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The halo effect (sometimes called the halo error)—a term coined by Edward Thorndike—is the tendency for positive impressions of a person, company, country, brand, or product in one area to positively influence one's opinion or feelings of a person, company, country, brand, or product in another area.[1][2] It is "the name given to the phenomenon whereby evaluators tend to be influenced by their previous judgments of performance or personality;"[3] in other words, a cognitive bias that can prevent people from forming an image based on the sum of all objective circumstances at hand.

A simplified example of the halo effect could be when people, after noticing that an individual in a photograph is attractive, well groomed, and properly attired, then assumes—using a mental heuristic based on the rules of their own social concept—that the person in the photograph is a good person.[4][5][6] This constant error in judgment is reflective of the evaluators' preferences, prejudices, ideology, aspirations, and social perception.[7][6][8][9][10]

Context and applications

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Psychology

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The term halo effect is used in psychology to describe a perception distortion that affects the way people interpret the information about others with whom they have formed a positive gestalt.[11] For example, they find out that someone with whom they have formed a positive gestalt has cheated on his taxes; but because of the positive gestalt, they may dismiss the significance of this behavior or even think the person simply made a mistake. The halo effect refers to the tendency to evaluate an individual positively on many traits because of a shared belief.[12]

It is a type of immediate judgment discrepancy, or cognitive bias, in which a person making an initial assessment of another person, place, or thing will assume ambiguous information based on concrete information.[13][14]: p. xi [7] The halo effect is an evaluation by an individual and can affect the perception of a decision, action, idea, business, person, group, entity, or other whenever concrete data is generalized or influences ambiguous information.[13][14]: 11 [9][15]

The halo effect can also be explained as the behavior (usually unconscious) of using evaluations based on unrelated criteria to make judgments about something or someone. The halo effect is sometimes used to refer specifically to when this behavior has a positive correlation, such as viewing someone who is attractive as likely to be successful and popular. When this judgment has a negative connotation, however, such as when someone unattractive is more readily blamed for a crime than someone attractive, it is sometimes referred to as the horn effect.[16]

Marketing

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The term halo effect is used in marketing to explain consumer bias toward certain products because of favorable experience with other products made by the same company.[17] It is used in the part of brand marketing called "line extensions." One common halo effect is when the perceived positive features of a particular item extend to a broader brand. A notable example is the manner in which the popularity of Apple's iPod generated enthusiasm for the corporation's other products.[18][19] Advertising often makes use of television shows, movies and those who star in them, to promote products via the halo effect.[20][21]

In the automotive industry, exotic, limited-production luxury models or low-volume sports cars made by a manufacturer's racing, motorsports, or in-house modification teams, are sometimes referred to as "halo cars" for the effect they are intended to produce on selling other vehicles within the make.[22] To contrast this with the automotive terminology "flagship model," see Flagship car.

In the wine industry, certain wine features create a halo effect that can influence the customer's opinion of a given wine. The inclusion of the category "organic" on the label of a wine can increase the consumer's positive valuation of the wine. Organic wines are conceived of as being healthy, having a better taste, scent, and color, and resulting in a higher degree of overall satisfaction.[23] Another example of the halo effect in the wine industry is the association of traditional corks with wine quality: corked bottles are systematically rated as of higher quality than bottles that use screw caps and plastic caps since the latter are viewed as signifiers of low-quality wines.[24]

Advertising in one channel has been shown to have a halo effect on advertising in another channel.[25][26]

A halo effect with regard to health, dubbed a "health halo," is used in food marketing to increase sales of a product; it can result in increased consumption of the product in the halo, which may be unhealthy.[27][28]

The term "halo effect" has also been applied to human rights organizations that have used their status to move away from their stated goals. Political scientist Gerald Steinberg has claimed that non-governmental organizations (NGOs) take advantage of the halo effect and are "given the status of impartial moral watchdogs" by governments and the news media.[29][30]

The Ronald McDonald House, a widely known NGO, openly celebrates the positive outcomes it receives from the halo effect. The web page for the Ronald McDonald House in Durham, North Carolina, states that 95% of survey participants were aware of Ronald McDonald House Charities. This awareness is attributed to the halo effect, as employees, customers, and stakeholders are more likely to be involved in a charity that they recognize and trust, with a name and logo that are familiar.[31]

A brand's halo effect can protect its reputation in the event of a crisis. An event that is detrimental to a brand that is viewed favorably would not be as threatening or damaging to a brand that consumers view unfavorably.[32][33]

Other uses

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Non-psychology/business use of the term "halo effect" describes the monetary value of the spillover effect[a] when an organization's marketing budget is subsequently reduced.[b] This was first demonstrated to students via the 1966 version of a textbook and a software package named "The Marketing Game."[c]

The halo effect can also be used in the case of institutions, as one's favorable perceptions regarding an aspect of an organization could determine a positive view of its entire operations.[34] For example, if a hospital is known for its excellent open heart and cardiac program, then the community would expect it to excel in other areas as well. This can also be demonstrated in the positive perceptions of financial institutions that gained favorable coverage in the media due to meteoric growth but eventually failed afterward.[35]

The term "halo effect" is also used in metal detecting [36] to denote the enhanced ability of a metal item or coin to be detectable when it has been left undisturbed for some period of time in wet soil. The object can leach some metallic properties into the soil, making it more detectable. The area surrounding the object is called its "halo."

History

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The halo effect was originally identified in 1907 by the American psychologist Frederick L. Wells (1884–1964).[37] However, it was only officially recognized in 1920 with empirical evidence provided by the psychologist Edward Thorndike (1874–1949).[37] Edward Thorndike was the first to say the halo effect is a specific cognitive bias in which one aspect of the person, brand, product, or institution affects one's thoughts or judgment of the entity's other aspects or dimensions.[38] Thorndike, an early behaviorist, was an important contributor to the study of the psychology of learning. He gave the phenomenon its name in his 1920 article "A Constant Error in Psychological Ratings."[4] In "Constant Error," Thorndike set out to replicate the study in hopes of pinning down the bias that he thought was present in these ratings. Subsequent researchers have studied it in relation to attractiveness and its bearing on the judicial and educational systems.[16] Thorndike originally coined the term referring only to people; however, its use has been greatly expanded, especially in the area of brand marketing.[4]

Supporting evidence

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In Thorndike's words, "Ratings were apparently affected by a marked tendency to think of the person in general as rather good or rather inferior and to color the judgments of the qualities by this general feeling."[39] In "A Constant Error in Psychological Ratings," Thorndike asked two commanding officers to evaluate their soldiers in terms of physical qualities (neatness, voice, physique, bearing, and energy), intellect, leadership skills, and personal qualities (including dependability, loyalty, responsibility, selflessness, and cooperation).[4] In Thorndike's study, attractiveness plays an important role in how people tend to consider a person, such as whether a person is friendly or not based on their physical appearance. His goal was to see how the ratings of one characteristic affected other characteristics.

Thorndike's study showed how there was too great a correlation in the commanding officers' responses. In his review, he stated, "The correlations are too high and too even. For example, for the three raters next studied[,] the average correlation for physique with intelligence is .31; for physique with leadership, .39; and for physique with character, .28."[40] The ratings of one of the special qualities of an officer often started a trend in the rating results. The halo effect is not an indication of the existence of a correlation, but instead indicates that the correlation is too high. Thorndike used the halo effect to describe both a positive and negative halo.

In 2023, a large study of 2748 participants found that the same individuals received significantly higher ratings of intelligence, trustworthiness, sociability and happiness after having applied a beauty filter. It found a correlation of .30 for intelligence, .20 for trustworthiness, .39 for sociability and .39 for happiness. However, the study also found that beautified men received significantly higher scores to their perceived intelligence compared to women.[41]

Cognitive bias

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Cognitive bias is a pattern in perception, interpretation, or judgment that consistently leads to an individual misunderstanding something about themselves or their social environment, leading to poor decision-making or irrational behavior.[42] The halo effect is classified as a cognitive bias because the halo effect is a perception error that distorts the way a person sees someone, and cognitive bias is a perception error that distorts the way that people see themselves.[12]

The term "halo" is used in analogy with the religious concept: a glowing circle crowning the heads of saints in countless medieval and Renaissance paintings, bathing the saint's face in heavenly light. The observer may be subject to overestimating the worth of the observed by the presence of a quality that adds light on the whole, like a halo. In other words, observers tend to bend their judgement according to one patent characteristic of the person (the "halo") or a few of his traits,[43] generalizing toward a judgement of that person's character (e.g., in the literal hagiologic case, "entirely good and worthy").

The effect works in both positive and negative directions (and is hence sometimes called the horns and halo effect). If the observer likes one aspect of something, they will have a positive predisposition toward everything about it. If the observer dislikes one aspect of something, they will have a negative predisposition toward everything about it.[44]

Role of attractiveness

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See also: Physical attractiveness stereotype

A person's attractiveness has also been found to produce a halo effect. Attractiveness contributes to the halo effect because it can be influenced by several specific traits.[45] These perceptions of attractiveness may affect judgments tied to personality traits. Physical attributes contribute to perceptions of attractiveness (e.g., physique, hair, eye color). For example, someone who is perceived as attractive, due in part to physical traits, may be more likely to be perceived as kind or intelligent. The role of attractiveness in producing the halo effect has been illustrated through a number of studies. Recent research, for example, has revealed that attractiveness may affect perceptions tied to life success and personality.[46] In this study, attractiveness was correlated with weight, indicating that attractiveness itself may be influenced by various specific traits. Trustworthiness and friendliness were included in the personality variables.[45] People perceived as being more attractive were more likely to be perceived as trustworthy and friendly. What this suggests is that perceptions of attractiveness may influence a variety of other traits, which supports the concept of the halo effect.

On personality

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People's first impressions of others influence their later decision to either approach or avoid those individuals.[47] When people first encounter someone, the information present about that individual is limited; therefore, people will use the information available to assume other characteristics about that person; for instance, observable behaviors such as eye contact, leaning forward, smiling and positive hand gestures (ex. steepling hands) are linked to positive emotions, while avoiding eye contact, leaning back, avoiding touch, and defensive hand gestures (ex. hands in pockets) or no gestures at all are linked to feelings of detachment.[47] Besides that, another popular example used when referring to the halo effect is the phenomenon called the attractiveness stereotype[6] or when encountering individuals who are similar to others in some aspects, like personality or life history like the school they attended.[48] People tend to assume that physically attractive individuals are more likely to be more healthy, successful, courteous, containing higher moral standards, and greater social competence than other people; on the other hand, the attractiveness stereotype can also carry a negative connotation as some people may think of attractive people as less honest and more conceited than others.[6]

Dion, Berscheid & Walster (1972) conducted a study on the relationship between attractiveness and the halo effect. Sixty students, thirty males and thirty females from the University of Minnesota took part in the experiment. Each subject was given three different photos to examine: one of an attractive individual, one of an individual of average attractiveness, and one of an unattractive individual.[49] The participants judged the photos' subjects along 27 different personality traits (including altruism, conventionality, self-assertiveness, stability, emotionality, trustworthiness, extraversion, kindness, and sexual promiscuity). Participants were then asked to predict the overall happiness the photos' subjects would feel for the rest of their lives, including marital happiness (least likely to get divorced), parental happiness (most likely to be a good parent), social and professional happiness (most likely to experience life fulfillment), and overall happiness. Finally, participants were asked if the subjects would hold a job of high status, medium status, or low status.[49] Results showed that most of the participants overwhelmingly believed more attractive subjects have more socially desirable personality traits than either averagely attractive or unattractive subjects, would lead happier lives in general, have happier marriages, and have more career success, including holding more secure, prestigious jobs. Participants, however, believed that attractive individuals would be worse parents than both averagely-attractive and unattractive individuals.

Academics and intelligence

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A study by Landy & Sigall (1974) demonstrated the Halo Effect, looking at male judgments of female intelligence and competence on academic tasks. Sixty male undergraduate students rated the quality of essays which included both well- and poorly-written samples. One third were presented with a photo of an attractive female as author, another third with that of an unattractive female as author, and the last third were shown neither. On average, most of the participants gave significantly better writing evaluations for the more attractive author. On a scale of 1 to 9, the well-written essay by the attractive author received an average of 6.7 while the unattractive author received a 5.9 (with a 6.6 as a control). The gap was larger on the poor essay: the attractive author received an average of 5.2, the control a 4.7, and the unattractive author a 2.7, suggesting male readers are generally more willing to give physically attractive females the benefit of the doubt when performance is below standard than those not considered attractive.

Research conducted by Moore, Filippou & Perrett (2011) sought residual cues to intelligence in female and male faces while attempting to control for the attractiveness halo effect. Over 300 photographs of Caucasian British college students were rated for perceived intelligence. The photographs that were scored lowest in perceived intelligence were used to create a low-intelligence composite face and those photographs that were scored highest in perceived intelligence were used to create a high-intelligence composite face. Both female and male faces of high- and low-perceived intelligence were created, resulting in four groups of composite faces. Participants for the study were recruited online; 164 female and 92 male heterosexual residents of the UK rated each of the composite faces for intelligence and attractiveness. Of the female composites, attractiveness seemed to be controlled as both the high- and low-perceived intelligence groups were rated as equally attractive. However, of the male face composites, the high-perceived intelligence group was rated as significantly more attractive than the low-perceived intelligence group, suggesting that either the authors could not adequately control for the attractiveness halo effect for the male composite photographs or that intelligence is an integral factor of attractiveness in high-intelligence male faces. The second part of the study found that the composites in the high-perceived intelligence group were rated highest in the factors of friendly and funny as markers of intelligence in both the female and male groups. While intelligence does not seem to be a factor that contributes to attractiveness in women, with regards to men, attractive faces are perceived to be more intelligent, friendly, and funny by women and men.

Political effects

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Officeholders who create what The New York Times called "a living legacy" benefit from a halo effect when their overall accomplishments are subsequently evaluated.[50][d]

Researchers have shown that perceived physical and vocal attractiveness (or their opposite) lead to bias in judgment.[51][52] A 2010 study[53] found that attractiveness and familiarity are strong predictors of decisions regarding who is put in a position of leadership. Judgments made following one-second exposures to side-by-side photos of two US congressional candidates were reasonably predictive of election outcomes. Similar studies (Palmer & Peterson 2012) found that even when taking factual knowledge into account, candidates who were rated as more attractive were still perceived as more knowledgeable. Thus, beauty evaluations also emerge as major predictors of electoral success.[54][55]

The judicial context

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Study results showing the influence of the halo effect in the judicial context exist:

  • Efran (1974) found subjects were more lenient when sentencing attractive individuals than unattractive ones, even though exactly the same crime was committed. The researchers attributed the result to a societal perception that people with a high level of attractiveness are seen as more likely to have successful futures due to corresponding socially desirable traits.
  • Monahan (1941) studied social workers who were accustomed to interacting with a diverse range of people and found that the majority experienced difficulty when asked to consider that a beautiful person was guilty of a crime.
  • A study presented two hypothetical crimes: a burglary and a swindle. The burglary involved a woman illegally obtaining a key and stealing $2,200 (equivalent to $13,000 today); the swindle involved a woman manipulating a man to invest $2,200 in a nonexistent corporation. The results showed that when the offense was not related to attractiveness (as in the burglary) the unattractive defendant was punished more severely than the attractive one. However, when the offense was related to attractiveness (the swindle), the attractive defendant was punished more severely than the unattractive one. The study imputes that the usual leniency given to the attractive woman (as a result of the halo effect) was negated or reversed when the nature of the crime involved her looks.[16]

Gender differences

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Kaplan (1978) found that some women were influenced by the halo effect on attractiveness only when presented with members of the opposite sex. Dermer & Thiel (1975) continued this line of research, going on to demonstrate that jealousy of an attractive individual has a slight effect in evaluation of that person. These works showed these halo effect more prevalent among females than males. Later research by Moore, Filippou & Perrett (2011) was able to control for attractiveness in composite photographs of females who were perceived to be of high or low intelligence, while showing that the attractiveness halo effect was seen in high intelligent male composite faces by heterosexual residents of the UK. Either the halo effect is negated by feelings of jealousy in women[56] or the halo effect is lessened when women are looking at same sex individuals[57] or the attractiveness halo effect can be controlled for in women.[58]

Possible causes

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Rating error effect, mistakes made by raters when they use a rating scale, reflect the task competence of the rater, as well as the rater's sex, social position, race, religion, and age. Researchers showed that halo effect is one component of this error.[39] Fisicaro and Lance introduced three explanatory models.[59] The first model named the general impression model states that global evaluation affects the rating of individual characteristics.[60] The salient dimension model states that how people perceive an individual characteristic affects their evaluation of other characteristics.[59] The inadequate discrimination model refers to the rater's failure to identify different behaviors of the person being evaluated.[60]

The reverse halo effect

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The reverse halo effect occurs when positive evaluations of an individual cause negative consequences. Rater errors pose special problems for the issues of reliability and validity.[39] Furthermore, ratings that differ in time may accurately reflect a change in behavior even though this difference would demonstrate an artificial lack of reliability. A follow-up study with both men and women participants supported this, as well as showing that attractive women were expected to be conceited and have a higher socioeconomic status. Eagly et al. (1991) also commented on this phenomenon, showing that more attractive individuals of both sexes were expected to be higher in vanity and possibly egotistic.[61] Applied instances of the reverse halo effect include negative evaluations of criminals who use their attractiveness to their advantage[16] and rating a philosophical essay lower when written by a young female than an old male.[16][62]

The horn effect

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Main article: Horn effect

A negative form of the halo effect, called the horn effect, the devil effect, or the reverse halo effect, allows a disliked trait or aspect of a person or product to negatively influence overall perception.[38] Psychologists call it a "bias blind spot:"[63] "Individuals believe (that negative) traits are inter-connected."[64] due to a negative first impression.[65][66] The Guardian wrote of the devil effect in relation to Hugo Chavez: "Some leaders can become so demonized that it's impossible to assess their achievements and failures in a balanced way."[67] For those seen in a negative light, anything they do that is negative is exemplified, while the positive things they do are not seen, or are doubted.[16]

Education

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Abikoff et al. (1993) found the halo effect is also present in the classroom. In this study, both regular and special education elementary school teachers watched videotapes of what they believed to be children in regular 4th-grade classrooms. In reality, the children were actors, depicting behaviors present in attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), or standard behavior. The teachers were asked to rate the frequency of hyperactive behaviors observed in the children. Teachers rated hyperactive behaviors accurately for children with ADHD; however, the ratings of hyperactivity were much higher for the children with ODD-like behaviors, showing a horn effect for children who appeared to have ODD.

Foster & Ysseldyke (1976) also found the halo effect present in teachers' evaluations of children. Regular and special education elementary school teachers watched videos of a normal child whom they were told was either "emotionally disturbed," possessing a learning disorder, "mentally retarded," or "normal." The teachers then completed referral forms based on the child's behavior. The results showed that teachers held negative expectancies toward emotionally disturbed children, maintaining these expectancies even when presented with normal behavior. In addition, the "mentally retarded" label showed a greater degree of negative bias than the "emotionally disturbed" or "learning disabled" label.

Observations

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"In the classroom, teachers are subject to the halo effect rating error when evaluating their students. For example, a teacher who sees a well-behaved student might tend to assume this student is also bright, diligent, and engaged before that teacher has objectively evaluated the student's capacity in these areas. When these types of halo effects occur, they can affect students' approval ratings in certain areas of functioning and can even affect students' grades."[68]

"In the work setting, the halo effect is most likely to show up in a supervisor's appraisal of a subordinate's job performance. In fact, the halo effect is probably the most common bias in performance appraisal. Think about what happens when a supervisor evaluates the performance of a subordinate. The supervisor may give prominence to a single characteristic of the employee, such as enthusiasm, and allow the entire evaluation to be colored by how he or she judges the employee on that one characteristic. Even though the employee may lack the requisite knowledge or ability to perform the job successfully, if the employee's work shows enthusiasm, the supervisor may very well give him or her a higher performance rating than is justified by knowledge or ability."[69]

Further research findings

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Murphy, Jako & Anhalt (1993) argue: "Since 1980, there have been a large number of studies dealing directly or indirectly with halo error in rating. Taken together, these studies suggest that all seven of the characteristics that have defined halo error for much of its history are problematic and that the assumptions that underlie some of them are demonstrably wrong." Their work claims that the assumption that the halo effect is always detrimental is incorrect, with some halo effects resulting in an increase in the accuracy of the rating. Additionally, they discuss the idea of "true halo"—the actual correlation between, for example, attractiveness and performance as an instructor—and "illusory halo," which refers to cognitive distortions, errors in observation and judgement, and the rating tendencies of the individual rater. They claim that any true differentiation between true and illusory halos is impossible in a real-world setting, because the different ratings are strongly influenced by the specific behaviors of the person observed by the raters.

A study by Forgas (2011) states that one's mood can affect the degree of the halo effect's influence. When someone is in a favorable mood, the halo effect is more likely to be influential—this was demonstrated by study participants choosing between pictures of an elderly man with a beard and a young woman, and deciding which subject possessed more philosophical attributes. Additionally, when asked to list the happy, neutral, or negative times in their life, the halo effect was more evident in the perceptions of the participants who chose to write about happy prior experiences. Forgas's study suggests that when one is gauging the extent of the halo effect in a situation, one must consider the emotional state of the person making the judgment.

A 2013 report on "the link between disease and leader preferences" claimed that "congressional districts with a higher incidence of disease" were more likely to show a halo effect "on electoral outcomes."[70]

See also

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Notes

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References

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Bibliography

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Further reading

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Revisions and contributorsEdit on WikipediaRead on Wikipedia

Halo effect

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The halo effect is a in which a favorable or unfavorable impression formed from one trait or characteristic of a person, product, or entity extends to influence unrelated judgments, leading to overgeneralized evaluations. First described by in 1920, the phenomenon was identified through his examination of subjective rating scales used by U.S. Army officers to assess subordinates, where ratings on isolated qualities like "" or "" correlated excessively with overall performance scores due to raters' tendency to let a single positive attribute dominate. Empirical research has substantiated the halo effect across psychological domains, with experiments showing that physical attractiveness alone can inflate perceptions of unrelated traits such as , competence, or , often unconsciously altering attribute evaluations even when contradictory is available. In organizational contexts, it manifests prominently in performance appraisals, where evaluators' positive views of an employee's demeanor or one skill erroneously elevate ratings on disparate competencies, contributing to inflated correlations among rating dimensions and reduced appraisal accuracy. The extends to , where a brand's prestige in one area, such as , enhances perceived in unrelated features like , though its remains debated due to challenges distinguishing true inter-trait correlations from rater artifacts. While the halo effect facilitates rapid judgments under uncertainty, it systematically distorts in hiring, , and interpersonal evaluations, with studies indicating that forewarning individuals about the bias does not reliably mitigate its occurrence, underscoring its robustness as a perceptual error rooted in associative rather than deliberate reasoning. The inverse, known as the , applies negative generalizations similarly, amplifying errors in high-stakes assessments where objective criteria are supplanted by holistic impressions. Recent analyses, including investigations during periods of social disruption like the , confirm its generalizability, though its magnitude varies by context and rater expertise.

Definition and Core Concept

Cognitive Bias Framework

The halo effect constitutes a in which an evaluator's global impression, derived from a single prominent trait or attribute, systematically skews judgments of unrelated traits, resulting in inflated correlations among assessments that should remain independent. This distortion manifests as a form of attributional , where perceivers generalize from limited information rather than integrating trait-specific evidence, leading to non-normative in domains like personnel and . Empirical quantification reveals overcorrelations, such as inter-rater reliabilities exceeding expected values due to shared evaluative halos, as observed in early performance ratings where traits like "physique" correlated with "" at r = 0.39 despite conceptual . Within the framework, the halo effect aligns with heuristic-driven processes that favor perceptual efficiency over analytical precision, often operating via intuitive cognition as described in dual-process models. Proximate mechanisms include associative thinking, wherein semantically linked concepts in —facilitated by shared lexical contexts—prompt trait , with recent analyses showing word embedding similarities (e.g., via cosine metrics) accounting for 39% of variance in co-occurrence judgments (r² = 0.19, p < 0.001). Augmented lexical models incorporating word frequency and valence further explain 45% of such variance, suggesting the bias partly reflects linguistic structures in natural language rather than purely perceptual innateness. Cognitive consistency motives reinforce this by minimizing dissonance through harmonious impressions, while evolutionary pressures may underpin trait-signal associations, such as attractiveness proxying health or competence. The framework distinguishes the halo effect from memory-based biases like availability, emphasizing its role in real-time impression formation and online processing. A reverse variant, the horn effect, applies analogous logic to negative generalizations, as evidenced in studies where unattractiveness lowered unrelated trait ratings (e.g., essay quality judgments by male participants). Mitigation strategies within this paradigm involve deliberate trait decoupling and evidence-based checklists, though persistent linguistic embeddings challenge full debiasing. The halo effect is primarily distinguished from the horn effect (also termed the reverse or negative halo effect) by the valence of the influencing impression: the former generalizes a single positive trait—such as physical attractiveness or competence in one skill—to inflate unrelated positive judgments, whereas the latter propagates a single negative trait to unduly diminish evaluations across other domains. For instance, an employee's exceptional sales performance might halo into assumptions of their leadership ability, while a single ethical lapse could horn into doubts about their overall reliability, both yielding overcorrelated trait ratings beyond empirical warrant. This directional difference underscores that halo and horn effects are valence-specific manifestations of the same underlying mechanism of impression spillover, rather than wholly separate biases. Unlike the similar-to-me effect, which biases judgments toward individuals perceived as akin to the evaluator in background, values, or demographics—often yielding favoritism in hiring or appraisals independent of isolated traits—the halo effect stems from a standout attribute of the target itself, without requiring personal resemblance to trigger generalization. Empirical studies in personnel selection highlight this divergence: similar-to-me bias correlates with rater-target overlap (e.g., shared alma mater inflating scores), while halo arises mechanistically from trait overgeneralization, as evidenced by higher inter-trait correlations in ratings lacking similarity cues. The halo effect also differs from confirmation bias, which involves selectively processing subsequent information to affirm preexisting beliefs, rather than an initial trait impression biasing the framework for all trait assessments ab initio. While halo establishes a pervasive positive (or negative) lens at formation—leading to assimilated perceptions of new evidence—confirmation bias emphasizes post-impression filtering, such as overweighting data aligning with the halo-induced view while discounting contradictions. This mechanistic separation is apparent in experimental designs: halo manifests in holistic rating inflation from a prime trait (e.g., attractiveness correlating with perceived intelligence, r ≈ 0.3–0.5 across studies), independent of deliberate evidence-seeking. In contrast to the primacy effect, which weights early-presented information more heavily in sequential judgments regardless of content specificity, halo specifically entails non-sequential trait inference spillover, often persisting even with balanced or later data.

Historical Origins

Early Conceptualization by Thorndike

American psychologist Edward L. Thorndike first articulated the halo effect in his 1920 article "A Constant Error in Psychological Ratings," published in the Journal of Applied Psychology. In this work, Thorndike identified a systematic bias in evaluative judgments, where a rater's overall impression of a subject unduly influences assessments across disparate traits, leading to inflated correlations between supposedly independent qualities. He introduced the term "halo effect" to denote this phenomenon, drawing an analogy to the radiant circle encircling a holy figure that obscures individual details with a unified glow. Thorndike's analysis stemmed from data collected during World War I, involving ratings by superior officers of 137 U.S. Army aviation cadets on approximately 20 traits, including intelligence, physical appearance, leadership ability, loyalty, and dependability. These traits were selected as presumptively distinct, yet the inter-trait correlations in the ratings proved consistently "too high and too even," exceeding levels attributable to true underlying relationships between the attributes. For instance, a favorable rating on one prominent quality, such as bearing or energy, tended to elevate scores on unrelated dimensions like character or intellect, regardless of objective evidence. Thorndike conceptualized the halo effect as a fundamental limitation in human raters' ability to treat individuals as aggregates of separable, independently measurable qualities, instead projecting a holistic affective response onto the entire profile. This "constant error" undermined the reliability of psychological ratings for personnel selection and assessment, as it masked true variability and introduced spurious uniformity. Thorndike emphasized that the bias arises from the rater's failure to differentiate traits analytically, advocating for methodological safeguards like averaged ratings from multiple independent observers to mitigate its distorting influence.

Development Through Mid-20th Century Studies

In the decades following Edward Thorndike's 1920 identification of the halo effect as a rater bias in military performance evaluations, mid-20th-century research shifted toward experimental demonstrations in , particularly impression formation. 's 1946 study involved over 1,000 college students who formed impressions based on trait lists, such as "intelligent, skillful, industrious, warm" versus the same list with "cold" substituted for "warm." Participants rated the hypothetical person on checklists of paired opposites (e.g., generous-ungenerous), revealing that the central trait "warm" produced markedly positive overall impressions—91% selected "generous" and 34% "good-natured"—while "cold" yielded negative ones, with only 8% "generous" and 17% "good-natured." Asch interpreted these results as evidence of structured personality impressions rather than mere averaging, though the disproportionate influence of a single trait aligned with halo-like generalization, where one descriptor colored judgments of unrelated qualities. This work extended Thorndike's findings beyond administrative ratings to cognitive processes in everyday person perception, highlighting central traits' outsized role. Peripheral traits like "polite" versus "blunt" produced smaller shifts, underscoring that not all attributes equally propagate the halo. Concurrently, industrial-organizational psychologists applied halo concepts to civilian performance appraisals, observing persistent overcorrelations among rated dimensions (e.g., leadership ratings inflating intelligence scores) in studies of employee evaluations during the post-World War II era, prompting early efforts to decompose ratings via statistical methods like factor analysis. By the 1950s, halo effect research informed rating scale design in education and personnel selection, with experiments confirming its prevalence—such as superiors' global favorability biasing specific competency assessments—but also revealing moderators like rater training, though mitigation proved challenging due to the bias's perceptual roots. These studies solidified the halo as a robust error in multi-dimensional judgments, influencing psychometric practices amid growing emphasis on reliability in behavioral assessments.

Underlying Mechanisms

Perceptual and Attributional Processes

The halo effect arises in perceptual processes through top-down cognitive mechanisms, where an initial salient trait—such as physical attractiveness—triggers schema activation that assimilates unrelated attributes into a unified positive (or negative) impression, overriding bottom-up detailed analysis. This assimilation reflects automatic, spontaneous impression formation, which favors holistic perceptions over piecemeal evaluation; deliberate, systematic processing, by contrast, mitigates such biases by encouraging trait-specific scrutiny. Experimental evidence demonstrates this dynamic, as positive affective states promote assimilative top-down styles that amplify halo distortions in trait judgments, such as rating philosophers higher on unrelated qualities when primed with favorable moods. Recent linguistic analyses propose an additional perceptual layer, attributing halo biases to learned semantic associations in language rather than innate cognitive universals; for instance, word embedding models like word2vec predict trait co-occurrence ratings with high accuracy (cross-validated r2=0.19r^2 = 0.19 to 0.450.45), suggesting perceivers import correlated connotations from linguistic exposure into person judgments. In empirical tests with 39 participants rating 126 trait pairs, cosine similarity between trait vectors accounted for 39% of variance in perceived co-occurrences, independent of synonymy (mean semantic similarity rated at 40.8/100). These processes underscore how perceptual halo emerges from both experiential priors and environmental cues, distorting objective trait differentiation. Attributional processes in the halo effect involve spillover biases, where a global impression influences causal inferences about behaviors and outcomes, leading to overgeneralized dispositional attributions consistent with the initial valence. For example, physically attractive individuals are attributed more positive internal traits—like success, happiness, and social skills—despite lacking domain-specific evidence, as shown in a 1972 study where participants stereotyped "beautiful" targets as possessing correlated virtues across unrelated life areas. This aligns with broader attributional frameworks, where halo constrains variance in explanations, attributing achievements to inherent qualities in positive cases while discounting inconsistencies, a pattern observed in rater errors since Thorndike's 1920 analysis of military evaluations, where inter-trait correlations exceeded true validities due to generalized impressions. Such mechanisms persist in controlled settings, with automatic processes exacerbating attributional uniformity unless interrupted by critical reflection, as evidenced by negative correlations between critical thinking scores and halo tendencies among 301 human resource managers (r=−0.32r = -0.32, p<0.001p < 0.001).

Evolutionary and Biological Bases

The halo effect is posited to have evolutionary roots in the adaptive need for rapid, heuristic-based person perception in ancestral environments, where quick evaluations of potential mates, allies, or competitors were crucial for survival and reproduction. This bias facilitates efficient social navigation by generalizing from salient cues, such as physical traits, to broader trait inferences, reducing cognitive load in time-sensitive scenarios. Cross-cultural studies demonstrate consistent halo effects for facial and bodily attractiveness, suggesting an innate mechanism shaped by natural selection rather than solely cultural learning. A primary manifestation involves the attractiveness halo, where physically attractive individuals are attributed positive qualities like health, intelligence, and prosociality, potentially because attractiveness serves as a proxy for genetic fitness and reproductive viability. Evolutionary theories, including the good genes hypothesis, propose that features such as facial symmetry, averageness, and bodily proportions (e.g., waist-to-chest ratio) signal underlying health and low parasite load, prompting generalized positive judgments that aided mate selection and intrasexual competition. Empirical evidence indicates these impressions hold some accuracy, particularly at lower attractiveness levels where unattractiveness correlates with poorer health outcomes, though the association weakens for highly attractive individuals. Biological underpinnings include perceptual biases toward symmetry and dominance cues, which are processed rapidly in the brain to infer mate or social value, as evidenced by stronger halo effects for dominant body traits in collectivistic cultures where group dynamics amplify adaptive signaling. These patterns persist across individualistic (e.g., German) and collectivistic (e.g., Japanese) observers, underscoring a universal, likely heritable component over purely environmental influences. However, while adaptive in ancestral contexts, such generalizations can lead to errors in modern settings where traits decouple from fitness indicators.

Influence of Physical Attractiveness

The halo effect involving physical attractiveness is bidirectional: while observers tend to infer positive traits—such as intelligence, kindness, and competence—from mere visual appeal, such as physical attractiveness or a neat appearance, often overriding objective evidence, high-status or wealthy individuals are rated as more attractive due to associations with positive qualities like intelligence and success, amplifying observed differences in attractiveness between social classes. This stereotype, encapsulated in the phrase "what is beautiful is good," was empirically demonstrated in a 1972 experiment by psychologists Karen Dion, Ellen Berscheid, and Elaine Walster, where 60 undergraduate participants rated photographed individuals on 18 personality and life outcome traits; attractive targets received significantly higher scores for social desirability, happiness, success, and moral character, with effect sizes indicating a consistent bias across both male and female judges. Subsequent meta-analyses have quantified the robustness of this effect while highlighting its boundaries. A 1991 review by Alice Eagly, Richard Ashmore, and Mita Makhijani synthesized data from 34 studies involving over 5,000 participants, finding moderate to strong halo effects for attractiveness on perceptions of social competence (r = .43), potency (r = .38), and adjustment (r = .33), though weaker for intellectual competence (r = .20); the bias was more pronounced for female targets and in studies using explicit trait ratings rather than behavioral predictions. These findings underscore that while the halo persists, it is not uniformly potent across all inferred domains, challenging overly generalized claims of attractiveness as a blanket enhancer of perceived virtue. Cross-cultural and contemporary research affirms the effect's persistence amid evolving media landscapes. A 2022 study across eight countries (including the U.S., U.K., India, and Mexico) exposed 11,000+ participants to facial images, revealing consistent halo biases where higher attractiveness ratings correlated with attributions of greater trustworthiness (β = .25–.35), confidence, and competence, with minimal variation by observer culture or target ethnicity. Similarly, a 2024 investigation into AI-enhanced beauty filters on social media profiles showed that filtered images boosted not only attractiveness scores but also inferences of intelligence and trustworthiness by 0.5–1 standard deviation, based on ratings from 300+ U.S. adults, suggesting digital alterations amplify the traditional halo without altering underlying perceptual mechanisms. Such evidence indicates evolutionary roots in rapid heuristic judgments, where facial symmetry and averageness signal health and genetic fitness, though cultural norms can modulate intensity. In applied contexts, the attractiveness halo influences interpersonal and professional evaluations. For instance, a 2020 analysis of U.S. survey data (n=1,200) linked higher self-reported attractiveness to increased likelihood of social joining behaviors, mediated by halo-driven perceptions of agreeableness and extraversion, with coefficients showing a 15–20% uplift in affiliation odds for those rated in the top attractiveness quartile. However, the effect diminishes under scrutiny or when countervailing evidence emerges, as demonstrated in controlled experiments where attractive individuals providing poor performance were still initially overrated but adjusted downward upon behavioral disconfirmation. This underscores the halo's role as an initial perceptual shortcut rather than an immutable bias, with implications for decision-making in hiring, dating, and leadership selection where first impressions dominate.

Domains of Application

Psychology and Interpersonal Judgments

In psychological research on person perception, the leads observers to generalize a single favorable trait—such as physical attractiveness or likability—into overly positive assessments of unrelated characteristics, including intelligence, morality, and competence. This bias arises because individuals seek cognitive consistency in forming impressions, often relying on heuristic shortcuts rather than comprehensive evaluation. Empirical demonstrations consistently show that such generalizations distort interpersonal judgments, with attractive individuals rated higher on prosocial traits like kindness and reliability. A foundational experiment by Dion, Berscheid, and Walster (1972) involved 60 undergraduates rating yearbook photographs of opposite-sex peers on 27 personality and life outcome traits. Physically attractive targets were perceived as more altruistic, happier in relationships, and destined for occupational success, embodying the "what is beautiful is good" stereotype; these patterns held across both male and female judges without significant sex-of-rater interactions. Subsequent replications have affirmed this in diverse samples, where attractiveness correlates with assumed better mental health and social adjustment, though effect sizes vary by cultural context and rater familiarity. In evaluative settings like job interviews, the halo effect amplifies when interviewers form an early positive impression from charisma or appearance, leading to inflated ratings of job-relevant skills such as problem-solving or work ethic. Literature reviews of recruitment decisions indicate that this bias contributes to inconsistent hiring outcomes, as one strong attribute overshadows objective qualifications or weaknesses in others. For example, candidates displaying enthusiasm may receive undue credit for technical proficiency, reducing the validity of assessments; structured interviews with behaviorally anchored scales mitigate this by compartmentalizing traits. Educational interpersonal judgments exhibit similar distortions, as teachers' overall liking for a student—stemming from behavior or prior performance—can bias evaluations of academic ability across subjects. A 2023 experimental study on grading practices found that halo effects generalized positive impressions from one domain (e.g., effort) to unrelated ones (e.g., creativity), inflating scores by up to 10-15% in holistic rubrics; this persists even among trained educators, underscoring the need for domain-specific criteria to counteract it. In peer ratings, likability similarly propagates, with agreeable individuals overrated on leadership potential in group settings.

Marketing and Brand Perception

In marketing, the halo effect describes the cognitive bias whereby a positive overall impression of a brand—stemming from one salient attribute like superior design or reputation—extends to unrelated evaluations, such as perceived product quality, value, or ethical standing, often overriding objective assessments. This spillover can enhance brand equity by creating consistent favorable judgments across diverse consumer metrics, as global affective responses dominate over differentiated attribute scrutiny. Empirical measures of brand halo quantify this as systematic variance in attribute ratings attributable to overall brand sentiment rather than independent evaluations. Cross-national research illustrates the halo's differential impact, with a 2012 study using survey data from competing brands in Argentina, China, Spain, and the United States revealing that halo biases are more pervasive for product quality perceptions than for corporate social responsibility associations, varying by brand and market while strongly correlating with recommendation intentions. In private label contexts, retailer image generates halo effects on consumer attitudes, where familiarity moderates inferences about attribute valence, leading to aggregated positive evaluations that function as a heuristic summary construct. A 2011 analysis confirmed this mechanism, showing halo-driven inferences elevate overall brand attitudes beyond specific evidence. Certified labels provide concrete evidence of halo in product perception, as third-party eco-labels prompt consumers to ascribe inflated sustainability, quality, and price premiums based on source credibility rather than label specifics. A 2021 experiment involving 412 participants evaluating bananas with EU organic and protected geographical indication labels found strong halo effects on these inferences via partial least squares modeling, with credibility mediating judgments; crucially, supplementary informational interventions did not reduce the bias, indicating entrenched heuristic reliance. Such dynamics underscore risks in branding, where overreliance on halo can misalign consumer expectations with actual attributes, particularly in sustainability claims. For brand extensions, halo facilitates vertical line expansions by transferring core brand favorability, though a 2019 empirical study applying central nucleus theory to product range levels demonstrated moderated effects, with stronger halo in narrower assortments where central attributes dominate peripheral perceptions. Celebrity endorsements similarly leverage personal halo to brands, but negative events can erode it through attributional processes, as a 2024 review of consumer responses highlighted amplified spillover via social media and shifting cultural norms toward accountability. These applications highlight halo's utility in building perception yet vulnerability to reversals absent robust attribute differentiation.

Education and Performance Assessments

In educational assessments, the halo effect occurs when teachers generalize a positive or negative impression from one aspect of a student's performance—such as behavior, appearance, or success in a single subject—to ratings across unrelated domains, leading to inflated or deflated scores. An experimental study involving 107 teachers and student teachers demonstrated this bias: participants graded vignettes of student performance in two subjects, with the first vignette varying (strong, average, or weak) and the second fixed at average; grades for the second vignette were significantly biased by the first (p < .01), with large effect sizes (Cohen's d = 5.88 for strong vs. average, d = 4.00 for weak vs. average), though overall explained variance was small (R² = .16). This suggests halo effects distort subject-specific grading but operate with limited magnitude in controlled settings. Experts assigned lower grades overall than novices (p < .05), indicating experience may mitigate but not eliminate the bias. Further evidence from two studies with 45 teachers assessing 379 students' predicted performance on standardized French language tests confirmed homogeneous judgments exceeding actual achievement variability, indicative of halo; in the second study, higher teacher certainty in predictions amplified the effect. In performance-based tasks like speech fluency ratings for 77 English language learners, analytic scales intended to isolate fluency (e.g., speed, pauses) were contaminated by unrelated factors such as lexical complexity and utterance length, as shown via many-facet Rasch analysis and regression, undermining the validity of targeted skill assessments. These distortions can perpetuate inequities, as initial impressions from non-academic traits (e.g., likability) spillover into academic evaluations, though methodological controls like multi-trait multi-method designs reduce but do not fully eradicate the influence. Conversely, in student evaluations of teaching (SET), halo effects arise when overall instructor impressions bias ratings of discrete elements like clarity or fairness; empirical quantification across large datasets reveals contamination between items, yet adjusted models retain some dimensionality, implying SETs provide partial valid signals despite bias. Such effects in bidirectional assessments highlight the need for rater training and structured rubrics to enhance objectivity, as unaddressed halo can skew resource allocation, promotions, and policy decisions in education.

Politics and Leadership Evaluation

The halo effect influences evaluations of political leaders by causing voters and observers to generalize positive impressions from one attribute, such as physical attractiveness or charisma, to unrelated competencies like policy expertise or ethical integrity. Empirical studies demonstrate that physically attractive candidates are perceived as more knowledgeable and persuasive, leading to increased likelihood of being consulted for political advice, independent of their actual expertise. In electoral contexts, this bias manifests as higher vote shares for attractive candidates; analysis of German federal elections from 2005 to 2021 found that greater physical attractiveness correlated with elevated vote percentages, even after controlling for party affiliation, incumbency, and other variables. Voters often extrapolate from limited information, such as a leader's appearance or a single policy stance, to form overly favorable overall judgments, reducing scrutiny of substantive records. This effect is evident in post-coup leadership transitions, where more attractive leaders achieve greater political success, as measured by office retention and policy implementation, due to heightened perceived competence. In health-compromised electorates, the attractiveness halo intensifies, with individuals facing chronic illnesses showing stronger preferences for appealing candidates, potentially amplifying biases in voter turnout dynamics. Beyond elections, the halo effect shapes broader leadership assessments in organizational and political settings, where strong performance in one domain, like economic growth under a leader's tenure, generates a positive aura extending to evaluations of their strategic acumen or personal traits. For corporate leaders, facial features signaling dominance or trustworthiness—often conflated via halo—predict inflated perceptions of firm performance; a study of Fortune 500 CEOs linked such traits to overestimations of financial outcomes by up to 15-20% in investor surveys. These patterns underscore how halo-driven evaluations can distort accountability, as isolated successes obscure failures in governance or decision-making. The halo effect manifests in judicial and legal decision-making when positive impressions from a defendant's physical attractiveness, trustworthiness, or other superficial traits influence perceptions of their character, guilt, or culpability, potentially leading to biased outcomes such as reduced convictions or lighter sentences. Empirical studies have documented this bias across stages of the criminal justice process, including arrests, prosecutions, and sentencing, where attractive individuals are often presumed to possess socially desirable qualities like honesty or low criminal propensity. For instance, a meta-analysis of U.S. criminal cases found that more physically attractive defendants receive more lenient treatment at multiple decision points, with effect sizes indicating a consistent but modest advantage in avoiding conviction or incarceration. Classic experiments simulating jury deliberations, such as those from the 1970s, demonstrated that physically attractive defendants were rated with lower certainty of guilt and recommended for less severe punishments compared to unattractive counterparts, even when case facts remained identical. This pattern extends to real-world sentencing data, where attractiveness correlates with shorter prison terms, as judges and juries extrapolate positive traits (e.g., perceived morality) from appearance alone. However, the effect varies by offense type: attractive defendants may be viewed as less guilty in violent crimes like murder but more culpable in sexual assault cases, reflecting stereotypes that link beauty to promiscuity or deception in interpersonal violations. Recent research tempers earlier findings, suggesting the halo effect's leniency is weaker or context-dependent in modern juror simulations, with attractive defendants sometimes facing heightened scrutiny or no overall benefit due to increased suspicion of ulterior motives. Trustworthiness cues in facial appearance independently amplify the bias, as seen in studies where male defendants rated as trustworthy received lighter penalties for economic crimes, independent of attractiveness. Judicial training and evidence-based reforms aim to mitigate these heuristics, though behavioral analyses in systems like Brazil's highlight persistent halo influences alongside other biases like anchoring in sentencing guidelines.

Variants and Opposing Effects

Reverse Halo Effect

The reverse halo effect, often termed the horn effect or devil effect, refers to a cognitive bias in which a single negative trait or impression of a person, object, or brand generalizes to produce an unduly unfavorable overall assessment, tainting perceptions of unrelated attributes. This phenomenon mirrors the halo effect but operates in the opposite direction, where negativity bias amplifies the impact of one flaw, leading evaluators to infer deficiencies across multiple dimensions despite evidence to the contrary. For instance, in interpersonal judgments, an observer might dismiss a candidate's qualifications entirely due to a minor ethical lapse, assuming incompetence or unreliability in unrelated skills. Empirical demonstrations of the reverse halo effect appear in controlled experiments on impression formation and decision-making. In a 1975 study by Sigall and Ostrove, mock jurors rated sentences for attractive versus unattractive defendants; while attractive individuals received leniency for non-utilizing crimes like burglary, they faced harsher penalties for swindling, where physical appeal was exploited, illustrating how a positive trait (attractiveness) can trigger a compensatory negative generalization when contextually incongruent. Similarly, Forgas's experiments with 246 participants induced negative moods via recall tasks, resulting in lower ratings of an essay's quality when associated with an attractive author image, reversing typical attractiveness-based leniency and showing mood as a modulator of negative spillover. These findings underscore the effect's sensitivity to contextual cues, where isolated negatives propagate via associative reasoning rather than deliberate analysis. In applied domains, the reverse halo effect manifests in hiring and performance evaluations, where one poor metric can skew holistic appraisals. A systematic review of 17 studies identified the horn effect in recruitment, with unfavorable applicant markers (e.g., a single weak interview response) adversely biasing overall hireability judgments, particularly in teacher assessments where six studies noted grading leniency's inverse: punitive scoring across subjects due to one failure. Consumer research echoes this, as in hotel attribute evaluations where negative ratings of specific features (e.g., cleanliness) diminished unrelated perceptions like location desirability, confirming the effect's role in asymmetric information processing favoring negativity. Such patterns align with evolutionary priors for rapid threat detection, though they introduce errors in nuanced evaluations by prioritizing single data points over comprehensive evidence.

Horn Effect

The horn effect, also known as the reverse halo effect or devil effect, refers to a cognitive bias wherein a single negative trait, behavior, or impression of an individual, brand, or entity leads to an overly generalized negative evaluation of their other attributes or overall character. This bias operates as the inverse of the halo effect, where positive traits inflate perceptions across unrelated dimensions; in contrast, the horn effect causes one perceived flaw—such as unprofessional attire or a curt demeanor—to taint assessments of unrelated qualities like competence, reliability, or intelligence. Originating from early 20th-century psychological observations on impression formation, the term gained prominence in human resource and organizational psychology for its role in distorting subjective judgments. In performance appraisals and employee evaluations, the horn effect manifests when evaluators overemphasize a single deficiency, such as low productivity in one task, to downgrade ratings across multiple competencies like teamwork or creativity, even absent supporting evidence. A 2023 systematic literature review of biases in organizational contexts identified the horn effect as a persistent issue in rating scales, where it contributes to rater errors by amplifying confirmation bias—raters selectively interpret subsequent data to align with the initial negative cue. Empirical studies in recruitment simulations have shown that candidates exhibiting minor negative signals, like inconsistent eye contact during interviews, receive lower overall scores on skills assessments, with effect sizes comparable to those in halo scenarios but skewed downward. This bias is exacerbated in high-stakes judgments, such as judicial sentencing, where a defendant's physical unattractiveness or prior minor infraction correlates with harsher penalties unrelated to the case merits. The horn effect extends to consumer and brand perceptions, where a single product failure—e.g., a defective item from a company—erodes trust in the entire portfolio, as demonstrated in marketing experiments where negative attribute priming reduced willingness to purchase unrelated goods by up to 25%. Unlike the halo effect, which can foster undue optimism, the horn effect promotes undue pessimism and risk aversion, often rooted in evolutionary heuristics for quick threat detection but maladaptive in modern, multifaceted evaluations. Mitigation strategies, including structured rating rubrics and multi-rater feedback, have been shown to reduce its incidence in controlled studies, though it persists in unstructured or time-pressured settings due to cognitive load.

Empirical Evidence

Classic Supporting Experiments

Edward Thorndike first identified the halo effect in a 1920 study involving ratings of 137 military officers by their superiors and subordinates on traits such as intelligence, physique, leadership, and character. The analysis revealed unexpectedly high intercorrelations among these ostensibly independent traits (e.g., correlations exceeding 0.7 in many cases), indicating that a general impression biased specific evaluations rather than independent assessments. Thorndike attributed this "constant error" to the tendency for raters to allow an overall favorable or unfavorable view to influence all ratings, coining the term "halo effect" to describe the phenomenon. In 1972, Karen Dion, Ellen Berscheid, and Elaine Walster examined the halo effect through physical attractiveness in an experiment with 120 undergraduate students who rated stimulus persons depicted in photographs on 18 personality and social traits. Participants assumed attractive individuals possessed more desirable traits, such as altruism, happiness, and occupational success, compared to unattractive ones, with effect sizes showing consistent stereotyping (e.g., attractive targets rated higher on 17 of 18 traits). This "what is beautiful is good" bias demonstrated how a single positive attribute like appearance generates a halo influencing unrelated judgments, supporting the effect's operation beyond professional ratings. Richard Nisbett and Timothy Wilson provided further evidence in a 1977 study where 60 female undergraduates evaluated a guest lecturer's attributes after viewing identical lectures, manipulated only by the lecturer's attire to imply socioeconomic status. Despite similar content, the "higher-status" version led to more positive trait ratings (e.g., knowledgeableness rated 6.3 vs. 4.9 on a 9-point scale), even though participants denied awareness of the manipulation's influence. This unconscious alteration of specific judgments by a global impression underscored the halo effect's automatic nature and resistance to self-awareness.

Cross-Cultural and Longitudinal Findings

Cross-cultural investigations reveal the halo effect's broad generalizability, particularly in attractiveness-based judgments, with consistent positive associations across diverse populations. A study aggregating ratings from 11,570 participants across 45 countries in 11 world regions (including , , , and the ) demonstrated that more attractive male and female faces were rated higher on intelligence, trustworthiness, confidence, emotional stability, and conscientiousness, with effect sizes indicating a robust halo irrespective of regional differences. Similarly, in a controlled comparison of 123 German and 100 Japanese observers rating European male faces and bodies, both groups exhibited strong halo effects linking facial attractiveness to perceived health (r = 0.60–0.62) and prosociality (r = 0.53–0.60), with no significant cultural divergences for facial traits; body attractiveness correlated similarly with health (r = 0.90–0.94) and physical dominance (r = 0.30–0.44) in both samples. Nuances in halo strength emerge between cultural groups. Japanese observers displayed a markedly stronger body attractiveness–prosociality halo (r = 0.70) than Germans (r = 0.17; z = 6.00, p < 0.001), suggesting East Asian cultural emphases may amplify certain trait inferences from physical form. In aesthetic–trustworthiness judgments, Asian participants (n = 145, primarily from Singapore) showed a stronger halo effect (higher correlation) than Caucasians (n = 235, from North America and Europe; p = 9.68 × 10⁻³⁹), while overall patterns held across ethnicities and face types (adults vs. children), with stronger effects for adult faces (r = 0.53) than children's (r = 0.47; p = 0.00194). Longitudinal evidence, though sparser, supports the halo effect's temporal stability over short-to-medium terms. Analysis of face perception data collected from August 2019 to April 2020 (pre- and post- onset) across Asian and Caucasian samples found the aesthetic–trustworthiness halo persisted without significant attenuation, even as absolute trustworthiness ratings for adult faces declined after February 2020 pandemic news; aesthetic pleasantness ratings remained unaffected, underscoring the bias's resilience amid external stressors. In consumer contexts, a longitudinal model tracking predispositions toward tourism destinations revealed that initial overall impressions continued to bias specific attribute evaluations (e.g., service quality inferred from destination appeal) over repeated assessments, with the halo mechanism evident in persistent positive spillover from predisposed favorability. These findings imply the effect's endurance, but longer-term studies (spanning years) are limited, potentially due to methodological challenges in isolating halo from evolving trait perceptions.

Criticisms and Limitations

Methodological Challenges in Measurement

One primary methodological challenge in measuring the halo effect lies in distinguishing spurious correlations induced by overall impressions from genuine covariation between traits or attributes. Researchers often assess halo through elevated correlations among ratings of ostensibly independent dimensions, but this approach struggles to isolate bias when traits are naturally linked, such as conscientiousness influencing both organization and reliability in performance appraisals. For instance, in student evaluations of teaching, high intercorrelations may reflect actual instructional quality rather than rater halo, complicating causal attribution without experimental manipulation of isolated traits. Statistical detection methods, such as confirmatory factor analysis (CFA), frequently underestimate halo by assuming orthogonal factors and prohibiting cross-loadings, which can mask general impression effects. More flexible approaches like exploratory structural equation modeling (ESEM) or bifactor models better capture halo via allowed cross-loadings or a dominant general factor, yet these require large samples (e.g., N > 20,000 for reliable estimation) and still face issues with measurement invariance across groups or contexts, where cultural response styles inflate apparent halo. Additionally, operational definitions of halo—often as low differentiation in multidimensional ratings—encounter difficulties in statistical control, as correcting for rater biases risks over-adjusting for true variance. Experimental designs aimed at quantifying halo, such as presenting raters with manipulated profiles varying one trait while holding others constant, confront confounds from rater expectations and demand characteristics, potentially artifactually reducing observed effects. In applied domains like personnel selection, self-report instruments exacerbate subjectivity, with response tendencies mimicking halo without objective benchmarks for validation. These issues contribute to inconsistent estimates, with halo appearing more pronounced in holistic judgments than decomposed ones, underscoring the need for multimethod convergence absent a universal metric.

Overgeneralization and Contextual Variability

The halo effect is frequently overgeneralized in psychological literature and applications as a robust, domain-invariant bias that uniformly distorts judgments across all evaluative contexts, yet this overlooks empirical evidence of its inconsistent magnitude and occasional absence. For instance, analyses of impression formation reveal that the effect's strength depends on semantic and lexical similarities between traits; overcorrelations in ratings diminish when traits lack shared contextual connotations, such as between "creativity" and "seriousness," where word embedding models predict lower co-occurrence probabilities (cross-validated r² = 0.19 for basic similarity, improving to 0.45 with valence and frequency adjustments). This linguistic foundation challenges blanket assumptions of an innate perceptual constant, suggesting instead that apparent halos may artifactually arise from evaluative language patterns rather than obligatory cognitive spillover, leading to inflated estimates of the bias's universality in non-linguistic tasks. Contextual moderators further underscore variability, with the halo effect weakening or failing under conditions of increased accountability, detailed information, or rater expertise. In managerial evaluations, imposing justification requirements reduces halo-induced leniency in bonus allocations by prompting differentiated assessments of distinct performance dimensions. Similarly, critical thinking skills inversely predict susceptibility, partially mediated by negative perfectionism, implying that analytically trained evaluators exhibit less trait spillover (path coefficients indicating mediation in HR contexts). Demographic and situational factors amplify this inconsistency: the effect proves stronger for adult faces (r = 0.53) than children's (r = 0.47, z = 0.000287), interacts with ethnicity in trustworthiness inferences, and destabilizes amid external stressors like the COVID-19 pandemic, where post-outbreak rating variance increased for adult aesthetics and trust (Levene's q = 0.025). Over time, accumulating specific evidence can erode initial halos, as in interpersonal or hiring scenarios where prolonged exposure reveals trait independence. Such variability cautions against prescriptive overreliance on halo mitigation strategies without tailoring to moderators like task or cultural priors, as cross-domain generalizations (e.g., from attractiveness to competence) falter when individual beliefs or message framing intervene, per contextual models in consumer and social judgments. Failure to account for these boundaries risks methodological overinterpretation, where low-stakes or uncontrolled settings exaggerate the effect's relative to high-stakes, info-rich environments. In business strategy and , popular applications of the halo effect often exaggerate its explanatory power by attributing firm success or failure to isolated practices, ignoring reverse where performance itself generates favorable perceptions of those practices. For instance, analyses of high-performing companies like in the late credited visionary leadership and innovative culture as direct causes of growth, yet post-2001 downturns prompted attributions of the same firm to flawed execution, despite minimal strategic shifts; this illustrates how halo distorts , leading to overstated claims of replicable "success formulas" in books and case studies. Phil Rosenzweig's 2007 analysis demonstrates that such narratives suffer from data contamination, as retrospective surveys and executive reports correlate highly with outcomes (r > 0.7 in some datasets), fostering delusions of absolute predictability rather than acknowledging competitive uncertainty. In hiring and performance appraisals, claims that the halo effect overwhelmingly skews decisions—such as overvaluing or pedigree to the exclusion of competencies—are overstated, as its magnitude depends on attribute importance and rating structure, with experimental manipulations showing stronger effects for key traits but modest overall inter-trait correlations (e.g., r = 0.20–0.40 in multi-dimensional ratings). Structured interviews and rater training reduce halo variance by 30–50% in meta-analytic reviews, indicating it is mitigable rather than an inevitable dominator of outcomes. Marketing applications invoke halo to claim broad spillover from brand attributes like health claims to unrelated product judgments, yet empirical quantification reveals context-specific effects, such as in food consumption where "health halo" leads to modest calorie underestimation (10–20% in lab settings) but fails to consistently drive sales without complementary evidence. Recent modeling distinguishes true halo from baseline preferences, debunking myths of automatic, universal positivity transfer. A linguistic further tempers exaggerated cognitive interpretations, attributing up to 45% of halo variance in trait ratings to shared word connotations and valence (e.g., via word2vec similarities predicting co-judgments, cross-validated r² = 0.45), suggesting applications treating it solely as perceptual overlook measurement artifacts from structure.

Recent Research and Developments

Post-2020 Studies on Digital and AI Contexts

A study involving 2,748 participants rating 462 facial images demonstrated the persistence of the attractiveness halo effect in digital contexts enhanced by AI beauty filters, where beautified images led to significantly higher perceptions of , trustworthiness, sociability, and alongside attractiveness (median increase of 1 point on a 7-point scale, p < 0.001). The effect was modulated by factors such as rater and subject age, with raters showing stronger shifts in and younger subjects exhibiting smaller increases in perceived post-filtering (p < 0.001). These findings indicate that digital beautification tools can amplify halo es in social judgments while potentially weakening associations for certain traits like in already attractive stimuli. In AI-driven hiring, a 2025 analysis of multimodal large language models (MLLMs) revealed pronounced halo effects from supplementary digital data like images and videos, biasing competency evaluations across roles such as UI designer and backend developer. Using datasets of 3,000 images and 120 video clips evaluated by models including GPT-4o and LLaVA-OneVision, image-based inputs produced stronger positive halos (e.g., +5.7 Likert-scale points for professional portraits in LLaVA-OneVision) compared to text alone, with reverse halos in some hobby-related scenarios (e.g., -4.678 for indoor activities in Llama-3.1). Demographic influences exacerbated biases, such as favoritism toward White males (+0.8 points), underscoring the need for in AI recruitment systems reliant on digital profiles. Research on large language models (LLMs) has identified an "AI-AI bias" akin to a , where LLMs preferentially favor content generated by other LLMs over human-authored material in tasks. Experiments across datasets of product descriptions, academic papers, and movie summaries (e.g., 250 movie pairs) showed models like selecting LLM-generated options at rates up to 89% for products, far exceeding human baselines (36%), with consistent patterns in GPT-3.5, Llama-3.1-70B, and others. This intra-AI raises concerns for applications, potentially entrenching advantages for AI-produced content and disadvantaging human outputs in digital ecosystems.

Updates on Attractiveness and Trustworthiness Biases

Recent empirical investigations have reaffirmed the influence of on perceived trustworthiness, with a 2024 study demonstrating that AI-enhanced of 462 faces led to significantly higher trustworthiness ratings across 2,748 participants (Wilcoxon W = 33.13, p < 0.001). This effect persisted across traits like but exhibited saturation, where further enhancements yielded for already highly attractive stimuli (n = 79, W/n = 6.71, non-significant). dynamics nuanced the findings, as raters showed reduced trustworthiness gaps for beautified female faces compared to originals (-95.68% vs. -37.74% for female raters). In , a 2025 trust game experiment with 57 decision-makers found that faces rated attractive prompted 30% higher initial investments (M = 0.61 vs. 0.47 for unattractive, F(1,56) = 36.68, p < 0.001, η_p² = 0.40), with similar effects for attractive voices (M = 0.58 vs. 0.51, F(1,56) = 19.77, p < 0.001, η_p² = 0.26). Reinvestments remained elevated even after trustees withheld repayments (faces: F(1,56) = 9.91, p = 0.003, η_p² = 0.15), attributing persistence to a halo linking attractiveness to assumed positive traits like reliability. Expected investments in hypothetical scenarios also favored attractive trustees (M = 0.57 vs. 0.53, F(1,56) = 6.19, p = 0.016, η_p² = 0.10). Emerging evidence highlights bidirectionality in these biases, as a 2025 analysis across three experiments (N = 249) showed trustworthiness cues infiltrating attractiveness judgments (β = 0.157, p < 10^{-4} in goal-directed tasks), resisting perceptual filtering unlike the reverse. In goal-agnostic contexts, holistic encoding amplified mutual influence (β = 0.249, p < 10^{-6}), positioning trustworthiness as a dominant dimension in face perception. Methodological advances challenge the halo's universality, with 2023 data-driven modeling revealing that attractiveness and trustworthiness cues in faces can be computationally dissociated, yielding stimuli free of correlated confounds and enabling independent judgments. Such separations suggest prior halo observations may stem from stimulus artifacts rather than inherent perceptual linkage, prompting refined experimental designs to isolate causal pathways. These updates underscore contextual modifiability while affirming the bias's robustness in unmanipulated settings.

References

  1. https://www.verywellmind.com/what-is-the-halo-effect-2795906
  2. https://www.simplypsychology.org/halo-effect.html
  3. https://psycnet.apa.org/record/1979-23612-001
  4. https://psycnet.apa.org/record/1993-15610-001
  5. https://www.researchgate.net/publication/349443219_The_halo_effect
  6. https://www.sciencedirect.com/science/article/pii/0022103181900494
  7. https://pmc.ncbi.nlm.nih.gov/articles/PMC11614318/
  8. https://pmc.ncbi.nlm.nih.gov/articles/PMC8024691/
  9. https://thedecisionlab.com/biases/halo-effect
  10. https://pmc.ncbi.nlm.nih.gov/articles/PMC11656545/
  11. https://www.sciencedirect.com/science/article/pii/S2949882125000222
  12. https://scholarworks.calstate.edu/downloads/2227mx622
  13. https://www.salisbury.edu/administration/administration-and-finance-offices/human-resources/current-employees/_files/recruitment/13-Types-of-Unconscious-Bias.pdf
  14. https://psycnet.apa.org/record/1920-10104-014
  15. https://doi.org/10.1037/h0071663
  16. https://psycnet.apa.org/record/1946-04654-001
  17. https://www.romolocapuano.com/wp-content/uploads/2013/08/Asch-Forming-Impressions-Of-Personality.pdf
  18. https://www.all-about-psychology.com/the-halo-effect-experiment.html
  19. https://pmc.ncbi.nlm.nih.gov/articles/PMC10376162/
  20. https://journals.sagepub.com/doi/10.1177/27000710241257814
  21. https://nobaproject.com/modules/attraction-and-beauty
  22. https://www.millionairematch.com/dating-tips/are-rich-people-more-physically-attractive
  23. https://psycnet.apa.org/record/1973-09160-001
  24. https://www4.uwsp.edu/psych/s/389/dion72.pdf
  25. https://psycnet.apa.org/record/1991-33123-001
  26. https://www.researchgate.net/publication/362913527_Examining_the_attractiveness_halo_effect_across_cultures
  27. https://pmc.ncbi.nlm.nih.gov/articles/PMC11597472/
  28. https://onlinelibrary.wiley.com/doi/abs/10.1111/ssqu.12892
  29. https://pmc.ncbi.nlm.nih.gov/articles/PMC10566695/
  30. https://www.researchgate.net/publication/233820889_What_is_beautiful_is_good
  31. https://www.researchgate.net/publication/373922242_How_Do_the_Halo_Effect_and_Horn_Effect_Influence_the_Human_Resources_Managers_Recruitment_Decision_in_an_Occupation_Interview
  32. https://www.tandfonline.com/doi/full/10.1080/01443410.2023.2194593
  33. https://www.researchgate.net/publication/242340572_Brand_equity_The_halo_effect_measure
  34. https://journals.sagepub.com/doi/10.1509/jim.11.0016
  35. https://www.tandfonline.com/doi/full/10.1111/j.1742-9536.2011.00015.x
  36. https://pmc.ncbi.nlm.nih.gov/articles/PMC8621627/
  37. https://hal.science/hal-02051232v1/document
  38. https://www.sciencedirect.com/science/article/abs/pii/S0007681324001563
  39. https://pubmed.ncbi.nlm.nih.gov/33180979/
  40. https://www.sciencedirect.com/science/article/pii/S2772766123000083
  41. https://www.tandfonline.com/doi/full/10.1080/02602938.2021.1888868
  42. https://journals.sagepub.com/doi/abs/10.1177/1532673x15600517
  43. https://www.researchgate.net/publication/281614119_Halo_Effects_and_the_Attractiveness_Premium_in_Perceptions_of_Political_Expertise
  44. https://www.cambridge.org/core/journals/politics-and-the-life-sciences/article/is-there-a-beauty-is-beastly-effect-in-electoral-success-an-empirical-analysis-of-the-german-federal-elections-2005-to-2021/CB3BC6DC7B5E6F3DEFEC8C15CC0E997E
  45. https://www.researchgate.net/publication/353927922_An_Investigation_of_Beliefs_Information_and_the_Halo_Effect_in_Electoral_Decision_Making
  46. https://www.causeweb.org/usproc/sites/default/files/usresp/2017-1/ClaraDrew_USRESP_Submission.pdf
  47. https://pmc.ncbi.nlm.nih.gov/articles/PMC4353482/
  48. https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/the-halo-effect-and-other-managerial-delusions
  49. https://www.sciencedirect.com/science/article/abs/pii/S1048984314000721
  50. https://pmc.ncbi.nlm.nih.gov/articles/PMC6762156/
  51. https://www.sciencedirect.com/science/article/abs/pii/0092656674900440
  52. https://journals.sagepub.com/doi/10.1177/17470218231218651
  53. https://theconversation.com/halo-effect-do-attractive-people-really-look-less-guilty-how-the-evidence-is-changing-220349
  54. https://pmc.ncbi.nlm.nih.gov/articles/PMC6775219/
  55. https://www.mdpi.com/2076-328X/14/10/922
  56. https://www.psychologytoday.com/us/basics/halo-effect
  57. https://www.researchgate.net/publication/369600152_Bias_Halo_Effect_and_Horn_Effect_A_Systematic_Literature_Review
  58. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.969.42&rep=rep1&type=pdf
  59. https://kwpublications.com/papers_submitted/10056/bias-halo-effect-and-horn-effect-a-systematic-literature-review.pdf
  60. https://www.healthline.com/health/horn-effect
  61. https://profrjstarr.com/cognitive-biases/horn-effect-why-one-bad-trait-pollutes-everything-else
  62. https://hr.untsystem.edu/sites/default/files/rating-pitfalls-to-avoid.pdf
  63. https://engagedly.com/blog/how-to-eliminate-halo-effect-in-performance-reviews/
  64. https://www.pmapstest.com/blog/what-is-horn-effect
  65. https://www.aihr.com/hr-glossary/horn-effect/
  66. https://www.ewadirect.com/proceedings/chr/article/view/4142
  67. https://web.mit.edu/curhan/www/docs/Articles/biases/4_J_Applied_Psychology_25_%28Thorndike%29.pdf
  68. https://psycnet.apa.org/record/2022-95217-001
  69. https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2021.631871/full
  70. https://www.researchgate.net/publication/341218784_The_halo_effect_A_longitudinal_approach
  71. https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2016.00110/full
  72. https://doi.apa.org/doi/10.1037/0021-9010.67.2.161
  73. https://www.sciencedirect.com/science/article/pii/S1044500521000123
  74. https://eddy.com/hr-encyclopedia/halo-effect/
  75. https://audencia.hal.science/hal-02957579/document
  76. https://online.ucpress.edu/collabra/article/9/1/84560/196995/From-Halo-to-Conditioning-and-Back-Again-Exploring
  77. https://knowledge.wharton.upenn.edu/article/the-halo-effect-debunking-some-hot-business-books-with-one-of-his-own/
  78. https://www.sciencedirect.com/science/article/abs/pii/S0969698999000193
  79. https://vervoe.com/halo-and-horns-effect-in-hiring/
  80. https://academic.oup.com/ijfst/article/59/1/208/7808253
  81. https://www.mckinsey.com/capabilities/growth-marketing-and-sales/solutions/periscope/our-insights/articles/from-myth-to-math-harnessing-the-halo-effect-of-promotions
  82. https://upcommons.upc.edu/bitstream/handle/2117/419847/RSOS-240882.pdf?sequence=2
  83. https://aclanthology.org/2025.findings-acl.1338.pdf
  84. https://www.pnas.org/doi/10.1073/pnas.2415697122
  85. https://royalsocietypublishing.org/doi/10.1098/rsos.240882
  86. https://pmc.ncbi.nlm.nih.gov/articles/PMC11851420/
  87. https://doi.org/10.1037/xge0001717
  88. https://journals.sagepub.com/doi/10.1177/03010066231178489
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