Citation: Nicolas, M.; Gaudino, M.;
Bagneux, V.; Millet, G.; Laborde, S.;
Martinent, G. Emotional Intelligence
in Ultra-Marathon Runners:
Implications for Recovery Strategy
and Stress Responses during an
Ultra-Endurance Race. Int. J. Environ.
Res. Public Health 2022, 19, 9290.
https://doi.org/10.3390/
ijerph19159290
Academic Editors: Javier
Abián-Vicén and Britton W. Brewer
Received: 24 May 2022
Accepted: 26 July 2022
Published: 29 July 2022
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International  Journal  of
Environmental Research
and Public Health
Article
Emotional Intelligence in Ultra-Marathon Runners:
Implications for Recovery Strategy and Stress Responses during
an Ultra-Endurance Race
Michel Nicolas 1,*
, Marvin Gaudino 1
, Virginie Bagneux 2, Gregoire Millet 3
, Sylvain Laborde 4
and Guillaume Martinent 5
1
Laboratory Psy-DREPI (EA 7458), University of Bourgogne Franche-Comté, 21000 Dijon, France;
marvin.gaudino@u-bourgogne.fr
2
LPCN, Université de Caen Normandie, 14032 Caen, France; virginie.bagneux@unicaen.fr
3
SSUL, Institute of Sport Sciences, Faculty of Biology and Medicine, University of Lausanne,
CH-1011 Lausanne, Switzerland; gregoire.millet@unil.ch
4
Department of Performance Psychology, Institute of Psychology, German Sport University Cologne,
50923 Cologne, Germany; s.laborde@dshs-koeln.de
5
Laboratory on Vulnerabilities and Innovation in Sport, University of Lyon 1, 69367 Lyon, France;
guillaume.martinent@univ-lyon1.fr
*
Correspondence: michel.nicolas@u-bourgogne.fr
Abstract: The aim of this research was to investigate the role of trait emotional intelligence (EI) in
recovery stress states in a mountain ultra-marathon (MUM) race. Recovery stress states of 13 ﬁnishers
were assessed before, during, and immediately after the end of an extreme MUM, whereas emotional
intelligence was assessed 2 days before the MUM race. Temporal evolutions of recovery stress
states were examined. Stress states increased after the race whereas recovery states decreased in all
participants. In addition, recovery states were inﬂuenced by the trait EI level assessed before the
competition. Results supported the hypothesis that trait EI tends to have a positive effect by boosting
recovery strategies. In this perspective, trait EI could have a protective role against stress and improve
pre-competition mental preparation. High scores of trait EI (in comparison to low scores of trait
EI) could have helped athletes to increase recovery states in order to improve their psychological
adaptation to one of the most difﬁcult races in the world.
Keywords: emotional intelligence; recovery stress states; mountain ultra-marathon
1. Introduction
Extreme sports situations demand multidimensional psychological adaptive responses
which could depend on recovery stress states [1], as well as individual factors such as
emotional intelligence [2]. Biopsychological perspective of recovery and stress [3], em-
braces physical and biopsychosocial dimensions of both stress and recovery to indicate
the extent to which someone is physically and/or mentally stressed, as well as whether
that person is capable of using individual strategies for recovery and which strategies are
used. EI refers to a form of intelligence which aims to capture individual differences in
interpersonal and intrapersonal emotional functioning [4–6]. Its potential contribution
in sporting competitions has been demonstrated and is considered to be a key factor in
improving individual adaptation, notably with regard to the stress process [2]. During the
last few decades, the recovery process has been associated with stress states to explain how
athletes may be better able to tolerate and buffer stress from training and competition [7].
Whereas the relationship between stress and EI has been largely documented, no study has
investigated the relationship between EI and recovery. The aim of this paper is to evaluate
the involvement of EI in recovery stress states.
Int. J. Environ. Res. Public Health 2022, 19, 9290. https://doi.org/10.3390/ijerph19159290
https://www.mdpi.com/journal/ijerph
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Extreme situations are demanding and challenging. They impose on an individual
the need to cope with exceptional physical or psychosocial circumstances that require
adaptive responses that engage personal resources which could be overwhelmed [8]. A
mountain ultra-marathon (MUM) race could be considered one of the most extreme sport-
ing situations after polar expeditions [9] because it implies a complex and multidimensional
adaptation deﬁned by the dynamic impact between environmental and personal constraints
and resources (i.e., physical, psychological, and social) on adjustment [8,10]. During a
MUM, athletes are exposed to a variety of stressors and have to run for extended periods
over long distances and dangerous terrain with changing altitudes in an uncertain and
risky environment [11]. Exposure to these stressful environmental and climatic conditions
tends to push participants to draw on their own resources in order to perform beyond their
ordinary limits [12]. MUM is by deﬁnition a playing ﬁeld for in situ ecological research
investigating psychological impairments that are mirrored in multidimensional psycho-
logical processes, such as emotional disturbances [13] and increases/decreases in recovery
stress states [14]. These impairments were also observed during the month following
the competition, highlighting that ultra-endurance sports are challenging situations with
long-term repercussions [14,15].
According to Lazarus and Folkman, the seminal model of psychological stress (1984),
extreme situations can exacerbate stress states [8]. Beyond a certain point, any effort to
manage an excessive stress state could engage personal resources and in turn cause their
potential consumption if the recovery process is not implemented [16]. However, a certain
level of perceived stress is an integral part of psychological adaptation [17]. The objective
is no longer to annihilate stress but to attempt to reach a balance between stress state and
personal resources. The recovery process actually represents a core concept in investigating
how to deal with and buffer the stress state because it helps to protect, build, reﬁll or restore
personal resources [7,18]. Recovery is deﬁned as a multilevel process used to tolerate
stress and to re-establish performance abilities and psychological and physical strength
in order to optimize situational conditions [7]. Thus, recovery is based on proactive and
self-initiated activities [18–20].
In the last decade, there has been an increased interest in the investigation of the
interrelated dynamics of recovery stress states in order to better understand the psycho-
logical adaptations in extreme situations. The theoretical model of the recovery stress
process [3,19] leads to a joint measurement of the extent to which an individual is fre-
quently and multidimensionally stressed (social, emotional, physical, and behavioral) and
its recovery-associated activities/states. The objective is to reach an individual biopsychoso-
cial balance in order to counterbalance the negative effects of stress, help to adjust to the
situation, and to achieve a continuous high-level performance [3]. Results from individuals’
exposure to spatial simulations [21], polar stations, i.e., wintering in Antarctica [22], and
extreme sports [14] have provided strong evidence of the importance of considering the
recovery stress process. Unbalanced recovery stress states (i.e., increased stress states and
decreased recovery states) can lead to dysfunctional outcomes such as chronic fatigue and
concomitant overtraining, and psychological exhaustion [1,20]. Consequently, the participant’s
adaptation to sports training and competition is compromised [1,19]. Results of previous
studies on ultra-endurance races showed that participants have simultaneously reported an
increase in stress states and a decrease in recovery states mirrored, notably, in the emotional
exhaustion dimension [14,15]. The repercussions could be observed up to four weeks after the
race, highlighting the long-term impact of a stressful event on the recovery stress states [15]. In
particular, evolutions in the recovery stress states experienced by MUM runners in the month
following a demanding MUM race have been characterized by a significant linear increase in
recovery and a linear decrease in stress states [15]. Results show that the harder the situation
is, the longer the need to evaluate and manage recovery stress states.
However, even in extreme environments, recovery stress states are not always unbal-
anced [22,23], suggesting that personal resources could be sustained. Results from previous
research showed that recovery stress states could be modulated according to individual
Int. J. Environ. Res. Public Health 2022, 19, 9290
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difference factors such as perceived stress and perceived control [19,22,24]. Speciﬁcally,
these studies have shown that perceived stress was positively linked to psychological,
physiological, and social stress responses whereas perceived control was positively linked
to recovery strategies [19,22,24]. These results provided supporting evidence that indi-
vidual cognitive resources were involved in managing the stress process [10,17]. These
results corroborate the cognitive–motivational–relational theory [10] and emphasize that
the interaction between the person and the environment is mediated by the degree to
which a situation is appraised as stressful and controllable. These ﬁndings suggest that
individual differences could help explain the differences in psychological responses within
a challenging situation [25].
Among individual variables identiﬁed as factors inﬂuencing stress management,
EI could determine an athlete’s ability to handle psychological stress and also facilitate
physical and psychological recovery [26]. The theoretical nature of EI-related constructs
remains assigned to a wide array of concepts and models [27]. EI provides an interesting
framework for assessing individual differences with regard to how individuals identify,
express, understand, regulate and use their own and others’ emotions to ultimately guide
their thinking and actions [4,5]. Among the several theoretical frameworks focusing on
EI [5,28–30], the present study was grounded within the trait model of EI [29,30] based on
the rationale that EI was conceptualized in the present study as an individual difference
variable. The trait model [29] deﬁnes EI as a lower-order personality trait that is mainly
evaluated using a self-report measure [30].
A systematic review [2] concluded that EI had a protective role with regard to the
stress process in athletes. For example, EI was found to be associated with the use of more
efﬁcient coping strategies (i.e., task-oriented coping) to manage stress [31]. Furthermore,
Laborde, Dosseville, Guillén, and Chavez [32] indicated that EI positively predicted per-
ceived control, coping (e.g., task-oriented coping strategies, coping effectiveness), and
performance satisfaction. In addition, numerous studies support the idea that EI is a key
factor in improving individual adaptation [33,34]. Individuals with high EI would be
more competent in coping with challenges and would perceive less stress [35] and more
well-being [36]. EI may help to explain how stress is physiologically better tolerated and
buffered by certain individuals [37]. Previous research within the context of MUM race also
supported the notion that EI is positively associated with pleasant emotional states [38]. The
connection between EI and pleasant emotions could be crucial to depicting the relationship
between EI and the recovery process. In her broaden-and-build theory, Fredrickson [39]
posited that experiences of pleasant emotions broaden people’s momentary thought–action
repertoires in a way that serves to build their enduring personal resources and subsequent
emotional well-being. Several empirical studies provide evidence supporting this theoreti-
cal approach [40] including studies in sports settings e.g., [41]. Consequently, EI could be
expected to play a major role in boosting recovery processes and helping to protect, build,
reﬁll or restore personal resources when individuals have faced stressful situations.
Based on previous studies in extreme situations, the interplay between recovery
and stress states has been shown to play a major role in the psychological adaptation
processes. However, some gaps remain in the research. Speciﬁcally, the role of trait EI in
the recovery process has not yet been investigated whereas promising theoretical support
exists for the link between EI and recovery [39]. Consequently, the present study aims to
provide experimental evidence regarding the psychological adaptation in MUM runners by
investigating the recovery stress process and the relationship between recovery stress states
and trait EI, especially before, during, and after one of the most extreme MUM races. This
study could provide insights on how stress states could be tolerated and/or buffered in
MUM in regard to recovery strategies [7]. Considering previous results on recovery stress
states in ultra-marathons [14,15], it was hypothesized that (1) stress states would increase
during and after the race compared to pre-race, whereas (2) recovery would decrease in the
same time evolution. Furthermore, based on previous research on EI [2], we hypothesized
Int. J. Environ. Res. Public Health 2022, 19, 9290
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that: (3) athletes with low trait EI would report lesser recovery and higher stress states
during the MUM race than athletes with a high trait EI.
2. Methods
2.1. Participants
Thirteen athletes running an extreme MUM event (2 women and 11 men), aged from
29 to 52 years old (Mage = 40.08 yrs, SDage = 6.76), voluntarily participated in this study.
Initially, 17 participants were recruited through an announcement for this study, which
was part of a larger research project that focused on the physiological consequences of
this race, which is considered to be the most challenging mountain ultra-marathon in
the world. Of the 17 participants initially enrolled in the study, 13 completed the race
(inclusion criterion) and thus constituted our sample for this study. The MUM was the
Tor des Géants® (TdG) and consisted of a semi-self-sufﬁciency race where the runners
covered a total of 338 km with a cumulated altitude of 30,959 m of positive elevation
under changing climate conditions (temperatures between −9 and 15 ◦C). For the rest,
rescue, and refreshment points, runners were able to rely on the seven base camps spaced
approximately 50 km apart. On average, participants accomplished the race in 132.67 h
(SD = 13.16). All participants signed a consent form stipulating their right to withdraw
from the experiment at any time without prejudice. This study was approved by the local
ethics committee in accordance with the Declaration of Helsinki (amended 2013).
2.2. Measures
2.2.1. Brief Emotional Intelligence Scale (BEIS-10)
The BEIS-10 [42] is based on both the EI model of Salovey and Mayer [6] and the work
of Lane et al. [43]. The BEIS-10 was administered to athletes to measure their trait EI using
a 6-point Likert scale (1 = never to 6 = always). The 10-item version is a short and efﬁcient
measure to quickly assess an individual’s perception of the extent to which they appraise,
regulate, and use emotions. For this study, the internal consistency of the BEIS-10 was 0.84.
2.2.2. Recovery Stress States (RestQ-36-R-Sport)
Based on the original Rest-Q for athletes [7], the French version of the RestQ-36-R-
Sport questionnaire [18] was used to quickly assess the multidimensional nature (physical,
emotional, behavioral, and social) of recovery and stress states. This questionnaire was
developed to quickly measure the frequency of current stress along with the frequency of
recovery using a 6-point Likert scale (1 = never to 6 = always). Higher scores in the stress
responses reflected an intense and elevated perceived stress state. Higher scores in the
recovery strategies reflected a high frequency of using numerous recovery strategies. Pre-
TdG instructions given to participants for the completion of the RestQ-36-R-sport referred to
«the 3 last days» whereas Per- and Post-TdG instructions referred to «the 3 last hours» in order
to evaluate the psychological states during the MUM. The internal consistency for total stress
and recovery scores across the several measurement times ranged from 0.53 to 0.98. Cronbach
alpha tends to increase with an increase in the number of participants [44], leading researchers
to suggest a cut-off value of 0.60 for a low sample size [45]. Other researchers prefer the use of
the raw average inter-item correlation (AIIC) as a statistical marker of internal consistency.
For this, a rule of thumb is offered by Clark and Watson [44] who recommend AIIC scores
higher than 0.15. In the present study, all the AIIC scores were higher than 0.15.
2.3. Procedure
The thirteen participants rated their recovery stress states and trait EI on self-report
questionnaires in the 3 h before the race (Pre-MUM). Secondly, while the majority of research
on emotion, EI, or recovery stress states conducted in ultra-endurance sports has focused
on the differences pre- and post-race e.g., [13–15], participants in the present investigation
also rated their recovery stress states during the race. This measure was completed at the
Donnas camp (located at the mid-race point: Per-MUM) after athletes had run 155 km with an
Int. J. Environ. Res. Public Health 2022, 19, 9290
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average running time of 51 h (SD = 3.41). Thirdly, the athletes completed the RestQ-36-R-sport
questionnaire for the last time during the three-hour period after finishing the race.
2.4. Statistical Analysis
Shapiro–Wilk and Levene’s tests were used to verify data normality and the homo-
geneity of variances at each time point. Trait EI data were analyzed: (a) using correlational
analysis with recovery stress states scores on the total sample; and (b) by dividing its scores
into either a high or low group based on the median value, a common practice within
the literature [46–48]. While dichotomization is sometimes criticized in the literature [49],
recent re-evaluations have shown that this practice is a robust, reliable, and appropriate
statistical analysis when independent variables are uncorrelated [46–48]. A median split
was therefore used to dichotomize participants based on their scores of trait EI. The re-
sults from our sample showed that the low trait EI scores and high trait EI scores were
uncorrelated (p = 0.07) and provided evidence supporting the use of a median split in the
present study. Literature has also shown that conducting a median split does not increase
the likelihood of a Type I error [47]. Additionally, given that the scores for all factors at the
different time measures were normally and homogeneously distributed, we conducted a
set of multivariate analyses of variance (MANOVA) with repeated measures to test: (1) The
effect of time on recovery stress states; (2) the effect of trait EI groups (high EI vs. low
EI); and (3) the effect of the interaction of trait EI-groups * time. Follow-up univariate
one-way ANOVAs were conducted in order to target signiﬁcant differences detected using
MANOVA. Pairwise comparisons (post hoc) were conducted using Tukey’s HSD.
3. Results
3.1. Descriptive Analyses
Descriptive statistics for recovery stress states and trait EI are shown in Table 1. Results
of correlational analysis for the total sample showed that recovery was negatively correlated
with stress state (r = −0.59, p < 0.05) whereas trait EI was not signiﬁcantly correlated with
stress state and recovery state.
Table 1. Descriptive statistics and inter-correlations for recovery stress states and EI scores in high
trait EI (n = 6) and low trait EI (n = 7).
Recovery
Stress
Emotional Intelligence
Total sample
Recovery
-
Stress
−0.59 *
-
Emotional Intelligence
0.41
−0.25
-
M
3.57
2.70
44.31
SD
0.47
0.30
6.79
High trait EI group
Recovery
-
Stress
−0.91 *
-
Emotional Intelligence
0.79
−0.90 *
-
M
4.26
2.61
49.96
SD
0.17
0.14
3.03
Low trait EI group
Recovery
-
Stress
−0.56
-
Emotional Intelligence
0.18
0.14
-
M
3.37
2.85
39.57
SD
0.16
0.13
5.86
Note. * p < 0.05.
Based on the median value (Me = 45), a signiﬁcant difference between the high trait
EI and low trait EI groups was observed in this study, t(11) = 4.53, p = 0.008, d = 2.23. The
Int. J. Environ. Res. Public Health 2022, 19, 9290
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high EI-level group contained 6 athletes (Mage = 50.12; SD = 2.71) while the low EI group
contained 7 athletes (Mage = 39.19; SD = 5.35). High trait EI and low trait EI mean scores
were not signiﬁcantly correlated (p > 0.05), encouraging the use of a median split. For
the high trait EI group, correlations revealed that recovery was negatively correlated with
stress state (r = −0.91, p < 0.05) and stress state was negatively correlated with EI (r = −0.90,
p < 0.05). For the low trait EI group, no signiﬁcant correlation was found.
3.2. Stress State
Figure 1 presents changes in stress scores during the TdG®. Firstly, the effect of the EI
group on stress state was not significant, F(1, 11) = 0.74, p = 0.408 (M low EI = 2.77, SD = 0.13;
M high EI = 2.62, SD = 0.14). Secondly, stress state scores changed over time, F(2, 22) = 5.19,
p = 0.014, ηp2 = 0.28. Tukey post hoc tests revealed significant increases, specifically between
pre-MUM (M = 2.57, SD = 0.11) and post-MUM (M = 2.88, SD = 0.12, p = 0.017, d = 3.04) and
between per-MUM (M = 2.62, SD = 0.11) and post-MUM (p = 0.043, d = 2.35). Thirdly, no
significant interaction was observed, showing that stress scores were not influenced by the
athletes’ EI levels throughout the race, Wilk’s λ = 0.97, F(2, 22) = 0.269, p = 0.767.
Figure 1. Total stress scores during MUM in high and low EI groups.
3.3. Recovery State
Figure 2 presents the changes in recovery states during the TdG®. Firstly, results
showed no signiﬁcant effect of the trait EI group on recovery scores, F(1, 11) = 3.77, p = 0.078
(M low EI = 3.31, SD = 0.16; M high EI = 3.78, SD = 0.17). Secondly, the effect of time on
recovery scores was signiﬁcant, F(2, 22) = 7.50, p = 0.003, ηp2 = 0.45. Tukey HSD post
hoc tests showed that the score for recovery decreased between pre-MUM (M = 3.81,
SD = 0.12) and per-MUM (M = 3.46, SD = 0.09, p = 0.02, d = 3.11) and between pre-MUM
and post-MUM (M = 3.43, SD = 0.09, p = 0.003, d = 3.58).
Thirdly, the interaction effect of trait EI group X time on recovery was signiﬁcant,
F(2, 22) = 12.21, p = 0.0003, ηp2 = 0.53. The low trait EI group reported a lower score for
recovery (M = 3.26, SD = 0.60) compared to the high trait EI group (M = 4.27, SD = 0.39,
p = 0.004, d = 4.35) at Pre-MUM and this effect was non-signiﬁcant at per-MUM and Post-
MUM. In addition, only recovery scores in the high trait EI group decreased over time.
Speciﬁcally, recovery scores decreased between pre-MUM (M = 4.27, SD = 0.19) and both
per-MUM (M = 3.61, SD = 0.16, p = 0.0009, d = 3.11) and between pre-MUM and post-
MUM (M = 3.46, SD = 0.19, p = 0.0002, d = 3.11) among the high trait EI group whereas no
signiﬁcant difference was observed among the low trait EI group. Finally, all participants
during the race reported high recovery levels compared to stress states, F(2, 48) = 7.74,
p = 0.001, ηp2 = 0.24 (Table 2). A Tukey’s HSD post hoc test conﬁrmed that all recovery
scores were higher than the stress scores, either before, during, or after the race (Table 1).
Int. J. Environ. Res. Public Health 2022, 19, 9290
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Table 2. Results of the MANOVA analysis for recovery stress states in the low EI and high EI groups.
Low Emotional Intelligence (n = 7)
High Emotional Intelligence (n = 6)
Tukey’s HSD Interpretation
Pre-MUM (1)
Per-MUM (2)
Post-MUM (3)
Pre-MUM (4)
Per-MUM (5)
Post-MUM (6)
M(SD)
M(SD)
M(SD)
M(SD)
M(SD)
M(SD)
Recovery (R)
3.30 (0.23) *
3.32 (0.11) *
3.48 (0.14) *
4.02 (0.23) *µ
3.57 (0.11) *
3.40 (0.14) *
EI-level effect
F(1, 11) = 5.23, p = 0.04, ηp2 = 0.322
R in high EI > R in low EI
Time effect
F(2, 22) = 9.10, p = 0.001, ηp2 = 0.452
R at Pre-MUM > R at Per- and
Post-MUM
EI level * Time
F(2, 22) = 12.53, p = 0.0002, ηp2 = 0.532
1 < 4; 4 > 5–6
Stress (S)
2.70 (0.15)
2.84 (0.18)
3.01 (0.16)
2.45 (0.16)
2.56 (0.19)
2.82 (0.17)
EI-level effect
F(1, 11) = 1.53, p = 0.24, ηp2 = 0.122
NS
Time effect
F(2, 22) = 4.36, p = 0.03, ηp2 = 0.283
S at Pre-MUM < S at
Post-MUM
EI level * Time
F(2, 22) = 0.07, p = 0.93
NS
Note. * Mean of recovery signiﬁcantly higher than mean of stress. NS = non-signiﬁcant; µ Mean of Pre-MUM recovery in high EI group signiﬁcantly higher than Mean of pre-MUM
recovery in low EI group.
Int. J. Environ. Res. Public Health 2022, 19, 9290
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Figure 2. Total recovery score during MUM in high and low trait EI groups. Notes. * Mean of
recovery for the high trait EI group signiﬁcantly higher than the mean of recovery for the low trait EI
group. ↕ Mean of recovery for the high trait EI group signiﬁcantly higher at pre-MUM than per- and
post-MUM and then the mean of recovery for the low trait EI group.
4. Discussion
The purpose of this study was to examine the time courses of recovery stress states
before, during, and after one of the most challenging MUM races. This study also con-
tributes to identifying how individuals’ high versus low trait EI affects their recovery
stress states. Results showed an imbalance between recovery stress states, highlighting an
increase in the stress states and a decrease in the recovery states. This conﬁrms the ﬁrst
two hypotheses and reafﬁrms that running a MUM race is a psychologically demanding
situation. However, a particularly interesting ﬁnding concerns the differences in recovery
states based on trait EI scores. As expected in regard to the third hypothesis, athletes with
higher trait EI scores reported higher recovery states compared to athletes with lower trait
EI scores. Our ﬁndings support the positive role of trait EI on an individual’s ability to
cope with challenging situations [38].
Consistent with previous research on extreme situations [14,21], the results of the
present study tend to reafﬁrm that the stress state is increased over time regarding an
ultra-endurance race. Speciﬁcally, stress states signiﬁcantly increased immediately after
the race compared to the start of the race, while no signiﬁcant variation of stress states was
observed between pre- and per-MUM. Even if athletes tended to experience a constant
stress state during the ﬁrst part of the race, prolonged and repeated exposure to stressful
environmental conditions increased the stress state after the race. It is well established
that runners completing a MUM have to push their resources beyond ordinary limits [12]
to cope with the severe demands placed upon them, such as physical repercussions (e.g.,
fatigue, sleep deprivation) [50], emotional disturbances [51], and social stress [14].
Athletes reported higher scores of recovery than stress at every time point. These
results suggest that the recovery strategies were frequently used to buffer stress states.
It seems that athletes who ﬁnished the race tended to efﬁciently manage their resources
throughout the race. Based on their higher scores of recovery compared to stress, they
had to prioritize recovery to ensure their performance, health, and well-being [52] an
Int. J. Environ. Res. Public Health 2022, 19, 9290
9 of 13
effective biopsychosocial adjustment during the race. However, it is also noteworthy that
recovery decreased over the duration of the race, reﬂecting the difﬁculty of the runners
in maintaining and using strategies to preserve physical and psychological resources
throughout the race. The impairment of this balance may be explained by the fact that
individuals have to draw on their own resources to achieve their goals over a long time [23].
In line with the ﬁndings for prolonged exposure to stressors, where recovery decreases
and stress increases simultaneously [21], continuous effort in demanding situations could
lead to exhaustion of psychological resources and in turn could prevent the use of recovery
strategies [14].
Based on the median split approach, two groups were distinguished with signiﬁcantly
different trait EI scores. Although a signiﬁcant negative correlation was observed between
recovery and stress scores among the total sample, the correlation between recovery and
stress scores only remained signiﬁcant among participants belonging to the high trait EI
group. As expected, recovery and stress states were signiﬁcantly related in individuals
reporting greater levels of trait EI. As suggested by Jeffrey [26], recovery stress states could
be more balanced in an athlete with a high trait EI in order to ﬁnd an optimal recovery
within any challenge. Our results agree with this statement: Athletes who reported a high
trait EI reported more recovery strategies (i.e., active, passive, and proactive), which could
provide them with better control of their stress states before the race.
Surprisingly, scores for stress states were not statistically different between the high
and low trait EI groups. Literature suggested that EI was associated with signiﬁcantly
lower stress scores in stressful situations (i.e., competition), highlighting the protective role
of trait EI within stressful events [2]. However, our results do not conﬁrm this literature.
This could be explained by the potentially positive impact of the stress states, which may
lead to psychological adaptation and coping within stressful environmental conditions.
Stressful conditions actually lead to an increase in the stress responses in ultra-endurance
athletes [13–15]. However, a certain level of stress state may be necessary for a successful
psychological adaptation, as long as the recovery is sufﬁcient to help mobilize personal
resources [7,17]. Stress is therefore no longer considered to be a negative consequence
because it supports adjustment. Thus, the goal is not to eliminate the stress state per se but
rather to use it, while maintaining high scores of recovery, to buffer, manage, and regulate
stress. In this way, trait EI could play a protector role in stress through cognitive appraisals
in helping individuals evaluate situations as being challenging [53]. Reaching a balance
between stress state and recovery state would be a particularly relevant strategy to promote
adjustments in a MUM situation. In addition, the stress state experienced by athletes could
be considered as eustress to help further increase and mobilize their personal resources in a
constant adjustment to the extreme situation [23]. As a reminder, all participants in this
study were part of the 55% of ﬁnishers, suggesting that an optimal recovery stress state
was observed.
As expected, athletes who reported a high trait EI showed higher scores of recovery
before the race. In other words, these runners tended to be more able to protect, build,
reﬁll or restore their personal resources compared to the low trait EI runners. This ﬁnding
highlights the positive role of trait EI on the passive, active and proactive approaches to
recovery, in addition to its positive inﬂuence on the use of several psychological skills,
such as self-talk, imagery, or activation [43]. Our ﬁndings at the outset of the competi-
tion highlight that trait EI would help to optimize psychological processes by buffering
stressor effects [28] and boosting personal resources (physical, emotional, behavioral, and
social) [18]. However, an alternative explanation could be provided for the fact that only
recovery scores in the high trait EI group decreased over time. High trait EI participants
could have a better introspective sense of their internal state, whereas low trait EI partic-
ipants may not have as ﬁne-tuned a sense of their internal states and therefore did not
report changes in their recovery states over time.
Int. J. Environ. Res. Public Health 2022, 19, 9290
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5. Limits
Due to limited access to the elite athlete population and ﬁnishers in these ecologically
extreme situations, the small sample size of the present study represents a limitation for
generalization and further analyses such as regression models. In this line, it would have
been interesting to have more information on the characteristics of the participants to
better understand our results by considering other potential biological, psychological,
and sociological factors. For example, age, gender, and experience, but also training
periodization, ﬁtness, nutrition, and type of recovery practices may be involved in the
development of recovery and stress states. Further research should consequently endeavor
to recruit larger sample sizes and, more speciﬁcally, to go beyond the global EI score
used in this study. This score was calculated from 5 distinct sub-dimensions: Appraisal
of one’s own emotions, appraisal of others’ emotions, regulation of one’s own emotions,
regulation of others’ emotions, and use of emotions. Previous research has revealed the
relevance of investigating these sub-dimensions independently given that they could be
differently associated with psychological responses, such as emotions [38,43]. Therefore,
future research with a larger sample and different EI or emotional regulation questionnaires,
e.g., CERQ [54]; PEC, [55]; TEIQue, [56] could lead to a more speciﬁc understanding of
the respective inﬂuence of each dimension of trait EI on recovery strategies in stressful
situations.
6. Practical Applications
This study gives insight into the role of trait EI in the recovery stress states during a
MUM race. Runners should be aware that ultra-endurance races lead to substantial changes
in recovery stress states and that trait EI could help them to improve their preparation
for a MUM race. The ability to balance recovery stress states is essential in preventing
pathogenic psychological outcomes but also for the development and maintenance of
skilled performance, health, and well-being [1,19]. The positive association between trait
EI and the recovery process could also help to improve pre-competitive resources and
mental preparation. Coaches, athletes, and psychological counselors are concerned by this
result because they could conduct speciﬁc interventions in order to improve the trait EI in
athletes and in turn the balance between recovery strategies and stress states. As shown in
previous studies, it is possible to improve trait EI [5,57]. EI interventions [58] should ﬁrst
focus on the understanding of the emotional information in order to lead individuals to be
aware and accumulate sufﬁcient knowledge to transform this into practice (i.e., recovery
strategies) to increase trait EI.
7. Conclusions
Despite the limitations of this study, investigating the role of trait EI in MUM athletes
should provide a better understanding of the balance of recovery and stress states. An
added value of this study was to indicate that high trait EI was linked to higher scores
of recovery before the race, suggesting that such athletes tend to be better prepared to
cope with MUM. Athletes, coaches, and practitioners in sports psychology could develop
trait EI in order to facilitate the use of recovery strategies and optimize personal resources
in competition.
Author Contributions: Conceptualization, M.N. and G.M. (Gregoire Millet); methodology, M.N.
and M.G.; formal analysis, M.G. and G.M. (Guillaume Martinent); investigation, M.G.; writing—
original draft preparation, M.N. and M.G. writing—review and editing, M.N., M.G., V.B., G.M.
(Gregoire Millet), S.L. and G.M. (Guillaume Martinent). All authors have read and agreed to the
published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki, and approved by the Institutional Review Board of the University of Burgundy.
Int. J. Environ. Res. Public Health 2022, 19, 9290
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Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: The data are available and can be sent by the corresponding author.
Acknowledgments: We would like to thank the participants of the study who were fully committed
during their preparation time prior to the MUM.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
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Emotional Intelligence in Ultra-Marathon Runners: Implications for Recovery Strategy and Stress Responses during an Ultra-Endurance Race.
Nicolas, Michel,Gaudino, Marvin,Bagneux, Virginie,Millet, Gregoire,Laborde, Sylvain,Martinent, Guillaume