Assessing the Relationship Between the Personality Trait Extraversion and Resilience Using a Pearsons Correlation.
Assessing the Relationship Between the Personality Trait Extraversion and Resilience Using a Pearsons Correlation.
Abstract
A sample of 23 participants from Wrexham University studying
psychology, completed two psychometric questionnaires assessing resilience and the
Five-Factor personality trait model (Openness, Conscientiousness, Extraversion,
Agreeableness, Neuroticism). Data analysis was conducted using SPSS statistical
software. Including assessing the reliability of the scales, testing for
normality, and conducting a Pearson correlation analysis to explore the
relationship between extraversion and resilience. The findings indicated a
positive correlation between extraversion and resilience. This study
contributes to a deeper comprehension of the relationship between resilience
and the personality trait of extraversion. To improve this study for future
research longitudinal studies, a multi-method approach or test-retest
assessments on the same participants could gain greater insight to personality
traits and extraversion.
Key
words: Extraversion,
Resilience, The Five-Factor Model, Brief Resilience Scale, Pearsons Correlation.
Word count: 3271
Assessing
the Relationship Between the Personality Trait Extraversion and Resilience
Using a Pearsons Correlation.
Personality is defined as distinctive and enduring patterns
of human behaviour, such as thoughts and emotions that individuals encounter
(Das & Arora, 2020). Recognized as fundamental psychological constructs
(Michalska et al., 2023), personality traits are influenced by both genetic and
environmental factors (Vize et al., 2023). These traits represent consistent
patterns of emotions, behaviours, and thoughts that distinguish individuals,
offering insights into various aspects of life including psychopathology,
interpersonal relationships, academic performance, and professional experiences
(Michalska et al., 2023). Instruments like the Five-Factor Model aid in the
exploration of an individual's personality (Michalska et al., 2023).
The Five-Factor Model offers a structured approach to define
individual differences (Michalska et al., 2023), probing into an individual's
approach towards life and their responses to challenges (Das & Arora,
2020). Each person possesses unique personality traits that partly determine
their reactions to diverse life circumstances (Hähnchen, 2022). The Five-Factor
model is widely acknowledged and studied and is used as a psychometric tool for
personality analysis (Buecker, 2020). This model that is used universally
(Boyle, 2008), suggests personality can be determined by five factors (Das
& Arora, 2020). It suggests that this hierarchal model of personality can
be categorised in five bipolar factors: Extraversion vs. Introversion, Openness
vs. Closedness, Spontaneity vs. Conscientiousness, Hostility vs. Agreeableness,
and Stability vs. Neuroticism (Gosling et al., 2003). These five dimensions can
aid in predicting specific behaviours such as academic performance and health
outcomes (Cuartero & Tur, 2021).
Extraversion is a personality trait, individuals who are classified
as extroverts normally enjoy pleasure from social interactions (Hähnchen,
2022). They tend to have characteristics like confidence, sociability, being
talkative, and assertiveness. Moreover, they often exhibit psychological
attributes such as optimism, enthusiasm, and high self-esteem (Hähnchen, 2022).
Extraversion was first found by Carl Jung in 1912 and later made as a trait by
Eysenck in 1947 (Hähnchen, 2022), the term extraversion underwent a factor
analysis, with goodness-of-fit tests affirming its inclusion in the Five-Factor
Model of Personality (Bowden-Green et al., 2020).
The opposite of extraversion is introversion. Studies
suggest that they have different neurological responses (Bowden-Green et al.,
2020). While both extraverts and introverts have similar levels of the pleasure
neurotransmitter dopamine, introverts often rely on acetylcholine, which is another
neurotransmitter that is associated with inward reflection (Granneman, 2015).
Introverts find energy in their inner world, facilitating deep reflection and deep
focus on tasks (Sahi & Raghavi, 2016). This may contribute to their
preference for solitude (Granneman, 2015). Frisk et al. (2021) proposed that
extraverts exhibit increased grey matter in brain regions such as the amygdala
and the orbitofrontal cortex, located in the frontal lobes. Research on
extraversion has highlighted the role of the medial orbitofrontal cortex in
decision-making processes (Bowden-Green et al., 2020; Frisk et al., 2021).
Resilience is defined as the ability to overcome barriers
and deal with problems in adverse situations, enabling an individual to deal
with unexpected events (Oshio et al., 2018). An individual acquires resilience
through a dynamic process where personal factors are acquired that protect the
individual (Cuartero & Tur, 2021). These factors help the individual to
overcome stressful situations and positively adapt to their surroundings
(Cuartero & Tur, 2021). Resilience can be found in individuals who strive for
good outcomes and overcome serious threats when trying to achieve a goal
(Hähnchen, 2022). Studies suggest that having high levels of resilience can
protect individuals from loneliness and psychological distress (Chernova et
al., 2021).
Individuals with higher levels of resilience often show
improved mental health, greater well-being, and reduced levels of anxiety
(Chernova et al., 2021; Ercan, 2017). They possess the ability to establish a
balance, whether biological or psychological, when confronted with challenging
circumstances. Moreover, individuals with heightened resilience demonstrate
increased courage, self-esteem, and adaptability (Foumaret al., 2015; Das &
Arora, 2020). Research suggests that resilience may correlate with
extraversion, as resilience plays a crucial role in adapting to social
conditions and maintaining positive mental health (Nakaya et al., 2006).
Individuals who navigate difficult life circumstances with relative ease tend
to show elevated levels of resilience (Hähnchen, 2022).
Several studies utilizing the Five-Factor Model have
investigated the association between personality traits and resilience in young
adults. One study involving 150 individuals aged 18-25 years revealed a
significant positive correlation between resilience and extraversion,
indicating that those with well-adjusted personality traits tended to score
higher on the resilience scale (Das & Arora, 2020). Similarly, research
focusing on women found a significant positive relationship between
extraversion and resilience, suggesting that higher levels of extraversion were
associated with increased resilience (Foumani et al., 2015).
Another study examining students also provided evidence
supporting a positive correlation between extraversion and resilience
(Hähnchen, 2022). These findings align with previous research indicating a
positive association between extraversion and resilience among adolescents
(Nakaya et al., 2006). Furthermore, the study conducted by Das & Arora
(2020) with young adults echoed these results, indicating that higher levels of
extraversion were linked to greater resilience. Overall, these studies collectively
suggest a positive relationship between resilience and extraversion. However,
further research is warranted to deepen our understanding of this association.
The report will investigate the relationship between
extraversion and resilience to determine whether extroverts have higher levels
of resilience compared to introversion. The literature review suggests that
there is a positive correlation between extraversion and resilience, therefore
supporting this research hypothesis. The findings from this study will enhance
existing research in this area, contributing to a deeper understanding of the
association between personality traits and resilience.
Method
The research will take a lexical approach as personality
research has relied on this method as a guide in choosing their variable
selection. The Five-Factor Model of personality was acquired by research based
on a lexical approach (Ashton & Lee, 2005). The study will utilize
ontological objectivism and epistemological positivism as frameworks. This
means that the study will focus on analysing language and words to understand
personality traits such as extraversion and resilience.
Ontological objectivism suggests that personality traits
like extraversion and resilience have objective properties that can be measured
(Bahari, 2010). Epistemological positivism uses empirical evidence and
scientific methods to gain knowledge about objective realities (Bahari, 2010).
Therefore, the research will rely on empirical data and statistical analysis to
investigate the relationship between extraversion and resilience, sticking to
the principles of positivism. These approaches aim to ensure a systematic and
rigorous examination of the research question (Boyle, 2008).
Participants
The sample comprised of 23 students
from the UK. All participants were over the age of 18 but further demographic
information was not obtained because it not deemed necessary for this research.
Participants were selected by a convenience sampling method from the psychology
students studying the module PSY513. Participation was voluntary and no participants
were excluded from the study. Participants were recruited via the University
VLE platform.
Design
There were two continuous variables:
resilience and extraversion. Participants were within-subjects and a convenience
sample was used. A quantitative approach was used, and the data was analysed by
a statistical software called SSPS which is used in social sciences to conduct
analysis on data collected (George & Mallery, 2019). A Correlational Design
was used to check for a relationship between the personality trait extraversion
and resilience. A Correlational Design aims to investigate the relationship between
two variables used on continuous variables (Ercan, 2017). A Pearsons Correlation
was calculated to examine the relationship between extraversion and
resilience.
Measures / Stimuli / Materials
The participants were asked to
complete two validated standardised psychometric questionnaires. The Brief
Resilience Scale (BRS) was used because it is a reliable means for assessing
resilience (Rodríguez-Rey et al., 2016; Smith et al., 2008). The scale
consisted of 6 questions including positively and negatively worded items. Items
were scored on a 5-point Likert scale which had a number range of 1-5; 1 being
low resilience and 5 being high resilience. Statements included were: ‘I tend
to bounce back quickly after hard times’ and ‘It is hard for me to snap back
when something bad happens’. Participants could respond on a 5-point-scale by
picking either Strongly Disagree, Disagree, Neutral, Agree or Strongly Agree
(Rodríguez-Rey et al., 2016; Smith et al., 2008).
The Five-Factor Model was used as
recent literature suggests this is a reliable way of assessing personality
(Ziegler, 2019). This is a test designed to assess personality using 5 categories:
Openness, Conscientiousness, Extraversion, Agreeableness and Neuroticism.
Participants were asked 44 questions (Khosbayar et al., 2022). Participants
responded on a 5-point-scale by picking either Strongly Disagree, Disagree,
Neutral, Agree or Strongly Agree. The questionnaires took approximately 10
minutes to complete. Examples of some questions regarding extraversion on the
scale ‘Is talkative’ and ‘is full of energy’ (Khosbayar et al., 2022).
Procedure
An invitation was distributed via the
University VLE, the procedure was voluntary. An information sheet was given out
along with the consent form for informed consent to be taken. Demographic data
was not collected as there was no need to collect this information at this time.
Participants completed 2 validated questionnaires. Participants were given a
personal ID number and debriefed after the questionnaires were completed. They
were signposted to the relevant bodies in case of any resulting harm or distress
caused. Information about the study and its outcome was given to the participants
once the research was completed.
When conducting data analysis in SPSS, it's
important to note that certain questions in the resilience scale and
extraversion scale were reverse-coded. In the resilience scale, Questions 2, 4,
and 6 were reverse-coded. Similarly, in the extraversion scale, Questions 6,
21, and 31 were reverse-coded. This means that the scoring for these questions
was reversed, with higher scores indicating lower levels of resilience or
extraversion. Therefore, when analysing the data, it's essential to ensure that
the reverse-coded items are appropriately accounted for to avoid
misinterpretation of the results.
Ethical Considerations
The Participants were given an information sheet and asked to sign a
consent form prior to taking part in the study. This was to ensure they were
aware of the purpose of the study and how their personal data would be
collected, stored and used. There was no persuasion or coercion in completing
the questionnaire. All participants gave informed consent and have
self-dedication of completing questionnaires. All information was taken in line
with current General Data Protection Regulations (GDPR) (Laybats, & Davies,
2018). Information was stored within the guidelines of the data protection act (Laybats,
& Davies, 2018) and the BPS code of ethics and conduct (Oates, 2020). Ethical
approval was granted by the Wrexham University Research Ethics Sub-committee. Researchers
will show professional accountability and use their knowledge and skills to
respect the welfare of any individuals taking part (Oates, 2020). Once the
questionnaires were complete, a debrief took place. The study was low risk and
unlikely to cause harm or distress to researchers or participants, however, were
there any concerns or issues there was relevant signpost information provided.
Results
Table 1
Descriptive Statistics and Correlations scale properties
|
Scale |
N |
Min |
Max |
Mean |
SD |
Alpha |
|
Extraversion |
23 |
12 |
34 |
24.39 |
6.45 |
.89 |
|
Resilience |
23 |
1.84 |
4 |
2.88 |
.61 |
.68 |
The data was analysed using a
normality test, reliability and a Pearsons Correlation. A normality test was
conducted for the resilience scale score which was normally distributed. The
Kolmogorov-Smirnov test of normality generated a significance of 0.20. A
Shapiro-Wilk analysis was also conducted which produced a significance of 0.55;
anything above 0.05 means the data is normally distributed. Normality tests
were conducted for the extraversion scale. The Kolmogorov-Smirnov test of
normality produced a significance of 0.20. A Shapiro-Wilk analysis was also conducted
which gave a result of 0.53. This means it is normally distributed. All
assumptions were met, so a parametric test was the most appropriate method of
analysis.
Cronbach’s Alpha is used to measure internal consistency of
a scale and is rated from 0-1. With 0 being poor internal consistency and 1
being excellent internal consistency (Bujang et al., 2018; Tavakol &
Dennick, 2011). An acceptable score for the reliability scale is 0.7 (Cortina,
1993). The resilience scale was calculated using the Cronbach’s Alpha
reliability test and had (a=0.68). The reliability for the extraversion scale
(a=0.89) was calculated when computing a Cronbach’s Alpha.
A correlation comprises of
measuring a positive or negative relationship between two variables (Obilor
& Amadi, 2018). To measure this, a correlation coefficient is used to
measure the magnitude and direction of the relationship (Obilor & Amadi,
2018). The magnitude consists of low or high scores. The direction of the
correlation can be either positive or negative; -1 would indicate a perfect
negative, whereas 1 will indicate a perfect positive correlation. Correlation
coefficients that are lower than 0.40 are low, whereas 0.40 to 0.60 are
moderate and 0.6 and above is high (Obilor & Amadi, 2018). Pearson’s
Correlation revealed that there was a small positive correlation between
extraversion and resilience.
r (21) = 0.27, 95% CI [-0.16, 0.62], p
< 0.206. A score between 0.2-0.3 in a Pearsons Correlation is deemed to be a
weak positive relationship between the variables.
Discussion
The aim of this research was
to investigate the correlation between extraversion and resilience. The
findings suggest a weak positive correlation between extraversion and
resilience. Previous studies have found significant correlations between
resilience and extraversion in young adults (Das & Arora, 2020; Nakaya et
al., 2006), with some indicating that women, who tend to show higher levels of
extraversion, may also show greater levels of resilience (Chernova et al.,
2021). Additionally, studies focusing on students have similarly reported
positive correlations between resilience and extraversion (Hähnchen, 2022).
While the current study's findings align with existing literature regarding the
positive correlation between these variables, it's noteworthy that the
correlation observed in this study was weaker compared to previous research. However,
results support the research hypothesis by confirming that there is a
correlation between resilience and extraversion. Further research with larger
sample sizes may provide additional insights into the relationship between
extraversion and resilience.
The Five-factor Personality
Test is widely used in personality research, but it has limitations, such as
how broad the trait definitions are. Future research should consider
cross-cultural research and language barriers. An optimal model of the
five-factor model of factor analysis is still to be acquired (Boyle, 2008).
This model hopefully will replicate cross-cultural generalisability and be
comprehensive (Boyle, 2008). It is believed that there are many other
personality traits for example honesty, thriftiness, humour, deceptiveness, and
religiousness are just a few to name (Boyle, 2008). These factors should warrant further exploration in future
research.
It's important to
acknowledge that the study's sample consisted only of psychology students,
which may limit the generalizability of the findings to the broader population
(Ferguson, 2004). Psychology students may show certain characteristics or
experiences that distinguish them from the general population. Future research
could aim to replicate the study using a more diverse sample, having
individuals from various backgrounds and demographic groups, to ensure greater
generalizability of the findings (Ferguson, 2004). Demographic data was not
included in the present study, future research could benefit from having this
information to explore differences across gender, age, race, and other
demographic variables. Examining demographic differences can provide valuable
insights into how personality traits and resilience may vary among different
groups within the population.
The study solely relied on self-report assessments to
evaluate personality traits and resilience, which may cause biases (Sleep et
al., 2021). The use of self-report measures alone can be susceptible to social
desirability bias, this is where participants may respond in a manner that they
think is socially acceptable rather than accurately reflecting their true
thoughts and behaviours (Tutzer et al., 2021). To enhance the accuracy and
validity of future studies, researchers could consider incorporating both
qualitative and quantitative research methods. Qualitative methods, such as
interviews or observations, can provide deeper insights into participants'
experiences and perspectives which will complement the quantitative data
obtained through self-report measures. This multimethod approach can decrease
the biases associated with self-reporting and offer a more comprehensive
understanding of personality traits and resilience (Mik-Meyer, 2020).
Although personality traits
tend to stay stable and are quite accurate, there could be response biases
(Bowden-Green et al., 2020). for example, an individual may be more willing to
provide inaccurate answers to the questionnaire that allow self-evaluation to
‘look better’ (Benjamin, 2015). This could cause inaccurate reporting leading
to inaccurate results. Social Desirability Bias is where participants will
respond in a way that they believe to be socially desirable. They will
disregard their own true thoughts, feelings and behaviours, leading to
overreporting or underreporting (Vesely & Klöckner, 2020). To reduce biases
in research validated and reliable measures should be used (Vesely &
Klöckner, 2020).
Tendencies to constantly
agree to questions in a questionnaire without thinking about the item in
context and not correctly reporting can occur in self-reported tests (Costello
& Roodenburg, 2015). This type of response bias is called acquiescence. Acquiescence
is a response bias where an individual consistently agrees with statements or
items presented in a questionnaire regardless of what their beliefs or
experiences are. This can skew the results of personality assessments, leading
to inaccurate or misleading answers of an individual's characteristics.
Reverse-scored items can help identify acquiescent response biases and improve
reliability of the data (Rammstedt & Farmer, 2013). Cognitive differences like verbal ability or reading
ability may also affect the results by forming an educational bias. If an
individual struggles to read or understand the question posed, they may give a
misleading response or be more likely to respond acquiescently (Rammsted &
Kemper, 2011; Morales-Vives et al., 2017).
Biases can be problematic
for researchers. The problems can be reduced by implying a source of error to
the measurement like reverse scoring (Costello & Roodenburg, 2015).
Personality self-reports requires items of the questionnaire to be worded
opposite to other items to identify if someone is acquiescent (Morales-Vives et
al., 2017). Personality self-reports could be subjected to response bias which
could lead to factor structure. Research implies that acquiescence occurs due
to social desirability, increasing with age and individuals with little
education which could affect their reliability (Costello & Roodenburg,
2015; Morales-Vives et al., 2017; Rammstedt & Kemper, 2011).
Future research could also
explore conducting a test-retest assessment with the same participants to
evaluate the validity and reliability of scores, which will also enhance the
robustness of the findings (Sleep et al., 2021). Such an approach would enable
researchers to show certainty whether resilience and extraversion scores show
to be stable over time or undergo changes. Additionally future studies could
consist of longitudinal research designs that could be employed to examine the
development of personality traits over time. Existing research suggests that
traits such as emotional stability, extraversion, and openness tend to increase
as individuals age (Cuartero & Tur, 2021). Therefore, longitudinal studies
would provide insights of these traits across the lifespan. The study has built
up on existing literature and improvements for future research has been
suggested for this study and in-depth detail has been used to describe the
process of the study so replication can take place in future if needs be.
Personality is defined as unique
distinctive patterns of human behaviour that individuals experience.
Personality traits are categorized as essential psychological constructs.
Personality tests such as the Five-Factor Model can assist in exploring an individual’s
personality. The Five-Factor Model provides a systematic way to define these
differences. Resilience is the ability to overcome barriers and deal with
problems in adverse situations, enabling an individual to deal with unexpected
events. Previous studies suggest that extraversion is related to resilience.
The current study found extraversion to be positively correlated with high
levels of resilience. Future studies could complete a test-retest for
reliability and validity. Alternatively, they can undergo a multi-method
approach or a longitudinal study to see personality and resilience changes
after a certain period of time.
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desirability in environmental psychology research: Three meta-analyses. Frontiers
in psychology, 11, 1395. doi: 10.3389/fpsyg.2020.01395.
Vize, C. E., Sharpe, B. M., Miller, J. D., Lynam, D. R., & Soto,
C. J. (2023). Do the Big Five personality traits interact to predict life
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Appendix
[1]PositivePsychology.com |
Positive Psychology Toolkit
The Brief Resilience Scale
Resilience is often studied in
the field of Positive Psychology. However, “resilience” has been defined in
different ways. The Brief Resilience Scale (Smith et al., 2008) assesses the
original and most basic meaning of the word resilience. The root of the English
word “resilience” is the word “resile,” which means “to bounce or spring back”
(from re- “back” + salire - “to jump, leap”; Agnes, 2005). In line with this
definition, this scale assesses the ability to bounce back or recover from
stress. Higher scores on the scale are negatively related to anxiety,
depression, negative affect, and physical symptoms.
Goal
This questionnaire was designed
to assess the ability to bounce back or recover from stress.
Advice
■Given the brief nature of this questionnaire,
it is very suitable for administering during multiple moments while conducting
therapy/coaching sessions to track progress in terms of resilience.
Scoring
To compute the score, first
reverse the scores of items 2, 4, and 6. Reversing a score is done by
exchanging the original value of an item by its opposite value: a score of 1
becomes a score of 5, a score of 2 becomes a 4, and so on. Subsequently, add up
all the individual item scores. A weighted score can be calculated by dividing
the total score by the number of items, in this case, 6. Higher scores reflect
more resilience.
References
■Smith, B. W., Dalen, J.,
Wiggins, K., Tooley, E., Christopher, P., & Bernard, J. (2008). The brief
resilience scale: assessing the ability to bounce back. International Journal
of Behavioural Medicine, 15, 194-200.
AssessmentResilience2 minClientYe
s
[2]PositivePsychology.com | Positive Psychology Toolkit
The Brief Resilience Scale
Instructions
To the left of each item,
indicate how much you disagree or agree with each of the statements, using the
following scale:
1 Strongly disagree
2 Disagree
3 Neutral
4 Agree
5 Strongly agree
1 I tend to bounce back quickly after hard times.
2r I have a hard time making it through stressful events.
3 It does not take me long to recover from a stressful event.
4r It is hard for me to snap back when something bad happens.
5 I usually come through difficult times with little trouble.
6r I tend to take a long time to get over setbacks in my life.
How I am in general
Here are a number of
characteristics that may or may not apply to you. For example, do you agree that you are
someone who likes to spend time with
others? Please write a number next
to each statement to indicate the extent to which you agree or disagree with that statement.
|
1 Disagree Strongly |
2 Disagree a little |
3 Neither
agree nor
disagree |
4 Agree a little |
5 Agree strongly |
I am someone who…
1.
_____ Is talkative
2.
_____ Tends to find fault with others
3.
_____ Does a thorough job
4.
_____ Is depressed, blue
5.
_____ Is original, comes up with new ideas
6.
_____ Is reserved
7.
_____ Is helpful and unselfish with others
8.
_____ Can be somewhat careless
9.
_____ Is relaxed, handles stress well.
10.
_____ Is curious about many different things
11.
_____ Is full of energy
12.
_____ Starts quarrels with others
13.
_____ Is a reliable worker
14.
_____ Can be tense
15.
_____ Is ingenious, a deep thinker
16.
_____ Generates a lot of enthusiasm
17.
_____ Has a forgiving nature
18.
_____ Tends to be disorganized
19.
_____ Worries a lot
20.
_____ Has an active imagination
21.
_____ Tends to be quiet
22.
_____ Is generally trusting
23.
_____ Tends to be lazy
24.
_____ Is emotionally stable, not easily upset
25.
_____ Is inventive
26.
_____ Has an assertive personality
27.
_____ Can be cold and aloof
28.
_____ Perseveres until the task is finished
29.
_____ Can be moody
30.
_____ Values artistic, aesthetic experiences
31.
_____ Is sometimes shy, inhibited
32.
_____ Is considerate and kind to almost everyone
33.
_____ Does things efficiently
34.
_____ Remains calm in tense situations
35.
_____ Prefers work that is routine
36.
_____ Is outgoing, sociable
37.
_____ Is sometimes rude to others
38.
_____ Makes plans and follows through with them
39.
_____ Gets nervous easily
40.
_____ Likes to reflect, play with ideas
41.
_____ Has few artistic interests
42.
_____ Likes to cooperate with others
43.
_____ Is easily distracted
44.
_____ Is sophisticated in art, music, or literatur
SCORING
INSTRUCTIONS
To score the
BFI, you’ll first need to reverse-score all negatively keyed items:
Extraversion:
6, 21, 31
Agreeableness:
2, 12, 27, 37
Conscientiousness:
8, 18, 23, 43
Neuroticism:
9, 24, 34
Openness:
35, 41
To recode
these items, you should subtract your score for all reverse-scored items from
6. For example, if you gave yourself a 5, compute 6 minus 5 and your recoded
score is 1. That is, a score of 1 becomes 5, 2 becomes 4, 3 remains 3, 4
becomes 2, and 5 becomes 1.
Next, you
will create scale scores by averaging the following items for
each B5 domain (where R indicates using the reverse-scored item).
Extraversion:
1, 6R 11, 16, 21R, 26, 31R, 36
Agreeableness:
2R, 7, 12R, 17, 22, 27R, 32, 37R, 42
Conscientiousness:
3, 8R, 13, 18R, 23R, 28, 33, 38, 43R
Neuroticism:
4, 9R, 14, 19, 24R, 29, 34R, 39
Openness: 5,
10, 15, 20, 25, 30, 35R, 40, 41R, 44
SPSS SYNTAX
*** REVERSED ITEMS
RECODE
bfi2 bfi6 bfi8 bfi9 bfi12 bfi18 bfi21 bfi23
bfi24 bfi27 bfi31 bfi34 bfi35
bfi37 bfi41 bfi43
(1=5)
(2=4) (3=3) (4=2)
(5=1) INTO bfi2r bfi6r bfi8r bfi9r bfi12r bfi18r bfi21r
bfi23r bfi24r
bfi27r bfi31r bfi34r bfi35r bfi37r bfi41r
bfi43r.
EXECUTE
.
*** SCALE SCORES
COMPUTE
bfie = mean(bfi1,bfi6r,bfi11,bfi16,bfi21r,bfi26,bfi31r,bfi36) .
VARIABLE
LABELS bfie 'BFI Extraversion scale score.
EXECUTE
.
COMPUTE
bfia = mean(bfi2r,bfi7,bfi12r,bfi17,bfi22,bfi27r,bfi32,bfi37r,bfi42) .
VARIABLE
LABELS bfia 'BFI Agreeableness scale score' .
EXECUTE
.
COMPUTE
bfic = mean(bfi3,bfi8r,bfi13,bfi18r,bfi23r,bfi28,bfi33,bfi38,bfi43r) .
VARIABLE
LABELS bfic 'BFI Conscientiousness scale score' .
EXECUTE
.
COMPUTE
bfin = mean(bfi4,bfi9r,bfi14,bfi19,bfi24r,bfi29,bfi34r,bfi39) .
VARIABLE
LABELS bfin 'BFI Neuroticism scale score' .
EXECUTE
.
COMPUTE
bfio = mean(bfi5,bfi10,bfi15,bfi20,bfi25,bfi30,bfi35r,bfi40,bfi41r,bfi44) .
VARIABLE
LABELS bfio 'BFI Openness scale score' .
EXECUTE .
REFERENCE
INFORMATION
John, O. P.,
Donahue, E. M., & Kentle, R. L. (1991). The Big Five Inventory--Versions 4a
and 54.
John, O. P., Naumann, L. P., & Soto,
C. J. (2008). Paradigm shift to the integrative Big Five trait taxonomy:
History, measurement, and conceptual issues. In O. P. John, R. W. Robins, &
L. A. Pervin (Eds.), Handbook of personality: Theory and research (pp.
114-158).
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