As of November 8th 2021, a total of 2,840 participants signed up for the online “Time Social Distancing” study in 12 countries (Argentina, Canada, Colombia, France, Germany, Greece, India, Italy, Japan, Turkey, United Kingdom, United States of America). The attrition rate was predictably very important in the course of the longitudinal study: 439 participants finished all tasks in the first session (S1; Table 1 and Supp. Fig. 1) conducted during the first lockdown; 200 participants finished the second session (S2) and 244 the third session (S3) which took place outside the initial lockdown confinement and about 2 weeks and 3 months after it, respectively. In some countries (France and Italy) a shortened fourth session was conducted (S4) on the same participants during their second lockdown with 275 participants. At least a year later, starting in May 2021, as restrictions started to be lifted in some countries, a control pool of naïve participants was recruited in each country. As of November 8th 2021, 243 participants completed the control session. This control population was tested on the full set of questionnaires and tasks originally tested in S1. As of November 8th 2021, these tests are finished in some countries (e.g. France, Japan, Italy, Germany), ongoing (e.g., Greece, Turkey) or planned (e.g., Argentina) in others.
In all sessions, participants reporting drug usage and psychiatric disorders were a priori excluded from data collection; some of the included questionnaires otherwise allow for an evaluation of depression, stress, anxiety and attenuated symptoms of psychosis. Data from Colombia, UK, and USA were too few to be included and were a priori discarded from most analyses (although made available in the database). Due to the exceptional nature and speed of change in governmental policies, experiments started during the first lockdown or state-of-emergency of each country in 2020 (Fig. 1) and continued longitudinally at a different pace according to local policies. We report in Fig. 1 the full demographics of the database during the experiments along with lockdown dates and general timelines of the study.
All participants were provided with full instructions and signed an online consent form following the Declaration of Helsinki (2018) and the ruling of Ethical committees. Participants were provided with a contact email if they had any questions before proceeding. The approval to run the study internationally was obtained from the University Paris-Saclay (CER-Paris-Saclay-2020-020). We also sought local approval for each country: Comité de Etica de la Universidad Nacional de Quilmes CE-UNQ No 2/2020 (Argentina); Université Laval, 2020-114 / 14-04-2020 (Canada); Institute for Frontier Areas of Psychology and Mental Health, Freiburg, IGPP_2020_01 (Germany, Switzerland, Austria); Ethical Committee for the Psychological Research of the University of Padova (Italy); Institutional Ethics Committee, Indian Institute of Technology Kanpur, IITK/IEC/2019-20/18-Apr-20/I (India); The Institutional Review Board of the University of Tokyo, #705 (Japan): UCLA Office of the Human Research Protection Program, IRB#20-000612 (USA); Koç University, 2020.113.IRB3.053 (Turkey).
Data Acquisition Procedure
We used the Gorilla Experiment Builder (www.gorilla.sc) to build and host our study (Anwyl-Irvine et al., 2019) in several languages and countries. The original project was designed in English. French, Japanese, Italian, Greek, Portuguese, German, Spanish, and Turkish were cloned from the original English templates, translated, and beta-tested by the local teams, and eventually adapted to the needs or cultural specificities of the country. All questionnaires and tasks are freely accessible in English (and other languages, see below) under the Gorilla Open Materials Attribution-NonCommercial Research-Only licensing: https://app.gorilla.sc/openmaterials/278377.
In most countries, participants were recruited by means of general advertisement using institutional newsletters and/or outside the institution through social media channels. In Japan, participants were recruited through an agency or online (half of the participants for the control session); all participants were given monetary rewards for completing each session. In France, participants in the control session were given an option to receive a small compensation for their participation and ~43% of them chose so (80 out of 184 participants). In Turkey and Greece, a group of participants was recruited through classes and compensated with bonus course credits.
General information was provided in different languages and updated over time for each country on a specific web page (https://brainthemind.com/covid19/) as well as locally in printed form (https://osf.io/359qm/). When participants connected to the protocol website, they were first provided with general information about the study and asked to provide their consent. Then, they were invited to create an anonymized public identification, which they kept for the rest of the study. Participants could leave the website and come back where they stopped at any time. They were free to stop the experiment when they wanted to. Any technical issue, bug, or any problem participants would have was handled by email.
The full experimental protocol consisted in three to four longitudinal sessions (S1, S2, S3, S4) and one control session (SC, new participants). In all sessions, participants went first through a series of questionnaires administered in a random order across participants, which they had to take once per session for the majority of them. After the series of questionnaires, they entered in a series of diverse behavioral tasks presented in pseudo-random order (latin-square design) across participants. Each task was presented up to three times within a session. In the course of the study, the number of runs was reduced to lighten up the requirements of the study. A general insight on the full session is described in Supp. Fig.1 and Table 1. Both provide a comprehensive description of the content of each session. A detailed description of questionnaires and tasks used in the study is provided below.
We included an extensive number of questionnaires that have been (cross-)validated in different languages and in several countries as well as designed new ones. Answering the first series of questionnaires took about an hour. We designed a Confinement Tracker questionnaire and an Isolation Questionnaire adapted to the circumstances to provide basic information on the state of lockdown (Supp. Mat). We included the UCLA Loneliness Scale (Russell, 1996; Russell et al., 1980) which provides several metrics of self-reported loneliness. The clinically-oriented Hospital Anxiety and Depression Scale or HADS (Crawford et al., 2001) provides reliable measures of the state of anxiety and depression of participants. The PQ16 (Ising et al., 2012) was used to screen participants’ attenuated symptoms of psychosis. Mindfulness was assessed using the Freiburg Mindfulness Inventory or FMI (Walach et al., 2006). Circadian preferences and sleep disturbances were assessed using the Morningness-Eveningness Questionaire reduced version or rMEQ (Randler, 2013), the ultra-short version of the Munich Chronotype Questionnaire μMCTQ (Ghotbi et al., 2020), as well as monthly and weekly versions of the Pittsburgh Sleep Quality Index or PSQI (Buysse et al., 1991; Smyth, 1999), and a daily sleep quality questionnaire (Supp. Mat). The general personality traits of participants were assessed using the Big Five Inventory or BFI-10 (Rammstedt, 2007; Rammstedt & John, 2007). The Zimbardo Time Perspective Inventory or ZTPI (Zimbardo, 1990; Zimbardo & Boyd, 2015) provides a general assessment of the individual’s temporal orientation trait (Sircova et al., 2014). The attentional orientation trait of participants was assessed using the Attentional Style Questionnaire or ASQ (Kraft et al., 2019; Van Calster et al., 2018).
Table 1: Overview of tasks and questionnaires. Sessions 1 and 4 took place during the first and the second lockdown, respectively. Sessions 2 and 3 were set at least 2 weeks and 3 months after the first lockdown. Thus, sessions 1, 2, 3, and 4 tested the same set of participants longitudinally in and out lockdown. The Control session tested a group of naive participants on the same set of questionnaires and tasks as those tested in Session 1 (during the first lockdown). A detailed description of Session 1 is provided in Supp. Fig.1.
The vast majority of studies in time perception use prospective timing tasks in which participants know beforehand they will be asked to estimate the duration of an upcoming event or stimulus (Block et al., 2018). While helpful (see below for prospective duration tasks), this paradigm also falls short of capturing temporal judgments that are commonly made retrospectively in daily life. Retrospective temporal judgments require individuals to make an estimate of elapsed time since a past event or during an activity that just happened without them knowing a priori they will have to time (Block et al., 2018; Grondin & Plourde, 2007; Hicks, 1992; Zakay & Block, 1997). Cognitive components (e.g., attention and memory) are considered to be differentially involved during retrospective vs. prospective timing (Block et al., 2018) with retrospective duration estimates assumed to engage episodic memory processes. In the Blursday project, we included retrospective duration estimations (Supp. Fig. 2) at several moments after a series of questionnaires or after specific tasks. Herein, we report the first retrospective duration estimate participants had to make in the study, which followed a series of initial questionnaires and thus spanned a scale of minutes to hours. The outcomes are included in the Results section and illustrated in Figure 4.
Passage of Time Judgments
Passage of time judgments can be used to estimate the subjective feeling that time passes otherwise commonly referred to as the “flow of time” (Thönes & Stocker, 2019; Wearden, 2015). In this study, passage of time judgments were either implemented as Visual Analog Scales (VAS) ranging from “very slow” to “very fast” or as Likert scales offering a categorical choice between: “very slow”, “slow”, “normal”, “fast”, and “very fast”. Like for retrospective duration estimates, we used passage of time judgments after several tasks during the study by asking participants to report how fast time felt in a given lapse of time (e.g., Supp. Fig. 5). Herein, we report the passage of time judgments that were estimated using a VAS and over the scale of the “last few days” (Supp. Fig. 2) in the Results section.
Temporal landmarks and event recording
By analogy to spatial landmarks, temporal landmarks are salient events that have been time stamped in memory. For instance, one’s birthday tends to be an important landmark. One way to assess the existence of temporal landmarks is to evaluate the speed (response times) and ease (error rate) with which one answers a question about a point in time. Chronometry and performance can be driven by the psychological distance of that point in time from the operative landmark in one’s temporal cognitive map. Temporal landmarks can be culturally and autobiographically idiosyncratic. For instance, when participants are asked to answer as fast and as accurately as possible “What day is it?”, the closer a day is to a cultural temporal landmark (e.g. Sunday in Catholicism or Shabbat in Judaism), the faster the responses and the lower the error rates (Koriat et al., 1976; Koriat & Fischhoff, 1974). In this study, we prompted participants at various times with the question “What day is it today?”, as well as asked them to report an important event for them on that same day (Supp. Fig. 2). The distribution of the collected responses times during lockdown in all participating countries are illustrated in Fig. 2d.
Subjective Temporal distance
An estimation of subjective temporal distance consists in asking participants to estimate how far away an event feels for them. Subjective temporal distances involve episodic memory processes and the abstraction of temporal relations between events (Friedman, 1993; Liberman & Trope, 2014). Herein, we asked participants to use a VAS to report how far away their first day of lockdown felt with respect to the moment at which they were asked this question (i.e., the present). This subjective temporal distance provides a subjective measure of elapsed time at the scale of days to weeks and months as recalled by the participant (Supp. Fig. 2). We also assessed participants’ subjective distance to a week and a month ahead, to test their future orientation. Although subjective distances may be related to the actual passage of time, people may feel more or less close to a past event regardless of its actual temporal distance (Ross & Wilson, 2002). The outcomes of these ratings are included in the Results section and illustrated in Fig. 5.
Fluency tasks: Semantic, Phonemic, and Time scales
Verbal fluency tasks involve reporting as many words as possible within an imparted lapse of time, based on phonemic or semantic criteria (Henry & Crawford, 2004). These tasks were originally developed for neurolinguistic and cognitive assessments. For instance, a semantic fluency task consists of asking participants to report as many animals as possible in 60 seconds (s); this was the semantic fluency task included in our study (Supp. Fig. 3). Similarly, the phonemic fluency task consisted here of reporting as many words as possible starting with the letter ‘P’ in 60 s. In addition to classic verbal fluency tasks, we included past and future event fluency tasks to assess the accessibility of mental representations of life events that participants experienced in the past or that they plan for the future (D’Argembeau et al., 2010). These fluency tasks took the form of a question “Write as many events as possible that occurred last week/moth/year]” for past fluency or “that will happen next [week/month/year“ for the future fluency tasks (Supp. Fig. 3). Hence, these fluency tasks tested the scales at which the fluency was assessed, namely over a week, a month, or a year. An additional semantic fluency task inquiring about associations with the word “time” was tested by simply asking participants to report as many spontaneous associations as possible they had with this word. All fluency tasks in the Blursday database were 60 s long and the number of collected items was unlimited.
Prospective duration estimation while counting up or down
When participants prospectively estimate a lapse of time, both attention and working memory influence their duration estimates. The demonstration of this influence is often based on a dual-task paradigm in which a participant is asked to perform both a temporal and a nontemporal task. Several nontemporal tasks have been used to show the impact of attention or working memory on prospective judgments of time (Brown, 1997; Grondin & Macar, 1992; Macar et al., 1994). Amongst these tasks, there is the possibility to ask participants to perform a counting task (Brown, 1997), a strategy that is adopted in the present investigation. Herein, participants were prompted with a prime number and asked to count up (addition) or down (subtraction) in steps of 3 or 7 as a way to control the difficulty of the task (Supp. Fig. 4). Following a trial, participants were asked to report the number they reached as well as the amount of time spent doing the task (which could be, unbeknownst to participants, either 12 s or 24 s).
Prospective duration estimation while performing an n-back task
Level of processing in working memory lengthened temporal production presumably by slowing down temporal integration (Fortin & Breton, 1995). One means to further explore the influence of working memory on time estimation is to use a parametrically variable n-back task in which a sequence of letters is displayed on the screen and participants decide on a trial-by-trial basis whether the displayed letter is identical to the previous one (n = 1) or to the one two letters before it (n = 2) and so on. It has recently been shown that increasing the working memory load (increasing the n) may proportionally shorten the prospective estimation of duration whereas paying attention to time may lengthen it in an additive fashion (Polti et al., 2018). In this study, we asked participants to perform an n-back task (n = 1 or n = 3) and to report how long the trial was (in minutes:seconds) as well as how fast time felt on a Likert scale. Unbeknownst to participants, a trial could last 45 s or 90 s (Supp. Fig. 5).
Duration production and metacognition
Duration production is another prospective timing task which consists of asking participants to estimate a time interval using overt motor behavior. Herein, participants were asked to produce 3.6 s by pressing the spacebar to initiate their time estimation and, once they considered that 3.6 s had elapsed, pressing the spacebar again (Supp. Fig. 6). Following each duration production, we asked participants to assess their performance, which constitutes a metacognitive judgment task, and provide an assessment of temporal error monitoring (Akdoğan & Balcı, 2017; Kononowicz et al., 2019). In temporal production tasks, the substantial variability within individuals that is observed is assumed to result from the endogenous timing uncertainty between trials. The statistical features of this timing variability and its relation to the time intervals being judged has been one of the primary focuses of the psychophysical study in interval timing (Grondin, 2001). The fact that organisms can access their level of endogenous timing uncertainty as a form of temporal metacognition (Akdoğan & Balcı, 2017; Kononowicz et al., 2019) might serve optimal temporal decisions in animals and humans (Balci, Freestone, et al., 2009). Hence, this novel metacognitive assessment of temporal judgments was included here by asking participants to not only evaluate the signed error magnitude of their temporal production (using a VAS) but also to rate their confidence either of their temporal production (Turkey) or of their metacognitive judgment (most countries). The descriptive statistics of the duration productions (s) for all participating countries in S1 are illustrated in Fig. 2b.
Spontaneous finger tapping (Free tapping)
Spontaneous motor tempo, i.e., the rate at which an individual taps in the absence of any timing cue, is universally situated between around 1 Hz and 4 Hz with a bimodal or even trimodal distribution of the intertap intervals (peaks at around 250, 500 and 1000 ms; Hammerschmidt et al., 2021). The rate at which participants tap is assumed to reflect the speed or the period of a still largely unknown timekeeper, and it has been shown to be sensitive to alterations such as aging (McAuley et al., 2006; Turgeon & Wing, 2012). This has been argued to be because spontaneous tapping tasks are too simple to be compensated by alternative compensatory mechanisms i.e., they are not cognitively penetrable (Turgeon et al., 2016). Basic information about the task is provided in (Supp. Fig. 7) and the descriptive statistics of the inter-tap-intervals (ITIs) for all participating countries in S1 are illustrated in Fig. 2a.
In the field of motor timing, the classical synchronization-continuation paradigm (Semjen et al., 2000) consists of asking participants to synchronize their finger tapping with an auditory metronome and then to continue finger tapping with a sequence of constant intervals at the pace they initially synchronized with (Wing & Kristofferson, 1973). In the continuation phase, the variability of the ITIs is the key dependent variable of interest (Wing & Kristofferson, 1973). When the stimulus period is varied parametrically, an auto-correlation analysis of the series of produced intervals can be used to sort out the part of observed variability due to the temporal component of the task (associated to the underlying timing mechanism) and the one due to the implementation of the intervals with finger taps (the motor component). The synchronization phase, also known as paced finger tapping, is one of the simplest tasks to study sensorimotor synchronization, which has been argued to capture the ability of coordinating one’s own movement with an external metronome (Repp & Su, 2013). In paced finger tapping, it is the asynchrony (the time difference between response and stimulus) which is the fundamental variable of interest (Chen et al., 1997), both for isochronous and for perturbed sequences (Bavassi et al., 2013). A succinct illustration of the task used in the study is provided in Supp. Fig. 8. We tested two conditions: tapping in-sync or out-of-sync with the stimuli. The measured asynchronies in the synchronization task and the ITIs in the continuation task during lockdown are illustrated in Fig. 2a for all participating countries.
Foreperiod paradigm and implicit timing
The implicit extraction of temporal regularities from the environment allows forming temporal predictions and orienting attention to particular moments in time (Nobre & Van Ede, 2018), which can lead to more efficient behavior, such as faster response times, or improved perceptual sensitivity (Cravo et al., 2011; Herbst & Obleser, 2019). Here, we implemented an implicit timing task (Supp. Fig. 9), in which we varied the foreperiod (the time interval between a cue and target tone), such that the duration was either fixed (hence predictable) or variable (non-predictable) throughout a block, and measured response times as an index of efficient temporal prediction. The measured reaction times (RTs) in S1 for all participating countries are illustrated in Fig. 2c.
Delay discounting refers to the devaluation of the reward amount as a function of delay to its receipt (Loewenstein, 1988), making the amount but also the proximity of the reward an important factor in determining the choice behavior of participants when they are asked to choose between two options. Some individuals may prefer the immediate reward over a delayed reward even when the amount offered immediately is substantially less than the amount offered after a delay (preferring to receive $5 now over receiving $20 in a year). Confinement is a condition that typically leads to the state of boredom, which can trigger impulsivity (Moynihan et al., 2017). In this task (Supp. Fig. 10), different amounts were offered to participants at different delays to estimate the subjective values of the offers as a function of time required to collect them.
Phenomenological approaches have related time with self as early as the 20th century (Husserl, 2012) leading psychiatrists to link time with disorders of the self in psychosis (Fuchs, 2007; Minkowski, 2013; Vogeley & Kupke, 2007). Such a link has been evidenced experimentally (Foerster et al., 2021; Martin et al., 2017). In addition to the PQ-16 questionnaire exploring attenuated psychosis, the self-preference task was added to provide an objective self-related measure. It has repeatedly been shown that a stimulus we associate with ourselves is processed faster and with higher accuracy than a stimulus we associate with others (Makwana & Srinivasan, 2019; Sui et al., 2012). These effects can either be accounted for by a self-referent memory advantage (Cunningham et al., 2008) or by enhanced attention drawn to self-related information (Keyes et al., 2010). To test this, and in accordance with previous work, we used a reaction time task in which participants learn to associate a geometrical shape with a label (“Self”, “Friend” and “Other”; Supp. Fig. 11). On subsequent trials, participants are presented with one shape and one label, which may or not match with the previously learned associations. Participants had to report as fast and as accurately as possible whether the shape and the label matched.