Introduction
In today’s world, catalyzed by the rapid development of the Internet and social media, studying human perceptions of self and some abstract, average person is particularly important. Users observe other people’s lives daily, evaluating and comparing themselves to them. At the same time, people turn out to be carriers of unique personal qualities, which can also become an object of comparison with others. In any of these comparison cases, there is a danger in that the individual cannot be objective about himself or herself, resulting in either an over- or underestimation of their self-esteem.
There is a term in cognitive psychology that describes bias or prejudice in the perception of one’s personality compared to some average individual, namely the Better-Than-Average-Effect. This effect was measured by Svenson (1981), who interviewed drivers about their competence compared to other drivers. Svenson’s finding was that most respondents thought they were more skilled and capable drivers than others: this is the Better-Than-Average-Effect, in which people tend to overestimate their qualities and abilities compared to others. In the essence of this effect, it is not difficult to draw a parallel with egocentrism: Kruger (1999) explained that respondents tend to focus on their qualities and downplay the characteristics of others.
To evaluate his hypotheses, Kruger surveyed Cornell University graduates to rate themselves on 14 skills and further correlated this with college board bias and found that this effect was not observed when assessing competencies in complex disciplines. Consequently, when an individual is found to be confident in a particular area or is asked to assess some abstract quality of personality, they tend to overestimate their assessments, which can be viewed as egocentrism. Egocentrism should be understood as a cognitive state in which a person cannot objectively evaluate outsiders but instead puts himself and his opinions and ideas at the center of attention.
An explanation for this effect can also be found in Brown (2012), who showed that people tend to evaluate themselves more strongly on important personality attributes than on unimportant ones. The author interviewed 29 students at the University of Washington and observed that people tend to rate themselves higher than the average person because it makes them feel better about themselves. Remarkably, according to Brown’s findings, this effect is more intense when the respondent’s dignity is threatened, implying that motivational forces determine this effect.
In the present study, statistical analyses were conducted to determine differences in perceptions of self and others and differences in ratings of personality attributes perceived as high and low importance. The first hypothesis postulated that people tended to rate themselves more on average than others. The second hypothesis postulated that ratings of more important personality attributes were higher than those of less important attributes, which determined the motivating force for self-esteem.
Method
A total of 465 participants participated in the study, of whom 31% (n = 143) identified themselves as male, and 66% (n = 309) were female. The remainder of the sample was comprised of non-binary individuals (1%, n = 4), as well as individuals whose gender was not listed in the response list (0%, n = 2) and 2% (n = 7) who chose not to specify their gender for this question. In the context of age distribution, the mean age of participants was 38.59 (SD = 17.35). Two participants did not state their age; the maximum age of participants was 89, with a minimum of 12. This shows that the sample was predominantly female and of middle age.
Design
The online survey design was based on four questions, two of which belonged to the demographic block, and two were the central questions of the questionnaire. In the context of the demographic variables, it was interesting to gather information about the participant’s gender and age to identify the average portrait. More important were the main block questions, which were asked to assess psychosocial constructs of self and others. Appendix A and Appendix B show these questions offered to respondents: the same personality traits rated on a five-point Likert scale. Half of the individuals in the sample were initially asked to rate their personality and then move on to rate other people, while the other half were offered the opposite approach.
In both sets of ten attributes, five were assigned to “High Importance” cohorts, and the other five were classified as “Low Importance” based on their social and personal influence level. The “High Importance” categories included passionate, empathetic, reliable, trustworthy, and hardworking as character characteristics of an individual, and the categories easy-going, energetic, frugal, assertive, and sporty were categorized as “Low Importance.” For statistical analysis, respondents’ responses regarding their attributes were averaged and clustered so that four quantitative clusters were ultimately used for analysis.
Depending on the mechanics of the survey, two additional categories called “Target” and “Interaction” were created. Target was defined as individuals comparing themselves against others. The first hypothesis was postulated as the belief that individuals tended to rate themselves through positive traits more highly than other people: put another way, respondents tended to rate themselves more positively than others. Interaction meant comparing oneself versus others, not by the main effect, but when differentiated by categories of importance. The second hypothesis implied that people tended to rate it higher under the “High Importance” categories than under the “Low Importance.” This meant that quantitative differences in the evaluation of self and others in the two categories would show a statistically significant difference.
Procedure
A nonprobability sampling mechanism was chosen to generate the sample based on including the most accessible participants. To do this, a four-question survey was created on the Google Forms platform. The invitation link for participation was posted on social networks (Facebook, Instagram, Twitter), and the posting was done by a group of students from different classes, which increased the reach of potential participants. The advantage of this mechanism is that it saves significant resources by targeting the invitation links. On the contrary, the disadvantage of this formation mechanism is the reduced representativeness of the sample, as there is no guarantee that all members of the general population have an equal chance to participate in the project.
The collected data were inserted into JAMOVI, after which they were subjected to a thorough statistical analysis. In addition to descriptive statistics, which allowed the identification of mean trends in the sample, the statistical analysis included a parametric Repeated Measure ANOVA test. Typically, this test is used when measurements of variables for a sample are repeated several times, that is, at different time points. In this research project, this test is used to compare differences in respondents’ responses based on whether they rated themselves or others.
More specifically, the Repeated Measure ANOVA was useful for identifying differences not only in how, on average, respondents rated themselves and others but also for detecting differences between items, that is, between attributes in the “High Importance” and “Low Importance” categories. The significance of all statistical tests was evaluated at an alpha of.05: calculated p-values below this level resulted in the need to reject the null hypothesis and, consequently, the recognition of differences.
Results
A Repeated Measure ANOVA statistical test was used to evaluate (i) the significance of differences between the two key factors, “Target” and “Interaction,” and (ii) differences in mean scores between “High Importance” and “Low Importance.”
“Target” vs. “Interaction”
It was assumed that respondents rated their character traits higher on average than the same traits for others. The analysis showed statistically significant differences between the two clusters “Target” and “Interaction,” F(1, 464) = 741.88, p <.001. The result’s significance is due to the low calculated p-value, which allowed to reject the null hypothesis. Consequently, in the context of the question under study, there were significant differences between the assessment of one’s personality attributes and those of others. When turning to descriptive statistics (Figure 1), it becomes apparent that the differences are due to a shift of higher scores toward self-esteem. Respondents rated themselves higher on average than others on the suggested ten attributes. From this, one can conclude that the working hypothesis was fully confirmed.
“High Importance” vs. “Low Importance”
This part of the analysis evaluated whether respondents rated themselves higher on average on the attributes in the “High Importance” cluster than others. Similarly, the same hypothesis suggested that respondents also rated themselves higher on the attributes of the “Low Importance” cluster than the same ratings for other people. The analysis demonstrated the statistical significance of differences in mean values, F(1, 464) = 797.02, p <.001.
The null hypothesis was rejected due to obtaining a lower alpha value for the calculated p-value. Turning to descriptive statistics (Table 1) shows that the mean High Importance scores for self-evaluation (M = 4.06, SE = 0.02) were higher than the same attributes for other people’s evaluation (M = 2.90, SE = 0.03). A similar pattern was evident for the categories in the High Importance cluster: evaluations of self (M = 3.03, SE = 0.02) were higher than those for other people (M = 2.86, SE = 0.02). It follows that respondents were statistically significantly more likely to rate themselves higher than other people in both clusters, and, at the same time, the High Importance scores were significantly higher than the Low Importance scores.
Discussion
The current research project examined patterns of self and other people’s perceptions of ten positive attributes. Respondents were asked to choose the extent to which they agreed that a particular characteristic applied to them and others. The measurements were taken on a five-point Likert scale, where a value of “5” corresponded to an extreme level of agreement. It is noteworthy that the term “other people” used in the survey was not aimed at a specific community whose representatives are familiar to the respondent but rather at some average person, a bearer of average socially common personality traits.
Of interest was whether respondents tended to show meaningful differences in their assessment of the same personality attributes in themselves and others. The results of the Repeated Measure ANOVA showed that respondents were self-esteem biased: they tended to emphasize their positive traits higher than others. These differences were observed for two clusters previously identified as high and low-importance attributes. At the same time, people tended to overestimate qualities from “High Importance” more than “Low Importance.”
To better understand the findings, they need to be placed within the current agenda of academic discourse. Brown (2012) emphasized that on more important personality attributes, people tended to give higher ratings than on less important ones, the importance of a particular personality quality was a motivating force for them when evaluating. A reference to psychological work identifies a state of cognitive bias known as the Illusory Superiority effect or The Dunning-Kruger effect (Muller et al., 2021).
The essence of this effect is an overestimation of one’s abilities relative to others, but the main focus of this bias is an overestimation of competence. For example, a person with little knowledge of politics might be convinced that their beliefs and strategies are far more intelligent and expedient than the corresponding knowledge of professional politicians. In the context of the research project, respondents were not surveyed on specific competencies, but overestimating one’s attributes relative to those of others may provide additional evidence for this cognitive effect. Support for these findings is also found in a study by Zell et al. (2020), who the Better-Than-Average-Effect.
The authors point out that the overestimation of personality traits compared to others is generally higher than that of competencies. An interesting conclusion was made regarding the Better-Than-Average-Effect relationship with life satisfaction: the correlation analysis showed a moderate positive relationship. Respondents who overestimated their assessments compared to others were more likely to be more satisfied with their lives.
This study, while validated in academic discourse, has several limitations. First, it is unknown how honestly the respondents filled out the questionnaires. They may have experienced the Hawthorne effect, leading to inflated results. This bias and lack of control over honesty may have led to some bias in the results. Second, the survey design did not consider that the same terms may be perceived differently by respondents.
Perceptions of the personality quality Dependable can have slightly different interpretations for two people with different cultural backgrounds. The lack of decoding of such questions could have violated the measurements’ validity. Finally, a non-probability mechanism was used to generate the sample, significantly reducing the chances of participants being included in the final sample. This creates barriers to the representativeness of the results, which means that the findings should be cautiously extrapolated to the population.
In conclusion, the lessons learned from this study show how strong the boundary exists in people’s perceptions of themselves and others in society. Respondents were not inclined to associate themselves with the average person, which created meaningful differences in evaluations. In turn, this can affect communication between them. If a person exalts themselves over others, it can lead to a lack of trust in relationships and the need to listen to the advice of others, whether family, friends, or other average acquaintances.
References
Brown, J. D. (2012). Understanding the better than average effect: Motives (still) matter. Personality and Social Psychology Bulletin, 38(2), 209–219. Web.
Kruger, J. (1999). Lake Wobegon be gone! The “below-average effect” and the egocentric nature of comparative ability judgments. Journal of Personality and Social Psychology, 77(2), 221–232. Web.
Muller, A., Sirianni, L. A., & Addante, R. J. (2021). Neural correlates of the Dunning–Kruger effect. European Journal of Neuroscience, 53(2), 460-484. Web.
Svenson, O. (1981). Are we all less risky and more skillful than our fellow drivers? Acta Psychologica, 47(2), 143-148. Web.
Zell, E., Strickhouser, J. E., Sedikides, C., & Alicke, M. D. (2020). The better-than-average effect in comparative self-evaluation: A comprehensive review and meta-analysis. Psychological Bulletin, 146(2), 118–149. Web.
Appendix
