The Blursday database as a resource to study subjective temporalities during COVID-19.

Humans COVID-19 Pandemics Retrospective Studies Communicable Disease Control Databases, Factual

Journal

Nature human behaviour

ISSN: 2397-3374

Titre abrégé: Nat Hum Behav

Pays: England

ID NLM: 101697750

Informations de publication

Date de publication:
11 2022

Historique:

received: 20 11 2021

accepted: 17 06 2022

pubmed: 16 8 2022

medline: 23 11 2022

entrez: 15 8 2022

Statut: ppublish

Résumé

The COVID-19 pandemic and associated lockdowns triggered worldwide changes in the daily routines of human experience. The Blursday database provides repeated measures of subjective time and related processes from participants in nine countries tested on 14 questionnaires and 15 behavioural tasks during the COVID-19 pandemic. A total of 2,840 participants completed at least one task, and 439 participants completed all tasks in the first session. The database and all data collection tools are accessible to researchers for studying the effects of social isolation on temporal information processing, time perspective, decision-making, sleep, metacognition, attention, memory, self-perception and mindfulness. Blursday includes quantitative statistics such as sleep patterns, personality traits, psychological well-being and lockdown indices. The database provides quantitative insights on the effects of lockdown (stringency and mobility) and subjective confinement on time perception (duration, passage of time and temporal distances). Perceived isolation affects time perception, and we report an inter-individual central tendency effect in retrospective duration estimation.

Identifiants

DOI: 10.1038/s41562-022-01419-2 PMID: 35970902

pubmed: 35970902

doi: 10.1038/s41562-022-01419-2

pii: 10.1038/s41562-022-01419-2

doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

Pagination

1587-1599

Informations de copyright

Références

Matthews, W. J. & Meck, W. H. Time perception: the bad news and the good. WIREs Cogn. Sci. 5, 429–446 (2014).

doi: 10.1002/wcs.1298

Holman, E. A. & Grisham, E. L. When time falls apart: the public health implications of distorted time perception in the age of COVID-19. Psychol. Trauma 12, S63–S65 (2020).

pubmed: 32525373 doi: 10.1037/tra0000756

Wittmann, M. & Paulus, M. P. Decision making, impulsivity and time perception. Trends Cogn. Sci. 12, 7–12 (2008).

pubmed: 18042423 doi: 10.1016/j.tics.2007.10.004

COVID-19 and Well-Being: Life in the Pandemic (OECD, 2021); https://www.oecd.org/wise/covid-19-and-well-being-1e1ecb53-en.htm

Yamada, Y. et al. COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak. Sci. Data 8, 3 (2021).

pubmed: 33398078 pmcid: 7782539 doi: 10.1038/s41597-020-00784-9

Buonomano, D. V. The biology of time across different scales. Nat. Chem. Biol. 3, 594–597 (2007).

pubmed: 17876310 doi: 10.1038/nchembio1007-594

Laje, R., Agostino, P. V. & Golombek, D. A. The times of our lives: interaction among different biological periodicities. Front. Integr. Neurosci. 12, 10 (2018).

pubmed: 29593507 pmcid: 5859086 doi: 10.3389/fnint.2018.00010

Balci, F., Meck, W. H., Moore, H. & Brunner, D. in: Animal Models of Human Cognitive Aging (eds Bizon, J. & Woods, A.) 1–41 (Springer, 2009).

Schmidt, C., Collette, F., Cajochen, C. & Peigneux, P. A time to think: circadian rhythms in human cognition. Cogn. Neuropsychol. 24, 755–789 (2007).

pubmed: 18066734 doi: 10.1080/02643290701754158

Balcı, F. et al. Optimal temporal risk assessment. Front. Integr. Neurosci. 5, 56 (2011).

pubmed: 21991250 pmcid: 3180672 doi: 10.3389/fnint.2011.00056

Blume, C., Schmidt, M. H. & Cajochen, C. Effects of the COVID-19 lockdown on human sleep and rest-activity rhythms. Curr. Biol. 30, R795–R797 (2020).

pubmed: 32693067 pmcid: 7284244 doi: 10.1016/j.cub.2020.06.021

Cellini, N., Canale, N., Mioni, G. & Costa, S. Changes in sleep pattern, sense of time and digital media use during COVID-19 lockdown in Italy. J. Sleep Res. 29, e13074 (2020).

pubmed: 32410272 pmcid: 7235482 doi: 10.1111/jsr.13074

Wright, K. P. Jr et al. Sleep in university students prior to and during COVID-19 stay-at-home orders. Curr. Biol. 30, R797–R798 (2020).

pubmed: 32693068 pmcid: 7284257 doi: 10.1016/j.cub.2020.06.022

Marelli, S. et al. Impact of COVID-19 lockdown on sleep quality in university students and administration staff. J. Neurol. 268, 8–15 (2021).

pubmed: 32654065 doi: 10.1007/s00415-020-10056-6

Dean, D. J. et al. Cross-cultural comparisons of psychosocial distress in the USA, South Korea, France, and Hong Kong during the initial phase of COVID-19. Psychiatry Res. 295, 113593 (2021).

pubmed: 33276269 doi: 10.1016/j.psychres.2020.113593

Lieberoth, A. et al. Stress and worry in the 2020 coronavirus pandemic: relationships to trust and compliance with preventive measures across 48 countries in the COVIDiSTRESS global survey. R. Soc. Open Sci. 8, 200589 (2021).

pubmed: 33972837 pmcid: 8074580 doi: 10.1098/rsos.200589

Micillo, L. et al. Time perspective predicts levels of anxiety and depression during the COVID-19 outbreak: a cross-cultural study. Preprint at PsyArXiv https://doi.org/10.31234/osf.io/8tqap (2021).

Fiorenzato, E., Zabberoni, S., Costa, A. & Cona, G. Cognitive and mental health changes and their vulnerability factors related to COVID-19 lockdown in Italy. PLoS ONE 16, e0246204 (2021).

pubmed: 33503055 pmcid: 7840042 doi: 10.1371/journal.pone.0246204

Droit-Volet, S. et al. Time and COVID-19 stress in the lockdown situation: time free, “dying” of boredom and sadness. PLoS ONE 15, e0236465 (2020).

pubmed: 32776990 pmcid: 7416923 doi: 10.1371/journal.pone.0236465

Droit-Volet, S. et al. The persistence of slowed time experience during the COVID-19 pandemic: two longitudinal studies in France. Front. Psychol. 12, 721716 (2021).

pubmed: 34539524 pmcid: 8442913 doi: 10.3389/fpsyg.2021.721716

Martinelli, N. et al. Time and emotion in the lockdown for the COVID-19 epidemic: the determinants of our experience of time? Front. Psychol. 11, 3738 (2020).

Ogden, R. Distortions to the passage of time during England’s second national lockdown: a role for depression. PLoS ONE 16, e0250412 (2021).

pubmed: 33878130 pmcid: 8057617 doi: 10.1371/journal.pone.0250412

Ogden, R. The passage of time during the UK COVID-19 lockdown. PLoS ONE 15, e0235871 (2020).

pubmed: 32628735 pmcid: 7337311 doi: 10.1371/journal.pone.0235871

Loose, T., Wittmann, M. & Vásquez-Echeverría, A. Disrupting times in the wake of the pandemic: dispositional time attitudes, time perception and temporal focus. Time Soc. 31, 110–131 (2021).

doi: 10.1177/0961463X211027420

Cravo, A. M. et al. Time experience during social distancing: a longitudinal study during the first months of COVID-19 pandemic in Brazil. Sci. Adv. 8, eabj7205 (2022).

pubmed: 35417245 pmcid: 9007501 doi: 10.1126/sciadv.abj7205

Glasauer, S. & Shi, Z. The origin of Vierordt’s law: the experimental protocol matters. PsyCh J. 10, 732–741 (2021).

pubmed: 34028202 doi: 10.1002/pchj.464

Lejeune, H. & Wearden, J. H. Vierordt’s The Experimental Study of the Time Sense (1868) and its legacy. Eur. J. Cogn. Psychol. 21, 941–960 (2009).

doi: 10.1080/09541440802453006

Petzschner, F. H., Glasauer, S. & Stephan, K. E. A Bayesian perspective on magnitude estimation. Trends Cogn. Sci. 19, 285–293 (2015).

pubmed: 25843543 doi: 10.1016/j.tics.2015.03.002

Grondin, S. & Plourde, M. Judging multi-minute intervals retrospectively. Q. J. Exp. Psychol. 60, 1303–1312 (2007).

doi: 10.1080/17470210600988976

Eisler, H. Experiments on subjective duration 1868–1975: a collection of power function exponents. Psychol. Bull. 83, 1154–1171 (1976).

pubmed: 996212 doi: 10.1037/0033-2909.83.6.1154

Block, R. A., Zakay, D. & Hancock, P. A. Human aging and duration judgments: a meta-analytic review. Psychol. Aging 13, 584–596 (1998).

pubmed: 9883459 doi: 10.1037/0882-7974.13.4.584

Pöppel, E. & Giedke, H. Diurnal variation of time perception. Psychol. Forsch. 34, 182–198 (1970).

pubmed: 5515502 doi: 10.1007/BF00424544

Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

doi: 10.18637/jss.v067.i01

Wearden, J. H. Passage of time judgements. Conscious. Cogn. 38, 165–171 (2015).

pubmed: 26115594 doi: 10.1016/j.concog.2015.06.005

Wearden, J., O’Donoghue, A., Ogden, R. & Montgomery, C. in Subjective Time: The Philosophy, Psychology, and Neuroscience of Temporality (eds Arstila, V. & Lloyd, D.) 287–306 (Boston Review, 2014); https://doi.org/10.7551/mitpress/8516.001.0001

Bertrand, L. et al. Sleep and circadian rhythm characteristics in individuals from the general population during the French COVID-19 full lockdown. J. Sleep Res. 31, e13480 (2021).

pubmed: 34490948 pmcid: 8646935

Wheeler, M. A., Stuss, D. T. & Tulving, E. Toward a theory of episodic memory: the frontal lobes and autonoetic consciousness. Psychol. Bull. 121, 331–354 (1997).

pubmed: 9136640 doi: 10.1037/0033-2909.121.3.331

Winkler, I. et al. Has it really been that long? Why time seems to speed up with age. Timing Time Percept. 5, 168–189 (2017).

doi: 10.1163/22134468-00002088

Addis, D. R., Wong, A. T. & Schacter, D. L. Age-related changes in the episodic simulation of future events. Psychol. Sci. 19, 33–41 (2008).

pubmed: 18181789 doi: 10.1111/j.1467-9280.2008.02043.x

Jazayeri, M. & Shadlen, M. N. Temporal context calibrates interval timing. Nat. Neurosci. 13, 1020–1026 (2010).

pubmed: 20581842 pmcid: 2916084 doi: 10.1038/nn.2590

Woodrow, H. The temporal indifference interval determined by the method of mean error. J. Exp. Psychol. 17, 167–188 (1934).

doi: 10.1037/h0070235

Yarmey, A. D. Retrospective duration estimations for variant and invariant events in field situations. Appl. Cogn. Psychol. 14, 45–57 (2000).

doi: 10.1002/(SICI)1099-0720(200001)14:1<45::AID-ACP623>3.0.CO;2-U

Roy, M. M. & Christenfeld, N. J. S. Effect of task length on remembered and predicted duration. Psychon. Bull. Rev. 15, 202–207 (2008).

pubmed: 18605504 doi: 10.3758/PBR.15.1.202

Looijmans, A., Spahrkäs, S. S., Sanderman, R. & Hagedoorn, M. Ethical review procedures in international internet-based intervention studies. Internet Interv. 28, 100487 (2021).

pubmed: 35646602 pmcid: 9136336 doi: 10.1016/j.invent.2021.100487

Anwyl-Irvine, A. L., Massonnié, J., Flitton, A., Kirkham, N. & Evershed, J. K. Gorilla in our midst: an online behavioral experiment builder. Behav. Res. https://doi.org/10.3758/s13428-019-01237-xi (2019).

van Wassenhove, V. et al. Blursday. OSF https://doi.org/10.17605/OSF.IO/359QM (2020).

Russell, D. W., Peplau, L. A. & Cutrona, C. E. The revised UCLA Loneliness Scale: concurrent and discriminant validity evidence. J. Pers. Soc. Psychol. 39, 472–480 (1980).

pubmed: 7431205 doi: 10.1037/0022-3514.39.3.472

Russell, D. W. UCLA Loneliness Scale (Version 3): reliability, validity, and factor structure. J. Pers. Assess. 66, 20–40 (1996).

pubmed: 8576833 doi: 10.1207/s15327752jpa6601_2

Crawford, J. R., Henry, J. D., Crombie, C. & Taylor, E. P. Normative data for the HADS from a large non-clinical sample. Br. J. Clin. Psychol. 40, 429–434 (2001).

pubmed: 11760618 doi: 10.1348/014466501163904

Ising, H. K. et al. The validity of the 16-item version of the Prodromal Questionnaire (PQ-16) to screen for ultra high risk of developing psychosis in the general help-seeking population. Schizophr. Bull. 38, 1288–1296 (2012).

pubmed: 22516147 pmcid: 3713086 doi: 10.1093/schbul/sbs068

Walach, H., Buchheld, N., Buttenmüller, V., Kleinknecht, N. & Schmidt, S. Measuring mindfulness—the Freiburg Mindfulness Inventory (FMI). Pers. Individ. Dif. 40, 1543–1555 (2006).

doi: 10.1016/j.paid.2005.11.025

Randler, C. German version of the reduced Morningness–Eveningness Questionnaire (rMEQ). Biol. Rhythm Res. 44, 730–736 (2013).

doi: 10.1080/09291016.2012.739930

Ghotbi, N. et al. The μMCTQ: an ultra-short version of the Munich ChronoType questionnaire. J. Biol. Rhythms 35, 98–110 (2020).

pubmed: 31791166 doi: 10.1177/0748730419886986

Buysse, D. J. et al. Quantification of subjective sleep quality in healthy elderly men and women using the Pittsburgh Sleep Quality Index (PSQI). Sleep 14, 331–338 (1991).

pubmed: 1947597

Smyth, C. The Pittsburgh Sleep Quality Index (PSQI) (SLACK Incorporated, 1999).

Rammstedt, B. The 10-item Big Five Inventory: norm values and investigation of sociodemographic effects based on a German population representative sample. Eur. J. Psychol. Assess. 23, 193–201 (2007).

doi: 10.1027/1015-5759.23.3.193

Rammstedt, B. & John, O. P. Measuring personality in one minute or less: a 10-item short version of the Big Five Inventory in English and German. J. Res. Pers. 41, 203–212 (2007).

doi: 10.1016/j.jrp.2006.02.001

Zimbardo, P. G. The Stanford Time Perspective Inventory (Stanford University, 1990).

Zimbardo, P. G. & Boyd, J. N. in Time Perspective Theory: Review, Research and Application (eds Stolarski, M. et al.) 17–55 (Springer, 2015).

Sircova, A. et al. A global look at time: a 24-country study of the equivalence of the Zimbardo Time Perspective Inventory. Sage Open 4, 2158244013515686 (2014).

doi: 10.1177/2158244013515686

Kraft, J. D. et al. Assessing the psychometric properties of the Attentional Style Questionnaire. Cogn. Emot. 34, 403–412 (2019).

pubmed: 31220999 doi: 10.1080/02699931.2019.1632802

Van Calster, L., D’Argembeau, A. & Majerus, S. Measuring individual differences in internal versus external attention: the Attentional Style Questionnaire. Pers. Individ. Dif. 128, 25–32 (2018).

doi: 10.1016/j.paid.2018.02.014

Block, R. A., Grondin, S. & Zakay, D. in Timing and Time Perception: Procedures, Measures, & Applications (eds Vatakis, A. et al.) 32–51 (Brill, 2018).

Hicks, R. E. in Time, Action and Cognition (eds Macar, F. et al.) 97–108 (Springer, 1992).

Zakay, D. & Block, R. A. Temporal cognition. Curr. Dir. Psychol. Sci. 6, 12–16 (1997).

doi: 10.1111/1467-8721.ep11512604

Thönes, S. & Stocker, K. A standard conceptual framework for the study of subjective time. Conscious. Cogn. 71, 114–122 (2019).

pubmed: 31004875 doi: 10.1016/j.concog.2019.04.004

Koriat, A., Fischhoff, B. & Razel, O. An inquiry into the process of temporal orientation. Acta Psychol. 40, 57–73 (1976).

doi: 10.1016/0001-6918(76)90044-5

Koriat, A. & Fischhoff, B. What day is today? An inquiry into the process of time orientation. Mem. Cogn. 2, 201–205 (1974).

doi: 10.3758/BF03208982

Friedman, W. J. Memory for the time of past events. Psychol. Bull. 113, 44–66 (1993).

doi: 10.1037/0033-2909.113.1.44

Liberman, N. & Trope, Y. Traversing psychological distance. Trends Cogn. Sci. 18, 364–369 (2014).

pubmed: 24726527 doi: 10.1016/j.tics.2014.03.001

Ross, M. & Wilson, A. E. It feels like yesterday: self-esteem, valence of personal past experiences, and judgments of subjective distance. J. Pers. Soc. Psychol. 82, 792–803 (2002).

pubmed: 12003478 doi: 10.1037/0022-3514.82.5.792

Henry, J. D. & Crawford, J. R. A meta-analytic review of verbal fluency performance in patients with traumatic brain injury. Neuropsychology 18, 621–628 (2004).

pubmed: 15506829 doi: 10.1037/0894-4105.18.4.621

D’Argembeau, A., Ortoleva, C., Jumentier, S. & Van der Linden, M. Component processes underlying future thinking. Mem. Cogn. 38, 809–819 (2010).

doi: 10.3758/MC.38.6.809

Brown, S. W. Attentional resources in timing: interference effects in concurrent temporal and nontemporal working memory tasks. Percept. Psychophys. 59, 1118–1140 (1997).

pubmed: 9360484 doi: 10.3758/BF03205526

Grondin, S. & Macar, F. in Time, Action and Cognition (Macar, F. et al.) 119–128 (Springer, 1992).

Macar, F., Grondin, S. & Casini, L. Controlled attention sharing influences time estimation. Mem. Cogn. 22, 673–686 (1994).

doi: 10.3758/BF03209252

Fortin, C. & Breton, R. Temporal interval production and processing in working memory. Percept. Psychophys. 57, 203–215 (1995).

pubmed: 7885819 doi: 10.3758/BF03206507

Polti, I., Martin, B. & van Wassenhove, V. The effect of attention and working memory on the estimation of elapsed time. Sci. Rep. 8, 6690 (2018).

pubmed: 29703928 pmcid: 5923266 doi: 10.1038/s41598-018-25119-y

Akdoğan, B. & Balcı, F. Are you early or late? Temporal error monitoring. J. Exp. Psychol. Gen. 146, 347–361 (2017).

pubmed: 28080127 doi: 10.1037/xge0000265

Kononowicz, T. W., Roger, C. & van Wassenhove, V. Temporal metacognition as the decoding of self-generated brain dynamics. Cereb. Cortex 29, 4366–4380 (2019).

pubmed: 30590497 doi: 10.1093/cercor/bhy318

Grondin, S. From physical time to the first and second moments of psychological time. Psychol. Bull. 127, 22–44 (2001).

pubmed: 11271754 doi: 10.1037/0033-2909.127.1.22

Balci, F., Freestone, D. & Gallistel, C. R. Risk assessment in man and mouse. Proc. Natl Acad. Sci. USA 106, 2459–2463 (2009).

pubmed: 19188592 pmcid: 2634808 doi: 10.1073/pnas.0812709106

Hammerschmidt, D., Frieler, K. & Wöllner, C. Spontaneous motor tempo: investigating psychological, chronobiological, and demographic factors in a large-scale online tapping experiment. Front. Psychol. 12, 2338 (2021).

doi: 10.3389/fpsyg.2021.677201

McAuley, J. D., Jones, M. R., Holub, S., Johnston, H. M. & Miller, N. S. The time of our lives: life span development of timing and event tracking. J. Exp. Psychol. Gen. 135, 348–367 (2006).

pubmed: 16846269 doi: 10.1037/0096-3445.135.3.348

Turgeon, M. & Wing, A. M. Late onset of age-related difference in unpaced tapping with no age-related difference in phase-shift error detection and correction. Psychol. Aging 27, 1152–1163 (2012).

pubmed: 23066805 doi: 10.1037/a0029925

Turgeon, M., Lustig, C. & Meck, W. H. Cognitive aging and time perception: roles of Bayesian optimization and degeneracy. Front. Aging Neurosci. 8, 102 (2016).

pubmed: 27242513 pmcid: 4870863 doi: 10.3389/fnagi.2016.00102

Semjen, A., Schulze, H.-H. & Vorberg, D. Timing precision in continuation and synchronization tapping. Psychol. Res. 63, 137–147 (2000).

pubmed: 10946587 doi: 10.1007/PL00008172

Wing, A. M. & Kristofferson, A. B. Response delays and the timing of discrete motor responses. Percept. Psychophys. 14, 5–12 (1973).

doi: 10.3758/BF03198607

Repp, B. H. & Su, Y.-H. Sensorimotor synchronization: a review of recent research (2006–2012). Psychon. Bull. Rev. 20, 403–452 (2013).

pubmed: 23397235 doi: 10.3758/s13423-012-0371-2

Chen, Y., Ding, M. & Kelso, J. S. Long memory processes (1/f α type) in human coordination. Phys. Rev. Lett. 79, 4501 (1997).

doi: 10.1103/PhysRevLett.79.4501

Bavassi, M. L., Tagliazucchi, E. & Laje, R. Small perturbations in a finger-tapping task reveal inherent nonlinearities of the underlying error correction mechanism. Hum. Mov. Sci. 32, 21–47 (2013).

pubmed: 23375111 doi: 10.1016/j.humov.2012.06.002

Nobre, A. C. & Van Ede, F. Anticipated moments: temporal structure in attention. Nat. Rev. Neurosci. 19, 34–48 (2018).

pubmed: 29213134 doi: 10.1038/nrn.2017.141

Cravo, A. M., Rohenkohl, G., Wyart, V. & Nobre, A. C. Endogenous modulation of low frequency oscillations by temporal expectations. J. Neurophysiol. 106, 2964–2972 (2011).

pubmed: 21900508 pmcid: 3234094 doi: 10.1152/jn.00157.2011

Herbst, S. K. & Obleser, J. Implicit temporal predictability enhances pitch discrimination sensitivity and biases the phase of delta oscillations in auditory cortex. NeuroImage 203, 116198 (2019).

pubmed: 31539590 doi: 10.1016/j.neuroimage.2019.116198

Loewenstein, G. F. Frames of mind in intertemporal choice. Manage. Sci. 34, 200–214 (1988).

doi: 10.1287/mnsc.34.2.200

Moynihan, A. B., Igou, E. R. & van Tilburg, W. A. Boredom increases impulsiveness: a meaning-regulation perspective. Social Psychology 48, 293 (2017).

doi: 10.1027/1864-9335/a000317

Eurostat–OECD Methodological Manual on Purchasing Power Parities (Organisation for Economic Co-operation and Development, 2012).

Husserl, E. On the Phenomenology of the Consciousness of Internal Time (1893–1917) Vol. 4 (Springer Science & Business Media, 2012).

Fuchs, T. The temporal structure of intentionality and its disturbance in schizophrenia. Psychopathology 40, 229–235 (2007).

pubmed: 17396049 doi: 10.1159/000101365

Minkowski, E. Le temps vécu (Presses Universitaires de France, 2013); https://doi.org/10.3917/puf.mink.2013.01

Vogeley, K. & Kupke, C. Disturbances of time consciousness from a phenomenological and a neuroscientific perspective. Schizophr. Bull. 33, 157–165 (2007).

pubmed: 17105967 doi: 10.1093/schbul/sbl056

Foerster, F. R. et al. Volatility of subliminal haptic feedbacks alters the feeling of control in schizophrenia. J. Abnorm. Psychol. 130, 775–784 (2021).

pubmed: 34780231 doi: 10.1037/abn0000703

Martin, B. et al. Fragile temporal prediction in patients with schizophrenia is related to minimal self disorders. Sci. Rep. 7, 8278 (2017).

pubmed: 28811493 pmcid: 5557764 doi: 10.1038/s41598-017-07987-y

Makwana, M. & Srinivasan, N. Self-associated stimuli produce stronger intentional binding. J. Exp. Psychol. Hum. Percept. Perform. 45, 1436–1442 (2019).

pubmed: 31436449 doi: 10.1037/xhp0000687

Sui, J., He, X. & Humphreys, G. W. Perceptual effects of social salience: evidence from self-prioritization effects on perceptual matching. J. Exp. Psychol. Hum. Percept. Perform. 38, 1105–1117 (2012).

pubmed: 22963229 doi: 10.1037/a0029792

Cunningham, S. J., Turk, D. J., Macdonald, L. M. & Macrae, C. N. Yours or mine? Ownership and memory. Conscious. Cogn. 17, 312–318 (2008).

pubmed: 17543540 doi: 10.1016/j.concog.2007.04.003

Keyes, H., Brady, N., Reilly, R. B. & Foxe, J. J. My face or yours? Event-related potential correlates of self-face processing. Brain Cogn. 72, 244–254 (2010).

pubmed: 19854553 doi: 10.1016/j.bandc.2009.09.006

Hale, T. et al. A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker). Nat. Hum. Behav. 5, 529–538 (2021).

pubmed: 33686204 doi: 10.1038/s41562-021-01079-8

Google COVID-19 Community Mobility Reports (Google, accessed 4 October 2021); https://www.google.com/covid19/mobility/

Huttenlocher, J., Hedges, L. V. & Prohaska, V. Memory for day of the week: a 5+ 2 day cycle. J. Exp. Psychol. Gen. 121, 313–325 (1992).

pubmed: 1402704 doi: 10.1037/0096-3445.121.3.313

Roediger, H. L. & Crowder, R. G. A serial position effect in recall of United States presidents. Bull. Psychon. Soc. 8, 275–278 (1976).

doi: 10.3758/BF03335138

Jonas, K. J. & Huguet, P. What day is today? A social–psychological investigation into the process of time orientation. Pers. Soc. Psychol. Bull. 34, 353–365 (2008).

pubmed: 18272804 doi: 10.1177/0146167207311202

Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).

pubmed: 26978244 pmcid: 4792175 doi: 10.1038/sdata.2016.18

Bridges, D., Pitiot, A., MacAskill, M. R. & Peirce, J. W. The timing mega-study: comparing a range of experiment generators, both lab-based and online. PeerJ 8, e9414 (2020).

pubmed: 33005482 pmcid: 7512138 doi: 10.7717/peerj.9414