Psychosocial Predictors of Sleep Disturbances during COVID-19: differential contributions of demographic, psychological, pandemic-related factors to sleep health.

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Vasiliki Varela, Erasmia Giogkaraki, Dimitrios Vlastos, Elisabet Alzueta, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4265194/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aim: Since the declaration of COVID-19 as a Public Health Emergency of International Concern on January 30, 2020, the disease escalated into a global pandemic forcing governments around the world to impose measures that affected all aspects of life. Among other countries, Greece adopted social restriction, lockdowns, and quarantines to reduce transmission from person to person. Subjects and Methods: This cross-sectional study aimed to investigate the impact of those measures on sleep health in a Greek adult sample. An online questionnaire collected data during from 650 participant. Results: 60% of responders scored below the clinical cut-off on the RU-SATED, indicating they experienced poor sleep health. Better sleep health was reported with increased age and years of education. On the other hand, higher trauma-related distress, depression, anxiety and stress symptomatology were related to poorer sleep health. No gender differences were observed, and degree of compliance to pandemic restrictions did not influence sleep health. Hierarchical regression analysis indicated difficulty in securing enough/healthy food, testing positive for COVID-19, experiencing an increase in verbal arguments/conflicts at home and an increase in responsibilities were the strongest predictors of poor sleep heath. Conclusions: Results highlight the importance of maintaining good sleep health as a pillar of general physical and mental health. Psychology Psychiatry Epidemiology sleep COVID-19 depression anxiety stress lockdown Figures Figure 1 Figure 2 Introduction The fast escalation of COVID-19 into a global pandemic forced many governments to impose measures that affected all aspects of life. In the absence of pharmacological treatment, the non-pharmacological interventions (NPIs) adopted as measures to mitigate the fast transmissibility of SARS-CoV-2 altered daily life in extreme ways: restrictions in social interaction meant loss of perceived -and actual- social support, business shut down led to financial insecurity and adversity, the daily dead count instigated imminent threat and phobia of contamination, and infection with the virus itself resulted in fear for one’s survival (Brooks et al. 2020 , Xiong et al. 2020 ). Naturally, these extremely stressful day-time circumstances also affected people’s night-time, with both sleep quantity and quality taking a toll (Rezaei et al. 2021; Yuan et al. 2022 ). While NPIs are especially important when addressing a global pandemic like COVID-19, there is an equally important need for a balanced examination after the fact, while maintaining the dual goals of safeguarding public health through NPIs and understanding their potential effects on sleep health. Studies are indeed reporting an increase in sleep disturbances during the pandemic, coupled with an increase in psychological distress (Alimoradi et al. 2021 ; Deng et al. 2021 ; Kolakowsky-Hayner et al. 2021 ; Targa et al. 2021 ; Yuksel et al. 2021). A systematic review and meta-analysis (Limongi et al. 2023 ), synthesised evidence from 63 studies that compared sleep hygiene pre- and during lockdown and found reductions in sleep efficiency and increases in sleep problems and use of sleep medication during pandemic time. These findings are not uniform, however, with several demographic, psychological and pandemic-related variables (situational) moderating the effect of COVID-19 on sleep health. The majority of research highlights pre-existing inequalities, as well as new, emergent factors that increase the risk of poor sleep hygiene during the pandemic. Gender has consistently come up, with women more likely to suffer from sleep problems than men (Jahrami et al. 2021 ; Mandelkorn et al. 2021 ; Voitsidis et al. 2020 ). Whether this gender difference comes as a direct influence of the pandemic, or whether it reflects pre-existing disparities in sleep hygiene between the sexes, remains a worthy question (Deng et al. 2021 ; Ohayon 2011). Furthermore, being of younger age is introduced as a new risk factor for both mental health and sleep deterioration during COVID-19 (Jahrami et al. 2021 ; Kolakowsky-Hayner et al. 2021 b; Sachs et al. 2022 ), reflecting how disproportionately affected this population section has been to the financial insecurities and social isolation that the pandemic brought with it. Sleep disorders were also found to be more prevalent in those unemployed at the time and those of lower educational attainment (Bhat and Chokroverty 2022 ; Casagrande et al. 2021 ; Pinto et al. 2020 ). Psychological variables have also emerged, many of which are known correlates of the above demographic factors (some causal). Naturally, one’s mental health status and pre-pandemic sleep hygiene are both consistently shown to predict sleep health during COVID-19. A Scientific Brief by the WHO published in March 2022, based on the Global Burden of Disease (Santomauro et al. 2020) and its own umbrella review (Witteveen et al. 2021 ), concluded that the pandemic has directly led to worldwide increases in depression and anxiety prevalence rates. Not only is there a magnitude of evidence for this link in international studies and large systematic reviews and meta-analyses (Limongi et al. 2023 ; Kocevska et al. 2020 ; Santomauro et al. 2020), but there is also a temporal association shown in the way our sleep health is affected by stress, anxiety, and depression. Studies are reporting that the somatic symptoms of stress and the characteristic thought pattern of anxiety, with its constant worries, precede sleep disturbances. In addition, evidence from intervention studies also demonstrate alleviation of sleep problems when daytime worrying (anxiety) or rumination (depression) are also decreased (Alimoradi et al. 2021 ; Du et al. 2020 ; Irish et al. 2015 ; Johnson et al. 2006 ). It is, therefore, no surprise that the inherent psychosocial pressures that came with the pandemic and its countermeasures acted as triggers that led to failing sleep health in the population. Lastly, situational variables related to the pandemic-conditions one experienced at the time are also important contributors to sleep health. The severity of NPIs, days spend in home confinement, contracting SARSCoV-2, losing a relative to the disease, experiencing conflict within the family have all been shown as risk factors for sleep disorders (Casagrande et al. 2021 ; Nochaiwong et al. 2021 ; Scarpelli et al. 2022 ). The present study aimed at identifying the impact of demographic, COVID-related, and mental health variables on the sleep hygiene of a sample of Greek adults during the 2nd wave of COVID-19. Previous reports show a considerable mental health burden in this population, with the COVID pandemic hitting the country just as it was coming out of a ten-year financial austerity period with dire mental health consequences (Economou et al. 2016 ; Liozidou et al. 2023 ). Specifically for the sleep health domain, the prevalence of sleep disorder has been found between 30–40% of respondents, with both quantity and quality of sleep further declining between pandemic waves (Fountoulakis et al. 2021 ; Trakada et al. 2020 , 2022; Voitsidis et al. 2020 ). Building on the available evidence to date, the current study presents an attempt at systematizing demographic, psychological and situational (pandemic-related) factors, using standardized and validated self-report scales and a large sample, to assess the prevalence and predictors of sleep hygiene disturbances during Greece’s second lockdown period. Materials and Methods Participants and Procedure All aspects of the study complied with the Declaration of Helsinki. The study was advertised on social media (WhatsApp, Twitter, Facebook and Instagram) and professional mailing lists, and the survey itself, hosted on SurveyMonkey, ran between February 3rd to June 1st, 2021, coinciding with the “second wave” of COVID 19. The final sample consisted of 650 respondents, with demographic information presented in Table 1 . Table 1 Summary of Sample Sociodemographic characteristics and History of Mental Health. Age (years), M ( SD) 33.13 (12.17) Education (years), M ( SD) 16.6 (4.2) Gender, % female 71.5 Employment status, % employed 89.8 Of those employed % working from home 67.5% Relationship status, % partnered , % single 34.9, 65 Lives with Children (underage or adult), % Yes 47.7 Lives with parents, % Yes 32.8 History of Medical conditions, % Yes 19.7 History of Neurological conditions, % Yes 2.8 History of Psychiatric conditions, % Yes 13.5 Degree of social isolation I was following moderate restrictions , % Yes 57.5 I was following severe restrictions , % Yes 17.7 I was not following any specific restrictions , % Yes 4 Measures Demographic variables were collected using a short form. To operationalized sleep health, a number of stand-alone questions about COVID-related sleep changes as well as the Regulatory Satisfaction Alertness Timing Efficiency Duration Scale was used (RU-SATED, Buysse et al. 2014). This is a widely used measure, shown to be reliable and valid (Ravyts et al. 2019). The items assess six dimensions of sleep (sleep regularity, satisfaction, alertness during the day, timing, efficiency of falling asleep, and duration) on a 3-point Likert scale. Higher scores indicate better sleep health. Scoring below 7 has been proposed as indicating poor sleep health (Dalmases et al. 2019 ; Yuksel et al. 2021). To operationalize pandemic-related factors, a 29-item version of the Epidemic–Pandemic Impacts Inventory (EPII) was used (Grasso et al. 2020 ). This measures the impact of COVID-19 on six life domains (infection history, work life, finance, education, home life and social isolation) on a dichotomous scale (Yes/No). We also asked participants to rate the degree of compliance to restrictions, using a four-point scale, “1) Level 0: I was not following any specific restrictions; 2) Level 1: I was following mild restrictions (e.g., not gathering with ten or more people, not traveling outside my city or state) ; 3) Level 2: I was following moderate restrictions (e.g., not leaving home except for working, care of another family member, exercise, or getting fresh air); 4) Level 3: I was following severe restrictions (e.g., not leaving home at all, or only leaving to buy food or medicine )”. Lastly, to operationalize the psychological variables of interest, we utilized the following scales: the Depression, Anxiety and Stress Scale (DASS-21; Lovibond and Lovibond 1995 ) and the Generalized Anxiety Disorder-7 (GAD-7; Spitzer et al. 2006 ) were used to quantify depression, anxiety and stress symptom severity; trauma-related distress was measured with the 8-item Child-Revised Impact of Events Scale (CRIES-8; Perrin et al. 2005 ). Results Graphical outputs of the findings on sleep behavior and COVID-related changes can be seen below (Fig. 1 ). On average, participants slept 7.35 hours per 24h period ( SD = 1.4), with 80% of the sample reporting sleeping between 6 to 8 hours. During the week preceding survey completion, and in comparison to pre-pandemic sleep habits, 23% reported sleeping “Less than usual” and “Much less than usual”, 26% of respondents reported experiencing more nightmares/bad dreams, 25.1% had more than usual trouble falling asleep and a 24% woke up in the middle of the night more than before COVID-19. Lastly, regarding use of sleep aids, 90.3% of respondents indicated that they rarely/never used prescription or over-the-counter sleep aids and 79% reported rarely or never having used natural sleep aids. Younger people were less likely to use prescribed sleep aids than older participants, x 2 = 19.6, p = 0.03. In an attempt to explore whether females were more vulnerable to sleep health changes than males, we run separate analyses by gender and found no gender differences in changes in sleep routines, x 2 = 6.9, df = 4, p = 0.146, in trouble falling asleep, x 2 = 5.1, df = 4, p = 0.28, or walking up the middle of the night, x 2 = 9.15, df = 4, p = 0.06, but did find a gender difference in increasing nightmares and bad dreams, where a higher proportion of females reported suffering more from these sleep disturbances than males (in respect to pre-pandemic times), x 2 = 15.9, df = 4, p = 0.003. In the RU-SATED, respondents reported an average score of 6.89 ( SD = 2.08) out of the maximum possible 12, with higher scores on this scale denoting better sleep health. The distribution of scores was somewhat negative (Fig. 2 ) (i.e., more people reported lower sleep health). 59% of participants scored below the median cut-off of the scale (7). In the correlation matrix (Table 2 ), overall sleep health was significantly correlated to age, r = 0.16, p < 0.001, and years of education, r = 0.13, p < 0.001: with increasing age and years of education, better sleep health was reported. No difference was observed between males ( M = 6.92, SD = 2.04) and females ( M = 6.88, SD = 2.10), t( 648) = 0.26, p = 0.39. Lastly, there was no difference found in sleep health between those respondents who worked from home ( M = 6.81, SD = 2.02) and those who did not ( M = 7.06, SD = 2.19), t( 648) = -1.45, p = 0.15. A significant, weak, and negative correlation between sleep health and trauma-related stress (as measured by the CRIES-8 scale) was also reported, r = − .13, p < 0.001, indicating that higher self-perceived trauma-related distress was associated to poorer sleep health. Significant, weak, negative correlations were also observed between the RU-SATED and depression, r = − .23, p < 0.001, stress, r = − .23, p < 0.001, and anxiety, r = − .23, p < 0.001 levels, with decreased sleep health related to increases in self-reported psychopathology. Table 2 Correlation matrix among demographic variables and health outcomes. M SD 1 2 3 4 5 6 1. Age (yrs) 33.14 12.2 -- 2. Education (yrs) 16.57 4.2 .36 ** -- 3. Trauma Distress CRIES−8 13.76 10.5 − .05 − .03 -- 4. Sleep Health RU−SATED 6.89 2.1 .16 ** .13 ** − .13 ** -- 5. Stress DASS 15.10 11.7 − .18 ** − .06 .53 ** − .23 ** -- 6.Depression DASS 10.53 10.7 − .14* * − .10 * .46 ** − .23 ** .71 ** -- 7. Anxiety GAD 7 5.93 5.6 − .15 ** − .07 .51 ** − .23 ** .83 ** .74 * * Correlation significant at the 0.05 level (2−taled). ** Correlation is significant at the Bonferroni−adjusted alpha level of 0.008 (2−tailed). Lastly, a three-step hierarchical linear regression analysis was conducted to evaluate the prediction of perceived sleep health (RU-SATED total score) from demographic variables (Model 1: F (8,638) = 2.84, p < .01, r adj 2 = 0.034), variables relating to COVID-19 (Model 2: F (28,618) = 2.34, p < .001, r adj 2 =.055, F change = 2.09, p < .01, r 2 change = .06), and the level of quarantine experienced (Model 3). The full model (Model 3) was statistically significant, F (29,617) = 2.12, p < .01., r adj 2 = .051. However, the addition of the last factor (level of quarantine) did not add to predictive power, F change = .13, p change = 0.94, r 2 change = .01. Therefore, the degree to which one was following the restrictions was not a significant predictor of sleep health. The variables that were found to be significant predictors of sleep health (in order of magnitude of contribution to model) were EPII items “U nable to get enough food or healthy food ” ( β = − .156, p = < 0.001), “ Tested and currently have the disease ” ( β = 0.139, p = 0.02), Age ( β = 0.107, p = 0.03), EPII items “ I experience increase in verbal arguments or conflict with other adult(s) in home ” ( β = -0.084, p = 0.045) and “ I experience an increase in workload/responsibilities ” ( β = 0.082, p = 0.044). Discussion Physical activity, dietary habits and sleep have consistently been recognized as pillars of health, with sleep disturbances shown to lead to both short-term and longstanding effects on cognitive function, metabolic and cardiac health, quality of life and mortality (Medic et al. 2017 ; Ramar et al. 2021 ). The results reported here highlight the complex inter-relationships between sleep health and a number of demographic, mental health and COVID pandemic-related factors. In our Greek sample, the majority (59%) of respondents scored below the clinical cut-off on a sleep health scale, with mental health problems and the lockdown effects exacerbating sleep difficulties. A large international study comparing sleep practices in 59 countries (~ 7000 participants), and using the same sleep health measure, reports a much lower 44.4% scoring below the cut-off (Yuksel et al. 2020). This difference is indicative of the considerable mental and physical health burden (sleep problems included) with which Greeks entered the pandemic, being the country adopting the most punitive austerity measures during the Great Recession period that preceded COVID-19 (Economou et al. 2016 ; Nena et al. 2014 ). Looking at demographic and psychological characteristics, both previously known and new risk factors emerged. Firstly, educational attainment and older age were protective factors for sleep health. Being of younger age has been introduced as a new risk factor for both mental health and sleep deterioration during COVID-19 in other studies (Jahrami et al. 2021 ; Kolakowsky-Hayner et al. 2021 b; Sachs et al. 2022 ), reflecting the vulnerability of this section of the population to the financial insecurities and social isolation that the pandemic brought with it. No gender difference in sleep health was found when looking at the RUSATED score. The only gender difference observed was an increase in nightmares and bad dreams, compared to before COVID-19 reported by women only. Nevertheless, the disparity in the gender distribution in our sample does not permit us to make inferences based on the present study. A recent meta-analysis by Alimoradi et al. (2020) also failed to find gender differences and attributed the lack of effect of gender on unequal sample sizes in the reviewed studies. For the moment, there is plenty of research showing both pre-existing and pandemic-instigated disparities in sleep health between the sexes that cannot be ignored, reflecting the presence of more prevalent psychosocial stressors in females, such as a gender gap in home, child, elderly care, and pay (e.g., Boll and Lagemann 2018 ; Cellini et al. 2021 ; Mergener et al. 2023 ; Wade et al. 2021 ). We next turned to factors relating exclusively to NPIs that were imposed to prevent virus spread. The forced social isolation measures have been shown to have affected every domain of life (social relationships, employment etc.) as well as physical and mental health. For example, studies are confirming that the pandemic has also created conditions that limited access and utilisation of non-COVID health services, including drops in planned surgeries, doctors’ appointments, access to medicine etc., with suffering disproportionately from these consequences (Núñez et al., 2021 ; Patel et al., 2020 ; Tuczyńska et al., 2021 ; WHO, 2020). It has become clear via cross-sectional and longitudinal studies that forced lockdown triggered a deterioration in mental health or significantly exacerbated the illnesses in pre-existing mental health sufferers in several countries, Greece included (Alzueta et al. 2020; Liozidou et al. 2023 ; Pierce et al. 2020 ; Santomauro et al. 2020). In our sleep study, it was found that the presence and degree of psychological distress relating to trauma, depression, anxiety and stress symptomatology was also associated with exacerbations of problems in falling asleep, sleep regularity, timing and duration, sleep satisfaction, and daytime alertness. Note, that the relationship between sleep and mental health has been documented well in research (see for review Witteveen et al. 2021 ), but also in clinical settings: assessment of sleep-related symptoms is embedded in standard clinical practice, where sleep disturbances are seen as core clinical diagnostic features in several disease categories in psychiatric classification manuals (DSM 5 and ICD 11; APA, 2013; WHO, 2022). It is therefore not surprising that the stressful and unpredictable pandemic circumstances have led to an exacerbation of sleep problems. Relatedly, some situational factors also emerged: facing difficulties in securing enough/healthy food, testing positive for SARS-COV-2, experiencing an increase in verbal arguments between adults at home and experiencing an increase in workload or responsibilities were all predictive of poor sleep health. Casagrande et al. ( 2021 ) also found that having fallen ill, losing a loved one and number of days spent in confinement were detrimental to sleep health in a large Italian sample of ~ 2300 people. Similar to our results, Yuksel et al. (2021) found the most significant predictor of sleep health to be conflict in the home, with having lost one’s job, not being able to get enough/good quality food, not being able to pay one’s bills, and having a hard time transitioning to working from home following suit. The detrimental effect of conflict in the home should be of special consideration, particularly in light of emerging evidence that shows increases in domestic violence during and immediately after the end of lockdown (Campbell 2020 ; Chatzifotiou & Andreadou 2021 ; Kourti et al. 2023; Usher et al. 2020 ). Note also, that unlike Yuksel et al., we did not find the transition to working from home as contributing to sleep deterioration, as one would perhaps expect. When we compared the total sleep hygiene (RUSATED) score of those who worked from home and those who did not, there was no difference found. This is in contrast to some authors arguing that working from home (via minimal commuting times, more flexible night and wake-up schedules etc.) might enhance sleep health (e.g., Altena et al. 2020 ; Robillard et al. 2021 ). One explanation could be that the more flexible schedule would have been positive indeed, was it not coupled with a simultaneous increase in workload and responsibilities (either imposed over-time or by taking advantage of the flexibility). This paradoxical disadvantage of remote work has been discussed since before the pandemic, when several studies showed that the previously considered family-friendly approach of remote work failed as a promoter of work-life balance and was associated with less happiness, more stress and anxiety, feelings of isolation and loneliness, and problems associated with poor ergonomics and home space (e.g., Ferrara et al. 2022 ; Henke et al. 2016 ; Song and Gao 2020). Since remote work/telework seems to be here to stay well after the pandemic, we need systematic reviews and meta-analyses of the large number of mixed results available, especially in relation to formal home working time versus informal overtime. As a final pandemic-related factor, we asked participants how closely they followed social distancing restrictions (quarantine), as a proxy of the level of isolation. We found that the degree of compliance to restrictions was not predictive of sleep disturbances. Our findings contradict both those of Yuksel et al (2021), who found that stricter quarantine was a significant predictor of sleep health, and Scarpelli et al. ( 2022 ), who in a recent review and meta-analysis found that more severe measures were associated with lower prevalence of sleep disorder (attributed to more flexible wake times, and less fear of getting infected). Perhaps our inability to find a differential impact of degree of social isolation to sleep health reflects sample characteristics: only a 4% in our sample did not follow any of the recommended restrictions around social isolation and traveling. This is arguably low, reflecting the fact that compliance to lockdown measures was generally high among Greeks in comparison to other countries (Fountoulakis et al. 2021 ; Skapinakis et al. 2020 ). To our knowledge, the present study is a first attempt to systematically evaluate sleep hygiene during the COVID-19 forced social isolation in a Greek sample. However, there are some noteworthy limitations, the most important of which being that sleep health assessment was done using a standardised, albeit self-report, instrument and not via a more objective measure, such as polysomnography or activity tracking. Moreover, these findings might be confounded by the very fact that the pandemic hit as Greeks were exiting a ten-year period of harsh austerity, with detrimental consequences on physical and mental health that potentially affected sleep practices, too. Longitudinal, and not cross-sectional designs are more adept at showing reliable change over time. Lastly, the medium of data collection (an online survey) restricted the sample to those who had internet access. While early non-pharmacological interventions (NPIs) have proven essential in supressing the virus, there does not need to be a compromise between saving lives and preserving mental and sleep health. It is hoped that studies such as ours will inform public policy in cases of future threats. Crucially, policy makers should attend to the needs of populations traditionally viewed as vulnerable (being female, of younger age, unemployed, suffering from mental and physical disabilities, being at risk of violence) when planning responses. In addition, when responding to those threats, policies should not end with protective measures only, but should be coupled with impact-reducing interventions to promote resilience and recovery, accessible to vulnerable populations. Finally, on a more optimistic note, we must be reminded that although a multitude of evidence already exists that point to pandemic-induced increases in mental and physical health problems, these findings are recent and sometimes mixed, and there is no certainty that these negative effects will persists over time, now that we leave the pandemic behind us. Nevertheless, recognizing sleep as one of the pillars of physical and psychological wellbeing makes more research investigating the mechanisms implicated in the bidirectional relationships between sleep hygiene, mental and physical health and societal factors warranted. Declarations Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Conflicts of interest/Competing interests: All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. Ethics approval : All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study received IRB approval from both host institutions (Autonomous University of Madrid Ethical Committee, Spain, CEI-106-206 & The Scientific College of Greece Human Research Ethics Committee). Consent to participate: Informed consent was obtained from all individual participants included in the study. Consent for publication: All participants agreed for their anonymized data to be published. Availability of data and material: Data and questionnaires available on request. Code availability: Not applicable. Authors' contributions: All authors contributed to the study conception and design, material preparation, data collection. Data analysis was performed by Vasiliki Varela and Dimitrios Vlastos. The first draft of the manuscript was written by Vasiliki Varela and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. References Alimoradi Z, Broström A, Tsang HW, Griffiths MD, Haghayegh S, Ohayon MM, Lin CY, Pakpour AH (2021) Sleep problems during COVID-19 pandemic and its’ association to psychological distress: A systematic review and meta-analysis. EClinicalMedicine, 36. 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Mandelkorn U, Genzer S, Choshen-Hillel S, Reiter J, Meira e Cruz M, Hochner H, Kheirandish-Gozal L, Gozal D, Gileles-Hillel A (2021) Escalation of sleep disturbances amid the COVID-19 pandemic: a cross-sectional international study. Journal of Clinical Sleep Medicine. 17(1):45-53. Medic G, Wille M, Hemels ME (2017) Short-and long-term health consequences of sleep disruption. Nature and science of sleep. 151-61. Mergener A, Entgelmeier I, Rinke T (2023) Does Working from Home Improve the Temporal Alignment of Work and Private Life? Differences Between Telework and Informal Overtime at Home by Gender and Family Responsibilities. InFlexible Work and the Family, pp. 129-157). Emerald Publishing Limited. Nena E, Steiropoulos P, Papanas N, Kougkas D, Zarogoulidis P, Constantinidis TC (2014) Greek financial crisis: From loss of money to loss of sleep?. Hippokratia.18(2):135. Nochaiwong S, Ruengorn C, Thavorn K, Hutton B, Awiphan R, Phosuya C, Ruanta Y, Wongpakaran N, Wongpakaran T (2021) Global prevalence of mental health issues among the general population during the coronavirus disease-2019 pandemic: a systematic review and meta-analysis. Scientific reports. 11(1):10173. Núñez A, Sreeganga SD, Ramaprasad A (2021) Access to Healthcare during COVID-19. International journal of environmental research and public health 14;18(6):2980. Ohayon MM (2021) Epidemiological overview of sleep disorders in the general population. Sleep Medicine Research. 2(1):1-9. Patel JA, Nielsen FB, Badiani AA, et al (2020) Poverty, inequality and COVID-19: the forgotten vulnerable. Public health 183:110-111. Perrin S, Meiser-Stedman R, Smith P (2005) The Children's Revised Impact of Event Scale (CRIES): Validity as a screening instrument for PTSD. Behavioural and Cognitive Psychotherapy 33(4):487-498. Pierce M, Hope H, Ford T, Hatch S, Hotopf M, John A, Kontopantelis E, Webb R, Wessely S, McManus S, Abel KM (2020) Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population. The Lancet Psychiatry 7(10):883-892. Pinto J, van Zeller M, Amorim P, Pimentel A, Dantas P, Eusébio E, Neves A, Pipa J, Santa Clara E, Santiago T, Viana P (2020) Sleep quality in times of Covid-19 pandemic. Sleep medicine. 74:81-5. Ramar K, Malhotra RK, Carden KA, Martin JL, Abbasi-Feinberg F, Aurora RN, Kapur VK, Olson EJ, Rosen CL, Rowley JA, Shelgikar AV (2021) Sleep is essential to health: an American Academy of Sleep Medicine position statement. Journal of Clinical Sleep Medicine. 17(10):2115-9. Ravyts SG, Dzierzewski JM, Perez E, Donovan EK, Dautovich ND (2021) Sleep health as measured by RU SATED: a psychometric evaluation. Behavioral Sleep Medicine. 19(1):48-56. Rezaei N, Grandner MA (2021) Changes in sleep duration, timing, and variability during the COVID-19 pandemic: large-scale Fitbit data from 6 major US cities. Sleep Health. 7(3):303-13. Robillard R, Dion K, Pennestri MH, Solomonova E, Lee E, Saad M, Murkar A, Godbout R, Edwards JD, Quilty L, Daros AR (2021) Profiles of sleep changes during the COVID‐19 pandemic: Demographic, behavioural and psychological factors. Journal of sleep research. 30(1):e13231. Sachs JD, Karim SS, Aknin L, Allen J, Brosbøl K, Colombo F, Barron GC, Espinosa MF, Gaspar V, Gaviria A, Haines A (2022) The Lancet Commission on lessons for the future from the COVID-19 pandemic. The Lancet. 400(10359):1224-80. Santomauro DF, Herrera AM, Shadid J, Zheng P, Ashbaugh C, Pigott DM, Abbafati C, Adolph C, Amlag JO, Aravkin AY, Bang-Jensen BL (2021) Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. The Lancet. 398(10312):1700-12. Scarpelli S, Zagaria A, Ratti PL, Albano A, Fazio V, Musetti A, Varallo G, Castelnuovo G, Plazzi G, Franceschini C (2022) Subjective sleep alterations in healthy subjects worldwide during COVID-19 pandemic: A systematic review, meta-analysis and meta-regression. Sleep Medicine. Skapinakis, P., Bellos, S., Oikonomou, A., Dimitriadis, G., Gkikas, P., Perdikari, E., & Mavreas, V (2020). Depression and its relationship with coping strategies and illness perceptions during the COVID-19 lockdown in Greece: a cross-sectional survey of the population. Depression research and treatment , 2020 . Song Y, Gao J. 2020. Does telework stress employees out? A study on working at home and subjective well-being for wage/salary workers. Journal of Happiness Studies. 21(7):2649-68. Spitzer RL, Kroenke K, Williams JB, Löwe B (2006) A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of internal medicine 166(10):1092-1097. Targa AD, Benítez ID, Moncusí-Moix A, Arguimbau M, de Batlle J, Dalmases M, Barbé F (2021) Decrease in sleep quality during COVID-19 outbreak. Sleep and Breathing. 1055-61. Trakada A, Nikolaidis PT, Andrade MD, Puccinelli PJ, Economou NT, Steiropoulos P, Knechtle B, Trakada G (2020) Sleep during “lockdown” in the COVID-19 pandemic. International Journal of Environmental Research and Public Health. (23):9094. Tuczyńska M, Matthews-Kozanecka M, & Baum E (2021) Accessibility to non-COVID health services in the world during the COVID-19 pandemic. Frontiers in public health, 9, 760795. Usher K, Bhullar N, Durkin J, Gyamfi N, Jackson D (2020) Family violence and COVID‐19: Increased vulnerability and reduced options for support. International journal of mental health nursing 10.1111/inm.12735. Voitsidis P, Gliatas I, Bairachtari V, Papadopoulou K, Papageorgiou G, Parlapani E, Syngelakis M, Holeva V, Diakogiannis I (2020) Insomnia during the COVID-19 pandemic in a Greek population. Psychiatry research. 289:113076. Yuan RK, Zitting KM, Maskati L, Huang J (2022) Increased sleep duration and delayed sleep timing during the COVID-19 pandemic. Scientific Reports. 12(1):10937. Yuksel B, Ozgor F (2020) Effect of the COVID‐19 pandemic on female sexual behavior. International Journal of Gynecology & Obstetrics 150(1):98-102. Wade M, Prime H, Johnson D, May SS, Jenkins JM, Browne DT (2021) The disparate impact of COVID-19 on the mental health of female and male caregivers. Social Science & Medicine. 275:113801. Witteveen A, Young S, Cuijpers P, Mateos JL, Barbui C, Federico B, Cabello M, Downes N, Franzoi D, Gasior ME, Gray B (2021) COVID-19 and Mental Health: An umbrella review of systematic reviews with or without meta-analyses. World Health Organization (2020) Responding to non-communicable diseases during and beyond the COVID-19 pandemic: state of the evidence on COVID-19 and non-communicable diseases: a rapid review. World Health Organization (2022) Mental health and COVID-19: early evidence of the pandemic’s impact: scientific brief, 2 March 2022 (No. WHO/2019-nCoV/Sci_Brief/Mental_health/2022.1). World Health Organization. World Health Organization (2022) ICD-11: International classification of diseases (11th revision). Xiong J, Lipsitz O, Nasri F, Lui LM, Gill H, Phan L, Chen-Li D, Iacobucci M, Ho R, Majeed A, McIntyre RS (2020) Impact of COVID-19 pandemic on mental health in the general population: A systematic review. Journal of affective disorders. 277:55-64. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4265194","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":291010436,"identity":"828b12dc-6e26-4079-8801-eebeb0c0aea8","order_by":0,"name":"Vasiliki Varela","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYNCCAgY5IGlAihYDBmPStSQ2EK3F4Ebysw8fDOzS17Y3b2DmqbBjkI8+QEhLmvHMGQbJudvOHCtg5jmTzGB4LgG/FsmeA8bMPAbMudtu5Bgw87YxMxj2EHCYZM/xz8x/DOrTze6/AWmpJ6yFn73HmJnB4HCC2Q0ekJbDDPI8hLUUM/YYHDfcdiat4OCcM8d5DAhpYWNm38zwo6Ja3uz44Y0P3lRUy8kTchgKOADEPAYHSNECBvINJGsZBaNgFIyCYQ4ARao72KCSam8AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-2907-8237","institution":"University Mental Health Research Institute (UMHR/EPIPSI), 1st Department of Psychiatry, Eginition Hospital, Medical School, University of Athens, Greece.","correspondingAuthor":true,"prefix":"","firstName":"Vasiliki","middleName":"","lastName":"Varela","suffix":""},{"id":291012158,"identity":"6b5849b9-ebdf-4d13-85f7-f7418fcd518c","order_by":1,"name":"Erasmia Giogkaraki","email":"","orcid":"","institution":"Laboratory of Cognitive Neuroscience and Clinical Neuropsychology, SCG - Scientific College of Greece, Athens, Greece.","correspondingAuthor":false,"prefix":"","firstName":"Erasmia","middleName":"","lastName":"Giogkaraki","suffix":""},{"id":291012159,"identity":"5ce44c5e-036a-4342-a6d4-a7a1b3d27be4","order_by":2,"name":"Dimitrios Vlastos","email":"","orcid":"","institution":"Laboratory of Experimental and Applied Psychology, SCG - Scientific College of Greece, Athens, Greece.","correspondingAuthor":false,"prefix":"","firstName":"Dimitrios","middleName":"","lastName":"Vlastos","suffix":""},{"id":291012160,"identity":"4707f08b-0d4e-4d77-913f-06445e5d36b3","order_by":3,"name":"Elisabet Alzueta","email":"","orcid":"","institution":"Center for Health Sciences, SRI International, Menlo Park, CA, USA.","correspondingAuthor":false,"prefix":"","firstName":"Elisabet","middleName":"","lastName":"Alzueta","suffix":""},{"id":291012161,"identity":"6e4d8628-0497-4505-8f53-5b6c99a4970c","order_by":4,"name":"Paul B Perrin","email":"","orcid":"","institution":"School of Data Science and Department of Psychology, University of Virginia, Charlottesville, VA, USA.","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"B","lastName":"Perrin","suffix":""},{"id":291012162,"identity":"f4b1363c-3d54-4b75-a1e2-7aa3ad0d3957","order_by":5,"name":"Daniela Ramos-Usuga","email":"","orcid":"","institution":"Biomedical Research Doctorate Program, University of the Basque Country, Leioa, Spain","correspondingAuthor":false,"prefix":"","firstName":"Daniela","middleName":"","lastName":"Ramos-Usuga","suffix":""},{"id":291012163,"identity":"d12190dd-4b34-4b45-8af9-0dd67318355b","order_by":6,"name":"Juan Carlos Arango-Lasprilla","email":"","orcid":"","institution":"Giunti Psychometrics. Madrid, Spain.","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"Carlos","lastName":"Arango-Lasprilla","suffix":""},{"id":380073229,"identity":"c6ea31dd-bfcf-4deb-9c3a-a0801cb11de8","order_by":7,"name":"Athanasia Liozidou","email":"","orcid":"","institution":"Laboratory of Cognitive Neuroscience and Clinical Neuropsychology, SCG - Scientific College of Greece, Athens, Greece","correspondingAuthor":false,"prefix":"","firstName":"Athanasia","middleName":"","lastName":"Liozidou","suffix":""}],"badges":[],"createdAt":"2024-04-14 13:50:17","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4265194/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4265194/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54773138,"identity":"3fd2ca74-6599-4eb6-939a-38378cea07f6","added_by":"auto","created_at":"2024-04-16 14:49:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":166635,"visible":true,"origin":"","legend":"\u003cp\u003eSleep behavior and COVID-related changes in sleep habits and sleep health.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4265194/v1/09a9e5de6dea42084afe3a2b.png"},{"id":54773137,"identity":"307831c1-536f-4539-8ed6-bac76b709588","added_by":"auto","created_at":"2024-04-16 14:49:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13189,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency distribution of sleep health (RU-SATED Total score, %).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4265194/v1/16b2f3f6606444e83a9d85d6.png"},{"id":69380851,"identity":"db1cd439-3237-4d89-a788-319d60d35c91","added_by":"auto","created_at":"2024-11-19 18:45:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":714185,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4265194/v1/54203db0-7716-4476-97f6-94c92b7c43e2.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePsychosocial Predictors of Sleep Disturbances during COVID-19: differential contributions of demographic, psychological, pandemic-related factors to sleep health.\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe fast escalation of COVID-19 into a global pandemic forced many governments to impose measures that affected all aspects of life. In the absence of pharmacological treatment, the non-pharmacological interventions (NPIs) adopted as measures to mitigate the fast transmissibility of SARS-CoV-2 altered daily life in extreme ways: restrictions in social interaction meant loss of perceived -and actual- social support, business shut down led to financial insecurity and adversity, the daily dead count instigated imminent threat and phobia of contamination, and infection with the virus itself resulted in fear for one\u0026rsquo;s survival (Brooks et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Xiong et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Naturally, these extremely stressful day-time circumstances also affected people\u0026rsquo;s night-time, with both sleep quantity and quality taking a toll (Rezaei et al. 2021; Yuan et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). While NPIs are especially important when addressing a global pandemic like COVID-19, there is an equally important need for a balanced examination after the fact, while maintaining the dual goals of safeguarding public health through NPIs and understanding their potential effects on sleep health.\u003c/p\u003e \u003cp\u003eStudies are indeed reporting an increase in sleep disturbances during the pandemic, coupled with an increase in psychological distress (Alimoradi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Deng et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kolakowsky-Hayner et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Targa et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yuksel et al. 2021). A systematic review and meta-analysis (Limongi et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), synthesised evidence from 63 studies that compared sleep hygiene pre- and during lockdown and found reductions in sleep efficiency and increases in sleep problems and use of sleep medication during pandemic time. These findings are not uniform, however, with several demographic, psychological and pandemic-related variables (situational) moderating the effect of COVID-19 on sleep health.\u003c/p\u003e \u003cp\u003eThe majority of research highlights pre-existing inequalities, as well as new, emergent factors that increase the risk of poor sleep hygiene during the pandemic. Gender has consistently come up, with women more likely to suffer from sleep problems than men (Jahrami et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mandelkorn et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Voitsidis et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Whether this gender difference comes as a direct influence of the pandemic, or whether it reflects pre-existing disparities in sleep hygiene between the sexes, remains a worthy question (Deng et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ohayon 2011). Furthermore, being of younger age is introduced as a new risk factor for both mental health and sleep deterioration during COVID-19 (Jahrami et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kolakowsky-Hayner et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003eb; Sachs et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), reflecting how disproportionately affected this population section has been to the financial insecurities and social isolation that the pandemic brought with it. Sleep disorders were also found to be more prevalent in those unemployed at the time and those of lower educational attainment (Bhat and Chokroverty \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Casagrande et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pinto et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePsychological variables have also emerged, many of which are known correlates of the above demographic factors (some causal). Naturally, one\u0026rsquo;s mental health status and pre-pandemic sleep hygiene are both consistently shown to predict sleep health during COVID-19. A Scientific Brief by the WHO published in March 2022, based on the Global Burden of Disease (Santomauro et al. 2020) and its own umbrella review (Witteveen et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), concluded that the pandemic has directly led to worldwide increases in depression and anxiety prevalence rates. Not only is there a magnitude of evidence for this link in international studies and large systematic reviews and meta-analyses (Limongi et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kocevska et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Santomauro et al. 2020), but there is also a temporal association shown in the way our sleep health is affected by stress, anxiety, and depression. Studies are reporting that the somatic symptoms of stress and the characteristic thought pattern of anxiety, with its constant worries, precede sleep disturbances. In addition, evidence from intervention studies also demonstrate alleviation of sleep problems when daytime worrying (anxiety) or rumination (depression) are also decreased (Alimoradi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Du et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Irish et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Johnson et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). It is, therefore, no surprise that the inherent psychosocial pressures that came with the pandemic and its countermeasures acted as triggers that led to failing sleep health in the population. Lastly, situational variables related to the pandemic-conditions one experienced at the time are also important contributors to sleep health. The severity of NPIs, days spend in home confinement, contracting SARSCoV-2, losing a relative to the disease, experiencing conflict within the family have all been shown as risk factors for sleep disorders (Casagrande et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nochaiwong et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Scarpelli et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe present study aimed at identifying the impact of demographic, COVID-related, and mental health variables on the sleep hygiene of a sample of Greek adults during the 2nd wave of COVID-19. Previous reports show a considerable mental health burden in this population, with the COVID pandemic hitting the country just as it was coming out of a ten-year financial austerity period with dire mental health consequences (Economou et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Liozidou et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Specifically for the sleep health domain, the prevalence of sleep disorder has been found between 30\u0026ndash;40% of respondents, with both quantity and quality of sleep further declining between pandemic waves (Fountoulakis et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Trakada et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, 2022; Voitsidis et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Building on the available evidence to date, the current study presents an attempt at systematizing demographic, psychological and situational (pandemic-related) factors, using standardized and validated self-report scales and a large sample, to assess the prevalence and predictors of sleep hygiene disturbances during Greece\u0026rsquo;s second lockdown period.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003eParticipants and Procedure\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eAll aspects of the study complied with the Declaration of Helsinki. The study was advertised on social media (WhatsApp, Twitter, Facebook and Instagram) and professional mailing lists, and the survey itself, hosted on SurveyMonkey, ran between February 3rd to June 1st, 2021, coinciding with the \u0026ldquo;second wave\u0026rdquo; of COVID 19. The final sample consisted of 650 respondents, with demographic information presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Sample Sociodemographic characteristics and History of Mental Health.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), \u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.13 (12.17)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (years), \u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.6 (4.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, \u003cem\u003e% female\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment status, \u003cem\u003e% employed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOf those employed % working from home\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelationship status, % \u003cem\u003epartnered\u003c/em\u003e, \u003cem\u003e% single\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.9, 65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLives with Children (underage or adult), % \u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLives with parents, % \u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Medical conditions, % \u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Neurological conditions, % \u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Psychiatric conditions, % \u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDegree of social isolation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eI was following moderate restrictions\u003c/em\u003e, % \u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eI was following severe restrictions\u003c/em\u003e, % \u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eI was not following any specific restrictions\u003c/em\u003e, % \u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003eDemographic variables were collected using a short form. To operationalized sleep health, a number of stand-alone questions about COVID-related sleep changes as well as the Regulatory Satisfaction Alertness Timing Efficiency Duration Scale was used (RU-SATED, Buysse et al. 2014). This is a widely used measure, shown to be reliable and valid (Ravyts et al. 2019). The items assess six dimensions of sleep (sleep regularity, satisfaction, alertness during the day, timing, efficiency of falling asleep, and duration) on a 3-point Likert scale. Higher scores indicate better sleep health. Scoring below 7 has been proposed as indicating poor sleep health (Dalmases et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yuksel et al. 2021).\u003c/p\u003e \u003cp\u003eTo operationalize pandemic-related factors, a 29-item version of the Epidemic\u0026ndash;Pandemic Impacts Inventory (EPII) was used (Grasso et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This measures the impact of COVID-19 on six life domains (infection history, work life, finance, education, home life and social isolation) on a dichotomous scale (Yes/No). We also asked participants to rate the degree of compliance to restrictions, using a four-point scale, \u0026ldquo;1) Level 0: \u003cem\u003eI was not following any specific restrictions; 2) Level 1: I was following mild restrictions (e.g., not gathering with ten or more people, not traveling outside my city or state)\u003c/em\u003e; 3) Level 2: \u003cem\u003eI was following moderate restrictions (e.g., not leaving home except for working, care of another family member, exercise, or getting fresh air);\u003c/em\u003e 4) Level 3: \u003cem\u003eI was following severe restrictions (e.g., not leaving home at all, or only leaving to buy food or medicine\u003c/em\u003e)\u0026rdquo;.\u003c/p\u003e \u003cp\u003eLastly, to operationalize the psychological variables of interest, we utilized the following scales: the Depression, Anxiety and Stress Scale (DASS-21; Lovibond and Lovibond \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) and the Generalized Anxiety Disorder-7 (GAD-7; Spitzer et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) were used to quantify depression, anxiety and stress symptom severity; trauma-related distress was measured with the 8-item Child-Revised Impact of Events Scale (CRIES-8; Perrin et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eGraphical outputs of the findings on sleep behavior and COVID-related changes can be seen below (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). On average, participants slept 7.35 hours per 24h period (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.4), with 80% of the sample reporting sleeping between 6 to 8 hours. During the week preceding survey completion, and in comparison to pre-pandemic sleep habits, 23% reported sleeping \u0026ldquo;Less than usual\u0026rdquo; and \u0026ldquo;Much less than usual\u0026rdquo;, 26% of respondents reported experiencing more nightmares/bad dreams, 25.1% had more than usual trouble falling asleep and a 24% woke up in the middle of the night more than before COVID-19. Lastly, regarding use of sleep aids, 90.3% of respondents indicated that they rarely/never used prescription or over-the-counter sleep aids and 79% reported rarely or never having used natural sleep aids. Younger people were less likely to use prescribed sleep aids than older participants, \u003cem\u003ex\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;19.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03.\u003c/p\u003e\n\u003cp\u003eIn an attempt to explore whether females were more vulnerable to sleep health changes than males, we run separate analyses by gender and found no gender differences in changes in sleep routines, \u003cem\u003ex\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;6.9, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.146, in trouble falling asleep, \u003cem\u003ex\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;5.1, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.28, or walking up the middle of the night, \u003cem\u003ex\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;9.15, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.06, but did find a gender difference in increasing nightmares and bad dreams, where a higher proportion of females reported suffering more from these sleep disturbances than males (in respect to pre-pandemic times), \u003cem\u003ex\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;15.9, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003.\u003c/p\u003e\n\u003cp\u003eIn the RU-SATED, respondents reported an average score of 6.89 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.08) out of the maximum possible 12, with higher scores on this scale denoting better sleep health. The distribution of scores was somewhat negative (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) (i.e., more people reported lower sleep health). 59% of participants scored below the median cut-off of the scale (7). In the correlation matrix (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), overall sleep health was significantly correlated to age, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.16, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, and years of education, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.13, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001: with increasing age and years of education, better sleep health was reported. No difference was observed between males (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.92, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.04) and females (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.88, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.10), \u003cem\u003et(\u003c/em\u003e648)\u0026thinsp;=\u0026thinsp;0.26, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.39. Lastly, there was no difference found in sleep health between those respondents who worked from home (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.81, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.02) and those who did not (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.06, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.19), \u003cem\u003et(\u003c/em\u003e648) = -1.45, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.15. A significant, weak, and negative correlation between sleep health and trauma-related stress (as measured by the CRIES-8 scale) was also reported, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.13, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating that higher self-perceived trauma-related distress was associated to poorer sleep health. Significant, weak, negative correlations were also observed between the RU-SATED and depression, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, stress, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.23, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, and anxiety, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.23, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 levels, with decreased sleep health related to increases in self-reported psychopathology.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelation matrix among demographic variables and health outcomes.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1. Age (yrs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2. Education (yrs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.36\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3. Trauma Distress \u003csub\u003eCRIES\u0026minus;8\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4. Sleep Health \u003csub\u003eRU\u0026minus;SATED\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.16\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.13\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.13\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5. Stress \u003csub\u003eDASS\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.18\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.23\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.Depression \u003csub\u003eDASS\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.14*\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.10\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.46\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.23\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.71\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7. Anxiety \u003csub\u003eGAD 7\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.15\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.23\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.83\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.74\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e* Correlation significant at the 0.05 level (2\u0026minus;taled).\u003c/p\u003e\n\u003cp\u003e** Correlation is significant at the Bonferroni\u0026minus;adjusted alpha level of 0.008 (2\u0026minus;tailed).\u003c/p\u003e\n\u003cp\u003eLastly, a three-step hierarchical linear regression analysis was conducted to evaluate the prediction of perceived sleep health (RU-SATED total score) from demographic variables (Model 1: \u003cem\u003eF\u003c/em\u003e(8,638)\u0026thinsp;=\u0026thinsp;2.84, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01, \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003eadj\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e = 0.034), variables relating to COVID-19 (Model 2: \u003cem\u003eF\u003c/em\u003e(28,618)\u0026thinsp;=\u0026thinsp;2.34, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003eadj\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e =.055, \u003cem\u003eF\u003c/em\u003e\u003csub\u003echange\u003c/sub\u003e = 2.09, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01, \u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003echange\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;.06), and the level of quarantine experienced (Model 3). The full model (Model 3) was statistically significant, \u003cem\u003eF\u003c/em\u003e(29,617)\u0026thinsp;=\u0026thinsp;2.12, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01., \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003eadj\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e = .051. However, the addition of the last factor (level of quarantine) did not add to predictive power, \u003cem\u003eF\u003c/em\u003e\u003csub\u003echange\u003c/sub\u003e = .13, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003echange\u003c/em\u003e\u003c/sub\u003e = 0.94, \u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003echange\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;.01. Therefore, the degree to which one was following the restrictions was not a significant predictor of sleep health. The variables that were found to be significant predictors of sleep health (in order of magnitude of contribution to model) were EPII items \u0026ldquo;U\u003cem\u003enable to get enough food or healthy food\u003c/em\u003e\u0026rdquo; (\u003cem\u003e\u0026beta;\u003c/em\u003e = \u0026minus;\u0026thinsp;.156, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001), \u0026ldquo;\u003cem\u003eTested and currently have the disease\u003c/em\u003e\u0026rdquo; (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.139, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02), Age (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.107, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03), EPII items \u0026ldquo;\u003cem\u003eI experience increase in verbal arguments or conflict with other adult(s) in home\u003c/em\u003e\u0026rdquo; (\u003cem\u003e\u0026beta;\u003c/em\u003e = -0.084, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.045) and \u0026ldquo;\u003cem\u003eI experience an increase in workload/responsibilities\u003c/em\u003e\u0026rdquo; (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.082, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.044).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePhysical activity, dietary habits and sleep have consistently been recognized as pillars of health, with sleep disturbances shown to lead to both short-term and longstanding effects on cognitive function, metabolic and cardiac health, quality of life and mortality (Medic et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ramar et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The results reported here highlight the complex inter-relationships between sleep health and a number of demographic, mental health and COVID pandemic-related factors. In our Greek sample, the majority (59%) of respondents scored below the clinical cut-off on a sleep health scale, with mental health problems and the lockdown effects exacerbating sleep difficulties. A large international study comparing sleep practices in 59 countries (~\u0026thinsp;7000 participants), and using the same sleep health measure, reports a much lower 44.4% scoring below the cut-off (Yuksel et al. 2020). This difference is indicative of the considerable mental and physical health burden (sleep problems included) with which Greeks entered the pandemic, being the country adopting the most punitive austerity measures during the Great Recession period that preceded COVID-19 (Economou et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Nena et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLooking at demographic and psychological characteristics, both previously known and new risk factors emerged. Firstly, educational attainment and older age were protective factors for sleep health. Being of younger age has been introduced as a new risk factor for both mental health and sleep deterioration during COVID-19 in other studies (Jahrami et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kolakowsky-Hayner et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003eb; Sachs et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), reflecting the vulnerability of this section of the population to the financial insecurities and social isolation that the pandemic brought with it. No gender difference in sleep health was found when looking at the RUSATED score. The only gender difference observed was an increase in nightmares and bad dreams, compared to before COVID-19 reported by women only. Nevertheless, the disparity in the gender distribution in our sample does not permit us to make inferences based on the present study. A recent meta-analysis by Alimoradi et al. (2020) also failed to find gender differences and attributed the lack of effect of gender on unequal sample sizes in the reviewed studies. For the moment, there is plenty of research showing both pre-existing and pandemic-instigated disparities in sleep health between the sexes that cannot be ignored, reflecting the presence of more prevalent psychosocial stressors in females, such as a gender gap in home, child, elderly care, and pay (e.g., Boll and Lagemann \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Cellini et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mergener et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wade et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe next turned to factors relating exclusively to NPIs that were imposed to prevent virus spread. The forced social isolation measures have been shown to have affected every domain of life (social relationships, employment etc.) as well as physical and mental health. For example, studies are confirming that the pandemic has also created conditions that limited access and utilisation of non-COVID health services, including drops in planned surgeries, doctors\u0026rsquo; appointments, access to medicine etc., with suffering disproportionately from these consequences (N\u0026uacute;\u0026ntilde;ez et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Patel et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tuczyńska et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; WHO, 2020). It has become clear via cross-sectional and longitudinal studies that forced lockdown triggered a deterioration in mental health or significantly exacerbated the illnesses in pre-existing mental health sufferers in several countries, Greece included (Alzueta et al. 2020; Liozidou et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pierce et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Santomauro et al. 2020). In our sleep study, it was found that the presence and degree of psychological distress relating to trauma, depression, anxiety and stress symptomatology was also associated with exacerbations of problems in falling asleep, sleep regularity, timing and duration, sleep satisfaction, and daytime alertness. Note, that the relationship between sleep and mental health has been documented well in research (see for review Witteveen et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), but also in clinical settings: assessment of sleep-related symptoms is embedded in standard clinical practice, where sleep disturbances are seen as core clinical diagnostic features in several disease categories in psychiatric classification manuals (DSM 5 and ICD 11; APA, 2013; WHO, 2022). It is therefore not surprising that the stressful and unpredictable pandemic circumstances have led to an exacerbation of sleep problems.\u003c/p\u003e \u003cp\u003eRelatedly, some situational factors also emerged: facing difficulties in securing enough/healthy food, testing positive for SARS-COV-2, experiencing an increase in verbal arguments between adults at home and experiencing an increase in workload or responsibilities were all predictive of poor sleep health. Casagrande et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) also found that having fallen ill, losing a loved one and number of days spent in confinement were detrimental to sleep health in a large Italian sample of ~\u0026thinsp;2300 people. Similar to our results, Yuksel et al. (2021) found the most significant predictor of sleep health to be conflict in the home, with having lost one\u0026rsquo;s job, not being able to get enough/good quality food, not being able to pay one\u0026rsquo;s bills, and having a hard time transitioning to working from home following suit. The detrimental effect of conflict in the home should be of special consideration, particularly in light of emerging evidence that shows increases in domestic violence during and immediately after the end of lockdown (Campbell \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chatzifotiou \u0026amp; Andreadou \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kourti et al. 2023; Usher et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNote also, that unlike Yuksel et al., we did not find the transition to working from home as contributing to sleep deterioration, as one would perhaps expect. When we compared the total sleep hygiene (RUSATED) score of those who worked from home and those who did not, there was no difference found. This is in contrast to some authors arguing that working from home (via minimal commuting times, more flexible night and wake-up schedules etc.) might enhance sleep health (e.g., Altena et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Robillard et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). One explanation could be that the more flexible schedule would have been positive indeed, was it not coupled with a simultaneous increase in workload and responsibilities (either imposed over-time or by taking advantage of the flexibility). This paradoxical disadvantage of remote work has been discussed since before the pandemic, when several studies showed that the previously considered family-friendly approach of remote work failed as a promoter of work-life balance and was associated with less happiness, more stress and anxiety, feelings of isolation and loneliness, and problems associated with poor ergonomics and home space (e.g., Ferrara et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Henke et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Song and Gao 2020). Since remote work/telework seems to be here to stay well after the pandemic, we need systematic reviews and meta-analyses of the large number of mixed results available, especially in relation to formal home working time versus informal overtime.\u003c/p\u003e \u003cp\u003eAs a final pandemic-related factor, we asked participants how closely they followed social distancing restrictions (quarantine), as a proxy of the level of isolation. We found that the degree of compliance to restrictions was not predictive of sleep disturbances. Our findings contradict both those of Yuksel et al (2021), who found that stricter quarantine was a significant predictor of sleep health, and Scarpelli et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), who in a recent review and meta-analysis found that more severe measures were associated with lower prevalence of sleep disorder (attributed to more flexible wake times, and less fear of getting infected). Perhaps our inability to find a differential impact of degree of social isolation to sleep health reflects sample characteristics: only a 4% in our sample did not follow any of the recommended restrictions around social isolation and traveling. This is arguably low, reflecting the fact that compliance to lockdown measures was generally high among Greeks in comparison to other countries (Fountoulakis et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Skapinakis et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo our knowledge, the present study is a first attempt to systematically evaluate sleep hygiene during the COVID-19 forced social isolation in a Greek sample. However, there are some noteworthy limitations, the most important of which being that sleep health assessment was done using a standardised, albeit self-report, instrument and not via a more objective measure, such as polysomnography or activity tracking. Moreover, these findings might be confounded by the very fact that the pandemic hit as Greeks were exiting a ten-year period of harsh austerity, with detrimental consequences on physical and mental health that potentially affected sleep practices, too. Longitudinal, and not cross-sectional designs are more adept at showing reliable change over time. Lastly, the medium of data collection (an online survey) restricted the sample to those who had internet access.\u003c/p\u003e \u003cp\u003eWhile early non-pharmacological interventions (NPIs) have proven essential in supressing the virus, there does not need to be a compromise between saving lives and preserving mental and sleep health. It is hoped that studies such as ours will inform public policy in cases of future threats. Crucially, policy makers should attend to the needs of populations traditionally viewed as vulnerable (being female, of younger age, unemployed, suffering from mental and physical disabilities, being at risk of violence) when planning responses. In addition, when responding to those threats, policies should not end with protective measures only, but should be coupled with impact-reducing interventions to promote resilience and recovery, accessible to vulnerable populations. Finally, on a more optimistic note, we must be reminded that although a multitude of evidence already exists that point to pandemic-induced increases in mental and physical health problems, these findings are recent and sometimes mixed, and there is no certainty that these negative effects will persists over time, now that we leave the pandemic behind us. Nevertheless, recognizing sleep as one of the pillars of physical and psychological wellbeing makes more research investigating the mechanisms implicated in the bidirectional relationships between sleep hygiene, mental and physical health and societal factors warranted.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests:\u003c/strong\u003e All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study received IRB approval from both host institutions (Autonomous University of Madrid Ethical Committee, Spain, CEI-106-206 \u0026amp; The Scientific College of Greece Human Research Ethics Committee).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e All participants agreed for their anonymized data to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u003c/strong\u003e Data and questionnaires available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e All authors contributed to the study conception and design, material preparation, data collection. Data analysis was performed by Vasiliki Varela and Dimitrios Vlastos. The first draft of the manuscript was written by Vasiliki Varela and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlimoradi Z, Brostr\u0026ouml;m A, Tsang HW, Griffiths MD, Haghayegh S, Ohayon MM, Lin CY, Pakpour AH (2021) Sleep problems during COVID-19 pandemic and its\u0026rsquo; association to psychological distress: A systematic review and meta-analysis. EClinicalMedicine, 36.\u003c/li\u003e\n\u003cli\u003eAltena E, Baglioni C, Espie CA, Ellis J, Gavriloff D, Holzinger B, Schlarb A, Frase L, Jernel\u0026ouml;v S, Riemann D (2020) Dealing with sleep problems during home confinement due to the COVID‐19 outbreak: Practical recommendations from a task force of the European CBT‐I Academy. 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World Health Organization. \u003c/li\u003e\n\u003cli\u003eWorld Health Organization (2022) ICD-11: International classification of diseases (11th revision). \u003c/li\u003e\n\u003cli\u003eXiong J, Lipsitz O, Nasri F, Lui LM, Gill H, Phan L, Chen-Li D, Iacobucci M, Ho R, Majeed A, McIntyre RS (2020) Impact of COVID-19 pandemic on mental health in the general population: A systematic review. Journal of affective disorders. 277:55-64.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Laboratory of Cognitive Neuroscience and Clinical Neuropsychology, SCG - Scientific College of Greece, Athens, Greece.","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sleep, COVID-19, depression, anxiety, stress, lockdown","lastPublishedDoi":"10.21203/rs.3.rs-4265194/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4265194/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAim: Since the declaration of COVID-19 as a Public Health Emergency of International Concern on January 30, 2020, the disease escalated into a global pandemic forcing governments around the world to impose measures that affected all aspects of life. Among other countries, Greece adopted social restriction, lockdowns, and quarantines to reduce transmission from person to person.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSubjects and Methods: This cross-sectional study aimed to investigate the impact of those measures on sleep health in a Greek adult sample. An online questionnaire collected data during from 650 participant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: 60% of responders scored below the clinical cut-off on the RU-SATED, indicating they experienced poor sleep health. Better sleep health was reported with increased age and years of education. On the other hand, higher trauma-related distress, depression, anxiety and stress symptomatology were related to poorer sleep health. No gender differences were observed, and degree of compliance to pandemic restrictions did not influence sleep health. Hierarchical regression analysis indicated difficulty in securing enough/healthy food, testing positive for COVID-19, experiencing an increase in verbal arguments/conflicts at home and an increase in responsibilities were the strongest predictors of poor sleep heath.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusions: Results highlight the importance of maintaining good sleep health as a pillar of general physical and mental health.\u003c/p\u003e","manuscriptTitle":"Psychosocial Predictors of Sleep Disturbances during COVID-19: differential contributions of demographic, psychological, pandemic-related factors to sleep health.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-16 14:48:57","doi":"10.21203/rs.3.rs-4265194/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65e64e18-ca2a-483d-902c-3a50e817f0ed","owner":[],"postedDate":"April 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":30653192,"name":"Psychology"},{"id":30653193,"name":"Psychiatry"},{"id":30653194,"name":"Epidemiology"}],"tags":[],"updatedAt":"2024-11-19T18:37:55+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-16 14:48:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4265194","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4265194","identity":"rs-4265194","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}