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How do we decide where to search for a target? Optimal search relies on first considering the relative informational value of different locations and then executing eye movements to the best options. However, many participants consistently move their eyes to locations that can be easily ascertained to neither contain the target nor provide new information about the target's location. Here, we asked whether this suboptimal search behaviour represents a specific example of a general tendency towards precrastination: starting sub-goals of a task before they are needed, and in so doing, spending longer time on doing the task than is necessary. To test this hypothesis, we asked 200 participants to do two tasks: retrieve two heavy buckets (one close and one far) and search for a line segment. Precrastination is defined as consistently picking up the closer bucket first, versus the more efficient strategy of picking up the farther bucket first. Search efficiency is the proportion of fixations directed to more cluttered regions of the search array. Based on the pilot data, we predicted an association of precrastination with inefficient search strategies. Personality inventories were also administered to identify stable characteristics associated with these strategies. In the final dataset, there was no clear association between search strategy and precrastination, nor did these correlate strongly with any of the personality measures collected. This article received in-principle acceptance (IPA) at Royal Society Open Science on 29 January 2020. The accepted Stage 1 version of the manuscript, not including results and discussion, may be found at https://osf.io/p2sjx. This preregistration was performed prior to data collection and analysis.

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Effective handling of objects requires proper use of the hands. If the object handling is done while standing or walking, it also requires proper use of the feet. We asked how people position their feet to meet future and ongoing object-handling demands. In previous research on this topic, participants walked to a table and picked up an object for a single displacement from one place to another. These studies shed light on sensitivity to kinematics but, strictly speaking, may not have revealed anything about sensitivity to dynamics. In the present study, we asked participants to walk to a table to move an object back and forth over different distances and at different rates. Prior to walking to the table, participants had full knowledge of what the task would be. By using a rhythmic rather than discrete object placement task, we could analyze participants' sensitivity to dynamics as well as kinematics. Consistent with our expectation that participants would tune their foot separations to demands related to dynamics, we found that stance width was wider for long than for short object displacements and was more pronounced for high displacement rates than for low displacement rates. Also consistent with our expectations about planning, these effects were evident as soon as participants reached the table. Our results add to the limited research on coordinated action of the hands and feet in purposeful object manipulation.

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Returning home from the grocery store with a car full of groceries requires decisions about how many bags to carry when. If the decisions exemplify procrastination, people should carry more bags per trip in late trips than in early trips (putting the hard work off until later), but if the decisions exemplify the recently discovered phenomenon of pre-crastination (Rosenbaum et al. in Psychol Sci 25: 1487-1496, 2014), people should carry more bags per trip in early trips than in late trips (doing the hard work early). To distinguish between these possibilities, we asked university students to carry 5 or 11 dodgeballs from one bin to another 4, 8, 12, or 16 feet away in as many trips as they wished. A random half of the subjects did the tasks with an additional requirement to memorize and then recall 7 digits after carrying all the balls from the home to the target bin. Consistent with pre-crastination, participants carried the most balls per trip in early trips, and consistent with the hypothesis that pre-crastination relates to memory load, the number of balls carried per trip was affected by the presence of a memory load. The results add to the growing evidence for the generality of pre-crastination.

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How far away from each other people sit or stand reveals much about their social proximity, but merely sitting or standing may not test the limits of social boundaries as much as collaborating on tasks requiring physical coordination. In this study, we asked university students to walk two abreast while carrying a long pipe from one end of a workspace to another. Hurdles in the workspace forced the dyads to decide whether to walk close together without stepping over the hurdles or walk farther apart, stepping over the hurdles. The subjects often chose the latter option, stepping over 18-inch high hurdles rather than walking on level ground.

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How do people determine the relative difficulty of mental tasks and physical tasks, and how do they determine the preferred order of such tasks? Is it harder to make such decisions if 1 task is mainly mental and the other is mainly physical than if both tasks are the same kind? To address these questions, we conducted 3 experiments. In experiment 1 we asked participants to judge the relative difficulty and preferred ordering of mental tasks (math problems). In experiment 2 we asked participants to judge the relative difficulty and preferred ordering of physical tasks (moving a bucket back and forth). In experiment 3 we asked participants to judge the relative difficulty and preferred ordering of the same mental and physical tasks as in the first 2 experiments but with 1 of the tasks being mental and the other being physical. We reasoned that if mental task difficulty and physical task difficulty share a common code and if task ordering is systematically related to task difficulty, then judgments in experiment 3 should be as systematic as judgments in Experiments 1 and 2. The results confirmed the prediction and helped extend the notion of common codes for perception and performance to the evaluation of task difficulty and task ordering. A surprising finding was that mental difficulty was implicitly judged to be more important than physical difficulty for the tasks and population studied here. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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People often try to complete tasks as soon as possible, even at the expense of extra effort-a phenomenon called precrastination (Rosenbaum et al., 2014). Because precrastination is so widespread-as in answering emails too quickly, submitting papers before they have been polished, or, on larger scales, convicting people in the rush to judgment, or even going to war in the rush for revenge-it is important to understand its basis. Building on previous work on this phenomenon, we focused on two plausible accounts of it. According to the behavioral account, there is a desire to act for the sake of acting itself. According to the cognitive account, there is a desire to shorten one's mental to-do list so cognitive resources can be directed to other things. We invented a new task to distinguish between these hypotheses. Our participants made yes-no decisions under the requirement that they always respond twice per trial. We found that participants took longer for the first choice than the second and rarely changed their minds, even when second response accuracy was emphasized. This outcome went against the behavioral account, which predicted shorter first-response times than second-response times and lower (near chance) first-response accuracies than second-response accuracies. Instead, the data clearly showed that participants did all or most of their decision-making up front. The double-response reaction time task provides a new tool for studying decision dynamics. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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A great deal of research has concerned choices of goods or services with different values receivable at various times. Temporal discounting - the magnification of values that can be obtained sooner rather than later - has proven to be immensely important in this regard. In the present article, we shift the focus from the receipt of goods or services to the performance of tasks. We show that temporal discounting also applies to task choices. Pre-crastination, the phenomenon we point to, was discovered by Rosenbaum, Gong, and Potts (2014) and is the tendency to hasten tasks even at the expense of extra energy. Pre-crastination was discovered in a study of psycho-motor performance, where the focus was on biomechanical factors affecting task choices. In the present article, we review that research, showing how the tendency found in the initial experiments are in fact illustrative of a more general motor-control tendency to inhibit easy forms of movement for the sake of later performance goals. Such inhibitory control may also be the basis for pre-crastination, provided one assumes that pre-crastination keeps working memory as clear as possible. A wide range of behavioral choices fit under the rubric of pre-crastination, such as answering emails too soon, submitting articles before they are ready, judging others before they should be judged, convicting others to get cases over with, and, in the worst case, going to war prematurely. Lack of temperance in these choices may seem to arise from impulsivity, but we argue against that view. The desire to "clear the decks" to be prepared for new challenges is, we suggest, a more apt account of pre-crastination.

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Which task is easier, doing arithmetic problems of specified form for some specified duration, or carrying a bucket of specified weight over some specified distance? If it is possible to choose between the "more cognitive" task and the "more physical" task, how are the difficulty levels of the tasks compared? We conducted two experiments in which participants chose the easier of two tasks, one that involved solving addition or multiplication problems (Experiment 1) or addition problems with different numbers of addends (Experiment 2) for varying amounts of time (in both experiments), and one that involved carrying a bucket of different weights over a fixed distance (in both experiments). We found that the probability of choosing to do the bucket task was higher when the bucket was empty than when it was weighted, and increased when the cognitive task was harder and its duration grew. We could account for the choice probabilities by mapping the independent variables onto one abstract variable, Φ. The functional identity of Φ remains to be determined. It could be interpreted as an inferred effort variable, subjective duration, or an abstract, amodal common code for difficulty.

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What makes a task hard or easy? The question seems easy, but answering it has been hard. The only consensus has been that, all else being equal, easy tasks can be performed by more individuals than hard tasks, and easy tasks are usually preferred over hard tasks. Feghhi and Rosenbaum (Journal of Experimental Psychology: Human Perception and Performance, 45, 983-994, 2019) asked whether task difficulty might reflect a single amodal quantity. Based on their subjects' two-alternative forced-choice data from tasks involving choices of tasks with graded physical and mental challenges, the authors showed that the difficulty of passing through a narrow gap rather than a wide gap was psychologically equivalent to memorizing an extra .55 digits. In the present study, we extended this approach by adding new arguments for the hypothesis that task difficulty might reflect a single amodal quantity (inspired by considerations of physics, economics, and the common code hypothesis for the study of perception and action), and we tested narrower gaps than before to see whether we would find a larger equivalent memory-digit. Consistent with our prediction, we obtained a value of .95. We suggest that our multi-modal two-alternative forced-choice procedure can pave the way toward a better understanding of task difficulty.

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The ultimate tool, it could be said, is the brain and body. Therefore, a way to understand tool use is to study the brain's control of the body. A more manageable aim is to use the tools of cognitive science to explore the planning of physical actions. Here, I focus on two kinds of physical acts which directly or indirectly involve tool use: producing finger-press sequences, and walking and reaching for objects. The main question is how people make choices between finger-press sequences, and how people make choices between walk-and-reach sequences. Are the choices made with reference to motor imagery, in which case the longer the sequences are the longer it takes to choose between them, or are shortcuts taken which rely on distinctive features of the alternatives? The reviewed experiments favor the latter alternative. The general view of action planning emerging from this work is one in which action features are highlighted and held in memory, not just to choose between potential actions but also to control the unfolding of long actions over time. Speculations are offered about tool use.

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How do we compare the difficulty of different kinds of tasks, and how we do sequence tasks of different kinds when the basis for the ordering is the tasks' difficulty levels? The ability to do these things requires a common currency, but the identity of that currency, if it exists, is unknown. We hypothesized that people may believe that the time that attention is paid to tasks enables people to compare and sequence tasks of different kinds. To evaluate this hypothesis, we tested three groups of participants. One group estimated the proportion of time that performance of a task requires attention-what we called attention time proportions or ATPs. We obtained ATPs for tasks that were "more intellectual" (counting) and others that were "more physical" (locomotion). Two additional groups made 2-alternative-forced-choice decisions about the relative ease and preferred sequencing of all possible pairs of tasks for which ATPs were independently obtained. We found that ATPs predicted judgments of task difficulty and preferred task order.

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Little is known about how effort is represented for different kinds of tasks. Recently, we suggested that it would help to establish empirical benchmarks for this problem. Accordingly, Feghhi and Rosenbaum (Journal of Experimental Psychology: Human Perception and Performance, 45:983-994, 2019) estimated how many additional digits to be memorized corresponded to navigating through a narrow gap versus a wide gap. The estimates were based on a study in which participants chose between walking paths with associated memory demands. We found that participants were equally willing to choose to walk through a narrow gap as to walk through a wide gap when the narrow-gap walk required memorization of 0.55 fewer digits on average than the wide-gap walk. In the present experiment, we sought to replicate and extend this previous finding in two ways: (1) by presenting the memory digits in auditory rather than visual form to test the hypothesis that participants used phonological recoding of the visually presented digits; and (2) by providing a new metric of the relative difficulty of navigation errors compared to recall errors. We provided 36 university students with two action/memorization options per trial and asked them to choose the easier option. Each option had varying degrees of physical demand (walking through a wide or narrow gap) and mental demand (memorizing 6, 7, or 8 digits). We expected performance to be comparable to what we observed earlier with visually presented digits to be memorized, and this prediction was confirmed. We also used a new metric to show that navigation errors were implicitly judged to be 17% more costly than recall errors. The fact that this percentage was not 0 indicates that reducing percent error was not the only basis for reducing effort.

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What accounts for the subjective difficulty of a task? It is easy to suggest ad hoc measures, such as how many individuals can do the task, how long it takes them to do it, how likely they are to complete it, how much attention it requires, and so on. But having such ad hoc measures may miss the point that it is possible to judge the relative difficulty of different kinds of tasks, suggesting that there may be a common basis for judging task difficulty. If there is such a common basis, it might be used to compare the difficulties of different kinds of task. We tested two hypotheses about what the common basis might be. One was that time serves this role. This hypothesis was attractive because time is amodal and previous studies have provided support for the hypothesis that time might be an index of task difficulty. The other hypothesis was new. According to the new hypothesis, the subjective difficulty of a task corresponds to its estimated sustainability. We obtained results consistent with the time hypothesis, but our data were less supportive of the sustainability hypothesis.

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A core question in the study of the dynamics of cognition is how tasks are ordered. Given two tasks, neither of which is prerequisite for the other and neither of which brings a clearly greater reward, which task will be done first? Few studies have addressed this question, though recent work has suggested one possible answer, which we here call the cognitive-load-reduction (CLEAR) hypothesis. According to the CLEAR hypothesis, there is a strong drive to reduce cognitive load (to "clear one's mind"). Given two tasks, one of which is more cognitively demanding than the other, the more cognitively demanding task will tend to be done first. We tested this prediction using a novel method inviting participants to freely choose when to perform each of c = 5, 10, or 15 items per category in item-generation tasks relative to b = 10 box-moving tasks. The box-moving tasks were cognitively undemanding relative to the item generation tasks, whose cognitive difficulty presumably grew with c. A full half of our n = 122 participants chose to complete all of the c tasks before performing any of the b tasks, and most other participants chose to complete a majority of the c tasks before any of the b tasks. This result is consistent with the CLEAR hypothesis. Speed on the box-moving task decreased the later the category-generation task was completed, supporting another CLEAR prediction. The general method used here provides direction for future work on task order choices in cognitive and perceptual-motor tasks.

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People judge the relative difficulty of different kinds of tasks all the time, yet little is known about how they do so. We asked university students to choose between tasks that taxed perceptual-motor control and memorization to different degrees. Our participants decided whether to carry a box through a wide (81 cm) or narrow (36 cm) gap after memorizing six, seven, or eight digits. The model that maximized the likelihood of observing the choice data treated the extra physical demand of passing through the narrow gap as functionally equivalent to memorizing an extra .55 digits. Substantively, the model suggested that participants judged the difficulty of the compound tasks in terms of separate resources. The approach introduced here may help interrelate different kinds of task difficulty. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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It is unusual for very little to be known about a highly influential psychological scientist, but that is the case for the individual responsible for promoting one of the most influential laws of the field, the Power Law of Learning, as well as a seminal model of aiming performance. The individual, who published as E. R. F. W. Crossman, is shrouded in mystery. The authors of the present article sought to find out who Crossman is or was. We discuss the scholarly context for Crossman's work, including the classroom event at which we resolved to find out more about Crossman. In the course of our investigation, which took quite a bit of detective work, we learned that many other psychological scientists have been curious about Crossman as well. Rather than resolve the mystery in this abstract, we leave the reader in the state we were in at first, wanting to satisfy our curiosity and, finally, feeling we had learned important things, not only about the individual at the heart of the investigation, but also about our field in general.

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Research on motor planning has revealed two seemingly contradictory phenomena. One is the end-state comfort effect, the tendency to grasp objects in physically awkward ways for the sake of comfortable or easy-to-control final postures (Rosenbaum et al., Attention and Performance XIII: Motor representation and control, Lawrence Erlbaum Associates, Hillsdale, New Jersey, 1990). The other is pre-crastination, the tendency to hasten the completion of tasks even at the expense of extra physical effort (Rosenbaum et al., Psychol Sci 25:1487-1496, 2014). End-state comfort seems to reflect emphasis on final states, whereas pre-crastination seems to reflect emphasis on initial states. How can both effects exist? We sought to resolve this seeming conflict by noting, first, that the effects have been tested in different contexts. End-state comfort has been tested with grasping, whereas pre-crastination has been tested with walking plus grasping. Second, both effects may reflect planning that aids aiming, as already demonstrated for end-state comfort but not yet tested for pre-crastination. We tested the two effects in a single walk-and-grasp task and found that demands on aiming influenced both effects, although precrastination was not fully influenced by changes in the demands of aiming. We conclude that end-state comfort and precrastination are both aiming-related, but that precrastination also reflects a desire to hasten early task completion.

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The science of mental life and behavior has paid scant attention to the means by which mental life is translated into physical behavior. Why this is so was the topic of a 2005 American Psychologist article whose main title was "The Cinderella of Psychology." In the present article, we briefly review some of the reasons why motor control was relegated to the sidelines of psychology. Then we point to work showing that experimental psychologists have much to contribute to research on action generation. We focus on studies showing that actions are generated in a way that, at least by default, minimize changes between successive actions. The method is computationally as well as physically economical but also requires consideration of costs, including costs of different kinds. How such costs are compared is discussed in the next section. The final section offers comments about the future of psychologically focused action research. Two additional themes of the review concern methods for studying action generation. First, much can be learned through naturalistic observation. Second, subsequent experiments, designed to check naturalistic observations, can use very simple equipment and procedures. This can make the study of action generation easy to pursue in the psychology laboratory.

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Precrastination, as opposed to procrastination, is the tendency to embark on tasks as soon as possible, even at the expense of extra physical effort. We examined the generality of this recently discovered phenomenon by extending the methods used to study it, mainly to test the hypothesis that precrastination is motivated by cognitive load reduction. Our participants picked up two objects and brought them back together. Participants in Experiment 1 demonstrated precrastination by picking up the near object first, carrying it back to the farther object, and then returning with both. Also, participants given an additional cognitive task (memory load) had a higher probability of precrastinating than those not given the added cognitive task. The objects in Experiment 1 were buckets with balls that had a very low chance of spillage; carrying them required low demands on attention. The near-object-first preference was eliminated in Experiment 2, where the near and far objects were cups with water that had a high chance of spillage; carrying them required higher demands on attention. Had precrastination occurred in this case, it would have greatly increased cognitive effort. The results establish the generality of precrastination and suggest that it is sensitive to cognitive load. Our results complement others showing that people tend to structure their behavior to minimize cognitive effort. The main new discovery is that people expend more physical effort to do so. We discuss the applied implications of our findings, as well as the possibility that precrastination may be a default, automatic behavior.

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When tasks are performed, other tasks are postponed, at least implicitly. Little is known about how task sequencing is determined. We examined task sequencing in object transfer tasks for which either task could easily or logically come before the other. The task was to transfer ping pong balls from two buckets into a bowl. To perform the task, participants walked down a corridor, picked up one of two buckets (their choice), carried it to the end of the corridor, transferred the balls from the bucket into a bowl, carried the bucket back to the start position, and then did the same with the other remaining bucket. As in an earlier study where just one of two buckets had to be carried to the end of a corridor (Rosenbaum et al. Psychol Sci 25(7):1487-1496, 2014), participants showed a marked tendency to start with the near bucket. The near-bucket preference was modulated only to a small extent by the number of balls that could be emptied into the bowl. The relative lack of importance of the number of balls to be transferred (to finish the first task more quickly or to get closer to the end goal of transferring all balls into the bowl) was further demonstrated by the fact that the effect of the number of balls to be transferred did not depend on how the emptying was supposed to occur (by pouring the balls or placing the balls one at a time into the bowl), or by whether the instruction focused on filling the bowl or emptying the buckets. The results suggest that the near-bucket preference reflects a strong inclination to start the task (sub-goal) as soon as possible rather than complete the task (sub-goal) as soon as possible. Starting the task as soon as possible may be related to the affordance triggered by the sight of the near object or by the freedom to perform without having to inhibit a reach for a bucket when the performer is empty-handed. Starting a task sooner may free up cognitive resources for subsequent decision-making.

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