The Attractiveness of Individuals and the Effect on Perception of Associated Personality Traits
The Attractiveness of Individuals and the Effect on Perception of Associated Personality Traits. Curtin University of Technology Abstract Dion, Berscheid and Walster (1972) hypothesized that “what is beautiful is good” and that attractive people were assumed to lead happier lives and have better prospects for the future. A survey was carried out among university students and their friends to determine whether attractiveness of facial features of an individual influences one’s perceived associated personality traits. The 425 participants completed the FPS 120 Impression Formation Project survey and data was collected and analysed.
It was discovered that a strong positive correlation existed between levels of attractiveness and sociability, friendliness and trustworthiness. This research study has attempted to apply Dion et al’s study of “what is beautiful is good” to the modern era and to determine if a halo effect for personality stereotyping is still applicable. This research was conducted to ascertain whether the study by Dion, Berscheid and Walster (1972) was still valid in modern day society and whether the stigma of “what is beautiful is good” still holds true.
Dion et al predicted that attractive people “were assumed to have better prospects for happy social and professional lives”. Dion et al tested their hypotheses by asking men and women to examine three photographs and rate them along a number of dimensions. Half received photographs of women who varied in physical attractiveness and the remainder received pictures of men (Berkowitz, 1974) It was discovered that there was no discrimination between males and females to the participants, who still rated attractive people of both sexes to most likely possess all the personality traits that were socially desirable.
It is apparent in their study that the thesis of beauty and its correlation to positive attributes is supported by a social stereotype. “Not only are physically attractive persons assumed to possess more socially desirable personalities than those of lesser attractiveness, but it is presumed that their lives will be happier and more successful” (Dion et al, 1972). In a comparable scenario, our stereotypical tendencies ollow through into other aspects in the sense that we tend to see good people do good things, bad people do bad things, good companies make good products and so forth, leading to distortions from the truth (Webb, 1999;Emslie, 1979). For example a positive rating in one area, in this case attractiveness leads to an over generalisation resulting in a more positive rating to other attributes such as desirable personality traits. This positive transfer is called the halo effect.
The well established information of which the halo effect is based is weighted more heavily than new information that is provided to us and thus the halo effect operates best when the established information or attitude is strong and new information is to an extent ambiguous. “When the established attitude is not particularly strong or the new information is more strongly positive or negative, the halo effect is not as strong. ” (Webb pp 98, 1999) This halo effect correlates to Dion et al’s study on attractiveness, as the physical attributes of a person is generally the first point of origin for a meeting between two individuals.
Upon meeting, the halo effect allows the individual to rate the attractiveness of the other individual creating a cognitive bias as one positive trait extends to influence other qualities of that person. Although previous studies conducted focused on the investigation of attractiveness in relation to personality traits where beauty equated to positive qualities, this research paper will be examining individual traits specifically. The aim of this current study is to explore whether (1. )attractive people are rated more sociable than unattractive people (2. )whether attractive people are rated friendlier than unattractive people; and (3. as attractiveness scores get higher the honesty scores should also get higher. Method Participants The sample comprised of 425 participants which consisted of 165 easily accessible male participants (M= 23. 09 years, SD= 7. 41 years) and 260 easily accessible female participants (M= 24. 31 years, SD= 9. 92 years). Participants were chosen out of convenience students enrolled in the Foundations of Psychological Science 120 unit at Curtin University of Technology. All participants were self-proclaimed regular users of Facebook and are aged between 18 to 48 years old. Participation in this survey was oluntary and no incentives were offered. Materials Consent forms and information sheets were given out to participants. The survey called the FPS 120 Impression Formation Project was uploaded on an online database where participants could complete it through accessing the website at home. The results from the survey were then viewed on the Statistical Package for the Social Sciences, also known as SPSS. Procedure Participants were asked read to the information sheets and to sign consent forms prior to the completion of the online survey. They were asked to complete the online survey called the FPS 120 Impression Formation Project.
This survey provided images of four people that are regular Facebook users. The participants were then asked to rate each person on a scale of one to six on a number of characteristics that they might attribute based on their appearance. Results were then gathered and viewed on the SPSS whereby our hypotheses were then generated. Results A paired sample t test with an ? of . 05 was used to compare the sociability of attractive (M = 4. 388, SD = . 8226) and unattractive (M = 2. 602, SD = . 8603) people as rated by the participants of the sample group (n= 425) (Table 1. 0 & Table 1. 1).
On average attractive participants scored 1. 7859 points (95%CI = 1. 9031 – 1. 6687) higher than unattractive participants (Table 1. 2). The difference was statistically significant, t(425) = 29. 995, p<. 001 and large d = 1. 766. It was concluded that the normality and normality of difference scores were not violated after outputting and visually inspecting data. A paired sample t test with an ? of . 05 was also used to compare the friendliness of attractive (M=4. 100, SD= . 8598) and unattractive people (M=2. 885, SD=. 8767) as rated by participants of a sample groups (n=425) (Table 2. 0 & Table 2. 1).
On average attractive participants scores higher friendliness scores than unattractive people. The difference was statistically significant, t(425) = 21. 156, p<. 001 and large d=1. 399 (Table 2. 2). It was concluded that the normality and normality of difference scores were not violated after outputting and visually inspecting data. To assess the size and direction of the linear relationship between attractiveness rating and honesty scores, a bivariate Pearson’s product-movement correlation coefficient (r) was calculated. The bivariate correlation between these two variables in the attractive group was positive and strong, r(425) = . 75, p<. 001, as was the case with the unattractive group, r(425) = . 051, p<. 001. Discussion The results portrayed from this study has a positive correlation to the literature. Like previous studies the results indicate that attractive people commonly scored higher with perceived possession of desirable physical traits, whereas the unattractive people generally tended to score lower on the socially desirable traits. The first hypothesis, is verified by the results concluding that there was a statistically significant difference between the sociability of attractive and unattractive groups.
The positive correlation of sociability and attractiveness, authenticate Dion et al’s ‘what is beautiful is good’ theory. The results also endorse the second hypothesis, that attractive people are rated friendlier than unattractive people, with a strong correlation being found and a significant difference in friendliness scores by participants. In the results collected for third hypothesis, there is once again positive correlation between honesty and attractiveness indicating that as attractiveness scores increases, perceived honesty scores also increase.
The variability in the scores illustrates how an individual’s visual perception can affects their observation of another individual’s personality traits. The findings from this research confirms the original hypothesis of Dion, Berscheid and Walster (1972) of “what is beautiful is good” and validates the theory in the 21st century. With the high accessibility of information we were able to create a study that allowed for the variety of other factors to be measured and rated by the participant, such as number of ‘facebook’ friends.
From this study it is apparent that even in today’s modern society, individuals are still affected by the halo effect with no restrictions from the mediums used for social interaction. People are still using this cognitive bias in making decisions or assumptions on other individual’s personality traits. Some further areas of study can be the halo effect and attractiveness preconceptions within different age groups. As the demographics of this study was conducted from young adults who frequent ‘Facebook’, an online based community with the mean age being 23. 829 years of age.
It has been discovered from this sample group that older adults were less superficial and tended not to stereotype their peers into different stigmas. Although Dion et al obtained participants from a different age demographic, further study can be performed to ascertain whether the same results will be yielded (Table 3. 0, Table 3. 1, Table 3. 2 & Table 3. 3). References Berkowitz, L. (1974). Advances in Experimental Social Psychology. Academic Press 1974. Dion, K. , Berscheid, E. , & Walster, E. (1972). What is beautiful is good. Journal of Personality and Social Psychology, 24(3), 285-290.
Emslie, G. R, Medcof, J. & Roth J. (1979). Approaches to Psychology. Routledge, 1979. Webb, Robert C. (1999). Psychology of the consumer and its development: an introduction The Plenum series in adult development and aging, Table 1. 0 Paired Samples Statistics| | Mean| N| Std. Deviation| Std. Error Mean| Pair 1| SOCIABLE_ATTR| 4. 388| 425| . 8226| . 0399| | SOCIABLE_UNATT| 2. 602| 425| . 8603| . 0417| Table 1. 1 Paired Samples Correlations| | N| Correlation| Sig. | Pair 1| SOCIABLE_ATTR & SOCIABLE_UNATT| 425| -. 066| . 173| Table 1. 2 Paired Samples Test| Paired Differences| t| df| Sig. (2-tailed)| | Mean| Std. Deviation| Std. Error Mean| 95% Confidence Interval of the Difference| | | | | | | | Lower| Upper| | | | Pair 1| SOCIABLE_ATTR - SOCIABLE_UNATT| 1. 7859| 1. 2291| . 0596| 1. 6687| 1. 9031| 29. 955| 424| . 000| Table 2. 0 Paired Samples Statistics| | Mean| N| Std. Deviation| Std. Error Mean| Pair 1| FRIENDLY_ATTR| 4. 100| 425| . 8598| . 0417| | FRIENDLY_UNATT| 2. 885| 425| . 8767| . 0425| Table 2. 1 Paired Samples Correlations| | N| Correlation| Sig. | Pair 1| FRIENDLY_ATTR & FRIENDLY_UNATT| 425| . 070| . 47| Table 2. 2 Paired Samples Test| | Paired Differences| t| df| Sig. (2-tailed)| | Mean| Std. Deviation| Std. Error Mean| 95% Confidence Interval of the Difference| | | | | | | | Lower| Upper| | | | Pair 1| FRIENDLY_ATTR - FRIENDLY_UNATT| 1. 2149| 1. 1839| . 0574| 1. 1021| 1. 3278| 21. 156| 424| . 000| Table 3. 0 Case Processing Summary| | Cases| | Valid| Missing| Total| | N| Percent| N| Percent| N| Percent| HONEST_ATTR| 425| 100. 0%| 0| . 0%| 425| 100. 0%| ATTRACTIVENESS_ATTR| 425| 100. 0%| 0| . 0%| 425| 100. 0%| Table 3. 1 Descriptives| | Statistic| Std. Error|
HONEST_ATTR| Mean| 3. 729| . 0381| | 95% Confidence Interval for Mean| Lower Bound| 3. 655| | | | Upper Bound| 3. 804| | | 5% Trimmed Mean| 3. 741| | | Median| 3. 500| | | Variance| . 615| | | Std. Deviation| . 7844| | | Minimum| 1. 5| | | Maximum| 6. 0| | | Range| 4. 5| | | Interquartile Range| 1. 5| | | Skewness| -. 172| . 118| | Kurtosis| . 063| . 236| ATTRACTIVENESS_ATTR| Mean| 5. 955| . 0794| | 95% Confidence Interval for Mean| Lower Bound| 5. 799| | | | Upper Bound| 6. 111| | | 5% Trimmed Mean| 6. 005| | | Median| 6. 000| | | Variance| 2. 682| | | Std. Deviation| 1. 376| | | Minimum| 1. 0| | | Maximum| 10. 0| | | Range| 9. 0| | | Interquartile Range| 2. 0| | | Skewness| -. 490| . 118| | Kurtosis| . 044| . 236| Table 3. 2 Case Processing Summary| | Cases| | Valid| Missing| Total| | N| Percent| N| Percent| N| Percent| HONEST_UNATT| 425| 100. 0%| 0| . 0%| 425| 100. 0%| ATTRACTIVENESS_UNATT| 425| 100. 0%| 0| . 0%| 425| 100. 0%| Table 3. 3 Descriptives| | Statistic| Std. Error| HONEST_UNATT| Mean| 3. 242| . 0413| | 95% Confidence Interval for Mean| Lower Bound| 3. 161| | | | Upper Bound| 3. 323| | | 5% Trimmed Mean| 3. 227| | Median| 3. 000| | | Variance| . 727| | | Std. Deviation| . 8524| | | Minimum| 1. 0| | | Maximum| 6. 0| | | Range| 5. 0| | | Interquartile Range| 1. 5| | | Skewness| . 241| . 118| | Kurtosis| . 131| . 236| ATTRACTIVENESS_UNATT| Mean| 2. 569| . 0617| | 95% Confidence Interval for Mean| Lower Bound| 2. 447| | | | Upper Bound| 2. 690| | | 5% Trimmed Mean| 2. 483| | | Median| 2. 500| | | Variance| 1. 619| | | Std. Deviation| 1. 2726| | | Minimum| 1. 0| | | Maximum| 7. 5| | | Range| 6. 5| | | Interquartile Range| 2. 0| | | Skewness| . 878| . 118| | Kurtosis| . 422| . 236|