Effects of Anxiety and Chronotype on Sleep Quality: Advantages of Evening Chronotype in the Post-Pandemic Era

Ubaldo Rodríguez-de Ávila; Fabíola Rodrigues-de França Campos; Adriano Chiombacanga-Nafital

doi:10.33069/cim.2024.0018

Chronobiol Med > Volume 6(3); 2024 > Article

Ávila, Campos, and Chiombacanga-Nafital: Effects of Anxiety and Chronotype on Sleep Quality: Advantages of Evening Chronotype in the Post-Pandemic Era

Original Article

Chronobiology in Medicine 2024;6(3):129-134.

Published online: September 30, 2024

DOI: https://doi.org/10.33069/cim.2024.0018

Effects of Anxiety and Chronotype on Sleep Quality: Advantages of Evening Chronotype in the Post-Pandemic Era

Ubaldo Rodríguez-de Ávila¹

, Fabíola Rodrigues-de França Campos²

, Adriano Chiombacanga-Nafital³

¹Psychology Department, Universidad del Magdalena, Santa Marta, Colombia

²Specialized Rehabilitation Center, Instituto Santos Dumont, Macaíba, RN-Brasil

³Biology Department, Universidade Púnguè, Chimoio, Moçambique

Corresponding author: Ubaldo Rodríguez-de Ávila, PhD, Psychology Department, Universidad del Magdalena, Santa Marta, Carrera 34C, No. 8-76, Santa Marta, Colombia.
Tel: 57-3106611275, E-mail: rodriguez.ubaldo@gmail.com

Received July 4, 2024 Revised July 28, 2024 Accepted July 31, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective

Prior to the pandemic, all scientific evidence suggested that the evening chronotype is a risk factor for mental pathologies, while the morning chronotype is a protective factor. However, by exploring the effects of anxiety and chronotype on sleep quality in a post-pandemic, segmented by age, new evidence is presented that contradicts the traditional ones.

Methods

This quantitative, exploratory, cross-sectional study included 2,253 participants, segmented into three age categories: <18 years, 18–23 years, and >23 years. Linear regression coefficients were calculated using weighted least squares, with a confidence level of 95% or greater (p<0.05) applied in all cases.

Results

The highest levels of anxiety were found in men. In all cases, significant correlation and variance were found in sleep quality with respect to age and anxiety. The increase in poor sleep quality is explained by between 1.8% and 1.9% in subjects with anxiety and morning chronotype as age advances in post-pandemic.

Conclusion

Anxiety, chronotype, and age significantly affect sleep quality. In the context of a pandemic, older subjects with a morning chronotype experience worse sleep quality. Specifically, under conditions of confinement and social isolation during a pandemic, morning chronotypes tend to have worse sleep quality compared to evening chronotypes, who may have an adaptive evolutionary advantage in such circumstances.

Keywords: Anxiety; Chronotype; Sleep quality; Post-pandemic; Evening

INTRODUCTION

Sleep quality varies between individuals in response to the sleep-wake cycle and various environmental factors, such as light and noise [1,2], nutrition [3], and physical activity [4-6], among other possible factors. Therefore, sleep is a biological need, and the mechanisms involved are a determinant of the performance of organic activities [7], social interaction [8], emotional activities [9], and cognitive function [10].

Anxiety, as a physiological response to adverse stimuli or due to individual psychological parameters, can coexist with a number of problems including sleep [11]. Although the regulation of emotions and the facets of sleep that contribute to the diagnosis of anxiety are not well explored, poor sleep quality and worse daytime functioning due to sleep can be important predictors of anxiety diagnosis [12]. Conversely, anxiety may be an important predictor of poor sleep quality.

Chronotype refers to preferences for the circadian rhythm or sleep/wake cycle or activity and rest. The morning chronotype prefers to sleep and wake up early, while individuals with the evening chronotype prefer to sleep and wake up late and perform better at night [13]. According to previous studies, the evening chronotype was associated with a deterioration in executive functions and neurocognitive performance [14], and risk behaviors increase with the delay of the circadian rhythm [15,16] and the presence of interaction between evening chronotype and insomnia leads to a greater risk of depressive symptoms [17]. Conversely, another study reported that the morning chronotype could protect against anxiety, depression, and insomnia, while the evening chronotype could be a risk factor for anxiety and depression [18].

The COVID-19 pandemic caused an increased risk of suffering from sleep disorders and an increase in psychological problems [19]. Multiple studies around the world reported significant correlations between anxiety and contact with COVID-19 positive patients, as well as disruptions to work routine among professionals [20] and the study among students [21].

Thus, to our knowledge, there are no studies on anxiety and the evening chronotype as a risk factor or protective factor for sleep quality, based on the implications of confinement during the pandemic and its associations on sleep/wake activity and its effects in the medium and long term. For this reason, this study was designed with the objective of exploring the effects of anxiety and chronotype on sleep quality, in a post-pandemic, because sleep quality indices vary according to the ages of the subjects, chronotype, and anxiety. In this way, the working hypothesis (H1) is that anxiety and chronotype affect sleep quality when controlling for age. Therefore, the null hypothesis (H0) is that anxiety and chronotype do not affect sleep quality when controlling for age. And the predictions (P) are as follows: 1) P1: As age increases, poor sleep quality increases; 2) P2: The higher the anxiety levels, the worse the quality of sleep; and 3) P3: Due to the circumstances of the pandemic and post-pandemic, morning chronotypes will have worse sleep quality.

METHOD

Participants

This quantitative, exploratory, cross-sectional study was conducted within the framework of a mental health intervention program that developed between June 2021 and December 2022.

Through an open call, participants were selected who voluntarily wanted to receive guidance and treatment for possible mental health problems caused or exacerbated by the COVID-19 pandemic. The sample consisted of 2,253 subjects, of which 61% (n=1,369) were male and 39% (n=884) were female.

For further exploration of the study, age (mean±standard deviation=24±10 years; median=19 years) was segmented into three categories: 35% (n=786) were <18 years old; 34.5% (n=778) between 18–23 years old; and 30.5% (n=688) >23 years old at the time of the study.

The inclusion criteria were: signing the informed consent, not having any type of psychiatric diagnosis, and not being under the effects of psychoactive drugs at the time of participating in the study. Participants aged <18 years received written authorization from their parents or responsible adults in their care.

Sleep quality was treated as a dependent variable; while anxiety, chronotype, age, and sex were considered as independent variables.

Measurements

Self-Rating Anxiety Scale-15

The Self-Rating Anxiety Scale-15 (SAS-15) created by Zung [22] is used to measure anxiety. It was validated in Spanish during the COVID-19 pandemic [23] and has been utilized in other studies [24-27]. The scale comprises 15 questions, each rated on a scale of 1–4 (never, sometimes, almost always, and always). Higher scores indicate the presence of anxiety symptoms and lower scores indicate the absence of anxiety symptoms. Scores were categorized into no anxiety, mild to moderate, marked to severe, and extreme anxiety. Cronbach’s alpha (α) for the present study was 0.896 (89.6%).

Morningness–Eveningness Questionnaire

The Morningness–Eveningness Questionnaire (MEQ) was created by Horne and Ostberg [28], and is widely used by chronobiologists and sleep scientists. It was validated in Spanish and utilized in similar studies [29-31]. The questionnaire consists of 19 items with 5-point Likert scale, with a maximum total score of 86 points. Scores of 41 or less indicate an “evening chronotype”; scores of 59 or more indicate a “morning chronotype”; and scores between 42 and 58 indicate an “intermediate chronotype.” Reliability analysis for the MEQ in the present study showed a Cronbach’s alpha (α) of 0.783 (78.3%).

Pittsburgh Sleep Quality Index

The Pittsburgh Sleep Quality Index (PSQI) is a 19-item instrument that is used to quantify sleep quality [32]. PSQI is widely used and validated in different languages, including Spanish [25-27,30]. The results are grouped into seven components. However, in the present study, only the general index of sleep quality is reported. The total score ranges from 0 to 21 points. A score of 0 to 4 indicates good sleep quality; scores ranging from 5 to 10 points indicate poor sleep quality; and scores above 10 points indicate possible sleep disturbances. The reliability analysis based on standardized elements carried out with a pilot for the present study with 212 subjects, yielded a value of 77.8% (α=0.778).

Statistical analyses

Measurements of frequency and percentages, as well as measures of central tendency (mean, standard deviation, and median), were reported. The sample was subjected to a normality analysis using the Kolmogorov-Smirnov (K-S) test for samples with more than 60 observations to assess parametric or non-parametric distribution. A non-parametric distribution was found, which led to the use of non-parametric statistical methods for contrast tests: Spearman correlation (rho), Kruskal-Wallis analysis of variance (χ²). When analyzing the sex variable, Kendall’s tau-b (τb) was used for correlation analysis.

In addition, a linear regression analysis was performed using the “enter” method. A probability of the Fisher statistic (F) with a p-value of <0.05 was set as the inclusion criterion. Sleep quality was determined as the dependent variable to identify the underlying explanatory mathematical model.

The coefficients of the linear regression model were calculated using weighted least squares (WLS), as this analysis technique allows the management of heteroskedasticity in the regression analysis, by assigning different weights to each observation based on their variations, providing more precise and accurate estimates of the regression coefficients. Given that the sex variable is the one that presents the greatest variability in its sample spectrum (male: 1,369 subjects; female: 884 subjects), the weighted estimation procedure was used to contrast different transformations of the sex groups and identify the best fit for the data. This approach aimed to identify the underlying mathematical model for poor sleep quality in subjects. Values were calculated for each power of the weighting source variable tested (R, R², R²-adjusted), ANOVA for the WLS model with the F-test coefficient, beta estimates (β) of the standardized parameters with their lower and upper limit values, and the standard error (SE) of the model.

For psychometric analysis, the statistical reliability of Cronbach’s alpha (α) was verified, establishing a minimum accepted value of 0.75 (75%). For all cases, significance (p) was established at a confidence level greater than or equal to 95% (p<0.05). The statistical package used was IBM SPSS Statistics Ver 28 (IBM Corp., Armonk, NY, USA).

Ethical considerations

The project was developed in accordance with the Resolution of the Ministry of Health 8430 that regulated health research, also, with the precise standards of the Colombian College of Psychologists, in accordance with law 1090 of 2006, which establishes the request for corresponding permits, the signing of informed consent, and confidential handling of all information collected. Subjects’ participation was conditional on their free, voluntary, and informed consent, and they could withdraw from the study at any time. Participants aged <18 years received written authorization from their parents or responsible adults in their care. The study received approval from the Ethics Committee of the University of Magdalena through code M301PR07F03 and code BPIN: 2020000100758.

RESULTS

The study was carried out with 2,253 subjects, of which 61% (n=1,369) were male and 39% (n=884) were female. Regarding ages, 35% (n=786) were <18 years old; 34.5% (n=778) were between 18–23 years old, and 30.5% (n=688) were >23 years old at the time of the study.

Regarding anxiety, 20.3% (n=457) of the total particpants presented anxiety between marked to severe or extreme; while 79.7% (n=1,796) marked no or mild to moderate anxiety.

On the other hand, the chronotype, 5% (n=109) correspond to the evening type, 44% (n=992) to the morning type, and 51% (n=1,152) have an intermediate type.

Sleep quality was found as follows: 57% (n=1,282) present sleep disturbances, 32% (n=724) poor sleep quality, and only 11% of the subjects (n=247) had good quality of sleep.

Table 1 presents the statistics of central tendency, normality, and analysis of intraclass variance, in a general way for each variable respectively, as well as segmenting the distribution by age range.

A non-parametric distribution was verified at a general level as well as significant variance in the distribution of all variables. From these data, variance tests and non-parametric correlations were used to find the significant differences of the studied variables controlled for age and their respective significance for each age range (Figure 1).

For all cases, the Kruskal–Wallis chi-square values (χ²) suggest significant variance in sleep quality with respect to anxiety and chronotype. The Spearman correlation coefficient (rho) also shows a direct significant correlation between sleep quality and all the variables, which is verified with the linear fit (Figure 1A and B). However, when the variables segmented by age ranges are analyzed, no significant correlations are verified between sleep quality with anxiety and chronotype (Figure 1C).

Sex was significantly inversely related to anxiety at all age levels (<18 years: τb=-0.232 [p<0.001]; 18–23 years: τb=-0.222 [p<0.001]; >23 years: τb=-0.122 [p<0.001]). It was found that men showed higher levels of anxiety.

As the linear fit or the estimated vector distance does not show a significant effect individually between the relationship of the variables involved (adjustment line R²) (Figure 1), we proceed to the weighted estimation analysis and the coefficients of the linear regression model were calculated using WLS to verify the effect of the age, anxiety, and chronotype on sleep quality in the studied subjects (Table 2).

DISCUSSION

The current sample shows a higher rate of sleep disturbances (89%, between poor quality and sleep disturbances), which agrees with recent studies that report a decrease in sleep quality as effects of COVID-19 [33].

Anxiety does not seem to be a prevalent factor in the population studied, where only around 20% present significant self-reported levels of this disorder, contrasting with the findings of a study that provides information on adverse psychiatric consequences, such as the high prevalence of anxiety among patients with comorbid conditions post-COVID-19 pandemic [34]. However, the present results support the conclusions of a study with subjects with mental disorders where they reported symptoms of anxiety and depression during the third pandemic wave, where the majority of patients showed improvement during a 3-month follow-up, despite the fact that differences emerged between the diagnostic categories and the variables involved [35].

This study confirms what chronobiologists and sleep scientists have been observing since the beginning of research in this matter [28]: the majority of individuals fall into the intermediate chronotype, followed by morning chronotypes, with eveningness being the least prevalent worldwide.

Based on these findings and in accordance with another recent study [36], we verify that there is limited evidence, with inconsistent results, regarding the acute physiological response to anxiety according to the chronotype types after the crisis due to the COVID-19 pandemic. This links the eveningness chronotype as a potential moderator of mental health in the face of generalized crises that involve changes in activity and rest schedules, as was indirectly verified in another study [37].

It has been proven that the energy expenditure of subjects with eveningness chronotype increases at night, and during the mornings and part of the day the cognitive, emotional and energetic demand is decreased, unlike people with morning chronotype, whose physiological, emotional, and cognitive demands decrease substantially at night, with peaks of activation during the morning and part of the afternoon.

The society in times of non-confinement, whose occupational demands generally take place outside the home, privilege the morning type, who easily adapt to said social organization for most of the day. Conversely, eveningness individuals experience sleep disturbances, obvious or covert, logically leading them to almost permanently poor quality sleep.

The confinement during the COVID-19 pandemic seems to have enabled an evolutionary advantage for subjects with eveningness chronotype; because for about a year, social activities stopped or took place inside homes, during daylight hours, with the possibility of remote work (work or education). It was there that the eveningness temporal organization may have had its evolutionary advantage, and in the short and medium term, the morning subjects must have experienced higher levels of sleep disturbances, mainly the older ones.

The data allow us to verify Prediction 1 (P1): as age increases, poor sleep quality increases (Figure 1A). Prediction 2 (P2) was also confirmed: the higher the anxiety levels, the worse the quality of sleep (Figure 1B). Likewise, Prediction 3 (P3) was verified: due to the circumstances of the pandemic and post-pandemic, morning chronotypes will have worse sleep quality.

Furthermore, the variability in sleep quality can be predicted based on anxiety, chronotype, and age. The coefficients of the linear regression model using MCP allowed us to verify the best fit for the data. Anxiety, chronotype, and age significantly affect sleep quality. In conclusion, individuals with a morning chronotype tend to have poorer sleep quality during a pandemic, such as COVID-19, especially in older subjects. This supports Hypothesis 0: “The subject’s anxiety and chronotype affect sleep quality, with age as a contributing factor.”

Thus, this study and its evidence open the discussion that, in the circumstances of a pandemic with confinement and social isolation, the morning chronotype will have worse sleep quality compared to the eveningness chronotypes, who (the eveningness chronotypes) present an adaptive evolutionary advantage to this type of circumstances.

More studies are needed to deepen knowledge about the impact of the pandemic on patients with or without mental disorders.

Until the time of this study, and before the pandemic, all the evidence shown by the scientific community suggests that the “eveningness chronotype could be a risk factor and the morning chronotype a protective factor.” However, this could be the first study that shows a different situation due to pandemic effects and post-pandemic situations. Therefore, this study itself is understood as the main argument for prediction 3.

The most important limitation of the study was the non-experimental design, in order to compare the results between the conditions of the eveningness and morning chronotypes, controlling stressor variables simulating pandemic. However, due to the exploratory nature of the study, this was not anticipated. Therefore, future experimental studies are recommended to contrast our conclusions.

NOTES

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Availability of Data and Material

The data generated or analyzed during the study are available from the corresponding author upon reasonable request.

Author Contributions

Conceptualization: Ubaldo Rodríguez-de Ávila. Data curation: Ubaldo Rodríguez-de Ávila. Formal analysis: all authors. Research: Ubaldo Rodríguez-de Ávila. Methodology: all authors. Software: all authors. Supervision: Ubaldo Rodríguez-de Ávila. Viewing: all authors. Writing—original draft: all authors. Writing—review & editing: all authors.

Funding Statement

This study was supported by the University of Magdalena and Sistema General de Regalias de Colombia.

Acknowledgments

None

Figure 1.

Boxplot grouped by sleep quality. A: Anxiety boxplot grouped by sleep quality and age range. B: Chronotype boxplot grouped by sleep quality and age range. C: Bivariate correlations of sleep quality with age, anxiety, and chronotype, at a global level and segmented by age ranges. χ², Kruskal–Wallis chi-square analysis of variance; df, degrees of freedom; rho, Spearman correlation coefficient for non-parametric samples; R², estimated vector distance or linear fit of the model; p, significance level. *The variance is significant; †The correlation is significant.

Table 1.

Statistics of central tendency, normality, and variance

Age ranges	Age	Sleep quality	Anxiety	Chronotype
General	24±10 (19)	14±9 (12)	24±8 (23)	57±8 (57)
<18 years old	16±6 (17)	13±9 (10)	23±4 (21)	55±8 (56)
18–23 years old	20±2 (19)	14±9 (12)	26±8 (24)	56±8 (55)
>23 years old	36±11 (33)	15±9 (14)	25±8 (24)	60±8 (61)

Values are presented as mean±standard deviation^* (median^†).

^* The sample, according to the Kolmogorov-Smirnov normality test, has a nonparametric distribution (p<0.001).

^† Kruskal-Wallis chi-square analysis of variance shows a significant difference (p<0.001).

Table 2.

Coefficients from the linear regression of weighted least squares

	β	95% CI		p
	β	Lower	High	p
(Constant)	6.530	3.354	9.724	<0.001^*
Anxiety	0.122	0.097	0.202	<0.001^*
Chronotype	0.044	-0.001	0.096	0.055
Age	0.056	0.011	0.086	0.011^*

^* statistically significant, p<0.05.

Dependent variable, constant (sleep quality, weighted for sex). CI, confidence interval

REFERENCES

1. Xu M, Tian C, Liang S, Tong B, Wu Y, Zhou L, et al. Comparative efficacy of exercise modalities on sleep quality in populations with sleep disorders: a systematic review and network meta-analysis. Sleep Med Rev 2024;73:101877.

2. Cajochen C, Reichert CF, Münch M, Gabel V, Stefani O, Chellappa SL, et al. Ultradian sleep cycles: frequency, duration, and associations with individual and environmental factors—a retrospective study. Sleep Health 2024;10(1S): S52–S62.

3. Saidi O, Rochette E, Dambel L, St-Onge MP, Duché P. Chrono-nutrition and sleep: lessons from the temporal feature of eating patterns in human studies - a systematic scoping review. Sleep Med Rev 2024;76:101953.

4. Boyle JT, Nielson SA, Perlis ML, Dzierzewski JM. Move your feet and sleep: a longitudinal dynamic analysis of self-reported exercise, sedentary behavior, and insomnia symptoms. Sleep Health 2024;10:321–326.

5. Xie W, Lu D, Liu S, Li J, Li R. The optimal exercise intervention for sleep quality in adults: a systematic review and network meta-analysis. Prev Med 2024;183:107955.

6. Xu X, Lian Z, Shen J, Lan L, Sun Y. Environmental factors affecting sleep quality in summer: a field study in Shanghai, China. J Therm Biol 2021;99:102977.

7. Connolly PJ, Quigg M, Davis EM. Improvement in non-24-h sleep-wake rhythm disorder in a sighted individual treated with a melatonin receptor agonist. Sleep Med 2024;116:41–42.

8. Zuckerman E, Fernandes SN, Sullivan SR, Ortin-Peralta A, Jeglic E, Miranda R, et al. Sleep quality and in-person versus online social interaction during the early COVID-19 pandemic lockdown: impact on affect and interpersonal needs among young adults. Psychiatry Res Commun 2023;3:100134.

9. Subramoniam A, Chen PC, Mednick S, Whitehurst L. Physiological sleep correlates are associated with positive and negative affect in younger and older adults. Sleep Med 2024;115(Suppl 1): S39.

10. Grove DM, McConnell BV. Sleep and cognition [Internet]. Available at: https://doi.org/10.1016/B978-0-323-95702-1.00157-3. Accessed February 24, 2024.

11. Aernout E, Benradia I, Hazo JB, Sy A, Askevis-Leherpeux F, Sebbane D, et al. International study of the prevalence and factors associated with insomnia in the general population. Sleep Med 2021;82:186–192.

12. Schantz BL, Toner ER, Brown ML, Kaiser N, Chen A, Adhikari S, et al. Examining the relationship between emotion regulation, sleep quality, and anxiety disorder diagnosis. J Mood Anxiety Disord 2024;8:100072.

13. Vitale JA, Roveda E, Montaruli A, Galasso L, Weydahl A, Caumo A, et al. Chronotype influences activity circadian rhythm and sleep: differences in sleep quality between weekdays and weekend. Chronobiol Int 2015;32:405–415.

14. Taillard J, Sagaspe P, Philip P, Bioulac S. Sleep timing, chronotype and social jetlag: impact on cognitive abilities and psychiatric disorders. Biochem Pharmacol 2021;191:114438.

15. Chan NY, Zhang J, Tsang CC, Li AM, Chan JWY, Wing YK, et al. The associations of insomnia symptoms and chronotype with daytime sleepiness, mood symptoms and suicide risk in adolescents. Sleep Med 2020;74:124–131.

16. Esaki Y, Obayashi K, Saeki K, Fujita K, Iwata N, Kitajima T. Higher prevalence of intentional self-harm in bipolar disorder with evening chronotype: a finding from the APPLE cohort study. J Affect Disord 2020;277:727–732.

17. Que J, Chen S, Chan NY, Wu S, Zhang L, Chen Y, et al. Associations of evening-type and insomnia symptoms with depressive symptoms among youths. Sleep Med 2024;118:81–87.

18. Mao B, Xie Z, Liu M, Gong Y, Wang H, Yang S, et al. Associations of chronotype with anxiety, depression and insomnia among general adult population: a cross-sectional study in Hubei, China. J Affect Disord 2024;351:250–258.

19. Zhang H, Yang Y, Hao X, Qin Y, Li K. Effects of digital sleep interventions on sleep and psychological health during the COVID-19 pandemic: a systematic review and meta-analysis. Sleep Med 2023;110:190–200.

20. Iqbal S, Alanazi RF, Alahmed AH, Alnakhli AF, Alghanim MH, Alghamdi MAA, et al. Prevalence of sleep disturbance and anxiety due to the COVID-19 pandemic in Saudi Arabia. Sleep Sci 2021;14(Spec 1): 56–62.

21. Arrona-Palacios A, Díaz-Morales JF, Adan A. Sleep habits and circadian preferences in school-aged children attending a Mexican double-shift school system. Sleep Med 2021;81:116–119.

22. Zung WW. A rating instrument for anxiety disorders. Psychosomatics 1971;12:371–379.

23. Rodríguez-de Avila UE, Leon-Valle ZL, Ceballos-Ospino GA. [Psychometric behavior of the Zung self-rating anxiety scale-15 (SAS-15) Spanish version, during Covid-19 pandemic physical isolation]. Duazary 2020;17:7–9.Spanish.

24. Múnera-Luque K, Rodríguez-De Ávila U. Association between violence and anxiety and depression problems in women living in the Magdalena region, Colombia. Eur Psychiatry 2023;66(S1): S652.

25. Rodriguez-De Avila U, Paba-Argote Z. Young vs adults: adaptability to ICTs, resilience, anxiety and depression in university students and professors. Eur Psychiatry 2023;66(S1): S461–S462.

26. Rodríguez-De Avila UE, Rodrigues-De França F, Jesus Simões MF. [Psychological impact and sleep quality in the COVID-19 pandemic in Brazil, Colombia and Portugal]. Duazary 2021;18:120–130.Spanish.

27. Rodríguez De Avila U, León Valle Z, Ceballos Ospino G. Suicidal ideation, anxiety, social capital, and sleep among colombians in the first month of COVID-19-related physical isolation. Psicogente 2021;24:1–18.

28. Horne JA, Ostberg O. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol 1976;4:97–110.

29. Rodríguez de Ávila UE, de França Campos FR, Paba Argote ZL. [Cronotipo, ansiedad flotante, desempeño académico y afabilidad en estudiantes universitarios]. Entretextos 2024;18:201–218.Spanish.

30. Rodríguez U, Campos FRD, Chionbacanga-Nafital A, Ceballos-Ospino G, Paba-Barbosa C. [Do the intelligences, emotions and chronotype, explain academic performance in university students?]. Educ Humanism 2020;22:1–21.Spanish.

31. Rodríguez de Ávila UE, de França Campos FR. 15 minutes of attention in class: variability of heart rate, personality, emotion and chronotype. Creat Educ 2019;10:2428–2447.

32. Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res 1989;28:193–213.

33. Daniels BT, Robinson S, Vargas I, Baum JI, Howie EK. Changes in physical activity and sleep following the COVID-19 pandemic on a university campus: perception versus reality. Sports Med Health Sci 2024;6:246–251.

34. Khalaf DAM, Arueyingho O. Exploring the psychological impact of anxiety, depression, and quality of life in patients with comorbid disease conditions post COVID-19 pandemic era. Vacunas 2024;25:46–53.

35. Carmassi C, Tosato S, Pedrinelli V, Bertelloni CA, Abbate-Daga G, Albert U, et al. Longitudinal trajectories of anxiety and depression in subjects with different mental disorders after one year in the COVID-19 pandemic. Psychiatry Res 2024;334:115680.

36. Benfica M, Messa R, Ribeiro L, Alves E. The acute physiological stress responses after total sleep deprivation in health individuals: a systematic review. Sleep Med 2024;115(Suppl 1): S145–S146.

37. Aggarwal B, Benasi G, Makarem N, Mayat Z, Byun S, Liao M, et al. Psychosocial factors are associated with sleep disturbances and evening chronotype among women: a brief report from the American Heart Association Go Red for Women strategically focused research network. Sleep Health 2024;10:65–68.