Optimism bias

Last updated

Optimism bias or optimistic bias is a cognitive bias that causes someone to believe that they themselves are less likely to experience a negative event. It is also known as unrealistic optimism or comparative optimism. It is common and transcends gender, ethnicity, nationality, and age. [1] Autistic people are less susceptible to this kind of bias. [2] It has also been reported in other animals, such as rats and birds. [3]

Contents

Four factors can cause a person to be optimistically biased: their desired end state, their cognitive mechanisms, the information they have about themselves versus others, and overall mood. [4] The optimistic bias is seen in a number of situations. For example: people believing that they are less at risk of being a crime victim, [5] smokers believing that they are less likely to contract lung cancer or disease than other smokers, first-time bungee jumpers believing that they are less at risk of an injury than other jumpers, [6] or traders who think they are less exposed to potential losses in the markets. [7]

Although the optimism bias occurs for both positive events (such as believing oneself to be more financially successful than others) and negative events (such as being less likely to have a drinking problem), there is more research and evidence suggesting that the bias is stronger for negative events (the "valence effect"). [4] [8] Different consequences result from these two types of events: positive events often lead to feelings of well being and self-esteem, while negative events lead to consequences involving more risk, such as engaging in risky behaviors and not taking precautionary measures for safety. [4]

Factors

The factors leading to the optimistic bias can be categorized into four different groups: desired end states of comparative judgment, cognitive mechanisms, information about the self versus a target, and underlying affect. [4] These are explained more in detail below.

Measuring

Optimism bias is typically measured through two determinants of risk: absolute risk, where individuals are asked to estimate their likelihood of experiencing a negative event compared to their actual chance of experiencing a negative event (comparison against self), and comparative risk, where individuals are asked to estimate the likelihood of experiencing a negative event (their personal risk estimate) compared to others of the same age and sex (a target risk estimate). [8] [9] Problems can occur when trying to measure absolute risk because it is extremely difficult to determine the actual risk statistic for a person. [9] [10] Therefore, the optimistic bias is primarily measured in comparative risk forms, where people compare themselves against others, through direct and indirect comparisons. [6] Direct comparisons ask whether an individual's own risk of experiencing an event is less than, greater than, or equal to someone else's risk, while indirect comparisons ask individuals to provide separate estimates of their own risk of experiencing an event and others' risk of experiencing the same event. [9] [11]

After obtaining scores, researchers are able to use the information to determine if there is a difference in the average risk estimate of the individual compared to the average risk estimate of their peers. Generally, in negative events, the mean risk of an individual appears lower than the risk estimate of others. [9] This is then used to demonstrate the bias' effect. The optimistic bias can only be defined at a group level, because at an individual level the positive assessment could be true. [8] Likewise, difficulties can arise in measurement procedures, as it is difficult to determine when someone is being optimistic, realistic, or pessimistic. [9] [11] Research suggests that the bias comes from an overestimate of group risks rather than underestimating one's own risk. [9]

An example: participants assigned a higher probability to picking a card that had a smiling face on its reverse side than one which had a frowning face. [12]

Cognitive mechanisms

The optimistic bias is possibly also influenced by three cognitive mechanisms that guide judgments and decision-making processes: the representativeness heuristic, singular target focus, and interpersonal distance. [4]

Representativeness heuristic

The estimates of likelihood associated with the optimistic bias are based on how closely an event matches a person's overall idea of the specific event. [4] Some researchers suggest that the representativeness heuristic is a reason for the optimistic bias: individuals tend to think in stereotypical categories rather than about their actual targets when making comparisons. [13] For example, when drivers are asked to think about a car accident, they are more likely to associate a bad driver, rather than just the average driver. [4] Individuals compare themselves with the negative elements that come to mind, rather than an overall accurate comparison between them and another driver. Additionally, when individuals were asked to compare themselves towards friends, they chose more vulnerable friends based on the events they were looking at. [14] Individuals generally chose a specific friend based on whether they resemble a given example, rather than just an average friend. [14] People find examples that relate directly to what they are asked, resulting in representativeness heuristics.

Singular target focus

One of the difficulties of the optimistic bias is that people know more about themselves than they do about others. While individuals know how to think about themselves as a single person, they still think of others as a generalized group, which leads to biased estimates and inabilities to sufficiently understand their target or comparison group. Likewise, when making judgments and comparisons about their risk compared to others, people generally ignore the average person, but primarily focus on their own feelings and experiences. [4]

Interpersonal distance

Perceived risk differences occur depending on how far or close a compared target is to an individual making a risk estimate. [4] The greater the perceived distance between the self and the comparison target, the greater the perceived difference in risk. When one brings the comparison target closer to the individual, risk estimates appear closer together than if the comparison target was someone more distant to the participant. [4] There is support for perceived social distance in determining the optimistic bias. [15] Through looking at comparisons of personal and target risk between the in-group level contributes to more perceived similarities than when individuals think about outer-group comparisons which lead to greater perceived differences. [15] In one study, researchers manipulated the social context of the comparison group, where participants made judgements for two different comparison targets: the typical student at their university and a typical student at another university. Their findings showed that not only did people work with the closer comparison first, but also had closer ratings to themselves than the "more different" group. [15]

Studies have also noticed that people demonstrate more optimistic bias when making comparisons when the other is a vague individual, but biases are reduced when the other is a familiar person, such as a friend or family member. This also is determined due to the information they have about the individuals closest to them, but not having the same information about other people. [8]

Desired end states of comparative judgment

Many explanations for the optimistic bias come from the goals that people want and outcomes they wish to see. [4] People tend to view their risks as less than others because they believe that this is what other people want to see. These explanations include self-enhancement, self-presentation, and perceived control.

Self-enhancement

Self-enhancement suggests that optimistic predictions are satisfying and that it feels good to think that positive events will happen. [4] People can control their anxiety and other negative emotions if they believe they are better off than others. [4] People tend to focus on finding information that supports what they want to see happen, rather than what will happen to them. [4] With regards to the optimistic bias, individuals will perceive events more favorably, because that is what they would like the outcome to be. This also suggests that people might lower their risks compared to others to make themselves look better than average: they are less at risk than others and therefore better. [4]

Self-presentation

Studies suggest that people attempt to establish and maintain a desired personal image in social situations. People are motivated to present themselves towards others in a good light, and some researchers suggest that the optimistic bias is a representative of self-presentational processes: people want to appear better off than others. This is not through conscious effort. In a study where participants believed their driving skills would be either tested in either real-life or driving simulations, people who believed they were to be tested had less optimistic bias and were more modest about their skills than individuals who would not be tested. [16] Studies also suggest that individuals who present themselves in a pessimistic and more negative light are generally less accepted by the rest of society. [17] This might contribute to overly optimistic attitudes.

Personal control/perceived control

People tend to be more optimistically biased when they believe they have more control over events than others. [4] [10] [18] For example, people are more likely to think that they will not be harmed in a car accident if they are driving the vehicle. [18] Another example is that if someone believes that they have a lot of control over becoming infected with HIV, they are more likely to view their risk of contracting the disease to be low. [9] Studies have suggested that the greater perceived control someone has, the greater their optimistic bias. [18] [13] Stemming from this, control is a stronger factor when it comes to personal risk assessments, but not when assessing others. [10] [18]

A meta-analysis reviewing the relationship between the optimistic bias and perceived control found that a number of moderators contribute to this relationship. [10] In previous research, participants from the United States generally had higher levels of optimistic bias relating to perceived control than those of other nationalities. Students also showed larger levels of the optimistic bias than non-students. [10] The format of the study also demonstrated differences in the relationship between perceived control and the optimistic bias: direct methods of measurement suggested greater perceived control and greater optimistic bias as compared to indirect measures of the bias. [10] The optimistic bias is strongest in situations where an individual needs to rely heavily on direct action and responsibility of situations. [10]

An opposite factor of perceived control is that of prior experience. [9] Prior experience is typically associated with less optimistic bias, which some studies suggest is from either a decrease in the perception of personal control, or make it easier for individuals to imagine themselves at risk. [9] [13] Prior experience suggests that events may be less controllable than previously believed. [9]

Information about self versus target

Individuals know a lot more about themselves than they do about others. [4] Because information about others is less available, information about the self versus others leads people to make specific conclusions about their own risk, but results in them having a harder time making conclusions about the risks of others. This leads to differences in judgments and conclusions about self-risks compared to the risks of others, leading to larger gaps in the optimistic bias. [4]

Person-positivity bias

Person-positivity bias is the tendency to evaluate an object more favorably the more the object resembles an individual human being. Generally, the more a comparison target resembles a specific person, the more familiar it will be. Groups of people are considered to be more abstract concepts, which leads to less favorable judgments. With regards to the optimistic bias, when people compare themselves to an average person, whether someone of the same sex or age, the target continues to be viewed as less human and less personified, which will result in less favorable comparisons between the self and others. [4]

Egocentric thinking

"Egocentric thinking" refers to how individuals know more of their own personal information and risk that they can use to form judgments and make decisions. One difficulty, though, is that people have a large amount of knowledge about themselves, but no knowledge about others. Therefore, when making decisions, people have to use other information available to them, such as population data, in order to learn more about their comparison group. [4] This can relate to an optimism bias because while people are using the available information they have about themselves, they have more difficulty understanding correct information about others. [4]

It is also possible that someone can escape egocentric thinking. In one study, researchers had one group of participants list all factors that influenced their chances of experiencing a variety of events, and then a second group read the list. Those who read the list showed less optimistic bias in their own reports. It's possible that greater knowledge about others and their perceptions of their chances of risk bring the comparison group closer to the participant. [13]

Underestimating average person's control

Also regarding egocentric thinking, it is possible that individuals underestimate the amount of control the average person has. This is explained in two different ways:

  1. People underestimate the control that others have in their lives. [13]
  2. People completely overlook that others have control over their own outcomes.

For example, many smokers believe that they are taking all necessary precautionary measures so that they won't get lung cancer, such as smoking only once a day, or using filtered cigarettes, and believe that others are not taking the same precautionary measures. It is likely that many other smokers are doing the same things and taking those same precautions. [4]

Underlying affect

The last factor of optimistic bias is that of underlying affect and affect experience. Research has found that people show less optimistic bias when experiencing a negative mood, and more optimistic bias when in a positive mood. [9] Sad moods reflect greater memories of negative events, which lead to more negative judgments, while positive moods promote happy memories and more positive feelings. [4] This suggests that overall negative moods, including depression, result in increased personal risk estimates but less optimistic bias overall. [9] Anxiety also leads to less optimistic bias, continuing to suggest that overall positive experiences and positive attitudes lead to more optimistic bias in events. [9]

Health consequences

In health, the optimistic bias tends to prevent individuals from taking on preventative measures for good health. [19] For example, people who underestimate their comparative risk of heart disease know less about heart disease, and even after reading an article with more information, are still less concerned about risk of heart disease. [11] Because the optimistic bias can be a strong force in decision-making, it is important to look at how risk perception is determined and how this will result in preventative behaviors. Therefore, researchers need to be aware of the optimistic bias and the ways it can prevent people from taking precautionary measures in life choices.

Risk perceptions are particularly important for individual behaviors, such as exercise, diet, and even sunscreen use. [20]

A large portion of risk prevention focuses on adolescents. Especially with health risk perception, adolescence is associated with an increased frequency of risky health-related behaviors such as smoking, drugs, and unsafe sex. [3] While adolescents are aware of the risk, this awareness does not change behavior habits. [21] Adolescents with strong positive optimistic bias toward risky behaviors had an overall increase in the optimistic bias with age. [19]

Unconditional risk questions in cross-sectional studies are used consistently, leading to problems, as they ask about the likelihood of an action occurring, but does not determine if there is an outcome, or compare events that haven't happened to events that have. [20] many times there are methodological problems in these tests.

Concerning vaccines, perceptions of those who have not been vaccinated are compared to the perceptions of people who have been. Other problems which arise include the failure to know a person's perception of a risk. [20] Knowing this information will be helpful for continued research on optimistic bias and preventative behaviors.

Neurosciences

Functional neuroimaging suggests a key role for the rostral Anterior Cingulate Cortex (ACC) in modulating both emotional processing and autobiographical retrieval. It is part of brain network showing extensive correlation between rostral ACC and amygdala during imagining of future positive events and restricted correlation during imagining of future negative events. Based on these data, it is suggested that the rostral ACC has a crucial part to play in creating positive images of the future and ultimately, in ensuring and maintaining the optimism bias. [1]

Policy, planning, and management

Optimism bias influences decisions and forecasts in policy, planning, and management, e.g., the costs and completion times of planned decisions tend to be underestimated and the benefits overestimated due to optimism bias. The term planning fallacy for this effect was first proposed by Daniel Kahneman and Amos Tversky. [22] [23] There is a growing body of evidence proving that optimism bias represents one of the biggest single causes of risk for megaproject overspend. [24]

Valence effect

Valence effect is used to allude to the effect of valence on unrealistic optimism. [25] It has been studied by Ron S. Gold and his team since 2003. [26] They frame questions for the same event in different ways: "some participants were given information about the conditions that promote a given health-related event, such as developing heart disease, and were asked to rate the comparative likelihood that they would experience the event. Other participants were given matched information about the conditions that prevent the same event and were asked to rate the comparative likelihood that they would avoid the event". They have generally found that unrealistic optimism was greater for negative than positive valence.

Valence effects, which is also considered a form of cognitive bias, [27] [28] have several real-world implications. For instance, it can lead to the overestimation of a company's future earnings by investors and this could contribute to a tendency for it to becoming overpriced. [28] In terms of achieving organizational objectives, it could encourage people to produce unrealistic schedules helping drive a so-called planning fallacy, which often result in making poor decisions and project abandonment. [29]

Attempts to alter and eliminate

Studies have shown that it is very difficult to eliminate the optimistic bias. Some commentators believe that trying to reduce it may encourage people to adapt to health-protective behaviors. Research has suggested that it cannot be reduced, and that efforts to reduce it tend to lead to even more optimistically biased results. [30] In a research study of four different tests to reduce the optimistic bias, through lists of risk factors, participants perceiving themselves as inferior to others, participants asked to think of high-risk individuals, and giving attributes of why they were at risk, all increased the bias rather than decreased it. [30] Other studies have tried to reduce the bias through reducing distance, but overall it still remains. [15]

This seemingly paradoxical situation – in which an attempt to reduce bias can sometimes actually increase it – may be related to the insight behind the semi-jocular and recursively worded "Hofstadter's law", which states that:

It always takes longer than you expect, even when you take into account Hofstadter's law.

Although research has suggested that it is very difficult to eliminate the bias, some factors may help in closing the gap of the optimistic bias between an individual and their target risk group. First, by placing the comparison group closer to the individual, the optimistic bias can be reduced: studies found that when individuals were asked to make comparisons between themselves and close friends, there was almost no difference in the likelihood of an event occurring. [14] Additionally, actually experiencing an event leads to a decrease in the optimistic bias. [9] While this only applies to events with prior experience, knowing the previously unknown will result in less optimism of it not occurring.

Pessimism bias

The opposite of optimism bias is pessimism bias (or pessimistic bias), because the principles of the optimistic bias continue to be in effect in situations where individuals regard themselves as worse off than others. [4] Optimism may occur from either a distortion of personal estimates, representing personal optimism, or a distortion for others, representing personal pessimism. [4]

Pessimism bias is an effect in which people exaggerate the likelihood that negative things will happen to them. It contrasts with optimism bias.

People with depression are particularly likely to exhibit pessimism bias. [31] [32] Surveys of smokers have found that their ratings of their risk of heart disease showed a small but significant pessimism bias; the literature as a whole is inconclusive. [33]

See also

Related Research Articles

<span class="mw-page-title-main">Wishful thinking</span> Formation of beliefs based on what might be pleasing to imagine

Wishful thinking is the formation of beliefs based on what might be pleasing to imagine, rather than on evidence, rationality, or reality. It is a product of resolving conflicts between belief and desire. Methodologies to examine wishful thinking are diverse. Various disciplines and schools of thought examine related mechanisms such as neural circuitry, human cognition and emotion, types of bias, procrastination, motivation, optimism, attention and environment. This concept has been examined as a fallacy. It is related to the concept of wishful seeing.

Hindsight bias, also known as the knew-it-all-along phenomenon or creeping determinism, is the common tendency for people to perceive past events as having been more predictable than they were.

A self-serving bias is any cognitive or perceptual process that is distorted by the need to maintain and enhance self-esteem, or the tendency to perceive oneself in an overly favorable manner. It is the belief that individuals tend to ascribe success to their own abilities and efforts, but ascribe failure to external factors. When individuals reject the validity of negative feedback, focus on their strengths and achievements but overlook their faults and failures, or take more credit for their group's work than they give to other members, they are protecting their self-esteem from threat and injury. These cognitive and perceptual tendencies perpetuate illusions and error, but they also serve the self's need for esteem. For example, a student who attributes earning a good grade on an exam to their own intelligence and preparation but attributes earning a poor grade to the teacher's poor teaching ability or unfair test questions might be exhibiting a self-serving bias. Studies have shown that similar attributions are made in various situations, such as the workplace, interpersonal relationships, sports, and consumer decisions.

The positivity effect is the ability to constructively analyze a situation where the desired results are not achieved, but still obtain positive feedback that assists one's future progression.

The illusion of control is the tendency for people to overestimate their ability to control events. It was named by U.S. psychologist Ellen Langer and is thought to influence gambling behavior and belief in the paranormal. Along with illusory superiority and optimism bias, the illusion of control is one of the positive illusions.

Depressive realism is the hypothesis developed by Lauren Alloy and Lyn Yvonne Abramson that depressed individuals make more realistic inferences than non-depressed individuals. Although depressed individuals are thought to have a negative cognitive bias that results in recurrent, negative automatic thoughts, maladaptive behaviors, and dysfunctional world beliefs, depressive realism argues not only that this negativity may reflect a more accurate appraisal of the world but also that non-depressed individuals' appraisals are positively biased.

Explanatory style is a psychological attribute that indicates how people explain to themselves why they experience a particular event, either positive or negative.

Social comparison theory, initially proposed by social psychologist Leon Festinger in 1954, centers on the belief that individuals drive to gain accurate self-evaluations. The theory explains how individuals evaluate their opinions and abilities by comparing themselves to others to reduce uncertainty in these domains and learn how to define the self. Comparing oneself to others socially is a form of measurement and self-assessment to identify where an individual stands according to their own set of standards and emotions about themselves.

<span class="mw-page-title-main">Risk perception</span>

Risk perception is the subjective judgement that people make about the characteristics and severity of a risk. Risk perceptions often differ from statistical assessments of risk since they are affected by a wide range of affective, cognitive, contextual, and individual factors. Several theories have been proposed to explain why different people make different estimates of the dangerousness of risks. Three major families of theory have been developed: psychology approaches, anthropology/sociology approaches and interdisciplinary approaches.

The overconfidence effect is a well-established bias in which a person's subjective confidence in their judgments is reliably greater than the objective accuracy of those judgments, especially when confidence is relatively high. Overconfidence is one example of a miscalibration of subjective probabilities. Throughout the research literature, overconfidence has been defined in three distinct ways: (1) overestimation of one's actual performance; (2) overplacement of one's performance relative to others; and (3) overprecision in expressing unwarranted certainty in the accuracy of one's beliefs.

Attribution is a term used in psychology which deals with how individuals perceive the causes of everyday experience, as being either external or internal. Models to explain this process are called Attribution theory. Psychological research into attribution began with the work of Fritz Heider in the early 20th century, and the theory was further advanced by Harold Kelley and Bernard Weiner. Heider first introduced the concept of perceived 'locus of causality' to define the perception of one's environment. For instance, an experience may be perceived as being caused by factors outside the person's control (external) or it may be perceived as the person's own doing (internal). These initial perceptions are called attributions. Psychologists use these attributions to better understand an individual's motivation and competence. The theory is of particular interest to employers who use it to increase worker motivation, goal orientation, and productivity.

The negativity bias, also known as the negativity effect, is a cognitive bias that, even when positive or neutral things of equal intensity occur, things of a more negative nature have a greater effect on one's psychological state and processes than neutral or positive things. In other words, something very positive will generally have less of an impact on a person's behavior and cognition than something equally emotional but negative. The negativity bias has been investigated within many different domains, including the formation of impressions and general evaluations; attention, learning, and memory; and decision-making and risk considerations.

Positive illusions are unrealistically favorable attitudes that people have towards themselves or to people that are close to them. Positive illusions are a form of self-deception or self-enhancement that feel good; maintain self-esteem; or avoid discomfort, at least in the short term. There are three general forms: inflated assessment of one's own abilities, unrealistic optimism about the future, and an illusion of control. The term "positive illusions" originates in a 1988 paper by Taylor and Brown. "Taylor and Brown's (1988) model of mental health maintains that certain positive illusions are highly prevalent in normal thought and predictive of criteria traditionally associated with mental health."

Error management theory (EMT) is an approach to perception and cognition biases originally coined by David Buss and Martie Haselton. Error management training is a related area that uses this theory. The objective of it is to encourage trainees to make errors and encourage them in reflection to understand the causes of those errors and to identify suitable strategies to avoid making them in future.

Self-enhancement is a type of motivation that works to make people feel good about themselves and to maintain self-esteem. This motive becomes especially prominent in situations of threat, failure or blows to one's self-esteem. Self-enhancement involves a preference for positive over negative self-views. It is one of the three self-evaluation motives along with self-assessment and self-verification . Self-evaluation motives drive the process of self-regulation, that is, how people control and direct their own actions.

In social psychology, illusory superiority is a cognitive bias wherein people overestimate their own qualities and abilities compared to others. Illusory superiority is one of many positive illusions, relating to the self, that are evident in the study of intelligence, the effective performance of tasks and tests, and the possession of desirable personal characteristics and personality traits. Overestimation of abilities compared to an objective measure is known as the overconfidence effect.

The fading affect bias, more commonly known as FAB, is a psychological phenomenon in which memories associated with negative emotions tend to be forgotten more quickly than those associated with positive emotions. FAB only refers to the feelings one has associated with the memories and not the content of the memories themselves. Early research studied FAB retrospectively, or through personal reflection, which brought about some criticism because retrospective analysis can be affected by subjective retrospective biases. However, new research using non-retrospective recall studies have found evidence for FAB, and the phenomenon has become largely accepted.

<span class="mw-page-title-main">Optimism</span> Positive mental attitude

Optimism is an attitude reflecting a belief or hope that the outcome of some specific endeavor, or outcomes in general, will be positive, favorable, and desirable. A common idiom used to illustrate optimism versus pessimism is a glass filled with water to the halfway point: an optimist is said to see the glass as half full, while a pessimist sees the glass as half empty.

The false-uniqueness effect is an attributional type of cognitive bias in social psychology that describes how people tend to view their qualities, traits, and personal attributes as unique when in reality they are not. This bias is often measured by looking at the difference between estimates that people make about how many of their peers share a certain trait or behaviour and the actual number of peers who report these traits and behaviours.

<span class="mw-page-title-main">Toxic positivity</span> Construct in psychology

Toxic positivity is dysfunctional emotional management without the full acknowledgment of negative emotions, particularly anger and sadness. Socially, it is the act of dismissing another person's negative emotions by suggesting a positive emotion instead.

References

  1. 1 2 Owen P, O'Sullivan (2015). "The neural basis of always looking on the bright side". Dialogues in Philosophy, Mental and Neuro Sciences. 8 (1): 11–15.
  2. Kuzmanovic, B.; Rigoux, L.; Vogeley, K. (2014-01-14). "Brief Report: Reduced Optimism Bias in Self-Referential Belief Updating in High-Functioning Autism". Journal of Autism and Developmental Disorders. 49 (7): 2990–2998. doi:10.1007/s10803-016-2940-0. PMID   27757736. S2CID   254571982.
  3. 1 2 Sharot, Tali (2011-12-06). "The optimism bias". Current Biology. 21 (23): R941–R945. doi: 10.1016/j.cub.2011.10.030 . ISSN   0960-9822. PMID   22153158.
  4. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Shepperd, James A.; Patrick Carroll; Jodi Grace; Meredith Terry (2002). "Exploring the Causes of Comparative Optimism" (PDF). Psychologica Belgica. 42 (1–2): 65–98. CiteSeerX   10.1.1.507.9932 . doi: 10.5334/pb.986 . Archived from the original (PDF) on 2011-11-25.
  5. Chapin, John; Grace Coleman (2009). "Optimistic Bias: What you Think, What you Know, or Whom you Know?". North American Journal of Psychology. 11 (1): 121–132.
  6. 1 2 Weinstein, Neil D.; William M. Klein (1996). "Unrealistic Optimism: Present and Future". Journal of Social and Clinical Psychology. 15 (1): 1–8. doi:10.1521/jscp.1996.15.1.1.
  7. Elder; Alexander "Trading for a Living; Psychology, Trading Tactics, Money Management" John Wiley & Sons 1993, Intro – sections "Psychology is the Key" & "The Odds are against You", And Part I "Individual Psychology", Section 5 "Fantasy versus Reality" ISBN   0-471-59224-2
  8. 1 2 3 4 Gouveia, Susana O.; Valerie Clarke (2001). "Optimistic bias for negative and positive events". Health Education. 101 (5): 228–234. doi:10.1108/09654280110402080.
  9. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Helweg-Larsen, Marie; James A. Shepperd (2001). "Do Moderators of the Optimistic Bias Affect Personal or Target Risk Estimates? A Review of the Literature" (PDF). Personality and Social Psychology Review. 5 (1): 74–95. CiteSeerX   10.1.1.567.546 . doi:10.1207/S15327957PSPR0501_5. S2CID   30461688.
  10. 1 2 3 4 5 6 7 Klein, Cynthia T. F.; Marie Helweg-Larsen (2002). "Perceived Control and the Optimistic Bias: A Meta-analytic Review" (PDF). Psychology and Health. 17 (4): 437–446. doi:10.1080/0887044022000004920. S2CID   144020132. Archived from the original (PDF) on 2016-10-10.
  11. 1 2 3 Radcliffe, Nathan M.; William M. P. Klein (2002). "Dispositional, Unrealistic, and Comparative Optimism: Differential Relations with the Knowledge and Processing of Risk Information and Beliefs about Personal Risk". Personality and Social Psychology Bulletin. 28 (6): 836–846. doi:10.1177/0146167202289012. S2CID   146244253.
  12. Taylor, Nigel, Making Actuaries Less Human: Lessons from Behavioral Finance. The Staple Inn Actuarial Society, 2000-01-18. Last accessed on 2009-03-16.
  13. 1 2 3 4 5 Weinstein, Neil D. (1980). "Unrealistic optimism about future life events". Journal of Personality and Social Psychology. 39 (5): 806–820. CiteSeerX   10.1.1.535.9244 . doi:10.1037/0022-3514.39.5.806. S2CID   14051760.
  14. 1 2 3 Perloff, Linda S; Barbara K. Fetzer (1986). "Self-other judgments and perceived vulnerability to victimization". Journal of Personality and Social Psychology. 50 (3): 502–510. doi:10.1037/0022-3514.50.3.502.
  15. 1 2 3 4 Harris, P; Wendy Middleton; Richard Joiner (2000). "The typical student as an in-group member: eliminating optimistic bias by reducing social distance". European Journal of Social Psychology. 30 (2): 235–253. doi:10.1002/(SICI)1099-0992(200003/04)30:2<235::AID-EJSP990>3.0.CO;2-G.
  16. McKenna, F. P; R. A. Stanier; C. Lewis (1991). "Factors underlying illusionary self-assessment of driving skill in males and females". Accident Analysis and Prevention. 23 (1): 45–52. doi:10.1016/0001-4575(91)90034-3. PMID   2021403.
  17. Helweg-Larsen, Marie; Pedram Sadeghian; Mary S. Webb (2002). "The stigma of being pessimistically biased" (PDF). Journal of Social and Clinical Psychology. 21 (1): 92–107. doi:10.1521/jscp.21.1.92.22405.
  18. 1 2 3 4 Harris, Peter (1996). "Sufficient grounds for optimism?: The relationship between perceived controllability and optimistic bias". Journal of Social and Clinical Psychology. 15 (1): 9–52. doi:10.1521/jscp.1996.15.1.9.
  19. 1 2 Bränström, Richard; Yvonne Brandberg (2010). "Health Risk Perception, Optimistic Bias, and Personal Satisfaction". American Journal of Health Behavior. 34 (2): 197–205. doi:10.5993/ajhb.34.2.7. PMID   19814599.
  20. 1 2 3 Brewer, Noel T.; Gretchen B. Chapman; Fredrick X. Gibbons; Meg Gerrard; Kevin D. McCaul; Neil D. Weinstein (2007). "Meta-analysis of the Relationship Between Risk Perception and Health Behavior: The Example of Vaccination" (PDF). Health Psychology. 26 (2): 136–145. doi:10.1037/0278-6133.26.2.136. PMID   17385964. S2CID   3022498. Archived from the original (PDF) on 2011-07-09.
  21. Gerrard, Meg; Gibbons, Frederick X.; Benthin, Alida C.; Hessling, Robert M. (1996). "A Longitudinal Study of the Reciprocal Nature of Risk Behaviors and Cognitions in Adolescents: What You Do Shapes What You Think, and Vice Versa" (PDF). Health Psychology. 15 (5): 344–354. CiteSeerX   10.1.1.452.3853 . doi:10.1037/0278-6133.15.5.344. PMID   8891713. Archived (PDF) from the original on 2016-06-02.
  22. Pezzo, Mark V.; Litman, Jordan A.; Pezzo, Stephanie P. (2006). "On the distinction between yuppies and hippies: Individual differences in prediction biases for planning future tasks". Personality and Individual Differences. 41 (7): 1359–1371. doi:10.1016/j.paid.2006.03.029. hdl:10806/1393.
  23. Kahneman, Daniel; Tversky, Amos (1982) [1977]. "Intuitive prediction: Biases and corrective procedures". In Kahneman, Daniel; Slovic, Paul; Tversky, Amos (eds.). Judgment Under Uncertainty: Heuristics and Biases (PDF) (Decision Research Technical Report PTR-1042-77-6). Vol. 185. pp. 414–421. doi:10.1017/CBO9780511809477.031. ISBN   978-0511809477. PMID   17835457. Archived (PDF) from the original on 2013-09-08.{{cite book}}: |journal= ignored (help)
  24. Flyvbjerg, Bent (2011). "Over Budget, Over Time, Over and Over Again: Managing Major Projects". In Morris, Peter W. G.; Pinto, Jeffrey; Söderlund, Jonas (eds.). The Oxford Handbook of Project Management. Oxford: Oxford University Press. pp. 321–344. doi:10.1093/oxfordhb/9780199563142.003.0014. ISBN   978-0-19956314-2.
  25. Gold, Ron S.; Sousa, Phillip N. de (2012). "When does event valence affect unrealistic optimism?". Psychology, Health & Medicine. 17 (1): 105–115. doi:10.1080/13548506.2011.582503. PMID   21745029. S2CID   38200574.
  26. Gold, Ron S.; Martyn, Kate (6 December 2016). "Event Valence and Unrealistic Optimism". Psychological Reports. 92 (3_suppl): 1105–1109. doi:10.2466/pr0.2003.92.3c.1105. PMID   12931926. S2CID   10210392.
  27. Szatkowski, Mirosław (2018). Ontology of Theistic Beliefs. Berlin/Boston: Walter de Gruyter GmbH & Co KG. p. 81. ISBN   978-3110565799.
  28. 1 2 Hardy, Mitch; Matson, Bill (2004). Data Driven Investing: Professional Edition. Newburyport, MA: Data Driven Publishing, LLC. p. 323. ISBN   0975584200.
  29. Wrycza, Stanisław (2011). Research in Systems Analysis and Design: Models and Methods: 4th SIGSAND/PLAIS EuroSymposium 2011, Gdańsk, Poland, September 29, 2011, Revised Selected Papers . Heidelberg: Springer. pp.  95. ISBN   978-3642256752.
  30. 1 2 Weinstein, Neil D.; William M. Klein (1995). "Resistance of Personal Risk Perceptions to Debiasing Interventions". Health Psychology. 14 (2): 132–140. doi:10.1037/0278-6133.14.2.132. PMID   7789348. S2CID   25474023.
  31. Sharot, Tali; Riccardi, Alison M.; Raio, Candace M.; Phelps, Elizabeth A. (2007). "Neural mechanisms mediating optimism bias". Nature. 450 (7166): 102–105. Bibcode:2007Natur.450..102S. doi:10.1038/nature06280. ISSN   0028-0836. PMID   17960136. S2CID   4332792.
  32. Wang, PS (2004), "Effects of major depression on moment-in-time work performance", American Journal of Psychiatry, 161 (10): 1885–1891, doi: 10.1176/ajp.161.10.1885 , PMID   15465987
  33. Sutton, Stephen R. (1999), "How accurate are smokers' perceptions of risk?", Health, Risk & Society, 1 (2): 223–230, doi:10.1080/13698579908407020

Bibliography

Further reading