Module Project: Factor Analysis of Personality Data Performing the Factor Analysis,

Module Project: Factor Analysis of Personality Data Performing the Factor Analysis, Methodology, and Results

Name: Jimmy Petruzzi
MSC Mental health psychology LPSY-302-5
LPSY 316: Personality, Individual Differences, and Intelligence

Participants included 1006 people aged from 9 years of age to 12 years of age. Equal distribution of male and females, residing in the Nunavut state in Canada. In accordance to the Canada School of Public Service Act, primary and secondary school attendance in Nunavut state is compulsory, part of the selection criteria was based on levels of school attendance. Participants were excluded if they had above unauthorised absenteeism above legal school attendance.
Participants parents and caregivers were requested to provide information on employment status in order for the questionnaire participation to reflect society to increase social validity.
In designing the questionnaire we took into consideration the variable factors which can impact the reliability of a participation response, factors such as interpretation of the question, the participants cognitive ability and motivation during the test.
The following research Gurven, Rueden, Massenkoff,Kaplan, Vie,(2013) indicated limitations of the FFM when administered amongst a rural community in Bolivia, the questionnaire was translated, though it appeared literacy was amongst the correlating factors impacting the reliability of the questionnaire, the significance of this research was the FFM has been demonstrated to be more reliable in developed nations, whilst this is not a direct correlating factor amongst our participants in the Intuit community it did suggest taking this and previous research into consideration about adapting the FFM for the adolescents participants.
We produced a modified sample questionnaire, parent or carer consent was authorised to conduct an initial modified version of the questionnaire. The questionnaire was trialled amongst 124 participants, equal distribution of male and female, the age ranges between 9 years of age to 12 year of age. Upon modification and administration of the modified Questionnaire and an evaluation of the data. A 25-item questionnaire, Costa and McCrae (1992) was developed to measure the Big Five personality factors in Inuit children in Canada.
Five items were taken from each of the five IPIP scales that measure the Big Five personality factors, adapting them where necessary so that they would be relevant to the lives and cognitive abilities of 9-year-old to 12-year-old Inuit children and translating them into the Inuktitut language.
Using the FFM Inventory developed by Costa and McCrae (1992), as a platform to develop a 25- Item questionnaire procured from the IPIP, utilising a five point Likert scale.
The participants completed the questionnaire with paper and black pen, SPSS program and software was used to implement the, Factor Analysis and PCA, the parallel analysis implemented with the e O’Connor learning resource
Informed consent was compulsory from parents and caregivers of the participants as the participants age range was 9 years of age to 12 years of age. The questionnaire was administered to the participants on the 23rd of June 2018 at 930am on commencement of the morning classroom lesson, the test was conducted in the school classrooms and the young people remained anonymous. The participants were instructed not to discuss questions with other participants, any questions could be discussed with study supervisors which could also speak intuit language
The duration for completion of the questionnaire, was in line with the duration of the compulsory education morning framework in Canada, which is approx. 2 hours and 30 minutes, as the questionnaire was designated during academic term time, minimal disruption to designated lesson, students returned to the usual class on completion.
The content of the questionnaire was the same for all participants, research by Goldberg (2001) suggests the FFM can be adapted successfully for the administration to suit the cognitive abilities of the participant’s, in accordance and consideration of research by Goldberg (2001) the questionnaire was adapted to suit the cognitive abilities of the participants and translated from English into Intuit language to ensure increased validity and reliability in measurements.
The object of the PCA was to Identify the eigenvalues, there after utilizing the eigenvalues to conduct a scree test. We also conducted the Kaiser-Guttman test to define the number of factors, although we were uncertain about the accuracy of the data. We proceeded in utilizing the O’Connor resource and conducted a parallel analysis ( which can be referred to in the appendix)
Once we identified the number of factors using the O’Connor resource, based on the number of factors we had discovered in our data, we were able to conduct a Factor Analysis with Oblique Rotation using oblimin utilising SPSS software ( the SPSS data can be referred to in the appendix)
Having conducted the PCA, the data indicated the first 6 components having an eigenvalue > 1.0.
The Mean eigenvalues we identified as 1.297, 1.252, 1.217, 1.189, 1.163, 1.137 see Table 2: below
Extraction Method: Principal Component Analysis.
Factor Critical value eigenvalue Variance % Cumulative %
1 1.297 2.160 8.641 8.641
2 1.252 2.114 8.456 17.098
3 1.221 1.893 7.571 24.668
4 1.189 1.703 6.810 31.478
5 1.163 1.642 6.569 38.047
6 1.137 1.064 4.258 42.305

Table 2: Parallel-test of Eigenvalues
Having identified the list of eigenvalues we performed a scree test.
Figure-02: Scree-plot of unrotated PCA-test (please see index for scree plot diagram )
According to Field (2013) the inflection point of retaining factors is above the curve which can be identified on the Scree plot graph. The point of inflexion is where the slope of the line changes dramatically, our findings demonstrated six factor-items loading at point of inflection at component 7, amongst components of the IPIP-25-item questionnaire 2.160,2.114,1.893,1.703,1.642 please see Table-03:
According to Stevens (2002) the Scree plot is relatively reliable in providing data for factor selection in samples of 200 participants or more, we had 1006 sample so we were confident in our data collected factor selection.
Rotated Principle analysis
Initial eigenvalues Loadings rotations
Factor total cumulative% total cumulative% total
1 2.160 8.641 1.411 5.642 1.375
2 2.114 17.098 1.370 11.121 1.359
3 1.893 24.668 1.131 15.647 1.100
4 1.703 31.478 .960 19.487 1.054
5 1.642 38.047 .866 22.952 .878

Table-03: PAF- Analysis test results
The factor rotation technique was used to differentiate between factors to interpret factor variable low and high loading with reliable extraction of data.
Upon establishing the data we ran a unrotated PCA to assist us in omitting the number of factor loads from the IPIP- 25 item questionnaire.
According to Horn (1965) we retain the factors that are higher from the research data, than the corresponding data which is run randomly.
Research by Fabrigar, & Wegener,(2012) was significant in our decision to utilised an oblique rotation method, we were able to identify the highest factor loadings see Figure 4:
According to Cooper (2010), if we use an oblique rotation, we should analyse the Pattern matrix a table ( please see index) the table enabled us to identify the factor for each item which has the highest loadings The items we analysed had correlations of .4 and higher, If they are related to each other, this means there are factors underlying the items and data.

Factor Analysis with Oblique Rotation
1: Conscientiousness 2 (.524) 13 (-507) 17 (.506) 19 (.543) 22 (.519)
2: Neuroticism 5 (.430) 8 (.520) 11 (.492) 16 (.507) 24 (.476) 15 (-.407)
3: Extroversion 4 (.385) 6 (-.520) 14 (.476) 20(.404) 25 (.524)
4: openness 3(.535) 10 (.552) 23 (.508) 21 (.423)
5:agreeableness 1 (.448) 7(.448) 12 (.408) 18 (.535)

Figure 4: Relationships between factors
We identified that 25 items questionnaire had successfully measured, by the five factors we expected. After analysing the results we were able to determine, factor 1 Conscientiousness had a correlation With 2 ,13 ,17 ,19 ,22, Factor 2 neuroticism had a correlation with 5,8,11,16,24,15 ,Factor 3 had a correlation with 4,6 ,14,20,25 ,Factor 4 openness had a correlation with 3,10,23,21,factor 5 had a correlation with 1,7,12 ,18
According to Cooper (2010) a minus sign indicates a negative correlation. We were able to establish item 13 belonging to factor 1 the consciousness group had a negative value of (-507) which would indicate a question that was reverse scored. By conducting the analysis we were able to identify the responses that the participants had given to each item our specifically designed 25 questionnaire personality test.
Other Items which indicated a negative value were 6 (-.520) in the factor 3 group : Extroversion and 15 in the factor 2 group : Neuroticism (-.407) which also indicates reverse scoring questions,we were able to establish factor 2: Neuroticism had the highest level of responses from participants. We also established that factor 1: consciousness had each item scored >.5.
The item 16 (.507) loaded onto factor 2 instead of the expected factor 5, (please see in the index)
And item 9 was omitted because it was loaded onto factor 6, which did not feature on the PA test.
Using the following methods Kaiser-Meyer-Olkin and The Bartlett’s Test of Sphericity
The results from the Kaiser-Meyer-Olkin test demonstrated a value of 0.703 according to Field (2013) the minimum level is 0.6>x
The Bartlett’s Test of Sphericity result was (df 300)= ( 2152.769, p< 0.005)
(statistics table in Appendix)

Word count 1498 total
Results 871

Arthurs N et al (2014) Achievement for Students Who are Persistently Absent: Missing School, Missing Out? Urban Review. Dec2014, Vol. 46 Issue 5, p860-876. 17p.(Abstract only)
Cooper, C. (2010). Individual differences and personality (3rd ed.). London: Hodder Education. Retrieved from
Statistics Canada, Education in Canada: A Statistical Review, Ottawa, 1973-2000.
Costa, P. T., & McCrae, R. R. (1992). NEO-PI(R) professional manual. Odessa, FL: Psychological Assessment Resources.
Fabrigar, L. R., & Wegener, D. T. (2012). Exploratory factor analysis. [electronic book]. Oxford; Oxford University PressChapter 17: “Exploratory factor analysis”
Field, A. (2013). Discovering Statistics using IBM SPSS statistics (4th Eds). UK: Sage Publication.
Gurven, M., von Rueden, C., Massenkoff, M., Kaplan, H., & Vie, M. L. (2013). How Universal Is the Big Five? Testing the Five-Factor Model of Personality Variation Among Forager–Farmers in the Bolivian Amazon. Journal of Personality and Social Psychology, 104(2), 354–370.
Horn, J. L. (1965), “A Rationale and Test For the Number of Factors in Factor Analysis,” Psychometrika, 30, 179-85.
Jolliffe, I. (1986). Principal Component Analysis. Springer Verlag.
Parallel Analysis. Retrieved from
Stevens, J. P. (2002). Applied multivariate statistics for the social sciences (4th ed.). Hillsdale, NS: Erlbaum.


6 scores greater than 1

Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 2.160 8.641 8.641 2.160 8.641 8.641
2 2.114 8.456 17.098 2.114 8.456 17.098
3 1.893 7.571 24.668 1.893 7.571 24.668
4 1.703 6.810 31.478 1.703 6.810 31.478
5 1.642 6.569 38.047 1.642 6.569 38.047
6 1.064 4.258 42.305 1.064 4.258 42.305
7 .932 3.730 46.035
8 .907 3.626 49.661
9 .881 3.525 53.186
10 .866 3.462 56.648
11 .850 3.399 60.047
12 .828 3.312 63.359
13 .817 3.268 66.628
14 .805 3.221 69.848
15 .769 3.074 72.923
16 .756 3.025 75.948
17 .740 2.960 78.908
18 .727 2.907 81.814
19 .706 2.825 84.639
20 .684 2.734 87.373
21 .678 2.714 90.087
22 .668 2.673 92.760
23 .633 2.533 95.292
24 .596 2.383 97.676
25 .581 2.324 100.000
Extraction Method: Principal Component Analysis.
The factors that are above the curve ( inflection point of retaining factors
According to Horn (1965) we retain the factors that are higher from the research data, than the corresponding data which is run randomly
Component or Factor Mean Eigenvalue Percentile Eigenvalue
1 1.297120 1.335867
2 1.252433 1.283924
3 1.217893 1.246695
4 1.189013 1.212341
5 1.162260 1.184262
6 1.138026 1.159807
7 1.115636 1.137627
8 1.093496 1.114383
9 1.071495 1.088771
10 1.051154 1.068740
11 1.030922 1.048493
12 1.011218 1.027736
13 0.991996 1.008935
14 0.973965 0.989698
15 0.955395 0.970783
16 0.936674 0.953473
17 0.917567 0.934328
18 0.898220 0.915141
19 0.879027 0.896027
20 0.859719 0.877748
21 0.838560 0.856029
22 0.817029 0.835840
23 0.795043 0.814159
24 0.769624 0.792291
25 0.736516 0.765227

KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .703
Bartlett’s Test of Sphericity Approx. Chi-Square 2152.769
df 300
Sig. .000

4, 6, 14, 20, 25
5, 8, 11, 15, 24
3, 9, 10, 21, 23
1, 7, 12, 16, 18
2, 13, 17, 19, 22
Pattern Matrixa
1 2 3 4 5
19 .543
2 .524
22 .519
13 -.507
17 .506
8 .520
16 .507
11 .492
24 .476
5 .430
15 -.407
25 .524
6 -.520
14 .476
20 .404
4 .385
10 .552
3 .535
23 .508
21 .423
18 .535
1 .448
7 .448
12 .408
Extraction Method: Principal Axis Factoring.
Rotation Method: Oblimin with Kaiser Normalization.
a. Rotation converged in 4 iterations.

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Eysenck and Freud


introspection of  Eysenck and Freud

by Jimmy Petruzzi


According to Eysenck (1967) we are born with a unique temperament with a genetic basis, and personality can be measured by dimensions on a continuum. The dimensions labelled by Eysenck consist of, extraversion/introversion, neurotic/stable, and psychotic each dimension has specific traits or characteristic’s related to them.

Freud (1923) Suggested our personality is governed by our unconscious thoughts, Freud’s theory involves  what he termed the id, which is based on biological drive and desire for instant gratification which develops  up to the age of 2 or 3, then the ego is developed through external experiences, the ego distinguishes boundaries of rationality and is developed up to around 5 years of age, then modification of the ego to super ego , the super ego sculpted by experiences  develops a sense of morality. The theory is based on sexual drives, based on stages of development influencing a person’s response to stimulus represents aspects of the development of personality.

Eysenck (1967) suggested that people on the high end of the scale of extraversion are searching for stimulus due to lower levels of brain activity and the opposite is for people who are considered to be introverts.

Research by Green (1984) demonstrated how a group of introverts and extroverts participated in a mundane task, the extroverts had chosen a higher volume of music whilst participating in the task comparatively to the introverts, under their chosen music volume levels both groups had displayed task efficiency. Interestingly when the volume levels were swapped around amongst the two groups’ task efficiency had been less effective.

According to the following research Mitchell & Kumari (2016)Using MRI and DTI and assessing the evidence over the past 15 years , were able to establish  Eysenck’s  theory, examining  extraversion and introversion  had a correlation to the function of different brain regions Including cortical regions  involved in  emotion regulation including limbic regions. Suggesting neuroticism is particularly sensitive to negative emotional cues and extraversion is sensitive to positive emotional cues.

According to Eysenck (1986) he implies Freud’s theories can be classed as science and can be falsified, which a different view is than Popper (1986) who suggests Freud’s theories cannot be falsified therefore not considered scientific.

Lo, Hinds,Tung, Franz, Fan,Wang, and Chen (2017) identified genetic spectrum of correlations between certain genes and FFM personality traits.

Twin studies (Hur, 2007) demonstrates how identical  twins are more likely to  demonstrate  similar  personality traits, compared  to  fraternal twins, and biological siblings are more likely to have similar personality traits then adopted sibling’s, this is significant because it suggests that a biological foundation to personality.

According to Laurent (2015) it is Impossible to eliminate the genetic variable which could potentially correlate with Child development correlation with adult development. The empirical research around Freud’s development theory is limited subjective experience.

Revelle, 2016 suggested Eysenck’s has left a strong legacy and influence field of psychology for example the neuroticism and extraversion of the FFM

Empirical and theoretically Eysenck theories on personality are more plausible than Freud. The evidence around biology around personality is overwhelming




Eysenck, H. J. (1986). Failure of treatment–failure of theory? Behavioral and Brain Sciences, 9, 236.

Eysenck, 1967 H.J. Eysenck The biological basis of personality Thomas, Springfield, IL (1967)


Eysenck H J. The effects of psychotherapy: an evaluation. J. Consult. Clin. Psychol. 16:319-24, 1952. [Inst. Psychiatry, Maudsley Hosp., Univ. London, London, England]

The Effects of Psychotherapy: An Evaluation H. J. Eysenck (1952) Institute of Psychiatry, Maudsley Hospital University of London First published in Journal of Consulting Psychology16, 319-324.

Freud, S. (1923). The ego and the id. SE, 19: 1-66.

Hur, Y. (2007). Evidence for Nonadditive Genetic Effects on Eysenck Personality Scales in South Korean Twins. Twin Research And Human Genetics, (2), 373.


Lo, M.-T., Hinds, D. A., Tung, J. Y., Franz, C., Fan, C.-C., Wang, Y., … Chen, C.-H. (2017). Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nature Genetics49(1), 152–156.

Mitchell, R. L. C., & Kumari, V. (2016). Hans Eysenck’s interface between the brain and personality: Modern evidence on the cognitive neuroscience of personality. Personality and Individual Differences, 74-81. DOI: 10.1016/j.paid.2016.04.009

Popper, K. (1986). Predicting overt  behavior versus predicting hidden states. Behavioral and Brain Sciences, 9, 254-255.

Plomin, R., DeFries, J. C., McClearn, G. E., & Rutter, M. (1997). Behavioral genetics (3rd. ed.). New York: Freeman.

Revelle, W. (2016). Hans Eysenck: Personality theorist. Personality & Individual Differences, 10332-39. doi:10.1016/j.paid.2016.04.007

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Effects of mindfulness training on different components of impulsivity in borderline personality disorder


Effects of mindfulness training on different components of impulsivity in borderline personality disorder


Jimmy Petruzzi


Selected articles for comparison

Elices, M., Soler, J., Feliu-Soler, A., Carmona, C., Tiana, T., Pascual, J. C., … Álvarez, E. (2017). Combining emotion regulation and mindfulness skills for preventing depression relapse: a randomized-controlled study. Borderline Personality Disorder and Emotion Dysregulation, 4, 13.

Soler J, Valdepérez A, Feliu-Soler A, Pascual JC, Portella MJ, Martín-Blanco A, et al. Effects of the dialectical behavioral therapy-mindfulness module on attention in patients with borderline personality disorder. Behav Res Ther. 2012;50:150–7


Elices, M., Soler, J., Feliu-Soler, A., Carmona, C., Tiana, T., Pascual, J. C., … Álvarez, E. (2017) conducted a pilot study the application of mindfulness with patients who had a diagnosis of BPD, the study took into consideration that mindfulness  training could assist in the modification of facets of impulsivity in patients with BPD. The method for the research  was  64 subjects with BPD diagnosis were  Subjected to 10 weeks of mindfulness training, with all participants being assessed pre and post intervention measuring impulsivity and neuropsychological tasks comparing the effects of MT and IE on borderline symptons with research randomization software to ensure reliability and validity.Interviews were conducted by skilled professionals with out prior knowledge of participants who were separated in groups of 8, the patients were recruited from a out patient psychiatry unit and of 92 screened participants 64 were randomised 32 to each treatment protocol, patients were selected with a strict quality control procedure


According to Behaviour Research and Therapy Soler J, Valdepérez A, Feliu-Soler A, Pascual JC, Portella MJ, Martín-Blanco A, Alvarez E, Pérez V Behav Res Ther. 2012 Feb; 50(2):150-7  there have been measurable improvements in patients with BPD utilising mindfulness in adverse to controlled interventions measured by the  (CPT-II)

this study was conducted with patients receiving treatment along side psychiatric treatment 60 patients we recruited for this study all of them having BPD, 40 of the patients received  DBT Mindfulness and Psychiatric treatment and 20 psychiatric treatment alone,based on the CPT-II neuropsychological test the more participation of mindfulness the more improvement of psychiatric symptons , in order to be recruited the patients had to meet a BPD diagnostic criteria and recruitment was from a psychiatric hospital , the interviews consisted of two semi structured interviews , the interviews and evaluations were conducted by experienced psychologists and psychiatrists , the main variable  assessed by CPT-II, psychopathological symptom’s assessed pre and post interventions using  HRSD-17, BPRS and  POMS; mindfulness questionnaire’s were given to the patients pre and post intervention  FFMQ and (EQ,

One of the themes of DBT is utilising psycho education, teaching and making patients aware of their condition. Mindfulness is a central part of DBT, cultivating an attitude of acceptance, not resignation, though acceptance, the situation is as it is, or the feeling, then taking responsibility to change. As it stands DBT is the treatment with the most empirical evidence for Border line Personality Disorder. Due to the high impulsivity of patients with BPD utilising mindfulness could potentially help the patients become more aware and not react as impulsive.

According to the results of the following study  Jessica R. Peters, Shannon M. Erisman, Brian T. Upton, Ruth A. Baer, Lizabeth Roemer. (2011): 228-235.Mindfulness has the potential to help with impulsivity and maladaptive behaviour due to impulsivity and aspect of patients with BPD is impulsivity.


I think the study provided some interesting findings and has the potential to be further developed, the researchers took into consideration whether some of the patient had exposure to mindfulness skills before, they also took into consideration which set of skills the patients had exposure to first and how that would correlate to DBT skills training, that said a core component of DBT is mindfulness and it is likely that patients with DBT will have had exposure to mindfulness skills prior to the participation. I think one of the biggest challenges is to construct a reliable model for testing impulsivity in BPD, it appears the researchers did extremely well  to  construct a multi model of assessment and in contrast to a former study of the group  Soler J, Valdepérez A, Feliu-Soler A, Pascual JC, Portella MJ, Martín-Blanco A, Alvarez E, Pérez V Behav Res Ther. 2012 Feb; 50(2):150-7

The improvement ratio differed in the areas of inhibition, the authors point out that might have been due to other variable factors such as the  co-morbidities differential’s between bulimia nervosa ADHD , the authors explain this is why the response  delay of gratification was improved and response inhibition. Though it is important to note ADHD was not directly assesses and going off the   CPT-II only a relative small proportion of the group 14 percent had 70 percent ADHD symptomology, I think it is important that future studies do incorporate variable BPD profiles which factor in the co-morbidities ratios and in the way the MT is applied

  1. Giluk, (2009)has demonstrated correlations between mindfulness and the impulsive aspect of DBT, though to date there is not much evidence to support mindfulness interventions on impulsivity related to BPD. I think one of the challenges of both studies would be the spectrum of low attention deficit in patients with DBT and the ability to partake and sustain a program of mindfulness which has a core base of awareness and being present.

Lars Schulze,(2016) conducted a study from a biological perspective of patients from BPD , pooling data from 19 published studies, and they reported structural differences in the Amygdala and pre frontal cortex, these are important findings because, it would suggest that depending on the severity and spectrum of biologically differences each person is going to respond in a different way. Hence I believe it is a challenge to monitor the effects of mindfulness on patients diagnosed with DBT,

Though I think with the benefit of technology, if a study could be conducted to assess structural changes to the brain, this may be a more accurate way to monitor improvements from treatment.





Elices, M., Soler, J., Feliu-Soler, A., Carmona, C., Tiana, T., Pascual, J. C., … Álvarez, E. (2017). Combining emotion regulation and mindfulness skills for preventing depression relapse: a randomized-controlled study. Borderline Personality Disorder and Emotion Dysregulation, 4, 13.

Jessica R. Peters, Shannon M. Erisman, Brian T. Upton, Ruth A. Baer, Lizabeth Roemer. (2011) A Preliminary Investigation of the Relationships Between Dispositional Mindfulness and Impulsivity. Mindfulness 2:4, 228-235.

Lars Schulze, Christian Schmahl, Inga Niedtfeld. Neural Correlates of Disturbed Emotion Processing in Borderline Personality Disorder: A Multimodal Meta-Analysis. Biological Psychiatry, 2016; 79 (2): 97 DOI: 10.1016/j.biopsych.2015.03.027

Soler J, Valdepérez A, Feliu-Soler A, Pascual JC, Portella MJ, Martín-Blanco A, et al. Effects of the dialectical behavioral therapy-mindfulness module on attention in patients with borderline personality disorder. Behav Res Ther. 2012;50:150–7


Tamara L. Giluk , Personality and Individual Differences. Mindfulness, Big Five personality, and affect: A meta-analysis  Dec 2009, Vol. 47, No. 8: 805-811

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Personality, Individual Differences, and Intelligence

Module Project: Factor Analysis of Personality Data Part 3 Discussion

LPSY 316: Personality, Individual Differences, and Intelligence

Jimmy Petruzzi


The research was able to provide evidence the 5 factors were present, by examining the data collected from the administration and participation of the questionnaire. Through conducting a factor analysis the research supported the hypothesis, reaffirming the reliability, validity and versatility of FFM administered across cultures, through the modification of the questionnaire with the IPIP. (2014).and the correlation with the FFM and the Traits.

The research we conducted met the following criteria, according to Stevens, (2002) a participant group over 200 is required  for reliability  and the loading value needs to be over .162, the number of participants we had was 1006, the 5 Items we retained were above .162.

Upon examination of the research it was established that the highest factor was 1, which was unexpected.   Factor 1 was the Conscientiousness trait: consciousness had each item scored >.5

The research recorded the highest number of  entries  for factor 2 Neuroticism, confirming from examination  of the data of the factor analysis factor 2 Neuroticism  as expected had the highest level of responses from participants. The research was able to establish below factor 2 Neuroticism was factor 3 Extroversion and factor 4 openness.

Consistent with the research hypothesis estimation the factor with the lowest values was factor 5: agreeableness, Taking into consideration that omission of item 9 because it was loaded onto factor 6,The following data Neuroticism receiving a high score and agreeableness a low score supported our estimation, although   in contrast the high entries for consciousness disproved our initial hypothesis.


Research by McCrae & Costa, 1997 suggested the FFM could be adapted cross culturally, in different societies and continents. The research suggested the modification of the Questionnaire for the participants  was successful and  able to  collect and provide data for  the 5 factors.

According to research by  Goldberg (2001) the FFM can be adapted successfully  for the administration to suit the cognitive abilities of the participant’s,  the research supported this hypothesis   the  questionnaire was successfully adapted and completed by the participants  to suit the cognitive abilities participants  and  translated from English into Intuit language.

In addition to support our hypothesis research by  Wiggins & Trapnell, 1997 suggesting  the FFM has a biological base and the ability to adapt cross cultural, which was an important factor as questions had to be adapted to culturally to the Intuit participants and adapted to the Intuit language.




This following values did not correlate with different research hypothesis or our estimation around conscientiousness ,according to the statistical data on the Intuit population Usalcas, (2009) suggesting high levels of unemployment , lower levels in education graduation and higher health risks amongst the Intuit population.

Which does not correlate with  research by  Scepansky,& Bjornsen, (2003) identified  higher levels of the personality traits conscientiousness, and openness  amongst students who had  who had a profound interest in  continuing on to  graduate education  and students who planned  to leave school and potentially find work , there was also a correlation between students interested in continuing their education and engagement in lessons, which suggests a correlation between personality traits.

The following statistics according to Usalcas, (2009) as specified above also did not support the following research ,according to Research by Bogg  & Roberts, (2013) suggest a correlation between Conscientiousness and long term  positive health, the research examines  the personality trait Conscientiousness and suggests a correlation with several health conditions.

Research suggests by Poropat, (2009). Conscientiousness has a correlation with academic achievement, the participants scored high on the conscientiousness trait  According to the IPIP The facets of Conscientiousness  are self-efficacy, orderliness , dutifulness, achievement striving, self-discipline which was not expected by our research considering past literature on the conscientiousness trait and correlation to education and well being.

One explanation could be upon examination from a different paradigm research by Shaw, (2016) suggests  emotional regulation is a component the resilience dealing with the challenges suggested the Inuit community face. The following research  Ferrazzi & Krupa, (2016) take into consideration the Intuit lifestyle and the responsibility adolescents have at early age and the changing demographic in the Intuit community , involving adaptation to western society and climatic changes impacting basic survival The responsibility of  an adolescent in the Intuit community, is vastly different comparatively to  western society, there could I been a misunderstanding in the translation or a factor in cultural values around the participants  understanding of the facets for conscientiousness.

To support this theory research by Lim & Abdullah, (2012) suggested that whilst openness and conscientiousness, did not have a direction causation in Malaysian  student  academic attainment. In identification of the facets associated  with openness and conscientiousness a platform could be built influencing learners performance in a positive way.

The trait conscientiousness could be correlated to aspects of Intuit adolescent life involving survival,

In support of the research hypothesis  Research  by  Laursen,Pulkkinen, & Adams, (2002) suggest  a low score on the  agreeableness  trait correlates to poor academic performance and behavioural problems  in school, suggesting higher scores on agreeableness in adulthood  correlate  with more stability on work and life, less maladaptive behaviour, and less likely to develop depression and alcohol problems.

The research is consistent with our research findings and hypothesis  suggesting the adolescent participants scored low on a agreeableness, and other research which suggested a high depression ratio amongst the Intuit community and higher rates of unemployment amongst the Intuit community comparatively to the general Canadian population according Inuit Tapiriit Kanatami and Indian and Northern Affairs Canada. (2007c). the ratio  of unemployment   in Nunavut  is 19.1%  with men  23.0% compared with women  15.1%. The following research by Feingold, (1994); suggest  women  in general  are  more agreeable then men. According to the following research by  Sackett and Walmsley, (2014) the agreeableness personality trait has a strong correlation to work performance across many sectors, this research could suggest a correlation between higher levels of employment in the Intuit community amongst women comparatively to men.

According to Usalcas, (2009 ) the   Canadian unemployment rate  was approx. 5.8% in 2008. Which contrasts the much higher levels of unemployment amongst the Intuit community compared to the Canadian population  outside the Intuit population.

In support to our hypothesis and research findings the research expected to establish the participants scored highly neuroticism, Research by Lahey (2009)  suggests neuroticism has a big impact on public health, suggesting that certain genes that correlate with neuroticism correlate with a number  of mental disorders mental disorders.

Neuroticism high response supports our hypothesis and supports the following research  According to Costa and McCrae( 1985), Neuroticism is a trait associated to lack of emotional control, anxiety, sadness,.

Research by  Eggertson (2013) suggests a higher level of suicide amongst the intuit community  which correlates to a higher level of depression, comparatively to the general Canadian population

Watson, D., & Naragon-Gainey, K. (2014). discuss how Neuroticism has the highest correlation of any of the traits to psychopathology , suggesting scores on the higher end of the Neuroticism have correlations with depression,anxiety , substance, link to health behaviours smoking and drinking, which supports our research findings around Neuroticism.



To complete the research questionnaire  the  participants  utilised paper and black pen, future  research would take into consideration using a computer and a specific software programme for practicality if the participants accidentally marked the wrong response could change it more efficiently.

The research to into consideration a study by De Fruyt, Mervielde, Hoekstra, & Rolland,(2000) demonstrating  certain questions were not understood  by children participating in a NEO–PI–R translated into Flemish. whilst the research questionnaire we developed took translation into consideration and provided participants support, additional research suggests the adolescents  taking a test on certain words to ensure they understand and interpreted the words correctly for example one of the questions was  I often feel blue, this could have been misinterpreted by  the colour blue by some participants.

According to Gurven, Rueden, Massenkoff, Kaplan, & Vie (2013) Discusses how administering the FFM in a largely illiterate society in Bolivia, raising questions marks on the validity of the  FFM, finding significant covariance amongst factors of the Big 5. Future research This may suggest further adaption to certain demographic which are outside the confines of urban populations and not in full time education, although a level of literacy testing  would have to be established to ensure reliability ,though testing the wider demographic adolescents who do not attend school would provide additional data for the hypothesis. We produced a modified sample questionnaire which could be administered to participants not in school.

The future research also would take the following research into consideration in developing a questionnaire.Research by Morizot, (2014) discusses the potential limitations of the FFM in the Inuit suggesting the abstract focus of the FFM does not factor the ever changing Inuit and cultural diversity, which may have been  a factor in the high Conscientiousness score.

According to Research by Woods & Hampson  (2005) in a comparison between simplified variations and longer variations to measure the big 5,this  procedure may have negotiated a more accurate  score of each individual trait, though it was deemed necessary to implement  for the research due to the demographic and profile of the participant’s as previously discussed, the research took into consideration, other research conducted utilising the FM, the degree of comprised reliability and  validity in setting a point for the questions, prior to administering the research question’s to the participants a trial set of questions were conducted to 120 participants  who met the research criteria, the validity and reliability on the shorter variation may not be as accurate as a longer test,





The implications of our research  findings based on our factor analysis of the data from the participants questionnaire, as the research hypothesised  we were able to identify  the 25 items questionnaire had successfully measured  the five factors. The factor analysis we conducted indicated 5 factors related to the IPIP-25 inventory.

The results of the questionnaire indicated that item 16 loaded onto factor 2 which was Neuroticism. Instead of the expected factor 5 which was  Agreeableness. Factor 5. Agreeableness demonstrated subordinate loadings   compared to the other factors on questionnaire   Extraversion, Neuroticism, Openness, and Conscientiousness. The research indicated the conscientiousness   results   have the highest connotation amongst the participant group and Neuroticism the  highest response The research suggested agreeableness  had scored the lowest comparatively to the other factors

Future research may involve a longer questionnaire administered for the participation of parents or carers of the participants to examine any correlation of traits to the hypothesis, Future research  adapting the questionnaire for the Intuit adolescent’s   population who do not attend school. Conduct a research test and examine the Conscientiousness trait in the participants as a follow up test in a few years and compare the traits amongst adolescents in education and not education to understand the environment as a correlating factor within the personality traits



Arthurs N et al (2014) Achievement for Students Who are Persistently Absent: Missing School, Missing Out? Urban Review. Dec2014, Vol. 46 Issue 5, p860-876. 17p.



Bogg, T., & Roberts, B. W. (2013). The Case for Conscientiousness: Evidence and Implications for a Personality Trait Marker of Health and Longevity. Annals of Behavioral Medicine : A Publication of the Society of Behavioral Medicine45(3), 278–288.


Costa, P. T., & McCrae, R. R. (1992). NEO-PI(R) professional manual. Odessa, FL: Psychological Assessment Resources.


Feingold, A. (1994). Gender differences in personality: A meta-analysis. Psychological Bulletin, 116(3), 429-456.


Ferrazzi, P., & Krupa, T. (2016). ‘Symptoms of something all around us’: Mental health, Inuit culture, and criminal justice in Arctic communities in Nunavut, Canada. Social Science & Medicine, 165159-167. doi:10.1016/j.socscimed.2016.07.033


Eggertson, L. (2013). Risk of suicide 40 times higher for Inuit boys. CMAJ : Canadian Medical Association Journal, 185(15), E701–E702.


Gurven, M., von Rueden, C., Massenkoff, M., Kaplan, H., & Lero Vie, M. (2013). How universal is the Big Five? Testing the five-factor model of personality variation among forager–farmers in the Bolivian Amazon. Journal of Personality and Social Psychology, 104(2), 354-370.


Inuit Tapiriit Kanatami and Indian and Northern Affairs Canada. (2007c). Inuit Social Trends Series: Employment, Industry and Occupations of Inuit in Canada, 1981-2001, Indian and Northern Affairs Canada, Catalogue R2-455/2007E-PDF. Ottawa: Minister of Public Works and Government Services Canada.



Goldberg, L. R. (1999). A broad-bandwidth, public domain, personality inventory measuring the lower-level facets of several five-factor models. In I. Mervielde, I. Deary, F. De Fruyt, & F. Ostendorf (Eds.),Personality Psychology in Europe, Vol. 7 (pp. 7-28). Tilburg, The Netherlands: Tilburg University Press.


IPIP. (2014). International personality item pool: A scientific collaboratory for the development of advanced measures of personality and other individual differences. Retrieved from



Lahey, B. B. (2009). Public Health Significance of Neuroticism. The American Psychologist64(4), 241–256.

Laursen, B., Pulkkinen, L., & Adams, R. (2002). The antecedents and correlates of agreeableness in adulthood. Developmental Psychology, 38(4), 591-603

Lim, P. S., & Melissa Ng Abdullah, L. Y. (2012). Relationship between Big-five Personality Domains and Students’ Academic Achievement. Pertanika Journal Of Social Sciences & Humanities, 20(4), 973-988


Morizot, J. (2014). Construct Validity of Adolescents’ Self-Reported Big Five Personality Traits: Importance of Conceptual Breadth and Initial Validation of a Short Measure. Assessment, 21(5), 580-606. doi:10.1177/1073191114524015


Poropat, A. E. (2009). A meta-analysis of the five-factor model of personality and academic performance. Psychological Bulletin, 135(2), 322-338.


Sackett, P. R, Walmsley, P. T. (2014). Which Personality Attributes Are Most Important in the Workplace? Perspectives on Psychological Science, 9(5), 538-551. DOI: 10.1177/1745691614543972

Stevens, J. P. (2002). Applied multivariate statistics for the social sciences (4th ed.). Hillsdale, NS: Erlbaum.

Usalcas, Jeannine. 2009. “The labour market in 2008.” Perspectives on Labour and Income. Vol. 10, no. 2. February. Statistics Canada Catalogue no. 75-001-X.


Van de Vliert, E. (2013). Climato-economic habitats support patterns of human needs, stresses, and freedoms. Behavioral and Brain Sciences, 36(5), 465-480. doi:10.1017/S0140525X12002828

Watson, D., & Naragon-Gainey, K. (2014). Personality, Emotions, and the Emotional Disorders. Clinical Psychological Science : A Journal of the Association for Psychological Science2(4), 422–442.


Woods S., & Hampson, S. (2005). Measuring the Big Five with single items using a bipolar response scale. European Journal of Personality, 19(5), 373-390

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Conduct an appropriate analysis to determine, what, if anything, predicts self-efficacy in Statistics.


In our week 8 assignment the objective is to Conduct an appropriate analysis to determine, what, if anything, predicts self-efficacy in Statistics.

According to Bandura (1997) there is a correlation between our beliefs and completing a specific task, suggesting self-efficacy plays a major role and is highly influential on a person’s ability to achieve a goal, Bandura discussed a relationship between variable factors and four key principles which play a major role in accomplishment.  Though is it the chicken or the egg, is it a question of competence or confidence. If I am competent in a task I am more likely to be confident. And believe I can do it. If I am not competent I am more likely to be less confident. Bandura ( 1997) did suggest even before we take any action there is a correlation of key principles. Though other factors to take into consideration are past experience and the link between past experiences and present learning. So for example if I am a competent driver, and I am travelling to a new destination I may be a be a bit apprehensive about my journey, though once I have travelled the journey on a few occasions it becomes much easier and I become more confident. Equally if a learner was going to start driving lessons, though had never been in a car before, it would be a far greater challenge one would think than if he or she had travelled on a car. One could also suggest past schemas play a role in self-efficacy, say for example you had built a negative association to delivering  presentations in your youth, this may manifest late in life. So one may have the competence, though not the confidence. Though there is a fine line between confidence and competence, and our ability to learn something new is a correlation to many variable factors, including how the information is presented and our learning style.


Looking at previous research of predictors in self-efficacy and academia, by exploring  the following research by Hall and Ponton,2002. We can see how in this comparative design study of two groups of students, briefly the study explores self-efficacy in maths, utilising a psychometric  test designed to measure self-efficacy in maths, the study explores different levels in maths. Notably  Algebra and calculus. Using an independent T Test the research found that the higher level maths group calculus, had a high degree of self-efficacy than the lower level maths group. So if we take Banduras ( 1997) theory into consideration it would suggest self-efficacy is linked to achievement. Though whilst the research did find some interesting correlations. Some of the things to take into consideration is the motivation to succeed, and the bigger picture, was the subject a component of additional study or course. Say for example in the mental health psychology course we cover statistics, having a certain level of knowledge of statistics is important, though not everyone who is doing the course will want to be a statistics teacher, given as such would require a different level of knowledge than if someone was choosing a different career path in the field, equally there are different components of a subject. And further more  reflecting back on the research the aspirations of the group studying the higher level maths, would play a part in self-efficacy and past experienced, if one had a goal of being an engineer than knowledge of maths would be more significant than if one had aspirations of being a historian.

One of the features  of the  following research by  Tiyuri et al. (2018) was it included  multiple linear regressions to study the impact of self-efficacy and performance in academia, over 300 learners participated in the study, across a broad range of academic levels, from degree to PHD. The group was divided into pretty much an equal split between female and male. The gender  (P = 0.754)  and school P value (P = 0.364) showed non-significant levels, although the psychometric test did not demonstrate a  significant difference based on gender and school, there was a significance difference (r = 0.393, P = 0.0001 in the level of academia amongst  PHD students. Equally in this study one could imply that the students doing the PHD had more motivation than the other students, also it is important to note the correlation between past experiences, prior knowledge. So whilst this research did produce interesting findings of the link between self-efficacy and learning performance, the objective of the study was not to examine variables which correlated to act as a catalyst for what underlies the self-efficacy.

According to Field (2012).in order for testing to be accurate, we must make the assumption the sampling distribution is normal” the implications as such and methodology if there any doubts.

The reason for the analysis in the assignment:

The Rationale

In order to predict self-efficacy in statistics I conducted a standard multiple regression to predict self-efficacy in statistics we explored self-efficacy, confidence, usefulness, gender, attitudes, age, maths and science levels.

Regression analysis was used to determine which amongst the following variables self-efficacy, confidence; usefulness, gender, attitudes, and age correlate with maths and science to form self-efficacy in statistics. The regression helps us to analyse and understand  which is the variables is statistically significance and non-significant and influential in the dependent variable. The spss output helps us to determine correlative factors. And isolate the variables and negative and positive relationships between variables, which factors are down to chance and which factors appear to be significant. For example the opportunity to examine p values and be able to test the hypothesis.

The regression analysis helped to isolate any patterns , and variable factors which colluded to determine  this case the  self-efficacy in statistics.

The reason I chose a Standard multiple regression was because i wanted to  predict the values on     the   research date data establishing the  continuous dependent variable factors  such as ,Confidence, Usefulness ,Male Dominated Field, Tutor Attitudes and self-efficacy the independent variable, as well as the categorical variables such as age and maths and sciences.

The main aims of using the multiple regression in the analysis were to examine and analyse the effect of ,Confidence, Usefulness, Male Dominated Field, Tutor Attitudes  on self-efficacy in statistics. Also the correlation of self-efficacy on  Confidence,Usefulness,Male Dominated Field, Tutor Attitudes  , how does a change in factor impact another.

This in turn gives us an opportunity to gain point estimates, understand and analyse correlative factors and predict further hypothesis.

The task was to identify self-efficacy in Statistics, I ran a multiple regression comparison on the Stats Confidence file provided

I decided to run a Standard multiple regression to predict predicts self-efficacy in Statistics. With the guidance of ( 2014) and Dolan, 2018.

The date consisted of the  following variables, Age,  Self Efficacy,Confidence,Usefulness,Male Dominated Field, Tutor Attitudes and grades in grades in Math or Science.

Also important to  note according to lens 2014 a regression analysis cannot be performed on ordinal level data, because maths and science are in this instance ordinal level data, I had to create dummy variables, which is something I really struggled with.

The study is, looks at the relationship between the variables as per above Self Efficacy,Confidence,Usefulness,Male Dominated Field,Tutor Attitudes grades in maths and science by participant’s  to predicting any variables or correlations of variables of self-efficacy in Statistics.

The results of the output the are as follows

Standard multiple regression

R=.568a the value of R Square= .279 it appears the variables are not good predictors of self-efficacy in statistics

The ANOVA significance value of .000b suggests that one of the predictor variables, with this information as per the video Dolan (2018) we can confirm that minimum of one variable predicts self-efficacy in statistics

A multiple regression was run to predict the following variables self-efficacy from

  • Confidence
  • Usefulness
  • Male dominated field
  • Tutor attitudes –
  • Maths
  • Science

Following the ANOVA  output  These variables statistically significant predicated  self-efficacy, F (6, 93)= 7.387, P <.000, R2=.323


The Standardized Coefficients for the following variables are

Confidence -.339
Usefulness -.146
Male Dominated Field  -.058
Tutor Attitudes -.132
maths  -.028
Science  -.013



The significance values are

Confidence .024
Usefulness .221
Male dominated field .529
Tutor attitudes .294
Maths  .755
Science .884


It appears that only one variable in the Confidence in the   coefficients with a significance value of  .024, significantly predicts self-efficacy, the rest of the variables in the coefficient are non-significant

The VIF values are

Confidence  3.004

Usefulness  1.932

Male dominated field  1.154
Tutor attitudes  2.130
Maths   1.117
science 1.053

All of  the VIF  values are under 4 or 5, according to Dolan ( 2018) if the The VIF values are above 4 or 5, there could potentially be a problem with multi linearity

The Beta values

Confidence  -.339  
Usefulness -.146  
Male dominated field   -.058  
Tutor attitudes  -.132  
Maths   .028  
Science -.013  


According to Dolan ( 2018) the higher the beta value, “the higher the impact of the independent variable on the dependent variable”. Interestingly enough, confidence has a beta value of -.339 the highest beta value and  a p value of Confidence .024 the lowest significance value







Anova table

  df F R2 P  
Self-Efficacy 7.387 6 R2=.323 P <.000  


Following the ANOVA  output  These variables statistically significant predicated  self-efficacy, F (6, 93)= 7.387, P <.000, R2=.323

A multiple regression table was run to predict self-efficacy from age , which produced the following significance values

    B SE B β t p Sig.    
Confidence       -.339     .024    
Usefulness       .146     .221    
Male dominated field       -.058     .529    
Tutor attitudes  –       -.132     . .294    
Maths Nominal (dummy )     .028     .755    
Science Nominal

( dummy)

    -.013     .884    
Age categorical                
Self-Efficacy Independent variable                




Self-efficacy is abstract concept, confidence had a beta value of -.339 the highest beta value and  a p value of Confidence .024 the lowest significance value, though how do you define confidence. And then there is the issue of confidence and competence, Quantitative states  facts for example  maths  and science, Qualitative is more speculative in this instance. Reflecting on my own experience, journey, the module as a whole and this assignment. One of the areas I got bogged down on was the dummy statistics, during which I had a moment of introspection and reflection, I was beginning to think I had come so far in the module and gradually through the attainment of grades and tutorials and assignments I had built a conviction I could get through the module, though more importantly develop my skills around statistics, the challenge I had was not in the understanding though in the technical knowledge around creating the dummy variables, ad all I could think of was the weight of the final project and how a process that is relatively simple to do, could undo all the work I had done. Reflecting on the research papers I had read around the university students and the college students around maths, I was beginning to release self efficacy is a complex area  to define. And whilst agree with some of the  research by Bandura (1997), this assignment suggested the variables work as a cocktail or perfect storm, that collude.  Qualitative Research can be challenging to define,  and quantify, Quantitative data gives us values. Though there is a saying in sport, you do not play on paper, certain data can point you in a certain direction, though what is concise for one person may not be concise for someone else. And how you quantify  Qualitative research can be a challenge in in itself. I think to a point all of the following variables we examine  have an impact on self-efficacy  on some level, although the data points towards confidence, this could be seen as a grey area. As you can start an assignment with to much confidence and that in itself could have negative implication, or you could start with little confidence, though that could grow as you go along. Though not journey is linear, each journey is filled with twists, turns, and permeations.



Bandura, A. (1997). Self-Efficacy: The exercise of control. New York, NY: W. H. Freeman.

Field, A. (2012). The linear model (regression part I) [Video file]. Retrieved from


Hall, M., & Ponton, M. (2002). A comparative Analysis of Mathematics Self-Efficacy of Developmental and Non-developmental Freshman Mathematics Students. Presented at the 2002 Meeting of Louisiana/Mississippi Section of the Mathematics Association of America.


Laureate Education (Producer). (2014). Weekly lecture notes, Week 8 – Part 1 [Video file]. Baltimore, MD: Author.

Laureate Education (Producer). (2014). Weekly lecture notes, Week 8 – Part 2 [Video file]. Baltimore, MD: Author. (Producer). (n.d.). Multiple regression [Video file]. Deerfield Beach, FL: ConsumerRaters. Retrieved 28 October 2014.


Tiyuri, A., Saberi, B., Miri, M., Shahrestanaki, E., Bayat, B. B., & Salehiniya, H. (2018). Research self-efficacy and its relationship with academic performance in postgraduate students of Tehran University of Medical Sciences in 2016. Journal of Education and Health Promotion, 7, 11.

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Here it is, the track title: Manarola


Here it is, the track title: Manarola

The beautiful tune is available to download free from the following link

The Track was inspired by reflecting on the life-changing events people experience, and that love, harmony, peace can co-exist in the modern world.: The goal of the track is to capture a sentiment that  a person has on their interpretation of  Buddhist philosophy, that the past  is an illusion and the future is an illusion, the only moment we truly have in the now: The style meets at a juncture of many different genres with the vocalisation of the angelic voice of  British Soprano Jennifer Lorelai Lee shining throughout:


Love and Light!

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jimmy petruzzi

Excited and thrilled to announce a collaboration with British Soprano Jennifer Lorelai Lee! Jennifer has a passion for music, musical theatre, and opera! Coupled with an incredible talent and down to earth approach! Watch this space! Looking forward to getting back in the recording studio!

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jimmy petruzzi

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Jimmy Petruzzi

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jimmy petruzzi

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