“Pleasant and unpleasant emotions in sport:
How I should I feel if I want to perform well?”
Andrew M. Lane
School of Sport, Performing Arts and Leisure, University of Wolverhampton, UK
Abstract
The present review examined relationships between emotions and performance. Evidence indicated that successful performance is associated with both pleasant emotions (happiness, calmness, and vigour) and unpleasant emotions (anger & anxiety). Data were presented from a recent study that investigated recent and optimal emotions and the intended direction of emotion regulation strategies. Results suggest that athletes are motivated to increase emotions associated with high action-tendencies regardless of whether these are pleasantly-toned (i.e., excitement) or unpleasantly-toned (i.e., anger and/or anxiety). Results show that; a) athletes hold beliefs that emotions such as anxiety and anger can be motivational; b) athletes actively engage in self-regulating strategies to increase these emotions; c) Ideal emotional states comprise a mix of pleasant and unpleasant emotions typically associated with high action-tendencies.Results are discussed using evolutionary perspectives on the function of emotion. Future research should look at the effectiveness of training packages designed to help athletes regulate their emotions.
Key words: affect, emotions, mood, psychological skills, self-regulation
Introduction
Emotions are omnipresent constructs that vary in intensity from moment to moment and between situations. Emotions have powerful effects on thoughts and behaviours (Baumeister, Vohs, DeWall, & Zhang, 2007; Lane, Beedie, Jones, Uphill, & Devonport, 2011; Lench, Flores, & Bench, 2011). Situations in which people typically experience intense emotions represent natural research environments to study the construct. One area of application associated with intense emotions is participating in competitive sport. Evidence shows thatathlete’s experience intense emotions before, during and following competition(Allen, Jones, & Sheffield, 2009; Hanin, 2010; Lane et al., 2011; Lane & Terry, 2000; Terry & Lane, 2000). Lazarus (2000) argued that the importance athletes place on the outcomes of competition can magnify the effects of changes in situational factors on emotional states. Evidence from four meta-analytic studies demonstrates significant relationships between pre-competitive measures of emotions and sport-performance (Beedie, Terry, & Lane, 2000; Craft, Magyar, Becker, & Feltz, 2003; Jokela & Hanin, 1999; Woodman & Hardy, 2003). However, evidence on the strength of emotion-performance relationships, indicates that the direction of relationships varies between studies (see Lane et al., 2011 for a review).
Pleasantly-toned emotions (see Figure 1) such as happiness and vigour have been found to associate with both successful and unsuccessful, with a similar pattern occurring for unpleasant emotions, particularly for anxiety and anger (see Beedie et al., 2000; Jokela & Hanin, 1999; Hanin, 2010). Researchers focusing on anxiety and performance have sought to examine how people believe emotions influence performance (Hanin, 2010). Research has asked when someone feels anxious, does he believe this feeling will help performance or hinder it (Hanton, Neil, & Mellalieu, 2008). The notion that pleasant emotions are not always helpful and unpleasant emotions always unhelpful is not restricted to sport. Evidence suggests that unpleasant emotions associate with a causal search for factors triggering the emotions and if these are performance-related, then the person might alleviate their depression but performing well (Brinkmann & Gendolla, 2008; Staw & Barsade, 1993).
The present article examines emotions in sport and particularly emotions experienced within an hour before competition which is the standard time to assess emotion in research (Martens, Vealey, Burton, Bump, & Smith, 1990). Emotions in this timeframe are likely to be an intensity that makes the individual conscious of them, and they are in a period of time when the individual has multiple opportunities to try to do something about them. It is proposed that emotion regulation is an organic process in which individuals actively monitor their emotional states and develop strategies to change or maintain emotion to desirable levels; if there is a sufficient discrepancy between one’s experienced and one’s desired feelings, then regulatory efforts are engaged (Carver, 2004; Gross & Feldman-Barrett, 2011; Higgins, 1999). With this in mind, the aim of this article is to examine the question: “If I want to perform better, then which emotion should I try to increase and which emotion should I try to decrease? In the present article, we use Russell’s (2003) model (see Figure 1) as a guide to describing discrete emotions in terms of their activation and valence. I am intentionally not using terms such as positive emotions and negative emotions. The terms positive and negative can be confusing as they imply that not only is the affective content of the emotion pleasant, but also, that there are positive effects associate with it. The present article makes no assumptions regarding the direction of emotion-performance relationships based on whether they are pleasant or unpleasant.
Measures of emotions
Research and practitioners typically assess emotions using a self-report scale. Research in sport has used different conceptualizations of emotions and as consequence a number of measures have been used. A great deal of the early research examined used the Profile of Mood States (McNair, Lorr, & Droppleman, 1971) which assesses six factors (anger, confusion, depression, fatigue, tension and vigour). Early studies found that successful performance was associated with high scores of vigour coupled with lower scores of anger, confusion, depression, fatigue and tension (Morgan, 1980). The implication from this model in terms of emotion regulation is that athletes seek to increase how vigorous and reduce how tense, depressed, confused, fatigue and angry they feel. However, subsequent research found evidence to show anger and tension associated with successful performance (see Beedie et al., 2000; Lane et al., 2011 for reviews). Lane and Terry (2000) proposed that whether anger and tension would help or harm performance would depend on its interaction with other emotional states, particularly other unpleasant emotions. Lane and Terry argued that when anger was coupled with feeling depressed, that feelings of anger would be turned inwards, and the person would withdraw; that is, sensations of anger would intensify feelings of depression, with the likelihood that the individual will not perform to her capability in sport. Lane (2007) reviewed tests of Lane and Terry’s model and argued that there is a great deal of evidence in support of this proposal.
Although Lane and Terry (2000) offered a theoretical framework for using the POMS in sport, sport psychologists were critical of the scale because it was initially validated for use in clinical settings. Recent research has led to the development of a sport-specific measure of emotion (Jones, Lane, Bray, Uphill, & Catlin, 2005). However, Jones et al. found close relationships between scores on their Sport Emotion Questionnaire, and a version of the POMS called the Brunel Mood Scale (Terry, Lane, & Fogarty, 2003),relationships that are strong enough to suggest that the two scales share a great deal of common variance. Lane (2007) argued that the choice of scale should be driven by the research question and that both the Brunel Mood Scale and Sport Emotion Questionnaire provide valid measures of emotions for use in sport.
In addition to the aforementioned scales, researchers have used the Positive and Negative Affect Schedule which has two broad measures; positive affect and negative affect(Watson, Clark, & Tellegen, 1988). Positive affect contains all pleasantly-toned emotions and negative affect contains all unpleasantly-toned emotions (see Figure 1). Examples of unpleasant emotions include anger, tension, and depression. Lane and Terry (2000) argued that researchers interested in examining relationships between emotion and performance should use discrete measures. They suggested that conceptualizing anger, anxiety, and depression individually rather than globally as negative emotion has had greater predictability. It is argued that using a two-dimensional measure of emotion such as positive affect and negative affect (Watson et al., 1988) results in a substantial loss of information. For example, if anger associates with good performance and depression associates with poor performance (Beedie et al., 2000; Jokela & Hanin, 1999), then an aggregate measure of anger-depression would show no relationship with performance (see Table 1).To emphasise why researchers should look for discrete relationships, I have created a fictional dataset in which anger and depression have perfect relationships with performance. As the data in Table 1 show, anger has an inverse relationship with performance (r = -1) and depression has a positive relationship (r = 1). If the data are added together to create a measure of negative affect, as advocated by some researchers (Watson et al., 1988), then the relationship with performance for each emotion is hidden. It should be noted that although I used anger and depression as examples, this argument could apply to other emotions within each factor.
Table 1.
Hypothetical data showing why researchers should conceptualize anger and depression.
Case / Anger / Depression / Negative affect(anger + depression / Performance1 / 1 / 10 / 11 / 10
2 / 2 / 9 / 11 / 9
3 / 3 / 8 / 11 / 8
4 / 4 / 7 / 11 / 7
5 / 5 / 6 / 11 / 6
6 / 6 / 5 / 11 / 5
7 / 7 / 4 / 11 / 4
8 / 8 / 3 / 11 / 3
9 / 9 / 2 / 11 / 2
10 / 10 / 1 / 11 / 1
Relationship between anger and performance = r = -1
Relationship between depression and performance r = +1
Relationship between negative affect and performance r = 0
Recent research has begun to use much shorter and direct measures of emotion. Brevity has been proposed as an important quality in a self-report scale (Lane, 2007). Our recent work has used single items to assess each quadrant of the circumplex (Russell, 2003 see Figure 1). Importantly, this approach allows the researchers to examine emotions in terms of their relative degree of activation-deactivation and pleasure-displeasure (Matthews, Jones, & Chamberlain, 1990).
Figure 1. Structure of emotion (Russell, 1980).
Emotions and performance: So how should I feel?
In a recent study, Lane, Stanley and Davis (2012) surveyed emotional states of 578 athletes. Athletes completed single item measures of emotional states (see Figure 2). Participants were asked them to describe their emotional state when they performed at their best and compared this emotional profile with a recent performance. Results of this survey are contained in Figure 2. Emotions were rated on a 1-7 scale where 1 = not at all to 7 = a great deal. Figure 2 illustrates that the ideal emotional profile for sport is characterized by feeling highly energetic, moderately clam and happy, somewhat anxious, a little angry and very little in terms of feeling downhearted and sluggish. This emotional profile is consistent with meta-analysis results of studies that examine emotion-performance relationships (Beedie et al., 2000).
However, Lane et al. (2012) also examined the preferred direction of emotion regulation of athletes. For example, if a athlete gave a score that best performance associated with a happiness score of 7 and was feeling quite happy (a score of 5), he indicated he wished to increase the intensity of this emotion; he wanted to feel happier. However, this could occur at relatively low intensities of emotions. If, for example, he believed ideal performance was associated with a happiness score of 4 and was feeling not feeling overly happy (represented by a score of 2), he would also wish to increase how happy he felt. The key part to this proposal is that researchers and practitioners should consider the discrepancy between ideal and experienced emotions. In the example above, both athletes wished to increase how happy they felt, but if we did not her optimal emotional state, then we might assume that the first athlete might be sufficiently happy, which is not the case if performance-enhancement is the goal.
Figure 2
Lane et al. (2012) examined the direction of preference to regulate emotions (see Figure3). As Figure 3illustrates, the majority of athletes were close to their optimal emotional state and wish to sustain the current intensity of each emotion. If an athlete is feeling excited and recognizes this to be the optimal level of excitement, he might have to engage in actions to sustain this emotional state. He might need to engage in cognitive strategies such as imagery or self-talk or physical strategies that promote physiological arousal. Thekey aspect is that athletes seek to self-regulate their emotional state to one that they believe will help performance, and an aspect of emotion regulation is maintaining an optimal state (see Lane et al., 2011). As Figure 3 also illustrates, athletes wished to increase and decrease theintensity of the full range of emotions; from pleasant to unpleasant. It is important to examine Figures 2 and 3 collectively. On first appearance, it could be concluded from observing differencesbetween ideal and experienced as presented in Figure 2, that athletes wanted to feel happier, calmer, more energetic, less anxious, sluggish, angry and downhearted. However, Figure 3 illustrates that this is not exactly the case. Figure 3 illustrates that some athletes wished to increase high action unpleasant emotions such as anxiety and anger and low action unpleasant emotions such as sluggish and downhearted. It is findings showing that athletes wished to increase theintensity of feeling downheartedness and sluggish, emotional states not typically associated with athletic success.
Figure 3
Findings of the study by Lane et al (2012) seem contradictory at first glance. It is almost paradoxical that an athlete might wish to feel more downhearted or sluggish and wish to perform successfully. However, there is evidence in the literature to support the findings present above ((Brinkmann & Gendolla, 2008; Staw & Barsade, 1993). Hanin (2010) has provided a wealth of evidence to show that emotion-performance relationships are highly individualized. It is possible that an athlete anticipates how he will feel post performance and then if he anticipates that he will feel downhearted, and does not want to feel this way, then this provides a signal to raise effort. It could be that anticipating feeling downhearted and sluggish provide triggers to regulation. Stanley, Beedie, Lane, Friesen and Devonport (2012) demonstrated that many strategies athletes use to change their emotions also could be described as strategies to improve performance; for example, warming up. Thus, unpleasant emotions experienced one hour before competition might be a signals to the individual that all is not well in her environment and that action is needed. If this is the case, then it is feasible to see how unpleasant emotions might help performance. It should be noted that there are other literature (Brinkmann & Gendolla, 2008; Staw & Barsade, 1993)that support the notion that emotional states are not inherently good or bad. It should be remembered that I intentionally labeled emotions as pleasant or unpleasant to avoid such confusion from the outset. Evolutionary perspectives on emotions tend to promote the argument that if certain emotions were inherently dysfunctional that evolution would have de-selected these from subsequent generations.
Emotions, like most psychological factors exist in part to inform behaviour in some way and have pervasive effects in all domains of human functioning (Baumeister et al., 2007). Moreover, this influence would have to be mainly benign and adaptive. As Baumeister et al. described; “If the total net effect of emotion were to cause behaviours that were maladaptive, such as by reducing survival and reproduction, then natural selection would likely have phased emotion out of the human psyche." Evolutionary psychologists propose that emotions are modes of functioning, shaped by natural selection, that coordinate physiological, cognitive, motivational, behavioural, and subjective responses in patterns that increase the ability to meet the adaptive challenges of situations that have recurred over evolutionary time (Nesse, 1990). They are adaptations that are useful only in certain situations and identifying person-situation interaction is complex. Like pain and sweating, they remain latent until an evolved mechanism detects cues associated with the situation in which they are advantageous. A key point to evolutionary psychologists is the notion that all emotions are helpful. Many evolutionary psychologists are critical of the use of terms such as ‘positive’, ‘negative’, ‘pleasant’, ‘unpleasant’, ‘helpful’, ‘unhelpful’, ‘functional’ and ‘dysfunctional’ when describing emotions (Nesse & Ellsworth, 2009). The idea that, because an emotion such as depression or anxiety is usually subjectively experienced as unpleasant, and is therefore ‘negative’, ‘unhelpful’ or ‘dysfunctional’ is questionable as each emotion serves to provide a signal to the individual. Sweating is a functional response and helps prevent over-heating, and over-heating can be fatal. Sweating is seen as dysfunctional in social settings, hence the development of a huge industry to help control it, but sweating itself is not necessarily a negative response.
Although depression is associated with maladaptive behaviours, even suicide, evolutionary psychologists argue that it does necessarily have negative effects on behaviour. Whilst such a suggestion seems ludicrous on first observation, careful examination of the underlying issues might suggest that there might be some logic to this line of thinking. Depression serves to inform the individual that he has insufficient resources to cope with the demands of the task, and that withdrawal is required. Depression is associated with low-levels of activation (see Figure 1) and therefore, signals to the individual that not doing much is the best course of action to take. In evolutionary terms, withdrawal might be best course of action rather than suffer humiliating loss that could influence chances of mating, or physical damage, which could mean loss of life or an inability to gather food through injury. When an athlete feels depressed, the emotion is signaling that at that moment he does not have the resources to cope with the demands of the task. The motivational signal coming from this emotion is not to take part. If feelings of depression represented a biological reality, that is, depression provided an accurate index of available physiological resources, then it is entirely reasonable to listen to these symptoms. If an individual said that he had not eaten within a week, we would not expect him to run a marathon. If feeling depressed signals that performance is not likely to be at the standard required and humiliation might follow, then not participating represents a plausible emotion regulation strategy.
However, many athletes attempt to override this emotional state and as a consequence, perform poorly in terms of trying to achieve the goal. In terms of efforts to regulate emotions, it is necessary to consider the concordance between the individual’s goals and the signal from the emotion being experienced. If a person believes that want to achieve X, and is feeling excited and energized, which is signaling that sufficient resources are available or could be made available, then there is concordance between the emotion and the goal. If the person wishes to achieve X, but feels depressed which is signalling withdrawal and preservation of resources, then there is discordance between the emotion and the goal. In this instance, the individual needs to identify the cause of the emotion and challenge whether that information is accurate, or re-evaluate his or her goals. The emotion is providing a signal to inform the individual that the situation warrants attention. Whilst research in sport tends to show depression is associated with poor performance, mainly because its effects on motivation and accompanies other emotions (Lane, 2007), research in other sub-disciplines of psychology indicates it has utility and associates with detailed planning and analysis of task demands (Staw & Barsade, 1993). If a depressed person identifies a reason for the depression and attending to this aspect was seen as sufficiently important, then depression might help performance (Brinkmann & Gendolla, 2008). However, as indicated by Baumeister, Zell, and Tice (2007), depression characterized by low-activation can hamper self-regulatory efforts. Depression sends a signal that regulatory efforts are futile as beliefs in being able to complete the task are futile.