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Emotional intelligence and psychological resilience to negative life events


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This study investigated the relative importance of six emotional intelligence (EI) dimensions in the prediction of psychological resilience to multiple negative life events. The strength of relations between life events and distress varied markedly across three latent classes of participants, reflecting vulnerable, average and resilient profiles. Discriminant function analysis indicated that class membership varied as a function of four EI dimensions, with higher scores predicting membership to the resilient class. Across the 414 participants, Emotional Self-Awareness, Emotional Expression, Emotional Self-Control and particularly Emotional Self-Management appeared central to psychological resilience in the aftermath of multiple negative life events.
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Emotional intelligence and psychological resilience to negative life events
Andrew R. Armstrong
, Roslyn F. Galligan
, Christine R. Critchley
AP-HP, Saint-Louis Hospital, Dept. of Clinical Research (PRO Unit), Paris, France
Swinburne University of Technology, Faculty of Life and Social Sciences, Melbourne, Australia
article info
Article history:
Received 8 June 2010
Received in revised form 15 March 2011
Accepted 17 March 2011
Available online 6 May 2011
Emotional intelligence
Psychological resilience
Life events
This study investigated the relative importance of six emotional intelligence (EI) dimensions in the pre-
diction of psychological resilience to multiple negative life events. The strength of relations between life
events and distress varied markedly across three latent classes of participants, reflecting vulnerable, aver-
age and resilient profiles. Discriminant function analysis indicated that class membership varied as a
function of four EI dimensions, with higher scores predicting membership to the resilient class. Across
the 414 participants, Emotional Self-Awareness, Emotional Expression, Emotional Self-Control and par-
ticularly Emotional Self-Management appeared central to psychological resilience in the aftermath of
multiple negative life events.
Ó2011 Elsevier Ltd. All rights reserved.
1. Introduction
Major life events, including the death of loved-ones, serious ill-
ness, or job loss, precede almost all types of mood disorder (Stueve,
Dohrenwend, & Skodol, 1998). Emotional intelligence (EI), or the
ability to intelligently utilise emotional information, may temper
their impact on mental health (Ciarrochi, Forgas, & Mayer, 2001).
How EI might buffer the effect of aversive events is the focus of
the present study.
Stressful or negative life events have typically been construed
as change events that precipitate movement from one set of living
conditions to another. The life transitions resulting from such
events pose significant adaptational challenges that can strain peo-
ple’s ability to cope to the point of clinical distress, manifest for in-
stance in symptoms of depression, anxiety, and stress. Moreover,
the experience of multiple such events can compound distress
(Monroe & Simons, 1991). Indeed, one stressful event can impede
coping efficacy for additional events, increasing vulnerability to
and even the likelihood of further negative events (Kessler,
1997). As well, transitional recovery periods are typically quite
long. Research has shown that significant life events often retain
their impact over a two-year period (Monroe & Simons, 1991).
While such events are potentially traumatic, people are im-
pacted differently. Some people experience long-term trauma.
Others suffer significant short-term impairment. Then there are
those who experience only mild, transient perturbations. Such per-
sons are considered resilient (Bonanno, 2004).
Emotional intelligence may well be directly connected to resil-
ience, such that emotionally intelligent behaviour in stressful cir-
cumstances is adaptive. Salovey, Bedell, Detweiler, and Mayer
(1999) theorize that persons with higher EI cope better with the
emotional demands of stressful encounters because they are able
to ‘‘accurately perceive and appraise their emotions, know how
and when to express their feelings, and can effectively regulate
their mood states’’ (p. 161). EI is thus postulated to buffer the ef-
fects of aversive events through emotional self-awareness, expres-
sion and management.
Researchers investigating these and other health-related links
have frequently distinguished between ability-based EI models in
which EI is assessed via intelligence-like tests (e.g. the Mayer-Salo-
vey-Caruso Emotional Intelligence Test; Mayer, Salovey, & Caruso,
2000) and trait models in which EI is measured via self-reported
emotion-related dispositions, self-perceptions or motivations (e.g.
the Trait Emotional Intelligence Questionnaire; Petrides, Pita, &
Kokinnaki, 2007). While ability tests purport to measure ‘‘maximal
performance’’, trait-models measure ‘‘typical performance’’
(Petrides et al., 2007). In the current study we focus on typical per-
formance rather than episodes of peak EI performance in coping
with event-related distress. Moreover we take the view that emo-
tional intelligence is antecedent to resilience (Matthews, Zeidner,
& Roberts, 2002) rather than encompassing resilience (Bar-On,
1997), such that EI functions through its composite dimensions
to facilitate resilience.
The evidence linking self-reported EI to health is considerable. A
meta analysis of 80 studies involving 20,000 participants found the
0191-8869/$ - see front matter Ó2011 Elsevier Ltd. All rights reserved.
Corresponding author.
E-mail address: (A.R. Armstrong).
Personality and Individual Differences 51 (2011) 331–336
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average strength of relationship between EI and mental health to
be around r= .36, r= .33 for psychosomatic health, and r= .27 for
physical health criteria (Martins, Ramalho, & Morin, 2010). Other
studies have shown that self-reported EI can moderate the psycho-
logical impact of experimentally induced-stress (Mikolajczak,
Petrides, Coumans, & Luminet, 2009), academic exam stress
(Mikolajczak, Luminet, & Mendil, 2006) and emotional labour in
the workplace (Mikolajczak, Mendil, & Luminet, 2007). Two studies
have also examined the buffering hypothesis in the context of mul-
tiple stressful life events (Ciarrochi, Deane, & Anderson, 2002; Day,
Therrien, & Carroll, 2005), but despite positive associations be-
tween EI and mental health, neither study found substantive
evidence of buffering.
In the current study, we examine the relative value of six EI
dimensions that constitute the Swinburne University Emotional
Intelligence Test (SUEIT; Palmer & Stough, 2002) in moderating
the ongoing psychological impact of multiple negative life events
that occurred in the preceding 2 years. The SUEIT was chosen for
its robust psychometric properties, well-defined scales, rigorous
testing history (Gignac, 2005, 2010) and alignment with Salovey
et al.’s (1999) theoretical postulate. The six EI dimensions concern:
(1) awareness of emotions in self, and (2) others, (3) emotional
expression, (4) emotional self-control, (5) emotional management
of self, and (6) others. Research in related fields highlights the po-
tential buffering effects of the six EI dimensions.
1.1. Emotional self-awareness
Research focused on alexithymia, a condition characterized by
poor emotional self-awareness, indicates that persons afflicted
typically fail to respond to rising stress levels until distress is
fully-blown (Martin & Pihl, 1986). They often experience more se-
vere symptoms and longer periods of recovery in the aftermath of
stressful events than more perceptive persons, who deploy per-
sonal coping resources earlier and more effectively (Naatanen,
Ryynanen, & Keltikangas-Jarvinen, 1999).
1.2. Emotional awareness of others
Perspective taking is an important tool in developing quality so-
cial relationships (Soenens, Duriez, Vansteenkiste, & Goossens,
2007), which are a well established source of psychological support
(Kessler, 1997). Propensity to anticipate and account for the feel-
ings of others may therefore play a role in facilitating greater
personal psychological resilience.
1.3. Emotional expression
Emotional expression through overt channels, such as voice and
musculature, has been found to result in attenuation of physiolog-
ical reactivity and associated psychological symptoms. On the
other hand, inhibition results in retention of physiological arousal
and psychological agitation, which over time manifests in physical
illness (Franz, Schaefer, & Schneider, 2003), and mental health
symptoms (Wastell, 2002).
1.4. Emotional self-control
Persons with poor emotional control are more likely to respond
to personal distress with anti-social behaviours (Roger & Najarian,
1989), driving supportive persons away (Benotsch, Christensen, &
McKelvey, 1997). Moreover, impulsive behaviour often translates
into unhealthy coping behaviours such as substance use (Salovey,
2001) Consequently, higher levels of distress are experienced when
faced with stressful situations (Roger & Najarian, 1989).
1.5. Emotional management of self
Persons able to self-induce positive moods are happier in both
positive and negative circumstances (Ciarrochi, Chan, & Caputi,
2000), and tend to be more physically and mentally healthy
(Extremera & Fernandez-Berrocal, 2002). They engage more fre-
quently in active coping behaviours such as problem-solving,
self-pep talks and physical exercise (Salovey, Stroud, Woolery, &
Epel, 2002).
1.6. Emotional management of others
Persons able to induce positive moods in others often have
greater access to social supports (Ciarrochi, Chan, & Bajgar,
2001). They are more willing to seek help when feeling over-
whelmed, and to benefit (Ciarrochi & Deane, 2001).
Evidently, there are a variety of ways in which EI can potentially
buffer individuals against life event distress. Why then did
Ciarrochi et al. (2002), and Day et al. (2005) fail to find substantive
support for this position? One possible answer stems from the fact
that moderator effects are notoriously difficult to detect in
observational field studies, using traditional moderated multiple
regression procedures. The measurement error typical of non-
experimental variables creates levels of noise that make reliable
effects hard to detect. Compounding this, measurement error is
exacerbated when independent variables are multiplied together
to form moderator variables (McClelland & Judd, 1993). This makes
moderator effects even harder to detect.
In light of this, we used a different approach to explore the
question of whether persons with higher EI scores are more
resilient to the effects of multiple events. We performed a series
of latent class regression analyses to determine whether the rela-
tionship between the frequency of negative events experienced
in the past two years and psychological distress was relatively
homogenous across all participants in the study, or, whether the
strength of this effect differed across participants to the extent that
latent classes of participants better represented the data. (i.e.
whether there were distinct clusters of participants who varied
according to their event-distress regression scores).
In line with previous research, it was expected that there would
be a latent class (i.e. cluster) of participants who would demon-
strate a significantly stronger association between life events and
distress (a vulnerable group). Conversely, it was expected that
there would be at least a second latent class that would demon-
strate a non-significant or weaker life events – distress relationship
(i.e., a resilient group). Moreover it was expected that EI would dis-
criminate between these two classes in that the vulnerable group
would have lower EI scores, whereas the resilient group would
have higher EI scores.
2. Method
2.1. Participants and procedure
Members from 56, life event focused, online discussion forums
(e.g.;; were
invited to complete an online survey. Of 1156 persons who an-
swered the first survey question, 414 (48.5%) completed the survey
and were of the age of adult consent. Participants were mostly wo-
men (76%), aged between 24 and 58 (M= 36.7, SD = 12.4), who had
completed a university degree (60%). Most were in paid employ-
ment (42% full-time, 17% part-time). A smaller number were full-
time students (19%) or performed home duties (10%). Citizens of
the USA comprised the largest proportion of participants (45%), fol-
332 A.R. Armstrong et al. / Personality and Individual Differences 51 (2011) 331–336
lowed by Australia (24%), the UK (15%) and Canada (9%). The
remainder were citizens of European, Asian or African countries.
2.2. Measures
2.2.1. Emotional intelligence
Emotional intelligence was measured using a revised 44-item
version of the SUEIT. This version was derived from extensive fac-
tor analytic investigation involving data from 1503 participants
(Gignac, 2005). It is the predecessor to the newly published
70-item Genos EI, factorially validated on some 4700 participants
(Gignac, 2010), with which it shares the same dimensional
structure and 44 items (Palmer, Stough, Harmer, & Gignac, 2009).
Participants responded to statements on a five-point Likert scale
from 1 = ‘almost never’ to 5 = ‘almost always’. Scores were calcu-
lated separately for six subscales: (1) Emotional Self-Awareness
and (2) Emotional Awareness of Others concern perceiving and
understanding one’s own and others’ emotions respectively; (3)
Emotional Expression concerns expressing one’s emotions effec-
tively; (4) Emotional Self-Control concerns controlling one’s strong
emotions; (5) Emotional Management of Self and (6) Emotional Man-
agement of Others concern managing one’s own and others’ emo-
tions respectively. A seventh and final subscale concerned with
‘Emotional Reasoning’ in decision-making, was not included in the
current study due to weak factorial validity, an issue common to
all such factors across EI inventories (Gignac, 2010).
2.2.2. Psychological distress
Distress was assessed using the short version of the Depression
Anxiety Stress Scale (DASS-21; Lovibond & Lovibond, 1995), which
contains 21 items distributed across depression, anxiety, and stress
subscales. Participants rate the extent to which they had experi-
enced each of the items over the past month on a 4-point sever-
ity/frequency scale ranging from 0 = ‘did not apply to me at all’
to 3 = ‘applied to me very much’. In the present study, the full scale
score was used.
2.2.3. Negative life events
Life events were sampled from a revised Social Readjustment
Rating Scale (SRRS; 43 items; Scully, Tosi, & Banning, 2000), the
original being devised by Holmes and Rahe (1967) and cited in
over 4000 publications (Hobson et al., 1998). As with the original,
events range from minor (e.g. change in dietary habits) to major
(e.g. death of a loved one). In the present study, events referring
to a change in circumstances were re-itemized to reflect improve-
ment or worsening of the situation (e.g. dietary habits worsened).
The number of events subsequently expanded to 59
. Participants
indicated whether they had experienced each event within the past
two years and whether the event continued to have a positive or
negative effect on their wellbeing. The frequency of events contin-
uing to have a negative effect was summed for a total out of 59 for
each participant.
3. Results
Table 1 presents descriptive statistics and correlations among
the variables. On average, the sample remained negatively affected
by five events that had occurred in the past 2 years, and reported
distress symptoms consistent with mild depression, anxiety and
stress. EI levels were comparable to those reported by Gignac
(2005). All six dimensions were positively interrelated, and most
were negatively related to life events and distress.
3.1. Latent class regression analysis: negative life events and distress
A series of latent class regression (LCR) analyses were per-
formed using Latent Gold (Version 4) to determine whether the ef-
fect of negative life events on distress was homogenous across all
participants, or whether the strength of this effect differed across
participants to the extent that latent classes of participants better
represented the data. Unlike traditional regression techniques,
which assume that a similar regression coefficient holds true for
all cases in a given sample, LCR detects and extracts distinct latent
classes of participants who share similar regression coefficients on
a set of predictor-outcome variables (Magidson & Vermunt, 2004).
As recommended by Vermunt and Magidson (2000), a 1-class
model was initially estimated using maximum likelihood (ML), fol-
lowed by additional models which successively incremented the
number of classes by one, until the simplest model with the small-
est Baysian Information Criterion (BIC) value was found. The de-
fault Latent Gold LCR setting of 10 random starts was retained
for each model.
As shown in Table 2, similar BIC values occurred for the 3 and
4-class models. However, classification error was notably larger for
the 4-class model, and parameters were fewer for the 3-class mod-
el. The 3-class model was thus considered better fitting and more
parsimonious. Eighty percent of variation in distress was explained
by negative life events in the 3-class model.
Latent class regression statistics for the 3-class model are
shown in Table 3. The unstandardized beta values indicate that
for each class, higher numbers of negative life events predicted
higher distress levels. However, Wald statistics for events indicated
that the strength of this relationship was significantly different be-
tween classes.
Regression lines depicting the relationship between accumu-
lated events and distress for each latent class are plotted in
Table 1
Intercorrelations among EI dimensions, distress and negative life events.
1. Emotional self-awareness 7.56 1.42 (.74)
2. Emotional expression 15.87 3.97 0.44
3. Emotional awareness of others 63.93 8.43 0.43
4. Emotional self-control 11.87 3.00 0.24
5. Emotional self-management 29.60 6.52 0.36
6. Emotional management of others 20.27 3.56 0.38
7. Distress 36.57 28.59 0.24
0.09 0.38
8. Negative life events 4.83 3.34 0.10
0.04 0.13
0.08 0.46
N= 414.
Cronbach’s alphas are located on the diagonal in parentheses.
p< 0.05.
p< 0.01.
p< 0.001.
Expanded scale available from first author
A.R. Armstrong et al. / Personality and Individual Differences 51 (2011) 331–336 333
Fig. 1. Anchors for negative life events comprise the mean and one
standard deviation above and below. Anchors for distress comprise
percentile ranks and ranges sourced from Lovibond and Lovibond
(1995).Figure 1 illustrates a pattern of graduated life event distress
class profiles. Class 2 were most distressed by higher numbers of
life events, Class 3 were least distressed, while Class 1 fell in be-
tween. Classes 2, 1 and 3 were thus labelled Vulnerable, Average
and Resilient.
3.2. Discriminant function analysis: class membership and emotional
A discriminant function analysis was subsequently modelled to
test whether membership to the three classes varied as a function
of the six EI variables. Summary statistics for the EI variables by
class are presented in Table 4.
The three classes were reliably distinguished by one discrimi-
nant function, which comprised four EI variables and explained
35% of the variation in class membership, Wilks = .65,
(12) = 174.27, p< .001. The function was very strongly correlated
with Emotional Management of Self, r= .90, p< .001, strongly cor-
related with Emotional Self-Control, r= .51, p< .001, and moder-
ately correlated with Emotional Expression, r= .44, p< .001, and
Emotional Self-Awareness, r= .39, p< .001. Centroids for the dis-
criminant function revealed that the Resilient class (.96) had signif-
icantly higher EI scores than both other classes, that the Vulnerable
class (.94) had the lowest EI scores, and that the Average class
(.04) fell almost precisely in between.
4. Discussion
The current study sought to identify which participants were
more and less successful at adapting to the emotional demands
of stressful events, and to identify the extent to which individual
differences in adaptation could be attributed to respective aspects
of emotional intelligence. The study found that the relationship be-
tween negative life events and distress varied as a function of four
intrapersonal EI dimensions. The life event-distress relationship
was weaker for participants with higher levels of Emotional Self-
Awareness, Emotional Expression, Emotional Self-Control and par-
ticularly, Emotional Self-Management.
4.1. The nature of relations between stressful life events and distress
Ninety-five percent of participants reported that one or more
stressful events continued to exert a negative influence on their
wellbeing up to 2 years later. On average, participants remained
negatively affected by around five events, while event distribution
data indicated that the number of such events typically ranged
from a low one or two, to a high eight events. A greater accumula-
tion of such events predicted heightened symptoms of psycholog-
ical distress in the preceding month.
Yet, while pervasive, the life event-distress relationship was not
uniform across the sample. Instead, three latent classes with dis-
tinct life event-distress profiles were identified. These classes were
subsequently labelled Vulnerable, Average and Resilient. For the
29% of participants classified into the Vulnerable class, the ongoing
negative affect of just one or two past events corresponded with
current distress levels within the moderate clinical symptom
range. Worse were those who continued to be affected by the sam-
ple average of five events who reported clinical symptoms border-
ing on severe. Those who remained affected by a high eight events
reported symptoms well within the severe clinical range.
For the 44% of participants in the Average class, the ongoing
negative affect of 1–2 events in the past 2 years corresponded with
normal present functioning. Five events corresponded with symp-
toms bordering on mild distress. Moderate distress symptoms
emerged for those who remained affected by a high eight events.
Finally, the 27% of participants that comprised the Resilient class
exhibited the weakest relationship between accumulated life
events and distress. Although their reported distress symptoms
were worse when event numbers were greater, their symptoms re-
mained well within the range of normal psychological functioning
even when event numbers were high.
4.2. Emotional intelligence and psychological resilience to life event
EI was negatively associated with events and distress. Most
persons with higher EI scores reported that fewer stressful events
Table 2
Latent class regression model fit statistics: negative life events regressed on distress.
Model LL BIC AIC NP Class. Error R
1-Class 1926.53 3871.14 3859.06 3 0 .21
2-Class 1873.62 3789.43 3761.24 7 .16 .71
3-Class 1855.97 3778.23 3733.94 11 .24 .80
4-Class 1844.22 3778.84 3718.44 15 .29 .92
Note. N= 414
LL, log-likelihood; AIC, akaike information criterion; NP, number of parameters;
Class. Error, Classification error.
Minimum BIC value.
Table 3
Latent class regression statistics for the best fitting 3-class model for negative life
events regressed on distress.
3-Class Model Wald
Class 1
Class 2
Class 3
.44 .26 .20
Distress intercept 15.05
(2.28) 37.40
(6.72) 6.01
(1.54) 24.40
Negative life
events B
(0.32) 4.59
(0.88) .90
(0.29) 26.18
Note.N= 414.
SE in parentheses.
p< 0.01.
p< 0.001.
Number of Negative Life Events
Class 1 (Average)
Class 2 (Vulnerable)
Class 3 (Resilient)
Fig. 1. Distress regressed on negative life events by latent class.
334 A.R. Armstrong et al. / Personality and Individual Differences 51 (2011) 331–336
continued to distress them. Importantly, individual differences in
four EI dimensions were found to distinguish between the Vulner-
able, Average and Resilient latent classes: Emotional Self-Aware-
ness, Emotional Expression, Emotional Self-Control and
particularly, Emotional Self-Management.
The small benefit of Emotional Self-Awareness in predicting
resilience is consistent with alexithymia research (e.g. Naatanen
et al., 1999), in which afflicted persons typically fail to detect stress
or deploy coping mechanisms until a stressor exerts its full impact.
The moderate benefit of Emotional Expression accords with re-
search in which overt expression has been shown to provide a
stress release (e.g., Wastell, 2002). The moderate benefits of Emo-
tional Self-Control concur with research linking this construct to
impulse control in times of stress (Salovey, 2001). The considerable
benefit of Emotional Self-Management is consistent with research
linking emotion regulation to positive mood maintenance
(Ciarrochi et al., 2000) and active rather than passive coping behav-
iours in times of stress (Salovey et al., 2002). Overall, the findings
support Salovey et al.’s (1999) theory that emotional self-aware-
ness, expression and self-management buffer the effects of aver-
sive events, and suggest that emotional self-control plays a role
as well.
It is notable that the two interpersonal EI dimensions, Emo-
tional Awareness of Others and Emotional Management of Others,
did not discriminate between more and less resilient persons in the
presence of the four intrapersonal dimensions. The current findings
suggest that when coping with multiple life events, the benefits of
intrapersonal EI outweigh the benefits of interpersonal EI.
4.2.1. Methodological and future considerations
Ours is the first study to find empirical support for the value of
EI as a psychological buffer in the context of multiple life events,
and to illustrate the relative importance of four intrapersonal EI
dimensions. The findings emphasise the value of examining the
relationship between aggregated life events and psychological
symptoms using latent class regression rather than traditional
regression techniques. Otherwise, the resilience of the majority is
likely to be blurred with the vulnerability of a sizable minority.
Furthermore, the importance of distinguishing between the
respective contributions of EI dimensions in the prediction of psy-
chological resilience, rather than treating EI as unitary construct, is
There were several study limitations. A self-selected rather than
representative sample was used. EI and distress levels were self-re-
ported rather than clinician-rated. The EI, life event, distress asso-
ciations may be an artifact of self-report mono-method bias
whereby mood congruent or dispositional response patterns may
be responsible for observed relations. A single point in time,
cross-sectional design was employed, limiting causal argument.
These are issues that future research may wish to address. Similar
future research would also benefit by identifying and controlling
for pre-event symptoms, and investigating the longitudinal stabil-
ity of latent class membership. Extending such research to samples
undergoing extremely stressful life transitions such as learning to
live with cancer or HIV, and to those who vary more widely in EI
traits, would further clarify the buffering effects of EI.
Bar-On, R. (1997). Emotional quotient inventory: Technical manual. Toronto: Multi-
Health Systems.
Benotsch, E. G., Christensen, A. J., & McKelvey, L. (1997). Hostility, social support,
and ambulatory cardiovascular activity. Journal of Behavioral Medicine, 20(2),
Bonanno, G. A. (2004). Loss, trauma, and human resilience. Have we underestimated
the human capacity to thrive after extremely aversive events? American
Psychologist, 59(1), 20–28.
Ciarrochi, J., Chan, A. Y. C., & Bajgar, J. (2001). Measuring emotional intelligence in
adolescents. Personality and Individual Differences, 31(7), 1105–1119.
Ciarrochi, J., Chan, A., & Caputi, J. (2000). A critical evaluation of the emotional
intelligence construct. Personality and Individual Differences, 28(3), 539–561.
Ciarrochi, J., & Deane, F. P. (2001). Emotional competence and willingness to seek
help from professional and nonprofessional sources. British Journal of Guidance
& Counselling, 29(2), 233–246.
Ciarrochi, J., Deane, F. P., & Anderson, S. (2002). Emotional intelligence moderates
the relationship between stress and mental health. Personality and Individual
Differences, 32(2), 197–209.
Ciarrochi, J., Forgas, J. P., & Mayer, J. D. (2001). Emotional intelligence in everyday life:
A scientific inquiry. New York: Psychology Press.
Day, A. L., Therrien, D. L., & Carroll, S. A. (2005). Predicting psychological health:
Assessing the incremental validity of emotional intelligence beyond
personality, type A behaviour, and daily hassles. European Journal of
Personality, 19(6), 519–536.
Extremera, N., & Fernandez-Berrocal, P. (2002). Relation of perceived emotional
intelligence and health-related quality of life of middle-aged women.
Psychological Reports, 91(1), 47–59.
Franz, M., Schaefer, R., & Schneider, C. (2003). Psychophysiological response
patterns of high and low alexithymics under mental and emotional load
conditions. Journal of Psychophysiology, 17(4), 203–213.
Gignac, G. (2005). Determining the dimensionality of a self-report emotional
intelligence inventory (SUEIT) and testing its unique factorial validity.
Unpublished doctoral dissertation, Swinburne University of Technology,
Gignac, G. (2010). Seven-factor model of emotional intelligence as measured by
Genos EI: A confirmatory factor analytic investigation based on self- and rater-
report data. European Journal of Psychological Assessment, 26(4), 309–316.
Hobson, C. J., Kamen, J., Szostek, J., Nethercut, C. M., Tiedmann, J. W., & Wojnarowicz,
S. (1998). Stressful life events: A revision and update of the Social Readjustment
Rating Scale. International Journal of Stress Management, 5(1), 1–23.
Holmes, T. H., & Rahe, R. H. (1967). The social readjustment rating scale. Journal of
Psychosomatic Research, 11, 213–218.
Kessler, R. C. (1997). The effects of stressful life events on depression. Annual Review
of Psychology, 48, 191–214.
Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the depression anxiety stress
scales. Sydney: The Psychology Foundation of Australia.
Magidson, J., & Vermunt, J. K. (2004). Latent class models. In D. Kaplan (Ed.), The sage
handbook of quantitative methods in the social sciences (pp. 175–198). Newbury
Park: Sage.
Martin, J. B., & Pihl, R. O. (1986). Influence of alexithymic characteristics on
physiological and subjective stress responses in normal individuals.
Psychotherapy and Psychosomatics, 45(2), 66–77.
Martins, A., Ramalho, N., & Morin, E. (2010). A comprehensive meta-analysis of the
relationship between emotional intelligence and health. Personality and
Individual Differences, 49(6), 554–564.
Matthews, G., Zeidner, M., & Roberts, R. D. (2002). Emotional intelligence: Science and
myth. Cambridge: MIT Press.
Mayer, J. D., Salovey, P., & Caruso, D. R. (2000). Emotional intelligence as zeitgeist, as
personality, and as a mental ability. In R. Bar-On & J. D. A. Parker (Eds.), The
handbook of emotional intelligence: Theory, development, assessment, and
application at home, school, and in the workplace (pp. 92–117). Jossey-Bass.
Table 4
Summary statistics and structure coefficients for emotional intelligence in the 3-class model.
Vulnerable Class (n= 120) Average Class (n= 184) Resilient Class (n= 110)
Emotional self-awareness 7.11 1.55 7.51 1.37 8.14 1.11
Emotional expression 14.20 4.08 16.07 3.74 17.35 3.56
Emotional awareness of others 63.38 9.58 63.41 8.41 65.37 6.87
Emotional self-control .75 3.02 11.64 2.75 13.49 .71
Emotional self-management 25.02 5.61 29.71 5.75 34.39 4.99
Emotional management of others 19.68 3.86 20.26 3.75 20.95 2.72
Note. N = 414.
A.R. Armstrong et al. / Personality and Individual Differences 51 (2011) 331–336 335
McClelland, G., & Judd, C. (1993). Statistical difficulties of detecting interactions and
moderator effects. Psychological Bulletin, 114(2), 376–390.
Mikolajczak, M., Luminet, O., & Mendil, C. (2006). Predicting resistance to stress:
Incremental validity of trait emotional intelligence over alexithymia and
optimism. Psicothema, 18, s79–88.
Mikolajczak, M., Mendil, C., & Luminet, O. (2007). Explaining the protective effect of
trait emotional intelligence regarding occupational stress: Exploration of
emotional labour processes. Journal of Research in Personality, 41(5), 1107–1117.
Mikolajczak, M., Petrides, K. V., Coumans, N., & Luminet, O. (2009). The moderating
effect of trait emotional intelligence on mood deterioration following
laboratory-induced stress. International Journal of Clinical and Health
Psychology, 9(3), 455–477.
Monroe, S. M., & Simons, A. D. (1991). Diathesis-stress theories in the context of life
stress research: Implications for the depressive disorders. Psychological Bulletin,
110(3), 406–425.
Naatanen, P., Ryynanen, A., & Keltikangas-Jarvinen, L. (1999). The influence of
alexithymic characteristics on the self-perception and facial expression of a
physiological stress state. Psychotherapy and Psychosomatics, 68(5), 252–262.
Palmer, B. R., & Stough, C. (2002). The development of the Swinburne University
Emotional Intelligence Test. Paper presented in July 2002 at the Third Conference
on Emotions and Organisational Life, Gold Coast, QLD.
Palmer, B. R., Stough, C., Harmer, R., & Gignac, G. E. (2009). Genos emotional
intelligence inventory. In C. Stough, D. Saklofske, & J. Parker (Eds.), Assessing
emotional intelligence: Theory, research, & applications (pp. 103–118). New York:
Petrides, K. V., Pita, N., & Kokinnaki, F. (2007). The location of emotional intelligence
in personality factor space. British Journal of Psychology, 98, 273–289.
Roger, D., & Najarian, B. (1989). The construction and validation of a new scale for
measuring emotion control. Personality and Individual Differences, 10(8),
845–853. Sociology, 66, 32–0.
Salovey, P. (2001). Applied emotional intelligence. Regulating emotions to become
healthy, wealthy, and wise. In J. Ciarrochi, J. P. Forgas, & J. D. Mayer (Eds.),
Emotional intelligence in everyday life: A scientific inquiry (pp. 168–184). New
York: Psychology Press.
Salovey, P., Bedell, B., Detweiler, J. B., & Mayer, J. D. (1999). Coping intelligently:
Emotional intelligence and the coping process. In C. R. Snyder (Ed.), Coping: The
psychology of what works (pp. 141–164). New York: Oxford University press.
Salovey, P., Stroud, L. R., Woolery, A., & Epel, E. S. (2002). Perceived emotional
intelligence, stress reactivity, and symptom reports: Further explorations using
the trait meta-mood scale. Psychology & Health, 17(5), 611–627.
Scully, J. A., Tosi, H., & Banning, K. (2000). Life event checklists: Revisiting the social
readjustment rating scale after 30 years. Educational and Psychological
Measurement, 60(6), 864–876.
Soenens, B., Duriez, B., Vansteenkiste, M., & Goossens, L. (2007). The
intergenerational transmission of empathy-related responding in adolescence.
The role of maternal support. Personality and Social Psychology Bulletin, 33,
Stueve, A., Dohrenwend, B. P., & Skodol, A. E. (1998). Relationships between stressful
life events and episodes of major depression and nonaffective psychotic
disorders: Selected results from a New York risk factor study. In B. P.
Dohrenwend (Ed.), Adversity, stress, and psychopathology (pp. 341–357). New
York: Oxford University Press.
Vermunt, J., & Magidson, J. (2000). Latent GOLD user’s manual. Boston: Statistical
Innovations Inc.
Wastell, C. A. (2002). Exposure to trauma: the long-term effects of
suppressing emotional reactions. Journal of Nervous and Mental Disease,
190(12), 839–845.
336 A.R. Armstrong et al. / Personality and Individual Differences 51 (2011) 331–336
... Furthermore, there are some reasons to consider a mediational approach to examine the impact of EI on positive outcomes through resilient coping among the unemployed (Chan, 2006;Peláez-Fernández et al., 2021). First, EI has been reported to be linked to adaptive resilient coping (Armstrong et al., 2011;Jayalakshmi & Magdalin, 2015). Second, resilient strategies have shown to be negatively correlated to negative indicators of mental health and positively linked to positive indicators of mental health (Hu et al., 2015). ...
... Also, unemployed reporting higher levels of EI and resilient coping showed less depressive symptomatology and higher subjective happiness. Similarly, these findings are supported by prior research reporting that EI levels and resilient coping are linked positively with well-being and negatively with a range of psychological maladjustment outcomes (Armstrong et al., 2011;Peláez-Fernández et al., 2019. In sum, these findings support the first hypothesis (H1) and shed light on both the linkage between EI and coping strategies variables and its associated correlates of well-being among unemployed adults. ...
... Likewise, unemployed people who report more resilient coping strategies might cope more effectively with adverse and negative symptoms associated with the stressful experience of unemployment. Previous research is also in line with our results, indicating that EI and resilient coping generally protect people from the adverse effects of unemployment (Armstrong et al., 2011;Moorhouse & Caltabiano, 2007;Peláez-Fernández et al., 2021). In regard to happiness, the results also showed an indirect mediation effect on resilient coping in the link between EI and subjective happiness levels. ...
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The scientific literature has shown interest in identifying psychological strengths that predict mental health and job search behaviors in the unemployed population. Emotional intelligence (EI) and resilience are key psychological resources, although there is a lack of understanding of underlying mechanisms involved during unemployment. In this study we aimed to examine whether resilient coping serves as a mediator between EI and depressive symptoms, happiness, and job search behaviors in unemployed. To prove whether resilient coping mediates this link, we recruited 401 unemployed through LinkedIn and asked them to complete self-report questionnaires. Correlational results showed significant relationships in the expected way. The results of the mediation analyses showed that resilient coping mediated the link between EI and job search behaviors, happiness, and depressive symptoms. The findings suggest that career counseling units should incorporate EI and resilience modules into their employability programs to promote the mental health and employability of the unemployed.
... Of the factors that make up this construct, it has been shown that emotional intelligence and resilience have a positive relationship, more significant in terms of the emotional repair factor. 62 Similarly, studies such as those of [63][64][65] confirmed that students who show good emotional control, present higher levels of resilience and therefore, they tend to deal effectively with the difficulties and stress situations that arise in the academic context. Along the same lines, 66,67 demonstrated that emotional intelligence facilitates resilience in difficult situations. ...
... 68 Emotional intelligence needs to be promoted to reduce the consequences of stressful and adverse situations and increase resilience in adolescents. 62,63 In turn, the fourth hypothesis was confirmed in two of the three variables analyzed. Specifically, sex-related differences were found in resilience and emotional intelligence among adolescents. ...
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Introduction: Resilience and academic engagement have become some of the most important elements in the academic context, due to their relationships with school adjustment, the protective role against risky behaviors and the well-being of adolescents. Purpose: Therefore, the objective of this study was to analyze the relationships established between the variables of resilience and academic engagement, the differences according to sex, as well as to determine the mediating role of emotional intelligence in the relationship between resilience and academic engagement in adolescence. Participants and methods: A cross-sectional descriptive study was performed. The sample consisted of 802 secondary school students, with an average age of 13.65 years (SD = 1.24) (where 50.6% were women and 49.4% men) who filled out the Connor-Davidson Resilience Scale (CD-RISC 10), the General Academic Engagement Scale for Spanish Adolescents (CAADE) and the Spanish version of the Wong Law Emotional Intelligence Scale (WLEIS-S). Results: The results showed the existence of positive relationships between resilience and factors of academic engagement. Furthermore, the mediation models showed the direct effect of emotional intelligence on this relationship. On the other hand, with respect to sex, men showed significantly higher averages in resilience and emotional intelligence, with no significant differences in the variable of academic engagement. Conclusion: Concluding, design of emotional intelligence intervention programs in secondary is recommended as an effective measure for promoting resilience and a positive academic trajectory.
... Indeed, the skills associated with EI, such as managing and understanding emotions, can help people cope successfully (Salovey et al. 1999). For example, self-reported EI has been shown to predict decreased stress responses to life stressors (Armstrong et al. 2011) and EI is measured as an ability correlated with a be er response to a laboratory stressor (Schneider et al. 2013). However, the link between EI and resilience does not seem to be as strong as to suggest that they might be the same ability. ...
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Resilience is often characterized as the outcome of well-being maintenance despite threats to that well-being. We suggest that resilience can also be characterized as an emotional-intelligence-related ability to obtain this outcome. We formulate an allostatic active inference model that outlines the primary tools of this resilience ability as monitoring well-being, maintaining stable well-being beliefs while updating situational beliefs and flexibly prioritizing actions that are expected to lead to well-being maintenance or gathering the information needed to discern what those actions could be. This model helps to explain the role of positive emotions in resilience as well as how people high in resilience ability use regulatory flexibility in the service of maintaining well-being and provides a starting point for assessing resilience as an ability.
... From the analysis, it can be deduced that while the role of emotional intelligence and positive thinking in relation to resilience have, even recently, been widely investigated (Armstrong et al., 2011;Cejudo et al., 2016;Belykh, 2019;Chen, 2019;Trigueros et al., 2019;Thomas and Zolkoski, 2020;Zhao et al., 2020;Cerit and Ş imşek, 2021;Cuartero and Tur, 2021;Rezaei et al., 2021;Sk and Halder, 2021;Zheng et al., 2021), to our knowledge, there are few studies that directly link planfulnessa process-focused trait of individual differences in goal achievementwith resilience. Specifically, no previous studies have been conducted on these three traits as constituents of individual resilience and their effects on academic achievements. ...
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Purpose Frequently the universities' Placement Service is based on the student's hard profile at the expense of soft traits. On the other side, the “person–organization fit” axiom suggests firms are looking for profiles with specific soft skills to face the increasing level of environmental turbulence. This research aims to understand if high-resilience students also have high academic achievements and how the three components of resilience (emotional intelligence, positive thinking, planfulness) can have different impact on individual performances. Design/methodology/approach The research was conducted on students enrolled on different courses of studies and years in an Economics and Law faculty. A questionnaire was administered during the first exam session (ante-Covid) and the second and third exam sessions (post-Covid). This questionnaire consists of 84 questions related to planfulness, emotional intelligence and positive thinking, whose combination can be considered a measure of resilience. In fact, the Principal Component Analysis (PCA) was carried to identify these three new variables (the components) based on the 84 initial ones. Finally, an ordered logit model was implemented to verify whether, and in what direction, planfulness, emotional intelligence, positive thinking and Covid 19 (the independent variables) affected the students' performance (the dependent one). Findings While planfulness positively affected academic performance, emotional intelligence affected it negatively. The impact of positive thinking and Covid was not significant, and thus what emerged from the preliminary analysis of the grades is not confirmed. Research limitations/implications This is a case study of a university experience that is paying great care in preparing students to satisfy the firms' work demands. To confirm and refine results the sample will be expanded to other faculties and other life/soft skills will be investigated. Practical implications This soft trait approach—that studies how various measures of soft skills are related to course grades—has a two-fold significance by crafting universities' placement activities and facilitating firms' onboarding. Social implications This is a case study of a university experience; a university that is paying great attention to preparing students ready to satisfy the firms' work demands but also citizens capable of supporting the growth of their nation and society in general. Originality/value The research can be considered a first step towards the inclusion of the formal evaluation of the students' life skills in their academic path, creating a link with their achievements.
... Resilience has been defined as the interaction of risk and protective variables, more precisely as a process that arises from personal response to environmental risk factors 12 or vulnerabilities. It can be said that resilient members are better at 13 facing and excelling from failure than others. According to some researchers, EI has been connected directly to resilience and it is good for human's such adapting is related with emotional 5 intelligence. ...
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... Negative life events refer to change events that cause negative outcomes and adaptational challenges in people's lives (Armstrong et al., 2011). They are viewed as specific types of stressors because stressors that appear in the form of disruptive life events cause stress and affect people's psychological status (Pearlin et al., 1981). ...
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The mechanism regarding how and for whom exposure to negative life events predicts adolescent internet gaming disorder (IGD) over time remains unknown. Using a prospective design, this study examined a moderated mediation model between negative life events and subsequent IGD, with maladaptive cognition toward internet gaming as a mediator and neuroticism as a moderator. A sample of 848 junior high school students in China (50.0% males, Mage = 13.49 years, SDage = 0.99) were asked to complete questionnaires including items on negative life events, maladaptive cognition toward internet gaming, IGD, and Big Five personality traits. After controlling for gender, age, and other personality traits, our results showed that maladaptive cognition (T1) partially mediated the relationship between negative life events and IGD (T2). Neuroticism (T1) moderated the direct and indirect association between negative life events and IGD (T2) via maladaptive cognition (T1), which did not support the diathesis-stress hypothesis or the social push hypothesis. In particular, the link between negative life events and IGD (T2) was stronger for adolescents with low neuroticism than for those with high neuroticism. Furthermore, the indirect effect of negative life events on IGD (T2) through maladaptive cognition (T1) was stronger for adolescents with high neuroticism (T1) than for adolescents with low neuroticism (T1).
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The major goal of green technology is to lessen the greenhouse effect and control global warming. Hence, the main idea is to come up with new inventions that do not deplete natural resources. The research, here, is attempted to examine the factors influencing consumers to purchase hybrid cars like environmentally friendlier automobiles that are gaining more popularity. Hybrid car is a vehicle that uses at least two or more power supply as to make the vehicle move. The combination of an internal combustion engine and electric motors is one of the uniqueness owned by hybrid cars. This study discusses various theoretical models and proposes a conceptual model based on those theories, especially on UTAUT2 (Extended Unified Theory of Acceptance and Use of Technology) which adapted and identified seven independent variables (performance expectancy, social influence, environmental concern, price value, hedonic motivation, facilitating conditions, and health benefit) and one dependent variable (behavioral intention to purchase) from the related literatures. Though there is huge importance or advantages of hybrid cars, there have been many people in Bangladesh till now who are not currently buying/using hybrid cars. This study is significant and rationale in environmental, marketers, and economic perspective. The expected outcome of this study will enhance new understanding on the profile of Bangladeshi consumers in purchasing hybrid cars as well as marketers, and policymakers can take opportunity to take decisions by utilizing the findings of this study.KeywordsHybrid carUTAUT2Conceptual modelBangladesh
University students are exposed to several changes related to their families and economic independence. The academic demands impose greater responsibilities and difficulties (Trigueros et al, The influence of emotional intelligence on resilience, test anxiety, academic stress and the Mediterranean diet. A study with university students. Environ Res Public Health 17(6):2071, 2020 [1]), a reality that worsened as a result of the pandemic between 2020 and 2021 due to the loss of social contact, economic problems, and the search for sources of income to help with family expenses, generating in students the need to abandon or postpone their studies; however, it has been possible to identify factors related to their emotional intelligence and resilience, which have allowed them to successfully cope with these difficulties. This study aims to analyze the validity and reliability of the Trait Meta-Mood Scale (TMMS-24) by combining an exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) model. The influence of emotional intelligence of Ecuadorian university students on resilience and academic performance in the context of SARS-COV-2 is analyzed using structural equation modeling (SEM) in a sample of 302 Ecuadorian university students aged 18–24 years following the impact of the COVID-19 pandemic. The EFA and CFA validated the TMSS-24 with acceptable fit indices, demonstrating construct validity. Through SEM modeling, resilience was found to have a significant and positive mediating role between emotional intelligence and academic performance.KeywordsResilienceEmotional intelligenceRSATMSS-24University students
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We examined the relationship between perceived emotional intelligence (PEI), measured by the Trait Meta-Mood Scale (TMMS), and psychophysiological measures of adaptive coping. The TMMS assesses perceived ability to (a) attend to moods (Attention), (b) discriminate clearly among moods (Clarity), and (c) regulate moods (Repair). Study 1 showed significant positive associations between PEI and psychological and interpersonal functioning. In Study 2, skill at mood Repair was associated with less passive coping and perceptions of repeated laboratory stressors as less threatening; Clarity was related to greater increases in negative mood, but lower cortisol release during repeated stress. In Study 3, Repair was associated with active coping and lower levels of rumination; Attention was associated with lowered cortisol and blood pressure responses to acute laboratory challenges. These findings suggest that psychophysiological responses to stress may be one potential mechanism underlying the relationship between emotional functioning and health.
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Despite criticism, the Social Readjustment Rating Scale (SRRS) is one of the most widely cited measurement instruments in the stress literature. This research assesses several criticisms of the SRRS after years of widespread use. Specifically, the authors evaluate content-related criticisms, including differential prediction of desirable relative to undesirable life events, controllable relative to uncontrollable life events, and contaminated relative to uncontaminated life event items. On balance, the authors find that the SRRS is a useful tool for stress researchers and practitioners.
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In this investigation, a series of progressively more complex factor models was tested based on self-report and rater-report data derived from the workplace version of the Genos Emotional Intelligence Inventory (Genos EI). Based on a total sample of 4775 individual self-reports and 6848 rater-reports, a theoretically derived higher-order 7-factor model of emotional intelligence (EI) was found to be adequately well-fitting, in comparison to a competing global EI single-factor model and a five-factor model of EI. Internal consistency reliabilities associated with the total scale scores were approximately .95 and the subscale score reliabilities were approximately .80. The results are interpreted as largely supportive of a 7-factor model of EI as measured by Genos EI in both self- and rater-report formats.
Background: In spite of the connection of alexithymic characteristics to many stress-related disorders, little is known about the effects of these characteristics on the self-perception of stress, which may have functional value in the regulation of daily behavior. The present study assessed the influence of alexithymic characteristics on the self-perception of stress in relation to the corresponding physiological/expressive responses during and while recovering from a phasic stressor. Methods: A median split of the scores on the Toronto Alexithymia Scale was used to divide 32 healthy middle-aged men into two groups, a high alexithymia (HA) and a low alexithymia (LA) group. Both groups participated in a 3-min hand-grip task, followed by a 3-min recovery period. During these periods, subjects’ heart rate (HR) and facial electromyographical (EMG) activity on the corrugator supercilii and frontalis lateralis areas were measured and perceptions of exertion, unpleasantness and tension were self-rated. The perceptual style was assessed with the discrepancy scores: standardized scores of the physiological measures were subtracted from the corresponding standardized scores of the perceptions. Thus, positive scores indicated that self-reported perceptions exceeded the corresponding physiological or expressive activity (overestimation) and negative scores indicated the opposite (underestimation). Results: The HA group decreasingly underestimated exertion in relation to HR during the task and increasingly overestimated it during the recovery period. The HA group also overestimated unpleasantness in relation to the corrugator EMG response during the recovery period. Conclusions: High alexithymic characteristics seem to predispose to the delayed self-perception of physiological stress state so that the beginning of this state may remain subjectively unnoticed and the subjective recovery from it prolonged relative to the physical recovery. During this prolonged subjective recovery the feelings of unpleasantness are not facially expressed. The consequences of this style for health-related behavior are discussed.