Making Significant Changes If a project is doing badly and you communicate about the changes to the stakeholders, they are often frustrated. This low tolerance towards bad news is a result of optimism bias.
Challenge Your Optimism Bias Researchers have stated that optimism bias is hardwired into our brains, making it impossible to be absolutely bias-free. Infrequent events influence optimism bias. We often think that we have things under control, making us believe in our skills to manage things that are beyond our control. If a negative event is perceived as unlikely, we undermine its likelihood of occurring for example, a severe health disorder.
Experience the event : Negative experiences are likely to minimize optimism bias. For example, many people achieve success in life by believing in their ability to succeed. Banks continued to engage in high-risk decision making and contributed to the growing economic bubble and its ultimate crash. The optimism bias also impacts our global response to climate change. We also tend to feel like bad things may happen to others, but not ourselves. With climate change, this can allow us to feel like the consequences of environmental disaster will not affect us personally.
We might acknowledge the imminence of climate change, but our ability to assume that we will come out unscathed often prevents serious action.
This was proved in a study where psychology researchers found that generally, the optimism bias resulted in less environmental concern. In order to understand the effects of the optimism bias, it is important to understand where it comes from and why. By breaking down biases into their cognitive processes and exploring their harms and benefits, we have a better chance of learning how to avoid costly decision-making.
The optimism bias instills feelings of control. We generally want to feel as if we have control over our lives and our fates. Negative events like illness, divorce, or financial loss often threaten our plans or derail the predictions we have about ourselves. Optimism prevents us from lingering in these negative outcomes. For many traits in humans, there are adaptive functions that can be traced back to the primitive evolutionary environment. If a trait promoted survival and furthered chances for reproduction, it would continue to be passed onto offspring.
It might seem as though a realist might be more successful than an optimist, yet the widespread optimism in humans shows a clear functional benefit. Economists Heifetz and Spiegel simulated interactions in our evolutionary environment between individuals with different degrees of optimism. Their optimistic bias towards their outcome results in more aggression and dominance in the conflict. Another area in which the optimism bias is adaptive is health, both physical and mental.
Quantitative data on levels of optimism and pessimism in depressive patients found that the optimism bias was positively associated with low levels of depression. Additionally, optimism has been shown to encourage healthy eating and exercise. So how do we stay optimistic in the face of information that tells us our beliefs are false?
Sharot and her colleagues sought out to answer this question. The subjects demonstrated how the optimism bias skews our judgment. With this information, Sharot concluded that we have the tendency to update our beliefs regarding positive information much more than we do with negative information.
Through selectively calibrating our expectations with positive events, we can maintain optimism even in the face of negativity. All of us, including experts, are susceptible to the optimism bias. In situations where we have a lot at stake surrounding our success, the optimism bias can cause us to ignore important information that can make or break our outcome. However, the fate of our projects, our businesses, our economy, and our planet can be put at risk by the optimism bias.
We must be able to recognize when our optimism is clouding our judgment at major costs, and there are tangible ways to do so. Nobel Prize-winning economist Daniel Kahneman has widely researched the optimism bias and proposes two different ways of mitigating its influence on our decision making: taking an outside view and a post mortem approach.
The optimism bias often causes us to overestimate our abilities or our control over our environment. Base rates are existing statistics from relevant situations that provide quantitative data to anchor our judgements. Base rates can be the probability of an event occurring, the average time something takes, or whatever figure fits the situation—as long as the base rate is from existing data. Kahneman proposes taking an outside perspective through the following three steps:. While these steps apply most directly to time management and planning, the use of base rates can be a major tool in grounding your expectations and combatting optimism bias.
The premortem approach is an exercise for teams to predict potential areas of failure when beginning a project. Everyone on the team is instructed to imagine it is a year from the present and the project has failed.
They are then instructed to write out what has gone wrong and why. By forcing team members to consider negative outcomes, we can resist the shortsightedness of overconfidence. For example, a respondent might be asked to "compare your risk with that of the average person of your age and sex" on a scale that ranges from "below average" to "above average" with "average" as the midpoint.
Investigators have generally used odd-numbered scales e. If the mean response is higher or lower than this midpoint, one has demonstrated an optimistic bias assuming that the sample is fully representative of the reference group, and that actual risk is not highly skewed. Another approach is to ask participants to make two judgments - an estimate of their own risk on a likelihood scale, for example , and an estimate of the risk of the average peer see Appendix.
These ratings can then be subtracted, and if the mean difference is not zero, a bias can be said to exist. This is called the "indirect" method of measuring optimistic bias.
The attractiveness of such an approach is that it is possible to assess whether a given moderator influences estimates of personal risk or the comparative target's risk. Interestingly, some studies show that the magnitude of bias is greater when using the direct method e. Bias at the individual level.
Although the above methods are effective when evaluating optimistic bias at the level of the group, they cannot be used to determine which members of a group are biased. A woman who believes her risk of breast cancer is below average, for example, may be quite accurate if she has no risk factors for breast cancer.
In fact, this woman may be unrealistically pessimistic if her comparative risk is even more below average than she thinks it is. It is important to be able to identify which members of a sample are biased, however, in order to determine whether biases are correlated with other individual-level variables such as personality and behavior see Appendix. Many studies attempting to link optimistic biases and related "positive illusions" with other variables such as health behavior simply define bias as a tendency to make self-serving judgments, without taking the important step of assessing the accuracy of these judgments.
Consequently, although we know that optimistic beliefs are related to precautionary behaviors and ultimately to a more adaptive psychophysiological profile e. A small number of studies have attempted to use objective criteria to assess individual bias. Several of these studies use experimenter-initiated models to determine which members of the sample are at higher risk e.
Very few studies measure actual outcomes to determine accuracy, and such studies are needed. Absolute vs. There is no reason, of course, to limit optimistic biases to comparative beliefs. The use of a comparative measure was initially based on the ease of demonstrating optimistic bias at the group level Weinstein, However, if a man predicts that he will not get prostate cancer and then he does, he would clearly be optimistically biased.
Whether an investigator measures optimistic bias based on comparative or absolute measures should depend on the hypothesis being tested. Absolute and comparative risk perceptions are not redundant; each explains independent variance in worry, behavior, and other related constructs Lipkus et al. Cross-sectional and prospective designs. An important methodological issue one faces when attempting to link optimistic biases with other constructs such as risk-reducing behavior is the type of design in which these constructs are measured.
Assessing any type of risk perception and behavior in a cross-sectional design makes it difficult to determine whether bias influences behavior, behavior influences bias or both , or whether a third variable such as education or negative affectivity influences both Gerrard et al.
The same problem applies when attempting to link biased risk perceptions with other constructs. Although there is now a growing literature using prospective designs to assess the link between risk perceptions and behavior, very few of these studies evaluate the accuracy of these risk perceptions.
Given the difficulty of measuring optimistic biases at the level of the individual, there are few if any studies that determine the test-retest reliability of optimistically biased judgments. Moreover, because bias is usually established for single events, no data are available to determine whether bias is consistent across multiple events, so there are no published scales that measure a general form of the optimistic bias.
Although some studies have collapsed comparative ratings across multiple events based on high reliability coefficients and identified the collapsed index as a generalized measure of optimistic bias e. Most research has investigated optimistic biases at the group level, which has been sufficient given the predominant focus on which types of events, comparative targets, and other factors elicit the most bias.
However, in order to establish the utility of this construct in the domain of health, it is necessary to measure optimistic bias at the level of the individual. Given the difficulties of doing so, research taking this approach is in its infancy. For the most part, the evidence so far suggests that optimistic biases may be harmful.
These studies typically control for obvious confounds such as educational level. Importantly, one study showed that HIV seropositive individuals who were optimistically biased about their AIDS risk engaged in more health-protective behaviors Taylor et al. Importantly, most of these studies are correlational, making it difficult to pinpoint optimistically biased risk perceptions as a direct cause of behavior.
Optimistic biases are thought to represent one example of an array of self-serving beliefs that may influence behavior including the illusion of control Langer, , the better-than-average effect e. Perceptions of control and self-efficacy represent key components of many models such as Social Cognitive Theory Bandura, and the Theory of Planned Behavior Ajzen, , highlighting the importance that biases in control and efficacy beliefs might play in health behavior.
It is notable that optimistic beliefs and health threats seem to be only weakly associated with dispositional optimism e. Conclusions Although much research has investigated the underlying causes and moderators of optimistic biases, less work has addressed how optimistically biased beliefs are related to health information processing, behavior, and physical health outcomes.
In order to properly assess the impact of optimistic biases, it is important to use accuracy criteria that identify optimistic biases at the level of the individual.
The increasing availability of risk engines such as the Harvard Risk Index Colditz et al. Ajzen, I. The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 , Alicke, M. Personal contact, individuation, and the better-than-average effect. Journal of Personality and Social Psychology, 68 , Armor, D. Situated optimism: Specific outcome expectancies and self-regulation.
Advances in Experimental Social Psychology, 30, Aspinwall, L. Distinguishing optimism from denial: Optimistic beliefs predict attention to health threats. Personality and Social Psychology Bulletin, 22 , Avis, N. Accuracy of risk perceptions of heart attack risk: What influences perceptions and can they be changed? American Journal of Public Health, 79 , Bandura, A.
Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52 , Blalock, S. Risk perceptions and participation in colorectal cancer screening. Health Psychology, 9 , Boney-McCoy, S. Self-esteem, compensatory self-enhancement, and the consideration of health risk.
Personality and Social Psychology Bulletin, 25 , Burger, J. In our careers, for example, optimism can become a self-fulfilling prophecy, according to Sharot. And when we expect positive things, we're happier and that has a positive effect on our health by reducing things like anxiety.
Optimism is also linked to success in multiple domains, whether it's business, politics or sports. CEOs tend to be more optimistic than the average person, as are entrepreneurs , whose optimism increases further once they take the leap into starting their businesses. The Olympics come with pageantry, colour and, in most cases, spiralling costs for the host linked to a surfeit of optimism Credit: Alamy. American psychologist Martin Seligman teaches people to cultivate a more optimistic viewpoint by ascribing permanent causes to positive things and temporary ones to negative things.
The message is that good things happen for reasons inherent to the individual, while bad things are attributed to causes that can be remedied, such as last-minute preparations. This cultivates a positive self-view that makes us optimistic about our future prospects. In the workplace, Laslett suggests keeping a diary of projections and outcomes in order to assess your own level of bias, so as to adjust for it if needed.
Doing so might result, for example, in allowing three weeks to complete a project, rather than two. How would we respond? Contingency planning can help make a plan more likely to reflect reality than just the optimism someone might feel about an initiative.
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