Ten Bad Habits of Personal Finance

The following list is in no particular order! It was written by me during three sessions on 2016-01-03, 2016-01-14, and 2016-01-16. These are issues salient to me. There are certainly other and perhaps more important issues such as salary negotiation, failing to itemize deductions, and poor estate planning. However, such issues are not my areas of expertise, nor are they current areas of interest for me.

Not getting what you deserve

I have met community-college students who literally did not know about the FAFSA. Their parents were low-income and they could have been getting over $2500 in federal Pell grant money per semester, but were instead getting nothing because they didn’t even apply.

This habit can be related to not researching or trying hard enough. For example, many consumers think they have no recourse when a price goes down after they purchase an item, while in fact, even if the lower price is being offered at another retailer, their credit card probably offers price protection if they would just take the time and effort to file a claim. Unfortunately, such individuals probably didn’t even read about their card benefits or think of this possibility.

This habit can also be related to being a push-over. I always choose the performance goal-orientation when it comes to matters of customer service or contract breakage: what are OTHER customers getting that I’m not, because they are standing up for themselves and demanding results? A VERY common example of this is bank fees. The typical consumer incurs bank fees without a whimper, yet these fees may not even be legitimate—or if they are, will probably be waived as a one-time courtesy if you ask nicely.

Not getting what you deserve is a HUGE problem. It relates to education, mindset, self-esteem, and many other issues. Most of us do not have an advocate when it comes to personal finance; we must do our own Google searches and take action to save ourselves money. Unfortunately, too many Americans would choose to put in extra hours at a low-paying job over using this time to become financially literate and earn or save many more dollars per hour.

Finally, consider that money saved is typically NOT taxable income. Pell grants, price-protection refunds, and courtesy waiver of bank fees are not subjected to payroll deductions or income taxes, yet if you DON’T pursue them, you have to earn anywhere from 15 to 50% more income to compensate for the opportunities you missed.

Paying for poison

When you buy alcoholic drinks, tobacco products, candy, soft drinks, or energy drinks you are literally PAYING to poison yourself. Not only do these products have no nutritional value; they actively damage your liver, lungs, and other organs, reduce your quality of life, and if chronically consumed, make you feel powerless and unhappy.

While soft drinks are expensive in 20-oz. bottles from the retail cooler, often running upward of $1.50, they are even more expensive at sit-down restaurants, often costing over $3.00 with tax and 20% tip. Just say no. If anyone judges you negatively for ordering water, you should probably find better dates or friends.

Financial needs expanding to match or exceed the amount of money available to you

Like many bad financial habits, this is more common with people who have achieved less formal education, e.g., high-school dropouts. If you have $10.00 in your pocket, this does NOT mean you need to spend $9.92 at the gas station on a 20-oz. bottle of Sprite, Monster energy drink, candy bar, and pack of cigarettes. YES, spending the $10.00 does prevent it from being stolen, and relieves you of the threat of it being “borrowed” (through peer pressure or coercion) by family or friends. However, it cuts off all future opportunities for the money and leaves you with no degrees of freedom to adapt to circumstances or opportunities.

Earning more money does not mean your lifestyle should immediately become more costly. In the Millionaire Next Door, people who invest wisely and increase their income, while continuing to drive an older car and live in a modest home, are called “prodigious wealth accumulators.” While this predilection for accumulation may seem empty if the wealth is never “enjoyed,” consider that these millionaires often enjoy the process of wealth accumulation itself, and the freedom it affords them. They typically are not preoccupied with spending. While “you only live once” is a comforting saying for the financially obtuse, heavy saving rather than heavy spending may lead to greater satisfaction and happiness, particularly when you have dependents to care for.

Obviously, this habit gets much worse when debt is involved. It is most certainly NOT in your best interests to pay 25.24% annual interest on these frivolous purchases.

Picking the wrong partners and friends

If you are dating or become married to someone who spends frivolously, it is very possible that they will not change. In fact, nagging and complaining may push them to become even more decadent and foolish in their financial habits. An analogous example is the devoutly religious family who raises a child who immediately announces his or her atheism at 18. Instead of seeing your partner as who you wish they would become in the future, a more realistic outlook may involve projecting their past behavior into the future; that is, assuming their financially unsound habits will only continue or become proportionally worse as they have access to increased income and lines of credit. If you accept these low expectations, you will probably have a truer understanding of the financial handicap (or even financial ruination) that being committed to this person will entail. In many cases this can be a deal-breaking issue.

Similarly, your choice of friends can hurt your finances quite a bit. Friends may use peer pressure to get you to buy things or go to events that are costly and not among your desires or in your best interests. Also, their bad financial habits can influence you, and they may become dismissive or jealous when you start working to improve your financial situation. Albeit, choosing good friends is a general issue that impacts many other areas of life. It may not seem that you have many choices in friends, but assuming you are an intro- or “ambi”-vert, consider that jettisoning toxic friends from your life may be a good choice, if they have proved unwilling to change.

Having or raising children

We often see the figure of $250,000 being bandied about as the cost of raising a child from birth to 18 years of age. While this may seem astronomical to some, to any middle-class American, the idea of a child costing $14,000 a year should seem quite modest. Of course, there are economies of scale to be considered when having multiple children, as well as many incentives and subsidies from the State. However, when considering how child-rearing transforms your life, it clearly costs far more than $250,000 per child in opportunity cost (particularly for mothers), and more importantly, time. Having a bigger house with additional bedrooms and bathrooms is very expensive. There is also so much time and energy to be sacrificed, and American children are prone to rebellion against even the best of parents. For example, at a young age, your child could take up drinking or some other dangerous pastime and wind up dead, completely destroying your investment.

One of the prime reasons people have children is to pass their genes on. When you die without having children, particularly if you are an only child, your lineage terminates. While raising the children of others (whether through adoption or committing to a single parent) is better for limiting the rate of increase of the human population, it does nothing for continuing your bloodline. When considering the astronomical toll that having or raising children imposes on your life, both financially and temporally, you should consciously consider how valuable continuing your bloodline is to you, particularly if you believe you are special and that your specialness is heritable.

Of course, it is well known that having children at an early age is predictive of poverty, and less formal education is predictive of, or at least correlated with, both. This cycle is perpetuated among children who grow up with low socioeconomic status (SES). Given that picking a financially reckless partner can have profound negative impacts on your SES, such a choice may function as a generational curse against your bloodline, especially if such recklessness is inherited, whether genetically or environmentally.

Obliviousness to basic arithmetic

With the recent Powerball lottery drawing on 2016-01-13, we saw that Americans are incapable of understanding odds. See, even with a $1.5 billion jackpot, your odds of winning still require a $584 million net payoff to be in your favor. The $2.00 you spend to buy the ticket are certainly net funds, since you have already paid FICA taxes, income taxes, etc. on them. Therefore, it is completely incorrect to focus on the gross amount of the jackpot. Further, the $2.00 spent on each ticket are funds spent now. Money is always more valuable in the present (among modern fiat currencies). The jackpot amount is based on a 30-year annuity, and is a figure based on the total gross amount you will receive without any downward adjustments for projected future inflation. The after-tax lump some payment was somewhere around $584 million, but with so much fascination with the jackpot, it ended up being split 3 ways. Therefore, the actual odds-based ticket value was probably somewhere around 80¢, after figuring in consolation prizes. That’s as good as it gets for the Powerball. An immediate 60% loss. Typically, jackpots are far lower, and even considering the recent 67% increase in odds from 1 in 175 million to 1 in 292 million, we see that this was still the best cost–benefit ratio for Powerball; the 2nd largest jackpot was much less than half the 2016-01-13 jackpot. Obviously, your (averaged) odds of dying in a car accident today are better than 1 in 292 million.

Insurance is arguably the inverse of lotteries; you pay a relatively small premium to avoid rare yet potentially catastrophic costs. With lotteries, you play a small entrance fee for a minuscule chance at a fantastic upside. While no competent financial planner advocates reckless lottery spending, being well-insured is something that experts and empirical evidence supports. However, without understanding of arithmetic, fractions, percentages, interest, compounding, odds, risk, insurance laws and procedures, etc., you could easily get suckered. This education is sorely lacking from K–12 schooling and many people find it tedious and uninteresting to acquire, despite its importance.

Obliviousness to basic arithmetic leads to being screwed over. You’ll buy the wrong things, be fooled by psychological tricks, and misunderstand every financial decision you make.

Eating out and throwing away food

I understand that some people do not have the appetite for large portion sizes that I have. Nevertheless, excluding salads, ice cream, and frozen yogurt, you can easily take home most foods to be eaten as leftovers. I can’t understand throwing away food prepared at home or purchased while dining. Even at a buffet, I rarely through out food. As someone who has worked in restaurants and in the stockroom of a grocery store, I know that conservation often seems pointless after seeing firsthand how much these businesses waste. However, it typically reduces your costs, improving your financial situation. Instead of getting a soda for $2.99 and eating part of your plate, drink water and eat all of (the food on) your plate. The calorie count will probably be the same, and you’ll be getting better nutrients.

Failing to understand the cost–time relationship

If time is money, money is time. You can buy other, foolish people’s time with your money! Therefore, while money cannot increase the amount of time you have (except with respect to extended lifespan due to better diet, medicine, etc.), it can allow you to accomplish more by using other people’s time, without slavery or duress. This is an amazing characteristic of money.

One example of where people vastly overvalue cost (and undervalue time) is in selecting a gas station. Basically, going out of your way at all to save a few cents per gallon is not worth the time, inconvenience, or effort, because you are probably only buying fewer than 20 gallons of gas anyway and would be saving less than a dollar or two. Yet, people often driver further, plan their routes, and devote considerable mental energy to such tiny savings on gas prices, while overlooking other huge financial blunders such as $100+ monthly cell phone bills.

Your time is valuable, and becomes obviously more valuable as you age. However, realizing the value of your time in youth is preferable; you are not likely not burdened by failing health and waning energy in your youth. Of course, the value of your time in dollars is probably related to your income and accumulated wealth; if you have no savings, you are going to have to make some very time-inefficient decisions just to survive. Becoming financially literate will help you avoid being homeless or without savings in the future, however.

If you live to 80, you have 62 adult years, or 22,645 days. How many of these days will be spent dying, sick, or in the service of others? Perhaps 5000? If you work in an awful career or live with a toxic spouse long enough, perhaps 10,000? You might only have 15,000 or fewer good days. Even a long human life is very short in many respects. You should not only value and guard your time, but you should also actively and thoughtfully evaluate its use and optimization. Since money is a vector for time, allowing you to free up time or employ the time of others, it should likewise be guarded.

Using credit cards really badly

There have been so many articles written about responsible credit card use that it is difficult to broach this subject without being trite. I will simply present this short vignette I typed up:

SMART:
Racking up charges on items that are cash-equivalents or are essential to earning money, on a credit card with a 12- to 24-month 0.00% promotional APR rate, while you have savings or low-risk investments that earn a solid return during this period. While the level of risk of your investments should always be such that it is very unlikely you would have to pay credit card interest rates, the potential for profit here is large: consider that if you max out a credit card with a $20,000 credit line for 12 months and invest the money in something such as an S&P 500 index fund, which earned about 8% annually on average over the past 10 years, you could make over $1500 gross in just one year. The savvy credit user also knows that the negative impact of high credit utilization effectively vanishes in less than a month after paying off the balance; as long as you aren’t taking out a mortgage or car loan during the 12-month period, it will be of no practical significance. (Caveat: Credit scores are being used for more things and I am not sure how detrimental this may be to your car insurance rates, health insurance rates, seeking an apartment, or seeking a job. If your overall utilization is below 30% across all your credit cards, the negative impact to your credit score will be lessened).

NOT SMART:
Racking up tuition charges on the above credit card at a 2% convenience fee, because you believe you “probably” can pay them back at the end of the year and avoid student loan fees and interest. Then, “probably” becomes “no way in hell” and you end up paying 22.99% APR on debt you could have been paying 3.4% APR on.

REALLY NOT SMART:
Racking up charges on the above credit card without understanding that the 0.00% APR does NOT mean no payment is due each month. Then, missing the monthly minimum payment and being immediately subject to the 29.99% penalty APR, with no way to pay off the debt.

Buying a house

Buying a house used to be a completely sane decision. As of January 2016, however, American housing prices are quite high; they are above historical averages when compared to wages, and perhaps entering another bubble. Very few people even think of making the standard 20% down payment on a house, let alone buying one entirely with accumulated savings. While cash sales are on the rise, these buyers are part of an elusive rentier class that epitomizes the startling stratification of wealth in America; many are banks themselves, and others are foreigners (try buying real estate in Mexico or another country as a foreigner, and you will see that America is unusual). While housing is historically an appreciating investment, and interest rates are quite low with good credit, maintaining a house costs a boatload of money, which may approach or even exceed the costs of renting or leasing. While accumulated equity is a salient rallying cry, a house can also be an albatross; it can tie you to a geographic area, preventing nationwide or even statewide job searches.

I have no fewer than three friends in their early to mid-twenties who are looking to buy houses, but without (in my opinion) any compelling reasons to do so. Paying rent every month is hard, and having a house is the holy grail of the American dream because it allows you to accumulate lots of stuff, but by renting and keeping your belongings to a reasonable minimum, you are much more flexible and mobile.

Picturing a fairytale future

I am amazed by how many women who are otherwise progressive feminists, yet still yearn for the “rich husband” who will wipe out their student loans and finance their unsustainable lifestyles. This is a profoundly demeaning and patriarchal idea, and yet, for many, it remains more appealing than self-discipline and personal responsibility!

Of course, it would not be fair to criticize young women without also criticizing young men who are aimless and adrift, not working toward a prosperous career nor even pursuits that provide meaningful personal fulfillment. In either case, descending into “magical thinking,” where one relies for hope on some black swan, external event such as winning the lottery or receiving an incredible job offer, becomes far too common. Self-discipline is a bitter pill to swallow, and is something that probably must come about by an internal impetus for meaningful change, rather than external pressures. It may also be disconcerting to recognize that self-discipline is a cumulative process, because it requires admitting that years or decades have basically been frittered away. However, our mortality coupled with the unidirectional nature of time indicts the present day as perennially the best and soonest feasible time to initiate meaningful change. While you may have to lower your fairytale expectations if advanced age, a criminal record, or enormous debts or obligations are present in your life, this does not mean you should give up. Further, the process of applying self-discipline may be enjoyable in itself (indeed, if it is not, persistence is difficult).

Conclusion

In encouraging personal financial literacy, as with any other educational ambition, criticizing and denigrating people for their ignorance, bad choices, and ridiculous beliefs often pushes them away. “Sneaking in” belief change in small, measured quantities, without labeling it as such, may be more efficacious. Moreover, maintaining an encouraging, forward-looking attitude that recognizes individual needs and individual levels of understanding is almost unarguably superior to belittlement. It is my hope that my online course on the Udemy platform, Introduction to American Personal Financial Literacy, currently under development and slated for completion in April 2016, partially fulfilling the requirements of my Master of Arts degree in Applied Learning & Instruction at University of Central Florida, will recognize these individual needs and encourage meaningful learning and change, without overwhelming or belittling students, encouraging a growth mindset throughout.

Proofs, Alibis, and Falsifiability

As a graduate student in the social sciences, I have firmly learned to avoid saying anything is “proven” on the basis of empirical research, but instead that some concept, such as Carol Dweck’s work on mindsets which I have recently began studying, has been “supported” by research.

This blog post by Satoshi Kanazawa from Psychology Today (2008) explains it in an accessible way:

Proofs exist only in mathematics and logic, not in science. Mathematics and logic are both closed, self-contained systems of propositions, whereas science is empirical and deals with nature as it exists. The primary criterion and standard of evaluation of scientific theory is evidence, not proof.

Surprisingly, I am just learning that math is not science. I had not heard of this before. “Doctor Ian” from the Math Forum at Drexel explains it fairly well in this forum post from 2001. Since math and logic exist in fairytale worlds, proofs are entirely possible in these worlds, but not in the world of empirical science.

Regarding science: This word is derived from the Latin word scire, which simply means “to know.” This is one of many areas where the accoutrements of a field have come to popularly define it—a “scientist” arguably does not need to have a position, title, or advanced education, but merely knowledge.

Alibis are a legal defense used to establish innocence, based on the defendant being in a different location at the time a crime occurred. Assuming validity, an alibi proves the defendant did not commit a crime (albeit not disproving ancillary involvement). Since people can only be in one place at a time, it is not possible for you to have directly committed a murder in someone’s home at 9:30 am and also to have been at church. Of course, you could have booby-trapped their home with explosives, which would still be murder, but my point is that an alibi can actually prove something by disproving all alternatives.

This blog post by Claes Johnson (2012) was my source for the idea regarding alibis and falsifiability. Johnson says:

Comparing with a legal case, we know that to convict someone for murder it is necessary with some positive evidence which connects the suspect to the deed, like fingerprints. We know that lack of negative evidence, such as lack of alibi, is not enough for conviction to the electric chair. It should neither be enough to convict a theory to the heavy burden of being scientific.

Popper’s negativism expresses his criticism of positivism, which serves the purpose of making modern physics based on statistics acceptable as science.

I thought an alibi would be positive evidence, but either I do not understand the difference between positivism and negativism or it is a matter of perspective, e.g., an alibi could be positive evidence with respect to establishing innocence, but negative evidence with respect to establishing lack of guilt, like the difference between “innocent” and “not guilty.” I am not sure if this is correct.

Regardless, the alibi is a time-limited device. It is much easier to prove that you did not commit a murder at 9:30 am on Sunday, than it is to prove that you have never committed a murder during your entire life to date, as the latter would require a comprehensive accounting of your entire life to date. Further, it is impossible to prove that you will not kill someone in the future, even to yourself. However, at all times, the conjecture that you have never committed a murder remains falsifiable—we may falsify it by simply discovering one murder you have committed. While such a discovery does not establish a ceiling on the total number of murders you may have committed, it does increase the floor from zero to one. (Floors and ceilings are mathematical terms that I am probably misusing.)

In science, we are often trying to establish theories that explain and make predictions that are timeless. Since this is a much broader task, “proving” something is out of the question. While we can disprove a conjecture by finding definitive evidence to the contrary, no amount of agreeable evidence can prove that disagreeable evidence does not exist.

Finding a ceiling requires comprehensive evidence. We need to have the entire population, rather than a sample, at our disposal. Further, we can always question the completeness and veracity of our record-keeping. While “big data” may solve some of these problems with respect to some subsets of digital communications, for practical purposes this problem is always in play. Even the U.S. Census admittedly misses thousands or millions of fugitives and illegal aliens. However, finding a floor is far easier. We could look at just 20 Americans and say, “well, we know at least 9 males exist in the U.S. population.” Without expanding our sample, we can say for sure that there are not fewer than 9 males in the U.S. population. Of course, this does not apply when mathematically negative values are a possibility, e.g., we cannot surmise an individual’s net worth is at least $5000 because they have $5000 in a bank account, for obvious reasons.

The difficulty associated with producing comprehensive evidence might be compared to the difficulty associated with “proving” something in science. Both are insurmountable. However, producing an alibi might be compared to falsifying a scientific conjecture. Both are possible, and sometimes easy. (Ah-ha: Now I understand what Johnson meant with an alibi being “negative evidence.”)

At this point, I want to introduce the Dunning–Kruger effect. This is a common cognitive bias where incompetent people grossly overestimate their skills; sometimes their self-appraisals are more aggrandizing than self-appraisals of experts! Experts suffer from the converse problem of underestimating their skills respective to others; I postulate that this leads to a chilling effect where experts give too much weight to crackpots and are restrained in denouncing them, while crackpots have no such reservations about attacking experts. Thus, crackpots get an unfair amount of attention and credibility. They make arguments that inherently (but not necessarily deliberately) cater to human cognitive biases. These might possibly include phrases like “I believe,” “any sensible person can see,” or “prove me wrong.” (“Crackpot” in this case is meant to be a humorously contemptuous characterization of individuals lacking both credentials and requisite expertise, but not individuals who merely lack the former.)

While the expert tries to present empirical evidence that the crackpot is wrong, and refrains from judgment until such evidence can be procured, the crackpot proceeds with circumstantial and logically flawed arguments, without worrying about rationally disproving the expert. Therefore, the crackpot is more confident and may even appear more credible, but this is because the playing field is not level. The expert is holding him- or herself to much higher standards than the crackpot. This is not fair to the laypeople who become misled; therefore, experts should probably “suspend the rules” and discredit crackpots more vigorously than they would colleagues. (For a presentation by me on Kruger’s more recent work on the “first-instinct fallacy,” see: A Review of “Counterfactual thinking and the first instinct fallacy” by Kruger, Wirtz, & Miller (2005) [PowerPoint].)

Getting back to proofs, alibis, and falsifiability: giving someone the “benefit of doubt” is related to all three. (Side note: I do not understand why it is always phrased “benefit of the doubt.” Additional side-note: It is not fair for anyone to imply something or someone is wrong or unusual just because they have not heard of it or encountered it before. Perhaps the problem is with me.) First, you lack proof. Second, they have an alibi, or you can think of one for them. Third, their innocence is falsifiable, but you don’t have enough evidence to feel confident. Clearly, the other person has all the knowledge with respect to his or her behavior. This might be called the “defender’s advantage,” and is present whenever the defender is given benefit of doubt and has a knowledge advantage—both are principles of American criminal justice. Conversely, the “attacker’s advantage” exists when benefit of doubt is removed, particularly when the attacker also has a knowledge advantage. An example of the attacker’s advantage is Amazon.com, Inc. defrauding me in September 2015 (and remains unresolved). Amazon.com, Inc. bans users and steals their gift card balances, Amazon Prime memberships, Kindle e-books, and other content, without possibility of appeal or explanation; they do not give customers benefit of doubt and immediately remove the customer’s access to all order history and other account data, which represents a strong and arguably unfair attacker’s advantage. Neither advantage is fair unless affirmative—in American criminal justice the defender’s advantage is typically fair because it compensates for the awesome prosecutorial power of the state (unless the defendant is wealthy). However, corporations defrauding their customers by enforcing punitive and open-ended terms of use is particularly insidious. It is a triple threat, because they hold both attacker’s advantages (greater knowledge and removal of benefit of doubt, which might also be labeled presumed innocence), plus far greater money and power.

While I am ending this essay on what appears to be a substantial tangent, I think tangents and interdisciplinary approaches are important. (I can even recall reading research that supports this.) There are often connections that we do not see without stepping out of our box. While this is not a license to become a dilettante, consider that branching out may be a better use of your energy than trudging forward.

If you are looking to branch out, I recommend reading about logic and philosophy, which has long been one of my favorite pastimes.

Research Proposal: Does Visual Search Performance Vary with Task Complexity as a Function of Mental Fatigue?

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The following essay was written by Richard Thripp as an assignment for EXP 6506: Cognition and Learning class at University of Central Florida in fall 2015 in Prof. Joseph Schmidt’s class. Mr. Thripp does not intend to conduct this research.

Click here to download the PDF copy of this paper.

Caveats:

Specific statistical analyses and implications were not discussed. Implications were not adequately related to the existing literature. (Paraphrased from professor’s comments.)

I forgot to mention that the positions of the circles and pegs would be randomized and randomly changed in each display, and I didn’t specify any parameters for this.

There was admittedly no reason to have normal sleep patterns or medications in the participants section. I think I forgot to develop that but should have just removed it.

Figure captions were included above figures, contrary to APA 6th edition style.

 

Does Visual Search Performance Vary with Task Complexity as a Function of Mental Fatigue?

Richard Thripp

University of Central Florida

November 4, 2015

 

Abstract

This proposal explores a potential experiment exposing participants to low and high levels of mental fatigue, followed by easy and hard visual search tasks. Mental fatigue will be achieved with an easy or difficult memory task involving memorizing target letters and identifying their presence in subsequent displays of letters; this task will be employed continuously for two 45-minute periods. Easy visual search will involve looking for a circle with a peg among plain circles, while hard visual search will involve looking for circles with no pegs or two pegs among circles with one peg. Participants will be asked to commit to four testing sessions on four separate days in a 2 × 2 within-subjects design. A version of the NASA Task Load Index will be administered at the mid-point and end of each session. Interactions involving accuracy, reaction times, and subjective task load will be explored. The results may indicate that mental fatigue should be taken more seriously for motorists, air traffic controllers, and other critical activities and careers.

Keywords: visual search, task complexity, mental fatigue, vigilance, after-effects of mental effort

 

Does Visual Search Performance Vary with Task Complexity as a Function of Mental Fatigue?

Professionals who perform complex and important tasks, such as medical doctors and air traffic controllers, are often subject to schedules encouraging insufficient sleep and severe mental fatigue, which leads to an increased frequency of errors (Lowy, 2015). How to allow for sufficient sleep is sometimes obvious: do not schedule shifts eight hours apart, for instance. However, mental fatigue may be a more complex issue.

Bullock and Giesbrecht (2014) found that intensive aerobic activity resulted in faster reaction times for a visual search task, but no change in accuracy. Schellekens, Sijtsma, Vegeter, and Meijman (2000) conducted an impressive study on mental fatigue where each participant worked in two simulated eight-hour office workdays in easy and difficult mental-load conditions. A memory-search probe task was conducted at the beginning of the workday, the end of the workday, and 2.5 hours after the end of the workday—it was found that participants committed significantly more errors in both probe tasks after a difficult workday, with no change in reaction times. While this is reminiscent of a speed–accuracy tradeoff, their speed did not improve—fatigue is a possible reason for their reduced performance.

Faber, Maurits, and Lorist (2012) reiterated the impacts of mental fatigue on attention, finding that continuous task performance led to increased distractibility that manifested as reduced accuracy and increased reaction times over a two-hour period of performing a flanker task. With respect to vigilance tasks, Tiwari, Singh, and Singh (2009) found that higher task demand and perceived mental workload resulted in significantly lower motivation, concentration level, attention, and accuracy, albeit insignificant differences regarding reaction time. Haga, Shinoda, and Kokubun (2002) implemented a dual tracking and memory search task for a total of 30 minutes at three difficulty levels; task difficulty level was found to be a greater determinant of subjective levels of stress than time-on-task. While 30 minutes is not long, the authors say they have found similar results in subsequent 60- and 90-minute experiments (p. 142).

Overall, the research indicates that mental fatigue has detrimental effects on performance for visual attention tasks, though degradation is more consistent for accuracy as compared to reaction time. Interestingly, ocular instability has been found to increase with time-on-task regardless of task complexity; this leads to increased drift velocity and decreased saccadic and microsaccadic velocity (Stasi et al., 2013). Stasi et al. used an air traffic control task designed for laypersons, making their study particularly original and relevant. While high air traffic density is admittedly a more powerful predictor of slowed reaction times, reduced accuracy, and greater subjective mental fatigue (p. 2396), time-on-task remains important—too much time spent on a low-complexity task (e.g., low air traffic) can still be dangerous. The impact of ocular instability and other confounding factors might explain why the relationship between performance and task complexity in mental fatigue research is sometimes murky.

When combining high mental fatigue with hard visual search, inferior performance may be expected than if visual search was preceded by low mental fatigue. However, high mental fatigue may have detrimental effects even for easy visual search. This study may be the first attempt to systematically study these phenomena with contemporary, computer-based methods.

Current Study

The current study will combine two levels of mental fatigue with easy or hard visual searches in a wholly within-subjects design. Vision is arguably the most important sense, and reduced visual search performance can result in loss of life, limb, and property—air traffic control is a salient example (Stasi et al., 2013; Lowy, 2015), as is operating heavy machinery or performing delicate surgery, but driving a car is a relevant and far more common example. I could find no study directly examining visual search performance as a function of mental fatigue via a memory-search task, much less one that manipulates difficulty levels for both tasks. While Schellekens et al. (2000) manipulated an entire workday to be mentally easy or difficult and measured performance on a probe memory-search task, the probe task difficulty remained the same for all participants. Nevertheless, their probe task of remembering a list of alphabetic letters and identifying the presence of a matching letter is useful because it can be quite demanding or easy, by manipulating the compatibility of the noise letters (Eriksen & St. James, 1986). Therefore, for the mental fatigue task, I propose a hybrid between Schellekens et al. (2000) and Eriksen and St. James (1986). Subjects will be asked to remember letters and determine if displays contain a remembered letter, but the difficulty will be varied, primarily by compatibility of noise letters. In the easy condition, noise letters will be incompatible, meaning they look different from the target letters. However, in the hard condition, noise letters will be compatible, meaning they will be easy to confuse with the target letters. The hard condition, because of its ambiguity, should be mentally exhausting in comparison with the easy condition.

Participants in this study will be asked to commit to four separate days of testing. On each day, they will be assigned to one of four conditions in a within-subjects design that varies complexity and difficulty for a memory-search and visual search task. They will be exposed to all four difficulty combinations, but the order will be counter-balanced. The memory-search task will last a total of 90 minutes, in two sessions of 45 minutes interspersed with a visual search task, a subjective fatigue questionnaire (the NASA-TLX), and a short break. The visual search task will be given three times (beginning, middle, and end) per session, and the NASA-TLX will be given twice (middle and end).

Easy visual searches will involve looking for a pegged circle among a field with 12–13 non-pegged circles, while hard visual searches will involve looking for an unpegged circle or a circle with two pegs among a field with 11–13 circles having one peg each. It is expected the hard visual search will be of much greater difficulty, given the nature of the task and the added cognitive load of looking for two types of targets. Additionally, the pegs in the hard condition will be about half the length of the pegs in the easy condition. The idea for pegged circles is borrowed from Persuh, Genzer, and Melara (2012), though they were using them for an iconic memory task, rather than a strict visual search task. We will see how performance on each level of the visual search task varies when paired with low versus high mental fatigue tasks.

Proposed Methods

Participants. Prospective participants will be required to have normal or corrected-to-normal vision, normal sleep patterns, to be without psychiatric or neurological illness, and to not be taking medications that might confound results. They will be asked to commit to 4 days of testing and to select possible dates and times they may be available. Participants will not be allowed to schedule more than one session in a calendar day. Participants will be asked to not consume alcohol for 24 hours before each session nor caffeine for 12 hours—caffeine has been found to have specific effects on information processing (Lorist, Snel, Kok, & Mulder, 1994). Participants will be encouraged to schedule sessions between 9:00–12:00 in the morning to avoid fatigue from daily life or diurnal rhythms impacting results, but it is not expected that all participants will be able to accommodate this. Compensation will be offered on a sliding scale to minimize attrition: for each of the four sessions, participants will receive, in order, $30, $40, $55, and $75. If an appointment is missed, participants will have the option of re-scheduling so they can still complete all four sessions, but this point will be omitted in the briefing session to discourage missed appointments, unless participants specifically ask. The air temperature of the testing space will be 72 F. Since the proportion of participants who attrite is difficult to predict, the initial sample size should be somewhat liberal to ensure enough participants complete all four conditions—perhaps 25–30 participants.

Materials and procedures. Participants will be seated at a computer desk in a lab with overhead fluorescent tube lighting and no natural lighting, 75 cm from a 19” true-color LED-backlit LCD monitor with a 16:9 aspect ratio, resolution of 1920 × 1080 pixels, and refresh rate of 60 Hz. The monitor will be calibrated to a color temperature of 6500 K, display gamma of 2.2, and luminance of 125 cd/m2 with a ColorVision Spyder colorimeter. Both types of tasks will entail binary responses; participants will textually be instructed to be both fast and accurate and no further elaboration will be given. Participants will press the “J” key on a QWERTY wired USB keyboard for “yes” and the “F” key for “no.” At all times, a computer program will record their reaction times and correctness, which will subsequently be statistically analyzed by the researcher. Between trials, a red fixation cross will be displayed for 200 ms on visual search trials; masking “%” percentage signs (like the asterisks used by Schellekens et al., 2000, p. 40) will be shown for 200 ms on mental fatigue tasks. When participants respond correctly, the fixation cross or masking percentage signs will be immediately displayed with no feedback; for incorrect responses, a blank screen saying “Incorrect” will first be displayed for 100 ms, followed by the fixation cross or masking percentage signs for 200 ms. Trials where participants fail to respond within 1500 ms for low mental load or easy visual searches, or within 2500 ms for high mental load or hard visual searches, will be counted as failures to respond for purposes of data analysis, but participants will not know about this. All text will be in Arial font. Backgrounds will be dark gray (#7A7B82) and cued items will be white (#FFFFFF) in all instructions and tasks, except the NASA-TLX questionnaire (see figure 15).

Mental fatigue tasks. The mental fatigue tasks will be similar to the probe task used by Schellekens et al. (2000), but will employ the concept of compatible and incompatible noise letters exemplified by Eriksen and St. James (1986). High mental fatigue tasks will involve participants being shown four underlined letters for 950 ms. On 2–5 subsequent displays, participants will have to respond indicating whether one of the four target letters is among the four displayed letters. Easy mental fatigue tasks will show three underlined letters for 1400 ms, and on exactly 3 subsequent displays, participants will respond indicating whether one of the three cue letters is among the three displayed letters. No time limits will be imposed on any responses.

Eriksen and St. James (1986) did a visual search experiment requiring little or no memory, so they simply duplicated the cue letters for compatible noise. For this experiment, I developed a list of 19 letters that look easily confusable with other letters (figure 1).

Figure 1: Letters and compatible noise letters employed for the high mental fatigue condition. 19 of 26 letters are included; excluded are A, C, G, H, L, T, and W. Note that most relationships are reciprocal, except D/B, R/P, and Y/V. Unfortunately, the author came up with this list in Microsoft Notepad in about 30 minutes; he has no empirical evidence to support it.

The low mental fatigue condition will only use the letters the author thinks are less confusable as target letters: A, C, G, H, L, T, and W. There will only be three letters per display, and predictably, three tasks per trial. While any of the 26 letters may be displayed in tasks, there will be a 25% chance that the same letter will be displayed in 2 out of 3 spots.

The high mental fatigue condition will use the 19 confusable letters from figure 1 as target letters. There will be four letters per display, and participants will be given two, three, four, or five tasks per trial, randomly; therefore, they will not know whether a new trial has started until the masking percentage signs appear for 200 ms, following which they will have only 950 ms to commit the newly displayed letters to memory. There will be a 60% chance that the compatible noise letter for a target letter will be selected as a displayed letter on each task; otherwise, a random letter will be selected. Positions will be shuffled on all trials.

It is predicted that the hard visual search task will be very distressing and mentally fatiguing, given the additional load, randomness, confusing letters, and reduced time for memorization (950 ms versus 1400 ms).

Figure 2: Instructions screen for both easy and hard visual search tasks.

Figure 3: Example of a low mental fatigue display of target letters.

Figure 4: Example of a low mental fatigue task. Two letters are duplicated in this display (occurs 25% of the time with the hope of making the task even easier).

Figure 5: Example of a high mental fatigue display of target letters.

Figure 6: Example of a high mental fatigue task where compatible noise letters for all target letters from figure 5 are displayed.

Figure 7: Masking percentage signs shown for 200 ms between high mental fatigue trials. Masks for low mental fatigue trials have three percentage signs instead of four.

Figure 8: Incorrect notification given for 100 ms in all tasks following an incorrect answer.

Visual search tasks. The visual search tasks will borrow the idea of pegged circles from Persuh, Genzer, and Melara (2012). In the easy condition, participants will be looking for a circle with a long peg in any of four 90º orientations among a display containing 13 circles, of which either 12 or 13 are unpegged. In the hard condition, participants will be looking circles with no pegs or two pegs among a display containing 13 circles, of which 11, 12, or 13 have one peg; pegs in the hard condition may be in any of eight 45º orientations; therefore, 28 variations of circles with two pegs may appear, as shown by this combinatory expression that disallows repetition:

Combinatory formula

Therefore, the total numbers of potential targets types and potential distractors are 29 and 8, respectively, in the hard visual search condition, as compared to 4 and 1, respectively, in the easy visual search condition. Time limits will not be imposed in any visual search tasks.

In both conditions, 50% of trials will have target(s) present and 50% will have target(s) absent. For the hard visual search condition, 15% of trials will have both targets present and 35% will have one target present. This means that 30% of target-present trials in the hard condition will be easier, since participants can press “J” for YES as soon as they find one of the two targets. This is intended to add flair to the hard condition; it should not impact results since the conditions are not designed to be compared to each other directly, and the hard condition is already so much harder than the easy condition.

Figure 9: Instructions screen for easy visual search condition.

Figure 10: Example of an easy visual search task, target present.

Figure 11: Instructions screen for hard visual search condition.

Figure 12: Example of a hard visual search task, both targets present (occurs in 15% of trials).

Figure 13: Fixation cross shown for 200 ms between visual search trials.

Further procedural details. The visual search task will be five minutes long and will be given continuously for 10 minutes at the start of all sessions (at the same difficulty level that will be used throughout the session), with the hope of standardizing practice effects so all participants are operating at a roughly equal level of practice in the pre-test, mid-test, and post-test. After a five-minute break, the visual search task will be given again as the official pre-test. During the 90-minute mental fatigue task, there will be an intermission after 45 minutes where the visual search task will immediately be given again (mid-test), followed by a fatigue questionnaire, and a 10-minute break. Upon return from break, the same sequence will repeat, and the session will conclude after the visual search task is administered for the 3rd time and the fatigue questionnaire is administered for the 2nd time.

Task complexity will be varied at two levels for both the mental fatigue task and subsequent visual search task. A within-subjects design will be used, where participants will be exposed to all four levels of the experiment on four separate days.

All tasks (including before and after the intermission) will be at the same complexity level for each session and day. The following four conditions will be used:

  • Condition 1: Low mental load, easy visual search
  • Condition 2: High mental load, easy visual search
  • Condition 3: Low mental load, hard visual search
  • Condition 4: High mental load, hard visual search

Conditions will be counter-balanced so that approximately a quarter of participants start with each condition in their first session. Subsequent sessions will be similarly counter-balanced.

In sustained tasks exceeding 30 minutes, maintaining arousal level is important to prevent boredom (Haga et a., 2002, p. 142); however, the author believes the easy mental load task is sufficient to maintain arousal, because of the additional memory requirement. Further, due to the brevity of the visual search tasks (less than 30 minutes), it is not anticipated that arousal level will be a problem with easy tasks.

Fatigue questionnaire. The NASA Task Load Index (TLX) will be used as our fatigue questionnaire (Hart & Staveland, 1988). A computerized version will be administered, in a “raw TLX” mode where pairwise comparisons are eliminated for brevity, and where the “physical demand” subscale is dropped. The other five subscales will be retained, including “temporal demand”—even though there is no time pressure placed on participants, it may be interesting to see whether more temporal demand is erroneously reported in the hard conditions. Participants will use a wired USB optical mouse to adjust the sliders on the subscales to their desired ratings—100 possible responses for each subscale will be possible, with each of the 20 displayed hatch marks being 5 points apart (though no numerical indication will be provided). Participants will be instructed to consider both the preceding mental fatigue tasks and visual search tasks as a unit, since the NASA-TLX will not be administered in between the two tasks.

Figure 14: Instructions screen for NASA-TLX questionnaire.

Figure 15: The modified NASA-TLX questionnaire that will be used. Note that the “physical demand” subscale will not be used or shown in the final implementation. Figure adapted from “Screenshot of the PEBL TLX scale” (2012).


 

Expected Results

It is predicted that accuracy and reaction times will be better on the hard visual search task when it follows low mental load rather than high mental load. Performance should be better on the easy visual search if mental fatigue is low; however, the effect of mental fatigue may be more pronounced with hard visual searches since they are more cognitively taxing. With the high mental fatigue conditions, visual search performance should be highest in the pre-test, lower on the mid-test, and lowest on the post-test, similar to findings by Tiwari et al. (2009) on stress and vigilance. Given that Haga et al. (2002) found that difficulty level, not time-on-task determined task load levels in their dual tracking and memory search task experiments, results for the NASA-TLX may be largely the same for the mid-administration as compared to the post-administration. Overall, NASA-TLX results should indicate low stress on the low mental load / easy visual search condition, and relatively higher stress on the high mental load / hard visual search condition, particularly on the effort and mental demand subscales. However, Haga et al. did find that other workload measures were sensitive to time-on-task and surmised the relationships to be complex and hard to dissect (p. 142). Therefore, as the session drags on, degradation in performance on the high mental fatigue task would be unsurprising.

The above predictions assume that participants who do not complete all four sessions will be excluded from statistical analyses. Counter-balancing will be used to ensure an approximately equal number of participants receive each permutation of conditions, which should compensate for many possible extraneous variables. The high mental load condition may be particularly frustrating for some participants—it may be necessary to make the task less frustrating to reduce attrition, but the verdict is unclear at this preliminary stage.

Since the easy and hard conditions within each category (mental fatigue and visual search) are different from each other in multiple ways, it is not anticipated that they will be directly comparable to each other—they may only be comparable to themselves as a function of difficulty level in the other category.

Many within-subject analyses of variance (ANOVAs) will be conducted on the statistical data to look for main effects between mean error rates and mean accuracy rates for the different combinations of tasks, as well as interactions with subjective fatigue reports on the five selected subscales of the NASA-TLX questionnaire, both as a whole and individually. Additionally, the real-time data for response times and accuracy rates for mental fatigue tasks will analyzed temporally, by breaking each 45-minute block down into nine 5-minute chunks and looking for trends, both for individual subjects and across multiple subjects. Since this is a complicated experiment, there are many interactions and combinations to be examined. Therefore, it is expected that at least several significant interactions will be found.

Discussion and Implications

This study will help elucidate whether mental fatigue has a relationship with visual search performance as a function of task complexity. If mental fatigue leads to poorer visual search performance, and these results withstand scrutiny and are amiable to replication, it should be recommended that motorists and others limit their mental fatigue prior to driving or performing other dangerous tasks.

The consequences of mental fatigue may be more severe when coupled with poor quality sleep, distracting emotions, alcohol and drug use, and difficult conditions such as heavy rain while driving or high air traffic volume for air traffic controllers (Stasi et al., 2013; Lowy, 2015)—further research is needed on these combinations. Studying mental fatigue in the laboratory may produce conservative results, particularly because we exclude participants with sleep aberrations, alcohol or caffeine addictions (Lorist et al., 1994), drug addictions or dependencies, and uncorrected vision. While these exclusions are necessary to produce homogenous samples, they are not naturalistic. Therefore, the costs and consequences of mental fatigue may be higher and more pronounced in the real world, where these factors are present.

How do you prevent prolonged mental fatigue? Frequent breaks are in order. Furthermore, structuring the workday in such a way that mental fatigue is spread out, interspersed with mundane activity such as basic data entry or housekeeping, may help. Research studies that identify mental fatigue as a real problem, as this one hopes to, will help us influence industries and individuals to account for it in their daily operations and lives.
 

References

Bullock, T., & Giesbrecht, B. (2014). Acute exercise and aerobic fitness influence selective attention during visual search. Frontiers in Psychology, 5(1290), 1–11. doi:10.3389/fpsyg.2014.01290

Di Stasi, L. L., McCamy, M. B., Catena, A., Macknik, S. L., Cañas, J. J., & Martinez-Conde, S. (2013). Microsaccade and drift dynamics reflect mental fatigue. European Journal of Neuroscience, 38, 2389–2398. doi:10.1111/ejn.12248

Eriksen, C., & St. James, J. (1986). Visual attention within and around the field of focal attention: A zoom lens model. Perception & Psychophysics, 40(4), 225–240. doi:10.3758/BF03211502

Faber, L. G., Maurits, N. M., & Lorist, M. M. (2012). Mental fatigue affects visual selective attention. Plos One, 7(10), 1–10. doi:10.1371/journal.pone.0048073

Haga, S., Shinoda, H., & Kokubun, M. (2002). Effects of task difficulty and time-on-task on mental workload. Japanese Psychological Research, 44(3), 134–143.

Hart, S. G. & Staveland, L. E. (1988). Development of NASA-TLX (task load index): Results of empirical and theoretical research. In P. A. Hancock and N. Meshkati (Eds.), Human mental workload. Amsterdam: North Holland.

Lorist, M. M., Snel, J., Kok, A., & Mulder, G. (1994). Influence of caffeine on selective attention in well-rested and fatigued subjects. Psychophysiology, 31, 525–534.

Lowy, J. (2015, August 11). Air traffic controllers are dangerously overworked. Business Insider. Retrieved November 4, 2015, from http://www.businessinsider.com/air-traffic-controllers-are-dangerously-overworked-2015-8

Persuh, M., Genzer, B., & Melara, R. D. (2012). Iconic memory requires attention. Frontiers in Human Neuroscience, 6(126), 1–8. doi:10.3389/fnhum.2012.00126

Schellekens, J. M. H., Sijtsma, G. J., Vegter, E., & Meijman, T. F. (2000). Immediate and delayed after-effects of long lasting mentally demanding work. Biological Psychology, 53, 37–56. doi:10.1016/S0301-0511(00)00039-9

Screenshot of the PEBL TLX scale, an implementation of the NASA-TLX subjective workload instrument. (2012, November 26). In Wikipedia. Retrieved November 4, 2015, from https://en.wikipedia.org/wiki/File:Tlx.pbl.png

Tiwari, T., Singh, A. L., & Singh, I. L. (2009). Task demand and workload: Effects on vigilance performance and stress. Journal of the Indian Academy of Applied Psychology, 35(2), 265–275.

 
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A Review of “Counterfactual thinking and the first instinct fallacy” by Kruger, Wirtz, & Miller (2005) [PowerPoint]

A Review of “Counterfactual thinking and the first instinct fallacy” by Kruger, Wirtz, & Miller (2005)

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References

Epstude, K., & Roese, N. J. (2008). The functional theory of counterfactual thinking. Personality and Social Psychology Review, 12(2), 168–192.

Kruger, J., Wirtz, D., & Miller, D. T. (2005). Counterfactual thinking and the first instinct fallacy. Journal of Personality and Social Psychology, 88, 725–735.

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Tags: cognitive psychology, counterfactual thinking, deal or no deal, first instinct fallacy, learning, logic, logical fallacies, monty hall problem, paradoxes, perception, reasoning, regret

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Fenske, M. J., Aminoff, E., Gronau, N., & Bar, M. (2006). Chapter 1: Top-down facilitation of visual object recognition: Object-based and context-based contributions. Progress in Brain Research, 155, 3–21. doi:10.1016/S0079-6123(06)55001-0

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