emotion recognition and emotional resonance: exploring the relationship between facial expression...
TRANSCRIPT
N0256275
Phil Banyard
April 2012
Emotion Recognition and Emotional Resonance: Exploring the Relationship between Facial Expression Recognition and Empathy
Rebecca Noskeau
BSc Psychology with Criminology
Psychology DivisionSchool of Social Sciences
Nottingham Trent University
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Emotion Recognition and Emotional Resonance: Exploring the
Relationship between Facial Expression Recognition and Empathy
Abstract
Current research investigating the relationship between empathy and facial expression
recognition suggests that the two are inter-related. The purpose of this study was to explore
this relationship by comparing participants’ scores from the EQ-Short; their levels of accuracy
when identifying facial expressions; and their levels of emotional resonance with each
expression. A one-way ANOVA highlighted that females scored significantly higher than
males on the EQ-Short: F (1,140) = 4.64, p = 0.033. A bi-variate correlation revealed that scores
on the EQ-Short correlated significantly with rates of accuracy when identifying facial
expressions: r = .245, n =142, p = 0.003. The EQ-Short explained 6% of the variance found in
accuracy scores, (R2 = .0600, p = 0.003). A paired-samples t-test revealed that the three female
facial stimuli produced the highest accuracy rates: t (141) = 5.595, p = <0.001, and resonance
scores: t (141) = 3.834, p = <0.001. Happiness, surprise, disgust and sadness were identified
significantly more accurately than fear and anger: t (141) = 11.52, p = <0.001. A One-Way
ANOVA revealed females recognised anger significantly more accurately than males: F
(1,140) = 3.92, p = 0.050). Paired-samples t-tests revealed that happiness was recognised t (141)
= 5.22, p = <0.001, and resonated with t (141) = 7.31, p = <0.001, significantly more than the
five other emotions. There were significant differences in both accuracy and resonance scores
in response to the 6 FEED subjects: t (141) = 14.779, p = <0.001. These findings lend weight to
the growing body of evidence which suggests that empathy and facial expression recognition
are intrinsically related to one-another. This has real-world implications for the treatment of
disorders which are characterised by atypical functioning in these areas.
Key Words: Emotion; Facial Expressions; Empathy; Emotional Resonance; Emotion
Recognition.
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Introduction
Due to the highly subjective and multi-faceted nature of emotion, researchers have struggled
to agree upon a clear definition of what emotions are, and indeed, what they are not (Scherer,
2005). However, what has been defined is that emotion is a complex psycho-physiological
phenomenon, which originates from an interaction between bio-chemical and environmental
influences (Meyer, 2004). Emotion is experienced as a mixture of physiological activation,
conscious experience and expressive behaviours (Meyer, 2004). Researchers believe that there
are at least six distinct basic emotional states: happiness, sadness, anger, disgust, surprise and
fear (Ekman, 1992, 1999; Ekman & Friesen, 1971). These states have been labelled the six basic
emotions, and are thought to blend together in order to create more complex emotional states
(Ekman, 1992, 1999; Ekman & Friesen, 1971; Scherer, 2005). Research has shown that these
emotions have a distinct pattern of expression upon the body and brain, both when we
ourselves are experiencing them, and when we see others doing so (App et al., 2011;
Chakrabarti et al., 2006; Ekman, 1992, 1999; Ekman & Friesen, 1971; Vignemont & Singer, 2006).
There is an ongoing debate as to whether emotions and facial expressions are innate, or are a
bi-product of socialisation (Barrett, 2011; Ekman, 1999; Matsumoto & Hwang, 2012).
Universalists believe that emotions and expressions are innate, adaptive and functional (Darwin, 1872/2009; Ekman, 1992, 1999; Ekman & Friesen, 1971; Shariff & Tracy, 2011).
However, cultural relativists and social constructivists emphasise a dominant role of
socialisation in the formation of emotional constructs and behaviours (Averill, 1980; Barrett,
2011; Mead, 1975; Russell, 1994, 1995). They believe that emotions and facial expressions are
predominantly culturally informed, and then later internalised and reproduced (Averill, 1980;
Barrett, 2011; Mead, 1975; Russell, 1994, 1995). In addition, they argue that by reducing emotion
to a few parsed archetypal concepts - such as in the case of the six basic emotions, universal
emotion researchers are reducing their potential understanding of these phenomena (Averill,
1980; Barrett, 2011; Ekman, 1992, 1999; Ekman & Friesen, 1971; Mead, 1975; Russell, 1994, 1995).
The relativists and constructivists believe that this is epitomised in emotion research when
pre-formed emotion labels are used, as they believe that this limits participants’ responses by
forcing them to rely on using the pre-formed emotion labels, when describing emotional
phenomena (Averill, 1980, Barrett, 2011; Mead, 1975; Russell, 1994, 1995).
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Nevertheless, despite the prevalence of criticisms against it, there is a huge body of research
that supports a universal theory of emotion, and in particular, the innateness of emotional
facial expressions. For example, researchers have found that members of remote tribes both
display and understand the same basic emotions and facial expressions, as people from mass-
socialised societies (Ekman & Friesen, 1971). Furthermore, it has been reported that
congenitally blind people exhibit the same basic facial expressions as sighted people (Shariff
& Tracy, 2011). In addition, it has been shown that babies are able to discriminate and imitate
facial expressions from as early as 36 hours old (Field et al., 1982). Indeed, a recent study even
claims to have discovered that babies produce basic facial expressions in utero (Reissland et
al., 2011). It is however important to note that this study was conducted using only two
participants and therefore much greater research is necessary before this theory can be
accepted or generalised further. What researchers have managed to establish is that from as
early as one-year old, we are able to use our facial expression recognition abilities to help us
to safely navigate the world around us (Sorce, et al., 1985; Vignemont & Singer, 2006).
The emotions and facial expressions of others are often automatically processed, and though
they remain below the threshold of conscious awareness, have been shown to significantly
affect the functioning of the autonomic nervous system (Côté & Hideg, 2011; Dimberg et al.,
2000; Dimberg et al., 2011). This is supported by the finding that involuntary and voluntary
facial expressions are automatically perceived and reacted to differently - both
psychologically and biologically (Ekman & Davidson, 1993; Shore & Heerey, 2011). The Mirror
Neuron System (MNS) is thought to play a significant role in this automatic processing of
others’ emotions, and in our understanding of their intentions and actions (Gallese et al., 2011;
Iacoboni, 2009; Iacoboni et al, 2005; Menon, 2011; Oberman & Ramachandran, 2007;
Ramachandran, 2000). However, the MNS only accounts in part for this process, as it has been
found that an empathiser’s own emotional state can bias their attentional system, making
people more prone to noticing facial expressions which are congruent with their own present
emotional state, (Becker & Leinenger, 2011). This means that at times we may not even be
aware of others’ emotions and facial expressions, unless they are similar to our own, and
therefore salient to us at any given moment.
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Understanding Empathy
Empathy has been identified as being the result of a combination of emotion recognition - the
ability to accurately identify another person’s emotional state, and emotional resonance - the
ability to feel what another person is feeling (Chakrabarti et al., 2006; Decety & Hodges, 2006;
Lama et al., 2008; Lawrence, et al., 2004; Shamay-Tsoory, 2011; Singer & Lamm, 2009). Empathic
abilities are believed to facilitate social communication and create social cohesion and
research suggests this happens both when we ourselves are being empathic towards others,
and when we perceive others as being empathic towards us (Cohen et al., 2012; Rifkin, 2010;
Verhofstadt et al., 2008; Vignemont & Singer, 2006). Researchers have found that empathy is
highly subjective and dependent upon the context and experiences of both the empathiser and
their target (Foroni & Semin, 2011; Hein & Singer, 2008; Matsumoto, 1991; Vignemont, & Singer,
2006). For example, it has been shown that the relationship dynamics that exists between two
people, including their relational hierarchical status to one-another, can have a profound
influence on the depth and the nature of emotional sharing, mutual-understanding and
personal identification, that thus ensues (Hein & Singer, 2008; Matsumoto, 1991; Vignemont, &
Singer, 2006).
Recent studies exploring empathic capabilities have been able to show that empathy is not a
fixed trait, but is a skill which can evolve over time, and as such, it can be learnt and
enhanced (Aziz-Zadeh et al., 2011; Baron-Cohen, 2011; Bastiaansen et al., 2011; Martin, et al., 2012;
Trepagnier et al., 2011). This is evident in the significant improvements found in the empathic
abilities of autistic children and adults who completed educational programmes designed to
help them to recognise and relate to others’ emotions and expressions more effectively
(Baron-Cohen, 2011; Hopkins, 2007; Hopkins et al., 2011; Trepagnier et al., 2011). As the MNS
plays such a significant role in the automatic processing of others’ emotions, and indeed, in
our understanding of their intentions and actions, it is believed to be an essential component
of empathy (Gallese et al., 2011; Iacoboni, 2009; Iacoboni et al, 2005; Oberman & Ramachandran,
2007; Menon, 2011; Ramachandran, 2000). It is hypothesised that autistic people have a delay in
the development of their MNS, and as a result are believed to suffer from deficits in cognitive
empathy (Bastiaansen et al., 2011; Oberman & Ramachandran, 2007). Until recently this was seen
as a fixed and life-long pattern, however recent research suggests that an Autistic person’s
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MNS catches up to a neuro-typical level of functioning at around 35-40 years-old - at which
point it is seen to go on to surpass it (see Figure 1 below), (Bastiaansen et al., 2011). This
contrasts with the neuro-typical pattern of development, which sees the MNS decline
gradually with age (see Figure 1), (Bastiaansen et al., 2011). Further evidence of the plasticity of
empathy is provided by a study which found that empathy can be enhanced by reading fiction
(Gabriel & Young, 2011). This is believed to occur due to the reader having access to the inner
motives, thoughts and intentions of the characters in the books - rather than only an exterior
view of their actions - thus enabling the reader to resonate more fully with them (Gabriel &
Young, 2011). The cumulative weight of these studies supports the hypothesis that empathy is
a dynamic, ever-evolving skill. This has important implications for further research and
treatments which are aimed at helping people with deficits in empathy. In addition, the last
study in particular has strong real-world applications in the reduction of discrimination,
prejudice and conflict.
Figure 1: The delayed pattern of development, and later
excelling, found in the MNS of people with Autism; as
compared with the gradual pattern of decline found in
neuro-typical development. Adapted by L. D. Cookson,
2012, from “Age-Related Increase in Inferior Frontal Gyrus
Activity and Social Functioning in Autism Spectrum
Disorder,” by J. A. Bastiaansen, M. Thioux, L. Nanetti, C. V.
D. Gaag, C. Ketelaars, R. Minderaa and C. Keysers, 2011,
Biological Psychiatry, 69(9), 832-838. Adapted with
permission.
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In order to understand what empathy is, it is helpful to consider what happens when there are
deficits in empathic abilities. Researchers believe that there are two routes by which empathy
is achieved - via emotional affect (affective empathy), and cognitive rationalisation (cognitive
empathy), (Decety & Hodges, 2006; Shamay-Tsoory, 2011; Shamay-Tsoory et al., 2009; Shamay-
Tsoory et al., 2010). It has been discovered that imbalances in either of these routes can result
in psychiatric and neurological disorders. An example of this (as previously mentioned), is in
the case of autism, where it is believed that there is a deficiency in cognitive empathy; in
contrast, the dark triad of personality - Narcissism, Machiavellianism and Psychopathy – are
all disorders that are believed to be attributable to impairments in affective empathy (Bastiaansen et al., 2011; Blair, 2005; Oberman & Ramachandran, 2007; Wai & Tiliopoulos, 2012).
Deficits in affective empathy have been shown to emerge when there is damage to the pre-
frontal cortex; and pre-frontal cortex injuries have been shown to mimic the deficits in
empathy which are present in psychopathy (Shamay-Tsoory et al., 2010). These findings
complement other research which suggests that people high in affective empathy perceive the
emotions of others more vividly, and of a higher intensity, than those with lower affective
empathy (Dimberg et al., 2011).
Perhaps the most acute disorder in which an imbalance in affective and cognitive empathy
exists is borderline personality disorder (BPD). In BPD emotions, facial expression
recognition and empathy are all heightened, and at times distorted (Donegan et al., 2003; Harari
et al., 2010; Lynch et al., 2006; Wagner & Linehan, 1999). Harari et al., (2010), suggest that there
is a common pattern of increased cognitive empathy and decreased affective empathy in the
general population, but that in BPD this pattern is reversed, meaning that sufferers have an
increased affective empathic response, and thus higher-sensitivity, to the emotions of others,
than is found in the norm. As such, this can cause sufferers to be overwhelmingly at the whim
of the emotions of those around them (Harari et al., 2010).
The Dark-Side of Empathy
As is evident in the case of BPD, there are negative aspects to experiencing high-levels of
emotion and empathy. This is especially true in our modern-day society and unique
predicament of being flooded with graphic depictions of others in desperate need, from all
over the world. It is believed that a high level of constant awareness of the suffering of others
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can produce what Karen Armstrong refers to as ‘compassion fatigue’ (Armstrong, 2009). An
additional negative aspect of empathy is that it is not always used to promote well-being - for
example in the case of bullying, whereby empathic abilites are used to target another person’s
weaknesses (Hein & Singer, 2008). This more negative take on empathic abilites complements
an alternative theory of empathy which suggests that pro-social behaviour and empathic
action may originate from a place of self-interest and social desirability, rather than altruistic
concern (Vignemont & Singer, 2006). This theory suggests that an ‘empathiser’ may in
actuality be attempting to avoid experiencing negative emotions - such as guilt and shame, by
performing a seemingly empathic action (Vignemont & Singer, 2006). A recent study by Côté
and Hideg (2011), propose that being able to affect people with emotional displays is a
desirable skill, because it can enhance perceptions of competence and liking. However, it
could be argued that having a pronounced ability to affect people emotionally may not in all
cases be desirable. This is especially true if the emotional affect is largely negative and
undermining of competence - for example, if a person is highly socially awkward.
The Benefits of Being Empathic
Despite the aforementioned negative aspects, empathy has been shown to be a vital tool both
psychologically and physiologically. A recent study revealed that when physicians related
empathically to their patients, it significantly helped to improve their chronic health
conditions and in turn their long-term health (Hojat et al., 2011). In addition, the study which
reported that reading fiction can enhance empathy also discovered that this enhanced sense of
emotional resonance felt with the characters, provided readers with a sense of belonging and
the same kinds of mood and life-satisfaction, as membership to real-life social groups (Gabriel
& Young, 2011). Research investigating the beneficial role that empathy plays within
marriages, has found that spouse’s feel most emotionally supported when their partner
emotionally resonates with their distress (Verhofstadt et al., 2008). Echoing these findings, a
recent study suggests that perceived empathic effort produces the strongest relationship
satisfaction (Cohen et al., 2012). These findings thus highlight a positive extra inter-personal
dimension to empathy and its real-world applications (Cohen et al., 2012).
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The Relationship between Facial Expression Recognition and Empathy
There is much evidence to suggest that facial expression recognition is a key skill of
empathy. This relationship is most evident when we consider what happens when this link is
broken or heightened. Damage to the pre-frontal cortex, as previously discussed, creates a
deficit in affective empathy which echoes the pattern of impairments found in psychopathy.
In psychopathy, and some cases of criminal offending, it has been found that there is lack of
emotional responsiveness to both the emotions and facial expressions of others (Blair, 2005;
Shamay-Tsoory et al., 2010). This finding complements research which has found that the
higher a person’s affective empathy is, the quicker they are able to recognise facial
expressions and begin experiencing another person’s emotions (Besel, 2007; Besel & Yuille,
2010). Furthermore, people high in affective empathy, are also more facially reactive when
experiencing the emotions of others, which researchers have postulated could bi-directionally
feedback, and increase their empathic feelings (Dimberg et al., 2011; Ekman, 1992).
These findings, relate directly to the pattern of heightened affective empathy, emotion and
facial expression recognition evident in BPD (Donegan et al., 2003; Harari et al., 2010; Lynch et
al, 2006; Wagner & Linehan, 1999). For example, researchers have found that people with BPD
have a heightened ability to both recognise emotional facial expressions quicker, and with
more accuracy, than controls, (Donegan et al., 2003; Lynch et al, 2006; Wagner & Linehan, 1999).
Furthermore, people with BPD have been found to have a negativity bias towards perceiving
fearful faces when presented with neutral facial stimuli – however, this has been shown not to
take away from their superior speed and accuracy when identifying emotional facial
expressions, (Wagner & Linehan, 1999). Further evidence highlighting a connection between
affective empathy and facial expression recognition has shown that people suffering with
BPD, display significantly higher levels of physiological reactivity within their brains, in
response to other people’s facial expressions and emotions – thus they experience and feel the
emotions of others significantly more than controls (see Figure 2 below), (Donegan, et al.,
2003). It is notable that this study also found that BPD sufferers and healthy controls both had
the highest levels of physiological activation in response to the happiness facial stimuli (see
Figure 2), (Donegan, et al., 2003). Interestingly, a pattern of physiological hyper-reactivity and
distorted facial expression recognition capacity is also found in other emotional disorders,
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such as major depression, social anxiety, and post-traumatic stress disorder (Blair, 2005;
Demenescu, et al., 2010; Hirstein & Ramachandran, 1997; Poljac et al., 2011).
Figure 2: Activation map showing regions in the amygdala
slice in which activation exceeded the criterion threshold level
of p _.005 for control and BPD groups, for four facial
expressions. Reprinted from “Amygdala hyper-reactivity in
borderline personality disorder: implications for emotional
dysregulation,” by N.H. Donegan, C. A. Sanislow, H. P.
Blumberg, R. K. Fulbright, C. Lacadie, P. Skudlarski, J. C.
Gore, I. R. Olson, T. H. McGlashan and B. E. Wexler, 2003,
Biological Psychiatry, 54(11), 1284-1293. Reprinted with
permission.
As the aforementioned studies attest, the hypothesis that facial expression recognition and
empathy are connected is emphasised by the finding that people who suffer from disorders in
facial expression recognition, also tend to suffer from disorders in their empathic abilities,
and vice versa. This connection has proven vitally important, as researchers have found ways
in which these two abilities can be mutually enhanced in order to alleviate deficits in these
areas (Domes et al., 2007; Duke & Nowicki, 1994; Grinspan et al., 2003; Hopkins, 2007; Hopkins et
al., 2011; Trepagnier et al., 2011). Thus in addition, lending weight to the hypothesis that
empathy and facial expression recognition are dynamic skills which can be learnt and
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enhanced over time (Aziz-Zadeh et al., 2011; Baron-Cohen, 2011; Bastiaansen et al., 2011; Martin,
et al., 2012; Trepagnier et al., 2011).
Methodological Implications
As empathy is believed to be the result of both the ability to recognise, and to feel the
emotions of others, the three individual parts of this experimental study have been designed
to test these two elements of empathy. It is the aim of this study to explore the relationship
between facial expression recognition and empathy by analysing and comparing participants’
scores on an empathy scale; by measuring their levels of accuracy when identifying the six
basic facial expressions; and by measuring their emotional resonance with each expression.
At the time of writing this the author knows of no other previous research that has explored
the relationship between empathy and facial expression recognition, using these unique
methodological constructs.
Researchers exploring sex differences in empathy have found that there is a significant
female advantage in empathic abilities (Baron-Cohen & Wheelwright, 2004; Goldenfeld et al.,
2010). Baron-Cohen believes that this is demonstrative of the essential difference between
male and female brains (Baron-Cohen, 2003). However this view is criticised as being largely
based upon findings which utilise self-report measures of empathy, and thus, could be more
attributable to differences in gender display rules and socialisation; rather than indicative of
innate sex-differences in empathic abilities (Ickes et al., 2000; Martin et al, 1996; Riggio et al.,
1989). As this study will utilise psychometrics, it is predicted that there will be a significant
female advantage in empathic abilities for this measure. Furthermore, it is predicted that there
will be significant age-differences in empathic abilities, as research suggests that empathy
and facial expression recognition are dynamic skills which evolve and develop over time
(Aziz-Zadeh et al., 2011; Baron-Cohen, 2011; Bastiaansen et al., 2011; Martin, et al., 2012).
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Drawing from previous research, the predictions of this study are as follows:
1. Scores from the EQ-Short will positively correlate with recognition and resonance scores.
2. Females will score higher than males on the EQ-Short.
3. There will be sex-differences in recognition and resonance scores.
4. There will be inter-sex differences in recognition and resonance scores when viewing
male vs. female facial stimuli.
5. There will be differences in recognition and resonance scores for each of the 6 FEED
Subjects.
6. There will be higher accuracy and emotional resonance scores for the happiness facial
stimuli.
7. There will be age-differences in EQ-Short, accuracy and resonance scores.
Methods
Design
Research was conducted using a nomothetic two-way, mixed between-within experimental
design, which utilised psychometrics.
Participants
142 participants, 62 male (44%) and 80 female (56%), took part in this online study. They
ranged in age from 18-70 years old (M = 32.07, SD = 13.75). Participants were sourced from
the local area of Nottinghamshire and the internet. Invitations were sent to online contacts via
email and Facebook messages (see Appendix 1a & 1b). Participants were also recruited
through two online research hosting websites (The Inquisitive Mind, 2012; Psychological
Research on the Net, 2012); and the SONA system (Nottingham Trent University’s research-credits
programme).
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Materials
The study was built using the online survey hosting website Zoomerang.com (Zoomerang,
2012). Zoomerang was utilised as it allow users to incorporate videos within surveys; has
highly customisable features; and has a user-friendly interface. The first page of the study
contained an integrated informed consent form (see Appendix 2). Throughout the study
participants were required to answer every question on each page before continuing to the
next. The first part of the study was conducted via the administration of the EQ-Short (See
Figure 1, and Appendix 3 & 4). The EQ-Short was placed at the beginning of the study in order
for participants to be able to complete it before becoming too fatigued.
Figure 1, Part One – The EQ-Short: This image shows how the EQ-Short was
formatted within the study and how a 4-point likert scale was utilised.
The second part of this study was created using 36 video-clips selected from the Facial
Expression and Emotion Database – FEED (Wallhoff, 2006). 3 male and 3 female subjects
were chosen from the FEED, each of which expressed the six basic emotions: anger, sadness,
happiness, disgust, surprise and fear (see Appendix 5). The videos were coded, uploaded to a
private YouTube address, and then linked to Zoomerang via embedded codes (see Appendix
5). Participants were asked to watch each video and then select which emotion they thought
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was being experienced (see Appendix 6a & 6b). In response to some of the criticisms that
earlier studies exploring universal facial expressions have faced, participants were able to
select from eight options for each video. They could choose either one of the six basic
emotions, or ‘I do not know’, or ‘Other Emotion’ - thus aiming to reduce the experimenter
effects of a total forced-choice methodology (Russell, 1994). In addition, as the FEED does not
use posed emotional expressions, this was hoped to further reduce experimenter biases
(Russell, 1994). The eight choices were contained within a drop-down box beneath each video
(see Appendix 6a & 6b). The videos were presented in a randomised order for each participant
in order to counter-balance any extraneous order-effects. Below each video was the
‘resonance bar’, which participants were required to use in order to rate their emotional states
upon (see Appendix 6a & 6b). The resonance bar was created using a 5-point likert scale and
scored using the Cambridge Scoring System (Baron-Cohen, & Wheelwright, 2004). Participants’
responses to the ‘positive’ emotion videos - happiness and surprise, were scored: 0, 0, 0, 1, 2;
whilst answers in response to the ‘negative’ emotion videos - anger, fear, disgust, sadness,
were scored: 2, 1, 0, 0, 0.
The final page of the study featured a photo of a polar-bear cub. This was included as a
positive counter-measure in order to neutralise any negative mood induction that may have
occurred from empathising with the ‘negative’ emotions (see Appendix 7). Underneath the
photo was an embedded debriefs, which included information concerning the subjects
investigated within the study; contact details for the researcher; and details of people who
participants could contact with any concerns. Before launching the study, a pilot-study was
performed using 6 participants. This study established an average time-frame for completing
the study (20 minutes); helped to make sure that all the tasks, text and format were easily
comprehensible; and ascertained that all elements of the study were working correctly.
The Empathy Quotient (EQ)
The Empathy Quotient (EQ) is a 40 item multi-dimensional scale, containing statements
designed to measure empathy (Baron-Cohen et al., 2001; Baron-Cohen & Wheelwright, 2004;
Lawrence et al., 2004). A recent study suggests that there is an emphasis in the EQ, on
measuring cognitive empathy and social understanding (Besel & Yuille, 2010). The EQ was
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found to have a high alpha reliability of .84 in a study exploring the effects of Aspergers
Syndrome on empathic abilities (Lawrence et al., 2004). In addition, the EQ has been shown
to have moderate concurrent validity, demonstrated by the moderate correlations between the
EQ and the ‘empathic concern’ and ‘perspective-taking’ subscales of the Interpersonal
Reactivity Index (IRI), (Davis, 1983; Lawrence at al., 2004). When completing the EQ,
participants are required to state how much they agree, or disagree with each statement, using
a 4-point likert scale.
For the purposes of this study the EQ-Short was utilised (Wakabayashi et al., 2006), (see
Appendix 4). The EQ-Short is 22-item version of the EQ. It has been shown to have higher
levels of internal consistency than the original, thus suggesting that some of the 40 items are
unnecessary (Wakabayashi et al., 2006). However, it is notable to state that by reducing these
‘unnecessary items’ some of the face-validity of the EQ also appears to have been
diminished. The depth and breadth of empathic experience appears minimised and the
questions seem to become more cognitively specialised. Nevertheless, the correlations
between scores on the 40-item EQ and the 22-item EQ-Short are high: r = 0.93 (r = 0.93 in
males, and r = 0.93 in females), (Wakabayashi et al., 2006). In addition, the EQ-Short has been
found to have good test-retest reliability (Wakabayashi et al., 2006). In the current study the
Cronbach alpha coefficient for the EQ-Short was a robust .90. Online administration of the EQ
has been reported to have strong concurrent validity and reliability (M = 39.00, SD = 11.44)
compared with face-to-face administration (M = 38.83, SD = 12.40), (Baron-Cohen et al., 2003).
The Facial Expression & Emotion Database (FEED)
The Facial Expressions and Emotions Database (FEED) was created as part of the European
Union project FG-NET (Face and Gesture Recognition Research Network), by Frank
Wallhoff at the Technical University in Munich (Wallhoff, 2006). The FEED contains 18
subjects – 9 male and 9 female, whom each express the six basic emotions as defined by
Ekman and Friesen, (1971). The database seeks to provide users with non-posed, natural
facial expressions, therefore emotions were evoked by subjects watching video clips and
looking at still images. The predominantly Caucasian ethnicity of the FEED is representative
of the predominant ethnicity of Western Europe - where the database originates from, and
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indeed, where this study took place. For the purposes of this study six subjects were chosen
from the FEED based on their sex, expressionality and likeability, (see Appendix 5).
Procedure
Participants accessed the study in their own time via the internet. Participants were asked to
carefully read the study information before agreeing to participate (see Appendix 2). After
reading the information, participants were asked to provide their written consent by creating a
unique identifier, and then provide details of their age and sex before starting the study. Once
participants had completed all parts of the study, they were taken to an embedded debrief
page and thanked earnestly for their time.
Reflecting on Methods
This study was administrated online due to the large and varied sample that this method is
able to provide. In addition, it was believed that this method would be most conducive to the
ecological validity of the study. Feedback from the pilot study revealed that some instructions
needed to be clearer and were thus altered accordingly. In addition, the pilot study
highlighted that some participants struggled to watch the videos due to the capabilities of the
devices which they accessed the study from. As a result, the invitations for the study made it
clear that the study would involve watching videos streamed from YouTube, and therefore
participants would need to make sure that the device they accessed the study from was
capable of doing this. When designing the study it was decided that the word ‘empathy’
should be used minimally throughout, in order to reduce any priming or experimenter-effects.
As the study was only administered online, there is a common methods variance issue -
therefore future studies could benefit from administering parts of the study online and in-
person.
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Results
Data was analysed using SPSS. The data met parametric assumptions as participants were
randomly sampled and Levene’s tests for homogeneity of variance revealed that the data was
normally distributed. A bi-variate correlation revealed that scores on the EQ-Short (M = 23.89,
SD = 9.26), (95% CI = 22.36 – 25.43), (5% Trimmed Mean = 24.07), correlated significantly with
rates of accuracy (M = 22.02, SD = 4.37), (95% CI = 21.30 – 22.75), (5% Trimmed Mean = 22.33),
when identifying the six emotional facial expressions: r = .245, n =142, p = 0.003. Performing
the coefficient of determination revealed that scores on the EQ-Short explained 6% of the
variance in accuracy scores - demonstrating that there was a positive linear relationship
between the two, with weak-to-moderate levels of homoscedasticity, R2 = .0600, p = 0.003, (see
Scatterplot 1 below). The removal of outliers resulted in a minor increase in the level of
shared variance to 6.05%, between EQ-Short (M = 23.97, SD = 9.30), (95% CI = 22.42 – 25.52),
(5% Trimmed Mean = 24.16), and accuracy scores (M = 22.31, SD = 3.67), (95% CI = 21.69 –
22.92), (5% Trimmed Mean = 22.43), r = .246, n = 140, p = 0.003, (R2 = .0605, p = 0.003).
Further analysis investigating the relationship between rates of accuracy and scores on the
EQ-Short using bi-variate correlation, revealed which individual emotions were significantly
correlated with scores from the EQ-Short (p = <0.05), (see Figure 3).
0 5 10 15 20 25 30 35 40 45 500
5
10
15
20
25
30
35
R² = 0.0600195154398054
Scatterplot 1: Correlation Between EQ-Short and Ac-curacy Scores
EQ-Short Scores
Accu
racy
Sco
res
17
Sadness Anger Surprise Disgust Fear Happy0
0.10.20.30.40.50.60.70.80.9
Figure 3: Correlations Between the EQ-Short and Accuracy Scores - for each of the Six Emotions
N = 142
Post-hoc testing exploring the recognition rates for each of the six emotions revealed that
happiness, surprise, disgust and sadness were identified significantly more accurately than
fear and anger (see Figure 4). This was evident within the significant drop in accurate
recognition rates between the fourth and fifth most recognised emotions - sadness and fear,
(M = 1.76, SD = 1.82), t (141) = 11.52, p = <0.001. Therefore, the difference between the most
accurately recognised emotion – happiness, and the least accurately identified emotion –
anger, was also significant, (M = 4.24, SD = 1.45), t (141) = 34.76, p = <0.001, (see Figure 4). In
addition, a paired-samples t-test revealed that happiness was recognised significantly more
accurately than any other emotion. This was evident in the significant difference between
happiness and the second most accurately identified emotion - surprise (M = .563, SD = 1.29), t
(141) = 5.22, p = <0.001. Despite anger being the least recognised facial expression, it was the
only emotion which produced a significant sex-difference in accuracy rates. This was found
using a one-way analysis of variance, which revealed that females (M = 1.45, SD = 1.04), were
significantly more accurate than males (M = 1.08, SD = 1.18), at identifying anger: F (1,140) =
3.92, p = 0.050.
18
Happy Surprise Disgust Sadness Fear Anger0
1
2
3
4
5
6
Figure 4: Accuracy when Identifying Facial Expressions
Accu
racy
Sco
res
A one-way analysis of variance highlighted that females scored significantly higher (M =
25.35, SD = 9.48), than males (M = 22.02, SD = 8.70) on the EQ-Short: F (1,140) = 4.64, p = 0.033.
The one-way analysis of variance also revealed however, that there were non-significant
differences in the scores between females (M = 22.48, SD = 4.41) and males (M = 21.44, SD =
4.28) in their levels of accuracy when identifying emotional facial expressions: F (1,140) =
1.990, p = 0.161. In addition, there were also non-significant differences in the scores between
females (M = 17.74, SD = 13.86) and males (M = 16.76, SD = 14.66) in the resonance measure: F (1,140) = 0.166, p = 0.684.
Resonance (M = 17.31, SD = 14.17), (95% CI = 14.96 – 19.66), (5% Trimmed Mean = 16.60) was
found to be non-significantly correlated to accuracy (r = .023, n = 142, p = 0.790), and to EQ-
Short scores (r = .145, n = 142, p = 0.084). A paired sample t-test revealed that there was a
significant difference in the resonance scores for happiness, compared with the other
emotions (see Figure 5). This was demonstrated by the difference in resonance scores for the
highest resonated emotion happiness (M = 5.09, SD = 4.19), and the second highest resonated
emotion disgust (M = 2.73, SD = 3.13), t (141) = 7.31, p = <0.001, (see Figure 3). Throughout the
resonance measure a high pattern of variability was demonstrated by large standard
deviations evident within the data (see Figure 5, 6, 7 & 9).
19
Happy Disgust Sadness Surprise Anger Fear0
1
2
3
4
5
6
Figure 5: Resonance Levels for the Six Emotions
Reso
nace
Sco
res
For the purposes of analysis participants were split into three age-groups (see Table 1).
Differences across the three age-groups in scores from the EQ-Short and accuracy measures
were non-significant. In addition, an independent t-test revealed that resonance scores
between the two most diverse groups: Group 3 (M = 19.34, SD = 15.86) and Group 2 (M =
13.21, SD = 15.99), were also non-significant: t (55) = 1.45, p = 0.152).
Group Number Age-Range Number of Participants
1 18 – 30 yrs old n = 85
2 31 – 43 yrs old n = 29
3 44 –70 yrs old n = 28
Table 1: Properties of the 3 Age Groups
The three female facial stimuli prompted the highest accuracy and resonance scores, for both
male and female participants (see Figure 6). A paired-samples t-test revealed that the
difference in responses to the male, versus female videos, was significant for both accuracy:
t (141) = 5.595, p = <0.001, and resonance: t (141) = 3.834, p = <0.001.
20
Accuracy Female Videos
Accuracy Male Videos
Resonance Female Videos
Resonance Male Videos
0
2
4
6
8
10
12
14
Figure 6: Differences in Accuracy and Resonance Scores for the Female and Male Facial Stimuli
Parti
cipan
t Sc
ores
A one-way between groups multivariate analysis of variance was utilised to explore possible
inter-sex differences between accuracy and resonance rates, for the male and female
participants, in relation to the male and female facial stimuli. Four dependent variables were
used: accuracy female stimuli, accuracy male stimuli, resonance female stimuli and
resonance male stimuli. The independent variable was sex. Checks were performed to test
whether assumptions of normality, linearity, univariate and multivariate outliers,
homogeneity of variance-covariance matrices, and multicolinearity could be accepted, and no
violations were discovered. There was a non-significant difference between males and
females on the combined dependent variables: F (1,142) = 982, p = .639; Wilks’ Lambda = .634;
partial eta squared = .018. Therefore, no significant inter-sex differences were found between
the scores of the male and female participants, in response to the male and female facial
stimuli (see Figure 7). In the resonance measure, the pattern of high variability in scores is
again demonstrated (see Figure 7 below).
21
M F M F M F M FAccuracy Female Accuracy Male Resonance Female Resonance Male
0
2
4
6
8
10
12
14
Figure 7: Inter-Sex Differences in Accuracy and Resonance Levels when Identifying Male vs. Female Facial Expressions
Mal
e (M
) &
Fem
ale
(F)
Par
ticip
ant S
core
s
There were no significant sex-differences found between the scores from male and female
participants for each of the six FEED subjects in the accuracy measure. However there were
significant differences in accuracy scores when recognising the emotions of Female 1 (F1), (M
= 4.24, SD = 1.12), (see Appendix 6a), versus the accuracy scores for Male 3 (M3), (M = 2.80,
SD = 0.80), (see Appendix 6b), t (141) = 14.779, p = <0.001, (see Figure 8).
0
1
2
3
4
5
Figure 8: Differences in Accuracy Scores in Relation to the Six Individuals Featured within the Videos
Accu
racy
Sc
ores
22
A similar pattern was identified in the resonance scores in response to the six FEED subjects,
demonstrated by the significant difference between the resonance scores for F1 (M = 3.23, SD
= 2.84), (see Appendix 6a), and M3 (M = 2.56, SD = 2.23), (see Appendix 6b), t (141) = 4.46, p =
<0.001, (see Figure 9).
F1 M1 F2 M2 F3 M30.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
Figure 9: Differences in Resonance Scores in Relation to the Six Individuals Featured in the Videos
Reso
nanc
e S
core
s
Discussion
Analysis
1. Scores from the EQ-Short will correlate positively with recognition and resonance scores.
The weak yet highly significant positive correlation between the EQ-Short and accuracy
scores when identifying facial expressions supports the hypotheses that empathy and facial
expression recognition are inter-related. The relatively low level of variance shared between
the two variables could support the analysis of the EQ-Short which suggests that is has an
emphasis on measuring cognitive empathy, rather than construct as a whole (Besel & Yuille,
2010). The EQ-Short did not correlate significantly with resonance scores, which again may be
indicative of the EQ-Short being predominately a cognitive empathy measure - as the
resonance bar was more suited to measuring affective empathy, (Besel & Yuille, 2010). As
such, future studies could consider using either a more comprehensive scale or multiple
empathy scales, in order to cover the wider construct of empathy - including both cognitive
and affective components.
23
2. Females will score higher than males on the EQ-Short.
3. There will be sex-differences in recognition and resonance scores.
Analysis revealed that females scored significantly higher than males on the EQ-Short
This finding supports previous research which has found that females score higher on self-
report measures of empathy, (Baron-Cohen, 2003; Baron-Cohen & Wheelwright, 2004; Goldenfeld
et al., 2010). However, as this pattern was not echoed significantly in accuracy and resonance
scores, these results could lend weight to the critique which states that rather than
highlighting an essential sex-difference in empathic abilities, this finding may be highlighting
a difference in gendered emotion display rules; or perhaps even, that it is more socially
desirable to be empathic for females, than it is for males, (Ickes et al., 2000; Martin et al, 1996;
Riggio et al., 1989). Despite anger being the least accurately recognised emotion, it was the
only one which produced a significant sex-difference in accuracy rates – whereby females
were significantly more accurate at identifying it than males This anger bias is thus a finding
that future studies would benefit from exploring further.
4. There will be inter-sex differences in recognition and resonance scores when viewing
male vs. female facial stimuli.
There was a significant difference in how participants related to the sex of the subjects in the
videos. Female subject’s facial expressions were identified more accurately than males (t
(141) = 5.595, p = <0.001). In addition, resonance scores for female stimuli were significantly
higher than those recorded for the male subjects, lending further support to the argument that
men and women are not significantly different in empathic ability, (Ickes et al., 2000; Martin et
al, 1996; Riggio et al., 1989). Furthermore, these results may be indicative that females are
somehow more emotionally expressive than males, which if accurate, would support the
research by Côté and Hideg, (2011) which sees superior emotional expression as a skill. These
findings also suggest that both males and females may be more open to being empathic with
females, than they are males. Thus, this is another area which would benefit from further
study.
24
5. There will be differences in recognition and resonance scores for each of the 6 FEED
Subjects.
There were significant differences in both the accuracy and resonance scores in response to
the six FEED Subjects - specifically between Female 1 (F1), (see Appendix 6a), who had the
highest accuracy and resonance scores, versus Male 3 (M3), (see Appendix 6b), who had the
lowest accuracy and resonance scores, These findings could be indicative of F1’s superior
skill at conveying her emotions, (Côté and Hideg, 2011). Furthermore, they could also be
related to her level of empathic ability - we are watching her, watch someone or something
else - which she is emoting to and empathising with; therefore it may be that the resonance
scores actually reflect the empathic abilities of the subjects, as well as the participants (Dimberg, 2011).
6. There will be higher accuracy and emotional resonance scores for the happiness facial
stimuli.
Happiness was the most significantly accurately identified emotion. This complements
previous findings which have highlighted that happiness is the most physiologically
responded to emotion, (Donegan et al., 2003). Thus, perhaps this physiological effect could be
producing a resulting boost in the salience of happiness, (Becker & Leinenger, 2011).
Happiness, along with sadness, disgust, and surprise were all identified significantly more
accurately than fear and anger. These results may be indicative that at the time of
participating in the study, anger and fear were less emotionally salient for the majority of
participants, (Becker & Leinenger, 2011). Conversely, anger may have been recognised the
least due to the diluted nature of the representation of anger that was expressed within the
videos. Again, it is important to make the observation that participants watched the subjects,
watching someone or something else. The anger stimulus that the subjects were viewing is
likely to be a primary source (i.e. someone getting very angry), whereas what participants are
then experiencing as viewers is a secondary source. Whereas, it is believed that the response
to happiness, sadness, disgust surprise and fear would all cause a primary replication of the
emotion in the subjects, thus causing participants to be more able to easily and accurately
recognise them. As such, this again may also be indicative of how empathic the subjects are,
in addition to the participants.
25
Happiness was resonated with significantly more than the other five emotions, again
supporting the finding that happy expressions produce the highest level of physiological
activation in empathisers, (Donegan et al., 2003). Conversely, happiness could have been
resonated with most significantly due to the social desirability attached to being happy or
rather, being seen as happy. Alternatively, this findings could be due to the scoring system,
and how intuitively feeling lots of happiness, equates to ‘+ 2’ on the resonance bar. Feeling
lots of sadness would work just as well – by equating this with ‘- 2’, but it is not as easy to
place surprise, fear, disgust and anger on the polarised bar. Therefore the design of this
methodological construct may have contributed to the high patterns of variability in levels of
resonance expressed by both sexes, and across all of the age-groups (see Figures 5, 6, 7 & 9).
The high pattern of variability in resonance levels may also be indicative of the multi-faceted
nature of each emotion and thus be highlighting that there are different types of sadness,
happiness, etc - some which are negative and some which are positive. Thus it could be that
the Cambridge Scoring System was not equipped to account with this level of variability.
This pattern of variability could also be attributed to the highly subjective and individual
nature of emotion. Indeed, perhaps this variability is attributable to the different environments
and conditions that the participants were in, when they took part in the study, (Foroni et al.,
2011; Hein & Singer, 2008; Matsumoto, 1991; Vignemont, & Singer, 2006). As this was an online
study, there is no way of knowing what emotional or mental states participants were in at the
time they took part, thus further emphasising the possibility of increased variability in their
emotional states and resulting levels of emotional resonance. Therefore future studies would
benefit from seeking information regarding participants’ emotional baselines at the beginning
of each section of the study, in order to explore the effects that emotional states can have on
empathic abilities, (Becker & Leinenger, 2011).
7. There will be significant age-differences in the EQ-Short, accuracy and resonance scores.
Though all tests for age related differences in significance across the three conditions were
non-significant; interestingly it was the eldest age group which displayed the least resonance
with the videos. Perhaps this could be attributable to an age-related type of ‘compassion
fatigue’, (Armstrong, 2009); or maybe even due to the elder generation being less used to
26
watching videos on YouTube and therefore being less empathically open, because the context
is unfamiliar to them. Especially in contrast to their younger counterparts, who will be more
likely to be familiar with watching videos via this medium. Their lower resonance scores
could also be a product of all the subjects in the FEED videos being roughly the same age as
each other – around 30years old, which may make them more relatable to the youngest and
middle-aged participants, than it does to the eldest ones. Conversely this lower score could be
indicative of the natural decline in the MNS with age (Bastiaansen et al., 2011).
Additional Limitations and Suggestions for Future Research
Feedback from participants revealed that they heavily doubted their ability to accurately
identify the facial expressions which resulted in them experiencing anxiety and in turn may
have interfered with their empathic abilities. Future studies could allow participants to pick
multiple emotions, or give open-ended answers instead, as this may help to alleviate
insecurity and elevate accuracy rates. Secondly, as this study was only administered once per-
participant, this has in reality only afforded a snap-shot representation of their potential
empathic abilities. Therefore future studies could administer the experimental measures on
multiple occasions in order to gain a more rounded view of participants’ abilities, and in
order to increase the studies temporal validity and reliability. Multiple administrations would
also allow for the exploration of the effects of the contexts within which participants took
part in the study, as this have been shown to play such a significant role in resulting empathic
abilities (Foroni & Semin, 2011; Hein & Singer, 2008; Matsumoto, 1991; Vignemont, & Singer,
2006).
The FEED stimuli used in this study may lack ecological validity as the empathiser is not
experiencing the emotions of another person face-to-face, nor in a real-world setting.
However, it could be argued that the modern ubiquitous use of computers, televisions and
smart phones, could mean that people are now accustomed to relating to and empathising
with others through this type of medium. An additional limitation of the FEED stimuli is that
it only provided a one dimensional sense of emotion – visual. If the FEED videos
incorporated sound, it may have increased the levels of accurate recognition and resonance
rates. Furthermore, the FEED only featured Caucasian subjects; therefore this may have
27
produced race effects in expression recognition which are not able to be accounted for, as
data was not collected on participant race/ethnicity. Therefore, future studies would benefit
from altering the stimuli to include multiple ethnicities, and in addition, could explore race
effects in empathy and expression recognition, when the empathiser is of both the same, and
of differing ethnic origin.
Conclusions and Implications
The results of this study support previous findings which have highlighted a link between
facial expression recognition and empathy. It is hoped that by further illuminating this
connection, a deeper understanding of conditions whereby this capacity is impaired or
heightened can be achieved. This is especially true in terms of educational, health and work-
place settings, where people suffering from these conditions would greatly benefit from
increased levels of support, understanding and awareness of the issues that they face on a
day-to-day basis, as a result. Knowledge of the connection between empathy and facial
expression recognition abilities can also bring great hope to sufferers and their families, as
research has shown that there are effective ways in which these two abilities can be mutually
enhanced, (Domes et al., 2007; Duke & Nowicki, 1994; Grinspan et al., 2003; Hopkins, 2007;
Hopkins et al., 2011; Trepagnier et al., 2011). In addition, at the opposite end of the spectrum,
knowledge of the hyper-activity present in empathic abilities, and disturbances in facial
expression recognition found in conditions such as BPD, major depression, PTSD and social
anxiety, can provide sufferers and their families with great comfort, by enabling sufferers to
be able to learn skills that help them to modulate and manage their own problematic and
heightened responses to emotional stimuli (Blair, 2005; Demenescu, et al., 2010; Hirstein &
Ramachandran, 1997; Poljac et al., 2011; Wagner & Linehan, 1999).
Furthermore, this and other studies have highlighted how powerful seeing others experience
the emotion happiness is; and reveals the profound effects it can have both physiologically
and emotionally. This finding has huge implications for understanding the positive and
negative effects that the environments we inhabit and the people that we are exposed to, on a
daily basis, can have on our minds and bodies. In addition, this happiness effect could be
utilised by mental-health care professionals to design treatments to positively support and
28
help people that are suffering from empathic and facial expression recognition disorders such
as BPD, depression, PTSD and social anxiety.
Further Information
For an excellent video introduction to empathy which explores its historical context, and
looks at its relevance in our modern-day world, see The Empathic Civilisation, (Rifkin, 2010).
In addition, for an enlightening video introduction to Mirror Neurons, please see Menon,
(2011).
Acknowledgements
The author would like to thank Phil Banyard for his enduring help in bringing this project to
fruition; Frank Wallhoff for creating the FEED and allowing the use of it in this study; and
Prof. Dr Akio Wakabayashi for his part in creating the EQ-Short and for giving his permission
for it to be used for the purposes of this study.
29
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Appendix 1
1a – Email Message
Do you consider yourself to be an empathic person?
Can you identify what emotion someone is feeling from their facial expression alone?
Are these two qualities related?
This psychological experiment is designed to explore these questions.
To take part you will need to be able to watch a selection of short videos streamed directly from YouTube - so it’s important that your computer / smart phone and internet connection are up to doing this.
If you know of anyone else who you think would be willing to complete this survey, please feel free to forward the survey link on to them.
This is for my third year dissertation so I'd really appreciate you taking part.
Many thanks & best wishes,Rebecca
1b - Facebook Message
Do you consider yourself to be an empathic person?
Can you identify what emotion someone is feeling from their facial expression alone?
Are these two qualities related?
This psychological experiment is designed to explore these questions.
To take part you will need to be able to watch a selection of short videos streamed directly from YouTube - so it’s important that your computer / smart phone and internet connection are up to doing this.
If you know of anyone else who you think would be willing to complete this survey, please feel free to invite them to this group, or forward the survey link on to them.
https://www.zoomerang.com/Survey/WEB22EBCLEVSAW
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Appendix 2
Informed Consent Form
* Please read the following information carefully before deciding whether to participate in this research:
Why are you doing this research? I want to understand the relationship between empathy and facial expression recognition. More specifically, I want to know whether people who rate highly on an empathy scale have increased facial expression recognition and emotional resonance.
Are there any risks?There are no known risks associated with taking part in an experiment of this kind. Please keep in mind that you are able to end the experiment at any time by simply closing the browser window.
What do I get out of it? If you are a fellow university student you will be awarded with research credits for taking part. In order to obtain your credits you will need to email [email protected], & quote your Unique Identifier & your N-Number. For everyone else, you will be awarded with my eternal gratitude. Will you share my information with other people? Your information will under no circumstances be shared. Your data will be anonymised, and only identifiable through a Unique Identifier - such as 'lotusflower1', which you will need to provide below. All data will be password-protected and secure. What if I change my mind and I don’t want to do the experiment anymore, or I want to have my data removed from the study? Your participation in this study is completely voluntary and you may exit at any point by simply closing the browser window. If you decide you want to have your data removed from the study this is possible up until February 17th 2012. In order to do this you will need to contact either myself ([email protected]) or my Project Supervisor, Phil Banyard ([email protected]). * However, please bear in mind that a by-product of doing this, is that you will lose your anonymity. What if I have questions or something to tell you? If you have any questions, comments or queries please use the above contact details to get in touch. What if I have questions about my rights in this research, have a
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complaint, or want to report a problem to someone besides the researcher? You can contact Phil Banyard using the above details, or alternatively you can contact Nottingham Trent University directly on: +44 (0)115 941 8418
How do I agree to participate? By providing a Unique Identifier & pressing 'Submit' below, you are confirming that you:
1. Agree to take part in this research. 2. Understand what you are getting into. 3. Understand you are free to leave the experiment at any point. 4. Are aged 18 years old, or above.
This research has been reviewed and approved by the Nottingham Trent University School Research Ethics Committee (SREC), and follows the British Psychological Society (BPS), & Nottingham Trent University's (NTU), Code of Conduct and Ethics Policies.
* I agree to take part in this research. I feel that I understand what I am getting into, and I know that I am free to leave the experiment at any time.
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Appendix 3
Appendix 3a – Intro to the EQ-Short
Part 1
On the following page there will be a list of statements.
Please read each statement very carefully and rate how strongly you agree or disagree with it by clicking next to the appropriate answer.
There are no right or wrong answers, or trick questions.
Appendix 3b – Intro to the Videos and Resonance Bar
Part 2
In the second part of this experiment you will watch a selection of short videos which show a group of people expressing different emotions.
After watching each video you will need to decide which emotion you think is being expressed via their facial expression.
Finally you will take a moment after each video, to rate how you are feeling by using the scale provided. This is in order to chart your emotional state as you progress through the videos.
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Appendix 4
The EQ-Short
1. (1.) I can easily tell if someone else wants to enter a conversation.
2. (3.) I really enjoy caring for other people.
3. (4.) I find it hard to know what to do in a social situation. a
4. (8.) I often find it difficult to judge if something is rude or polite. a
5. (9.) In a conversation, I tend to focus on my own thoughts rather than on what my listener
might be thinking. a
6. (11.) I can pick up quickly if someone says one thing but means another.
7. (12.) It is hard for me to see why some things upset people so much. a
8. (13.) I find it easy to put myself in somebody else’s shoes.
9. (14.) I am good at predicting how someone will feel.
10. (15.) I am quick to spot when someone in a group is feeling awkward or uncomfortable.
11. (18.) I can’t always see why someone should have felt offended by a remark. a
12. (21.) I don’t tend to find social situations confusing.
13. (22.) Other people tell me I am good at understanding how they are feeling and what they are
thinking.
14. (26.) I can easily tell if someone else is interested or bored with what I am saying.
15. (28.) Friends usually talk to me about their problems as they say that I am very
understanding.
16. (29.) I can sense if I am intruding, even if the other person doesn’t tell me.
17. (31.) Other people often say that I am insensitive, though I don’t always see why. a
18. (34.) I can tune into how someone else feels rapidly and intuitively.
19. (35.) I can easily work out what another person might want to talk about.
20. (36.) I can tell if someone is masking their true emotion.
21. (38.) I am good at predicting what someone will do.
22. (39.) I tend to get emotionally involved with a friend’s problems.
( ) Nos. of items are in original versions.
a Reversal items.
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Appendix 5
How the 36 FEED videos were coded for the six subjects and emotions
F1 - FEEDF61 = SURPRISE – 26/27- FEEDF65 = SAD – 28/29- FEEDF63 = HAPPY – 30/31- FEEDF66 = FEAR – 32/33- FEEDF62 = DISGUST – 34/35- FEEDF64 = ANGER – 36/37
F2 - FEEDF53 = SURPRISE – 38/39- FEEDF55 = SAD – 40/41- FEEDF51 = HAPPY – 42/43- FEEDF54 = FEAR – 44/45- FEEDF56 = DISGUST – 46/47- FEEDF52 = ANGER – 48/49
M1 - FEEDM42 = SURPRISE – 50/51- FEEDM41 = SAD – 52/53- FEEDM44 = HAPPY – 54/55- FEEDM45 = FEAR – 56/57- FEEDM46 = DISGUST – 58/59- FEEDM43 = ANGER – 60/61
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M2 - FEEDM32 = SURPRISE – 62/63- FEEDM36 = SAD – 64/65- FEEDM33 = HAPPY – 66/67- FEEDM31 = FEAR – 68/69- FEEDM34 = DISGUST – 70/71- FEEDM35 = ANGER – 72/73
F3 - FEEDF22 = SURPRISE – 74/75- FEEDF23 = SADNESS – 76/77- FEEDF25 = HAPPY – 78/79- FEEDF26 = FEAR – 80/81- FEEDF21 = DISGUST – 82/83- FEEDF24 = ANGER – 84/85
M3 - FEEDM16 – SURPRISE – 86/87- FEEDM15 = SAD – 88/89- FEEDM14 = HAPPY – 90/91- FEEDM13 = FEAR – 92/93- FEEDM11 = ANGER – 94/95- FEEDM12 = DISGUST – 96/97
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Appendix 6a
Example of Pages with Video and Resonance Bar
Example 1: F1 - Surprise
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Appendix 6b
Example 2: M3 – Fear
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Appendix 7
Embedded Debrief with Cute Picture as Mood Counter-Measure
Thank you for participating in this survey!
This experiment was designed to explore the relationship between an individual’s self-referential feelings and beliefs about their own level of empathy - with how accurate they are at identifying emotions through facial
expressions; and in addition, their level of emotional resonance when doing so.
If you wish to withdraw your data from the study, you can do so up until February 17th 2012, by contacting me on: [email protected] and quoting your Unique Identifier.
Data will be stored until August 2012
If you would like a copy of the final report please contact me on [email protected]..
There are no known risks in taking part in this type of study, although if you feel particularly uncomfortable or upset by anything in this study please contact your doctor and / or your local counselling services.
If you have any queries, please do not hesitate to contact me at [email protected] or alternatively you can contact my project supervisor, Phil Banyard: [email protected];
+44 (0)115 848 5585
IMPORTANT - NTU STUDENTS: In order to obtain your Research Credits you will need to email me on [email protected], & quote your
Unique Identifier & N-Number.
47