Dynamics of retrospective timing: A big data approach.

Most interval timing research has focused on prospective timing tasks, in which participants are explicitly asked to pay attention to time as they are tested over multiple trials. Our current understanding of interval timing primarily relies on prospective timing. However, most real-life temporal judgments are made without knowing beforehand that the durations of events will need to be estimated (i.e., retrospective timing). The current study investigated the retrospective timing performance of ~24,500 participants with a wide range of intervals (5-90 min). Participants were asked to judge how long it took them to complete a set of questionnaires that were filled out at the participants' own pace. Participants overestimated and underestimated durations shorter and longer than 15 min, respectively. They were most accurate at estimating 15-min long events. The between-subject variability in duration estimates decreased exponentially as a function of time, reaching the lower asymptote after 30 min. Finally, a considerable proportion of participants exhibited whole number bias by rounding their duration estimates to the multiples of 5 min. Our results provide evidence for systematic biases in retrospective temporal judgments, and show that variability in retrospective timing is relatively higher for shorter durations (e.g., < 30 min). The primary findings gathered from our dataset were replicated based on the secondary analyses of another dataset (Blursday). The current study constitutes the most comprehensive study of retrospective timing regarding the range of durations and sample size tested.