Stability of the Big Five Personalities

1978 words (8 pages) Essay in Psychology

08/02/20 Psychology Reference this

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Rationale

The primary goal of the 2017 study titled “Big Five Personality Stability, Change, And Co-Development Across Adolescence And Early Adulthood“ that is published under the Journal Of Personality and Social Psychology were to evaluate general conditions and shapes of the Big Five Personality characteristic growth in the adolescence. To effectively accomplish this research objective, the study team segmented the general objective into four goals. The first objective was to stipulate details of twelve-months rank-order mean and stability intensities of big five personalities while the second purpose was to approximate the extent of the individual disparities in the behavior changes of the young adolescents (Borghuis, Denissen, Oberski, Sijtsma, Meeus, Branje, & Bleidorn, 2017). The third objective evaluated the relationship between personality trajectories of adolescent siblings and friends while the last goal explored the possible boundary circumstances of the codevelopment by examining the influences of several probable facilitators.

Study Methods and Design

The study used secondary data to accomplish the study objectives. This is because the study used data collected by the Research on Adolescent Development and Relationship (RADAR) study of the Dutch-vernacular families in the Netherlands. The study focused on information about the self-reported personalities of the adolescents, their siblings and their friends from all waves of the available time.  In general, the survey targeted 1293 respondent including 663 friendships and 631 respondents (Borghuis, Denissen, Oberski, Sijtsma, Meeus, Branje, & Bleidorn, 2017). These respondents were randomly recruited from selected elementary and high schools from central and western regions of the Netherlands.  The researchers used the shortened Dutch version of Goldberg’s Big five questionnaire to measure personality while eight items drawn from the Support Scale of the Network of Relationship inventory were used to measure relationship quality.

Findings

The study respondents exhibited five different personality traits including openness, agreeableness, extraversion, emotional stability, and consciousness. The outcomes of the model comparison assessment failed to uncover proof for the associate effects in the rank-order steadiness for the respondents aged between 16 and 18 years. However, the model supported the existence of an increasing trend in the middling one-year behavior traits during the initial and middle adolescent. But, this trend was not evident in the late adolescent and early adulthood.  These findings accomplished the first goal of the study.

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Furthermore, the study indicated that the extent of individual dissimilarity in the personality characteristic changes across the change of the respondents. In particular, the study indicates that slope variances were extreme for the respondents with emotional stability, extraversion, and conscientiousness. At the same time, the slope variance was lower for the openness and agreeableness traits. Besides, the study reported a weak positive correlation between the personality traits of the dyad members and the qualities of the siblings and friends. In this context, the study reported the small degree of the initial similarity between friends for the extraversion, conscientiousness and agreeableness traits. Also, smaller degrees of initial similarity were found on siblings with emotional stability and openness stability.  Finally, the study findings failed to support the hypothesis that gender differences had a moderating impact on the initial similarity and the latter codevelopment.  In this analysis, gender was used as the major potential moderator of personality trait codevelopment among the targeted adolescents.

In general, the study outcomes indicate that adolescents become more stable in their personality trait rankings as they experience psychological growth and maturity. Also, adolescents have different personality trajectories although these individual differences are independent of the personal trajectories of their siblings and friends.

Conformity And Personality

Goal

Hellmer, Stenberg, and Fawcett provide remarkable insights about the link between personality traits and compliance in the 2018 study published under the British Journal of Developmental Psychology.  Even though the study was exploratory as it did not focus on a particular hypothesis, the researchers paid substantial attention in evaluating the ways respondent’s personality trait influence conformity and motivation of the participants. Also, the study assessed the frequency of normative conformity, non-conformity, and informational conformity. Lastly, the researchers tested the employment of the eye-tracking paradigm to determine the individual responses of the respondents (Hellmer, Stenberg, & Fawcett, 2018). In this study, compliance was defined as the overt behavior of selecting a target that is incorrect after observing a model that describes incorrect objectives to be correct.

Method

The research targeted 59 respondents aged 3.5 years old from a list of Swedish families who had exhibited the interest of participating in the study with the kids. The study overlooked the demographic details of the respondents as all respondents were from white and middle-class families. Both the consent and gift-voucher worth EUR 10 was sent to the caregivers of each participant before the implementation of the research (Hellmer, Stenberg, & Fawcett, 2018). The Tobii T120 near-infrared eye tracker registered the gaze of the participants and the information was recorded using a five-point calibration procedure.  Parents were then asked to complete online questionnaires about their children’s personalities. At the lab, the participants were made to believe that the experimenter was in need of urgent help in identifying the animal that had many dots. These respondents were required to quickly determine the animal with many dots immediately after the adults who were offering help pointed to the animal that they thought had many dots. The intentional pointing of correct and incorrect answers helped the researchers to categorize the study’s trials into two broad groups including the congruent and incongruent trials. The congruent trials are the models that correctly pointed to the animal that had many dots while incongruent trials are the models that incorrectly pointed the animals with fewer dots. Upon familiarizing with the models, the participants were asked to use verbal or gesture clues in identifying the animal with many dots.

Findings

  The study outcomes indicated that the direction of the model influenced the definite answers of the respondents. This is because 70.7% of the definite answers were correct during the congruent trials while the 42.4% of definite answers were correct during the incongruent trials (Hellmer, Stenberg, & Fawcett, 2018). Also, the study reported a significant difference between the personalities of the conformity and non-conformity groups. In contrast, the extroversion of the parents was lower among the conformist participants as compared to the non-conformity respondents.  Additionally, the study findings failed to depict significant influences of the respondent’s personality traits on conformity although the likelihood of conforming to the trials had a negative correlation with the extroversion of the parents. However, the results did not support a positive relationship between parental conscientiousness and conformist behaviors.

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Overall, the study supports the hypothesis that children have the differences in their likelihood of conforming and the factors that motivate their conformity and the difference are highly related to the personality traits of the parents.  In the case of motivation,  the researchers concluded that normative motivation which was described as looking for the correct answers are rated high on extroversion trait and lower on the openness trait.

Social Media And Peer Influence

The 2018 research article published in the Journal of Child Development explores the association between social media usage and behaviors in young adults.  In particular, the primary purpose of this study was to evaluate assessable behavioral results of cohort influence on social media and the neural courses causing the observed effects.   The specific objectives of this study include assessing the link between age and cognitive responses to influences and examining the difference cognitive reactions to the neutral and risky contents. The study targeted 18 female students and 16 male leaners (Sherman, Greenfield, Hernandez, & Dapretto, 2018). The respondents were recruited from the Los Angeles community via message boards and flyers. Upon providing their consent, the respondents were examined to make sure that they had not been suffering from psychiatric, development or neurological disorders.

Method

The researchers conducted an experiment where they asked all participants to share photos from their Instagram accounts.  The respondents were made to believe that the shared images will be utilized to produce an core social network and they were to see the photos in the scanner, in the same manner, they appeared in Instagram.  Also, the researchers used deception to establish the size of the audience as they told the respondents that more than 50 people had participated in the experiment. However, the respondents saw their customized images and the customized images chosen by the study panel from the freely available pictures on Instagram. Photographs were categorized into three groups including risk images which depicted drug abuse and partying behaviors, neutral images consisting of images of typical teens from social media websites, and the comparable images obtained from the profiles of the respondents. The research team categorized images into popular and unpopular value depending on the number of likes of each image. Also, half of the respondents’ pictures were allocated many likes while the remaining half was allocated few likes.  Next, the participants viewed the image and decided whether they liked each image. Upon completing the experiment, the respondents completed the revised cognitive appraisal of a risky event questionnaire which consisted of two sections including risk and benefits and past experiences.  Stata Version 14.1 was used to analyze the recorded behavioral data.

Findings

The study outcomes indicate that respondents were more likely to like images with many likes as compared to the photos with fewer likes. This trend was apparent despite the content of the photos since participants did not discriminate risky, neutral or comparable images when deciding the photos to like. However, the researchers observed different brain responses to risky and neutral photos. In particular,  the respondents showed reduced activities in the frontal brain control region when viewing risky images as compared to brain activity of intrigued by neutral photos. These findings support the study hypothesis that high school learners were more probable to like well-liked pictures and ignore unpopular photos. 

Also, the study found out that respondents showed more activation in both rights and left NAcc when observing their photos that had lots of likes as compared to the time when they view images with fewer likes. In this case, the students demonstrated greater activation in major brain regions when seeing popular photos as compared to the unpopular images. These areas include social reward areas such as Caudate, Orbitofrontal Cortex, and NAcc, the social cognition system including the Precuneus and medial prefrontal cortex, and the visual attention section such as the occipital cortex.

Besides, the study found out that age played a critical role in the brain responses of the respondents. This is because an increase in age resulted in greater NAcc responses for the photos with lots of likes as compared to images with fewer likes.  These outcomes supported the pre-study hypothesis that NAcc thoughtfulness to the rewarding incentives upsurges in the adolescent development stage and it peaks at about 16 to 17.years.

References

  • Borghuis, J., Denissen, J. J., Oberski, D., Sijtsma, K., Meeus, W. H., Branje, S., … & Bleidorn, W. (2017). Big Five personality stability, change, and codevelopment across adolescence and early adulthood. Journal of personality and social psychology, 113(4), 641.
  • Hellmer, K., Stenberg, G., & Fawcett, C. (2018). Preschoolers’ conformity (and its motivation) is linked to own and parents’ personalities. British Journal of Developmental Psychology.
  • Sherman, L. E., Greenfield, P. M., Hernandez, L. M., & Dapretto, M. (2018). Peer influence via instagram: Effects on brain and behavior in adolescence and young adulthood. Child development, 89(1), 37-47.

 

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