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EXPLORING FACTORS ASSOCIATED WITH EMPATHY i

Sociodemographic, trait, and state predictors of empathy in psychology students

Ashley Lamont

U4219453

Australian National University

Supervisor: Associate Professor Rhonda Brown

January 2017

Author Note

A thesis submitted in partial fulfilment of the requirements for the Master of Clinical

Psychology program at the Australian National University. As per the requirements stipulated

in the Clinical Psychology Program Handbook, the abstract, article, and appendices have

been formatted in accordance to guidelines prescribed by the relevant journal of submission

(Health Psychology).

EXPLORING FACTORS ASSOCIATED WITH EMPATHY ii

Acknowledgements

Three very long years and an enormous emotional ride. Even when I have felt like my

back was to the wall – ils ne veulent pas que je succède has been a mental challenge for a large

part of this project – there have been many people there to support me and I thank you all. Of

particular note I would like to thank my supervisor, Rhonda Brown, for salvaging me from a

prior research project and having the patience to deal with the neuroses that followed my

program change through to submission. I would also like to thank my co-supervisor Boris

Bizumic for his assistance throughout this project. Conceptually, he assisted with the

construction of the project both directly and via facilitating his lab group where I gained

additional feedback and perspective from both he and his students, notably Conal Monaghan

and Liz Huxley. Boris was also a valuable sounding board for discussing hypotheses

regarding personality constructs and provided insightful suggestions regarding the

interpretation and presentation of results. I regret to say I could have communicated to Boris

much better during my project and yet his feedback has always been timely, informative, and

greatly appreciated.

Finally, I would like to also thank the friends, family, and special people in my life

who have enabled and supported me to continue fighting through impatience and

demoralisation to be able to complete this task. It has been a challenging process although the

rewards this promises make me optimistic of the opportunities this offers for the future.

EXPLORING FACTORS ASSOCIATED WITH EMPATHY iii

Contents:

Abstract .......................................................................................................................... 1

Background: ............................................................................................................... 1

Methods: .................................................................................................................... 1

Results: ....................................................................................................................... 1

Conclusions: ............................................................................................................... 2

Exploring Factors Associated with Empathy ................................................................. 4

Method ........................................................................................................................... 9

Participants ................................................................................................................. 9

Materials and Procedure .......................................................................................... 10

Statistical Analyses .................................................................................................. 14

Results .......................................................................................................................... 14

Mediational Analyses............................................................................................... 15

Discussion .................................................................................................................... 16

References .................................................................................................................... 23

EXPLORING FACTORS ASSOCIATED WITH EMPATHY iv

Tables and figures

Table 1: Sample Characteristics of the Psychology Student Sample (N=382)……………… 32

Table 2: Means and Standard Deviations (SD) of Empathy and Personality Construct and

State Predictors of Total, Affective, and Cognitive Empathy………………………………….. 33

Table 3: Correlational Matrix of Empathy, and Personality Construct and State Predictors of

Total, Affective, and Cognitive Empathy…………………………………………………………. 34

Table 4: Hierarchical Multiple Linear Regression Analyses for Associations between Total,

Affective, and Cognitive Empathy and Demographic, Personality Construct, and State

Variables…………………………………………………………………………………………….... 36

Table 5: Hierarchical Multiple Linear Regression Analyses for Associations between Total,

Affective, and Cognitive Empathy scales and Demographic, Personality Construct, and State

Variables, Including Continuous Measure of ASD Traits…………………………………….... 38

Table 6: Hierarchical Regression Analyses Exploring Contributions of Interaction Effects

between Interoceptive Sensibility and Personality Constructs on Associations between

Personality Constructs and Body Perception……………………………………………………. 40

Table 7: Sobel Mediation Analyses Exploring Indirect Effects of Interoceptive Sensibility on

the Association between Personality Constructs and Empathy………………………………... 41

Running head: EXPLORING FACTORS ASSOCIATED WITH EMPATHY 1

Abstract

Background:

Empathy is gaining increased attention in health practitioners, especially in light of

the reported declines in empathy over time. However, empathy as a construct and its

interactions with associated variables are poorly understood.

Methods:

Undergraduate psychology students (N=380) completed a questionnaire assessing

empathy, age, gender, autistic traits, Machiavellianism, grandiose and vulnerable narcissism,

burnout, affective distress, and interoception. Hierarchical multiple regression analyses

examined the factors that most strongly predicted variance in empathy scores. Mediational

analyses explored the possible indirect role of affective symptoms (i.e. stress, anxiety, and

depression) and interoceptive sensibility in mediating with the relationship between the high

expression of the trait variables to low empathy levels.

Results:

Hierarchical multiple regression analyses predicted significant variance in global

(40.4%), affective (40%), and cognitive (32.9%) empathy. A range of demographic (male

gender), personality (high Machiavellianism and autistic traits), and state and body

perception variables (high anxiety and low awareness of Autonomic Nervous System

reactivity; ANS-R) predicted lower empathy, although personality constructs were generally

the strongest predictors. Indirect mediational relationships were found to exist between high

Machiavellian views to low global empathy, with high interoceptive sensibility as the

mediator.

Conclusions:

Empathy was predicted by a combination of demographics (i.e. male gender),

personality constructs (i.e. autistic and Machiavellianism), and state factors (i.e. high ANS-R,

EXPLORING FACTORS ASSOCIATED WITH EMPATHY 2

low anxiety), suggesting that it is likely determined by a combination of factors. Further, the

results point to the potential importance of targeting aspects of the self that can be changed

such as autonomic arousal and affective symptoms to assist adults in maximising their

empathy levels. The results are likely to have implications for the training of psychology

clinicians and other health professionals.


Sociodemographic, trait and state predictors of empathy in psychology students

Empathy is simply defined as the capacity to recognize another person’s emotional

state and spontaneously and appropriately respond emotionally to them (Decety & Jackson,

2004). Thus, it is a multidimensional construct that includes two components: cognitive

empathy (i.e., recognition and identification of another person’s emotional state) and

affective or emotional empathy (i.e., matching of emotional arousal in the observer and

observed) (Baron-Cohen & Wheelwright, 2004; Chakrabarti, Bullmore, & Baron-Cohen,

2006). The two empathy processes are reported to be associated with separate neural

networks as described in the neuroimaging literature (Bird & Viding, 2014).

In addition, motivational components (e.g., aims, values, or biases that attenuate or

augment empathic responding) are suggested to exist (Bird & Viding, 2014; Coutinho, Silva,

& Decety, 2014; Decety & Lamm, 2006). However, it is unclear whether empathy is an

internal predisposition, communication skill (Auxiliadora Trevizan et al., 2015), process that

involves vicarious matching of emotion (Eisenberg & Lennon, 1983), interactive process that

is shared between two people, or if it is better to examine the outcomes of empathy (e.g.,

prosocial behaviour) (Eisenberg & Lennon, 1983; Gleichgerrcht & Decety, 2013). In this

study, we assessed empathy as a trait-based construct as suggested by Baron-Cohen and

colleagues (Baron-Cohen, Golan, & Ashwin, 2009; Baron-Cohen & Wheelwright, 2004;

Chakrabarti et al., 2006) and its components were measured using the Empathy Quotient

(Baron-Cohen & Wheelwright, 2004).

The specific processes that contribute to empathic responding remain largely

speculative. Social neuroscience researchers have recently suggested that emotional

contagion (i.e., innate mirroring of another person’s autonomic and neurophysiological

emotional response) may underpin the development of affective empathy, and as a

consequence, the empathizer may be able to derive insight, acknowledge the emotional


arousal, and generate a shared emotional state (Arizmendi, 2011; Bird & Viding, 2014;

Coutinho et al., 2014; Gleichgerrcht & Decety, 2013; Khanjani et al., 2015). However,

cognitive empathy processes - that are thought to assist people in understanding the

emotional experiences of others (Ahrweiler, Neumann, Goldblatt, Hahn, & Scheffer, 2014) -

are thought to overlap significantly with Theory of Mind (i.e., ability to impute mental states

to self and others) (Premack & Woodruff, 1978) and perspective-taking (Decety & Lamm,

2006; Decety & Meyer, 2008). Finally, higher-order motivational factors are thought to assist

the empathizer in balancing the demands of the situation against their own explicit and

implicit aims to prevent the shared emotion from becoming aversive (Campbell-Yeo,

Latimer, & Johnston, 2008; Coutinho et al., 2014; Decety & Lamm, 2006).

Empathy has recently gained attention in the health professions due to its importance

in clinical practice. However, few prior studies have empirically examined empathy in

training clinicians including psychology students (Coutinho et al., 2014; Halpern, 2014; Pohl,

Hojat, & Arnold, 2011) or healthy adults. Nonetheless, there is a small literature pertaining to

medical student empathy (Neumann et al., 2011; Sulzer, Feinstein, & Wendland, 2016)

showing that their empathy levels tend to decline with years of medical training, persisting

into early clinical practice (Mangione et al., 2002; Nunes, Williams, Sa, & Stevenson, 2011).

Importantly, the efforts made to address this decline have so far been unsuccessful (Sulzer et

al., 2016). Furthermore, prior studies in medical students have rarely been informed by

theory, have examined few potential predictors, and tend to use narrow definitions of the

construct. For example, empathy has previously been defined as cognitive empathy only,

whereas affective empathy has been operationalized as “sympathy” due to a concern that its

function may adversely impact on objective decision-making (Hojat et al., 2009).

With relevance to this study, few prior studies have examined the likely determinants

of empathy in healthy adults (e.g. university students) in a systematic and quantitative


manner. However, based on the qualitative research, researchers have explained the decline

in medical student empathy as due to developing a cynicism towards others (Hojat et al.,

2009) that is thought to protect doctors from experiencing distress in a challenging work

environment (Colliver, Conlee, Verhulst, & Dorsey, 2010). Thus, work-stress, time pressure,

adverse working conditions, and high workload have been reported to detrimentally impact

on empathy (Ahrweiler et al., 2014; Derksen, Bensing, Kuiper, van Meerendonk, & Lagro-

Janssen, 2015), although this has rarely been explored empirically.

Burnout has also been discussed in relation to clinician empathy. The compassion-

fatigue hypothesis posits that empathic responding and compassion increases the burden on

clinicians by requiring them to interact with and respond to distressed individuals in

challenging work circumstances, which then predisposes them to experience burnout

(Derksen, Bensing, Kuiper, van Meerendonk, & Lagro-Janssen, 2015). However, the small

empirical literature suggests that empathy actually protects against burnout (Gleichggercht &

Decety, 2013; Mandel & Scheinle, 2012; Neumann et al., 2011), whereas the doctors with

alexithymia who have difficulties identifying and describing their own emotions may

experience burnout more often (Gleichggercht & Decety. 2013).

Demographic factors

Several empirical studies have examined demographics such as gender and medical

specialty (Ahrweiler et al., 2014; Neumann et al., 2011), finding that lower empathy levels

were associated with male gender (especially low affective empathy) (Gleichgerrcht &

Decety, 2013) and the technical medical specialties (Kataoka, Koide, Hojat, & Gonnella,

2012). Age-related declines in empathy have been documented and they are generally

attributed to a coincident age-related change in cognition (Khanjani et al., 2015; O'Brien,

Konrath, Grühn, & Hagen, 2012). However, these results are contentious due to the small to

non-significant effect sizes (Grühn, Rebucal, Diehl, Lumley, & Labouvie-Vief, 2008).


Further, recent longitudinal research has shown the results may be better explained by cohort

effects (Grühn et al., 2008), and that if anything the relationship is non-linear with empathy

levels peaking in middle-age (O'Brien, Konrath, Grühn, & Hagen, 2012).

Trait factors

Several traits and associated disorders have been shown to be related to low empathy

levels. People with Autism Spectrum Disorder (ASD) are reported to lack empathy, and they

score low on global empathy (Baron-Cohen & Wheelwright, 2004), cognitive empathy, and

emotional reactivity aspects of affective empathy (Dziobek et al., 2008). Similarly, Autism

Spectrum Quotient (AQ) score has been shown to be negatively associated with global

(Baron-Cohen & Wheelwright, 2004), cognitive, and affective empathy (Melchers, Montag,

Markett, & Reuter, 2015). The deficits in cognitive empathy in people with ASD are thought

to reflect a broader impairment in Theory of Mind, and some researchers have tended to treat

Theory of Mind and cognitive empathy as synonymous constructs (Baron-Cohen &

Wheelwright, 2004).

A variety of mechanisms have been posited to explain the empathy deficits in people

with ASD. In particular, impaired autonomic processing – specifically, greater attention given

to autonomic arousal sensations – is thought to best explain the emotion processing deficits in

people with ASD and those in the general population (Garfinkel et al., 2016). In addition, the

processing of self-derived autonomic nervous system stimuli (e.g. heart rate) is thought to be

an early step in empathy processing (Arizmendi, 2011; Decety & Lamm, 2006), thus, if

greater attention is given to these sensations then this might augment (or interfere with)

empathy, as explained in greater detail below.

In the personality construct literature, the “Dark Triad” – comprised of

Machiavellianism, narcissism, and psychopathy – has been shown to share a core of


undesirable interpersonal characteristics that include low empathy (Jonason & Krause, 2013).

In particular, people high on Machiavellianism are expected to show low responsiveness to

other peoples’ distress, although they may be less impaired dealing with other emotions (Wai

& Tiliopoulos, 2012). They also have a propensity to adopt an external locus of control that

can promote a willingness to manipulate others in what might be perceived to be an unfair

world (McIlwain, 2013). Thus, Machiavellianism is comprised of cynical views about the

nature of the world and a willingness to use deceitful tactics in order to achieve one’s goals

and needs without concern for others (Monaghan, Bizumic, & Sellbom, 2016). A

manifestation of this tends to be low empathy in both cognitive and affective domains

(Jonason & Krause, 2013), but it is more pronounced in the affective domain (Jonason &

Krause, 2013).

In contrast, people high on narcissism are expected to show greater awareness of other

people’s emotions as they have the capacity to understand the extent to which other people

respect or admire them. Several researchers suggest that narcissism may even be related to

high cognitive empathy as the individuals are practiced in assessing how they are viewed by

others (Wai & Tiliopoulous, 2012). Nonetheless, they are typically considered to act in ways

that are inconsistent with empathy, for example, their grandiose self-perception promotes a

willingness to disregard normal social conventions (Watson & Morris, 1990). However,

narcissism is also related to a hypersensitive vulnerability to perceived threat (Fossati et al.,

2009; Gentile et al., 2013). Thus, people high on narcissism may respond with high personal

distress but less other-directed concern and this may compromise the experience of affective

empathy (Watson & Morris, 1990).

Psychopathy is the final element in the Dark Triad. It is associated with the most

profound interpersonal deficits, and some researchers indicate that it may be difficult to


identify adaptive interpersonal styles in people who are high on this trait (Paulhus &

Williams, 2002). Nonetheless, psychopathy is notably associated with a profound lack of

anxiety reactivity but also sufficient cognitive empathy so that affected individuals tend to act

manipulatively (Paulhus & Williams, 2002). Thus, they may have a reduced capacity to

experience autonomic reactivity and this may act to impair their ability to experience emotion

and empathy (Paulhus & Williams, 2002).

Trait activation and expression

Personality traits are defined as stable characteristics but they are also assumed to be

latent variables inasmuch as they can be activated by interactions with a person’s

environment (Tett & Guterman, 2000). This activation in the expression of personality

constructs is typically discussed in the literature in terms of specific situations that can

interact with the latent traits. However, traditional personality theory asserts that a

predisposition can be provoked or elicited by current demands which may include a person’s

emotional state (e.g., mood). For example, a person’s emotional state (e.g. high perceived

stress) may activate the effects of certain latent traits (e.g. Machiavellianism) (Tett &

Guterman, 2000) and this increase in trait expression may adversely impact on empathy.

Such a premise will be examined using mediational analyses in this study, as detailed below.

State factors

To date, states have rarely been explored in relation to empathy, although high stress

(Ahrweiler et al., 2014; Neumann et al., 2011), anxiety, depressive symptoms, and neurotic

and psychotic disturbances (Diseker & Michielutte, 1981; Grühn et al., 2008; Johnson,

Cheek, & Smither, 1983) have been shown to be related to low empathy levels. The studies

are only correlational, but it is noteworthy that anxiety, stress, and tension can reduce the

responsiveness of the mirror neuron system (which is implicated in affective empathy)


(Arizmendi, 2011; Neumann et al., 2011), and empathy is reduced in people with symptoms

of the states (Neumann et al., 2011).

As mentioned earlier, burnout has previously been examined in relation to empathy,

although typically only in the context of the flawed “compassion fatigue” hypothesis

(Derksen, Bensing, Kuiper, van Meerendonk, & Lagro-Janssen, 2015), such that high

empathy levels were shown to protect against compassion fatigue rather than increasing it

(Gleichgerrcht & Decety, 2013; Mandel & Schwinle, 2012; Neumann et al., 2011).

Interoception.

Finally, empathy has recently been shown to be related to interoception (Fukushima,

Terasawa, & Umeda, 2011) which is defined as the ability to detect and perceive changes in

internal bodily state and organ function (Garfinkel et al., 2016). Fukushima et al. (2011)

reported that people who performed better in detecting their own heartbeat in a behavioral

task had higher self-reported empathy. However, alternately, Garfinkel et al. (2016) found no

association between empathy and heartbeat detection accuracy, although they did find that

those who accurately predicted how well they would perform on the heartbeat detection task

also displayed higher empathy. Thus, the results that are reported to date are somewhat

conflicting.

Further, no prior studies have examined the role played by self-reported bodily

awareness (i.e., interoceptive sensibility) in relation to self-reported empathy levels.

Interoceptive sensibility (e.g. awareness of bodily sensations) is known to be poorly

correlated with measures of interoceptive accuracy (e.g., heartbeat detection task) (Garfinkel

et al., 2016), thus, the results of the above two studies cannot be used to make inferences

about the likely relationship between bodily awareness and empathy. Furthermore, it is

unclear if empathy is associated with the perception of all bodily sensations or just autonomic


arousal symptoms, and such a premise has not been examined. Nonetheless, physiological

responsiveness via the mirror neuron system is known to be important in the initial stages of

empathic processing (Arizmendi, 2011; Decety & Lamm, 2006), thus, the capacity to identify

one’s bodily sensations and emotional state are likely to be relevant to empathy.

Summary and hypotheses

In summary, low empathy levels have previously been explored in regards to

demographics (i.e., male gender, older age, ASD diagnosis), personality constructs (i.e.,

Machiavellianism, narcissism, autistic traits), and certain states (e.g., burnout, depression,

anxiety, stress, low interoceptive sensitivity), and the reported associations are detailed in

Figure 1.

Figure 1. Summary of the model of empathy to be tested as informed by theory and empirical

study results

Nonetheless, few prior studies have concurrently examined multiple predictors of

empathy in healthy adults or psychology students. Therefore, it is not clear which factors will

most strongly predict empathy levels, and whether they will differentially predict cognitive

and affective empathy. Thus, in this study we examined a broad range of demographic, trait,

state, and interoceptive measures as predictors of global, affective, and cognitive empathy,

Predictors: Demographics: Male gender ASD diagnosis Traits: High grandiose narcissism High Machiavellianism High vulnerable narcissism States: High burnout High affective distress Low interoception

Trait expression States – affective symptoms & ANS-R as potential mediators

Lower empathy

levels


using the Empathy Quotient (EQ), and after controlling for AQ score and demographics such

as age and gender. Consistent with the prior relevant literature, it was expected that:

(i) Demographics such as male gender will predict lower affective empathy;

(ii) Personality constructs such as narcissism (grandiose and vulnerable) will predict

lower affective empathy, Machiavellianism will predict low global, affective, and

cognitive empathy, and high AQ score will predict low global, affective, and

cognitive empathy levels when controlling for age and gender;

(iii) States such as burnout and its components (i.e., emotional exhaustion, cynicism,

low professional efficacy) will predict lower affective empathy, affective distress

(i.e., depression, anxiety, and stress) will predict lower global, affective, and

cognitive empathy, and high interoceptive sensibility will predict higher global

and affective empathy, after controlling for age, gender, and AQ score;

(iv) Affective symptoms (i.e. stress, anxiety, depression) and ANS-reactivity will

mediate between the various traits to worsen trait expression and thereby

contribute to lower empathy levels, consistent with the assertion that traits may

indirectly impact on an outcome (e.g. empathy) via current demands which may

include affective symptoms and autonomic arousal.

Method

Participants

All aspects of this study were approved by the Australian National University (ANU)

Human Research Ethics Committee (Protocol 2015/528). ANU psychology undergraduate

students were recruited via the psychology research participation platform and student social

media pages associated with the ANU Research School of Psychology, from April to October

2016. They were eligible to participate if they were aged at least 18-years and studied

psychology at ANU. In total, 451 people clicked on the URL embedded in the online study


advertisement, of whom 401 filled in the questionnaire (response rate=88.9%), although 18

did not fully complete the questionnaire. Two people who reported having a diagnosis of

ASD, and one case who identified their gender as ‘other’ were deleted, leaving 380

participants. Demographic characteristics of the sample are provided in Table 1.

Materials and Procedure

Participants were asked about demographics including their age, gender, mental

health history (including a diagnosis of Autism Spectrum Disorder [ASD]), and study in

psychology, and then they completed the questionnaire in the same order as is specified

below. Participants had up to 1-week to complete the questionnaire and the median time to

complete it was 34 minutes.

Empathy was assessed using the Empathy Quotient (EQ, 40-item; Baron-Cohen &

Wheelwright, 2004). Participants were asked to rate each item (e.g., “I really enjoy caring for

other people”) using 4-point Likert type scales ranging from ‘strongly agree’ to ‘strongly

disagree’ with higher scores indicating greater empathy. Factor analysis has identified that

the EQ has a three-factor structure including cognitive empathy (11-item), emotional

reactivity (referred to as affective empathy; 11-item), and social skills (6-item; Lawrence,

Shaw, Baker, Baron-Cohen, & David, 2004). In this study, only total, cognitive, and affective

EQ scores were used in the planned study analyses. Total EQ score has strong test-retest

reliability over 10-12 months (r=.84, p<.001) and moderate convergent validity with the

Interpersonal Reactivity Index (r=.49) (Lawrence et al., 2004). In this study, strong internal

consistencies were shown for total (Cronbach’s α=.89), affective (α=.81), and cognitive

empathy scores (α=.88).

Grandiose narcissistic traits were assessed using the Narcissistic Personality

Inventory (NPI-13; 13-item) (Gentile et al., 2013), an abridged version of the 40-item NPI.

The NPI-13 has three subscales including leadership/authority, grandiose exhibitionism, and


entitlement/exploitativeness (Gentile et al., 2013). Each NPI-13 item contains two paired

statements – one representing a narcissistic response and the other a less narcissistic response

(e.g., “I find it easy to manipulate people” [narcissistic]; “I don’t like it when I find myself

manipulating people”). Participants were asked to identify the statement they most strongly

agreed with and the number of narcissistic responses they endorsed was calculated. The NPI-

13 is reported to have strong convergent validity with the 40-item NPI (r=.88; p<.001) and

high internal consistency for the total score (α=.82), but somewhat lower values for the

subscales: leadership (α=.55-.72), grandiose exhibitionism (α=.52-.68), and entitlement/

exploitativeness (α=.41-.62) (Gentile et al., 2013). In this study, internal consistencies were

similar for the total score (α=.71), leadership (α=.66), grandiose exhibitionism (α=.65), and

entitlement/exploitativeness (α=.44).

Vulnerable hypersensitive narcissistic traits were assessed using the HyperSensitive

Narcissism Scale (HSNS, 10-item) (Hendin & Cheek, 1997). Participants were asked to

determine how characteristic each statement was of themselves (e.g., “My feelings are easily

hurt by ridicule or the slighting remarks of others”), using 5-point intensity rating scales

ranging from ‘very uncharacteristic or untrue/strongly disagree’ to ‘very characteristic or

true/strongly agree’, with high scores indicating greater vulnerable narcissism. The HSNS has

good convergent validity with the MMPI measures of vulnerable narcissism (r=.61-.63;

p<.01) and acceptable internal consistency with a Cronbach’s α of .62-.76 (Hendin & Cheek,

1997). In this study, the HSNS had acceptable internal consistency with a Cronbach’s α of

.69.

Machiavellian traits were assessed using an abridged version of the Mach-IV, the

Two-Dimensional Mach-IV (TDM-IV; 10-item) (Monaghan et al., 2016), which was derived

via item and factor analysis of the original scale (Christie & Geis, 1970). The TDM-IV has

two subscales: Tactics (4-item) and Views (6-item) (Monaghan et al., 2016). Participants


were asked to indicate the extent to which they agreed with each statement (e.g., “It is hard to

get ahead without cutting corners here and there”), using 7-point Likert-type scales ranging

from “strongly disagree” to “strongly agree”, with high scores indicating greater

Machiavellianism. The scale is reported to have strong convergent validity with the original

40-item Mach-IV (r=.90; p<.001) and acceptable internal consistency (α=.66) (Monaghan et

al., 2016). In this study, the tactics (α=.72) and views (α=.74) subscales showed adequate

internal consistency.

Autistic traits were assessed using an abridged version of the Autism Spectrum

Quotient (AQ-Short; 28-item) (Hoekstra et al., 2011). The AQ-Short was derived via factor

analysis of the original 50-item AQ (Baron-Cohen, Wheelwright, Skinner, Martin, &

Clubley, 2001). The AQ-Short has a 4-factor structure including social skills, routine,

attention switching, and numbers/patterns (Hoekstra et al., 2011). Participants were asked to

rate the items (e.g., “New situations make me anxious”) using 4-point Likert type scales

ranging from ‘definitely agree’ to ‘definitely disagree’, with high scores indicating greater

autistic traits. The AQ-Short is reported to have strong convergent validity with the original

AQ (r=.93-.95; p<.001) and adequate to high internal consistency (α=.77-.86) (Hoekstra et

al., 2011). In this study, AQ-short score showed adequate internal consistency (α=.73).

Burnout was assessed using the Maslach Burnout Inventory (MBI, General Form, 16-

item) (Maslach, Jackson, Leiter, Schaufeli, & Schwab, 1996) across three domains:

professional efficacy (6-item), exhaustion (5-item), and cynicism (5-item). Participants were

asked to indicate how frequently they had experienced each aspect of work or study (e.g., ‘In

my opinion, I feel I am good at my job’ [professional efficacy]; ‘I feel emotionally drained

from my work’ [emotional exhaustion]; ‘I just want to do my job and not be bothered’

[cynicism]), using 7-point rating scales ranging from ‘never’ to ‘every day’, with low scores

on professional efficacy and high scores on the other subscales indicating greater burnout.


The MBI is reported to have good test-retest reliability over 1-year (r=.60-.67) and good

internal consistency (α=.73-.91) (Schaufeli & Enzman, 1998). In this study, the subscales

showed high internal consistencies as follows: professional efficacy (α=.85), emotional

exhaustion (α=.90), and cynicism (α=.86).

State depression, anxiety, and stress over the past week were assessed using the

Depression Anxiety Stress Scales (21-item; DASS-21) (Lovibond & Lovibond, 1995). The

DASS-21 contains three subscales: depression, anxiety, and stress (7-items each).

Participants were asked to indicate the frequency with which they had experienced each state

experience (e.g., “I found it difficult to relax”) using 4-point rating scales ranging from ‘did

not apply to me at all/never’ to ‘applied to me very much or most of the time/almost always’,

with high scores indicating worse symptoms. The scale and subscales are reported to have

high internal consistency (Cronbach’s α=.87-.94) and strong convergent validity with the

Beck Depression Inventory (r=.79), Beck Anxiety Inventory (r=.85), and State-Trait Anxiety

Inventory (r=.68) (Antony, Bieling, Cox, Enns, & Swinson, 1998). In this study, DASS-21

subscales showed high internal consistencies as follows: depression (α=.90), anxiety (α=.84),

and stress (α=.86).

DASS-Anxiety score correlates significantly with trait measures of anxiety (e.g. State

Trait Anxiety Inventory; r=.44), suggesting it has some sensitivity in detecting trait distress.

However, its stronger relationships are with state-based depression and anxiety subscales

including the Beck Depression Inventory, r=.77 (Beck Anxiety Inventory, r=.84), thus,

demonstrating strong convergent validity with state anxiety measures (Antony et al., 1998).

Interoceptive sensibility (i.e., internal bodily awareness) was assessed using the Body

Perception Questionnaire (BPQ) (Porges, 1993) that contains five subscales, two of which

were used in this study: Awareness (of all bodily reactions, 45-item) and autonomic nervous

system reactivity (ANS, 27-item). Participants were asked to report the frequency with which


they had experienced physical phenomena such as “swallowing frequently” and “shortness of

breath”, using 5-point scales ranging from ‘never’ to ‘always’, with high scores indicating

greater awareness of the sensations. There is no clear psychometric literature pertaining to the

BPQ (Mehling et al., 2009), but there is strong convergent validity between BPQ scores and

activation in certain brain regions (e.g., anterior insula) that are known to process internal

bodily information (Critchley, Wiens, Rotshtein, Öhman, & Dolan, 2004). In this study, the

two BPQ subscales had high internal consistencies: Awareness (α=.97) and ANS (α=.94).

Statistical Analyses

Routine statistical analysis was conducted using SPSS (Version 22). Hierarchical

multiple linear regression analyses explored a broad range of personality constructs and state

factors to determine if they predicted total, affective, and cognitive empathy scores, after

controlling for relevant demographics (age and gender) at step 1 of the analyses. Personality

constructs (AQ-Short, HSNS, and TDM-IV and NPI-13 subscales) were entered at step 2,

state factors (MBI and DASS-21 subscales) were entered at step 3, and interoceptive

sensibility (BPQ subscales) was entered at step 4 of the analyses.

Mediational analyses used Sobel test statistics and they were bootstrapped using 1,000

resamples to estimate the direct relationships between each independent variable (IV) and

dependent variable (DV), indirect effects occurring via the potential mediator, and whether

subtracting the indirect effects significantly reduced the variance explained by the direct

effects, using Sobel test statistics. State variables (i.e. affective symptoms and ANS-

reactivity) that predicted significant variance in empathy scores were explored as potential

mediators between the trait variables and empathy levels.

Results

Means and standard deviations of the key study variables are presented in Table 2 and

a correlational matrix is presented in Table 3. Participants’ years of study in psychology was


omitted from the analyses as it was uncorrelated with empathy scores, although more years of

study was correlated to older age and lower anxiety levels. Hierarchical multiple regression

analyses examined the predictors of empathy scores, see Table 4. Variables collectively

predicted 40.4% (F=14.465; p<.001) of the variance in global empathy, and low total EQ

score was predicted by male gender and high scores on the AQ-Short, TDM-IV-tactics and -

views, and BPQ-ANS. Variables also predicted 40% (F=14.465; p<.001) of the variance in

affective empathy, and low affective empathy was predicted by male gender, older age, high

scores on the AQ-Short, TDM-IV-tactics and –views and BPQ-ANS, and low anxiety levels.

Variables collectively predicted 32.9% (F=14.285; p<.001) of the variance in cognitive

empathy, and low cognitive empathy was predicted by high scores on the AQ-Short and

BPQ-ANS and low anxiety levels.

Mediational Analyses

Of the hypothesized state variables (i.e. stress, anxiety, depression, ANS-reactivity),

only BPQ-ANS predicted significant variance in all empathy levels, and so only it was

explored as a potential mediator between the personality construct to empathy relationships.

In separate analyses: 1) total EQ score was the DV and AQ-Short and TDM-IV-views were

IVs; 2) affective EQ score was the DV and AQ-Short and TDM-IV-views were IVs; and, 3)

cognitive EQ score was the DV and AQ-Short was the IV. No mediation analyses were

conducted on TDM-IV-tactics, NPI-13 subscales, and HSNS as they were unrelated to BPQ-

ANS. All analyses were bootstrapped using 1,000 resamples, see Table 5.

For total EQ score, significant indirect effects were detected for TDM-IV-views when

BPQ-ANS was entered as the mediator. Sobel test results indicated that the indirect effects

via BPQ-ANS significantly reduced the relationship between TDM-IV-views and total EQ

score. No significant indirect effects were found for affective and cognitive EQ score when

BPQ-ANS was entered as the mediator.


Discussion

Few prior studies have systematically examined the predictors of empathy in healthy

adults, including psychology students. In addition, the studies examining medical student

empathy have tended to assess only a few potential predictors that were not selected on the

basis of theory or they used narrow definitions of the constructs (e.g., cognitive empathy

only). Furthermore, the other studies examining empathy have tended to come from different

disciplines such as personality psychology and physiology and they used different

measurement approaches. Thus, it is unclear whether empathy is best predicted by personality

constructs or state factors, and if the predictors are the same or different for cognitive and

affective empathy. Thus, in this study, we examined a broad range of demographic,

personality construct, state, and interoception measures as predictors of global, affective, and

cognitive empathy, using the Empathy Quotient (EQ), and after controlling for AQ-Short

score and demographics such as age and gender.

Demographics, personality constructs, state factors, and interoception all predicted

significant variance in global empathy (40%), affective empathy (40%), and cognitive

empathy (33%). Of the demographics, male gender predicted low affective and global

empathy in all the analyses but it did not predict cognitive empathy, consistent with findings

in the prior relevant literature (Gleichgerrcht & Decety, 2013). Additionally, older age

predicted low affective empathy in the final model but not at step 1 when it was entered alone

with gender. Age-related declines in empathy have been observed in the small literature

(Beadle, Brown, Keady, Tranel, & Paradiso, 2012; O'Brien et al., 2012), but they tend not to

be detected in longitudinal studies suggesting they are simply cohort-related effects (Grühn et

al., 2008).

Personality constructs predicted the most variance in student empathy levels. The

AQ-Short was the strongest individual predictor of low global, affective, and cognitive


empathy, especially cognitive empathy, consistent with findings in the ASD literature

(Baron-Cohen & Wheelwright, 2004; Dziobek et al., 2008). In addition, global and affective

empathy were predicted by Machiavellian-views and –tactics, but not grandiose narcissism

and hypersensitive narcissism. Machiavellianism is typically associated with low cognitive

and affective empathy in personality literature (Jonason & Krause, 2013), but in this study, it

was only related to global and affective empathy. Similarly, narcissism is typically linked to

low affective empathy in the literature (Watson & Morris, 1990), but it did not predict low

empathy levels in this study which is likely due to the large proportion of empathy variance

that was predicted by the AQ-Short.

Significant relationships between Machiavellianism and low empathy suggest that

individuals who tend to value other people poorly or in a utilitarian manner (e.g., manipulate

others for advantage) will have lower empathy levels, especially low affective empathy. In

particular, they will tend to believe that it is appropriate to deceive others (i.e., tactics) on the

basis that they are immoral, untrustworthy, unintelligent, and lazy (i.e., views) (Monaghan et

al., 2016), but it is unclear which aspect(s) of the personality constructs (e.g., suppressed

emotional reactivity or appraisal biases) (McIlwain, 2013) underpins the impairment in

empathy. In the personality literature, suppressed emotional reactivity or appraisal biases

have been proposed to explain the low empathy in Machiavellian individuals (McIlwain,

2013), but alternately, it may be explained by motivational influences on empathy (e.g. low

empathy in the case that empathizing is irrelevant to one’s immediate aims) (Campbell-Yeo,

Latimer, & Johnston, 2008; Coutinho et al., 2014; Decety & Lamm, 2006).

State factors such as awareness of autonomic nervous system-reactivity (ANS-R)

predicted significant variance in global, affective, and cognitive empathy, whereas low

anxiety levels predicted low cognitive and affective empathy. However, stress, depression,

and participants’ awareness of all bodily sensations did not. Interoception has rarely been


examined in relation to empathy or the functionally-related mirror-neuron system. Several

recent studies have reported a significant association between empathy and interoception

measures (Fukushima et al., 2011; Garfinkel et al., 2016), although the results appear to be

inconsistent. Nonetheless, long-standing theories of emotion suggest that variability in the

perception of bodily sensation is central to our understanding of emotional experience

(Critchley et al., 2004; Garfinkel et al., 2016). Consistent with this assertion, high ANS-R has

previously been shown to be related to emotional processing deficits in people with ASD and

in the general population, and also in people with anxiety symptoms and disorders (Garfinkel

et al., 2016).

Thus, there is some evidence suggesting that if a person has difficulty sensing their

bodily sensations the capacity to respond to others using the mirror neuron network will be

compromised (Neumann et al., 2011). Furthermore, our study result that high ANS-R

predicted low empathy levels may indicate that a strong internal focus on autonomic arousal

sensations can reduce a person’s capacity to process external-other-person information,

including another’s distress. That is, the students who focused a lot on their own internal state

may have been less able to engage with the external environment, including interpersonal

stimuli, and this may have compromised their ability to be empathic, although such a premise

has not yet been examined. Nonetheless, taken together with the trait results, they suggest

that low empathy will be present in the people who experience difficulties in engaging with

the interpersonal context, either due to the presence of certain personality constructs and/or

autonomic arousal symptoms.

However, the small positive association between anxiety and empathy levels was

unexpected, but it is noteworthy that low anxiety was also correlated with older age and more

years of psychology study. Thus, it is possible that this particular result best captured the

expected decline in empathy levels which is documented in medical students (Hojat et al.,


2009; Neumann et al., 2011). That is, low anxiety levels were most evident in older females

who were at the end of their psychology studies and as a result of their years of study they

may have experienced lower empathy levels. However, it is noteworthy that cynicism (a core

feature of Machiavellian views) is proposed to be the mechanism by which empathy declines

in medical trainees as the demands of the clinical environment contribute to emotional

blunting and the need for additional coping strategies (Colliver et al., 2010; Hojat et al.,

2009). Thus, the result may reflect that burnout occurs in later year students as a result of

experiencing chronic high stress over which they have little control (Handford et al., 2013;

Neumann et al., 2011), and this may tend to adversely impact on their affective empathy.

However, it is noteworthy that other affective symptoms (i.e., depression and stress)

did not predict student empathy levels, and this may be partly due to the high comorbidity

between affective symptoms and ANS-reactivity, which indexed autonomic arousal

symptoms (Kreibig, 2010). That is, the result may reflect that: (a) ANS reactivity was a better

predictor than affective symptoms of the overlapping variance they predicted in empathy

levels; and/or (b) the people with high autonomic arousal may have failed to detect the

additional distress (of others) that could have cued an appropriate empathic response. This

latter interpretation is consistent with the Insular Model of Anxiety (Paulus & Stein, 2006,

2010) which suggests that high background noise in the neuro-circuitry underpinning

interoception may impair a person’s sensitivity to changes in their bodily state and the

incorporation of this information into emotional experience (Terasawa, Fukushima, &

Umeda, 2013) such as is thought to be the case in empathic emotion (Bird & Viding, 2014).

Finally, the mediational analyses explored whether affective symptoms (i.e. stress,

anxiety, depression) and/or high ANS-reactivity explained the indirect relationships between

worsened trait expression to lower empathy levels. High ANS-reactivity partly mediated

between high trait levels of Machiavellian-views to low global empathy. However, affective


symptoms did not mediate the relationships and indirect effects were not found for affective

and cognitive empathy.

No prior studies have examined the propensity of autonomic arousal or affective

symptoms to worsen trait expression to thereby impair empathy levels. Nonetheless, people

high on Machiavellianism are reported to show low emotional reactivity to other people’s

emotions (McIlwain, 2013). In addition, the emotional processing deficits in people with and

without ASD are thought to be at least partly due to greater attention given to autonomic

arousal sensations (Garfinkel et al., 2016). Thus, taken together, the results suggest that if a

person with these trait/s is highly aroused or sensitized to their autonomic arousal sensations,

they may be less empathic than if they were not affected in this way.

Finally, the mediational results may have implications for the training of psychology

students, and perhaps even medical students. In particular, the results suggest that asking

students to focus on their autonomic arousal sensations may assist them in recognizing that

their feelings of stress/tension can adversely impact on their ability to be empathic, either by

directly focusing on the symptoms or by worsening the effects of certain trait behaviour.

Psychotherapeutic interventions should also be investigated for their utility in improving

interoceptive sensibility in people with low empathy levels and to establish whether this

activates the mirror neuron system. Interestingly, mindfulness-based therapies have been

reported to be effective in part because of the emphasis on bodily sensations (e.g.

mindfulness meditation) in a manner that promotes unbiased attention, thus, potentially

avoiding hypervigilance and catastrophic interpretations of the reactivity (Mehling, 2016).

However, the study results should be interpreted with caution given several study

limitations. First, the sample was mostly comprised of young female full-time first- and

second-year psychology students and only a minority (n=11) of them were postgraduate

clinical trainees, thus, limiting the generalizability of the results to psychology clinicians.


Nonetheless, the sample was large and the gender distribution was consistent with the

observed tendency of females to study psychology (Gosling, Vazire, Srivastava, & John,

2004). Further, given the limited availability of postgraduate clinical psychology trainees in

Australia it was necessary to recruit undergraduate psychology students to meet the

requirement of a large sample. However, this sample is analogous in terms of years of study

to the early career students used in medical trainee studies (Neumann et al., 2011; Pohl,

Hojat, & Arnold, 2011).

Second, several trait subscales showed poor internal consistencies including the

entitlement/exploitative subscale of the NPI-13, suggesting the results involving this variable

should be interpreted with caution. Third, due to time constraints, several abridged scales

(e.g., autistic traits and grandiose narcissism) were used instead of the full-length scales, and

despite having strong psychometrics, this may have reduced the participants’ score

variability. Fourth, the results were only cross-sectional in nature therefore precluding any

causal inferences being drawn about the likely relationships between the predictor variables,

mediators and empathy levels. Finally, additional research is required to further scrutinize the

likely indirect relationships between autonomic arousal, affective symptoms, personality

constructs, and empathy, and also other factors that are known to be related to empathy (e.g.

alexithymia, that is characterised by externally-oriented thinking and difficulties in detecting

and describing feelings) (Pollatos et al., 2011), especially since interoceptive deficits have

been shown to occur in people with alexithymia (Herbert, Herbert, & Pollatos, 2011).

In conclusion, student empathy levels were predicted by a combination of

demographics (i.e. male gender), personality constructs (i.e. Autistic, Machiavellianism), and

state factors (i.e. high ANS-reactivity and low anxiety) in a large sample of psychology

students, thus, suggesting that empathy is determined by a combination of factors. In regards

to the traits, people who tended to value other individuals as inferior to themselves or in a


utilitarian manner (e.g., manipulate others for advantage) had low empathic abilities,

especially low affective empathy. In contrast, autistic traits were associated with large deficits

in global, affective, and cognitive empathy, especially cognitive empathy. In addition, high

ANS-reactivity predicted low global, affective, and cognitive empathy levels, suggesting that

a strong internal focus on bodily sensations may reduce a person’s capacity to process

external other-person information.

Mediational analyses indicated that high ANS-reactivity indirectly explained low

empathy levels via a worsening of trait expression, including Machiavellian-views and

hypersensitive narcissism. These results suggest that if a person with certain personality

trait/s experiences high autonomic arousal, their empathy may be impaired to a greater extent

than if they were not affected in this way. Finally, the results may have implications for the

training of psychology clinicians. In particular, a focus on autonomic arousal sensations may

help trainees to recognize that their symptoms can adversely impact on their ability to

empathize with others, either directly by focusing on the symptoms or by worsening the

effects of certain trait behaviour.


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Table 1

Sample Characteristics of the Psychology Student Sample (N=380).

Mean (SD) Range

Age 20.21 (4.77) 18-61 Number %

Gender (Female) 259 68.2 Gender (Male) 121 31.8 Autism Spectrum Disorder diagnosis 0* 0 No Autism Spectrum Disorder diagnosis 380* 100 History of mental health diagnosis 103 27.1

Currently seeking mental health treatment 38 10 No history of mental health diagnosis 277 72.9 Study program

Diploma 1 0.3 Undergraduate student 368 96.8 Postgraduate clinical student 11 2.9 Full time 357 93.9 Part time 23 6.1

Year of study (in current course)

First 287 75.5 Second 77 20.3 Third 12 3.2 Fourth or above 4 1.1

*Please note two cases reported an Autism Spectrum Disorder diagnosis in the overall sample population, these were omitted from analyses.


Table 2

Means and Standard Deviations (SD) of Empathy and Personality Construct and State Predictors of Total, Affective, and Cognitive Empathy.

Mean (SD) Range

EQ-Total 44.98 (12.29) 16-74 EQ-Affective 13.96 (5.13) 2-24 EQ-Cognitive 16.09 (5.41) 1-26 AQ-Short 64.05 (8.00) 41-96 TDM-Tactics 13.09 (4.08) 4-25 TDM-Views 20.77 (5.85) 7-40 NPI-Leadership 1.16 (1.26) 0-4 NPI-Grandiosity 1.58 (1.43) 0-5 NPI-Entitlement 0.91 (1.02) 0-4 HSNS 32.06 (5.35) 17-51 MBI-Professional Efficacy 25.49 (6.80) 0-36 MBI-Emotional Exhaustion 18.25 (6.80) 0-30 MBI-Cynicism 14.92 (7.63) 0-30 DASS-21 Depression 6.45 (4.74) 0-21 DASS-21 Anxiety 5.68 (4.37) 0-21 DASS-21 Stress 7.88 (4.52) 0-21 BPQ-Awareness 102.51 (34.65) 45-225 BPQ-ANS Reactivity 49.96 (17.57) 27-135

Note: EQ – Empathy Quotient; AQ-Short – Autism Spectrum Quotient-Short; TDM – Two-Dimensional Mach-IV; NPI – Narcissistic Personality Inventory-13;

HSNS – HyperSensitive Narcissism Scale; MBI – Maslach Burnout Inventory; DASS-21 – Depression Anxiety Stress Scales-21; BPQ – Body Perception Questionnaire.


Table 3

Correlational Matrix of Empathy, and Personality Construct and State Predictors of Total, Affective, and Cognitive Empathy. 1 2 3 4 5 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

r r r r r r r r r r r r r r r r r r r r

1. EQ Total - .89*** .82*** -.08 .23*** -.51*** -.05 -.03 -.24*** -.16** -.39*** -.34*** .21*** -.15** -.30*** -.23*** -.15** -.14** -.18*** -.23***

2. EQ Affective

- .63*** .11* .31*** -.39*** -.13* -.10 -.30*** -.22*** -.44*** -.26*** .18*** -.10 -.28*** -.15** -.04 -.06 -.12* -.11*

3. EQ Cognitive

- -.004 .08 -.50*** .12* .05 -.04 -.01 -.11* -.23*** .23*** -.08 -.16** -.16** -.08 -.08 -.11* -.16**

4. Age - -.13* -.07 -.10 .07 .06 .12* -.06 .05 .06 .02 .05 -.10 -.17** -.05 -.09 -.08

5. Gender - -.06 -.15** -.10* -.13* -.08 -.20*** -.03 .01 .01 -.05 -.01 .05 .03 .06 .12*

7. AQ-Short - -.06 -.14** .18*** -.03 .32*** .45*** -.27*** .24*** .2/*** .31*** .37*** .35*** .30*** .30***

8. NPI-13 Leadership

- .23*** .42*** .21*** .18*** .05 .20*** .05 .09 -.04 -.04 .06 -.01 -.01

9. NPI-13 Grandiosity

- .17** .18*** .04 .01 .10 -.11* .01 -.11* -.16** -.11* -.12* -.12*

10. NPI-13 Entitlement

- .25*** .36*** .27*** -.05 .13* .21*** .15** .08 .19*** .07 .01

11. TDM-IV Tactics

- .19*** .09 -.03 .09 .20*** .02 -.02 -.02 -.07 -.10

12. TDV-IV Views

- .41*** -.17** .29*** .36*** .33*** .29*** .30*** .22*** .20***

13. HSNS - -.15** .35*** .38*** .44*** .39*** .44*** .25**** .32***

14. MBI Efficacy

- -.03 -.09*** -.25*** -.14** -.13* -.14** -.12*

15. MBI Exhaustion

- .59*** .49*** .40*** .45*** .28*** .33***

16. MBI Cynicism

- .50*** .23*** .31*** .25*** .28***

17. DASS-Depression

- .59*** .64*** .40*** .43***

18. DASS-Anxiety

- .71*** .53*** .63***

19. DASS-Stress

- .40*** .48***

20. BPQ Awareness

- .73***


21. BPQ ANS

-

Note: * p<.05; ** p<.01; *** p<.001

EQ – Empathy Quotient; AQ-Short – Autism Spectrum Quotient-Short; TDM – Two-Dimensional Mach-IV; NPI – Narcissistic Personality Inventory-13; HSNS

– HyperSensitive Narcissism Scale; MBI – Maslach Burnout Inventory; DASS – Depression Anxiety Stress Scales-21; BPQ – Body Perception Questionnaire.


Table 4

Hierarchical Multiple Linear Regression Analyses for Associations between Total, Affective, and Cognitive Empathy scales and Demographic,

Personality Construct, and State Variables, Including Continuous Measure of ASD Traits.

Total EQ Affective EQ Cognitive EQ β P ΔR2 p β p ΔR2 p β p ΔR2 p

Step 1 .053 <.001** .102 <.001** .006 .295

Age -.046 .360 -.072 .143 .007 .895 Gender .220 .<001** .301 <.001** .081 .119 Step 2 .312 <.001** .254 <.001** .265 <.001**

Step 3 .022 .045* .034 .003* .027 .034*

Step 4 .023 .001** .012 .029* .012 .049*

Age -.074 .089 -.093 .035* -.002 .968 Gender .145 .001* .196 <.001** .069 .139 AQ-Short -.431 <.001** -.321 <.001** -.520 <.001** TDM-IV Tactics -.091 .040* -.113 .011* -.045 .348 Views -.166 .001* -.261 <.001** .057 .295 NPI-13 Leadership -.010 .843 -.040 .412 .057 .282 Grandiosity -.028 .517 -.040 .366 -.014 .771 Entitlement -.056 .259 -.078 .116 .029 .585 HSNS -.038 .470 .005 .928 -.043 .447 MBI Efficacy .039 .384 .050 .266 .084 .084 Exhaustion .062 .263 .077 .170 .022 .710 Cynicism -.068 .234 -.080 .168 -.006 .925 DASS-21 Depression -.096 .121 -.073 .245 -.096 .154 Anxiety .131 .059 .164 .019* .197 .009*


Stress .124 .062 .124 .064 .064 .367 BPQ Awareness .077 .201 .022 .712 .075 .251 ANS -.242 <.001** -.158 .019* -.176 .015*

Note: ASD – Autism Spectrum Disorders; TDM-IV – Two Dimensional Mach-IV; NPI-13 – Narcissistic Personality Inventory-13; HSNS – HyperSensitive

Narcissism Scale; MBI – Maslach Burnout Inventory; DASS-21 – Depression Anxiety Stress Scales-21; BPQ – Body Perception Questionnaire; ANS – Autonomic Nervous

System Reactivity. Variables added to the model at step 2 – AQ-Short, TDM-IV Tactics and Views, NPI-13 Leadership/Authoritativeness (Leadership), Grandiosity, and

Entitlement/Exploitativeness (Entitlement), HSNS. Variables added to the model at step 3 – MBI Professional Efficacy (Efficacy), Emotional Exhaustion (Exhaustion), and

Cynicism, and DASS-21 Depression, Anxiety, and Stress. Variables added to the model at step 4 – BPQ Awareness and ANS.


Table 5

Sobel Mediation Analyses Exploring Indirect Effects of Interoceptive Sensibility on the Association between Personality Constructs and

Empathy

DV – Total EQ

Direct effect on DV Direct effect on ANS Indirect effect on DV Sobel 95% CI for mediation effect Predictor β SE β p β SE β p β SE β p Value p Mean Lower Upper

BPQ-ANS -.227 .035 <.001** AQ-Short -.507 .044 <.001** .300 .050 <.001** -.082 .046 .07 -.025 .088 -.024 -.056 .005 TDM-Views -.378 .046 <.001** .200 .050 .001* -.154 .047 .001* -.031 .013* -.031 -.061 -.009 DV – Affective EQ


BPQ-ANS -.111 .015 .030* AQ-Short -.365 .048 <.001** .300 .050 <.001** -.001 .050 .983 <.001 .984 <.001 -.031 .035 DV – Cognitive EQ


BPQ-ANS -.161 .016 .002* AQ-Short -.487 .045 <.001** .300 .050 <.001** -.008 .047 .860 -.003 .862 -.003 -.033 .027 TDM-Views -.066 .050 .194 .199 .050 <.001** -.143 .051 .006* -.029 .025* -.028 -.058 -.006

Note: BPQ-ANS – Body Perception Questionnaire Autonomic Nervous System Reactivity; AQ-Short – Autism Spectrum Quotient-Short; TDM – Two Dimensional

Mach-IV; MBI – Maslach Burnout Inventory.


Appendix A: Health Psychology (Journal)

Health Psychology is a journal affiliated with the American Psychological

Association to “advance the science and practice of evidence-based health psychology and

behavioral medicine”.1 Of relevance to the current study, the journal publishes research on

topics including professional issues in health psychology.

The normal limit for article submissions is 30 pages. However, authors are welcome

to request in advance of submission for additional length to be allowed where studies are

unusual or complex. For longer submissions, authors are also encouraged to submit excess

material rather than within the core manuscript.

The journal requests standard APA formatting for submissions. Titles are requested to

be no longer than 12 words and accompanied by an abstract not exceeding 250 words.

Introduction is requested to be of around 3-4 pages in length and appropriately referenced.

The journal requests the name of overseeing institutions and review board(s) to be reported

within the Methods section. Statistical tests should be accompanied by effect sizes and

confidence intervals where possible. First-person and gender-neutral language is requested.

Authors are also asked to identify the novel contribution of their work within the manuscript

unless focusing on replication or extension, in which case the rationale for repetition should

be clearly stated.

Finally, the journal stipulates that they expect de-identified data upon which analyses

are based should be made available on request to other competent professionals seeking to re-

analyse the data to verify findings. This stipulation is made to comply with published APA

Ethical Principles.

1 American Psychological Association, Health Psychology. http://www.apa.org/pubs/journals/hea/

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