Cognitive Miserliness Preserves the Self- Regulatory Resource Andrew James Vonasch

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2016 Cognitive Miserliness Preserves the Self- Regulatory Resource Andrew James Vonasch

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COLLEGE OF ARTS AND SCIENCES

COGNITIVE MISERLINESS PRESERVES THE SELF-REGULATORY RESOURCE

ANDREW VONASCH

A Dissertation submitted to the Department of Psychology in partial fulfillment of the requirements for the degree of Doctor of Philosophy

2016 Andrew Vonasch defended this dissertation on June 10, 2016. The members of the supervisory committee were:

Roy Baumeister Professor Directing Dissertation

Al Mele University Representative

E. Ashby Plant Committee Member

James McNulty Committee Member

Colleen Kelley Committee Member

The Graduate School has verified and approved the above-named committee members, and certifies that the dissertation has been approved in accordance with university requirements.

Dedicated to the memory of Bill Banks, who taught me that it was possible to use science to answer philosophical questions about the mind, and who inspired me to spend my life doing that. And to Dimitri, who brought love, humor, and joy to everyone he encountered.

iii ACKNOWLEDGMENTS

Numerous people contributed directly or indirectly to the creation of this dissertation. I could not have completed this research without the help of 48 research assistants who have worked on these and other projects for the past six years: Kirsten Harvey, Celia Ibarra, Amanda Rohan, Hernan Pinto-Zambrano, Rafael Gonzalez, Rafael Batista, Dade Stromwall, Craig Howey, Daniel Colvin, Allene Korie, Sarah Radford, Mariana Villegas, Jody O’Steen, Katherine Burkhardt, Xenia Hatzilas, Marco Romero, Korey Jones, Julie Octaviano, Alyse Johnson, Heather Maranges, Frances Bigay, Corey Berg, Mark Lopez, Taylor Langley, Garrett Brady, Shaina Downing, David Linder, Zachary Presley, Nate McAuliffe, Breona Alvarado, Alex DiChiara, Megan McConnaughay, Megan Attanasio, Sam Jones, Nicole Connoly, Vera Burns, Mary Funston, Alexis Garrett, Jonathan Cohen, Melissa Kotziers, Kritikaa Agnani, Eli Zajchowski, Jessica Wheeler, Gabi Munoz, Emily Mingote, Clint Regal, Shannon McDonald, Leandro Lescailles, Zachary Guy, and Katie Lewis. I hope I remembered everyone. Without them, there would be no data, and therefore no evidence in support of my hypotheses.

I thank the many scholars who have mentored me and contributed to my growth as a scholar. Thanks to Roy Baumeister for inspiring me to test many interesting ideas, and to write about them clearly. Although Roy was my primary advisor during graduate school, but so many others helped round out my education and taught me skills that I now use as a researcher: Kathleen Vohs, Jon Maner, E.J. Masicampo, Paul Conway, Al Mele, John Bargh, Jaime Napier, Bill Banks, Cecilia Conrad, and Suzanne Thompson merit specific mention.

Special thanks go to my labmates who shared space, resources, and materials with me. I learned a lot from my “older” lab siblings, Sarah Ainsworth, Jessica Alquist, Jina Park, and Lauren Brewer. I have, in turn, tried to share what I’ve learned with my “younger” lab siblings, Heather Maranges, Mike Mackenzie, Tania Reynolds, and Bo Winegard. Thanks, too, to my conference roommates Mike Ent, Justin Moss, Jenny LaCosse, Heather, and Hallgeir Sjastad.

Finally, thanks to the people who helped support my wellbeing during this long process. Thanks to the people and organizations that kept me fit and happy: Swim Club, Terrible Tallahassee Soccer, and my racquetball partners Chris Vorstius and Rafael Kampmann. Thanks to Student Life Cinema. Thanks to Bo for the long walks. Most of all, thanks to my family and Allison for their love and support at all times.

iv TABLE OF CONTENTS

List of Figures ...... vi Abstract ...... vii

1. INTRODUCTION ...... 1

2. STUDY 1 ...... 8

3. STUDY 2 ...... 11

4. STUDY 3 ...... 16

5. GENERAL DISCUSSION...... 32

APPENDICES ...... 41

A. STUDY 1 HUMAN SUBJECTS APPROVAL MEMO ...... 41 B. STUDY 1 MATERIALS ...... 43 C. STUDY 2 HUMAN SUBJECTS APPROVAL MEMO ...... 53 D. STUDY 2 MATERIALS ...... 54 E. STUDY 3 HUMAN SUBJECTS APPROVAL MEMO ...... 62 F. STUDY 3 MATERIALS ...... 64

References ...... 77

Biographical Sketch Biographical Sketch ...... 82

v LIST OF FIGURES

Figure 1. Depleted participants solved fewer CRT problems correctly than non-depleted participants because depleted participants used more heuristic responses. All error bars are standard errors...... 10

Figure 2. Participants randomly assigned to use intuition rather than controlled thinking to solve word problems subsequently reacted more quickly to incongruent Stroop task items...... 14

Figure 3. Participants high in trait self-control used more heuristics to solve CRT problems when they anticipated a future problem solving task...... 24

Figure 4. Participants high in trait self-control answered fewer questions correctly when they anticipated a future problem solving task...... 26

Figure 5. Participants high in trait self-control thought the problems were easier when they anticipated a future problem solving task...... 28

vi ABSTRACT

People use heuristics, even though these produce wrong answers to problems. The present

research tested an explanation for this seemingly irrational phenomenon. People use heuristics to preserve mental energy and avoid self-regulatory failures that occur when one’s mental resources become depleted (i.e., ego depletion). Three studies tested different hypotheses derived from this

model. Study 1 found that people assigned to complete a depleting task (compared to an easy,

non-depleting task) subsequently used more heuristics to solve word problems. Study 2 found

that people assigned to use intuition (rather than controlled thinking) to solve the same set of problems were more likely to use heuristics to solve the problems. Crucially, using intuition also

improved performance on a subsequent self-control task (the Stroop test). Study 3 found that people who merely anticipated a future effortful task (compared to anticipating no future task)

were more likely to use heuristics to solve the problems currently in front of them. People high in

trait self-control were especially likely to use heuristics in this apparently strategic manner.

Surprisingly, however, people were seemingly unaware that they had adopted the strategy to use

heuristics to save energy for the future. Overall, the results supported the idea that one reason for

cognitive miserliness is to avoid ego depletion.

vii CHAPTER 1

INTRODUCTION

Cognitive miserliness preserves the self-regulatory resource

People often use mental shortcuts rather than using effortful, controlled thinking to solve each problem they encounter in their lives. This tendency toward lazy thinking is called cognitive miserliness. Because cognitive misers rely on mental shortcuts, they often make errors that could be avoided if they used controlled thinking (see Ariely, 2008; Kahneman, 2011).

Although cognitive misers are prone to making avoidable errors, some scholars have proposed that cognitive miserliness is a rational strategy because there are benefits to making decisions quickly and intuitively (Gigerenzer & Goldstein, 1996; Simon, 1955). In this dissertation, I test an additional, complementary explanation for cognitive miserliness: miserly thinking prevents the depletion of the limited resource that people use for self-regulation. Miserliness allows people to preserve the self-regulatory resource until it is needed for the most important tasks.

Cognitive miserliness

Cognitive miserliness is the tendency for people to think, solve problems, and make choices using effortless, rather than effortful ways of thinking (Fiske & Taylor, 1991; Tversky &

Kahneman, 1974). People can think effortlessly or effortfully (Chaiken & Trope, 1999;

Kahneman, 2011). There are many benefits to effortful thinking. Most obviously, effortful thinking is more likely to yield correct answers to problems, and people are usually more satisfied with their choices when they make them effortfully (Kahneman, 2011; Newell, Wong,

Cheung, & Rakow, 2009; Payne, Samper, Bettman, & Luce, 2008; but see Dijksterhuis, Bos,

Nordgren, & van Baaren, 2006). However, effortful thinking is slower than effortless thinking

and in many situations speed would be a major decision-making cost. For example, when

deciding which way to run from a lion, carefully deliberating would cost one precious time that

would be better spent fleeing in any direction. Time is also an important cost in nonemergency

situations because of opportunity cost. Spending time deciding which color shirt to wear is time

not spent working to gain valuable resources or relaxing and enjoying oneself. Therefore, most

theories of cognitive miserliness emphasize that the quicker heuristic decision-making style is

functional because time spent deliberating is costly (Gigerenzer & Goldstein, 1996).

In addition to being quicker, using heuristics also bypasses the need for the self to use

effortful reasoning. Controlled thinking feels more effortful, and theorists have argued that

limiting effort may also be an important benefit of using heuristics (Kahneman, 2011). Limiting

effort (not merely the feeling of effort) would be functional if it preserved the ability of the self

to engage in self-regulation for future tasks. If self-regulation depends on a limited resource, then preserving that resource for important tasks by conserving it during relatively unimportant tasks would be functional, even adaptive and beneficial for the self.

The strength model of self-regulation

Self-regulation is the process by which people control the self. It is used to override habits, exert self-control to increase goal-pursuit and decrease undesired behavior, plan effectively, and respond actively rather than passively (Baumeister, 2010). Good self-regulation is associated with a broad array of good outcomes, including better educational outcomes, better work success, reduced addictive behaviors, reduced criminality, better health, and better relationships with others (Tangney, Baumeister, & Boone, 2004). Overall, good self-regulation is one of the most important traits in predicting successful life outcomes.

The strength model of self-regulation holds that self-regulation operates by consuming a

limited energy resource. When this resource becomes depleted, people become less volitional (or

ego-depleted) because of reduced energy (Baumeister, Muraven, & Tice, 2000; Baumeister &

Vohs, 2015; Hagger, Wood, Stiff, & Chatzisarantis, 2010). A broad literature has supported this

model. For example, people who are randomly assigned to complete a depleting task are later

less able to successfully self-regulate to persist in problem solving activities, make effective

choices, and restrain themselves from breaking their diet, being unethical, or being overly

aggressive (Baumeister, Bratslavsky, Muraven, & Tice, 1998; Gino, Schweitzer, Mead, &

Ariely, 2011; Hagger, Wood, Stiff, & Chatzisarantis, 2010; Kahan, Polivy, & Herman, 2003,

Stucke & Baumeister, 2006; Vohs et al., 2014).

The use of self-regulation produces a mental state commonly referred to as ego depletion,

wherein people’s self-regulatory efforts flag. According to the strength model, self-regulation performance decreases as a limited resource in the brain dwindles. Recently, several alternatives

to the strength model have been proposed (Inzlicht & Schmeichel, 2012; Kurzban, Duckworth,

Kable, & Myers, 2013; Job, Dweck, & Walton, 2010) in which self-regulatory performance

suffers for reasons other than depletion of a limited resource. These theories propose that performance suffers after repeated self-regulation efforts because people believe that willpower

is limited (Job, Dweck, & Walton, 2010), or that because people become less motivated to pursue work-like tasks after exerting self-control (Inzlicht & Schmeichel, 2012; Kurzban,

Duckworth, Kable, & Myers, 2013). Despite disagreement on the mechanisms that produce ego

depletion, most scholars agree on the behavioral effect—using self-control decreases subsequent

self-regulatory efforts (although even the existence of the effect has recently been challenged;

see Carter & McCollough, 2014; Hagger, et al., in press).

Ego depletion decreases the use of controlled, effortful thinking relative to automatic thinking. Depleted people are less able to solve problems that require fluid intelligence (i.e., flexible in-the-moment thinking), even though they do not forget facts that have already crystalized in their minds and do not require additional controlled thinking to recall (Schmeichel,

Vohs, & Baumeister, 2003). People postpone and avoid making effortful decisions when they are depleted, and when they do decide, those decisions tend to be unwise (Vohs, et al., 2014). People are more easily persuaded by fallacious arguments that they are able to rebuff when their resources are more plentiful (Janssen, Fennis, Pruyn, & Vohs, 2008; Otgaar, Alberts & Cuppens,

2012; Wheeler, Brinol, & Hermann, 2007). People are more likely to use heuristics to solve problems (and therefore make predictable errors) when they are depleted than when not

(Masicampo & Baumeister, 2008; Pocheptsova, Amir, Dhar, & Baumeister, 2009; Pohl,

Erdfelder, Hilbig, Liebke, & Stahlberg, 2013).

Preserving resources

One reason why people might use less effortful styles of thinking when they are depleted is to preserve the self-control resource for future tasks. There is some evidence that when people conserve energy by sacrificing performance on earlier tasks they are able to successfully allocate that energy to subsequent tasks that they deem more important (Muraven, Shmueli, & Burkley,

2006). However, in that study, conserving self-regulation entailed a major cost to performance on the earlier task. There are, however, strategies that can conserve the self-regulatory resource without usually harming performance on other tasks. Using heuristics to solve problems is one way in which people can save energy without harming performance (on most types of question).

Heuristics allow one to rely on automatic, effortless thinking rather than engage in controlled, effortful thinking.

There are tradeoffs between using controlled vs. automatic thinking. Automatic thinking

requires less effort and is faster but is less accurate than controlled thinking (Chaiken & Trope,

1999; Kahneman, 2011; Stanovich & West, 2000). Tverksy and Kahneman famously

demonstrated a myriad of cases in which people made suboptimal and seemingly irrational

choices because they used heuristics rather than controlled thinking. Less appreciated, however,

is the fact that outside of the laboratory heuristics are mostly (but not always) accurate

(Czerlinski, Gigerenzer, & Goldstein, 1999; Gigerenzer & Goldstein, 1996; Gigerenzer & Todd,

1999; Kahneman, 2011; Tversky & Kahneman, 1974). Using heuristics to solve problems may

allow one to both solve a problem correctly (most of the time) and preserve energy for a future

use of self-regulation. Thus, by using heuristics, one might be able to avoid facing the

effort/accuracy tradeoff (in most cases).

Cognitive reflection

Cognitive reflection is the tendency to resist reporting incorrect intuitive responses to problems (Frederick, 2005). Cognitive reflection involves two processes (Campitelli & Gerrans,

2014). First, one must notice that the intuition is incorrect and inhibit that response. Second, one

must solve the problem effortfully and give the correct response. The Cognitive Reflection Test

(CRT) consists of 3 word problems that generate incorrect intuitive responses. For example, “A bat and a ball together cost $1.10. The bat costs $1.00 more than the ball. How much does the ball cost?” The intuitive answer is 10 cents, but the correct answer is 5 cents.

The CRT is an ideal measure of whether someone is using controlled or automatic processing because the CRT detects whether a person used controlled vs. intuitive thinking to

solve each single problem. The vast majority of people who rely on automatic processing to

solve CRT problems using the intuitive answer. Likewise, the majority of people who notice that

controlled thinking is needed to solve the problem are able to produce the correct answer. Thus,

the CRT can distinguish between answers that were wrong because the person used only

intuition and no reflection, and answers that were wrong because the person overrode the

intuitive answer but did the math improperly.

Present research

Although rarely stated explicitly, the concept of cognitive miserliness implies that there is a limited resource with which one is miserly. A likely possibility is that the limited resource that cognitive misers conserve is the self-regulatory resource (Kahneman, 2011). It would be sensible to conserve this resource because self-regulation is vitally important for successfully completing many different tasks: avoiding temptation, making good decisions, persevering past difficult obstacles, etc. I conducted three studies testing different predictions of the thesis that the function of cognitive miserliness is to preserve self-regulatory resources.

One prediction is that when self-regulatory resources are depleted, people will become increasingly miserly in order to preserve the leftover resources. The resource is used for many important purposes. Using it to solve one problem means having less of it available to do something else. Even if the resource is not in immediate danger of running out, conserving the resource would allow one to avoid running out in the future if an important use of it becomes necessary. Using a heuristic could conserve the resource while still solving most problems correctly.

A second prediction is that using miserly strategies to preserve the self-regulatory resource will be an effective strategy. Using heuristics may help conserve the self-regulatory resource because they enable one to make decisions quickly and effortlessly, that in many cases are just as good as decisions made more effortfully (Gigerenzer & Todd, 1999). People who use

miserly strategies to solve problems will have more resources available to improve performance

on subsequent self-regulatory tasks. People who use controlled thinking to solve problems will

deplete their mental resources and their performance will suffer on subsequent tasks requiring

the resource. However, people who use intuition will retain more of their resources, enabling better performance on other tasks.

A third prediction is that people will be most likely to use a miserly strategy in the present when they anticipate having to successfully self-regulate in the near future. Although the resource is not yet depleted, it soon will be by the other task. In an effort to conserve it, people may use more heuristics when they know they will exert mental effort in the near future. Three studies tested each of the above hypotheses in turn.

CHAPTER 2

STUDY 1

Depletion increases the use of heuristics

Study 1 tested whether depleted participants would be less likely than non-depleted participants to use cognitive reflection when solving word problems. All participants first established a habit of crossing out all es on a page of paper from a scientific article. Then, participants were randomly assigned either to continue crossing out all es or to override the habit and follow a more complex rule. Previous research has established that overriding a habit in this way is more depleting than continuing the habit (Baumeister, Bratslavsky, Muraven, & Tice,

1998).

Then, participants completed the Cognitive Reflection Test (CRT) (Frederick, 2005),

which is comprised of three word problems, including the bat and ball problem described above.

The problems are not particularly difficult to solve mathematically, but many people answer

incorrectly because they rely on the intuitive (heuristic) answer rather than using controlled processing to calculate the answer. I hypothesized that depletion would impair performance on

the CRT. Furthermore, although there are an infinite number of incorrect answers to each problem, I predicted that depletion would specifically increase participants’ reliance on heuristics

to solve the problems. Therefore, depleted participants would be more likely to use the heuristic

wrong answer, not just any wrong answer.

Method

Participants. Forty-five undergraduates (36 female) participated for partial course credit.

Participants were randomly assigned to either a depleting condition or a non-depleting condition.

Procedure. Participants’ first task manipulated self-control resource depletion.

Participants were given a page of text and crossed out every e on the page to induce a habit. Then participants were given a second page with instructions that varied by condition. In the non-

depletion condition, participants were instructed to continue crossing out every e on the page. In the depletion condition, participants were told to cross out every e except if it was followed by a vowel or a vowel appeared two letters before the e.

Next, participants completed the Cognitive Reflection Test (Frederick, 2005), a measure of cognitive reflection, or the tendency to recognize and correct one’s incorrect intuitions. The

CRT consists of three word problems, each of which elicits an incorrect intuitive answer.

For exploratory purposes I included the Ten Item Personality Inventory (TIPI) (Gosling,

Rentfrow, & Swann, 2003), the Trait Self-Control Scale (Tangney, Baumeister, & Boone, 2004), and a measure of discounting (Frederick, 2005) at the end of the study.

Results

As expected, depleted participants answered fewer CRT problems correctly (M = 0.33,

SE = 0.198, 95% CI = 0.01-0.65) than non-depleted participants (M = 0.95, SE = 0.21, 95% CI =

2 0.42-1.48), F(1, 43) = 4.58, p = .036, ηp = .096. Participants who answered incorrectly almost always answered using the answer provided by the heuristic (as opposed to some other wrong answer). Overall, participants answered 29 questions correctly, 105 with the heuristic response, and 7 with any other incorrect response. Depleted participants were marginally more likely to answer the CRT problems using the heuristic response (M = 2.50, SE = 0.20, 95% CI = 2.17-

2.83) than were non-depleted participants (M = 1.95, SE = 0.22, 95% CI = 1.40-2.50), F(1, 43) =

2 3.36, p = .074, ηp = .073. See Figure 1.

3 2.5 2 1.5 1 0.5

Participant Answers CRT Answers to Participant 0 Average # of Correct CRT Average # of Heuristic CRT Answers Answers Depletion No Depletion

Figure 1. Depleted participants solved fewer CRT problems correctly than non-depleted participants because depleted participants used more heuristic responses. All error bars are standard errors.

Discussion

Depletion impaired cognitive reflection. Depleted participants answered fewer CRT

questions correctly than non-depleted participants. Depleted participants answered predictably

incorrectly. That is, they did not fail to respond to the questions, nor answer randomly. Depleted participants did answer the CRT questions, but they were more likely than non-depleted participants to rely on the intuitive answer to respond. Depleted participants might have engaged

in less cognitive reflection in order to avoid expending cognitive effort solving difficult problems

when effortless, intuitive heuristic answers would suffice to “solve” those problems.

CHAPTER 3

STUDY 2

Using heuristics attenuates depletion

Study 2 tested the hypothesis that using intuition would enable a person to avoid the

depleting effects of cognitive reflection. The main prediction was that using intuition would

conserve more energy than using effortful thinking to solve the CRT, and that the conserved

energy would enable better performance on a self-regulatory task.

The order of the variables was the opposite of Study 1: first came the CRT and then came

the depletion measure. All participants first completed a 10-item version of the CRT (Frederick, personal communication, 2012). They were randomly assigned to use either intuition or

cognitive reflection to solve the problems. The CRT was chosen because it provided a natural

manipulation check—participants who used intuition were expected to use more heuristics than participants who used controlled thinking to solve the problems. The long version of the CRT

was chosen over the three question version to lengthen the task and strengthen the power of the

manipulation. After completing the CRT, participants completed the Stroop task (Stroop, 1935).

The Stroop task involves quickly reading the font color of words (i.e., red, yellow, blue, green)

that are presented in either congruent (e.g., ‘red’ written in red font) or incongruent color (e.g.,

‘red’ written in yellow font). This task involves overriding the habitual response to read words,

and is considered a classic measure of the executive functioning of mind. I hypothesized that participants would react faster to the incongruent Stroop items when they had used intuition

rather than cognitive reflection on the previous task.

Method

Forty undergraduate students (27 female) came into the lab to participate in a study on

cognition and choices. Participants answered the long form of the Cognitive Reflection Test. By

condition, participants were instructed to answer either using their intuition or using controlled

thinking.

The instructions in the intuition condition were as follows. “Today’s study is about using

intuition to solve problems. For the first task we want to know people’s intuitive responses to a

set of questions. Please answer these problems in order. Read each question and answer using the

first answer that comes to mind. It does not matter if it is the right or wrong answer. In fact, you probably will the get the wrong answer sometimes. We just want to know what your intuition

tells you first. Just answer using your first intuitive guess for each problem and then knock on the

door when you’re done and we’ll start the next task.”

The instructions in the controlled thinking condition were as follows: “Today’s study is

about using deep thinking to solve problems. For the first task we want you to solve a set of

questions. Please answer these problems in order. Read each question carefully. You should

know that many of these are trick questions. Your first intuition will seem right but will actually be the wrong answer. For these problems, speed does not matter. We just want you to think

carefully and try to get the answers correct. Knock on the door when you’re done and we’ll start

the next task.”

After completing the 10 problem CRT, participants completed the Stroop task, which was

the main dependent variable. There were four Stroop practice trials followed by 48 Stroop trials

in the main task. Half of the main trials were incongruent trials (e.g., ‘red’ in green font) and half

were congruent trials (e.g., ‘green’ in green font).

Results

Manipulation checks. Each CRT problem had a correct answer and at least one common heuristic answer. I assumed that any participant who gave the heuristic answer had used a heuristic to solve that problem. I calculated the sum total number of heuristic answers each participant gave to the 10 problems. Participants who were instructed to use intuition to solve the problems were more likely to use heuristics (M = 6.15, SE = 0.50) than participants who were instructed to use controlled thinking to solve the problems (M = 4.00, SE = 0.43), F(1, 38) =

10.68, p < .01. Participants in the intuition condition solved fewer problems correctly (M = 0.90,

SE = 0.40) than participants in the controlled thinking condition (M = 1.95, SE = 0.41), F(1,38) =

3.31, p = .08. Participants in the intuition condition spent much less time solving the problems

(M = 246s, SE = 48) than participants in the controlled thinking condition did (M = 766, SE =

48), F(1,38) = 58.33, p < .001.

Main analyses. The first four Stroop trials were practice trials and were not analyzed.

(This decision was made a priori). To analyze reaction times to the Stroop task, I computed the average time for all correct trials (i.e., trials on which the participant pressed the correct button).

Only trials within 3 standard deviations from the group mean reaction time of correct responses were included. The mean reaction time was calculated for each participant for each trial type

(congruent and incongruent trials).

Controlling for participants’ trait self-control, participants in the intuitive thinking condition reacted more quickly to incongruent Stroop trials (M = 1027, SE = 39) than did participants in the controlled thinking condition (M = 1123, SE = 39), F(1,37) = 4.64, p < .05,

2 ηp = .11. Without including trait self-control as a covariate, the results were marginal in the same direction, F(1, 38) = 3.15, p = .08. The results were robust to researcher degrees of freedom in

analyzing reaction time data (analyzing RTs to both correct and incorrect trials, restricting RTs

to 2 SD above the mean, or no treatment of outliers).

There was no significant effect of condition on reaction times for congruent Stroop trials.

Controlling for participants’ trait self-control (F(1,37) = 0.66, ns), I found that participants in the intuitive thinking condition reacted nonsignificantly more quickly to congruent Stroop trials (M

= 877, SE = 39) than did participants in the controlled thinking condition (M = 960, SE = 39),

2 F(1, 37) = 2.18, p = .15, ηp = .06.

I looked to see whether condition predicted RTs to incongruent Stroop stimuli controlling

for RT to congruent Stroop trials. Including trait self-control and mean congruent Stroop RTs as

covariates, participants in the intuitive thinking condition reacted more quickly to incongruent

Stroop trials (M = 1051, SE = 19) than did participants in the controlled thinking condition (M =

2 1099, SE = 20), F(1,36) = 2.93, p < .10, ηp = .08. In other words, the results became marginal when I added congruent RTs as a covariate (and lost a degree of freedom).

Incongruent Stroop 1200

1150

1100

1050

1000

Reaction Time (ms) 950

900 Intuition Controlled Thinking Strategy used to solve problems

Figure 2. Participants randomly assigned to use intuition rather than controlled thinking to solve word problems subsequently reacted more quickly to incongruent Stroop task items.

There was no significant effect of condition on error rates for either congruent (F(1, 38) =

0.54, ns) or incongruent trials (F(1,38) = .031, ns), suggesting that participants did not make a

speed/accuracy tradeoff. In other words, participants did not react faster in the intuition condition because they sacrificed accuracy for speed and made more errors.

Discussion

Participants who were randomly assigned to solve word problems requiring cognitive

reflection using intuition rather than controlled thinking subsequently reacted more quickly to

incongruent Stroop task items. This supported the hypothesis that using heuristics and intuition

allows one to preserve the self-regulatory resource for future tasks. One limitation of Study 2

was its relatively low sample size compared to the new standards expected in the field.

CHAPTER 4

STUDY 3

Using heuristics to preserve mental energy

Study 3 tested the hypothesis that people strategically use heuristics to preserve energy for later uses. Participants solved the ten CRT problems from Study 2. All participants knew that they would be monetarily rewarded for solving each problem. Participants in the No Anticipation

Condition were truthfully informed that the 10 initial word problems were the only problems they would have to complete. However, participants in the Anticipated Effort Condition were falsely informed that after solving the initial problems, there would be a second set of problems that would require a great deal of self-regulation and effort to solve (and for which participants would be generously monetarily rewarded). The main hypothesis was that participants would use more heuristics and perform worse on the CRT because they would conserve effort for the future task.

Method

Initially, one hundred and eight participants were recruited from the psychology department’s human subjects pool, based on a power analysis reported below. After it was determined that the results approached, but did not reach significance, a much larger total sample size of 200 participants was chosen to reduce the likelihood of a type II error while also minimizing the risk of inflated type I error due to selective stopping (Simmons, Nelson, &

Simonsohn, 2011). Once the final sample size was chosen, data collection continued until the full sample size had been met.

After consenting, participants completed demographics and four scale questionnaires to measure individual differences in beliefs and personality traits thought to be possibly relevant to self-control and decision-making: Trait Self-Control (Tangney, Baumeister, & Boone, 2004),

Implicit Theories of Willpower (Job, Dweck, & Walton, 2010), Big 5 (John & Srivastava, 1999), and the Consideration of Future Consequences Scale (Strathman, Gleicher, Boninger, &

Edwards, 1994). The individual difference measures were included for exploratory purposes.

Then, participants were instructed about the logistics and rewards for the next task.

Anticipated effort condition. Participants in the Anticipated Effort Condition were told:

“In the main part of today’s study, we are testing your ability to solve various types of problems.

There will be two parts to today’s study. In the first part, you will be given 10 problems to solve.

You will receive 10 cents for each correct answer. When you are done with the first part, you can hand your sheet to me and I will compute your score while you work on the next set of problems.

The second set of problems is difficult, but with enough effort you should be able to solve them.

You will need to concentrate very hard to solve them. However, because they take so much effort to solve, we will increase the reward for solving these problems. You will receive $1 for each correct answer on the second set of problems, even though you will only receive 10 cents for each correct answer on the first problems. There are 10 problems in each set, so you can theoretically earn up to $11 in today’s study. Even if you don’t know the answer, please at least guess and put down an answer for each problem.”

Each participant was asked three questions to ensure that they understood the task:

“Before you begin to solve problems, I need to verify that you understand today’s tasks. There are two sets of problems. How many problems in each set? (10). Correct. And how much will you earn for each correct answer? (10 cents for the first set and $1 for the second set). And why

are we paying more for the second set of problems? (Take a lot of effort and concentration to

solve, but people do well with effort).” The research assistant clarified the task for the participant

as necessary, and then the participant was handed the sheet of problems. Unbeknownst to the participant, the research assistant started a stopwatch immediately after leaving the room and

closing the door.

No anticipation condition. Participants in the No Anticipation Condition were told: “In the main part of today’s study, we are testing your ability to solve word problems. You will be given 10 problems to solve. You will receive 10 cents for each correct answer, so you can earn up to a dollar in today’s study. Even if you don’t know the answer, please at least guess and put down an answer for each problem. After this task, you’ll be all done except for answering just a few questions about these problems.”

Each participant was asked two questions to ensure that they understood the task: “Before you begin to solve problems, I need to verify that you understand today’s task. How many problems are there? (10). Correct. And how much will you earn for each correct answer? (10

cents for each). The research assistant clarified the task for the participant as necessary, and then

the participant was handed the sheet of problems. Unbeknownst to the participant, the research

assistant started a stopwatch immediately after leaving the room and closing the door.

Post CRT questions. Participants knocked on the experiment room door to indicate that

they had completed the word problems. The research assistant stopped the stopwatch, recorded

the duration of the task, and entered the experiment room. Next, participants reported their perceptions of the task on eleven 7-point Likert items: How difficult were the problems? (Not at

all difficult to Very difficult), How easy were those problems? (Not at all easy to Very easy),

How much effort did you put into solving the problems? (No effort to A lot of Effort), How hard

did you work to solve the problems? (Not at all hard to Very Hard), Did you solve the problems

effortlessly (i.e., not effortfully)? (Not at all Effortlessly to Very effortlessly), Did solving the problems feel effortful? (Not at all effortful to Very effortful), How much mental energy did you

spend trying to solve the problems? (No energy to A lot of energy), How quickly did you try to

solve the problems? (Not at all quickly to Very quickly), Did you try less hard on the problems

so you could save energy for the future? (No to Yes), Did you purposefully save energy on the problems so you could have more energy later? (No to Yes), and Did you think there would be a

second set of problems to solve? (No to Yes). Participants also reported their strategy and

expected results for the set of problems. For these questions, participants were asked to circle the

number of problems (from 0 to 10), as appropriate. For each question, participants were

instructed that “If you don’t remember the exact number, give your best guess.” The questions

were: How many problems do you think you answered correctly? How many problems did you

answer using mostly gut intuition? How many problems did you answer using mostly controlled,

effortful thinking? How many answers did you double-check? The last question was an open-

ended short answer question: Briefly, please describe how you decided the amount of effort to put into the problems you just completed.

Then, participants answered the following questions about the experiment in short answer

format: “Have you taken a course in social psychology? Is there anything unusual about today

that could have affected your results? (e.g., did you not sleep last night, or are you stressed about

an upcoming exam?) Had you seen the exact word problems from the study before today’s

study? If so, where and when? Did you notice that the word problems are trick problems? (Be

honest). They provide intuitive answers, but the intuition is incorrect. What do you think today’s

study is about? Did anything about today’s study make you suspicious?”

Finally, participants were debriefed and paid. Because participants anticipated an

opportunity to make between $0 and $11 in this study, all participants were paid $5 at the end of

the experiment.

Power analysis

2 The anticipated effect size was estimated to be the same as the effect size in Study 2: ηp =

.11. G*Power software was used to compute the sample size needed to have 95% power to find a significant main effect of condition for a one-way ANCOVA with a single covariate. G*Power estimated that 108 participants would be required to have 95% power to find a significant main effect. In retrospect, the assumption that the effect size in Studies 2 and 3 would be similar was flawed. One reason is that the studies tested different hypotheses. Study 3 involved withholding of effort due to anticipated future effort, whereas Study 2 tested the effect of decision fatigue on self-regulatory outcomes. It is intuitively plausible that actual decision fatigue (as tested in Study

2) might impair decision-making more than anticipated decision-fatigue (as tested in Study 3).

The initial pattern of results was consistent with the hypothesis, but did not reach

statistical significance (for the key test of the effect of condition on use of heuristics, the results were in the expected direction, but not quite significant, F(1,106)=2.22, p=.14). A second power

analysis, based on the effect size (d=.29) in the 108-person sample, revealed that 192 participants

would be needed to yield 80% power. To increase power somewhat, we decided to collect data

from 200 participants. No further analyses were conducted until the full sample size was

achieved.

Results

Personality measures. I first tested for any failures of random assignment in the initial personality ratings, which were collected prior to the manipulation. As expected, none of the Big

5 personality measures varied by condition (Fs<.0.5, ps>.48; see Table 1). There was also no

difference by condition in consideration of future consequences, F(1,198)=.79, p=.39, see Table

1. However, participants reported higher trait self-control in the expected future task condition

(M=3.26, SE=.05, 95%CI:[3.16,3.36]) than in the no expected future task condition (M=3.12,

SE=.05, 95%CI:[3.02,3.22]), F(1,198)=4.30, p=.039, η2=.021, even though trait self-control was

measured before the manipulation and could not have been affected by it. Additionally, participants in the expected future task condition (M=3.28, SE=.053) reported marginally lower belief in limited willpower than participants in the no expected future task condition (M=3.41,

SE=.053), F(1,198)=3.17, p=.077, η2=.016. Because these variables failed random assignment, I ran key subsequent analyses both controlling and not controlling for them.

Manipulation checks. Participants who were instructed to expect a second task (M=6.14,

SE=.17, 95%CI:[5.80,6.48]) reported stronger expectations that there would be a second task than participants who were not instructed that there would be a second task (M=2.12, SE=.17,

95%CI:[1.78,2.46]), F(1,198)=275.56, p<.001, η2=.58.

Participants in the anticipation condition (M=587.65sec, SE=25.65) took fewer seconds to

complete the problems than did participants in the no anticipation condition (M=646.38sec,

SE=25.65), although the difference was not significant, F(1,198)=2.62, p=.107, η2=.013.

Problem solving results. Participants who expected a future task (M=1.32, SE=.201) answered fewer questions correctly than participants who did not expect a future task (M=2.20,

2 SE=.201), F(1,199)=9.54, p=.002, ηp =.046. Participants who expected a future task (M=5.18,

SE=.228) answered more questions using heuristics than participants who did not expect a future

2 task (M=4.24, SE=.228), F(1,199)=8.49, p=.004, ηp =.041.

Because belief in limited willpower and trait self-control were different between

conditions, I reran the above analyses using them as covariates. The pattern remained similar,

and the effects of condition on both correctness (F(1,196)=7.53, p=.007) and use of heuristics

(F(1,196)=6.54, p=.011) remained significant.

Participant thoughts about the problems. Participants were asked to estimate the

number of problems they solved correctly. Participants in the anticipation condition (M=5.77,

SE=.20) thought they had solved just as many problems correctly as did participants in the no

2 anticipation condition (M=5.58, SE=.20), F(1,198)=0.43, p=.51, ηp =.002. Overall, participants thought they had solved more problems than they actually solved, but participants in the anticipation condition (M=4.45, SE=.25) overestimated their performance more than participants

2 in the no anticipation condition (M=3.38, SE=.25), F(1,198)=8.92, p=.003, ηp =.043.

Participants in both the anticipation condition (t(99)=18.31, p<.001, 95%CI:[3.96,4.93]) and no anticipation condition (t(99)=12.94, p<.001,95%CI:[2.86,3.90]) significantly overestimated the number of problems they solved correctly.

Five questions were combined to form a composite index (α=.82) of the level of self- reported effort used to solve the first set of problems (How much effort did you put into solving the problems? How hard did you work to solve the problems? Did you solve the problems effortlessly (i.e., not effortfully)? (Reverse coded) Did solving the problems feel effortful? How much mental energy did you spend trying to solve the problems?). Participants in the anticipated effort condition (M=4.68, SE=.096, 95%CI:[4.49,4.87]) reported expending no less effort than participants in the no anticipated effort condition (M=4.75, SE=.096, 95%CI:[4.56,4.94]),

2 F(1,198)=0.28, p=.60, ηp =.001.

Participants were seemingly unaware of their own increased use of heuristics to solve the problems. Two items were combined to form an index (α=.90) of saving energy for the future

(Did you try less hard on the problems so you could save energy for the future? Did you purposefully save energy on the problems so you could have more energy later?). Participants in the anticipated effort condition (M=2.44, SE=.16, 95%CI:[2.12,2.75]) reported no more energy saving than participants in the no anticipation condition (M=2.55, SE=.16, 95%CI:[2.23,2.86]),

2 F(1,198)=0.24, p=.63, ηp =.001.

There was no evidence that participants used heuristics because they were concerned

about running out of time for the second set of problems. Most participants in the no anticipation

condition were unconcerned that they might run out of time to complete the second task

(M=3.23, SE=2.36). Excluding the few participants who were concerned about running low on time did not change the main analyses. Additionally, participants in the anticipated effort condition (M=3.90, SE=.15) were no more likely than participants in the no anticipation condition (M=3.66, SE= .15) to report trying to solve the problems quickly, F(1,98)=1.35,

2 p=.247, ηp =.007.

There was no difference in the number of answers participants reported double-checking between the anticipation condition (M=2.72, SE=.27) and the no anticipation condition (M=2.87,

2 SE=.27), F(1,198)=0.16, p=.69, ηp =.001.

Participants in the anticipation condition (M=3.92, SE=.18) reported that they answered

more questions using mostly gut intuition than participants in the no anticipation condition

2 (M=3.42, SE=.18), F(1,198)=3.72, p=.055, ηp =.018. However, there was no difference in the amount of problems that participants reported using mostly controlled thinking, F(1,198)=.073,

2 p=.79, ηp =.000.

Trait self-control. A priori, I had no clear prediction about whether people high in trait

self-control would perform better or worse on the CRT. One could predict that high self-control

would lead one to answer more problems correctly because high self-control is generally

associated with high-functioning and positive outcomes. Alternatively, one might predict that

high self-control would lead people to use more heuristics to solve the problems because

heuristics are generally accurate and are thought to save mental energy. I conducted two

exploratory regression analyses using condition, mean-centered trait self-control, and their

interaction, to predict the number of correct answers and heuristic answers to CRT problems.

3 NoAnticipation Anticipation 2

Heuristic Responses to CRT to Responses Heuristic 1

0 LowTSC HighTSC +/- 1SD Trait Self-Control

Figure 3. Participants high in trait self-control used more heuristics to solve CRT problems when they anticipated a future problem solving task.

The results suggest that people high in trait self-control are more likely to use heuristics

when anticipating the need to preserve willpower, but not when they are focused on a single,

isolated task. Trait self-control moderated the main effect of condition on the use of heuristics 24

(see Figure 3). There was a marginal interaction between condition and trait self-control (B=-

1.06, SE=0.63, t(196)=1.69, p=.093). I tested the effect of condition on participants one standard

deviation above the mean of trait self-control and one standard deviation below the mean of trait

self-control. Participants who were high in trait self-control used more heuristics when they were

in the anticipation condition (M=5.80, SE=0.30) than when they were in the no anticipation

condition (M=4.45, SE=0.34), B=1.35, SE=0.45, t(196)=2.98, p=.003. Participants who were low

in trait self-control used about the same number of heuristics, regardless of whether they were in

the anticipation condition (M=4.35, SE=0.34) or the no anticipation condition (M=4.08,

SE=0.30), B=0.27, SE=0.45, t(196)=0.59, p=.56. Thus, participants who were high in trait self- control modified their behavior so that they could perform better in the future, but only if they expected a difficult task in the future. Similarly, participants who were in the anticipation condition were more likely to use heuristics if they were high in trait self-control than if they were low in trait self-control, B=1.43, SE=0.45, t(196)=3.19, p=.002. However, participants who

were in the no-anticipation condition used about the same number of heuristics, regardless of

their level of trait self-control, B=0.37, SE=0.44, t(196)=0.83, p=.41.

This increase in heuristic responding produced a reduction in correct responses among

high trait self-control participants in the anticipation condition (see Figure 4), although the

interaction between condition and trait self-control was not significant, B=.80, SE=.56, t(196)=1.43, p=.154. Participants high in trait self-control answered fewer questions correctly

when they were in the anticipation condition (M=0.88, SE=0.26) than in the no-anticipation

condition (M=2.08, SE=.30), B=1.20, SE=.40, t(196)=2.98, p=.003. Participants who were low in trait self-control answered about the same number of problems correctly, regardless of whether they were in the anticipation condition (M=1.91, SE=0.31) or the no-anticipation condition

(M=2.29, SE=0.26), B=.38, SE=.40, t(196)=0.94, p=.35. Compared another way, participants

who were in the anticipation condition answered fewer questions correctly if they were high in

trait self-control than if they were low in trait self-control, B=-1.01, SE=.40, t(196)=2.54, p=.012. However, participants who were in the no-anticipation condition answered about the

same number of questions regardless of their level of trait self-control, B=-.21, SE=.40, t(196)=.53, p=.60.

2.5

1.5 NoAnticipation 1 Anticipation

Correct Responses to CRT to Responses Correct 0.5

0 LowTSC HighTSC +/- 1SD Trait Self-Control

Figure 4. Participants high in trait self-control answered fewer questions correctly when they anticipated a future problem solving task.

People high in trait self-control appeared to perceive the problems as less difficult when they anticipated future problems. Trait self-control moderated the main effect of condition on perceived problem difficulty, B=-.58, SE=0.34, t(196)=1.69, p=.092. I tested the effect of condition on participants one standard deviation above the mean of trait self-control and one standard deviation below the mean of trait self-control (see Figure 5). Participants high in trait

self-control perceived the problems as less difficult in the anticipation condition (M=3.59,

SE=.16) than in the no anticipation condition, M=4.13, SE=.18, B=5.45, SE=.24, t(196)=2.24,

p=.027. Participants low in trait self-control perceived the problems as equally difficult in the

anticipation condition and no anticipation conditions, B=.039, SE=.24, t(196)=.16, p=.87. In the

anticipation condition, participants high in trait self-control perceived the problems as less

difficult (M=3.59, SE=.16) than participants low in trait self-control (M=4.13, SE=.19) perceived

them to be, B=-.54, SE=.24, t(196)=2.23, p=.027. In the no anticipation condition, there was no effect of trait self-control on perceived effort, B=.037, SE=.24, t(196)=.16, p=.88. One

interpretation of these findings is that, consistent with past research (Frederick, 2005), people

who used a miserly strategy to solve these problems failed to notice that they were trick

questions, and thus thought the problems were easy. To test this interpretation, I reran each of the

above analyses controlling for heuristics use and found that people who used heuristics to solve

the problems thought the problems were easier (B=-.15, SE=.037, t(195)=3.98, p<.001, and that after controlling for this effect, the interaction (B=.42, SE=.33, t(195)=1.27, p=.21) and both the simple effect of condition for participants high in trait self-control (B=.35, SE=.24, t(195)=1.44, p=.15) and the simple effect of trait self-control for participants in the anticipation condition

(B=-.33, SE=.24, t(195)=1.37, p=.17) were reduced to nonsignificance. Thus, high trait self- control participants in the anticipation condition were more likely to use a miserly strategy, and because of this, they thought the problems were easier.

Although trait self-control moderated behavioral responses, there was little evidence that people high in trait self-control consciously used more heuristics in order to preserve willpower,

in either condition. Neither trait self-control (B=-.11, SE=.19, t(196)=.57, p=.57), condition

(B=0.013, SE=.20, t(196)=.066, p=.95), nor their interaction (B=-.074, SE=.27, t(196)=.27,

p=.79) predicted self-reported effort used to solve the problems. Similarly, neither trait self-

control (B=.19, SE=.32, t(196)=.58, p=.56), condition (B=.25, SE=.33, t(196)=.78, p=.44), nor

their interaction (B=.20, SE=.45, t(196)=.44, p=.66) predicted self-reports of strategically saving

energy on the first set of problems. There was also no effect of condition (B=-.02, SE=.41,

t(196)=.06, p=.96), trait self-control (B=-.10, SE=.40, t(196)=.25, p=.81), or their interaction

(B=.31, SE=.57, t(196)=.54, p=.59) on the number of problems participants thought they solved.

4 NoAnticipation

3 Anticipation

2 How difficult were the problems? were Howdifficult

1 Low TSC High TSC +/-1SD Trait Self-Control

Figure 5. Participants high in trait self-control thought the problems were easier when they anticipated a future problem solving task.

Consideration of future consequences. Consistent with the idea that people high in trait

self-control would use heuristics in an attempt to conserve energy for the future, people who

considered the future consequences of their actions might be expected to use more heuristics in

order to preserve willpower for the future. Support for this idea was mixed. I conducted two

regression models using condition, mean-centered scores on the Consideration of Future 28

Consequences scale, and their interaction to predict heuristics use and correct answers.

Participants in the anticipation condition used more heuristics (B=.91, SE=.32, t(196)=2.82,

p=.005). Participants high in consideration of future consequences used marginally more

heuristics (B=.46, SE=.26, t(196)=1.78, p=.077). The interaction did not predict heuristic use

(B=-.40, SE=.37, t(196)=1.07, p=.29).

There was a similar pattern in predicting correct responses to the CRT. Participants in the anticipation condition answered fewer questions correctly (B=-.85, SE=.29, t(196)=2.98, p=.003). Participants high in consideration of future consequences answered nonsignificantly fewer questions correctly (B=-.30, SE=.23, t(196)=1.33, p=.185). The interaction did not predict

correct answers (B=.06, SE=.33, t(196)=.18, p=.86). Controlling for trait self-control eliminated

the relationship between Consideration of Future Consequences and heuristic use, suggesting

that trait self-control was the main individual difference driving the results.

Belief in limited willpower. Past research indicated that people who believe that

willpower becomes depleted with effort, whereas people who believe that willpower is unlimited

do not typically show depletion effects (Job, Dweck, & Walton, 2010), unless they are extremely

depleted (Vohs, Baumeister, & Schmeichel, 2012). Would willpower beliefs also moderate the

use of heuristics in anticipation of depletion? I conducted two regression analyses using

condition, mean-centered willpower beliefs, and their interaction, to predict both the number of

correct answers and the number of heuristics used. Willpower beliefs did not moderate the effect

of condition. In predicting correct answers, condition was a significant predictor (B=-.85,

SE=.29, t(196)=2.94, p=.004), but neither willpower beliefs (B=.25, SE=.36, t(196)=.69, p=.49)

nor the interaction (B=.014, SE=.55, t(196)=.025, p=.98) had a significant effect. In predicting

heuristic answers, condition was a significant predictor (B=.92, SE=.33, t(196)=2.81, p=.005),

29 but neither willpower beliefs (B=-.02, SE=.41, t(196)=0.05, p=.96) nor the interaction (B=-.30,

SE=.63, t(196)=.48, p=.63) was significant.

Discussion

The results supported the main hypotheses: people who anticipated future expenditures of

limited mental resources used more heuristics to solve problems, apparently in order to conserve

those resources. This resulted in people solving fewer problems correctly in the anticipation

condition than in the no-anticipation condition. Somewhat surprisingly, people high in trait self-

control actually solved fewer questions correctly than people low in trait self-control. The reason

for this was that people high in trait self-control were more likely to adopt a miserly strategy for problem solving when they anticipated future expenditures of their mental resources in a second problem-solving task.

People high in trait self-control, but not people low in trait self-control, used heuristics in

an apparently strategic way—using effort-saving heuristics more when they knew they would

have to think effortfully in the near future. This strategy could help one to avoid deleterious

consequences of becoming depleted in an inopportune moment (such as those shown in Study 2).

This strategy is consistent with recent research showing that having high self-control generally

means planning your life so that your willpower does not lapse, more so than facing and

conquering difficult situations through sheer strength of willpower (Ent, Baumeister, & Tice,

2015). Although this finding is consistent with the literature on trait self-control, I did not predict

this effect, so the reader should interpret it with some caution. As with any unpredicted finding,

experimental replication of this effect would provide greater confidence in its robustness and

reliability.

Although people used heuristics in an apparently strategic pattern, there was little

evidence that people were consciously aware that they were following this strategy. People in the

anticipation condition were aware that they had solved more problems using their gut intuition.

However, they did not think that this meant that they would have solved fewer problems

correctly. If anything, they thought they had solved more of them correctly. Additionally, even people who preferentially used heuristics to solve problems in the anticipation condition perceived that they had exerted no less effort than people who did not use more heuristics. If

anything, they thought they had exerted more. People in the anticipation condition were no more

likely to say they had intentionally saved energy than people who thought through the problems

more carefully.

CHAPTER 5

GENERAL DISCUSSION

Cognitive miserliness and ego depletion

The results of three studies support a link between cognitive miserliness and ego

depletion, in which miserliness serves to avoid the deleterious effects of ego depletion. Study 1

found that people who were more depleted acted more miserly by using heuristics to solve problems. This could mean one of two things. People who were depleted might have run low on

mental energy and therefore relied on less effortful, more heuristic strategies to solve problems.

Another explanation is that people who had partially depleted their energy were motivated to preserve the limited energy they had left by using heuristics to solve problems. This second

explanation is more consistent with motivational theories of ego depletion (see Inlicht &

Schmeichel, 2012; Baumeister & Vohs, 2015), and also comports with the other present findings.

If depleted people become motivated to use miserly strategies to solve problems, there is presumably a benefit to using the miserly strategy that would counterbalance the increased

likelihood of solving problems incorrectly. One benefit would be that heuristics enable one to

solve problems more quickly, but people were at least not consciously concerned about the

amount of time the problems took to solve. Study 2 found that the major benefit of using miserly

heuristics seems to be that they save energy, which improves performance later on. People who

used heuristics avoided becoming depleted, while still solving the same problems (albeit

incorrectly because of the particularly tricky problems in the present research). This is the first

experimental evidence I know of showing that heuristics save energy.

Because heuristics save energy for the future, people can use them strategically when

they know they will need their peak mental faculties next. In Study 3, people who knew they

would need to solve valuable problems next used heuristics to save energy when solving problems in the present. Only some people adopted this strategy, however. As is typical of people high in trait self-control, they organized their life so that they could maximize their wellbeing in the future (Ent, Baumeister, & Tice, 2015). They strategically used heuristics when they knew it was important to save for the next task, but not if there was no future task to save for.

Curiously, although they acted strategically, they did not appear to be consciously aware that they were engaged in this strategy.

Implications for decision-making

Since Kahneman and Tversky began conducting experiments on heuristics and other sources of irrational decision-making in the 1970s, researchers have debated the extent to which people’s decision-making is rational vs. irrational. The debate was initiated because of the widespread assumption in neoclassical economics that people use all of the available information in each situation to make a logical, well-informed decision (e.g., Binmore, 2015). Even before

Kahneman and Tversky, economists realized that this assumption was psychologically unrealistic (for example, see Simon, 1955), but the two psychologists provided experimental evidence to support the claim that people often ignore available information and instead rely on simple decision rules (i.e., heuristics; Tversky & Kahneman, 1974). Because the experiments on heuristics involved showing departures from the fully informed, rational outcomes predicted by neoclassical economics, it was widely assumed that heuristics generally produce irrational, biased, and bad outcomes.

The present research contributes to a growing literature showing that sometimes an

answer that appears irrational by economic standards is practically rational for an individual who

is constrained by limited time, information, ability to do computation, and energy, as is anyone

in the real world (Goldstein & Gigerenzer, 2002). For example, time pressure can make it

rational for one to use heuristics instead of taking the time to calculate the best possible solution

to a problem (Gigerenzer & Goldstein, 1996). For another example, heuristics can outperform

complex reasoning and sophisticated modeling when there is a great deal of uncertainty about the

details of a problem, as when predicting the optimal diversity of financial investments

(DeMiguel, Garlappi, & Uppal, 2009); Gigerenzer & Brighton, 2007). Furthermore, using

controlled reasoning does not necessarily guarantee that one’s reasoning will be sound or that

one will correctly solve a problem, so heuristics may be useful when one’s capacity to reason

about a problem is limited (Kruglanski & Gigerenzer, 2011).

The present studies show another major reason how using heuristics can be rational.

Heuristics help one avoid decision fatigue and ego depletion. Some theorists have suggested this

as a possibility (Kahneman, 2011), but to my knowledge this is the first set of studies to

empirically test this hypothesis. The present research suggests that people are more likely to use

heuristics when their resources are depleted, and even when they merely expect to deplete them

in the near future. Furthermore, this strategy is apparently effective, because using intuition to

solve problems actually does reduce the depletion one experiences compared to solving the same problems using controlled thinking. To put it in plain language, people are lazy thinkers in part because thinking harder takes more effort.

The finding that heuristics save energy has potentially broad implications for the

literature on judgment and decision making. There are many different types of heuristics (see

Kahneman, 2011), many or all of which may save energy. Future research should investigate the effectiveness of a variety of heuristics for preserving mental resources and attenuating depletion.

One particularly interesting implication could be that people may use some forms of moral reasoning (i.e., moral heuristics; Sunstein, 2005) in order to save energy. Some people may face unwarranted moral and legal condemnation from a judge who used a moral heuristic because he was depleted (Danziger, Levav, & Avnaim-Pesso, 2011).

Implications for ego depletion

The limited resource model of self-control has been the target of several critical attacks, on two grounds. One critique is that the behavioral effects of ego depletion occur because of a lack of motivation, rather than depletion of a limited resource (Inzlicht & Schmeichel, 2012; Job,

Dweck, & Walton, 2010; Kurzban, Duckworth, Kable, & Myers, 2013). The other critique is that the behavioral effects of ego depletion have been exaggerated and that due to publication bias there may actually be no behavioral consequences of ego depletion at all (Carter & McCollough,

2014; Hagger, et al., in press; but see Baumeister & Vohs, in press). Obviously, the critiques cannot both be true. If there is no behavioral effect, then the alternative explanations cannot be true; likewise, if any explanation of the effect is true, then the effect must exist.

The present research (Study 1) provides evidence in support of the effects of ego depletion. People used more heuristics when they were depleted—a finding consistent with past literature showing that depletion produces miserly decision-making (Masicampo & Baumeister,

2008; Pocheptsova, Amir, Dhar, & Baumeister, 2009; Pohl, Erdfelder, Hilbig, Liebke, &

Stahlberg, 2013; Vohs, et al., 2014). It is also consistent with a meta-analysis showing effects of ego depletion (Hagger, Wood, Stiff, & Chatzisarantis, 2010; but a different meta-analysis found no effect, Carter & McCollough, 2014). Additionally, Study 2 suggests a reason why depletion

would increase reliance on heuristics: using heuristics improved future task performance, presumably because using heuristics prevents one from becoming depleted.

Study 3 is relevant to the debate about the mechanism behind ego depletion. People used more heuristics in anticipation of future self-regulatory expenditures needed for solving problems. If the limited resource model is correct, then people should have mental mechanisms to prevent exhausting this limited resource. One mechanism would be to use self-control strategically, such that when one expects to need to use controlled thinking soon, one should minimize use of controlled thinking now. An analogy is that using heuristics to save energy is like an army commander deciding to rest the soldiers before they head into battle. Anticipation of future effort apparently changes present behavior, which implies that the future effort changes the reasons for behavior in the present. The most parsimonious reason why future effort would reduce present effort is that there is a limited energy resource that would be depleted in the future if one expended a lot of energy in the present.

People may use more heuristics because depletion reduces motivation for the present task

(Inzlicht & Schmeichel, 2012; Kurzban, Duckworth, Kable, & Myers, 2013). Unlike most ego depletion findings, however, the reduction in motivation for the present task cannot be readily explained by opportunity cost. One reason that has been proposed for why people might become less motivated when they are depleted is that continued effort toward a (perhaps futile) present task means that one cannot do other concurrent things. For example, eating radishes rather than cookies means that one misses out on the opportunity to eat the cookies, complete one’s homework, go on a date, or do anything else. According to the opportunity cost model, therefore, one might become demotivated to persist on tasks over time, thereby causing the appearance of ego depletion. The current results show, however, that people avoid effortful thinking in

36 anticipation of future energy expenditures. Engaging in effort on the present task has little if any impact on the opportunities one might have in the future (after the present task is over), so the opportunity cost model may not be able to explain this finding.

Another alternative model of ego depletion is the idea that people act as though willpower is limited when they believe it to be so (Job, Dweck, & Walton, 2010). I found little support for the idea that beliefs about willpower changed behavior in Study 3 (and did not measure beliefs about willpower in the other studies). There were no effects of beliefs about willpower. This is not necessarily a failure to replicate Job and colleagues’ findings, as Study 3 measured the effects of anticipated self-control effort, rather than immediate self-control effort.

Still, it would have been logical for people who believe that willpower is limited to show the found effect more than people who do not believe in limited willpower. Rather than belief in limited willpower, it was trait self-control that moderated the effect.

There are numerous possible future directions that are relevant to ego depletion. One is to investigate how anticipation affects self-regulation more generally. Based on the limited resource model, I would predict that anticipating future effortful activities, but not easy activities requiring no self-control, should increase the use of heuristics in the present. Furthermore, anticipating future effortful tasks should affect no only the use of heuristics, but other activities involving self-control, too.

Implications for trait self-control

The results showed that people high in trait self-control used more heuristics and therefore made more errors in solving the problems than did people low in trait self-control.

Superficially, this finding would seem to demonstrate a downside of high self-control, which would be rare (Baumeister & Alquist, 2009). Trait self-control is positively associated with

essentially every desirable behavioral outcome, from education attainment and work success, to

low crime and addictive behaviors (de Ridder, Lensvelt-Mulders, Finkenauer, Stok, &

Baumeister, 2012). However, this view of self-control leading to more errors ignores the bigger

ecological picture.

The increased number of errors for people high in trait self-control was consistent with a

reasonable strategy to match effort to potential payout. High trait self-control did not entail

making more errors across the board—people high in trait self-control made more errors when

using heuristics helped them prepare to self-regulate on future tasks. Although people high in

trait self-control did make more errors, they only did so because they were using heuristics to preserve energy for a more highly rewarded task later. In the present studies, using heuristics

almost perfectly corresponded to making more errors because the studies were designed that

way. However, in the real world using heuristics would both preserve energy for the future and

usually produce the correct answer anyway. People who could strategically allocate their energy by using heuristics on relatively unimportant tasks would be able to use that energy on tasks in which being sure of the correct answer would be more important.

The finding that people high in trait self-control do not necessarily maximize willpower usage in the present is consistent with a growing literature on trait self-control. For example, people high in trait self-control attempt to avoid distraction during studying, rather than facing temptation and steadfastly withstanding the pressure to succumb to it (Ent, Baumeister, & Tice,

2015). Overall, high trait self-control appears to involve regulating one’s environment and establishing habits so that one does not face temptation, rather than strengthening one’s will (de

Ridder, Lensvelt-Mulders, Finkenauer, Stok, & Baumeister, 2012; Hofmann, Baumeister,

Förster, & Vohs, 2012; Imhoff, Schmidt, & Gerstenberg, 2014). In addition to avoiding

temptation, people high in trait self-control apparently also avoid ego depletion by using

heuristics to solve relatively unimportant problems.

One major future direction to guide further research is to test the moderating effects of

trait self-control on ego depletion. Paradoxically, it seems to be people high in trait self-control

who often show the effects of ego depletion (Imhoff, Schmidt, & Gerstenberg, 2014).

Understanding why this occurs is an important direction for future research.

Limitations

One limitation of the present research was the focus on a single measure of heuristic problem-solving. The Cognitive Reflection Test was chosen because it enables researchers to

distinguish when people use heuristics and controlled thinking. As a byproduct, however, this

entails that heuristic responding will be conflated with incorrect responding. It is worth repeating

that in the real world, heuristic responding would not only preserve energy and avoid ego

depletion, but heuristics generally also provide correct answers in the majority of cases

(Kahneman, 2011), and sometimes even outperform careful calculation (Gigerenzer & Brighton,

2010). Had I used a different measure of heuristics, people high in trait self-control may have

appeared less foolish in using heuristics strategically.

Another limitation is the small sample size of the studies, especially the first two studies.

These studies were conducted before the field (and I) began to recognize the importance of

running high-powered studies, which generally means large samples. Small samples are

associated with low power, which by definition inflates Type II error (falsely finding no

evidence of a true effect). Paradoxically, small samples can also inflate Type I error (falsely

finding support for an effect that is actually false). Although you are less likely to find a

significant finding with a small sample, the significant findings that you do find are more likely

39 to be Type I error than in a high-powered study because the found effect size is likely to be larger than the true effect size (Button, et al., 2013). One result of the field’s prevalent reliance on small experimental samples is that many studies across psychology and other fields are underpowered and therefore unreliable. A relatively small proportion of studies published in the top journals were successfully replicated by independent experimenters (Open Science

Collaboration, 2015). Of the present research, Study 3 was adequately powered (post-hoc power for key analyses was greater than .80). Studies 1 (post-hoc power = .54) and 2 (post-hoc power =

.56) both suffer from low power, and therefore their results should be considered preliminary until replicated. My collaborators and I are currently replicating both studies. Study 1’s replication is ongoing. My collaborator, Hallgeir Sjåstad, and I recently finished a preregistered, high powered version of Study 2, with results consistent with those of Study 2.

Conclusion

The name “cognitive miser” implies that people are stingy with a mental resource. These studies show that the resource people are stingy with is the limited resource used for self- regulation. Cognitive miserliness saves the resource for the future, effectively trading irrationality now for rationality and self-control later.

APPENDIX A

STUDY 1 HUMAN SUBJECTS APPROVAL MEMO

Office of the Vice President For Research Human Subjects Committee Tallahassee, Florida 32306-2742 (850) 644-8673, FAX (850) 644-4392

APPROVAL MEMORANDUM

Date: 4/27/2011

To: Andrew Vonasch [********@psy.fsu.edu]

Address: 4301 Dept.: PSYCHOLOGY DEPARTMENT

From: Thomas L. Jacobson, Chair

Re: Use of Human Subjects in Research Heuristics and the Self-Control Resource

The application that you submitted to this office in regard to the use of human subjects in the research proposal referenced above has been reviewed by the Human Subjects Committee at its meeting on 03/02/2011. Your project was approved by the Committee.

The Human Subjects Committee has not evaluated your proposal for scientific merit, except to weigh the risk to the human participants and the aspects of the proposal related to potential risk and benefit. This approval does not replace any departmental or other approvals, which may be required.

If you submitted a proposed consent form with your application, the approved stamped consent form is attached to this approval notice. Only the stamped version of the consent form may be used in recruiting research subjects.

If the project has not been completed by 2/29/2012 you must request a renewal of approval for continuation of the project. As a courtesy, a renewal notice will be sent to you prior to your expiration date; however, it is your responsibility as the Principal Investigator to timely request renewal of your approval from the Committee.

You are advised that any change in protocol for this project must be reviewed and approved by the Committee prior to implementation of the proposed change in the protocol. A protocol change/amendment form is required to be submitted for approval by the Committee. In addition, federal regulations require that the Principal Investigator promptly report, in writing any 41

unanticipated problems or adverse events involving risks to research subjects or others.

By copy of this memorandum, the Chair of your department and/or your major professor is reminded that he/she is responsible for being informed concerning research projects involving human subjects in the department, and should review protocols as often as needed to insure that the project is being conducted in compliance with our institution and with DHHS regulations.

This institution has an Assurance on file with the Office for Human Research Protection. The Assurance Number is FWA00000168/IRB number IRB00000446.

Cc: Roy Baumeister, Advisor HSC No. 2011.5896

APPENDIX B

STUDY 1 MATERIALS Consent Form

Purpose: In this research study, we are studying cognitive processes, physiology and decision- making.

Procedures: We will ask you to fill out a broad personality questionnaire that will take no more than one hour. We will take a blood glucose measurement using a finger-prick. We will ask you to solve problems and make choices. We may evaluate your pain tolerance by immersing your hand in cold water for a period of no more than 2 minutes. We will ask you to describe yourself. We will ask you about this study. You will receive 1 credit for participation in today’s study.

Risks and Benefits: Although this research will not benefit you personally, it will add to our knowledge of people’s decision-making processes. We judge risks to be minimal. You may experience some discomfort due to finger pricking and/or placing your hand in cold water. You may experience some frustration, fatigue, and/or boredom. The entire research session will take no more than one hour.

Confidentiality: Your information will be confidential to the extent allowed by law. There is no need to collect any identifying information. All responses will be identified only by number, gender and age. All data will be kept on password-protected computers to which only researchers directly associated with the research will have access. There will be no way in which the resultant data can be traced back to an individual participant.

Voluntary participation: Your participation in this study is completely voluntary. You are free to decline to participate, or to end participation at any time for any reason. If you begin the study and decide to withdraw at any point or not to answer any particular question or questions you will still receive your class credit (1/2 credit for participation). There is no penalty for withdrawal.

Questions: I understand that I may contact Andy Vonasch, Florida State University, Department of Psychology, Psychology building room ****, (***) ***-****, or Dr. Roy Baumeister, Florida State University, Department of Psychology, Psychology building room ****, (***) *** – ****, for answers to questions about this research or my rights. Group results will be sent to me upon my request. If I have questions about my rights as a subject/participant in this research, or if I feel I have been placed at risk, I can contact the Chair of the Human Subjects Committee, Institutional Review Board, through the Office of the Vice President for Research, at (850) 644-8633.

Agreement to Participate: I have read and understand the above information and have agreed to participate in this study.

Signature______Date______

Please read each of the following statements carefully and indicating how much like you the statement is by circling the appropriate response using the scale provided. 1. I am able to work effectively toward long-term goals.

1 2 3 4 5 Not at all Somewhat Very much

2. People would say that I have iron self-discipline. 1 2 3 4 5 Not at all Somewhat Very much

3. I often act without thinking through all the alternatives. 1 2 3 4 5 Not at all Somewhat Very much

4. I refuse things that are bad for me. 1 2 3 4 5 Not at all Somewhat Very much

5. I am lazy. 1 2 3 4 5 Not at all Somewhat Very much

6. Pleasure and fun sometimes keep me from getting work done. 1 2 3 4 5 Not at all Somewhat Very much

7. I wish I had more self-discipline. 1 2 3 4 5 Not at all Somewhat Very much

8. I have a hard time breaking bad habits. 1 2 3 4 5 Not at all Somewhat Very much

9. I do certain things that are bad for me, if they are fun. 1 2 3 4 5 Not at all Somewhat Very much

10. I am good at resisting temptation. 1 2 3 4 5 Not at all Somewhat Very much

11. Sometimes I can't stop myself from doing something, even if I know it is wrong. 1 2 3 4 5 Not at all Somewhat Very much

12. I say inappropriate things. 1 2 3 4 5 Not at all Somewhat Very much

13. I have trouble concentrating. 1 2 3 4 5 Not at all Somewhat Very much

Here are a number of personality traits that may or may not apply to you. Please write a number next to each statement to indicate the extent to which you agree or disagree with that statement. You should rate the extent to which the pair of traits applies to you, even if one characteristic applies more strongly than the other.

1 = Disagree strongly 2 = Disagree moderately 3 = Disagree a little 4 = Neither agree nor disagree 5 = Agree a little 6 = Agree moderately 7 = Agree strongly

I see myself as:

1. _____ Extraverted, enthusiastic.

2. _____ Critical, quarrelsome.

3. _____ Dependable, self-disciplined.

4. _____ Anxious, easily upset.

5. _____ Open to new experiences, complex.

6. _____ Reserved, quiet.

7. _____ Sympathetic, warm.

8. _____ Disorganized, careless.

9. _____ Calm, emotionally stable.

10. _____ Conventional, uncreative.

For this task, please cross out all instances of the letter “e” in the text below. Please continue on to the next page when you are done.

Neurocognitive studies using the Wisconsin Card Sorting Test (WCST; Loong, 1990) and other executive tasks have yielded mixed results regarding patients with obsessive-compulsive disorder (OCD; Moritz, Kloss, Katenkamp, Birkner, & Hand, 1999; Schmidtke, Schorb, Winkelmann, & Hohagen, 1998). Several researchers have speculated that WCST deficits (i.e., dysfunctions in set-shifting), which are inferred to be mediated by dysfunctions of the dorsolateral prefrontal cortex, may be confined to OCD patients exhibiting comorbid depressive or psychotic symptoms (e.g., Cox, 1997; Malloy, 1987). However, this hypothesis has not been directly tested but inferred post hoc: Whereas studies that excluded patients with high depression severity scores have mostly shown that set-shifting performance is unimpaired in OCD (e.g., Boone, Ananth, Philpott, Kaur, & Djenderedjian, 1991; Purcell, Maruff, Kyrios, & Pantelis, 1998a), investigations that did not control for depressive symptoms have revealed dysfunctions (e.g., Cox, Fedio, & Rapoport, 1989; Moritz et al., 1999). Moreover, dorsolateral prefrontal impairment, which is considered to be a major contributor to set-shifting deficits (e.g., Lombardi et al., 1999), has been implicated in the pathogenesis of depression (for reviews, see Rogers, Bradshaw, Pantelis, & Phillips, 1998) but not OCD. For OCD, on the other hand, there is increasing evidence for orbito-frontal impairment (for a review, see Saxena, Brody, Schwartz, & Baxter, 1998).

Following the suggestion of Purcell et al. (1998a) that “future research should explicitly measure comorbid depressive symptoms in patients with OCD to examine any relationship between depressive symptoms and set-shifting deficits” (p. 422), for the present study an OCD sample was split according to the severity of depressive symptoms and compared with matched healthy control subjects with regard to WCST performance. In addition, researchers investigated whether comorbid depressive symptoms can also account for divergent finding regarding other executive tasks—most important being fluency tests, which are considered correlates of the medial-frontal cortex (Crosson et al., 1999; Hugdahl et al., 1999).

Next are several problems that vary in difficulty. Try to answer as many as you can.

A bat and a ball cost $1.10 in total. The bat costs a dollar more than the ball. How much does the ball cost? ______cents

If it takes 5 machines 5 minutes to make 5 widgets, how long would it take for 100 machines to make 100 widgets? ____ minutes

In a lake, there is a patch of lily pads. Every day, the patch doubles in size. If it takes 48 days for the lily pads to cover the entire lake, how long would it take for the lily pads to cover half of the lake? _____ days

Which would you rather win? $3400 this month or $3800 next month Which would you rather win? $100 now or $140 next year Which would you rather win? $100 now or $1100 in ten years Which would you rather win? $40 immediately or $1000 in ten years Which would you rather win? $100 now or $20 every year for 7 years Which would you rather win? $400 now or $100 every year for 10 years Which would you rather win? $1000 now or $100 every year for 25 years Which would you rather win? 30 min. massage in 2 weeks or 45 min. massage in November Which would you prefer? Lose $1000 this year or lose $2000 next year Which would you prefer? To get your tooth pulled now or your tooth pulled in two weeks What is the smallest amount of money you would take right now in place of winning $170 in two months? How impulsive are you? How much do you tend to procrastinate? How much do you think about your future? How much do you worry about inflation?

Have you ever completed any of these tasks or answered these questions before? Explain. What do you think today’s study was about? You will not be penalized based on your answer to this question: did you pay attention and try your best to complete the tasks in today’s experiment? Were you distracted by anything? Explain. What is your gender? What is your race? Are you Latino or Hispanic? How old are you?

Debriefing Form

Thank you for completing our study. At this point, we would like to explain what our study was about. Prior research by Roy Baumeister has shown that self-control is a limited resource. If you use self-control in one task (for example, by naming the color of a word rather than reading the word) you will be less likely to use self-control on a subsequent task. This resource has been linked to levels of glucose available to the brain. When blood glucose is low, people are less able, or less willing to use self-control.

Other research by Daniel Kahneman has shown that we make decisions in a two-step process. When we first look at a problem, we have a quick, intuitive response. These responses are based on rules of thumb called heuristics. Our brains have evolved to use these shortcuts because it’s quicker and easier than consciously deliberating over a problem. However, for complex problems we sometimes get answers wrong if we don’t take the time to rationally evaluate our intuition. An example follows: A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost? The natural division of costs in the bat and ball problem is $1.00 and 10 cents, but this intuition is wrong. The ball costs 5 cents.

So far, scientists have shown that making decisions in general uses up glucose and self-control in the brain, but no one has looked at the different types of decision to see if we need self-control only for using the rational system, or if intuitive answers use up self-control, too. The scientist who designed this study hypothesizes that only rationally second-guessing your answers will fatigue the “self-control muscle.”

Since we needed to measure self-control, we had to keep you in the dark as to why you were doing all of the tasks you did today. If we had told you ahead of time what our hypothesis was, it would have ruined the experiment. We are sorry for doing this to you today. We believe this scientific question is important, and we thank you for your participation. We also thank you for allowing a small finger prick to test your blood’s glucose levels. We understand this may not be a comfortable procedure, but we hope your participation today will improve scientific understanding of self-control and decision-making. If you are upset by not knowing all of the details about the experiment ahead of time today, you have the right to withhold your data from analysis. To do so, you would just tell the experimenter now, or contact the primary investigator via email.

Thank you for participating in this study. If you have any questions or comments about the study, please contact the primary investigator via email: ********@psy.fsu.edu.

APPENDIX C

STUDY 2 HUMAN SUBJECTS APPROVAL MEMO

The Florida State University Office of the Vice President For Research Human Subjects Committee Tallahassee, Florida 32306-2742 (850) 644-8673, FAX (850) 644-4392 RE-APPROVAL MEMORANDUM

Date: 4/18/2013

To: Andrew Vonasch [*******@psy.fsu.edu]

Address: 4301 Dept.: PSYCHOLOGY DEPARTMENT

From: Thomas L. Jacobson, Chair

Re: Re-approval of Use of Human subjects in Research Heuristics and the Self-Control Resource

Your request to continue the research project listed above involving human subjects has been approved by the Human Subjects Committee. If your project has not been completed by 4/9/2014, you are must request renewed approval by the Committee.

If you submitted a proposed consent form with your renewal request, the approved stamped consent form is attached to this re-approval notice. Only the stamped version of the consent form may be used in recruiting of research subjects. You are reminded that any change in protocol for this project must be reviewed and approved by the Committee prior to implementation of the proposed change in the protocol. A protocol change/amendment form is required to be submitted for approval by the Committee. In addition, federal regulations require that the Principal Investigator promptly report in writing, any unanticipated problems or adverse events involving risks to research subjects or others.

By copy of this memorandum, the Chair of your department and/or your major professor are reminded of their responsibility for being informed concerning research projects involving human subjects in their department. They are advised to review the protocols as often as necessary to insure that the project is being conducted in compliance with our institution and with DHHS regulations.

Cc: [] HSC No. 2012.9704

APPENDIX D

STUDY 2 MATERIALS

Consent Form

Purpose: In this research study, we are studying cognitive processes and decision-making.

Procedures: We will ask you to fill out a broad personality questionnaire that will take no more than one hour. We will ask you to solve problems and make choices. We will ask you to describe yourself. We will ask you about this study. You will receive 1 credit for participation in today’s study.

Risks and Benefits: Although this research will not benefit you personally, it will add to our knowledge of people’s decision-making processes. We judge risks to be minimal. You may experience some frustration, fatigue, and/or boredom. The entire research session will take no more than one hour.

Voluntary participation: Your participation in this study is completely voluntary. You are free to decline to participate, or to end participation at any time for any reason. If you begin the study and decide to withdraw at any point or not to answer any particular question or questions you will still receive your class credit (1 credit for participation). There is no penalty for withdrawal.

Agreement to Participate: I have read and understand the above information and have agreed to participate in this study.

Signature______Date______

Below are 10 problems that vary in difficulty. Studies have shown that using your gut intuition usually gives you the wrong answer to these types of problem. Please try to answer the following questions as best you can, without just relying on your first guess. You will have to explain your reasoning and answers at the end of the study.

1) A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost? ______cents

2) If you flipped a fair coin 3 times, what is the probability that it would land “Heads” at least once? ______

3) If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets? ______minutes

4) Two cars are on a collision course, travelling towards each other in the same lane. Car A is traveling 70 miles an hour. Car B is traveling 80 miles an hour. How far apart are the cars one minute before they collide? ______miles

5) In a lake, there is a patch of lilypads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake? ______days

6) If John can drink one barrel of water in 6 days, and Mary can drink one barrel of water in 12 days, how long would it take them to drink one barrel of water together? ______days

7) If three elves can wrap six toys in half an hour, how many elves are needed to wrap twenty toys in one hour? ______elves

8) Jerry received both the 15th highest and the 15th lowest mark in the class. How many students are in the class? ______students

9) Just after being picked, a 90 pound watermelon was 90% water. But after being left in the sun for a week, only 80% of its weight is water. How much does it weigh then?

______pounds 10) Suppose you fold a 2mm thick piece of paper in half, so that it’s twice as thick as before, i.e. 4mm. How thick would the paper be if you folded it 7 times?

______mm 55

Below are 10 problems that vary in difficulty. Studies have shown that using your gut intuition usually gives you the correct answer to these types of problem. Please try to answer the following questions using your first gut intuition in the first few seconds and then move on to the next question. Do not go back to previous problems.