The relationship between Dark Triad personality traits and emotional intelligence: the influence of gender
The relationship between Dark Triad personality traits and emotional intelligence: the influence of gender
Abstract
Though emotional intelligence (EI) is generally considered a positive trait, research has begun exploring the potential for EI to be used malevolently. Dark Triad traits (Machiavellianism, narcissism and psychopathy) are often used as measures of socially aversive intentions. While research in this field exists, it is limited in that gender differences are rarely explored, and findings of such studies are inconsistent. This study aimed to investigate the influence of gender on relationships between Dark Triad traits and EI. It was hypothesised that narcissism would show positive relationships with EI regardless of gender, that psychopathy would show negative relationships with EI regardless of gender, and that the relationship between Machiavellianism and EI would be moderated by gender. 356 participants (278 female and 78 male) completed the Short Dark Triad (SD3) and the Trait Emotional Intelligence Questionnaire- Short Form (TEIQue-SF). Three moderated regression analyses were run, each using a Dark Triad characteristic as a predictor of EI, with gender as a moderator. Results showed that psychopathy and EI had a negative relationship regardless of gender, that the positive relationship between narcissism and EI was moderated by gender (reaching significance for females only), and that the negative Machiavellianism/EI relationship was not moderated by gender, though it reached significance for females only. These findings open the door for further research into relationships between socially deviant personalities and EI and how these may present behaviourally. Conclusions from research in this area may have applications in education, relationship counselling, conflict mediation, the judicial system and individual clinical psychology or counselling practice.
The relationship between Dark Triad personality traits and emotional intelligence: the influence of gender
While possessing high levels of emotional intelligence (EI) is generally considered positive for both the individual and those they interact with (Austin, Farrelly, Black & Moore, 2007), it has been acknowledged that EI need not necessarily coincide with morality. In fact, EI may serve the purposes of those who possess it, regardless of how positive or negative their intentions may be (Carr, 2000; Ct, DeChelles, McCarthy, Van Kleef & Hideg, 2011; Nagler, Reiter, Furtner & Rauthmann, 2014). The potential for a dark side to EI (using EI to manipulate others in a harmful way) (Davis & Nichols, 2016) has become of interest to researchers, with several choosing to use Dark Triad traits as measures of socially aversive tendencies (Austin et al., 2007; Bacon & Regan, 2016; Nagler et al., 2014; Petrides, Vernon, Schermer & Veselka, 2011; Zhang, Zou, Wang & Finy, 2015).
The Dark Triad describes a collective of three overlapping socially aversive traits: Machiavellianism, narcissism and psychopathy (Jones & Paulhus, 2014; Petrides et al., 2011). As narcissism and psychopathy are conceptually derived from clinical literature, it is important to note that the Dark Triad refers to sub-clinical conceptions of these traits (Furnham, Richards & Paulhus, 2013). Machiavellianism encompasses a degree of emotional detachment (Petrides at al., 2011) and the belief that manipulating others is key to advancing ones own goals (Furnham et al., 2013). Narcissism refers to a beliefs in ones superiority over others, which includes a sense of entitlement and grandiosity (Furnham et al., 2013). Psychoticism involves both high impulsivity and thrill-seeking (Furnham et al., 2013), as well as low empathy (Paulhus, Hemphill & Hare, as cited in Jonason, Li, Webster & Schmitt, 2009). The three Dark Triad characteristics share associations with reduced empathy and increased self-interest (Jonason et al., 2009).
There are numerous conceptions of EI, though it is generally defined as a set of skills regarding interpretation and regulation of emotions, in both oneself and others (Ackley, 2016; Austin et al., 2007). While many models of EI exist, they can effectively be divided into ability or trait models. Ability models consider EI to be an innate capacity much like IQ, whereas trait models view EI as a learnable skill (Ackley, 2016). There are studies which measure both trait and ability EI, finding differences between the two for the same participants (Davis & Nichols, 2016; Zhang et al., 2015). This may suggest that these conceptualisations of EI are in fact two distinct constructs. For the present studys purposes, trait EI theories are most appropriate as a basis, for they do not strictly define EI as socially adaptive (Petrides et al., 2011).
Given dark personalities are typically viewed negatively, and EI positively, it could be considered illogical to suggest they could coincide. There is however a considerable body of evidence showing that narcissism and EI are in fact positively correlated (Nagler et al., 2014; Jauk, Freudenthaler & Neubauer, 2016; Petrides et al., 2011; Zhang et al., 2015). This may allow for narcissists to use EI to maintain their sense of superiority by controlling and dominating others. It may also suggest that high EI facilitates the development of narcissistic personalities. Negative relationships between psychopathy and EI have been consistently reported in the literature (Jauk et al., 2016; Petrides et al., 2011), unsurprisingly considering that psychopathy by definition is related to lower empathy (Jonason et al., 2009). The third Dark Triad characteristic, Machiavellianism, typically shows negative correlations with EI (Austin et al., 2007; Nagler et al., 2014; Petrides et al., 2011; Zhang et al). However, when gender is considered, this relationship becomes less clear. Research has found positive correlations between Machiavellianism and EI in females only (Bacon & Regan, 2016), but also in males only (Jauk et al., 2016).
It is recognised that EI operates differently to predict socially aversive behaviour for males and females (Davis & Nichols, 2016; Grieve & Panebianco, 2013; Jauk et al., 2016). Given this understanding, the influence of gender on relationships between dark characteristics and EI has been insufficiently explored. Furthermore, the existing findings are inconsistent, with opposing results reported (Bacon & Regan, 2016; Jauk et al., 2016). Understanding the influence of gender on relationships between socially aversive personality traits and EI may have applications in a variety of areas. These include conflict resolution in the workplace, marriage counselling, education and the criminal justice system.
The present study aims to answer the question: How does gender influence relationships between dark triad traits and emotional intelligence? Consistent with previous findings, it is hypothesised that narcissism will show a positive relationship with EI regardless of gender. It is also hypothesised that psychopathy and EI will have a negative relationship regardless of gender. Finally, it is hypothesised that the relationship between Machiavellianism and EI will be moderated by gender.
Methods
Participants
Using convenience sampling, 526 participants were recruited. Of these, 164 were excluded as they did not complete the surveys required or were under 18 years. Four participants did not specify their gender and two identified as other; given the low representation of these categories, they were excluded from the analysis. 356 participants were included in the analysis. Of these, three missed single questions; the mean fill was used to supplement missed responses. The sample consisted of 278 females and 78 males. Age ranged from 18 to 69 years, with a mean of 25.23 years (SD= 9.52). Eleven participants did not specify their age. (See Appendix 1)
Materials
The present study used the Short Dark Triad (SD3) to measure Dark Triad traits (see Appendix 2). This short-form Dark Triad questionnaire features three subscales for Machiavellianism, narcissism and psychopathy, each comprised of nine statements to which participants rate their agreement on a 5-point Likert scale from strongly disagree (1) to strongly agree (5). Examples of statements include: Its wise to keep track of information that you can use against people later (Machiavellianism), I know that I am special because everyone keeps telling me so (narcissism) and People who mess with me always regret it (psychopathy). Three narcissism items and two psychopathy items are reverse scored, then totals for each subscale are calculated to give scores for Machiavellianism, narcissism and psychopathy. The SD3 scales show acceptable reliability (Cronbachs = .71, .77 and .74 for Machiavellianism, psychopathy and narcissism respectively) (Jones & Paulhus, 2014). It also shows greater validity over the common alterative, the Dirty Dozen (Jones & Paulhus, 2014; Maples, Lamkin & Miller, 2013). The Trait Emotional Intelligence Questionnaire- Short Form (TEIQue-SF) measured EI (see Appendix 2). This questionnaire features 30 statements requiring an agreement rating on a 7-point Likert scale from completely disagree (1) to completely agree (7). Examples of statements include: Im usually able to find ways to control my emotions when I want to, and I believe Im full of personal strengths. Half of the statements are reverse-scored (such as I often find it difficult to show my affection to those close to me), and scores are totalled to give a global EI score. The questionnaire is reliable (Cronbachs = .88 and .87 for males and females respectively) (Cooper & Petrides, 2010), and support has been found for its incremental and construct validity (Oconnor, Nguyen & Anglim, 2017).
Procedure
Researchers composed the SD3 and TEIQue-SF as one questionnaire to be completed online through Qualtrics. The questionnaire was open to the public and was distributed via various forms of social media. Participants were also be asked to indicate their gender and provide other demographic information. Data was collated into SPSS for analysis.
Results
With alpha at .05, three moderated regression analyses were run to determine the impact of gender on Dark Triad trait/EI relationships. Outliers referred to high scores (>3.3 SD above the mean) in narcissism and psychopathy and were removed, as extremes for both of these traits encapsulate clinical diagnoses (Furnham et al., 2013), suggesting these participants may not represent a sub-clinical population. Following this, assumptions regarding normality, multicollinearity, univariate and multivariate outliers, independence, linearity, homoscedasticity and normality of residuals were upheld (see Appendix 3). Reliability for the three Dark Triad scales were =.713, =.628 and =.697 for Machiavellianism, narcissism and psychopathy respectively. For the TEIQue-SF, reliability was tested at =.87 (see Appendix 4). As both the narcissism and psychopathy scales show reliability below =.7 for the present sample, results should be interpreted with caution.
Table 1 below presents the moderated regression analysis for the effect of gender on the relationship between narcissism and EI.
Table 1.
Narcissism/EI relationship moderated by gender
B SEB t p
Constant 141.646
[136.577, 146.716] 2.578 54.955 >.001
Narcissism .574
[-.349, 1.496] .469 1.223 .222
Gender -2.217
[-7.890, 3.457] 2.885 -.769 .443
Narcissism * Gender 1.764
[.613, 2.915] .585 3.015 .003
Note. R2= .164
As shown in Table 1, the interaction (Narcissism*Gender) was significant (p= .003); therefore, the relationship between narcissism and EI was moderated by gender. Specifically, an enhancing moderation occurred in that being female strengthened the positive relationship between narcissism and EI, reaching significance for females only (see Appendix 5). The predictive model outlined in Table 1 was significant, F(3, 347)= 15.710, p< .001, accounting for 16.4% of the variance in EI.
Table 2 below presents the moderated regression analysis for the effect of gender on the relationship between psychopathy and EI.
Table 2.
Psychopathy/EI relationship moderated by gender
B SEB t p
Constant 144.133
[138.994, 149.272 2.613 55.164 >.001
Psychopathy -1.056
[-1.935, -.177] .447 -2.363 .019
Gender -5.898
[-11.699, -.097] 2.949 -1.200 .046
Psychopathy * Gender -.457
[-1.515, .602] .538 -.849 .397
Note. R2= .083
Table 2 above shows that the interaction (Psychopathy*Gender) was not significant; therefore, the relationship between psychopathy and EI was not moderated by gender. However, both gender and psychopathy had significant negative effects on EI. The overall regression model was significant F(3, 347)= 10.972, p< .001, accounting for 8.3% of the variance in EI. The negative effects of psychopathy on EI were significant for both males and females (see Appendix 5).
Table 3 below presents the moderated regression analysis for the effect of gender on the relationship between Machiavellianism and EI.
Table 3.
Machiavellianism/EI relationship moderated by gender
B SEB t p
Constant 142.517
[137.901, 147.132] 2.347 60.733 >.001
Machiavellianism -.364
[-1.501, .772] .578 -.630 .530
Gender -4.093
[-9.460, 1.271] 2.727 -1.501 .134
Machiavellianism * Gender -1.177
[-2.428, .073] .636 -1.852 .065
Note. R2= .092
As shown in Table 3 above, the interaction (Machiavellianism*Gender) was not significant; therefore, the relationship between Machiavellianism and EI was not moderated by gender. The overall predictive model was however significant F(3, 347)= 11.532, p< .001, accounting for 9.2% of the variance in EI. While moderation did not occur, Machiavellianism showed a significant negative relationship with EI for females only (see Appendix 5).
Discussion
The present study aimed to explore the question: How does gender influence relationships between Dark Triad traits and emotional intelligence? It was hypothesised that narcissism would show a positive relationship with EI, which would not be moderated by gender. The second hypothesis was that psychopathy would have a negative relationship with EI, which would not be moderated by gender. Finally, it was hypothesised that the relationship between Machiavellianism and EI would be moderated by gender.
Hypothesis 1, that narcissism would positively impact EI regardless of gender, was not supported. In fact, gender had an enhancing moderating effect on the positive relationship between narcissism and EI, where the relationship was significant for females only. This finding adds a new dimension to existing knowledge relating to the narcissism/EI relationship, where the effects of gender were previously under-explored. It has been found that self-serving cognitive distortions (such as narcissistic beliefs) are less predictive of antisocial behaviour in females (Van Leeuwen, Rodgers, Gibbs & Chabrol, 2014). As EI is associated with socially adaptive behaviour (Austin et al., 2007), this lack of antisocial behaviour could in fact relate to greater EI in females who possess these distortions compared with their male counterparts. Such a link would support the present studys finding that narcissistic females are more likely to possess higher EI than narcissistic males.
Hypothesis 2, that psychopathy would show a negative relationship with EI irrespective of gender, was supported. Negative relationships between psychopathy and EI were significant for males and for females; this relationship did not differ significantly based on gender. This is consistent with existing literature (Jauk et al., 2016; Petrides et al., 2011), as well as the current conceptualisation of psychopathy as a trait involving lowered empathy (Jonason et al., 2009), which logically ought to associate it with reduced EI.
The final hypothesis, that the relationship between Machiavellianism and EI would be moderated by gender, was not supported. The negative relationship between Machiavellianism and EI was however only significant for females. This reflects the mixed evidence found in previous research (Austin et al., 2007; Bacon & Regan, 2016; Jauk et al., 2016). Findings may suggest that while gender differences do exist, they are not strong enough to establish moderation. It is also possible that inconsistent results have been associated with measurement issues. Studies of relationships between Machiavellianism, EI and gender have used the Dirty Dozen (Jauk et al., 2016), which as noted previously shows lower validity than the SD3. The Mach IV is also commonly used to assess Machiavellianism (Austin et al., 2007; Bacon & Regan, 2016), however, this scale has been found to show low reliability and construct validity (Ray, 1983). It could be argued that Machiavellianism as a concept is not as well defined as the other two Dark Triad traits, particularly given it is the only trait which does not stem from clinical diagnostic definitions (Furnham et al., 2013).
Findings of the present study highlight a previously under-explored area in the literature, specifically, gender differences in relationships between EI and socially aversive personality traits. While the narcissism/EI positive relationship was relatively uncontested in current research (Nagler et al., 2014; Jauk et al., 2016; Petrides et al., 2011; Zhang et al., 2015), this relationship has been shown to exist for females only. This discovery may have a wide range of applications in explaining gender differences in relational and interpersonal behaviour. It suggests that narcissistic females may be better equipped than their male peers (via higher EI) to manipulate others in order to fuel their grandiose self-beliefs and sense of entitlement. The opposite argument could also be made, such that the heightened empathy associated with EI would discourage socially aversive behaviours in narcissistic females more so than males.
Difficulties in defining gender differences in the Machiavellianism/EI relationship were encountered in the present study, as in previous research (Austin et al., 2007; Bacon & Regan, 2016; Jauk et al., 2016). Inconsistency among the literature may in fact reflect issues with the scales used, or with unclear definition of Machiavellianism as a concept. This is in itself an important finding, as personality assessments in a clinical setting may be utilising such scales, potentially damaging clinicians capacity to accurately interpret their clients needs.
It is important to reiterate that this study yielded lowered reliabilities for narcissism and psychopathy scales than existing research. It is possible that cultural differences played a role in this effect, as previous studies have been conducted using predominantly European and US samples (Jauk et al., 2016; Nagler et al., 2014; Petrides et al., 2011). These traits may apply differently in an Australian cultural context compared with previously explored populations. Another potential issue exists within the use of the Qualtrics online survey, as it allowed multiple attempts of the questionnaire. It cannot therefore be guaranteed that each set of scores represents an individual participant, which could have been avoided in a more controlled setting.
Findings, particularly those relating to gender differences in narcissism and EI, have applications in various interpersonal contexts. Understanding the way dark traits and EI differ (or do not, as with psychopathy) between males and females could assist in empathy development programs in schools, marriage and other relationship counselling, conflict mediation, the judicial system and individual clinical psychology or counselling practice. Future research should explore gender differences in the relationship between narcissism and EI. This body of work should focus particularly on how differences may impact behaviour, as this understanding may help guide practical applications. Researchers should also further investigate potential issues with Machiavellianism as a personality trait, and work to better define the concept and develop more reliable scales for its measurement.
Overall, the present study has taken a step along the path of exploring a previously overlooked area of relationships between EI and dark personalities. It acts as a foundation for more specific research relating to the way men and women may access EI skills for socially deviant applications.
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Appendices
Participant information/normality:
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation Skewness Kurtosis
Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error
age 341 18.00 69.00 25.2639 9.56130 2.096 .132 3.673 .263
Total machiavellianism 351 13.00 43.00 27.2137 5.15502 -.016 .130 -.235 .260
Total narcissism 351 12.00 38.00 24.3932 4.49627 .113 .130 .281 .260
Total psychopathy 351 9.00 32.00 18.5356 4.77832 .319 .130 -.238 .260
total emotional intelligence 351 65.00 194.00 139.7179 23.37453 -.459 .130 .329 .260
Valid N (listwise) 341 Gender
Frequency Percent Valid Percent Cumulative Percent
Valid Male 76 21.7 21.7 21.7
Female 275 78.3 78.3 100.0
Total 351 100.0 100.0 (lets just pretend I included the SD3 and TEIQue-SF scales here hey)
Descriptive Statistics
N Minimum Maximum
Zscore: Total machiavellianism 351 -2.75725 3.06232
Zscore: Total narcissism 351 -2.75632 3.02625
Zscore: Total psychopathy 351 -1.99560 2.81781
Zscore: total emotional intelligence 351 -3.19655 2.32227
Valid N (listwise) 351 Descriptive Statistics
Mean Std. Deviation N
total emotional intelligence 139.7179 23.37453 351
Gender=Female .78 .412 351
Total machiavellianism 27.2137 5.15502 351
Assumption checks:
Correlations
total emotional intelligence Gender=Female Total machiavellianism
Pearson Correlation total emotional intelligence 1.000 -.050 -.269
Gender=Female -.050 1.000 -.164
Total machiavellianism -.269 -.164 1.000
Sig. (1-tailed) total emotional intelligence . .176 .000
Gender=Female .176 . .001
Total machiavellianism .000 .001 .
N total emotional intelligence 351 351 351
Gender=Female 351 351 351
Total machiavellianism 351 351 351
Variables Entered/Removeda
Model Variables Entered Variables Removed Method
1 Total machiavellianism, Gender=Femaleb . Enter
a. Dependent Variable: total emotional intelligence
b. All requested variables entered.
Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson
R Square Change F Change df1 df2 Sig. F Change 1 .285a .081 .076 22.46711 .081 15.422 2 348 .000 1.533
a. Predictors: (Constant), Total machiavellianism, Gender=Female
b. Dependent Variable: total emotional intelligence
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 15568.820 2 7784.410 15.422 .000b
Residual 175660.257 348 504.771 Total 191229.077 350 a. Dependent Variable: total emotional intelligence
b. Predictors: (Constant), Total machiavellianism, Gender=Female
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig. Correlations Collinearity Statistics
B Std. Error Beta Zero-order Partial Part Tolerance VIF
1 (Constant) 179.142 7.276 24.620 .000 Gender=Female -5.469 2.951 -.097 -1.853 .065 -.050 -.099 -.095 .973 1.028
Total machiavellianism -1.291 .236 -.285 -5.468 .000 -.269 -.281 -.281 .973 1.028
a. Dependent Variable: total emotional intelligence
Collinearity Diagnosticsa
Model Dimension Eigenvalue Condition Index Variance Proportions
(Constant) Gender=Female Total machiavellianism
1 1 2.817 1.000 .00 .02 .00
2 .168 4.095 .02 .85 .05
3 .015 13.531 .98 .13 .95
a. Dependent Variable: total emotional intelligence
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 118.1498 161.0649 139.7179 6.66951 351
Std. Predicted Value -3.234 3.201 .000 1.000 351
Standard Error of Predicted Value 1.356 4.345 1.987 .605 351
Adjusted Predicted Value 117.9519 161.5338 139.7161 6.69771 351
Residual -76.69635 64.79852 .00000 22.40282 351
Std. Residual -3.414 2.884 .000 .997 351
Stud. Residual -3.436 2.928 .000 1.001 351
Deleted Residual -77.71926 66.77218 .00186 22.59768 351
Stud. Deleted Residual -3.491 2.960 .000 1.005 351
Mahal. Distance .278 12.095 1.994 1.922 351
Cook's Distance .000 .087 .003 .007 351
Centered Leverage Value .001 .035 .006 .005 351
a. Dependent Variable: total emotional intelligence
Descriptive Statistics
Mean Std. Deviation N
total emotional intelligence 139.7179 23.37453 351
Gender=Female .78 .412 351
Total narcissism 24.3932 4.49627 351
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Correlations
total emotional intelligence Gender=Female Total narcissism
Pearson Correlation total emotional intelligence 1.000 -.050 .380
Gender=Female -.050 1.000 -.059
Total narcissism .380 -.059 1.000
Sig. (1-tailed) total emotional intelligence . .176 .000
Gender=Female .176 . .136
Total narcissism .000 .136 .
N total emotional intelligence 351 351 351
Gender=Female 351 351 351
Total narcissism 351 351 351
Variables Entered/Removeda
Model Variables Entered Variables Removed Method
1 Total narcissism, Gender=Femaleb . Enter
a. Dependent Variable: total emotional intelligence
b. All requested variables entered.
Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson
R Square Change F Change df1 df2 Sig. F Change 1 .381a .145 .140 21.67090 .145 29.596 2 348 .000 1.742
a. Predictors: (Constant), Total narcissism, Gender=Female
b. Dependent Variable: total emotional intelligence
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 27798.499 2 13899.250 29.596 .000b
Residual 163430.578 348 469.628 Total 191229.077 350 a. Dependent Variable: total emotional intelligence
b. Predictors: (Constant), Total narcissism, Gender=Female
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig. Correlations Collinearity Statistics
B Std. Error Beta Zero-order Partial Part Tolerance VIF
1 (Constant) 92.931 6.889 13.490 .000 Gender=Female -1.569 2.813 -.028 -.558 .577 -.050 -.030 -.028 .997 1.003
Total narcissism 1.968 .258 .379 7.627 .000 .380 .378 .378 .997 1.003
a. Dependent Variable: total emotional intelligence
Collinearity Diagnosticsa
Model Dimension Eigenvalue Condition Index Variance Proportions
(Constant) Gender=Female Total narcissism
1 1 2.824 1.000 .00 .02 .00
2 .161 4.193 .02 .91 .04
3 .016 13.459 .98 .06 .95
a. Dependent Variable: total emotional intelligence
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 114.9832 166.1625 139.7179 8.91203 351
Std. Predicted Value -2.775 2.967 .000 1.000 351
Standard Error of Predicted Value 1.308 3.794 1.906 .620 351
Adjusted Predicted Value 115.7755 166.5442 139.7290 8.92153 351
Residual -77.14141 55.23777 .00000 21.60890 351
Std. Residual -3.560 2.549 .000 .997 351
Stud. Residual -3.583 2.559 .000 1.002 351
Deleted Residual -78.17009 55.65810 -.01102 21.81764 351
Stud. Deleted Residual -3.646 2.579 -.001 1.005 351
Mahal. Distance .279 9.730 1.994 2.019 351
Cook's Distance .000 .072 .003 .007 351
Centered Leverage Value .001 .028 .006 .006 351
a. Dependent Variable: total emotional intelligence
Descriptive Statistics
Mean Std. Deviation N
total emotional intelligence 139.7179 23.37453 351
Gender=Female .78 .412 351
Total psychopathy 18.5356 4.77832 351
-6172201879600
-12534902510790
Correlations
total emotional intelligence Gender=Female Total psychopathy
Pearson Correlation total emotional intelligence 1.000 -.050 -.262
Gender=Female -.050 1.000 -.229
Total psychopathy -.262 -.229 1.000
Sig. (1-tailed) total emotional intelligence . .176 .000
Gender=Female .176 . .000
Total psychopathy .000 .000 .
N total emotional intelligence 351 351 351
Gender=Female 351 351 351
Total psychopathy 351 351 351
Variables Entered/Removeda
Model Variables Entered Variables Removed Method
1 Total psychopathy, Gender=Femaleb . Enter
a. Dependent Variable: total emotional intelligence
b. All requested variables entered.
Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson
R Square Change F Change df1 df2 Sig. F Change 1 .286a .082 .076 22.46590 .082 15.442 2 348 .000 1.536
a. Predictors: (Constant), Total psychopathy, Gender=Female
b. Dependent Variable: total emotional intelligence
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 15587.634 2 7793.817 15.442 .000b
Residual 175641.443 348 504.717 Total 191229.077 350 a. Dependent Variable: total emotional intelligence
b. Predictors: (Constant), Total psychopathy, Gender=Female
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig. Correlations Collinearity Statistics
B Std. Error Beta Zero-order Partial Part Tolerance VIF
1 (Constant) 171.064 5.915 28.922 .000 Gender=Female -6.585 2.991 -.116 -2.201 .028 -.050 -.117 -.113 .947 1.056
Total psychopathy -1.413 .258 -.289 -5.472 .000 -.262 -.281 -.281 .947 1.056
a. Dependent Variable: total emotional intelligence
Collinearity Diagnosticsa
Model Dimension Eigenvalue Condition Index Variance Proportions
(Constant) Gender=Female Total psychopathy
1 1 2.791 1.000 .01 .02 .01
2 .185 3.888 .01 .73 .09
3 .025 10.620 .98 .25 .90
a. Dependent Variable: total emotional intelligence
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 119.2695 154.1105 139.7179 6.67354 351
Std. Predicted Value -3.064 2.157 .000 1.000 351
Standard Error of Predicted Value 1.355 3.909 1.983 .617 351
Adjusted Predicted Value 120.0423 154.4892 139.7248 6.67073 351
Residual -80.63357 49.95106 .00000 22.40162 351
Std. Residual -3.589 2.223 .000 .997 351
Stud. Residual -3.615 2.227 .000 1.001 351
Deleted Residual -81.78374 50.26727 -.00688 22.58594 351
Stud. Deleted Residual -3.679 2.240 -.001 1.005 351
Mahal. Distance .276 9.597 1.994 1.913 351
Cook's Distance .000 .062 .003 .005 351
Centered Leverage Value .001 .027 .006 .005 351
a. Dependent Variable: total emotional intelligence
-404495000right0
left1247800
Scale reliability
Case Processing Summary
N %
Cases Valid 351 100.0
Excludeda 0 .0
Total 351 100.0
a. Listwise deletion based on all variables in the procedure.
Reliability Statistics
Cronbach's Alpha N of Items
.713 9
Scale Statistics
Mean Variance Std. Deviation N of Items
27.21 26.574 5.155 9
Item Statistics
Mean Std. Deviation N
M1 It is not wise to tell your secrets 3.43 .989 351
M2 Generally speaking, people won't work hard unless they have to. 3.13 1.087 351
M3 Whatever it takes, you must get the important people on your side. 3.03 1.015 351
M4 Avoid direct conflict with others because they may be useful in the future. 2.91 1.085 351
M5 It is wise to keep track of information that you can use against people later. 2.43 1.111 351
M6 You should wait for the right time to get back at people. 2.41 1.094 351
M7 There are things you should hide from other people because they don't need to know. 3.81 .912 351
M8 Make sure that your plans benefit you, not others. 2.64 1.019 351
M9 Most people can be manipulated. 3.44 1.034 351
Item-Total Statistics
Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted
M1 It is not wise to tell your secrets 23.78 23.159 .256 .711
M2 Generally speaking, people won't work hard unless they have to. 24.09 22.096 .323 .700
M3 Whatever it takes, you must get the important people on your side. 24.19 21.622 .415 .683
M4 Avoid direct conflict with others because they may be useful in the future. 24.31 21.368 .402 .685
M5 It is wise to keep track of information that you can use against people later. 24.79 19.888 .550 .654
M6 You should wait for the right time to get back at people. 24.80 20.164 .531 .659
M7 There are things you should hide from other people because they don't need to know. 23.40 22.360 .392 .688
M8 Make sure that your plans benefit you, not others. 24.58 22.805 .281 .707
M9 Most people can be manipulated. 23.78 22.293 .329 .699
Case Processing Summary
N %
Cases Valid 351 100.0
Excludeda 0 .0
Total 351 100.0
a. Listwise deletion based on all variables in the procedure.
Reliability Statistics
Cronbach's Alpha N of Items
.628 9
Item Statistics
Mean Std. Deviation N
N1 People see me as a natural leader. 3.1396 1.01159 351
N3 Many group activities can be dull without me. 2.3761 .85917 351
N4 I know that I am special because everyone keeps telling me. 2.3077 .87631 351
N5 I like to get acquainted with important people. 3.0484 .97421 351
N7 I have been compared to famous people. 2.3305 1.06054 351
N9 I insist on getting the respect I deserve. 3.3305 1.00237 351
Narcissism 2 reverse scored 2.7037 1.07329 351
Narcissism 6 reverse scored 2.6724 1.09977 351
Narcissism 8 reverse scored 2.4843 .97638 351
Item-Total Statistics
Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted
N1 People see me as a natural leader. 21.2536 15.984 .397 .578
N3 Many group activities can be dull without me. 22.0171 16.417 .440 .573
N4 I know that I am special because everyone keeps telling me. 22.0855 16.644 .392 .583
N5 I like to get acquainted with important people. 21.3447 16.747 .316 .599
N7 I have been compared to famous people. 22.0627 17.190 .216 .624
N9 I insist on getting the respect I deserve. 21.0627 17.699 .179 .632
Narcissism 2 reverse scored 21.6895 15.786 .384 .580
Narcissism 6 reverse scored 21.7208 16.785 .247 .618
Narcissism 8 reverse scored 21.9088 17.186 .257 .613
Scale Statistics
Mean Variance Std. Deviation N of Items
24.3932 20.216 4.49627 9
Case Processing Summary
N %
Cases Valid 351 100.0
Excludeda 0 .0
Total 351 100.0
a. Listwise deletion based on all variables in the procedure.
Reliability Statistics
Cronbach's Alpha N of Items
.697 9
Item Statistics
Mean Std. Deviation N
P3 Payback needs to be quick and nasty. 1.9174 .88577 351
P4 People often say I'm out of control. 1.9715 .89716 351
P5 It's true i can be mean to others. (or enjoy having sex with people I hardly know.) 2.4103 1.19872 351
P6 People who mess with me always regret it. 2.2422 .96868 351
P8 I like to pick on losers. 1.4046 .63820 351
P9 I'll say anything to get what i want. 1.8946 .92752 351
P1 I like to get revenge on authorities. 1.9801 .92406 351
Psychopathy 2 reverse scored 2.5556 1.01793 351
Psychopathy 7 reverse scored 2.1595 1.24793 351
Item-Total Statistics
Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted
P3 Payback needs to be quick and nasty. 16.6182 18.802 .422 .663
P4 People often say I'm out of control. 16.5641 18.738 .423 .663
P5 It's true i can be mean to others. (or enjoy having sex with people I hardly know.) 16.1254 17.207 .421 .662
P6 People who mess with me always regret it. 16.2934 17.699 .515 .643
P8 I like to pick on losers. 17.1311 20.446 .343 .680
P9 I'll say anything to get what i want. 16.6410 18.882 .383 .670
P1 I like to get revenge on authorities. 16.5556 17.745 .544 .639
Psychopathy 2 reverse scored 15.9801 20.037 .193 .707
Psychopathy 7 reverse scored 16.3761 18.950 .214 .713
Scale Statistics
Mean Variance Std. Deviation N of Items
18.5356 22.832 4.77832 9
Case Processing Summary
N %
Cases Valid 351 100.0
Excludeda 0 .0
Total 351 100.0
Reliability Statistics
Cronbach's Alpha N of Items
.870 31
Item Statistics
Mean Std. Deviation N
1. Expressing emotions with words is not a problem for me. 4.5157 1.77254 351
3. On the whole, I'm a highly motivated person. 4.6667 1.50238 351
6. I can deal effectively with people. 5.1225 1.33066 351
9. I feel that i have a number of good qualities. 5.1880 1.35603 351
11. I'm usually able to influence the way other people feel. 4.1453 1.40975 351
15. On the whole, I'm able to deal with stress. 4.2650 1.61454 351
17. I'm normally able to 'get into other people shoes' and experience their emotion. 4.9430 1.58462 351
19. I'm usually able to find ways to control my emotions, when I want to. 4.6838 1.49274 351
20. On the whole, I'm pleased with my life. 5.0028 1.55747 351
21. I would describe myself as a good negotiator. 4.5840 1.40130 351
23. I often pause and think about my feelings. 4.3390 1.61657 351
24. I believe I'm full of personal strengths 4.7464 1.51981 351
27. I generally believe that things will work out in life. 5.1823 1.54765 351
29. Generally, I'm able to adapt to new environments. 5.0826 1.40062 351
30. Others admire me for being relaxed. 4.1937 1.75404 351
EI16 reversed 4.6068 1.92112 351
EI2 reversed 5.2707 1.54484 351
EI18 reversed 4.2194 1.68532 351
EI4 reversed 3.9744 1.67398 351
EI5 reversed 5.1709 1.67992 351
EI7 reversed 3.4729 1.53762 351
EI22 reversed 3.9772 1.62289 351
EI8 reversed 4.1567 1.78276 351
EI10 reversed 4.5641 1.72238 351
EI25 reversed 4.2080 1.77910 351
EI26 reversed 4.5071 1.30902 351
EI12 reversed 5.0598 1.76938 351
EI13 reversed 5.9715 1.29142 351
EI14 reversed 4.9202 1.51353 351
EI28 reversed 4.9772 1.70530 351
Item-Total Statistics
Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted
1. Expressing emotions with words is not a problem for me. 138.0313 458.339 .480 .864
3. On the whole, I'm a highly motivated person. 137.8803 457.517 .594 .862
6. I can deal effectively with people. 137.4245 462.096 .596 .863
9. I feel that i have a number of good qualities. 137.3590 461.019 .603 .863
11. I'm usually able to influence the way other people feel. 138.4017 482.378 .219 .870
15. On the whole, I'm able to deal with stress. 138.2821 460.426 .504 .864
17. I'm normally able to 'get into other people shoes' and experience their emotion. 137.6040 474.577 .302 .869
19. I'm usually able to find ways to control my emotions, when I want to. 137.8632 465.118 .475 .865
20. On the whole, I'm pleased with my life. 137.5442 449.797 .692 .860
21. I would describe myself as a good negotiator. 137.9630 466.453 .488 .865
23. I often pause and think about my feelings. 138.2080 479.079 .230 .871
24. I believe I'm full of personal strengths 137.8006 457.994 .579 .862
27. I generally believe that things will work out in life. 137.3647 459.404 .545 .863
29. Generally, I'm able to adapt to new environments. 137.4644 461.781 .568 .863
30. Others admire me for being relaxed. 138.3533 467.103 .366 .868
EI16 reversed 137.9402 472.359 .262 .871
EI2 reversed 137.2764 475.892 .292 .869
EI18 reversed 138.3276 456.632 .534 .863
EI4 reversed 138.5726 461.320 .470 .865
EI5 reversed 137.3761 455.167 .557 .863
EI7 reversed 139.0741 471.074 .367 .867
EI22 reversed 138.5698 476.474 .266 .870
EI8 reversed 138.3903 455.147 .521 .863
EI10 reversed 137.9829 463.314 .427 .866
EI25 reversed 138.3390 485.299 .121 .874
EI26 reversed 138.0399 483.627 .219 .870
EI12 reversed 137.4872 452.319 .565 .862
EI13 reversed 136.5755 477.239 .337 .868
EI14 reversed 137.6268 462.543 .509 .864
EI28 reversed 137.5698 461.034 .464 .865
Scale Statistics
Mean Variance Std. Deviation N of Items
142.5470 497.946 22.31470 31
Moderated regression analyses
Run MATRIX procedure:
************* PROCESS Procedure for SPSS Release 2.16.3 ******************
Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2013). www.guilford.com/p/hayes3
**************************************************************************
Model = 1
Y = EI_total
X = Machiave
M = Female
Sample size
351
Coding of categorical M variable for analysis:
Female D1
.00 .00
1.00 1.00
**************************************************************************
Outcome: EI_total
Model Summary
R R-sq MSE F df1 df2 p
.3040 .0924 500.1787 11.5316 3.0000 347.0000 .0000
Model
coeff se t p LLCI ULCI
constant 142.5170 2.3466 60.7334 .0000 137.9016 147.1323
Machiave -.3638 .5775 -.6298 .5292 -1.4997 .7722
D1 -4.0939 2.7277 -1.5008 .1343 -9.4589 1.2711
int_1 -1.1774 .6358 -1.8518 .0649 -2.4280 .0732
Covariance matrix of regression parameter estimates
constant Machiave D1 int_1
constant 5.5065 -.0164 -5.5065 .0164
Machiave -.0164 .3335 .0164 -.3335
D1 -5.5065 .0164 7.4405 .0729
int_1 .0164 -.3335 .0729 .4043
Product terms key:
int_1 : D1 X Machiave
R-square increase due to interaction:
R2-chng F df1 df2 p
.0110 3.4290 1.0000 347.0000 .0649
***************************************************************************
Conditional Effect of Focal Predictor in Groups Defined by the Moderator Variable:
Female coeff se t p LLCI ULCI
.0000 -.3638 .5775 -.6298 .5292 -1.4997 .7722
1.0000 -1.5412 .2660 -5.7947 .0000 -2.0643 -1.0181
***************************************************************************
Data for visualizing conditional effect of X on Y
Paste text below into a SPSS syntax window and execute to produce plot.
DATA LIST FREE/Female Machiavellianism_total EI_total.
BEGIN DATA.
.0000 -5.1550 144.3921
1.0000 -5.1550 146.3678
.0000 .0000 142.5170
1.0000 .0000 138.4231
.0000 5.1550 140.6418
1.0000 5.1550 130.4784
END DATA.
GRAPH/SCATTERPLOT=Machiavellianism_total WITH EI_total BY Female.
******************** ANALYSIS NOTES AND WARNINGS *************************
Level of confidence for all confidence intervals in output:
95.00
NOTE: The following variables were mean centered prior to analysis:
Machiave
NOTE: All standard errors for continuous outcome models are based on the HC3 estimator
------ END MATRIX -----
Run MATRIX procedure:
************* PROCESS Procedure for SPSS Release 2.16.3 ******************
Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2013). www.guilford.com/p/hayes3
**************************************************************************
Model = 1
Y = EI_total
X = Narcissi
M = Female
Sample size
351
Coding of categorical M variable for analysis:
Female D1
.00 .00
1.00 1.00
**************************************************************************
Outcome: EI_total
Model Summary
R R-sq MSE F df1 df2 p
.4054 .1644 460.5064 15.7100 3.0000 347.0000 .0000
Model
coeff se t p LLCI ULCI
constant 141.6464 2.5775 54.9550 .0000 136.5770 146.7159
Narcissi .5737 .4690 1.2232 .2221 -.3488 1.4962
D1 -2.2169 2.8845 -.7685 .4427 -7.8903 3.4565
int_1 1.7643 .5852 3.0148 .0028 .6133 2.9153
Covariance matrix of regression parameter estimates
constant Narcissi D1 int_1
constant 6.6435 -.5351 -6.6435 .5351
Narcissi -.5351 .2200 .5351 -.2200
D1 -6.6435 .5351 8.3205 -.5849
int_1 .5351 -.2200 -.5849 .3425
Product terms key:
int_1 : D1 X Narcissi
R-square increase due to interaction:
R2-chng F df1 df2 p
.0190 9.0888 1.0000 347.0000 .0028
***************************************************************************
Conditional Effect of Focal Predictor in Groups Defined by the Moderator Variable:
Female coeff se t p LLCI ULCI
.0000 .5737 .4690 1.2232 .2221 -.3488 1.4962
1.0000 2.3380 .3500 6.6799 .0000 1.6496 3.0264
***************************************************************************
Data for visualizing conditional effect of X on Y
Paste text below into a SPSS syntax window and execute to produce plot.
DATA LIST FREE/Female Narcissism_total EI_total.
BEGIN DATA.
.0000 -4.4963 139.0669
1.0000 -4.4963 128.9171
.0000 .0000 141.6464
1.0000 .0000 139.4295
.0000 4.4963 144.2260
1.0000 4.4963 149.9420
END DATA.
GRAPH/SCATTERPLOT=Narcissism_total WITH EI_total BY Female.
******************** ANALYSIS NOTES AND WARNINGS *************************
Level of confidence for all confidence intervals in output:
95.00
NOTE: The following variables were mean centered prior to analysis:
Narcissi
NOTE: All standard errors for continuous outcome models are based on the HC3 estimator
------ END MATRIX -----
393405527182
Run MATRIX procedure:
************* PROCESS Procedure for SPSS Release 2.16.3 ******************
Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2013). www.guilford.com/p/hayes3
**************************************************************************
Model = 1
Y = EI_total
X = Psychopa
M = Female
Sample size
351
Coding of categorical M variable for analysis:
Female D1
.00 .00
1.00 1.00
**************************************************************************
Outcome: EI_total
Model Summary
R R-sq MSE F df1 df2 p
.2880 .0829 505.3961 10.9718 3.0000 347.0000 .0000
Model
coeff se t p LLCI ULCI
constant 144.1331 2.6128 55.1639 .0000 138.9942 149.2721
Psychopa -1.0557 .4468 -2.3627 .0187 -1.9346 -.1769
D1 -5.8982 2.9494 -1.9998 .0463 -11.6992 -.0972
int_1 -.4566 .5381 -.8485 .3967 -1.5149 .6018
Covariance matrix of regression parameter estimates
constant Psychopa D1 int_1
constant 6.8268 -.4248 -6.8268 .4248
Psychopa -.4248 .1997 .4248 -.1997
D1 -6.8268 .4248 8.6990 -.4359
int_1 .4248 -.1997 -.4359 .2895
Product terms key:
int_1 : D1 X Psychopa
R-square increase due to interaction:
R2-chng F df1 df2 p
.0014 .7200 1.0000 347.0000 .3967
***************************************************************************
Conditional Effect of Focal Predictor in Groups Defined by the Moderator Variable:
Female coeff se t p LLCI ULCI
.0000 -1.0557 .4468 -2.3627 .0187 -1.9346 -.1769
1.0000 -1.5123 .2998 -5.0441 .0000 -2.1020 -.9226
***************************************************************************
Data for visualizing conditional effect of X on Y
Paste text below into a SPSS syntax window and execute to produce plot.
DATA LIST FREE/Female Psychopathy_total EI_total.
BEGIN DATA.
.0000 -4.7783 149.1778
1.0000 -4.7783 145.4613
.0000 .0000 144.1331
1.0000 .0000 138.2349
.0000 4.7783 139.0884
1.0000 4.7783 131.0085
END DATA.
GRAPH/SCATTERPLOT=Psychopathy_total WITH EI_total BY Female.
******************** ANALYSIS NOTES AND WARNINGS *************************
Level of confidence for all confidence intervals in output:
95.00
NOTE: The following variables were mean centered prior to analysis:
Psychopa
NOTE: All standard errors for continuous outcome models are based on the HC3 estimator
------ END MATRIX -----
Title that summarises your research topic
Abstract
A summary of your research, generally one sentence per area
Summary of link between your topics
Rationale for study
Statistic(s) and participants
Main results
Main implications/conclusions
200 words max, does not count to your word countTitle again
Introduce your topic(s) with cited definitions.
Establish the importance of understanding the link between your topic(s)
What has previous research found?
DO NOT INCLUDE information that is not pertinent to your research question.
Start broad and narrow down to your research.
Make sure your points are logical and flow, dont abruptly change topics or you will confuse your audience.
Hypothesis should be phrased in current/future language at this point it is hypothesised not it was hypothesised.
In general, at least a third of your word count should be used here (500 words or more)
Methods
Participants
How many participants are there?
How were they collected?
How many were excluded (not based on assumptions) and why?
Presenting demographics in an APA table will save on word count (below is an example, these are not your demographics), at the very least you will be expected to state the age and one of the gender variables
Table 1. Sample Demographics.
Biological Sex N M(SD) age Age range
Male 95 24.56 (3.353) 18-30
Female 101 24.67 (3.726) 18-30
Unspecified 4 24 (3.742) 20-29
Primary School High School Undergraduate Masters/PhD Unspecified
Highest Education level 6 94 82 12 6
Single Partner (>18months) Partner/ Married (<18months) Unspecified
Relationship Status 117 9 71 3
Materials
What scales did you use?
What are the meant to measure?
How are they scored?
Cronbachs alphas
Example items if you have the word count.
Do you have any citations of other people using the scale that you can use to claim validity with?
Procedure
The steps required to completely re-run your study from start to finish.
Will likely be 2-3 sentences at the most for this study.
Results
Opening statement should include.
Alpha
The stat that was run and why.
The phrasing on this will infer what your IVs, DVs, and CVs are.
Assumptions and anyone removed based on assumptions.
Descriptives (usually presented in a table, example below)
Remember with tables:
Introduce in text.
Present table.
Refer to some interesting point of the table that isnt just restating something in the table. (e.g. gender split, whether the averages where high or low based on the mean, what this might mean for generalisability)
Table 2. Sample Descriptives
Scale Subscale N M SD Sample min-Max
UPPS-P Negative Urgency 200 30.355 7.896 12-48
Positive Urgency 200 28.730 8.906 14-56
Lack of Premeditation 200 20.225 4.920 11-38
Lack of Perseverance 200 21.945 5.083 10-36
Other scale Sub1 ## ###.## #.## ##-##
Sub2 ## ###.## #.## ##-##
Present your actual resultsANOVAs will detail interactions, main effects, and pairwise comparisons, with F statements.
Regression will detail R2, adjusted R2 as well as F statements for EACH model run, and then the coefficients for each model.
Make use of tables to save on word count, examples are shown below, highlighted to emphasize where each comes from in your output (do not highlight your tables)
Yellow come from model summary in output.
Green come from ANOVA in output.
Blue come from Coefficients in output.
Pink come from Bootstrap for coefficients in output if you ran a bootstrap or from coefficients if you didnt, with the exception of confidence intervals (which are only present in bootstrapping)
Table 3. Regression Model Summary
Model R2 Adj R2 dfF p
1 2 3 If you present everything for your F statements in a table like table 3, you do not need to write out your F statements. It is up to you whether you want a table or text.
Table 4. Detailed Regression Results Predicting _____
B [95% CI] Stand. Error t p Semi-Partial
1 Constant 23.120
[20.251, 26.082] 1.491 18.004 <.001 MCSD -.950
[-1.472, -.438] .264 -.232 -3.689 .001 -.232
2 Constant 5.062
[-2.270, 11.515] 3.458 1.456 .145 MCSD -.397
[-.850, .070] .235 -.097 -1.510 .089 -.090
Impulsivity 6.781
[4.083, 9.837] 1.452 .356 5.541 <.001 .329
Bootstrapped to 5000. MSCD = _____, CI = _____.
But what do the numbers mean?
is your standardized beta weights. These allow for direct comparisons of predictive strength. The bigger the number, regardless of direction, the more important the predictor.
Semi-Partial shown in output as Part is a measure of the unique variance accounted for by each variable when taking into account the other variables in the model.
B is your unstandardized beta weights. A 1 point increase in your IV results in an increase of B in your DV.
[95% CI] across all of your bootstrapped samples, 95% of the beta weights fell within this range.
`
Discussion
Start specific, restate your aim and whether your data supported your hypotheses or not.
Broaden out from your hypotheses, contrasting to previous literature, and what this means in basic easy to follow language.
What are the implications of this in a broader sense, think in terms of research, clinical application, and/or potential real-world change. Keep in mind who your sample represent and how far you can generalise.
What are the limitations of your study? Keep it to 2 or 3 of your biggest limitations (try to think beyond sample size) and what this means for your research and potential future research.
Conclude with a statement that is more than just a summary, what is the take home point of your research that you want the reader to walk away with if nothing else?
In general, at least a third of your word count should be used here (500 words or more)
References
Does not count towards your word count.
APA formatting
Willie, C., Gill, P., Teese, R., Jago, A., & Stavropoulos, V. (2024).Re-evaluating and Refining Popular Conceptualisations of Impulsivity: Introducing the UPPS-P 39. [Manuscript submitted for publication].
Appendices
Put your SPSS output here in whatever format you want as long as it is readable, it does not have to be in APA formatted tables for the appendices.
