2011. Vol.2, No.6, 633-637
Copyright © 2011 SciRes. DOI:10.4236/psych.2011.26097
Validity of the Emotion Regulation of Self Scale
among Runners
Andrew M. Lane, Christopher J. Beedie, Damian M. Stanley,
Tracey J. Devonport
School of Sport Performing Arts and Leisure, University of Wolverhampton, Wolverhampton, UK.
Received June 17th, 2011; revised July 24th, 2011; accepted August 27th, 2011.
The Emotion Regulation of Other and Self scale (EROS: Niven, Totterdell, Stride, & Holman, 2011) was origi-
nally designed to assess str ategies used to increase both pleasant and unp leasant emotions in a ra ng e o f s itu at ions
and over a 4 week period. The aim of the present study was to cross-validate the scale in a specific situation and
over a shorter timeframe, specifically in sport competition. Participants (N = 700) completed the EROS scale
whilst recalling strategies within an hour of competing in a running race of personal importance. Confirmatory
factor analysis results indicate some support for the integrity of a two-factor model. Factor loadings indicated
limitations with items designed to assess behavioral strategies to increase pleasant emotions and also unpleasant
emotions. After removing these weak-loading items and reanalyzing data, results indicated acceptable fit indices.
We suggest the scale has some utility in running but recommend that future research should develop domain-
specific items.
Keywords: Mood, Affect, Psychological Skills, Self-Regulation, Measurement
Emotions have a pervasive effect on human functioning
(Baumeister, Vohs, DeWall, & Zhang, 2007; Nesse, 1990).
Evidence indicates significant relationships between emotional
states and performance in different areas of application includ-
ing work (Wallace, Edwards, Shull, & Finch, 2009), the mili-
tary (Tenenbaum, Edmonds, & Eccles, 2008 2008) and sports
competition (Beedie, Terry, & Lane, 2000; Jokela & Hanin,
1999; Lazarus, 2000). Research has demonstrated that indi-
viduals who report positive1 emotions before performing are
likely to have regulated them in the period before competition
(Pensgaard & Duda, 2003; Robazza, Pellizzari, Bertollo, &
Hanin, 2008; Totterdell & Leach, 2001). Given the relationship
between emotions and performance, it is not surprising that
practitioners have sought to examine not only the emotions
experienced by athletes, but also the regulatory processes re-
lated to them (Gould & Maynard, 2009). Emotion regulation is
defined as a set of automatic and controlled processes involved
in the initiation, maintenance, and modification of the occur-
rence, intensity, and duration of feeling states (Gross, 2007;
Gross & John, 2003). One way of measuring emotion regula-
tion strategies is to use questionnaires or inventories, but the
utility of an instrument will depend fundamentally upon its
psychometric properties. If validity has not been demonstrated,
it is hazardous to accept and apply data derived from such
measures (Cronbach & Meehl, 1955; Schutz & Gessaroli,
Psychometric assessment of emotion regulation tends to fo-
cus on the conscious use of strategies (Parkinson & Totterdell,
1999; Thayer, Newman, & McClain, 1994). Conscious regula-
tory acts involve the agent identifying the desirable affective
state, and then engaging in some kind of action, such as
thoughts or behaviors, to reduce the difference between their
current and preferred state (Carver, 2004; Cervone, Mor, Orom,
Shadel, & Scott, 2004). Researchers typically ask participants
to identify emotion regulation strategies used over a given pe-
riod of time (Augustine & Hemenover, 2008; Parkinson & Tot-
terdell, 1999; Thayer et al., 1994). In their recent meta-analysis
of emotion regulation strategies, Augustine and Hemenover
noted there are at least 300 possible strategies, and proposed
that a broad cognitive versus behavioral distinction provides the
most acceptable classification. Examples of cognitive strategies
include thinking positive or hopeful thoughts, whereas behav-
ioral strategies comprise actions such as listening to music and
intentionally doing something pleasant. Clearly, attempting to
include all 300 strategies would create a lengthy measure, espe-
cially as brevity is particularly important for researchers wish-
ing to assess emotion regulation strategies in ecologically valid
situations such as before athletic competition or giving a public
performance (Davies, Lane, & Devonport, 2010; Lane, 2007).
1There are substantial semantic issues related to the use of terms such as
‘positive’, ‘negative’, ‘pleasant’, ‘unpleasant’, ‘helpful’, ‘unhelpful’, ‘func-
tional’ an d ‘d ysfu nction al’ in relati on t o emot ions . The i dea t hat , becau se an
emotion s uch as depr ess ion or anx iet y is u sual ly s ubj ectiv ely ex per ien ced as
unpleasant, it is at the same time therefore ‘negative’, ‘unhelpful’ or ‘dys-
functional’ is questioned by many authors, especially those examining the
phenomena from a psycho-evolutionary angle (e.g., Nesse, 1990). To re-
main cons ist ent with pr evi ous resear ch i n sp ort , we u se terms su ch as ‘n ega-
tive’ and ‘un
leasant ’ to describe emot ions such as anger, anxiety, s adness,
and depression, and terms such as ‘positive’ or ‘pleasant’ to describe emo-
tions such as happiness, relief, hope and excitement. Some greater clarity on
these issues however, although beyond the scope of the present paper, is
long overdue.
A great deal of research has investigated the argument that
individuals generally seek to increase pleasant and to reduce
unpleasant emotions (Augustine & Hemenover, 2008). In this
context it has been proposed that emotional well-being is in-
dexed by the ratio of pleasant to unpleasant emotions (Larsen,
2009). Whilst this approach to examining emotion regulation is
appropriate in the long-term, it does not always apply in the
short-term where different emotion regulatory motives might
apply; although Larsen argued that the primary focus of emo-
tion regulation research should be to examine strategies to en-
hance pleasant emotions, there are a number of different situa-
tions when this model might not apply (Martin, 2001). For ex-
ample, an individual is likely to accept feeling sad at a funeral
but would be less likely to accept feeling sad at a birthday party
and would likely engage in efforts to regulate such feelings.
Similarly, before an important task (e.g., a surgeon performing
an operation, an athlete trying to win an Olympic medal, or a
manager giving a presentation to a board of directors), an indi-
vidual could expect to feel a wide range of pleasant and un-
pleasant feelings, either of which may facilitate performance. In
fact, recent research has demonstrated that individuals increase
unpleasant emotions as well as pleasant emotions for such in-
strumental purposes (Tamir, 2009; Tamir, Chiu, & Gross, 2007;
Tamir, Mitchell, & Gross, 2008). This suggests that if an indi-
vidual believes that increasing unpleasant emotions will evoke
action tendencies that help goal pursuit, then the individual
could be motivated to regulate their emotions in that direction.
From an evolutionary perspective, it is proposed that emotions
such as anxiety and anger function to inform the individual of
impending loss or danger unless action is taken (Nesse, 1990).
Indeed, at least two meta-analytic studies have demonstrated
that emotions such as anger and anxiety are sometimes associ-
ated with successful sport performance (Beedie et al., 2000;
Jokela & Hanin, 1999). Further, qualitative research has dem-
onstrated that athletes develop meta-beliefs that emotions such
as anger and anxiety can be functional both before and during
competition, as these emotions signal that goal attainment is
threatened (Hanin, 2003). A scale to assess the motivation un-
derlying attempts to increase unpleasant emotions would help
elucidate this phenomenon.
Based on the theoretical framework developed by Niven,
Totterdell, and Holman (2009), researchers have recently de-
veloped a 12-item scale to assess emotion regulation strategies
intended to both improve and worsen emotions (Emotion
Regulation of Self and Others; EROS, (Niven et al., 2011). The
term ‘improving emotions’ refers to strategies aimed at in-
creasing pleasant emotions whereas the term ‘worsening emo-
tions’ refers to strategies aimed at increasing unpleasant emo-
tions. Given findings that suggest that emotions described as
‘unpleasant’ can associate with good performance (Beedie et al.,
2000; Jokela & Hanin, 1999), as well as evidence that athletes
often attempt to increase the intensity of these unpleasant emo-
tions (Hanin, 2003), it is suggested that the terms ‘worsening’
and ‘improving’ are misleading. We suggest that they should be
replaced and propose using the labels ‘increasing pleasant emo-
tions’ and ‘increasing unpleasant emotions’.
Niven et al. (2011) demonstrated factorial validity of the
EROS scale among two independent samples using confirma-
tory factor analysis. It should be noted that Niven et al. asked
participants to report usage of emotion regulation strategies
over the previous 4 weeks and so people are likely to have had
an opportunity to engage in a range of different tasks. Recent
research has found that the scale has utility across a range of
different areas of application. Niven and Holman (2009) dem-
onstrated that strategies used to regulate one’s own emotions
associated with general well-being among a heterogeneous
sample of over 500 participants from the general public. Dhin-
gra, Totterdell, Tantam, and Taylor (2010) found that strategies
used to increase unpleasant emotions associated with increased
likelihood of engaging in self-harm in a clinical setting.
Given the notion that validation of psychometric measures is
regarded as an ongoing process (Cronbach & Meehl, 1955;
Schutz & Gessaroli, 1993) we sought to cross-validate the
measure for use in sport. Sport and exercise psychology is an
area of application in which the tradition is to develop a situa-
tion-specific measure. This tradition is based on the argument
that measures developed in one area transfer poorly to sport and
exercise with the result being a large body of sport-specific
scales (Duda, 1998). Therefore, we argue that cross validating a
measure to sport represents a rigorous test of the validity of the
The sample of volunteer runners was heterogeneous (N = 700;
male, n = 338, age, M = 37.98 years, SD = 9.9; fema le , n = 360,
age, M = 36.02 years, SD = 8.54; 2 did not report gender) in
terms of previous experience ranging from recreational to in-
ternational (n = 369, club n = 182, regional n = 82, national n =
44, international n = 19). Runners competed at distances rang-
ing from 5km to a marathon.
The emotion regulation scale consists of 12 items designed to
assess strategies intended to increase pleasant emotions and
strategies intended to increase unpleasant emotions (see Table 1
for examples of items). Participants are instructed to rate the
frequency of usage, rather than to evaluate whether each strat-
egy was effective. Participants rate items on a 5-point scale (1 =
not at all, 5 = a great deal). In the present study, participants
reported the strategies they used during the hour before compe-
Following institutional ethical approval, participants were
recruited online via the website of the magazine ‘Runner’s
World’. Participants were asked to recall an important race in
which they had competed during the last 4 weeks. A retrospec-
tive approach was used with participants recalling emotion
regulation strategies used in the hour before competition. Ek-
man and Davidson (1994) suggested that people tend to re-
member emotionally charged events well, and retrospective
measures of anxiety have been shown to be reliable up to 3
months after competition (Hanin & Syrja, 1996).
Data Analysis
Confirmatory factor analysis (CFA) using EQS V6 (Bentler
& Wu, 1995) was used to test the hypothesized model. As there
was evidence of multivariate non-normality in the data, models
were tested using the Robust Maximum Likelihood method.
This method has been found to effectively control for overesti-
mation of X2, under-estimation of adjunct fit indexes, and un-
der-identification of errors. The 2-factor measurement model
for the EROS scale specified that each item related to its hy-
pothesized factor with the variance of the factor fixed at 1.
Factors were allowed to freely inter-correlate. Model fit was
judged acceptable if incremental fit indices were greater
than .95 and the standardized Root Mean Error of Approxima-
tion (RMSEA) was lower than .08 (Hu & Bentler, 1999).
CFA results demonstrate that fit indices are marginally lower
than values needed to be acceptable. The Robust Confirmatory
A. M. LANE ET AL. 635
Table 1.
Descriptive statistics and factor l o ad ings for the emotion regula t i o n o f s e l f scale in runners.
Items M SD Factor loading Standarized Error R2
Strategies to increase pleasant emotions
I laughed to try to improve how I felt 2.96 1.97 .42 .91 .18
I did some th ing I enjoy to try t o improve how I felt 3.61 1.98 .55 .83 .30
I sought support from others to try and make me feel better 3.39 2.02 .45 .90 .20
I thought about somethi ng nice to try and make me feel better 4.05 1.87 .83 .561 .69
I thought abo ut positive aspects of my situation to try to improv e how I felt 4.63 1.74 .76 .65 .58
I thought about my positiv e characteristics to try and make me feel better 4.04 1.80 .61 .79 .38
Strategies to increase unple asant emotions
I started an a r gument with someone to tr y and make me feel worse 1.15 0.64 .39 .92 .15
I expressed cynicism to try and m ake me feel worse 1.55 1.15 .62 .78 .39
I listened to sad music to try and make me feel worse 1.16 0.63 .30 .96 .09
I looked for problem s in my current situation to try t o make me feel worse 1.65 1.28 .73 .68 .54
I thought about my shortc omings to try and make me feel worse 1.69 1.28 .78 .62 .61
I thought about nega tive experiences to try and make me feel worse 1.53 1.15 .68 .73 .47
Fit Index, RCFI = .92, and the Non-Normed Fit Index NNFI
= .90, were marginally lower than the .95 criterion proposed by
Hu and Bentler (1995). The RMSEA (.07) was on the limit of
acceptability. Factor loadings are contained in Table 1. As Ta-
ble 1 indicates, weak factor loadings were found for the fol-
lowing items: “I laughed to try to improve how I felt”, “I
sought support from others to try and make me feel better “, “I
started an argument with someone to try and make me feel
worse”, and “I listened to sad music to try and make me feel
worse”. We removed 4 items and tested the 8 item and
two-factor model. Results indicated improved fit indices (RCFI
= .97, NNFI = .95, RMSEA = .06) were acceptable according
the criteria suggested by Hu and Bentler (1995).
The aim of the present study was to extend the validation
process of the emotion regulation of others and scale (Niven et
al., 2011) for use in sport, namely running. Results of the pre-
sent study provide some support for the validity of the scale.
Acceptable fit indices (Hu & Bentler, 1999) were found for a
revised 8-item measure. However, despite these promising
findings, concern is raised regarding the utility of some behav-
ioral items. We propose that the shorter time frame used in the
present study might explain why behavioral items showed poor
factor loadings. Participants in the present study rated their use
of emotion regulation strategies one hour before competition as
opposed to over a 4 week period. However, in the hour before
running competition, practical factors limit the possibility of
using certain behavioral strategies. For example, it might not be
possible to listen to music if athletes do not have access to a
personal music player. We suggest the notion that athletes listen
to music with a view to increase unpleasant emotions might be
particularly problematic. Evidence suggest that an athlete who
is attempting to self-regulate her emotions by listening to music
tends to do so with a view to enhance performance (Bishop,
Karageorghis, & Loizou, 2007).
Given low factor loadings for behavioral items, we suggest
that future researchers should develop items that are specific to
the domain and timeframe under investigation. With reference
to running, previous research has found that emotions in run-
ning associate with the relative difficulty of the self-set goal
and the athlete’s confidence to achieve this, the relative suit-
ability of the course, and interactions with the coach (Jones,
Swain, & Cale, 1990; Lane, 2001). Studies have also suggested
that runners cope with the demands of performance by focusing
on the task at hand, for example concentrating on running tech-
nique (Stevinson & Biddle, 1998) or on physical aspects of
performance such as keeping their heart rate below a desired
value, or focusing on distraction (Buman, Omli, Giacobbi, &
Brewer, 2008). We suggest that the emotion regulation scale
should include additional behavioral items that focus on be-
havioral strategies focused on overcoming task demands (e.g.,
talking to runners who have completed the run, physically pre-
paring for the run).
Given that evidence has demonstrated over 300 different
strategies available (Augustine & Hemenover, 2008), present-
ing this list to participants represents an impractical step for-
wards, particularly for applied research where brevity is an
important issue. The number of strategies used is indicative of
the ideographic nature of emotion regulation, and seeking to
standardize or generalize these might result in a considerable
loss of information. By developing items that cover generic
categories of emotion regulation strategies it is argued that
identification of commonly used strategies that individuals find
effective could be obscured. For example, the growing use of
transportable music devices has led to an increase in runners
listening to music before and during running races. Therefore,
we suggest that researchers should include open-ended ques-
tions to facilitate the ideographic nature of emotion regulation.
Continuing this line of research, we suggest future research
should investigate the test-retest reliability of the scale. Al-
though emotion regulation strategies have been proposed to be
habitual (Wood, Quinn, & Kashy, 2002), the extent to which
they would be used in a specific situation will relate to emo-
tional states. Emotions are transitory constructs and each com-
petition carries a degree of uncertainty that will also tend to
vary, and therefore, if regulatory efforts are needed before one
particular race, but not before another, it is possible that
test-retest relationships could be weak in cross-sectional studies.
It is important to show that the scale has sufficient sensitivity,
and that relationships between emotion and emotion regulation
are invariant even if the relative frequency of usage and inten-
sity of emotions changes.
In conclusion, we suggest that the emotion regulation scale
shows a promising degree of validity for use in running. We
suggest that future validation work should develop specific
behavioral items for use in running.
The support of the Economic and Social Research Council
(ESRC) UK is gratefully acknowledged (RES-060-25-0044:
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