Sooner Rather Than Later: Precrastination Rather Than Procrastination

The Discovery of Precrastination

Precrastination was found by accident in a study of the planning and control of physical actions. Rosenbaum et al. (2014) asked university students to walk down an alley and pick up either of two buckets: one some distance away on the left edge of the alley or one some distance away on the right edge of the alley. The participants were asked to take whichever bucket seemed easier to carry to the end. It was expected that participants would pick up the bucket closer to the end of the alley because that bucket would be carried a shorter distance. The researchers’ plan was to explore the biomechanical trade-offs between distance and weight: How far would participants be willing to walk with a relatively light bucket to avoid a relatively short walk with a heavier bucket?

Surprisingly, most participants chose the bucket that was closer to the starting point, not the one that was closer to the end of the alley. This was odd because the near-bucket choice resulted in a longer carrying distance. When participants were interviewed about their choices, they said they chose the near bucket to get the task done as quickly as possible. Such a claim made little sense from the point of view that the time would presumably have been the same if subjects had picked up the near bucket or the far bucket. On the basis of nine experiments designed to test alternative hypotheses, Rosenbaum et al. (2014) were led to the hypothesis discussed in the next section.

Precrastination Reduces Cognitive Demands

Rosenbaum et al. (2014) suggested that the near-bucket preference stemmed from a desire to reduce cognitive demands. The idea was that picking up and carrying a bucket is nontrivial from a cognitive perspective (Rosenbaum, 2017); witness the fact that robots still have a very hard time with such tasks. In addition, maintaining the intention to pick up a bucket loads working memory. Therefore, picking up a bucket sooner rather than later enables people to rid themselves of the cognitive load sooner rather than later.

This interpretation was supported by Fournier, Stubblefield, Dyre, and Rosenbaum (2018), whose participants performed a task similar to the one used by Rosenbaum et al. (2014). Fournier et al.’s participants picked up two objects at two distances and brought them back to the start position in one trip. The question was whether the participants would (a) pick up the near object, carry it out to the far object, then pick up the far object, and then return with both objects or (b) walk past the near object, pick up the far object, and then pick up the near object on the way back. Fournier et al. found that participants opted for choice (a). The researchers coded this choice as precrastination. In another experiment, Fournier et al. found that when a detail of the task was changed so that the objects to be carried were cups filled with water that could easily be spilled but were supposed to be prevented from spilling, the near object was seldom picked up first; option (b) was now preferred over option (a). Fournier et al. concluded that precrastination is used to reduce cognitive demands: When precrastination would have increased cognitive demands (increasing attention to the carried objects if the objects were cups filled with water), precrastination was eschewed.

In another experiment, Fournier et al. (2019) gave participants a memorization task in conjunction with less attention-demanding object carrying. These participants precrastinated at higher rates than participants who were not given the added memorization. The researchers observed that this result was again consistent with the hypothesis that precrastination is associated with reducing cognitive effort.

In still other experiments, Fournier and her colleagues (2018) showed that precrastination is likely to be automatically invoked, though it can be inhibited if needed. Fournier et al. (2018) introduced manipulations that revealed that precrastination is so strong that it actually applies to the starting of tasks, not just the completion of tasks. The results fit with an optimal-foraging view, in which expressing a bias to grab potentially scarce resources tends to increase fitness and in turn encourages quick action (Yoon, Geary, Ahmed, & Shadmehr, 2018). An optimal-foraging view and a cognitive-easing view are certainly not inconsistent with one another. Indeed, having a clear (or cleared) mind should help one forage more effectively.

VonderHaar, McBride, and Rosenbaum (2017) provided more evidence for the hypothesis that reducing cognitive demands gets high priority. They asked university students to complete a computerized box-moving task as well as a semantic item-generation task. Their participants slid 10 boxes, one at a time, from one place to another on a computer screen and also generated items from various semantic categories. The item generations had to occur without interruption but could occur whenever participants preferred—before the first box move, before the second box move, before the third box move, and so on, all the way to after the 10th box move. A priori, the probability of doing the category-generation task at any serial position was 1/11, but a full half of the 122 participants chose to do all of the category generation before moving any box, an outcome whose probability was 1/11⁶¹, or astronomically small. Most other participants also did the category generation earlier rather than later. This outcome fits with the view that there is a strong preference to unload working memory as soon as possible. The conclusion supports the interpretations given above and makes sense from the point of view that prospective memory is mentally taxing (Einstein & McDaniel, 2005; see also Kool, McGuire, Rosen, & Botvinick, 2010).

Yet another demonstration concerns a recently discovered phenomenon called the mere-urgency effect (Zhu, Bagchi, & Hock, 2018; Zhu, Yang, & Hsee, 2018). Here, participants chose between tasks with short or long deadlines. All of the tasks could be completed within the available times, and the researchers showed that the participants believed that the short-deadline tasks were no harder than the long-deadline tasks. Nevertheless, the participants preferred the short-deadline tasks. Zhu, Bagchi, and Hock (2018) and Zhu, Yang, and Hsee (2018) suggested that participants preferred the shorter deadlines because those deadlines helped them avoid the need to monitor the passage of time. Keeping track of time is cognitively taxing (Grondin, 2008), as is the need to remember to do upcoming tasks (Einstein & McDaniel, 2005).

Consistent with this interpretation, findings from another study (Levy-Tzedek, Ben Tov, & Karniel, 2011) revealed that participants “jumped the gun” by switching from one mode of manual behavior (a discrete mode) to another (a continuous mode) rather than staying the course in the discrete mode until forced to switch to the continuous mode. Premature switching was also observed when the continuous mode was the first mode and the discrete mode was the second. In other work, Levy-Tzedek (2017) showed, much as Fournier et al. (2019) did, that adding a cognitive task (counting backward) affected the likelihood of precrastination. Levy-Tzedek (2017) also found that older adults precrastinated less than younger adults, for reasons still to be explored.

Individual Differences

Sauerberger, Rosenbaum, and Funder (2018) explored individual differences in precrastination. They replicated the original bucket-choice task of Rosenbaum et al. (2014) and found that most (59%) of the university-student participants chose the near bucket rather than the far bucket, a rate comparable with that seen by Rosenbaum et al. (2014). Sauerberger et al. also found that participants’ choices were stable: 22% of the participants always chose the first bucket, and 13% of the participants never chose the first bucket; 55% deviated once, at most, from their choices in all other trials.

These results indicate stable individual differences whose bases were revealed through personality questionnaires. Impulsivity did not predict precrastination, an outcome that surprised us initially, considering Fournier et al.’s (2018) conclusion that precrastination is automatically invoked, subject to inhibition. Yet Fournier and her colleagues found that precrastination is used strategically, which was also shown in another behavioral experiment by Rosenbaum and Sauerberger (2019) involving choosing buckets to be carried over long or short distances to platforms that were either high or low; subjects made sophisticated trade-offs between the preference for the near bucket and aversion to bending down at the end. In their questionnaire study, Sauerberger, Rosenbaum, and Funder (2018) found, in addition to the noneffect of impulsivity, a positive relation between precrastination and conscientiousness; people with high levels of conscientiousness may want to get things done as soon as possible. Third, Sauerberger et al. (2018) found a positive relation between precrastination and agreeableness. The basis for this result is under investigation.

Animal Studies

If precrastination is a basic phenomenon, one would expect to see it in nonhuman animals. That expectation has been confirmed. Wasserman and Brzykcy (2015) demonstrated precrastination in pigeons. Pigeons could get food after making three pecks. The first peck was made in a square in the center of a computer screen. The second peck was made either in that same center square or in a square that randomly appeared to the left or right. The third peck was made in the just-shown left or right square after a star appeared within it. Critically, food was given after the final peck regardless of whether the second peck struck the center square or side square. The pigeons overwhelmingly directed their second pecks to the side square. In so doing, they moved to the final position earlier rather than later, though there was no obvious reason or extra reward for doing so. By pecking on the side square, the birds behaved in a manner consistent with precrastination. The result cannot be ascribed to reducing errors, because no errors were possible with this procedure; reward was always obtained. The result also cannot be ascribed to confusion, for then the birds would have responded equally often to the center and side squares.

A related effect was found by Rayburn-Reeves, Molet, and Zentall (2011), who trained pigeons to peck a red light for 40 trials and then peck a green light for the next 40 trials. Despite considerable training, the pigeons tended to switch to the green light before the reversal occurred. The pigeons precrastinated, anticipating the switch to the green light, though they would have been more accurate (made only a single error) had they waited for the first trial in which a red-light peck would have been wrong. Recall that Levy-Tzedek et al. (2011) obtained a similar result.

Zentall, Case, and Andrews (2018) got a somewhat different result, which, interestingly, they took to reflect procrastination rather than precrastination. They gave pigeons a choice between (a) a 15-s green light followed by a 5-s red light signaling food or (b) a 5-s blue light followed by a 15-s yellow light signaling the same food. All durations were fixed-interval schedules that required pigeons to peck immediately at the end of each interval. The pigeons preferred the long-short sequence even though the total time from choice to food was the same in both instances. Furthermore, the pigeons pecked the terminal 5-s red light at twice the rate of the terminal 15-s yellow light. Zentall et al. suggested that it may be especially rewarding to have a short cue immediately signaling reinforcement even if one has to wait longer to receive it (cf. Fantino, 1969; Fantino & Abarca, 1985).

Wasserman and Zentall here hypothesize that organisms will precrastinate if reward will be available soon (as found by Wasserman & Brzykcy, 2015) but will procrastinate if reward will be available later (as found by Zentall et al., 2018). This view, which was inspired by and echoed by Rachlin and Green (1972), Rung and Madden (2018), and Wasserman (2018), was previewed earlier, when we indicated that one might hurry to bring in groceries (precrastination) but delay working on term papers (procrastination).

Conclusions and Future Directions

Precrastination is the tendency to hurry to get things done and even to start as soon as possible, even if that involves extra effort. As shown here, the tendency is strong. It may be triggered automatically but can be inhibited. The drive to act quickly may optimize foraging. More interestingly, however, precrastination reduces cognitive demands. The desire to unload working memory may be so strong that one is willing to work hard physically to do so.

Questions remain. One pertains to cognitive-demand reduction in animals. The studies described above showed differential reliance on precrastination and procrastination in animals, but cognitive demands were not varied. Tools for doing so have been developed (Wasserman & Zentall, 2006). It will be interesting to see whether precrastination is undertaken to reduce cognitive demands in animals.

A second question is whether the tendency to precrastinate generalizes over tasks. If someone picks up near buckets, will he or she answer e-mails immediately, finish work too soon, and hurry on physical tasks that may lead to injury? If precrastination reflects stable individual differences, one would expect such generalization. Personnel-selection studies might be designed accordingly. Cognitive abilities should also affect the likelihood of precrastination according to the main hypothesis offered here.

Finally, practical questions arise. Are accidents due to procrastination, and how can they be prevented? Is the fast-food industry a reflection of precrastination? Do people interrupt others in conversation to reduce mental workload and not just to exert power over them? Do people multitask because of precrastination? Finally, do people precrastinate to different degrees in different cultures and social settings? These are all important questions. We expect answers to be sought for them sooner rather than later.

Recommended Reading

Rosenbaum, D. A., Gong, L., & Potts, C. A. (2014). (See References). The first article to report on and name precrastination.

Wasserman, E. A. (2018). (See References). A review of evidence concerning precrastination that connects that evidence with a long history of interest in anticipatory learning, sensitivity to stimuli originating outside of the body, and brain evolution.

Zhu, M., Yang, Y., & Hsee, C. K. (2018). (See References). A description of the mere-urgency effect—the tendency to choose less important tasks that must be completed immediately rather than more important tasks that can be completed later.