Illusory superiority

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Illusory_superiority

In the field of social psychology, illusory superiority is a condition of cognitive bias wherein a person overestimates their own qualities and abilities, in relation to the same qualities and abilities of other people. 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 term illusory superiority was first used by the researchers Van Yperen and Buunk, in 1991. The phenomenon is also known as the above-average effect, the superiority bias, the leniency error, the sense of relative superiority, the primus inter pares effect, and the Lake Wobegon effect, named after the fictional town where all the children are above average. The Dunning-Kruger effect is a form of illusory superiority shown by people on a task where their level of skill is low.

A vast majority of the literature on illusory superiority originates from studies on participants in the United States. However, research that only investigates the effects in one specific population is severely limited as this may not be a true representation of human psychology. More recent research investigating self-esteem in other countries suggests that illusory superiority depends on culture. Some studies indicate that East Asians tend to underestimate their own abilities in order to improve themselves and get along with others.

Explanations

Better-than-average heuristic

Alicke and Govorun proposed the idea that, rather than individuals consciously reviewing and thinking about their own abilities, behaviors and characteristics and comparing them to those of others, it is likely that people instead have what they describe as an "automatic tendency to assimilate positively-evaluated social objects toward ideal trait conceptions". For example, if an individual evaluated themselves as honest, they would be likely to then exaggerate their characteristic towards their perceived ideal position on a scale of honesty. Importantly, Alicke noted that this ideal position is not always the top of the scale; for example, with honesty, someone who is always brutally honest may be regarded as rude—the ideal is a balance, perceived differently by different individuals.

Egocentrism

Main article: Egocentrism

Another explanation for how the better-than-average effect works is egocentrism. This is the idea that an individual places greater importance and significance on their own abilities, characteristics, and behaviors than those of others. Egocentrism is therefore a less overtly self-serving bias. According to egocentrism, individuals will overestimate themselves in relation to others because they believe that they have an advantage that others do not have, as an individual considering their own performance and another's performance will consider their performance to be better, even when they are in fact equal. Kruger (1999) found support for the egocentrism explanation in his research involving participant ratings of their ability on easy and difficult tasks. It was found that individuals were consistent in their ratings of themselves as above the median in the tasks classified as "easy" and below the median in the tasks classified as "difficult", regardless of their actual ability. In this experiment the better-than-average effect was observed when it was suggested to participants that they would be successful, but also a worse-than-average effect was found when it was suggested that participants would be unsuccessful.

Focalism

Main article: Focalism

Yet another explanation for the better-than-average effect is "focalism", the idea that greater significance is placed on the object that is the focus of attention. Most studies of the better-than-average effect place greater focus on the self when asking participants to make comparisons (the question will often be phrased with the self being presented before the comparison target—"compare yourself to the average person"). According to focalism this means that the individual will place greater significance on their own ability or characteristic than that of the comparison target. This also means that in theory if, in an experiment on the better-than-average effect, the questions were phrased so that the self and other were switched (e.g., "compare the average peer to yourself") the better-than-average effect should be lessened.

Research into focalism has focused primarily on optimistic bias rather than the better-than-average effect. However, two studies found a decreased effect of optimistic bias when participants were asked to compare an average peer to themselves, rather than themselves to an average peer.

Windschitl, Kruger & Simms (2003) have conducted research into focalism, focusing specifically on the better-than-average effect, and found that asking participants to estimate their ability and likelihood of success in a task produced results of decreased estimations when they were asked about others' chances of success rather than their own.

Noisy mental information processing

A 2012 Psychological Bulletin suggests that illusory superiority, as well as other biases, can be explained by an information-theoretic generative mechanism that assumes observation (a noisy conversion of objective evidence) into subjective estimates (judgment). The study suggests that the underlying cognitive mechanism is similar to the noisy mixing of memories that cause the conservatism bias or overconfidence: re-adjustment of estimates of our own performance after our own performance are adjusted differently than the re-adjustments regarding estimates of others' performances. Estimates of the scores of others are even more conservative (more influenced by the previous expectation) than our estimates of our own performance (more influenced by the new evidence received after giving the test). The difference in the conservative bias of both estimates (conservative estimate of our own performance, and even more conservative estimate of the performance of others) is enough to create illusory superiority.

Since mental noise is a sufficient explanation that is much simpler and more straightforward than any other explanation involving heuristics, behavior, or social interaction, the Occam's razor principle argues in its favor as the underlying generative mechanism (it is the hypothesis which makes the fewest assumptions).

Selective recruitment

Selective recruitment is the notion that an individual selects their own strengths and the other's weaknesses when making peer comparisons, in order that they appear better on the whole. This theory was first tested by Weinstein (1980); however, this was in an experiment relating to optimistic bias, rather than the better-than-average effect. The study involved participants rating certain behaviors as likely to increase or decrease the chance of a series of life events happening to them. It was found that individuals showed less optimistic bias when they were allowed to see others' answers.

Perloff and Fetzer (1986) suggested that when making peer comparisons on a specific characteristic, an individual chooses a comparison target—the peer to whom he is being compared—with lower abilities. To test this theory, Perloff and Fetzer asked participants to compare themselves to specific comparison targets like a close friend, and found that illusory superiority decreased when they were told to envision a specific person rather than vague constructs like "the average peer". However, these results are not completely reliable and could be affected by the fact that individuals like their close friends more than an "average peer" and may as a result rate their friend as being higher than average, therefore the friend would not be an objective comparison target.

"Self versus aggregate" comparisons

This idea, put forward by Giladi and Klar, suggests that when making comparisons any single member of a group will tend to evaluate themselves to rank above that group's statistical mean performance level or the median performance level of its members. For example, if an individual is asked to assess their own skill at driving compared to the rest of the group, they are likely to rate themself as an above-average driver. Furthermore, the majority of the group is likely to rate themselves as above average. Research has found this effect in many different areas of human performance and has even generalized it beyond individuals' attempts to draw comparisons involving themselves. Findings of this research therefore suggest that rather than individuals evaluating themselves as above average in a self-serving manner, the better-than-average effect is actually due to a general tendency to evaluate any single person or object as better than average.

Non-social explanations

The better-than-average effect may not have wholly social origins—judgments about inanimate objects suffer similar distortions.

Neuroimaging

The degree to which people view themselves as more desirable than the average person links to reduced activation in their orbitofrontal cortex and dorsal anterior cingulate cortex. This is suggested to link to the role of these areas in processing "cognitive control".

Effects in different situations

Illusory superiority has been found in individuals' comparisons of themselves with others in a variety of aspects of life, including performance in academic circumstances (such as class performance, exams and overall intelligence), in working environments (for example in job performance), and in social settings (for example in estimating one's popularity, or the extent to which one possesses desirable personality traits, such as honesty or confidence), and in everyday abilities requiring particular skill.

For illusory superiority to be demonstrated by social comparison, two logical hurdles have to be overcome. One is the ambiguity of the word "average". It is logically possible for nearly all of the set to be above the mean if the distribution of abilities is highly skewed. For example, the mean number of legs per human being is slightly lower than two because some people have fewer than two and almost none have more. Hence experiments usually compare subjects to the median of the peer group, since by definition it is impossible for a majority to exceed the median.

A further problem in inferring inconsistency is that subjects might interpret the question in different ways, so it is logically possible that a majority of them are, for example, more generous than the rest of the group each on "their own understanding" of generosity. This interpretation is confirmed by experiments which varied the amount of interpretive freedom. As subjects evaluated themselves on a specific, well-defined attribute, illusory superiority remains.

Academic ability, job performance, lawsuits going to trial, and stock trading

In a survey of faculty at the University of Nebraska–Lincoln, 68% rated themselves in the top 25% for teaching ability, and 94% rated themselves as above average.

In a similar survey, 87% of Master of Business Administration students at Stanford University rated their academic performance as above the median.

Illusory superiority has also explained phenomena such as the large amount of stock market trading (as each trader thinks they are the best, and most likely to succeed), and the number of lawsuits that go to trial (because, due to illusory superiority, many lawyers have an inflated belief that they will win a case).

Cognitive tasks

Main article: Dunning–Kruger effect

In Kruger and Dunning's experiments, participants were given specific tasks (such as solving logic problems, analyzing grammar questions, and determining whether jokes were funny), and were asked to evaluate their performance on these tasks relative to the rest of the group, enabling a direct comparison of their actual and perceived performance.

Results were divided into four groups depending on actual performance and it was found that all four groups evaluated their performance as above average, meaning that the lowest-scoring group (the bottom 25%) showed a very large illusory superiority bias. The researchers attributed this to the fact that the individuals who were worst at performing the tasks were also worst at recognizing skill in those tasks. This was supported by the fact that, given training, the worst subjects improved their estimate of their rank as well as getting better at the tasks. The paper, titled "Unskilled and Unaware of It: How Difficulties in Recognizing One's Own Incompetence Lead to Inflated Self-Assessments", won an Ig Nobel Prize in 2000.

In 2003 Dunning and Joyce Ehrlinger, also of Cornell University, published a study that detailed a shift in people's views of themselves influenced by external cues. Cornell undergraduates were given tests of their knowledge of geography, some intended to positively affect their self-views, others intended to affect them negatively. They were then asked to rate their performance, and those given the positive tests reported significantly better performance than those given the negative.

Daniel Ames and Lara Kammrath extended this work to sensitivity to others, and the subjects' perception of how sensitive they were. Research by Burson, Larrick, and Klayman suggests that the effect is not so obvious and may be due to noise and bias levels.

Dunning, Kruger, and coauthors' latest paper on this subject comes to qualitatively similar conclusions after making some attempt to test alternative explanations.

Driving ability

Svenson (1981) surveyed 161 students in Sweden and the United States, asking them to compare their driving skills and safety to other people's. For driving skills, 93% of the U.S. sample and 69% of the Swedish sample put themselves in the top 50%; for safety, 88% of the U.S. and 77% of the Swedish put themselves in the top 50%.

McCormick, Walkey and Green (1986) found similar results in their study, asking 178 participants to evaluate their position on eight different dimensions of driving skills (examples include the "dangerous–safe" dimension and the "considerate–inconsiderate" dimension). Only a small minority rated themselves as below the median, and when all eight dimensions were considered together it was found that almost 80% of participants had evaluated themselves as being an above-average driver.

One commercial survey showed that 36% of drivers believed they were an above-average driver while texting or sending emails compared to other drivers; 44% considered themselves average, and 18% below average.

Health

Illusory superiority was found in a self-report study of health behaviors (Hoorens & Harris, 1998) that asked participants to estimate how often they and their peers carried out healthy and unhealthy behaviors. Participants reported that they carried out healthy behaviors more often than the average peer, and unhealthy behaviors less often. The findings held even for expected future behavior.

Immunity to bias

Main article: Bias blind spot

Subjects describe themselves in positive terms compared to other people, and this includes describing themselves as less susceptible to bias than other people. This effect is called the "bias blind spot" and has been demonstrated independently.

IQ

One of the main effects of illusory superiority in IQ is the "Downing effect". This describes the tendency of people with a below-average IQ to overestimate their IQ, and of people with an above-average IQ to underestimate their IQ (similar trend to the Dunning-Kruger effect). This tendency was first observed by C. L. Downing, who conducted the first cross-cultural studies on perceived intelligence. His studies also showed that the ability to accurately estimate other people's IQs was proportional to one's own IQ (i.e., the lower the IQ, the less capable of accurately appraising other people's IQs). People with high IQs are better overall at appraising other people's IQs, but when asked about the IQs of people with similar IQs as themselves, they are likely to rate them as having higher IQs.

The disparity between actual IQ and perceived IQ has also been noted between genders by British psychologist Adrian Furnham, in whose work there was a suggestion that, on average, men are more likely to overestimate their intelligence by 5 points, while women are more likely to underestimate their IQ by a similar margin.

Memory

Illusory superiority has been found in studies comparing memory self-reports, such as Schmidt, Berg & Deelman's research in older adults. This study involved participants aged between 46 and 89 years of age comparing their own memory to that of peers of the same age group, 25-year-olds and their own memory at age 25. This research showed that participants exhibited illusory superiority when comparing themselves to both peers and younger adults, however the researchers asserted that these judgments were only slightly related to age.

Popularity

In Zuckerman and Jost's study, participants were given detailed questionnaires about their friendships and asked to assess their own popularity. Using social network analysis, they were able to show that participants generally had exaggerated perceptions of their own popularity, especially in comparison to their own friends.

Despite the fact that most people in the study believed that they had more friends than their friends, a 1991 study by sociologist Scott L. Feld on the friendship paradox shows that on average, due to sampling bias, most people have fewer friends than their friends have.

Relationship happiness

Researchers have also found illusory superiority in relationship satisfaction. For example, one study found that participants perceived their own relationships as better than others' relationships on average, but thought that the majority of people were happy with their relationships. It also found evidence that the higher the participants rated their own relationship happiness, the more superior they believed their relationship was—illusory superiority also increased their own relationship satisfaction. This effect was pronounced in men, whose satisfaction was especially related to the perception that one's own relationship was superior as well as to the assumption that few others were unhappy in their relationships. On the other hand, women's satisfaction was particularly related to the assumption that most people were happy with their relationship. One study found that participants became defensive when their spouse or partner were perceived by others to be more successful in any aspect of their life, and had the tendency to exaggerate their success and understate their spouse or partner's success.

Self, friends, and peers

One of the first studies that found illusory superiority was carried out in the United States by the College Board in 1976. A survey was attached to the SAT exams (taken by one million students annually), asking the students to rate themselves relative to the median of the sample (rather than the average peer) on a number of vague positive characteristics. In ratings of leadership, 70% of the students put themselves above the median. In ability to get on well with others, 85% put themselves above the median; 25% rated themselves in the top 1%.

A 2002 study on illusory superiority in social settings, with participants comparing themselves to friends and other peers on positive characteristics (such as punctuality and sensitivity) and negative characteristics (such as naivety or inconsistency). This study found that participants rated themselves more favorably than their friends, but rated their friends more favorably than other peers (but there were several moderating factors).

Research by Perloff and Fetzer, Brown, and Henri Tajfel and John C. Turner also found friends being rated higher than other peers. Tajfel and Turner attributed this to an "ingroup bias" and suggested that this was motivated by the individual's desire for a "positive social identity".

Moderating factors

While illusory superiority has been found to be somewhat self-serving, this does not mean that it will predictably occur—it is not constant. The strength of the effect is moderated by many factors, the main examples of which have been summarized by Alicke and Govorun (2005).

Interpretability/ambiguity of trait

This is a phenomenon that Alicke and Govorun have described as "the nature of the judgement dimension" and refers to how subjective (abstract) or objective (concrete) the ability or characteristic being evaluated is. Research by Sedikides & Strube (1997) has found that people are more self-serving (the effect of illusory superiority is stronger) when the event in question is more open to interpretation, for example social constructs such as popularity and attractiveness are more interpretable than characteristics such as intelligence and physical ability. This has been partly attributed also to the need for a believable self-view.

The idea that ambiguity moderates illusory superiority has empirical research support from a study involving two conditions: in one, participants were given criteria for assessing a trait as ambiguous or unambiguous, and in the other participants were free to assess the traits according to their own criteria. It was found that the effect of illusory superiority was greater in the condition where participants were free to assess the traits.

The effects of illusory superiority have also been found to be strongest when people rate themselves on abilities at which they are totally incompetent. These subjects have the greatest disparity between their actual performance (at the low end of the distribution) and their self-rating (placing themselves above average). This Dunning–Kruger effect is interpreted as a lack of metacognitive ability to recognize their own incompetence.

Method of comparison

The method used in research into illusory superiority has been found to have an implication on the strength of the effect found. Most studies into illusory superiority involve a comparison between an individual and an average peer, of which there are two methods: direct comparison and indirect comparison. A direct comparison—which is more commonly used—involves the participant rating themselves and the average peer on the same scale, from "below average" to "above average" and results in participants being far more self-serving. Researchers have suggested that this occurs due to the closer comparison between the individual and the average peer, however use of this method means that it is impossible to know whether a participant has overestimated themselves, underestimated the average peer, or both.

The indirect method of comparison involves participants rating themselves and the average peer on separate scales and the illusory superiority effect is found by taking the average peer score away from the individual's score (with a higher score indicating a greater effect). While the indirect comparison method is used less often it is more informative in terms of whether participants have overestimated themselves or underestimated the average peer, and can therefore provide more information about the nature of illusory superiority.

Comparison target

The nature of the comparison target is one of the most fundamental moderating factors of the effect of illusory superiority, and there are two main issues relating to the comparison target that need to be considered.

First, research into illusory superiority is distinct in terms of the comparison target because an individual compares themselves with a hypothetical average peer rather than a tangible person. Alicke et al. (1995) found that the effect of illusory superiority was still present but was significantly reduced when participants compared themselves with real people (also participants in the experiment, who were seated in the same room), as opposed to when participants compared themselves with an average peer. This suggests that research into illusory superiority may itself be biasing results and finding a greater effect than would actually occur in real life.

Further research into the differences between comparison targets involved four conditions where participants were at varying proximity to an interview with the comparison target: watching live in the same room; watching on tape; reading a written transcript; or making self-other comparisons with an average peer. It was found that when the participant was further removed from the interview situation (in the tape observation and transcript conditions) the effect of illusory superiority was found to be greater. Researchers asserted that these findings suggest that the effect of illusory superiority is reduced by two main factors—individuation of the target and live contact with the target.

Second, Alicke et al.'s (1995) studies investigated whether the negative connotations to the word "average" may have an effect on the extent to which individuals exhibit illusory superiority, namely whether the use of the word "average" increases illusory superiority. Participants were asked to evaluate themselves, the average peer and a person whom they had sat next to in the previous experiment, on various dimensions. It was found that they placed themselves highest, followed by the real person, followed by the average peer, however the average peer was consistently placed above the mean point on the scale, suggesting that the word "average" did not have a negative effect on the participant's view of the average peer.

Controllability

An important moderating factor of the effect of illusory superiority is the extent to which an individual believes they are able to control and change their position on the dimension concerned. According to Alicke & Govorun positive characteristics that an individual believes are within their control are more self-serving, and negative characteristics that are seen as uncontrollable are less detrimental to self-enhancement. This theory was supported by Alicke's (1985) research, which found that individuals rated themselves as higher than an average peer on positive controllable traits and lower than an average peer on negative uncontrollable traits. The idea, suggested by these findings, that individuals believe that they are responsible for their success and some other factor is responsible for their failure is known as the self-serving bias.

Individual differences of judge

Personality characteristics vary widely between people and have been found to moderate the effects of illusory superiority, one of the main examples of this is self-esteem. Brown (1986) found that in self-evaluations of positive characteristics participants with higher self-esteem showed greater illusory superiority bias than participants with lower self-esteem. Additionally, another study found that participants pre-classified as having high self-esteem tended to interpret ambiguous traits in a self-serving way, whereas participants pre-classified as having low self-esteem did not do this.

Relation to mental health

Main article: Depressive realism

Psychology has traditionally assumed that generally accurate self-perceptions are essential to good mental health. This was challenged by a 1988 paper by Taylor and Brown, who argued that mentally healthy individuals typically manifest three cognitive illusions—illusory superiority, illusion of control, and optimism bias. This idea rapidly became very influential, with some authorities concluding that it would be therapeutic to deliberately induce these biases. Since then, further research has both undermined that conclusion and offered new evidence associating illusory superiority with negative effects on the individual.

One line of argument was that in the Taylor and Brown paper, the classification of people as mentally healthy or unhealthy was based on self-reports rather than objective criteria. People prone to self-enhancement would exaggerate how well-adjusted they are. One study claimed that "mentally normal" groups were contaminated by "defensive deniers", who are the most subject to positive illusions. A longitudinal study found that self-enhancement biases were associated with poor social skills and psychological maladjustment. In a separate experiment where videotaped conversations between men and women were rated by independent observers, self-enhancing individuals were more likely to show socially problematic behaviors such as hostility or irritability. A 2007 study found that self-enhancement biases were associated with psychological benefits (such as subjective well-being) but also inter- and intra-personal costs (such as anti-social behavior).

Worse-than-average effect

Main article: Worse-than-average effect

In contrast to what is commonly believed, research has found that better-than-average effects are not universal. In fact, much recent research has found the opposite effect in many tasks, especially if they were more difficult.

Self-esteem

Main article: Self-esteem

Illusory superiority's relationship with self-esteem is uncertain. The theory that those with high self-esteem maintain this high level by rating themselves highly is not without merit—studies involving non-depressed college students found that they thought they had more control over positive outcomes compared to their peers, even when controlling for performance. Non-depressed students also actively rate peers below themselves as opposed to rating themselves higher. Students were able to recall a great deal more negative personality traits about others than about themselves.

In these studies there was no distinction made between people with legitimate and illegitimate high self-esteem, as other studies have found that absence of positive illusions mainly coexist with high self-esteem and that determined individuals bent on growth and learning are less prone to these illusions. Thus it may be that while illusory superiority is associated with undeserved high self-esteem, people with legitimate high self-esteem do not necessarily exhibit it.

Optimism bias

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Optimism_bias 

Optimism bias (or the 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.

Optimism bias is common and transcends gender, ethnicity, nationality, and age. Optimistic biases are even reported in animals such as rats and birds. However, autistic people are less susceptible to optimistic biases.

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. 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, 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, or traders who think they are less exposed to potential losses in the markets.

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). 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.

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. 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). Problems can occur when trying to measure absolute risk because it is extremely difficult to determine the actual risk statistic for a person. Therefore, the optimistic bias is primarily measured in comparative risk forms, where people compare themselves against others, through direct and indirect comparisons. 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.

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. 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. Likewise, difficulties can arise in measurement procedures, as it is difficult to determine when someone is being optimistic, realistic, or pessimistic. Research suggests that the bias comes from an overestimate of group risks rather than underestimating one's own risk.

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.

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.

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. 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. 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. 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. Individuals generally chose a specific friend based on whether they resemble a given example, rather than just an average friend. 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.

Interpersonal distance

Perceived risk differences occur depending on how far or close a compared target is to an individual making a risk estimate. 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. There is support for perceived social distance in determining the optimistic bias. 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. 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.

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.

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. 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. People can control their anxiety and other negative emotions if they believe they are better off than others. People tend to focus on finding information that supports what they want to see happen, rather than what will happen to them. 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.

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. However, 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. Studies also suggest that individuals who present themselves in a pessimistic and more negative light are generally less accepted by the rest of society. 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. For example, people are more likely to think that they will not be harmed in a car accident if they are driving the vehicle. 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. Studies have suggested that the greater perceived control someone has, the greater their optimistic bias. Stemming from this, control is a stronger factor when it comes to personal risk assessments, but not when assessing others.

A meta-analysis reviewing the relationship between the optimistic bias and perceived control found that a number of moderators contribute to this relationship. 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. 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. The optimistic bias is strongest in situations where an individual needs to rely heavily on direct action and responsibility of situations.

An opposite factor of perceived control is that of prior experience. 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. Prior experience suggests that events may be less controllable than previously believed.

Information about self versus target

Individuals know a lot more about themselves than they do about others. 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.

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. However, 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.

Egocentric thinking

Main article: Egotism

"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. 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.

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.

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.
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. However, it is likely that many other smokers are doing the same things and taking those same precautions.

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. Sad moods reflect greater memories of negative events, which lead to more negative judgments, while positive moods promote happy memories and more positive feelings. This suggests that overall negative moods, including depression, result in increased personal risk estimates but less optimistic bias overall. Anxiety also leads to less optimistic bias, continuing to suggest that overall positive experiences and positive attitudes lead to more optimistic bias in events.

Health consequences

In health, the optimistic bias tends to prevent individuals from taking on preventative measures for good health. 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. 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.

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. While adolescents are aware of the risk, this awareness does not change behavior habits. Adolescents with strong positive optimistic bias toward risky behaviors had an overall increase in the optimistic bias with age.

However, 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. 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. 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.

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. There is a growing body of evidence proving that optimism bias represents one of the biggest single causes of risk for megaproject overspend.

Valence effect

Valence effect is used to allude to the effect of valence on unrealistic optimism. It has been studied by Ron S. Gold and his team since 2003. 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, 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. 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.

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. However, research has suggested that it cannot be reduced, and that efforts to reduce it tend to lead to even more optimistically biased results. 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. Other studies have tried to reduce the bias through reducing distance, but overall it still remains.

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. Additionally, actually experiencing an event leads to a decrease in the optimistic bias. 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. Optimism may occur from either a distortion of personal estimates, representing personal optimism, or a distortion for others, representing personal pessimism.

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. Surveys of smokers have found that their ratings of their risk of heart disease showed a small but significant pessimism bias; however, the literature as a whole is inconclusive.

Medical education in the United States

From Wikipedia, the free encyclopedia

The Jackson Memorial Hospital (MJMH) complex in Miami, Florida, which serves as the primary teaching hospital for the Leonard M. Miller School of Medicine ((UMMSM) within the University of Miami (UM), is pictured in July 2010.

Medical education in the United States includes educational activities involved in the education and training of physicians in the country, with the overall process going from entry-level training efforts through to the continuing education of qualified specialists in the context of American colleges and universities.

A typical outline of the medical education pathway is presented below. However, medicine is a diverse profession with many options available. For example, some physicians work in pharmaceutical research, occupational medicine (within a company), public health medicine (working for the general health of a population in an area), or even join the armed forces in America.

Issues in higher education in the U.S. have particular resonance in this context, with multiple analysts expressing concern of a physician shortage in the nation. 'Medical deserts' have also been a topic of concern.

Medical school

Main article: Medical school in the United States

In the U.S., a medical school is an institution with the purpose of educating medical students in the field of medicine. Admission into medical school may not technically require completion of a previous degree; however, applicants are usually required to complete at least 3 years of "pre-med" courses at the university level because in the US medical degrees are classified as Second entry degrees. Once enrolled in a medical school the four years progressive study is divided into two roughly equal components: pre-clinical (consisting of didactic courses in the basic sciences) and clinical (clerkships consisting of rotations through different wards of a teaching hospital). The degree granted at the conclusion of these four years of study is Doctor of Medicine (M.D.) or Doctor of Osteopathic Medicine (D.O.) depending on the medical school; both degrees allow the holder to practice medicine after completing an accredited residency program.

Further information: Comparison of MD and DO in the United States

Internship

Main article: Internship (medicine)

During the last year of graduate medical education, students apply for postgraduate residencies in their chosen field of specialization. These vary in competitiveness depending upon the desirability of the specialty, prestige of the program, and the number of applicants relative to the number of available positions. All but a few positions are granted via a national computer match which pairs an applicant's preference with the programs' preference for applicants.

Historically, post-graduate medical education began with a free-standing, one-year internship. Completion of this year continues to be the minimum training requirement for obtaining a general license to practice medicine in most states. However, because of the gradual lengthening of post-graduate medical education, and the decline of its use as the terminal stage in training, most new physicians complete the internship requirement as their first year of residency.

Not withstanding the trend toward internships integrated into categorical residencies, the one-year "traditional rotating internship" (sometimes called a "transitional year") continues to exist. Some residency training programs, such as in neurology and ophthalmology, do not include an internship year and begin after completion of an internship or transitional year. Some use it to re-apply to programs into which they were not accepted, while others use it as a year to decide upon a specialty. In addition, osteopathic physicians "are required to have completed an American Osteopathic Association (AOA)-approved first year of training in order to be licensed in Florida, Michigan, Oklahoma and Pennsylvania."

Residency

Main article: Residency (medicine)

Each of the specialties in medicine has established its own curriculum, which defines the length and content of residency training necessary to practice in that specialty. Programs range from 3 years after medical school for internal medicine and pediatrics, to 5 years for general surgery, to 7 years for neurosurgery. Each specialty training program either incorporates an internship year to satisfy the requirements of state licensure, or stipulates that an internship year be completed before starting the program at the second post-graduate year (PGY-2).

Fellowship

Main article: Fellowship (medicine)

A fellowship is a formal, full-time training program that focuses on a particular area within the specialty, with requirements beyond the related residency. Many highly specialized fields require formal training beyond residency. Examples of these include cardiology, endocrinology, oncology after internal medicine; cardiothoracic anesthesiology after anesthesiology; cardiothoracic surgery, pediatric surgery, surgical oncology after general surgery; reproductive endocrinology/infertility, maternal-fetal medicine, gynecologic oncology after obstetrics/gynecology. There are many others for each field of study. In some specialties such as pathology and radiology, a majority of graduating residents go on to further their training. The training programs for these fields are known as fellowships and their participants are fellows, to denote that they already have completed a residency and are board eligible or board certified in their basic specialty. Fellowships range in length from one to three years and are granted by application to the individual program or sub-specialty organizing board. Fellowships often contain a research component.

Board certification

Main article: Board certification

The physician or surgeon who has completed their residency and possibly fellowship training and is in the practice of their specialty is known as an attending physician. Physicians then must pass written and oral exams in their specialty in order to become board certified. Each of the 26 medical specialties has different requirements for practitioners to undertake continuing medical education activities.

Continuing Medical Education

Main article: Continuing medical education

Continuing medical education (CME) refers to educational activities designed for practicing physicians. Many states require physicians to earn a certain amount of CME credit in order to maintain their licenses.  Physicians can receive CME credit from a variety of activities, including attending live events, publishing peer-reviewed articles, and completing online courses. The Accreditation Council for Continuing Medical Education (ACCME) determines what activities are eligible for CME.

Physicians in the United States

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Physicians_in_the_United_States 

U.S. physicians per 10,000 people, 1850-2009

Physicians are an important part of health care in the United States. The vast majority of physicians in the US have a Doctor of Medicine (MD) degree, though some have a Doctor of Osteopathic Medicine (DO), Doctor of Podiatric Medicine (DPM), or Bachelor of Medicine, Bachelor of Surgery (MBBS).

The American College of Physicians, uses the term physician to describe specialists in internal medicine, while the American Medical Association uses the term physician to describe members of all specialties.

Trends related to a physician shortage in the U.S. have generated discussion by the American news media in publications such as Forbes, The Nation, and Newsweek.

Working conditions

Doctors may work independently, as part of a larger group practice, or for a hospital or healthcare organization. Independent practices are defined as one in which the physician owns a majority of his or her practice and has decision making rights. In 2000, 57% of doctors were independent, but this decreased to 33% by 2016. Between 2012 and 2015, there was a 50% increase in the number of physicians employed by hospitals. 26 percent have opted out of seeing patients with Medicaid and 15 percent have opted out of seeing patients with health insurance exchange plans.

On average, physicians in the US work 55 hours each week and earn a salary of $270,000, although work hours and compensation vary by specialty. 25% of physicians work more than 60 hours per week.

Demographics

While an impending "doctor shortage" has been reported, from 2010 to 2018, the actively licensed U.S. physician-to-population ratio increased from 277 to 301 physicians per 100,000 people. Additionally, the number of female physicians, and osteopathic and Caribbean graduates have increased at a greater percentage.

As of 2018, there were over 985,000 practicing physicians in the United States. 90.6% have an MD degree, and 76% were educated in the United States. 64% were male. 82% were licensed in a medical specialty. 22% held active licenses in two or more states. The percentage of females skews younger. In 2018, 33% of female physicians were under 40 years old, compared with 19% of male physicians. The District of Columbia has, by far, the largest number of physicians as a percentage of the population, with 1,639 per 100,000 people. Additionally, Among active physicians, 56.2% identified as White, 17.1% identified as Asian, 5.8% identified as Hispanic, 5.0% identified as Black, and 0.3% identified as American Indian/Alaska Native.

Specialists

The term, hospitalist, was introduced in 1996, to describe US specialists in internal medicine who work largely or exclusively in hospitals. Such 'hospitalists' now make up about 19% of all US general internists.

There are three agencies or organizations in the United States which collectively oversee physician board certification of medical and osteopathic physicians in the United States in the 26 approved medical specialties recognized in the country. These organizations are the American Board of Medical Specialties and the American Medical Association; the American Osteopathic Association Bureau of Osteopathic Specialists and the American Osteopathic Association; the American Board of Physician Specialties and the American Association of Physician Specialists. Each of these agencies and their associated national medical organization functions as its various specialty academies, colleges, and societies.

All boards of certification now require that medical practitioners demonstrate, by examination, continuing mastery of the core knowledge and skills for a chosen specialty. Recertification varies by particular specialty between every eight and ten years.

Salaries

Pay gap by gender and race

The average salary for white male physicians was $253,000 compared with $188,230 for black male physicians, $163,000 for white female physicians, and $153,000 for black female physicians.

Medscape's 2019 Physician Compensation Report found that "males out-earned their female counterparts in both primary care and specialist positions with men earning 25% and 33% more, respectively."

The AMA has advocated to reduce gender bias and close the pay gap. The AMA said that “significant sex differences in salary exist even after accounting for age, experience, specialty, faculty rank, and measures of research productivity and clinical revenue.” A 2015 study of gender pay disparities among hospitalists found that women were more likely to be working night shifts despite having lower salaries. In 2018, the AMA delegates advocated for transparency in defining the criteria for initial and subsequent physician compensation, that pay structures be based on objective, gender-neutral objective criteria, and that institutes take a specified approach using metrics for all employees to identify gender disparity.

The AMA has also advocated to move USMLE Step 1 to pass/fail to decrease racial bias. A 2020 study showed lack of diversity within specialities and that that underrepresented students were more likely to go into specialities that have lower Step 1 cut offs like Primary Care.

Pay cuts due to COVID

One in five physicians reported having a pay cut during the COVID-19 pandemic. The majority of the monetary loss was a result of low volume of patients and lack of elective surgeries.

Compared to foreign countries

The United States has the highest paid general practitioners in the world. The US has the second-highest paid specialists in the world behind the Netherlands. Public and private payers pay higher fees to US primary care physicians for office visits (overall 27 percent more for public and 70 percent more for private) than in Australia, Canada, France, Germany and the United Kingdom. US primary care physicians also earn more (overall earning $186,000 yearly) than the foreign counterparts, with even higher numbers for physician compensation for medical specialists. Higher fees, rather than factors such as higher practice costs, volume of services, or tuition expenses, mainly drive higher US spending.

Variations within the US

For specialty-specific salaries, see Specialty (medicine).

A 2011 survey of 15,000 physicians practicing in the United States reported that, across all specialties, male physicians earned approximately 41% more than female physicians. Also, female physicians were more likely to report working fewer hours than their male counterparts.

The same survey reported that, the highest-earning physicians were located in North Central region, comprising Kansas, Nebraska, North and South Dakota, Iowa, and Missouri, with a median salary of $225,000 per year, as per 2010. The next highest earning physicians were those in the South Central region, comprising Texas, Oklahoma, and Arkansas, at $216,000. Those physicians reporting the lowest compensation levels were located in the Northeast and Southwest, earning an across-specialty median annual income of $190,000.

The survey concluded that physicians in small cities (50,000–100,000) earned slightly more than those living in community types of other sizes, ranging from metropolitan to rural, but the differences were only marginal (a few percent more or less).

Other results from the survey were that those running a solo practice earned marginally less than private practice employees, who, in turn, earned marginally less than hospital employees.

The Bureau of Labor Statistics reports mean annual income for physicians at $251,990, and mean annual income for surgeons at $337,980, as of 2022.

Medical education

The US medical education for physicians includes participation in a US medical school that eventually grants a US form of Doctor of Medicine (M.D.) degree^[28] or a Doctor of Osteopathic Medicine degree. During the process of medical school, physicians who wish to practice in the U.S. must take standardized exams, such as the United States Medical Licensing Examination steps 1, 2 and 3 or Comprehensive Osteopathic Medical Licensing Examination Level 1, 2, and 3.

In addition, the completion of a residency is required to practice independently. Residency is accredited by the ACGME and is the same regardless of degree type. After residency, physicians can become board certified by their specialty board. Physicians must have a medical license to practice in any state.