Psychology
(5841 word count)
Abstract
Identifying and predicting psychopathic traits by analyzing childhood behaviours must be based on sound psychometrics to ensure scientifically reliable results. Statistical analysis using G-Power (computer model for calculations) aids in analyszing the results from surveys and personality assessments which are administered to teens and young adults from communities, colleges, juvenile homes and jails in order to understand how the data from self reported questionnaires can reliable be used to predict psychopathic behavior. The ability to do so would be very helpful for counseling and could possibly help avoid psychopathic behaviors in young people that are self-destructive and that may lead to crime. Research survey templates for adults are customized for use with younger participants. This research reported that the ccomparison of the three factors Narcissistic/CU, Impetuous, and Arrogant descriptive statistics (N-117) for Adolescent Antisocial Attitudes Scale (AASAS) and Antisocial Process Screening Device (APSD) correlated satisfactorily for the purpose. Careful statistical use of severity information was valuable in reaching the conclusion.
Juvenile Psychopathy: Comparing Assessment Scales Using the Adolescent Antisocial Attitudes Scale as an Experimental Measure
Factor analysis has become an important statistical tool used to evaluate antisocial assessments in determining juvenile traits of psychopathy. In order to identify and predict psychopathic traits by analyzing childhood behaviours must be based on sound psychometrics to ensure scientifically reliable results from surveys and personality assessments. The study of adult psychopathy has determined that the traits reach a level of temporal stability, but the same cannot be said of traits observed in adolescence. Adolescence is a time of many developmental changes, some of them similar to psychopathic traits.
Lynam (2002) has explained an important reason for studying juvenile psychopathy is because “the assessment and study of fledgling psychopathy holds the key to its treatment” (p. 257). The disagreement for studying the juvenile behaviour in terms of psychopathy has been over how to separate the natural development during adolescence from unwanted psychopathic tendencies. Seagrave and Grisso (2002) pointed out the resemblance between normal developmental changes and “fledgling psychopaths” may misidentify traits in young people who are passing through natural growth phases, for example, the time before the abstract notion of empathy has been totally developed (p. 219). Other researchers recognize these challenges.
Another discussion has centered about how to apply or extend measurement scales of adults to young people. Adult self-reporting surveys have been adjusted to better fit participants aged from very young to mid-twenties. The hope is that just as self-reporting surveys have helped identify psychopathy in adults the same can be done with youths. Therefore statistical analysis techniques are especially important to understand the degree of reliability for each change. Results must be compared between research studies with confidence.
Research has indicated that psychopathy in both adults and children exhibits with characteristic traits of impulsiveness, lack of compassion and other traits leading to predictive criminal behaviour (Lyman, 2002;) Adult psychopathology exhibits as stable in adulthood but the same type of stability may or may not be part of adolescence.(Lynam, 1997; Lynam, 1998; Frick, Bodin & Barry, 2000; Cooke & Michie, 2002; Ellen, 2002; Skeem & Cauffman, 2003; Vincent et al., 2003) Sub-traits and sub-behavioural patterns have been developed so that although the adult scale template is used as a guide surveys are specifically developed for teens and young adults. Vincent (et al., 2003) has noted that “assessments that disregard callous-unemotional traits will likely result in high false positive rates among adolescent offenders” and they have recommended “follow-up in adulthood” with chronic offender models (p. 695).
The participants also self-addressed the catagories of occupation which suited their family situation. In Australia and New Zealand eight catagories for
“Professional perform analytical, conceptual and creative tasks through the application of theoretical knowledge and experience in the fields of the arts, media, business, design, engineering, the physical and life sciences, transport, education, health, information and communication technology, the law, social sciences and social welfare.” (ANZSCO)
Two assessment tools have been compared under experimental conditions the Adolescent Antisocial Attitudes Scale (AASAS) and the Antisocial Process Screening Device (APSD).
In his book statistical Power Analysis for the Behavioural Sciences, Jacob Cohen (1988) briefly discussed power analysis by pointing out the three most important issues “effect size, the role of psychometric reliability and the efficacy of “qualifying” (differencing and partially) variables” (p. 531). The determination of sample size in must take into account effect size (ES) when using power analysis while remembering that ES does not automatically account significance to large values that describe a phenomena; large values do not necessarily equal significance to test results. (Cohen, 1988, p. 253) Therefore the moment correlation coefficient, r, and its square, r2, should be uses to interpret the differences between factors” (p. 532)
Hypothesis: If teen and young adult participants are honest when given AASAS and APSD assessments the two surveys will show agreement for at least one characteristic trait of psychopathy.
Method
Participants and Procedure
An online survey received ethics approval from the University of Southern Queensland (USQ) Human Research Ethics Committee (H12REA065; H12REA068; H12REA075) The online survey included four self-report inventories: Adolescent Antisocial Attitudes Scale (AASAS), Antisocial Process Screening Device (APSD), Psychopathy Content Scale (PCS), and the Adolescent Antisocial Behaviour Scale (AASBS) for the purposes of evaluating the empirical validity of the AASAS. The duration of the survey was about 30 to 45 minutes. The effort made to minimise response bias was to avoid the term ‘psychopathy.’ The participants were individuals aged at least 17 years and before 20 years old. One hundred twenty eight participants meeting the age qualifications responded to the online surveys (N=128). The sample group included both genders and mainly consisted of first-year psychology students and included two subsets, 108 students enrolled in other programs at USQ (n=108) and members of the general public (n=9). The psychology students were given a 1 percent credit for participating in the survey.
Eleven cases from the sample group of first-year psychology students were excluded due to invalid responses, therefore the final total sample was equal to one hundred seventeen (N = 117) The mean age in the sample group was 18.5 years (M=18.5 years, SD = 0.75). Seventy two percent of the final sample group were female (85 girls) and 27.4 percent were male (32 boys). Approximately seventy six percent of the participants grew up in households with both a mother and a father (n=89). The cultural background of 84 percent of the participants was Australian (n=98). The participants also self-reported their parental occupations by choosing from eight categories to determine their socioeconomic status (SES). The occupations, which were classified into one of eight occupational groups Australian and New Zealand Classification of Standard Occupations (ANZSCO) (Pink & Bascand, 2009) and cross referenced against the Australian Socioeconomic Index 2006 (AUSEI06; McMillan, Beavis, & Jones, 2009). Participant SES backgrounds were classified as high (n = 43, 37.1%), moderate (n = 55, 47.4%) or low (n = 18, 15.5%), and missing (n = 1).
Materials
The Adolescent Antisocial Behaviour Scale could be helpful in defining the start, peak and endpoint of adolescent antisocial behavior (ASB) which naturally occurs in growth development. (AASBS; Czech & Kemp, 2010) Mak (1998) explained that “The resulting Australian Self-Reported Delinquency Scale assesses individual differences in engagement in a list of 34 types of delinquent activity. The instrument contains nine subscales (Cheat, Status, Fight, Vehicle, Drugs, Theft, Harm, Driving, and Disturb), which enable assessment of involvement in specialised areas of offending. The AASBS is a 40-item self-report questionnaire adapted from the Self-Reported Behaviour Scale (SRBS; Mak, 1993). The AASBS is considered appropriate for use as the criterion measure in this study as it captures specific aspects of ASB participation including severity, first age of participation and recency of participation. For each item respondents indicated whether they had ever participated in the behaviour in addition to whether they had participated in the last 12 months, and at what age they were the first time they committed the act, for example, “Have you bought or sold stolen goods (a) ever, (b) in the last 12 months, and (c) at what age were you when you first bought or sold stolen goods?” The original 40-item scale, which includes four lie scale and three validity scale item was administered to participants. Czech and Kemp (2010) found evidence for a (28-item) three-factor structure representing increasing severity of ASB from factor 1, delinquent behaviour; to factor 2, reckless behaviour; and to factor 3, serious ASB. The scale is considered to have good overall reliability with a Cronbach (1951) alpha coefficient of .84. Coefficients of .81 for factor 1 (16 items) and .74 for factor 2 (eight items) are considered good and acceptable, respectively (Cronbach, Gleser, Nanda, & Rajaratnam, 1972). The coefficient of .64 on factor 3 (four items) is deemed questionable and most likely results from the low number of items (Cronbach et al., 1972). For the purposes of the current study, these three factors and the resultant Total 28 items were included in analyses.
Data Screening and Treatment
Data Screening
Where relevant, items of each measure were reverse-coded and reverse-scored prior to analysis. Analyses were completed using Statistical Package for Social Scientists (SPSS), version 21).
The data was screened for univariate (cut-off of z ≥ 3.29); and multivariate outliers (Mahalanobis distance, p < .001), and all cases were retained. A review of squared multiple correlations computed from Variance Inflation Factors and Tolerance values, indicated no problems of singularity or multi-co linearity.
Data Treatment
AASAS and APSD
The participant-to-variable ratio guidelines vary, but one general rule is that a minimum of five cases per variable is required to conduct factor analysis. (Gorsuch, 1983) This minimum guideline criteria was met for both the AASAS ( N=20 items) and the APSD (N=18 items) with a final sample size of 117.
there are no outliers
mean is greater than the media
the skewness is 1.479 there is a deviation from the normal distribution
the kurtosis is 1.778 so the curve is flatter than normal distribution
The skewness increases in from Severity1 to Severity2 to Severity3 but the First Stage ASB and Recent ASB are close (1.4861 and 1.412). The difference between the mean and the median of First Stage ASB and Recent ASB are also close; both are approximately 6.
Previous findings in non-clinical samples, has revealed that approximately 1% of participants meet the criterion of a psychopathic personality (based on a cut-off score at the 75th percentile). Therefore, data were inspected 1%
Skewness and kurtosis statistics indicated violations of normality; however, inspection of the normal probability plots revealed that the data points approximated the expected quantiles, indicating that the data come from a distribution, which does not depart significantly from normal (Chambers, Cleveland, Kleiner, & Tukey 1983). The data were therefore found to be amenable to principal component analysis (PCA; Pearson, 1901).
AASBS.
A priori power analyses conducted using G*Power Version 3.1.3 (Buchner, Erdfelder, Faul, & Lang, 2012) determined a sample size of 84 was required to attain a power level of 0.80 for two-tailed tests detecting a medium effect size (f2 = .3; Cohen’s, 1988 conventions).
Comparison of the three factors Narcissistic/CU, Impetuous, and Arrogant descriptive statistics (N-117) for Adolescent Antisocial Attitudes Scale (AASAS) and Antisocial Process Screening Device (APSD) totals with Large standard deviation positive skewness and kurtosis (deviation from normal distribution) The Narcissistic/CU is the factor that determines the totals for the AASAS based on the values of skewness and kurtosis. For the APSD the factor of impetuous determines the totals
All of the factors have very large standard deviations compared to the means so the data point values are widely distributed (nonlinear).
No outliers were detected in the data. However, Kolmogorov-Smirnov tests indicated that assumptions of normality were not met D (117) = .21, p < .0001. Therefore AASBS analyses were conducted to suit non-parametric data, i.e., bivariate correlations were conducted with Spearman Rank Order Correlations (rs).
Internal Validity.
Test of reliability of the three scales in this sample indicated good internal consistency (AASAS α = .91, 20 items; APSD α = .84, 18 items; AASBS α = .81, 28 items), defined as Cronbach’s (1951) coefficient alpha > .7 (Kline, 1999). Internal consistency of the APSD was improved from .82 to .84 by removing an item (Lies Skilfully and Easily), which has performed inconsistently in past studies (e.g., Frick, Bodin & Barry; Fite, Greening, Stoppelbein & Fabiano 2008).
The published factors for the AASBS (Czech & Kemp, 2010) were adopted for use in this study. Severity factor scores, first age of, and recent, participation variables were computed, and the associations between these variables provided further evidence of internal validity for this criterion measure. An earlier first age of participation in ASB (n = 90) was significantly associated with greater total AASBS scores (Total ASB; rs = -.15, p < .10, 2-tailed), and each of the three factors were correlated with Total ASB (rs =.36 to .91, p < .001, 2-tailed), and with each other (rs =.25 to . 41, p < .001, 2-tailed).
Results
Factor Analysis (Structural Validity)
Initially, the factorability of the 20 AASAS items and the 18 APSD items was examined. Several well-recognised criteria for the factorability of a correlation were used. Firstly, reasonable factorability was established with Bartlett’s (1950) test of sphericity reaching statistical significance (2 (190) = 963.88 and 604.92 for the AASAS and the APSD respectively, p < .001), and the majority of items correlating at least .3 with at least one other item within the respective scales (Gorusch, 1983, p 150). Secondly, the Kaiser-Meyer-Olkin measure of sampling adequacy (Kaiser, 1974) for the AASAS and APSD was .89 and .83, respectively, which is above Tabachnick and Fidell’s (2001) recommended value of .6; an examination of the diagonals of the anti-image correlation matrix indicated that all correlations were above .5 for each measure, supporting the inclusion of each item in the factor analyses. Finally, with the exception of two APSD items (Keep The Same Friends [REV] and Does Not Show Emotions), the communalities were all above .3 on the AASAS, further confirming that each item shared some common variance with other items (Guadagnoli &Velicer, 1988). Given the overall indicators of suitability, however, these two APSD items were retained and factor analysis was conducted with all 18 APSD items to allow comparison with prior published studies.
Principle components analysis was used for both measures because the primary purpose was to identify and compute composite scores for the separate underlying factors, which may be used to predict antisocial or criminal behaviour.
AASAS 20 Item.
Unconstrained PCA revealed six components with eigenvalues exceeding 1.0 with 64.6% total variance explained. The initial eigenvalues showed that the first factor explained 29% of the variance, and examination of the scree plot revealed a clear break after the second component and a smaller break after the third component. The three factor solution, which explained 46% of the variance, was preferred because of the ‘leveling off’ of eigenvalues after three factors (8.8% and 8.2% for the second and third components respectively), which was also revealed on the scree plot, and the insufficient number of primary loadings and difficulty of interpreting the fourth factor and subsequent factors. Values of ±0.32 within the factor correlation matrix indicated that oblique rotation was appropriate (Tabachnick & Fiddell, 2001); therefore, Promax rotation was applied for all initial analyses.
APSD 18 Item.
Unconstrained PCA revealed three components with eigenvalues exceeding 1.0 with 52.1% total variance explained. The initial eigenvalues showed that the first factor explained 39% of the variance, and examination of the scree plot revealed a clear break after the second component and a smaller break after the third component. The three factor solution was preferred because of the ‘leveling off’ of eigenvalues after three factors (7.0% and 5.9% for the second and third components respectively), which was also revealed on the scree plot. Values of, or approximating, ±0.32 within the factor correlation matrix indicated that oblique rotation was appropriate; therefore, Promax rotation was applied for all initial analyses.
Across both scales, all items met a minimum criteria of having a primary factor loading of .3 or above, and communalities were within an acceptable range (0.27 – 0.67), with the exception of two items on the APSD: Keep The Same Friends (REV; 0.13 and Does Not Show Emotions (0.15). Three items on each scale, respectively, revealed a cross-loading above .3. On the AASAS, these items were: I Think Am Better Than Most People, Say Anything so Others Know How Important I Am, and I Am Bored with most things. On the APSD these items were Blame Others for Mistakes, Uses or Cons Others, and Gets Bored Easily. The factor loading matrix for the final solution for each scale is presented in Tables 1 and Table 2.
Factor loadings and communalities based on a principle components analysis with promax rotation for the 18 item Antisocial Process Screening Device (APSD) (N = 117; α = .84)
Note. Factor loadings < .2 are suppressed
h2 = communality
The factor labels traditionally used in the literature (Narcissistic, CU, Impulsive), did not produce a precise fit to the extracted factors from the data in this sample for either measure. Rather, the items loaded in a somewhat consistent pattern across both measures: One factor revealed that Narcissistic and CU items loaded together, and two unique factors were produced and, therefore, have been labelled as: Impetuous (includes impulsive externalising behaviours), and Arrogant (an exaggerated sense of one's own importance or abilities). Internal consistency for each of the scales was examined using coefficient alpha. The AASAS subscale alphas were good (.86 for Narcissistic/CU [n=8 items]) and fair (.78 and .77 for Impetuous [n= 7 items] and Arrogant [n=5 items] respectively). Overall, the APSD subscales did not perform as well comparatively: a good reliability coefficient (.84) was produced for Arrogant [n=8 items]); however, coefficients were marginal (.63) and unacceptable (.52) for Impetuous (n= 5 items) and Narcissistic/CU (n=5 items) respectively. No substantial increases in alpha for any of the scales could have been achieved by eliminating more items.
Composite scores were created for each of the three factors for each scale, based on the mean of the items, which had their primary loadings on each factor. Higher scores indicated a greater level of possessing the personality characteristic. The highest scores in this sample were obtained on the AASAS Impetuous and Arrogant subscales and the APSD Narcissistic/CU and Arrogant subscales, suggesting a closer examination of the content validity of these items (see xx). Although standard deviations were consistently proportionately large for all total and subscale scores (suggesting large variability in responses), several fell within a tolerable range of kurtosis. As expected, all distributions were positively skewed, indicating a high proportion of low item-endorsement across all subscales, with the exception of APSD Arrogant subscale. Therefore, subsequent inferential analyses were conducted using non-parametric tests.
Descriptive statistics for Adolescent Antisocial Attitudes Scale and Antisocial Process Screening Device totals and three factors (N = 117)
As expected the extracted factors are non-orthogonal; although oblique rotation was applied, fairly substantial correlations between each of the composite scores existed. These were larger for the AASAS subscale associations: rs = .56 between Narcissistic/CU and Impetuous; rs =.50 between Narcissistic/CU and Arrogant; and rs =.56 between Impetuous and Arrogant, compared to rs =.30, .35 and .39 for the respective APSD subscale composite score associations.
Overall, these analyses indicate that three somewhat distinct factors were underlying participant responses to items on each of the respective psychopathy scales, and that these factors were somewhat consistent across the two scales. All three AASAS factors were moderately internally consistent; however, for the APSD, only the Narcissistic/CU factor demonstrated internal reliability.
Concurrent validity was also evidenced by the large correlations (p <.01, 2-tailed) revealed by bivariate analyses of associations between the AASAS and APSD total scores(rs = .83), Arrogant composite scores (rs = .69), and Impetuous composite scores (rs = .67). However, although statistically significant, the association between Narcissistic/CU subscale composite scores for the two scales was substantially weaker (rs = .26).
Item Analysis (Content Validity)
Classical Test Theory was applied to conduct item analysis to examine content validity. Prior to conducting item discrimination analyses, the response format scales on each scale were transformed to dichotomous variables. The four-point response option on the AASAS was recoded from 0 = Doesn’t apply at all, 1 = Sometimes or somewhat applies, and 2 = Often applies to 0 = Not representative; and from 3 = Applies most of the time or very well to 1 = Representative. The three-point response option on the APSD was recoded from 0 = Not at all True and 1 = Sometimes true to 0 = Not representative; and from 2 = Definitely true to 1 = Representative.
The p-values were computed to assess item difficulty (Wood, 1960); lower scores indicate that very few individuals endorsed the item (i. e., Not Representative, as would be expected in a non-clinical sample), and higher scores indicate that a large proportion of the sample indicated that that the item-characteristic described them very well (i.e., Representative). Both the corrected point-biserial coefficient (riT), and the Item Discrimination Index (d; Kelley, 1939), were computed to judge item quality; lower values indicate that the scores on individual items are not consistent with scores on the overall scale.
For the purposes of this study, only p-values exceeding 0.20 were identified as poor-performing items, as values above this threshold indicate that a relatively large proportion of the sample indicated that the item was representative of them. Values below .3 for both riT and d indicate that the item is not discriminating well between low and high test scorers (Nunnally & Bernstein, 1994, p 304-306), and these items were flagged for further examination.
As displayed in Table 4, items on the AASAS performed fairly well: all p-values were .10 or below, and several items produced d values above .20 (Items 1, 3, 4, 5, 19, and 23). However, the remaining items produced d values below .15, and three items (Items 8, 26, and 28) also produced low riT values.
Item difficulty (p-value) and discriminating (point-biserial and D-Index) values for the 20 item Adolescent Antisocial Attitudes Scale (AASAS) (N = 117).
p = p-value
rpb = corrected point-biserial
D = D-Index
Item difficult (p-value) and discriminating (point-biserial and D-Index) values for the 18 item Antisocial Process Screening Device (APSD) (N = 117).
p = p-value
rpb = corrected point-biserial
D = D-Index
The D-Index for this item appears acceptable, indicating a clear differentiation between low and high scorers on the APSD; however, the regression line is relatively flat due to the high endorsement across all three scoring groups, particularly in the low scoring group (refer to Figure 1). Similarly, whilst producing acceptable riT and d-indices, a p-value of 0.33 produced for Item 9 indicates unusually high endorsement across this non-clinical sample. However, although Item 17 produced a p-value of 0.21, and a low riT, the D-Index demonstrates that high scorers are endorsing this item at much greater frequency than both low and moderate scorers.
Figure 1. Meaningful endorsements of traits from APSD
Several items on the APSD failed to capture any meaningful endorsement of the trait in question in this community sample. Due to low base rates, several items (Items 4, 5, 7, 8 , 10, 12, 15, and 16) produced low d-indices with good riT coefficients; however, base rates were nearly zero for Items 1, 3, 18, and 20 resulting in uninterpretable results for these items. The best discriminating items in this sample of community young adults for the APSD were Items 11, 13, 14, and 17.
Figure 2a. Proportion of responses across the four-response format scale for items on the Adolescent Antisocial Attitudes Scale (N =117).
Figure 2b. Proportion of responses across the four-response format scale for items on the Adolescent Antisocial Attitudes Scale (N =117).
A final test of convergent validity of the AASAS revealed that each item on the AASAS was significantly (p < .0001) positively correlated with the total APSD scale. The majority of items ranged in value from r = .38 to .62; however, although still statistically significant, the item I Like Talking about Myself produced a relatively smaller correlation coefficient (r = .30).
Correlations (Criterion Validity)
The correlation between the total ASB and the severity factors decreased from Severity Factor 1 (correlation coefficient .908) toSeverity3 (correlation coefficient .364). The total ASB is not correlated with the First Stage of ASB but it is highly correlated with the recent ASB (from the past 12 months). The total ASB has significant correlations with AASAS Factors and the APSD factors. For example the total AASAS20 compared to AASAS Factors 1, 2 and 3 is high; the range is .8 to .9. The APSD total is correlated with the APSD factors 1, 2 and 3. The high correlation is expressed by the correlation coefficients of .64 and .87.
Discussion
Whereas the most important factors for influencing the same traits, Narcissitic/CU, Impetuous and Arrogant, are listed here with the α-value are the following. The four most important factors for influencing Narcissistic/CU (a) Thinks better than others, 0.76; does not plan ahead, 0.60; Concerned about others feelings (REV), 0,55; and (d) does not show emotion, 0.49. The four most important factors for influencing Impetuous are (a) Gets bored easily, 0.44; (b) Tease others, 0.81; (c) Feel bad or guilty (REV), 0.64 ; (d) Engages in risky activities, 0.63. The four most important factors for influencing Arrogant are (a) Blame others for mistakes, 0.78; Care about schoolwork (REV), 0.77; Act without thinking of consequences, 0.76; (d) Emotions are shallow, .0.70.
Although the wording is different the narcissistic traits are thinking more of one’s own value than others. Impetuous shows behaviours such as acting with thinking and under arrogance both sets demonstrate lack of feelings for others. Table 3 lists the descriptive statistics (N-117) from the AASAS and APSD totals with the three factors (see above): Narcissistic/CU, Impetuous, and Arrogant which are predictive traits of psychopathy and the data indicated similarities in theism three traits between the two surveys. Therefore the Severity factors were rescaled.
In Table 4 note that the probability of the significance all fall in the range .02 and .08 significance levels listed under (p). The rpb is the correct point biserial that tells you how well the participants answered the questions referring to the three charater traits. The values are good except for the last two which are low, .08 and .11 on questions AASASQ26 and AASASQ28. But the overall indication is that the questions are very good at discriminating between the students.
The highest significance 0.02 is for the same factor with the highest rpb number, .83 meaning that there is high discrimination. Questions 17, 20, 25, 6, and 5 are the most discriminating questions bases on rpb values.
Figure 1 is a linear graph of APSD9, APSD17 and APSD19 recodes. The best discriminating items in this sample of community young adults for the APSD were Items 11, 13, 14, and 17 according to Rit which is indicated in the ‘D’ column.
Figures 2a demonstrate that, in general, the most answers for the AASAS were “not at all” and the “somewhat”; in other words they are the most significant based on the percentages graphed. In the case of Figure 2b for APSD the “not at all” and “sometimes” with the exception of questions of 9 and 19 where “sometimes” and “definitely” were the most significant answers. The sample group contained mostly first year psychology students so they were not expected to demonstrate highly psychopathic traits whereas if the group had been from a group of juvenile offenders.
Conclusion
The hypothesis “If teen and young adult participants are honest when given AASAS and APSD assessments the two surveys will show agreement for at least one characteristic trait of psychopathy” has proved to be correct because using statistical analysis three characteristic traits that are highly associated with psychopathy were identified when comparing the two surveys; those traits being Narcissistic, Impetuous, and Arrogant. This research has added important information to the use of AASAS and APSD when participants are college age. It would be interesting to carry out this research at another university in a different city so that the results could be compared with this research. Further research would be necessary to refine the statistical analysis techniques in regards to other surveys and different psychopathic traits.
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ANZSCO http://www.abs.gov.au/ausstats/abs@.nsf/Latestproducts/71200051AA046
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