key: cord-0702374-fbumgogt authors: Roitblat, Yulia; Burger, Jacob; Leit, Aidan; Nehuliaieva, Liliia; Umarova, Gulrukh Sh.; Kaliberdenko, Vitalii; Kulanthaivel, Shanmugaraj; Buchris, Noa; Shterenshis, Michael title: Stay-at-home circumstances do not produce sleep disorders: An international survey during the COVID-19 pandemic date: 2020-10-26 journal: J Psychosom Res DOI: 10.1016/j.jpsychores.2020.110282 sha: a12ce0db2cd5e58feb06c71a3c08ba1e3ba4f832 doc_id: 702374 cord_uid: fbumgogt Objective The anxiety-related insomnia and other sleep disorders were mentioned as possible side effects of quarantine and stay-at-home conditions. The questions to be explored were: Are there discernable differences in hours of sleep and sleep habits between the normal operational environment and the stay-at-home condition? and How seriously anxiety-induced insomnia or other sleep disorders may affect individuals during the stay-at-home? Methods This international prospective study analyzed results from the sleep-wake patterns questionnaire, daily logs, and interviews. During COVID-19 pandemic, surveys were administered to the healthy volunteers with stay-at-home for 14 days or more, without previous sleep disorders; volunteers were not involved in online education/work daily timetable-related activities. Results We analyzed 14,000 subjects from 11 countries with average stay-at-home of 62 days. The most significant changes in sleep occurred during the first 14 days of stay-at-home. The difference in the sleep duration between weekdays and weekends disappeared. Most of the participants discontinued using alarm clocks. The total sleep time increased in duration up to 9:10 ± 1:16 to the end of the quarantine/stay-at-home (+1:34, p = 0.02). The age-dependent changes in napping habits occurred. Only 1.8% of participants indicated insomnia during the first 14-day period with a decline to 0.5% after two months of stay-at-home. Conclusion During the stay-at-home situation, both duration and timing of sleep significantly differ from those of daily routine and most humans sleep longer than in a schedule-dependent operational environment. An appearance of anxiety-induced insomnia is extremely rare if a healthy individual is already in the stay-at-home situation. The topic of human behavior during quarantine and stay-at-home conditions is extremely understudied [1] . Sleep habits during quarantine were never studied before in detail. General articles dedicated to Ebola and SARS-related quarantines mentioned insomnia as a possible side effect without detailed analysis of the phenomenon [2] [3] [4] . The COVID-19 pandemic has put millions of humans in stay-at-home and self-quarantine situations. The COVID-19-pandemicrelated WHO release and the review on the psychological impact of quarantine mentioned the possibility of "anxiety-induced insomnia" [5, 6] . The topic of sleep habits, sleep disorders, and daily temporal patterns during quarantine is not just a theoretical question. The similar stay-at-home and country "lock-down" events may reappear in the future and psychologists, psychiatrists, public health professionals, and sleep disorders practitioners should be more prepared for such situations. The results might also have implications for unique variations in human chronotype as these variations apply to the optimization of daily productivity once people return to work. The studies of sleep habits of healthy individuals concentrated on sleep duration and sleep timing. For sleep duration, the "eight hours for rest, eight hours for labour, and eight hours for amusement" was accepted as a sound possibility in the 1840s and postulated as true hygiene of sleep in the 1890s [7, 8] . The eight-hours maxim was confirmed in the 20 th century for "normal sleepers" [9, 10] and the researchers of the 21 st century established that sleep duration did not decline over the last 50 years and remains between seven and eight hours [11, 12] . Sleep of Through structured interviews, the participants should provide information on sleep timing and duration in a free conversation manner. The general approach to conducting the interview and the confidentiality of the respondents followed the NSF principles established for the 2005 "Sleep in America poll" [13] . The first 500 respondents who met the inclusion criteria were selected. The topics repeated all items of the questionnaire and touched the variables of the expanded daily log (the same V1 and V2). The main purpose of the interviews was to establish a certain temporal pattern of a participant, appearance or disappearance of sleep-related complaints, and to detect their possible evolutions during the stay-at-home period. During freeresponse conversations, we aimed to grasp some logic behind the possible appearance of sleeprelated complaints of the participants. The participant's permission should be obtained to contact him/her at the end of each week during the stay-at-home. The survey averaged 15-20 minutes in length. Surveys were administered to the volunteers who met the following inclusion criteria: stay-athome conditions for 14 days or more, no chronic diseases, no previous sleep disorders and sleeprelated or mood-related complaints, volunteers do not take sleeping pills, did not work night shifts before quarantine, and were not involved in online education/work-from-home and other daily schedule/timetable-related activities. Education/work-from-home activities without timetables and daily schedules were allowed. Volunteers who were pregnant, had any sleep disorders before the quarantine, mood disorders, take sleeping pills, or were involved in online education/work-from-home daily schedule/timetable-related activities were excluded. The age limit was set from 15 to 60 years. The younger children were excluded because of possible parental influences. The upper limit of 60 years was set because in some surveyed J o u r n a l P r e -p r o o f countries the retirement age for women is 60 and because of age-related changes in sleep habits. The participants were divided into three age groups: adolescents (Group 1, 15-18 y), younger adults (Group 2, 19-39 y), and older adults (Group 3, 40-60 y). The target sample size for each research tool was initially set at 500 participants to keep the margin of error below 5% (4.4% with 95% confidence interval). Due to unexpectedly active responses of volunteers, the sample size for the questionnaire survey was changed to 10,000 (the margin of error ˂ 1%) and the sample size for the simplified log survey was changed to 3,000 (the margin of error 1.8%). The extended log and the interview cohorts were kept at 500. The data were collected in the USA, the UK, Australia, Canada, Israel, Germany, France, Ukraine, Russia, India, and Uzbekistan. Since March 1, the pilot project began and since March 15, when several countries went in a full stay-at-home or "lock-down" condition, the full study was implemented. The data were collected until the end of May. The pyramid system of data collection ("snowball sampling technique") was designed. The primary investigators had spread the survey tools in a friend-to-friend manner, to the collaborators, through an online forum, and via Internet social networks. The collaborators repeated the same procedure country-specific. After that, further dissemination of the questionnaire and the simplified log became uncontrollable contact to contact or online activity. A volunteer had a choice either to fill the questionnaire or to keep the log. The returning of the filled forms was done in the same pyramid manner. The survey was anonymous and all personal data, except age and sex, were not included in the data spreadsheets. Following the Ethics Committees regulations, while the study used mostly online-manner survey, the confidentiality of the participants was maintained in compliance with the requirements of the Data Protection Act 1998 and the subsequent General J o u r n a l P r e -p r o o f Journal Pre-proof Data Protection Regulation (GDPR). All investigators, their collaborators in the countries, and study site staff complied with the requirements of the Data Protection Act 1998 and GDPR concerning the collection, storage, processing and disclosure of personal information and upheld the Act's core principles. This included the creation of depersonalized data spreadsheets, secure maintenance of information, with access limited to the minimum number of individuals necessary for quality control, audit, and analysis. At the end of the study, the online forums and other Internet-related survey activities were immediately terminated. The detailed log instructions were distributed separately by the investigators in the USA, the UK, and Israel. Phone/Skype interviews were conducted in the USA and Israel. The collection of the filled questionnaires was terminated when 10,000 filled forms qualified for further analysis were collected. By selecting the forms, preference was given to the forms that were kept for a longer time. The filled forms with ambiguous answers (multiple responses for a single question, "unsure" answers, questions left blank, etc.) were excluded from the analysis. The collection of the simplified daily logs was terminated when 3,000 filled forms qualified for further analysis were collected. As for the questionnaire, preference was given to the logs that were kept for a longer period. The participants could select either the questionnaire form of the survey or the simplified log by their own choosing, but only one tool could be selected by a participant. The extended log forms were offered to 1,000 volunteers but the properly filled logs arrived only from 543 participants and 500 logs being kept for a longer time were selected. The interviews were conducted among 500 volunteers as planned. At least four weekly interviews should be collected from each participant. The prospective study was approved by the responsible Ethics Committees as a "non- Descriptive analysis was provided to describe basic and general information about the demographic and specific question results. The results include the distribution of survey participants by age and sex classifications. In most cases, the categorical data specific to the amount of sleep obtained was ordinal. Sleep duration and sleep patterns data were analyzed using univariate analyses of covariance (ANCOVA) with age group and gender as fixed factors. The difference between "time in bed" and "total sleep time" was taken into account. The questionnaires and logs reported time in bed because no one can record when he/she fell asleep. The difference between these two conditions was established to be 10% on average [12, 15, 16] . The initial step of the statistical analysis of sleep duration included the 10% reduction from the reported numbers. We used oneway analysis of variance (ANOVA) to compare the data from three age groups (df1 = 2, df2a = 13,999, df2b = 12,380). Within the same group, the longitudinal analysis (before stay-at-home, two weeks, one months, and two months of stay-at-home) was performed by repeated-measures ANOVA (df1 = 3, df2a = 13,999, df2b = 12,380). While decimal statistics does not apply to minutes, SPSS TIME.HMS function was applied. Chi-square tests were used to analyze age and gender distribution and the questionnaire or log responses for differences in sleep habits distribution between groups. The correlation analysis (r value) was performed between V1, V2, and total sleep duration (V3) and age and sex. The correlation of presence/absence of regular naps was also performed against these two fixed factors. The r˃0.60 was counted as the significant correlation. All statistical analyses were performed using SPSS (version 19.0, SPSS Inc., Chicago, IL). A significance threshold of p˂0.05 was used for all analyses. Data on home sleep habits were analyzed for the 14,000 subjects (Tables 2 and 3 ). The average stay-at-home for the whole cohort was 62 days, mainly between March 15 and May 15. The sleep habit-related data were derived from the logs (n=3,500; the margin of error 1.7% at a 95% confidence interval; 3,500 x 62 days = 217,000 responses for V1 and V2), interviews (n=500, the margin of error 4.4%; 500 x 7 or 8 interviews = 3,872 responses), and daily pattern-related filled questionnaires (n=10,000, the margin of error ˂1%; 10,000 x 2 or 3 filled parts = 29,670 responses), and 14,000 cases with sufficient data were analyzed. The agreements between the data collection tools were: the logs vs. the interviews -97.8% agreement; the log vs. the The most significant changes in sleep habits occurred during the first 14 days of stay-athome; the first week was the most critical. The difference in the sleep duration between weekdays and weekends disappeared. Most of the participants discontinued using alarm clocks. Table 3 indicates that the total sleep time increased in duration up to 8:52 ± 1:07 (+1:16 against pre-stay-at-home condition, p=0.03) after the first 14 days with a subsequent increase to 9:10 ± 1:16 to the end of the quarantine/stay-at-home (+1:34, p=0.02). The age-dependent changes in napping habits occurred. In general, daily temporal patterns and sleep habits of the majority of the participants underwent significant changes that were developing further during a prolonged stay-at-home condition. According to the data extracted during interviews and from questions Q12, Q17, Q22, and Q26 of the questionnaire, only 184 participants (1.8% from 10,500) indicated the appearance of insomnia during the first 14-day period. This amount dropped to 37 J o u r n a l P r e -p r o o f participants (0.5%) after two months of stay-at-home. Another 38 participants (0.5%) indicated their sleep pattern as "unusual" without further clarification. Group 1 was the smallest group of the participants because many high school students were engaged in various Zoom-related scheduled educational activities. Before stay-at-home, the absolute majority of the participants used alarm clocks, and about one-third of them, mainly girls, practiced midday napping (Tables 4 and 5 ). The wake-up time was the most variable in this group with one-hour standard deviation because bell schedules in different high schools were set for the first bell from 6:30 a.m. to 10:00 a.m. as extremes and from 7:15 a.m. to 8:40 as a general pattern. Table 3 indicates that to the end of the stay-at-home period, the sleep duration of the adolescents was 58 min longer than during the pre-quarantine period (9:34 ± 0:24 vs. pre-stay-athome 8:36 ± 1:20; p=0.05) and Table 5 shows that the number of nap users significantly decreased. Before stay-at-home, the sleep duration of 586 adolescents (19%) was less than 8 h. This number dropped to 47 (1.5%) after two months of the stay-at-home. Group 2 participants remained relatively stable in their daily patterns if compared with the adolescents, but their sleep duration also increased from 7:24 ± 0:17 to 8:20 ± 1 h (+56 min, p=0.05. Before stay-at-home, the sleep duration of 1011 younger adults (21.4%) was less than 7 h. This number dropped to 229 (4.8%) after two months of the stay-at-home. The Group 3 participants increased their sleep duration from 7:33 ± 0:40 to 9:12 ± 1:27 (+1:49, p=0.02) and the number of nap users was significantly increased. Before stay-at-home, the sleep duration of 1148 older adults (18.5%) was less than 7 h. This number dropped to 117 (1.9%) after two months of the stay-at-home. No sex-related correlations were detected except J o u r n a l P r e -p r o o f Journal Pre-proof that girls of Group 1 used napping more often before the stay-at-home (r=0.66) and that Group 3 males used napping more often during the stay-at-home (r=0.70). Before the stay-at-home, 74.1% of all respondents used morning alarms (Table 4) Before the stay-at-home, 16 .5% of all respondents practiced napping regularly (Table 5 ). In Group 1, 36.3% practiced napping regularly while only 7.5% of young adults (Group 2) indicated this habit (p=0.002). For Group 3, 13.5% practiced napping (p=0.006 against adolescents) with longer napping duration. The correlation with the female gender (r=0.66) was found in Group 1 and the correlation with the male gender (r=0.67) in Group 3. During the first 14 days of stay-at-home, the number of nap-users among adolescents dropped to 8.6% (p=0.003) J o u r n a l P r e -p r o o f with a subsequent decline to 7.1% after two months irrespective to their sex. In Group 2, the percentage of nap-users increased to 10% during the first 14 days with slow further growth to 11.3% after two months of stay-at-home. In Group 3, this tendency was more significant when 20.2% of the participants introduced napping in their daily life during the 14 days of the stay-athome period with a subsequent increase of this percentage to 29.2% after the two-month period (p=0.04). More than one nap per day was a very rare habit for the participants during the first 14 days of stay-at-home (0.2%). After two months of stay-at-home, 1% of the respondents practiced two or more naps a day (p=0.03). Our results that describe sleep duration and sleep timing of healthy individuals in a prequarantine environment are in concord with the previously reported data [9] [10] [11] [12] [13] 16] . The main part of our results indicates that both the duration and timing of sleep of stay-at-home individuals significantly differ from those of socially and economically predesigned daily routine conditions. The changes in sleep duration were beneficial. For example, the recommended amount of nocturnal sleep for adolescents was estimated as eight to 10 hours [17, 18] . The emerging literature reported that from 18% to one-third of adolescents got insufficient sleep during normal life [17, [19] [20] [21] . During stay-at-home, the sleep duration of the majority of our participants in all Table 1 . Sleep patterns during the stay-at-home conditions questionnaire that was used in the current survey. Please fill this questionnaire IF you are 15-60 years old, are in quarantine or other stay-at-home conditions for 14 days or more, had no previous chronic diseases, sleep disorders, and sleeprelated complaints, do not take sleeping pills, did not work night shifts, and are not currently involved in online teaching, learning, work-from-home and other daily schedule/timetablerelated activities. Please DON'T FILL this questionnaire if you had any sleep disorders before the quarantine (sleepiness, wakefulness (insomnia), sleep apnea, etc.), take sleeping pills, or if you are involved in online teaching, learning, work-from-home and other daily schedule/timetable-related activities during the stay-at-home period. Pregnant women should not fill the questionnaire. If your stay-at-home condition is prolonged, please fill this questionnaire again after 1 month at home and 2 months at home. Q5a. When did you go to bed regularly? Time: ________ Table 4 . 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YES NO (Highlight the answer) Q10a. If YES, did you change your sleep duration? How? _____________________ Stay-at-home for 14 days When do you usually wake up in the morning? Time: ________ Q14. Do you currently practice midday napping/siesta regularly? YES NO Q14a. If YES, specify the time (from -till) or for how long: _____________ Q15. In general, how many times do you sleep daily now? ONCE TWICE THREE times Stay-at-home about a month: Q16 Do you currently practice midday napping/siesta regularly? YES NO Q19a. If YES, since when? Day: _____________ Q19b. If YES, specify the time (from -till) or for how long: _____________ Q20. In general, how many times do you sleep daily now? ONCE TWICE THREE times Stay-at-home about two months: Q21 When do you usually wake up in the morning? Time: ________ Q24. Do you still currently practice midday napping/siesta regularly? YES NO Q24a. If YES, since when? Day: _____________ Q24b. If YES, specify the time (from -till) or for how long: _____________ Q25. In general, how many times do you sleep daily now? ONCE TWICE THREE times Q26 Demographic and general data of the surveyed cohort (n=14,000) obtained from filled questionnaire forms, daily logs, and during interviews Average stay-at-home During the analysis, 10% of the time was deducted to turn "time in bed" into actual "total sleep time". Standard deviations are given in brackets Evening bedtime Morning get-up time :34) 14 days stay-at-home Evening bedtime Morning get-up time :07) 1 month stay-at-home Evening bedtime Morning get-up time 2 months stay-at-home ((obtained from 12 Evening bedtime Morning get-up time Sleep duration alarm users 8 h 2 months stay-at-home ((obtained from 12 Table 5 .The data of the survey related to napping. The number of nap users is given against the total number of participants in each age group. Standard deviations are presented in brackets.