and increase the risk of mental health problems (Leigh-Hunt et al., 2017) . Sivertsen et al. (2019) have shown that young adults in a range between 18 and 35 years old tend to have a high and growing prevalence of sleep problems, and young adults make extensive use of social media devices that interact with daily activities, including sleep (Gradisar et al., 2013; Orzech, Grandner, Roane, & Carskadon, 2016) . Social media platforms offer an opportunity to ameliorate social isolation, but the use of digital media near bedtime could have a broadly negative effect on sleep outcomes of young adults (Orzech et al., 2016) .
We were interested in characterizing the change in digital media use before going to bed, in sleep quality and timing, and in the subjective experience of time passing, and their relationship with depression, anxiety and stress levels. To achieve this, we administered a cross-sectional survey to non-hospitalized Italian residents. In this survey we asked participants to think about the previous week (March 17-23, which was the second week of the lockdown) and the period prior to the first week of February (February 3-10, before any restriction in any Italian area).
Participants completed an anonymous online survey, after reading the written consent form and explicitly agreeing to participate in the survey. The survey was shared via social media for a limited time window (from March 24 to 28, 2020), targeting people from 18 to 35 years old to obtain a homogenous sample of responders, because young adults (e.g., ages 18-35 years) are likely to be heavy digital users and they are especially at risk of sleep disturbance (Levenson, Shensa, Sidani, Colditz, & Primack, 2017; Sivertsen et al., 2019) .
There was no monetary or credit compensation for participating in the study. The study protocol was approved by the Ethics Committee of the Centre for Research and Psychological Intervention (CERIP) of the University of Messina and was conducted in accordance with the Declaration of Helsinki. A total of 1,342 participants completed the survey. From this sample, we excluded 26 participants who reported having been infected by COVID-19, 17 participants with age >35 or <18 years and one outlier. The final sample consisted of 1,310 young adults living in the Italian territory. Data reported in this study were part of a wider research project designed with multiple purposes regarding the psychological impact of home confinement in Italy, and other data with different purposes will be presented elsewhere.
Perceived sleep quality in the previous week (March 17-23, the second week of the lockdown) and prior to the first week of February (February 3-10, before any restriction in any Italian area) was assessed using the Italian version of the Pittsburg Sleep Quality Index (PSQI; Curcio et al., 2013) . Scores higher than 5 indicate poor sleep.
From the PSQI we also derived information about how many hours they spent in bed (TIB; hr), at what time participants went to bed to sleep (bedtime) and at what time participants woke up in the morning (wake time).
The use of digital media was assessed by asking participants to report their frequency of digital media activity choices in the 2 hr before bedtime in the previous week and prior to the first week of February. We selected 10 digital media activities based on the work of Orzech et al. (2016) , such as computer work, Email/instant messaging, social networking sites, videogames, surfing the internet, video calls/calls on phones, watching online videos, reading e-books, watching TV/DVDs, and watching TV series. Response options ranged from "never" to "every day" and were transformed into weighted responses to estimate total digital media use per week (range, 0-70), as previously done by Orzech et al. (2016) .
An ad-hoc questionnaire was created to assess the ability of participants to keep track of physical time (Time Track, three items referring to difficulties in remembering the day of the week, remembering the day of the month and keeping track of the time of day), to assess the subjective experience of time (Time Expansion, two items referring to the feeling of boredom and that time is passing slowly) and to assess the regularity of daily routines (Schedule, two items referring to maintaining routines such as meal times and bedtimes).
The short-form version of the Depression Anxiety Stress Scales (DASS-21) was used to assess stress, depression and general anxiety (Bottesi et al., 2015) . Scores from each subscale were summed up and multiplied by two to suit the original 42 items. The cut-offs for moderate symptomatology for depression, anxiety and stress are ≥14, ≥10 and ≥19, respectively (Lovibond & Lovibond, 1996) .
Of the 1,310 participants (M age = 23.91 ± 3.60 years), 501 were workers (M age = 26.0 ± 4.06 years, 315 F) and 809 were university students (M age = 22.6 ± 2.53 years, 565 F). One-fourth (24.2%) of the entire sample reported moderate to extremely severe symptoms of depression, 32.6% of the sample reported moderate to extremely severe symptoms of anxiety, and 50.12% of the sample reported moderate to extremely severe symptoms of stress (Figure 1a) .
Under the restriction, our sample increased the frequency of digital media use in the 2 hr before going to bed from ~27 activities a week before the restriction to ~31 activities under lockdown (F 1,1,308 = 113.37, p < .0001, η p 2 = .08).
Looking at changes in sleep habits, we observed a significant increase of the PSQI score under the restriction (F 1,1,308 = 67.47, p < .0001, η p 2 = .05), with no difference between students and workers (all ps > .187, Figure 2a ). The proportion of poor sleepers (i.e., PSQI > 5) increased from 40.5% to 52.4% (χ 2 1 = 84.50, p < .0001; log odds ratio = 1.070 [CI = 0.84-1.30]; Figure 1b) . Sleep timing changed dramatically, with all participants going to bed later under restrictions (F 1,1,308 = 384.1, p < .0001, η p 2 = .22; Figure 2b ). On average, bedtime was delayed by ~41 min in both workers and students. The restrictions had an even stronger effect on wake time (F 1,1,308 = 535.29, p < .0001, η p 2 = .29), in particular in workers (F 1,1,308 = 22.25, p < .0001, η p 2 = .02; Figure 2c ), who started to wake up about 1 hr and 13 min later than usual, whereas students delayed their wake time by ~45 min. The later wake time resulted in a generally longer TIB under restrictions (F 1,1,308 = 51.08, p < .0001, η p 2 = .04), which was mainly driven by workers (F 1,1,308 = 25.60, p < .0001, η p 2 = .02; Figure 2d ), who spent ~26 min more in bed than before the restrictions (change for students: ~5 min).
Regarding the experience of time, the lockdown induced a signif- Also, they experienced an expansion of time during the lockdown (F 1,1,308 = 188.05, p < .0001, η p 2 = 0.13), with people increasingly feeling a sense of boredom, and they felt stuck in time about five times in the week compared to 3.5 times before lockdown.
We observed that the change in sleep quality (PSQI global score) was stronger in participants with a high DASS-21 score (i.e., participants with higher symptoms of depression, anxiety and stress; r = .27, p<.001), in particular in students ( Figure 3a) . Interestingly, the increase in subjective elongation of time was moderately associated with poorer sleep quality (r = .33, p < .001), in particular in workers (see Figure 3b ), but mildly associated with the increased use of digital media (r = .15, p < .001). Lastly, the increase in digital media use before going to bed mildly affected sleep habits; that is, sleep latency (r = .10, p < .001), bedtime (r = .09, p = .001) and wake time (r = .13, p < .001), but not sleep quality (r = .04, p = .166).
In this cross-sectional study, we investigated the impact of the Italian restriction measures on individuals' daily habits, such as sleep-wake rhythms, digital media use and the experience of time. As expected, during the lockdown people increased the usage of digital media near bedtime. However, this change in digital media use did not affect sleep habits. Nevertheless, already in the second week of the lockdown (March 17-23), sleep-wake rhythms markedly changed, with people going to bed and waking up later, and spending more time in bed, but, paradoxically, also reporting a lower sleep quality.
The decrease in sleep quality was stronger for people with a higher level of depression, anxiety and stress symptomatology and also associated with an increased feeling of expansion of time.
Although this is a partial snapshot of the current Italian situation and does not consider adults older than 35 years and children and adolescents, our data seem to confirm the evidence already observed in quarantined individuals (Brooks et al., 2020) , showing that people in lockdown are experiencing negative psychosocial changes, which have an impact on well-being (e.g., sleep disturbances, depression and anxiety). As stated by a task force of the European CBT-I Academy (Altena et al., 2020), during total lockdown individuals' sleep habits are challenged by several factors (i.e., reduced exposure to sunlight, reduced physical activity and psychological distress.
We also think that the lack of social zeitgebers, such as regular work schedules and social activities, as well as changes in living conditions (e.g., moving to parents' house), are strongly affecting sleep habits under restrictions. Of note, our data were collected before the F I G U R E 1 (a) Frequency of participants reporting moderate symptoms of depression, anxiety and stress as derived by the Depression Anxiety Stress Scales (DASS)-21 scores. (b) Frequency of participants with a Pittsburg Sleep Quality Index (PSQI) score ≤ 5 and > 5 before and during the lockdown F I G U R E 2 Changes in (a) Pittsburg Sleep Quality Index (PSQI) total score, (b) time in bed, (c) bedtime and (d) wake time as a function of the presence of the lockdown and the status (worker or student) of the participants. Error bars represent confidence intervals F I G U R E 3 Change in Pittsburg Sleep Quality Index (PSQI) global score (before lockdown scores minus during lockdown scores) as a function of (a) Depression Anxiety Stress Scales (DASS)-21 total score and (b) time expansion change in students and workers