S‐EDS was 10.0% (95% CI 9.2–11.7). After adjustment, a higher probability of occurrence of EDS was found among women (prevalence ratio [PR] 1.37, 95% CI 1.24–1.53), younger students (PR 1.23, 95% CI 1.07–1.42), those who were studying medicine (PR 1.14, 95% CI 1.02–1.28), with poor sleep quality (PR 1.29, 95% CI 1.17–1.43), and among those who reported constant loss of sleep due to internet use (PR 1.14, 95% CI 1.02–1.27). After adjustment, the highest probability of occurrence of S‐EDS was found among women (PR 1.72, 95% CI 1.22–2.43), among those with poor sleep quality (PR 2.17, 95% CI 1.54–3.08), and medical students (PR 1.39, 95% CI 1.01–1.90). In conclusion, there was a high prevalence of daytime sleepiness among healthcare university students, especially among medical students and women.

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Section: Discussionsupporting

confidence: 89%

“…It is noteworthy that no previous studies identified associations of S‐EDS with other variables in university students. In some studies, as already mentioned, only the prevalence values were presented (Gaultney, 2010; Nino Garcia et al, 2019; Pagnin et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Prevalence and factors associated with excessive and severe daytime sleepiness among healthcare university students in the Brazilian Midwest

Silva

Garcez

Pattussi

et al. 2021

Journal of Sleep Research

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“…Sleep is an excellent indicator of the health status and an element that favors good quality of life [ 20 ], but entering university is a change that highly impacts the student in every dimension, including sleep habits [ 21 , 22 ]. A potential barrier for maximizing performance during the university stage is the irregular sleep schedule, which lead to sleep deficit and high prevalence of somnolence during the day [ 23 ]. A review by Shochat et al (2014) [ 24 ] examined the consequences of lack of sleep among Nursing students, and confirmed the relationship between sleep disorders and changes in sleep patterns with a reduced academic performance.…”

Section: Discussionmentioning

confidence: 99%

“…We observed that most of the university students with evening chronotypes were aged < 25, had bad sleep habits, and a poor academic performance. Physiologically, adolescents and adults tend to have delayed circadian preferences and are “lovers of the night” [ 23 ]. In our study, 20.2 % of students had an evening chronotype, which is lower than that reported in other studies, where 59 % of the students between 18 and 29 years of age described themselves as night owls [ 32 ].…”

Section: Discussionmentioning

confidence: 99%

“…The results of this study evidence the need to seriously take into consideration the sleep deficits that are associated with inadequate sleep habits, with the aim of developing preventative and educational initiatives to improve the sleep habits of the university population. The challenge ahead starts with the social awareness of the importance of having good-quality sleep since many times, adequate knowledge about sleep does not translate into a change of sleep habits [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

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Relationship between sleep habits and academic performance in university Nursing students

Gallego‐Gómez

González-Moro

et al. 2021

BMC Nurs

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Background Sleep disorders are composed of a group of diseases of increasing prevalence and with social-health implications to be considered a public health problem. Sleep habits and specific sleep behaviors have an influence on the academic success of students. However, the characteristics of sleep and sleep habits of university students as predictors of poor academic performance have been scarcely analyzed. In the present study, we aimed to investigate sleep habits and their influence on academic performance in a cohort of Nursing Degree students. Methods This was a cross-sectional and observational study. An anonymous and self-administered questionnaire was used, including different scales such as the ‘Morningness and Eveningness scale’, an author-generated sleep habit questionnaire, and certain variables aimed at studying the socio-familial and academic aspects of the Nursing students. The association of sleep habits and other variables with poor academic performance was investigated by logistic regression. The internal consistency and homogeneity of the ‘sleep habits questionnaire’ was assessed with the Cronbach’s alpha test. Results Overall, 401 students (mean age of 22.1 ± 4.9 years, 74.8 % females) from the Nursing Degree were included. The homogeneity of the ‘sleep habits questionnaire’ was appropriate (Cronbach’s alpha = 0.710). Nursing students were characterized by an evening chronotype (20.2 %) and a short sleep pattern. 30.4 % of the Nursing students had bad sleep habits. Regarding the academic performance, 47.9 % of the students showed a poor one. On multivariate logistic regression analysis, a short sleep pattern (adjusted OR = 1.53, 95 % CI 1.01–2.34), bad sleep habits (aOR = 1.76, 95 % CI 1.11–2.79), and age < 25 years (aOR = 2.27, 95 % CI 1.30–3.98) were independently associated with a higher probability of poor academic performance. Conclusions Almost 1/3 of the Nursing students were identified as having bad sleep habits, and these students were characterized by an evening chronotype and a short sleep pattern. A short sleep pattern, bad sleep habits, and age < 25 years, were independently associated with a higher risk of poor academic performance. This requires multifactorial approaches and the involvement of all the associated actors: teachers, academic institutions, health institutions, and the people in charge in university residences, among others.

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Latent profile analysis for health-related quality of life, sleep quality, morning and evening type, and internet addiction among medical students

Ling

Guo

et al. 2023

Sci Rep

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Health-related quality of life, sleep quality, morning and evening types, and internet addiction are of significant importance to the development of medical students, yet they have rarely been studied. Taking this into consideration, the study aimed to confirm latent profiles in health-related quality of life, sleep quality, morning and evening types, and internet addiction in medical students and investigate the characteristics of participants in each profile to provide suggestions for students’ health. This was an observational cross-sectional study including 1221 medical student subjects at China Medical University in 2019. Multiple correspondence analysis was the initial step to verify the correspondence, dispersion, and approximation of variable categories. Latent profile analysis was used to identify the multiple correspondences between the levels of variables. Three profiles were found, including: (1) The Low sleep quality profile was characterized by the lowest sleep quality among the three existing profiles. (2) The High health-related quality of life and Low internet addiction profile was characterized by the highest level of health-related quality of life but the lowest level of internet addiction. (3) The Low health-related quality of life and High internet addiction profile was characterized by the highest standardized values of internet addiction but the lowest standardized values of health-related quality of life. This study had important implications for improving student health and supported the medical universities and hospitals in implementing targeted policies based on distinctive student characteristics.

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Factors associated with excessive daytime sleepiness in medical students of a higher education institution of Bucaramanga

Cited by 3 publications

References 23 publications

Prevalence and factors associated with excessive and severe daytime sleepiness among healthcare university students in the Brazilian Midwest

Prevalence and factors associated with excessive and severe daytime sleepiness among healthcare university students in the Brazilian Midwest

Relationship between sleep habits and academic performance in university Nursing students

Latent profile analysis for health-related quality of life, sleep quality, morning and evening type, and internet addiction among medical students

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