The effects of Punishment and Reward Sensitivities on Mental Toughness and Performance in Swimming

Abstract

1 The purpose of the current study was to examine the interactive effects of punishment 2 and reward sensitivity in predicting Mentally Tough behaviour and performance in 3 swimming. First, we validated a measure of MT behaviour in a mixed sample of competitive 4 swimmers and then examined the interactive effects of punishment and reward sensitivities in 5 predicting MT behaviour. A second purpose of the study was to examine whether punishment 6 and reward sensitivities can account for race time performance. Results found significant 7 interactions between reward and punishment sensitivity across both studies. That is, as 8 punishment sensitivity increased MT and race times improved when reward sensitivity was 9 low. However, both decreased when reward sensitivity was high. Results add to previous 10 research showing that athletes who are sensitive to punishment and insensitive to reward 11 display stronger MT behaviours and as a consequence, swim faster. 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Personality, mental toughness and swimming performance 2 The development and maintenance of Mental Toughness (MT) in sport has become a 1 topic of increasing interest over the past 15 years. Researchers generally agree that MT can 2 be defined as consistently maintaining performance and goal directed behaviour under a 3 range of different stressors (e.g., Gucciardi, Hanton, & Mallett, 2012; Hardy, Bell & Beattie, 4 2014). However, early research findings were heavily driven by qualitative studies (e.g., Bull, 5 Shambrook, James, & Brooks, 2005; Connaughton, Hanton, & Jones, 2010; Connaughton, 6 Wadey, Hanton, & Jones, 2008; Gucciardi, Gordon, & Dimmock, 2008; Jones, Hanton, & 7 Connaughton, 2002; Jones, Hanton, & Connaughton, 2007) who identified a very large 8 number of characteristics that are associated with MT (e.g., Anderson, 2011 lists over 70). 9 Hardy et al. (2014) also argue that although qualitative studies allow one to examine 10 correlates of MT, they do little to determine the causes, processes, and outcomes of being 11 mentally tough. 12 Quantitative research in MT has received equal criticism. For example, Gucciardi, 13 Mallett, Hanrahan and Gordon (2011) note various limitations in measures of MT e.g., the 14 Mental Toughness Questionnaire 48 (Clough, Earle & Sewell, 2002); the Cricket Mental 15 Toughness Inventory (Gucciardi & Gordon, 2009); the Australian football Mental Toughness 16 Inventory (Gucciardi, Gordon, & Dimmock, 2009); the Psychological Performance Inventory 17 (Loehr, 1986); and the Sport Mental Toughness Questionnaire (Sheard, Golby, Wersch, 18 2009). Such limitations include poor construct validation, measurement invariance, 19 reliability, and lack of generalisability across populations. Further, as in the qualitative 20 research, there has been an abundance of factors associated with quantitative measures of 21 MT, which would suggest MT is multidimensional in nature. Some of these factors include 22 self-confidence; negative energy control; attention control; visualisation and imagery control; 23 motivation; positive energy; attitude control; challenge; commitment; emotional control; life 24 Personality, mental toughness and swimming performance 3 control; confidence in abilities; interpersonal confidence; constancy; and thrive through 1 challenge (to name but a few). 2 In much of the above research, there also appears to be considerable overlap between 3 proposed MT factors and psychological skills. For example, if some of the MT factors 4 reported above were compared against multifactorial measures of psychological skills (e.g., 5 Test of Performance Strategies; Hardy, Roberts, Thomas, & Murphy, 2010) it would be seen 6 that they contain a number of identical factors (e.g., attention and emotional control). A 7 further limitation of self-report MT inventories is that they are open to social desirability and 8 self-presentation abuse (Hardy et al., 2014). 9 To overcome some of the limitations presented above, Hardy et al. (2014) conducted 10 a series of studies to develop a theoretical account of MT. These authors noted that there is 11 little point in linking cognitions, attitudes and emotions to MT unless one knows that MT 12 behaviour has actually occurred (see also Arthur, Fitzwater, Hardy, Beattie, & Bell, 2015). 13 Therefore, Hardy et al. validated an 8-item informant rating of MT in which coaches could 14 rate MT behaviours of their athletes under various stressors that they would typically face in 15 competition. Further, as MT is generally thought of as a relatively stable disposition, Hardy et 16 al. (2014) hypothesised that MT behaviour could be predicated by existing personality 17 theories, more particularly, the revised Reinforcement Sensitivity Theory (rRST; Gray& 18 McNaughton, 2000). 19 According to Gray and McNaughton (2000) there are three neuropsychological 20 systems underpinning rRST. Neural circuits that mediate responses to reward, punishment 21 and goal conflict underpin these systems. First, rewarding appetitive stimuli (e.g., money or 22 food) activate the behavioural approach system (BAS) where the individual approaches such 23 rewarding stimuli. Second, the fight, flight, freeze system (FFFS) is activated when specific 24 threats are detected. For example, one may want to avoid a dental appointment due to fear of 25 Personality, mental toughness and swimming performance 4 needles and drills. Here, the avoidance of such threatening stimuli is paramount. The final 1 system termed behavioural inhibition system (BIS) is associated with resolving approach2 avoidance conflict between the BAS and FFFS. For example, one may put up with mild 3 dental pain (avoidance) in the hope that it may subside. However, if dental pain gets too 4 severe, then the BIS system will resolve such approach-avoidance conflict by engaging with 5 appetitive stimuli due to the reward stimulus (stop the pain) and seek dental support, despite 6 the impending (punishment) consequences. 7 As discussed above, Hardy et al. (2014) hypothesised that rRST could explain MT 8 behaviour. They noted a number of studies where reward sensitivity was associated with high 9 levels of performance and mild reactions to stress under threatening conditions (e.g., Perkins 10 & Corr, 2006; Perking, Kemp, & Corr, 2007). Further, individuals high in punishment 11 sensitivity seem to suffer from poor performance under pressure (Perkins et al., 2007), avoid 12 threatening situations (Perkins & Corr, 2006), and negatively evaluate their capacity to deal 13 with pain (Muris et al., 2007). Based on those findings, Hardy et al. proposed that higher 14 levels of reward sensitivity would be associated with higher levels of MT behaviour, whereas 15 higher levels of punishment sensitivity would be associated with lower levels of MT 16 behaviour. One final point regarding Hardy et al.’s hypothesis is that, even though reward 17 and punishment sensitivities are orthogonal constructs (Gray & McNaughton, 2000), studies 18 testing interactive effects between these two systems are rare. Therefore, Hardy et al. 19 predicted that MT would be associated with high levels of reward and low levels of 20 punishment sensitivity. However, results revealed findings contrary to their hypothesis. 21 Specifically, across two separate studies of elite level county cricketers, a significant 22 interaction between reward and punishment sensitivity revealed that when reward sensitivity 23 was low, increasing levels of punishment sensitivity were associated with an increase of MT 24 behaviour. Further, when reward sensitivity was high, as punishment sensitivity increased, 25 Personality, mental toughness and swimming performance 5 MT behaviour decreased. To clarify these findings, Hardy et al. conducted a follow up study 1 and found that participants who were high in punishment and low in reward sensitivity 2 detected threats early thereby enabling them more time to plan an effective response. 3 The purpose of the current study was to examine Hardy et al.’s (2014) findings in the 4 context of a different sport, namely, swimming. We chose the sport of swimming for a 5 number of reasons. First, a limitation in the Hardy et al. studies was that only elite level male 6 cricketers aged between 15 and 19 years old participated. Swimming offered us an 7 opportunity to examine data from a wider age range in both male and female athletes. 8 Further, objective performance data is more easily obtained from swimming, as swim times 9 are impartial to the interpretations of others (e.g., as opposed to a coach judging the 10 performance of cricketers who were playing against other players of varying abilities). 11 Finally, cricket is a team sport whereby one player’s poor performance can be mitigated by 12 another’s exceptional performance. In swimming, individual accountability is much easier to 13 attribute. A second purpose of the study was to examine whether punishment and reward 14 sensitivities could actually predict race time performance. 15 The current study set out to re-examine and extend the findings from Hardy et al. 16 (2014). Similar to Hardy et al., we aimed to develop an informant rating measure of MT in 17 competitive swimming environments. We also re-examined Hardy et al.’s findings that when 18 reward sensitivity is low, increasing levels of punishment sensitivity would positively relate 19 to MT behaviour; but when reward sensitivity is high, increasing levels of punishment 20 sensitivity would negatively relate to MT behaviour. Finally, on the basis that mentally tough 21 personalities should maintain higher levels of personal performance under pressure than non22 mentally tough personalities, a second purpose of the study was to examine the relationship 23 between rRST and swimming performance time. More precisely, we predicted that when 24 reward sensitivity was low, increasing levels of punishment sensitivity would be associated 25