Five Topics in Sports Psychology

Five Topics in Sports Psychology IBN: 978-1-904542-69-8 Kevin Brewer 2013 2

This document is produced under two principles: 1. The images are all available in the public domai n (from http://openclipart.org ). You are free to use this document, but, please, quote the source (Kevin Brew er 2013) and do not claim it as you own work. This work is licensed under the Creative Commons Attribution (by) 3.0 License. To view a copy of thi s license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ or, send a letter to Creative Commons, 171 2nd Street, Suite 300, San Francisco, California, 9 4105, USA. 2. Details of the author are included so that the l evel of expertise of the writer can be assessed. This co mpares to documents which are not named and it is not poss ible to tell if the writer has any knowledge about their subject. Kevin Brewer BSocSc, MSc ( http://kmbpsychology.jottit.com/ ) An independent academic psychologist, based in Engl and, who has written extensively on different areas of psychology with an emphasis on the critical stance towards traditional ideas. Orsett Psychological Services, PO Box 179, Grays, Essex RM16 3EW UK [email protected]


CONTENTS Page N umber 1. EXPERT PERFORMANCE 4 1.1. Expert performance and practice 1.2. Cognitive differences 1.3. Sports official 2. TEAM COHESION 9 2.1. Task and social cohesion 2.2. Measuring team cohesion 2.3. Team cohesion and performance 2.4. Attributions 2.5. Role of coach 2.6. Appendix 2A - Leadership and cohesion 3. HOME ADVANTAGE 21 3.1. Factors in home advantage 3.2. Research examples 3.3. Home disadvantage 3.4. Officiating 4. INDIVIDUAL DIFFERENCES BETWEEN PERFORMERS 27 4.1. Cognitive abilities 4.2. Anxiety and confidence 4.3. Mental toughness 4.3.1. Techniques to help confidence and performance 4.4. Extreme sports 5. EXERCISE AND HEALTH 44 5.1. Introduction 5.2. Improvements in exercise 5.2.1. Encouraging physical activity in childr en 6. REFERENCES 49


1. EXPERT PERFORMANCE 1.1. Expert performance and practice 1.2. Cognitive differences 1.3. Sports official 1.1. EXPERT PERFORMANCE AND PRACTICE "Nobody becomes an outstanding professional wi thout experience, but extensive experience does not invar iably lead people to become experts...Although everyone i n a given domain tends to improve with experience initi ally, some develop faster than others and continue to imp rove during ensuing years. These individuals are eventua lly recognized as experts and masters. In contrast, mos t professionals reach a stable, average level of performance within a relatively short time frame an d maintain this mediocre status for the rest of their careers" (Ericsson 2004 pS70). Why this difference? The traditional answer ha s been innate factors related to biology. Francis Galton f irst proposed this idea in the late 19th century particu larly in relation to mental abilities. Ericsson (2004) argued for an alternative to n ature - deliberate and continued practice (nurture) 1. This is different to experience alone as experienced indivi duals are not automatically better than novices (eg: comp uter programmes, wine tasters, financial advisors) (Eric sson 2004). Studying the superior performance of an expert over a novice or less skilled individual is not easy. Th is is partly because expert skills are many and varied (f rom chess masters to physical sporting abilities to med ical diagnosis), and they are difficult to study in real -life. On the other hand, laboratory studies are artificia l and reductionist. Thus the need to design controlled st udies which use real-life elements that an expert is face d with. de Groot (1946/1978) was the first to design a controlled study of expertise using naturally occur ring tasks. Chess players were presented with chess posi tions (taken from games) and asked to make the next move. The quality of the move chosen was better for world-cla ss players as compared to club players. Subsequent use of this method 2 has standardised

1 Howard (eg: 2009) has challenged the importance of deliberate practice, and emphasised innate talent with a limit to the individual's performance. Playing the sport will improve performance up to the individual's limit. 2 Sometimes called the expert-performance approach (Ericsson and Ward 2007).


scoring, encourages the participant to think aloud as solving the problem, and uses measures like eye mov ement tracking (Ericsson and Ward 2007). Ericsson and Ward (2007) noted from research o f activities like darts, music performance, and surgi cal procedure, that expert performance requires an exte nded period of skill development (eg: ten years). This i s because physiological differences between experts a nd novices are often the product of training (eg: grea ter maximal oxygen uptake of endurance athletes or stru cture of ballet dancers' hip joints altered between 9-12 years old; Ericsson and Ward 2007). Intense training prod uces biochemical changes that trigger dormant genes, and these lead to physical changes. Deliberate practice (for thousands of hours) also improves performance throu gh feedback of success. "The commonly held but empiric ally unsupported notion that some uniquely 'talented' individuals can attain superior performance in a gi ven domain without much practice appears to be a destru ctive myth that could discourage people from investing th e necessary efforts to reach expert levels of perform ance" (Ericsson and Ward 2007 p349). Ericsson (2004) summarised the evidence about the development of expert performance: � Performance increases gradually over time and not i n

sudden bursts, even among child prodigies. � Individuals reach their peak after many years of

performance - eg: in late 20s in vigorous sports, b ut in 30-40s in non-vigorous activities.

� Deliberate practice should focus on a specific task

with immediate feedback. Ericsson et al (1993) studied expert musicians at a music academy in Berlin, Germany. The best violinis ts spent around four hours every day on solitary pract ice of specific aspects of their performance. It was calcu lated that these players had spent more than 10 000 hours on practice by age 20 compared to half or three-quarte rs of that amount for less accomplished experts 3.

3 Accurately measuring the amount of practice of performers can be difficult. The most common method is self-report. But this is prone to recall error, particularly depending on the time period used. Ericsson et al (1993) asked the musicians to recall the preceding day as 15-minute segments, and this was supported by diary-keeping. There was a high degree of consistency between the sources of information. Less reliable is a general question like, "How many hours per week on average have you studied chess in the past year (eg: read chess books, studied computer databases, analysed games, and so on)?" in Howard's (2012) Internet survey. Ericsson and Moxley (2012) observed: "It must be very


1.2. COGNITIVE DIFFERENCES Asking individuals to think aloud (process-tra cing) has shown the cognitive mechanisms involved in the acquisition of expert performance. For example, the ability to plan, monitor and reflect upon performan ce are different between experts and novices, but not "bas ic" abilities like intelligence or memory capacity (Eri csson and Ward 2007). Even if experts do not have better general mem ory than novices, they do have superior pattern recall for their area of expertise (eg: positions of pieces in chess) and similar areas (eg: position of pieces in draughts). For example, Abernethy et al (2005) foun d that expert netball players recalled details of clips of netball games better than novices, but so did exper ts from other sports (eg: basketball, hockey). This is taken

as evidence of transfer of skills. Expertise in a domain also varies with the role. In sport, this refers to players, coaches, and referees/officials. Allard et al (1993) tested basketball coaches, players and referees on different aspects of their sport. Referees fared best on knowledge of rules, hand signals used by officials, and details of fouls, while coaches and players

recalled more pictures showing different basketball plays. MacMahon et al (2007) compared the expertise o f seven Belgian elite association football referees w ith 34 Belgian elite clubs' academy players. The participa nts were shown twenty short clips of tackles and given ten seconds after each one to decide if it was not a fo ul, a foul only, a foul requiring a yellow card, or a fou l worthy of a red card (as previously determined by a FIFA panel of experts). This was called the referee tack le assessment task. The referees had a mean accuracy of 81% compared to 55% for the players (p<0.001). Among th e referees, hours per week in refereeing practice was

difficult for the respondents to retrieve all the relevant information about all these different activities for a complete year and generate an answer rapidly" (p652).


related to accuracy. MacMahon et al (2007) noted: "Put simply, refe rees observe players perform game-related actions and re act by applying the rules, whereas players perform game-re lated actions and observe or react as referees apply the rules. Players do not regularly make rule application deci sions, and thus referees should outperform them" (p66). Individuals become experts through deliberate practice of their skills, but how does that apply t o referees? MacMahon et al (2007) questioned seven Be lgian and 26 English elite association football referees on the type of training undertaken throughout their career s (including physical fitness training, and activitie s undertaken by coaches and players). Other than the obvious need for physical fitness, refereeing games was seen as most relevant for improving performance (fi gure 1.1). 10 - High relevance Refereeing league matches (9.3) Technical refereeing skills (8.9) Speed endurance (8.7) 5.9 - Overall mean Playing football (3.1) Player meetings (2.4) 1 - Low relevance (In brackets = mean score) (Data from MacMahon et al 2007 table II p75)

Figure 1.1 - Examples of training activities rated as significantly relevant or not relevant by referees. 1.3. SPORTS OFFICIALS Sports officials included judges who score ath letes' performance (eg: gymnastics) and referees/umpires w ho enforce rules (eg: football). Both groups can show varying degrees of expert performance (ie: accuracy of officiating). The expert performance of officials will be influenced by external factors like the crowd, and internal factors like the official's experience. Th e experience can be visual (from watching many games as an official or spectator) as well as motor (having pla yed the sport) (Pizzera and Raab 2012). Pizzera and Raab (2012) found that the differe nt types of experience varied in importance depending on the sport. They studied 370 officials from football (n = 77), handball (n = 107), ice hockey (n = 121), and


trampolining (n = 65) in Germany. Details of the officials' experience were collected - officiating (years as judge or referee), motor (years playing the spor t which now officiate), and visual (years watching as a spectator). Performance measures of the officials w ere made by expert referee coaches. Officiating experience was significantly relat ed to performance in handball and ice hockey, while motor experience was important in ice hockey and trampoli ning. Football refereeing was associated with visual experience.


2. TEAM COHESION 2.1. Task and social cohesion 2.2. Measuring team cohesion 2.3. Team cohesion and performance 2.4. Attributions 2.5. Role of coach 2.6. Appendix 2A - Leadership and cohesion 2.1. TASK AND SOCIAL COHESION The sports team is a specific type of group, a nd a key element is cohesion. This is "an individual's s ense of belonging to a particular group and his or her feelings of morale associated with membership in gr oups" (Bollen and Hoyle 1990 p482), or "a dynamic process that is reflected in the tendency for a group to stick together and remain united in the pursuit of its instrumental objectives and/or for the satisfaction of member affective needs" (Carron et al 1998 p213). Cartwright (1968) used the term, "we-ness", where "members all work together for a common goal, or on e where everyone is ready to take responsibility for group chores" (p70). Team cohesion is sub-divided into task cohesio n (working together to achieve the goals) and social cohesion (liking each other) (Cota et al 1995). The ideal is to have high task and social cohesion - individu als who like each other working for a common goal, but there will be variations in reality (eg: low task/high so cial; low social/high task). Team cohesion will be influenced by: i) External factors - outside the team (eg: social environment). ii) Internal factors - inside the team. a) Personal - eg: team homogeneity (Widmeyer a nd Williams 1991). b) Stability - length of time playing together . c) Leadership (appendix 2A). d) Team size


2.2. MEASURING TEAM COHESION Carron et al (1985) developed the Group Enviro nment Questionnaire (GEQ) to measure team cohesion 4. The 18 items measure two dimensions - individual team memb er's perception of the team, divided into group integrat ion (perception of how well the team works together) an d individual attraction; and the player's group orien tation (divided into social and task cohesion) 5. This gives four sub-scales: i) Group integration/social cohesion (GIS) - a n individual's perceptions of the unity of the group in relation to social aspects of the group. ii) Group integration/task cohesion (GIT) - an individual's perceptions of the unity of the group in relation to tasks of the group. iii) Individual attraction/social cohesion (AT G-S) - an individual's perceptions of their involvement in social aspects of the group. iv) Individual attraction/task cohesion (ATG-T ) - an individual's perceptions of their involvement in ta sks of the group.

4 The first stage in designing the GEQ involved asking undergraduates at a Canadian university who played team sports to say why people join, leave, or stay in groups. Open-ended questions were used. Then sixty students who were part of swimming, cross-country running, or cheerleading teams were asked the same questions. The most popular responses were combined with definitions of cohesion from 29 articles found in a literature search to produce the item pool. A total of 354 items were reduced to 53 by five experts. This was GEQ version 1. Two hundred and twelve university players from twenty teams were given this questionnaire to complete. Item analysis reduced the items to 24 which discriminated most between respondents. The final version of the GEQ was reduced to eighteen items with more respondents. The use of both positively and negatively worded items combats "response acquiescence" or "agreement (or disagreement) tendency", where individuals give the same answer without paying attention to the question. But how the positive wording is changed to negative wording is important. For example, "I am satisfied with my job" rephrased to "I am not satisfied with my job" leaves the possibility of misreading, so "I hate my job" would be better (Eys et al 2007). Eys et al (2007) compared the responses to the GEQ using the official version (12 negatively and 6 positively worded items), and a modified version (with all positively wording). For example, "I do not enjoy being part of the social activities of this team" changed to "I enjoy being part of the social activities of this team". The meaning of the items was not altered. The 276 participants were undergraduate team sports players at a Canadian university. The modified version was found to have better internal reliability. 5 18 items divided into 4 for ATGT, 5 for ATGS, 5 for GIT, and 4 for GIT.


2.3. TEAM COHESION AND PERFORMANCE The social cohesion model predicts that groups "which succeed in reaching their goals, should be m ore cohesive than those which do not. Failure, defeat, deprivation, or other negative outcomes related to group membership should reduce intra-group cohesiveness" (Turner 1981 quoted in Taylor et al 1983). Martens and Peterson (1971) was the first well -known study of the relationship between team cohesion and performance. Based on interviews with 1200 male university athletes in the USA, it was found that h ighly cohesive teams were more successful than low cohesi ve ones, and this produced more satisfaction and cohes ion. A "circular relationship between satisfaction, cohesiveness, and success" (figure 2.1).

Figure 2.1 - Circular relationship between cohesion , performance and satisfaction. Twenty years later, Widmeyer et al (1993) revi ewed the studies finding that 83% of them supported a po sitive relationship between cohesion and performance: "ath letes on successful teams perceive the team to be more cohesive, while athletes on unsuccessful teams perc eive the team to be less cohesive" (Turman 2003) 6. But Mullen and Copper (1994) suggested that th e relationship between cohesion and success was only modest. While Grieve (2000) fund that performance h ad more impact on cohesion than cohesion on performanc e 7.

6 Why does team cohesion lead to team success? Paskevich (1995; quoted in Carron et al 2002) suggested that cohesion creates a collective efficacy (a feeling of being able to succeed) that leads to the team success. 7 Carron et al (2002) highlighted problems with many studies of team cohesion and success, including small sample size (eg: less than eight teams), not real sports teams (ie: artificially created groups), measurement of cohesion with psychometrically established tests or not, and whether to compare cohesion or task cohesion with success. Hoyle and Crawford (1994) pointed out that a "single score that represents the thoughts, feelings, or behavioural tendencies of the group results in a loss of


In studies of this relationship, what should b e the unit of analysis? Carron and Spink (1995) replied: "The answer, of course, is that there is no definitive a nswer - it depends on the nature of the question. Cohesio n is a cognition that exists in the minds of individual gr oup members. If the question of interest is centred on the relationship of cohesiveness to individual behaviou r - adherence for example - then the individual's cogni tion about cohesion is the critical consideration... Conversely, if the focus was on a group behaviour - group performance for example - then the average level of cohesion in the group would be the appropriate unit of analysis" (quoted in Carron et al 2002 p120). Carron et al (2002) preferred to concentrate o n the relationship between task cohesion and team success , using 294 Canadian university male and female playe rs from eighteen basketball and football teams. Team s uccess was operationalised as the percentage of games won in the regular season, and task cohesion was measured by t he GIT and ATG-T items of the GEQ completed two weeks befo re the

end of the season. The GEQ scores were found to be significantly positively correlated to the team success overall (r = 0.57 GIT; r = 0.67 ATG-T), and also for each sport separately. Cox (1990) suggested that the relationship between cohesion and performance was mediated by the level of interaction of the players in the team - high (eg:

football, basketball) or low (eg: golf, bowls) 8. High team cohesion in high interaction sports leads to g ood performance, but produces poor performance in low interaction sports (figure 2.2). For example, Lande rs and Luschen (1974) found a negative relationship betwee n cohesion and success among ten-pin bowling teams. Mullen and Copper's (1994) meta-analysis of 49 studies of different types of groups did not find t hat interaction was a moderating factor.

information about the character of the group" (quoted in Carron et al 2002 p124). 8 Also known as coacting sports.


Figure 2.2 - The relationship between cohesion and performance in high and low interaction sports. Stogdill (1972) emphasised the importance of g roup norms, particularly for productivity, as interactin g with cohesion to influence performance. Norms for high productivity (all players working hard) and high te am cohesion produces good performance, but high team cohesion and low productivity norms leads to poorer performance (figure 2.3).

Figure 2.3 - The relationship between productivity norms, cohesion, and performance.


Taylor et al (1983) presented an example of a losing team that continued to have high team cohesion. The attribution of the cause of failure was important ( ie: group-serving attributions by individual members). The researchers found that responsibility for losing wa s attributed to the whole group rather than to indivi duals or sub-groups (diffusion of responsibility), while individuals took responsibility for failure themsel ves at the same time. Taylor et al followed a college men's ice hock ey team over a 25-game season, and interviewed each pl ayer soon after each game. The questionnaires explored t he attributions made for winning or losing based on th ree types - internal (the whole group, my sub-group - a ttack or defence, self), external within-group (other individual players, other sub-group), and external (eg: luck, referee). The team won three games in the sea son. The rating of team cohesion remained high thro ughout the season with similar ratings after each game. Ta ylor et al concluded: "This pattern is not typical of sh ort-term laboratory experiments, suggesting that good interpersonal relations, which are more crucial in long-standing groups, may explain the predominance of th e group-serving pattern" (p197). 2.4. ATTRIBUTIONS An attribution is "an explanation advanced to account for a specific outcome or behaviour" (Marti n and Carron 2012 p157). Individuals and teams will make attributions about their wins and losses. Weiner (1972) outlined four types of attributi on - ability, effort, task difficulty, and luck (table 2 .1).

Table 2.1 - Four types of attribution for winning a nd losing. Weiner (1985) preferred to use three dimension s of attribution: i) Locus of causality - The extent to which th e cause of winning or losing is down to the individua l (internal) or other reasons (external).

ATTRIBUTION WIN LOSS

Ability More skilled than opponents. Opponents more skilled.

Effort More effort by us. More effort by them.

Task difficulty We mastered course. Course very difficult.

Luck We were lucky. We were unlucky.


ii) Stability - Whether the causes change over time (stable/unstable). iii) Controllability - The extent to which an individual has control over the causes of winning o r losing (controllable/uncontrollable). Winners are more likely to attribution their s uccess as internal, stable, and controllable (eg: work har der), and losers as external, unstable, and uncontrollabl e (eg: bad refereeing decisions). This is called the "self -serving bias" (Martin and Carron 2012) (table 2.2).

Table 2.2 - Attributions of loss and future perform ance. Coffee and Rees (2011) tested experimentally t he prediction that a single failure would not lead to poorer future performance if individuals believed the circumstances were controllable and/or unstable, bu t would reduce performance if attributions of uncontrollable and stable were made. Participants, who were students in England, were asked to throw three darts at a dartboard while blindfolded. The first set of throws established the baseline performance of each partic ipant (a score out of 30), but was also used to give nega tive feedback. All participants were told that they had scored six points, and were given a reason why (based on f our conditions): � Controllable/stable (CS). � Controllable/unstable (CU). � Uncontrollable/stable (US). � Uncontrollable/unstable (UU). The participants then threw the darts again. T he participants in the CS and CU conditions showed improvements in performance between the baseline an d the second throwing, while participants in the US showe d a decline. The participants in the UU condition showe d an improvement. Subsequently, the participants were given cont rary feedback before a third set of throws. For example, individuals in the US condition were given informat ion that put them in the CS condition. Performance on t he

CONTROLLABLE UNCONTROLLABLE

STABLE I lost because my tactics were poor, and that will not change - decline in future performance.

I was unlucky and that will not change - decline in future performance.

UNSTABLE I lost because my tactics were poor, but that can be changed - improved performance in future.

I was unlucky, but I could be lucky next time - performance unchanged in future.


last throwing improved when the feedback was linked to controllable and/or unstable attributions. Much research has looked at this process for individual athletes, but it also occurs with the performance of a team ("team-serving bias") (Mullen and Riordan 1988). Team-oriented attribution is usually measured by questionnaires like the Causal

Dimension Scale for Teams (CDS-T) (Greenlees et al 2005). Martin and Carron (2012) performed a meta-anal ysis on twenty-one studies of team-serving bias confirmi ng its existence in a variety of team sports 9. Thus individuals emphasise internal factors like team ability as the cause of the win, and downplay these for a loss. Team-ser ving bias occurs in relation to "self-threat" ("when favourable views about oneself are questioned, contradicted, impugned, mocked, challenged, or othe rwise put in jeopardy") (Baumeister et al 1996). Social Identity Theory (Tajfel and Turner 1979 ) has also been applied to explain the bias. This is wher e individuals gain their sense of self from group membership, while being motivated to enhance their self-esteem. These are achieved by seeing their own grou p (ingroup) as better than other groups (outgroups). This is confirmed after winning, but threatened after lo sing. So, in the latter case, the need to blame external reasons for the loss. 2.5. ROLE OF COACH Coaches' feedback to players and their interac tions with them (including the "motivational climate" and "goal-reward structure) influence the players' beli efs and behaviours. In a mastery (task-involving) clima te, coaches emphasise effort, learning, self-improvemen t, and skill mastery as compared to the focus on compariso ns between players and mistake punishment of the perfo rmance (ego-involving) climate. Players in the former clim ate defined success in terms of learning and improvemen t rather than outperforming others (even showing more pro-social behaviours), while the opposite was the case in the performance climate (Stuntz and Garwood 2012).

9 The meta-analysis found no gender differences in team serving bias, nor age differences, nor team size (<12 vs >12 players), nor skill level (competitive vs recreational). Previous research had found, for example, that male teams only use it.


In terms of motivational climate and goal-rewa rd structures, Stuntz and Garwood (2012) compared competitive (rewards for beating others), individua listic (self-improvement), and co-operative (success of gr oup) types. One hundred and ninety-eight US students wer e randomly divided into one of these three conditions to play a social dilemma game in pairs. Each player ma de a choice from a payoff matrix presented (figure 2.4). In the competitive condition, participants were told t hat scoring more points than the partner was the goal o f the game, while the instructions in the individualistic condition emphasised self-improvement. In the co-operative condition, the goal was the most points f or the pair. Participants played three sets of ten games.

(Based on Stuntz and Garwood 2012 figure 1 p264)

Figure 2.4 - Payoff matrix used 10. The participants tended to describe success an d failure in the game based on the instructions given . However, interestingly, the co-operative group scor ed most individual points (mean: 89.01) followed by th e individualistic group (mean: 74.31) and the competi tive group last (mean: 62.06). So, in team sports at lea st, promoting co-operative goals appears to produce bet ter results than emphasising competitive or individuali stic ones. 2.6. APPENDIX 2A - LEADERSHIP AND COHESION Leadership by coaches/managers based on social support, training and instruction, positive feedbac k, and being democratic is better at producing team cohesi on than an autocratic leadership style (Turman 2003). Among professional basketball players in Iran, Moradi (2004) found that a player's perception of t eam

10 Choice A was viewed as more collaborative as more points are scored for group, and choice B as more competitive as it brings more points for the individual (Stuntz and Garwood 2012).


cohesion was associated with perception of the coac h showing democratic behaviour, training and instruct ion, social support, and positive feedback, and not bein g autocratic or using punishment-oriented feedback. The coach's leadership behaviour can be measur ed using the Leadership Scale for Sport (LSS) (Chellad urai and Saleh 1980) 11 which has five dimensions - training and instruction (TI), positive feedback (PF), socia l support (SS), democratic behaviour (DB), and autocr atic behaviour (AB) (table 2.3). There are 40 items (13 measuring TI, 9 for DB, 5 AB, 8 SS, and 5 PF). Item s include: "My coach sees to it that athletes work to capacity", rated on a five-point scale from "always " to "never". There are three versions of the LSS - the athl ete's preference for coaching behaviour, the athlete's perception of coaching behaviour, and the coach's perception of their own behaviour. � Training and instruction - coach's role in improvin g the

performance level of the player; eg: "specify in de tail what is expected of each athlete", "figure ahead on what sh ould be done", "point out each athlete's strengths and weaknesses" .

� Democratic behaviour - coach permits participation of players in

decision-making; eg: "let his athletes share in dec ision-making", "let athletes work at own speed", "let the group se t its own goals".

� Autocratic behaviour - coach keeps apart from team and emphasises

their authority; eg: "not explain his action", "kee p to himself", "refuse to compromise a point".

� Social support - coach's role in satisfying interpe rsonal/social

needs of team and members; eg: "look out for the pe rsonal welfare of the athlete", "invite athletes to his home", "do personal favours to the athletes".

� Positive feedback - coach uses positive comments; e g: "tell an

athlete when he does a particularly good job", "giv e credit when credit due", "see that an athlete is rewarded for a good performance".

Table 2.3 - Dimensions of the LSS. Ramzaninezhad and Hoseini Keshtan (2009) gave the LSS and the GEQ to 264 players in twelve football t eams

11 In the first stage of the development of the LSS, 160 physical education students at a Canadian university responded to 99 items about the ideal coach taken from existing leadership scales and adapted. Thirty-seven items were taken as relevant and added to thirteen new items. This revised questionnaire was given to 102 more physical education students and 223 university athletes from different team sports at other Canadian universities. Analysis of the responses lead to 40 items for the LSS.


in the Iranian professional league at the end of th e 2006-7 season. Positive leadership behaviours (TI, DB, SS, and PF) were significantly positively correlate d with task and social cohesion, and significantly negativ e correlated with AB (figure 2.5). Comparing successf ul and unsuccessful teams, the former were more cohesive a nd their coaches had higher levels of DB and SS.

(Data from Ramzaninezhad and Hoseini Keshtan 2009 t able 2 p116)

Figure 2.5 - Correlations between leadership behavi ours and cohesion. Turman (2003) surveyed fifteen male athletes f rom six sports (eg: baseball, swimming) and fifteen fem ale athletes from six sports (eg: gymnastics, volleybal l) at an Iowa university in the USA about what coaching behaviours motivated or demotivated them. Turman (2 003) also interviewed in-depth twelve male college US fo otball players. The most important motivating behaviours were inspiration, the quality of personal relationship, and support. While the athletes were demotivated by abu sive language and ridicule, a superior-subordinate relationship, and unequal treatment of players. Among the US football players, joking and team prayer were also reported as motivating as well as the coach's enthusiasm. As one player said: "When we se e one of our coaches get pumped up it usually pumps the t eam up and we will usually pump each other up so we kind o f together everybody pulls together and kind of pump each other up in a way that it will help you. You are ki nd of saying that you are getting pumped up so that I can get out there and play for you not only myself. So it b rings unity a majority of the time" (Turman 2003 p99). Effective leadership involves good relationshi ps with team members, which can produce greater indivi dual enthusiasm and team cohesion (Van Breukelen et al 2 012).


But coaches may behave differently towards differen t members of the team. This includes support, attenti on, positive and negative feedback (social-related differential treatment), and "career opportunities" (eg: captaincy, playing time, substitution) (task-relate d differential treatment). This is covered by the lea der-member exchange (LMX) theory (Graen et al 1982). Sias and Jablin (1995) explored this idea in a work situation with 29 employees. Employees with poor relationships with their supervisors (low-quality L MX relations) perceived differential treatment by the supervisors as unfair, while employees with high-qu ality LMX relations saw the treatment as fair. Van Breukelen et al (2012) investigated the ef fect of differential treatment on team atmosphere and performance among 605 players in 69 amateur sport t eams in the Netherlands, including hockey, football and volleyball. The researchers hypothesised that playe rs who perceived a high degree of task-related and/or soci al-related differential treatment by the coach of thei r team would view the team atmosphere and performance as l ess positive than players who perceived a low degree of differential treatment. Differential treatment by the coach was measur ed on a five-point scale in response to the following fou r questions for social-related: "Does your coach expr ess his/her sympathy more often to some players than to others?"; "Does your coach prefer some players in y our team to others, based upon their personality?"; "Is your coach more likely to point out the mistakes of cert ain players than those of others?"; "Is your coach more likely to give compliments to some players than to others?". Task-related differential treatment was measured by perceived differences in playing time, and number of times substituted in the season. Data wer e collected towards the end of the season in 2005, 20 06, and 2007. Team members who perceived a high degree of differential treatment rated the team atmosphere le ss positively in relation to social-related and not ta sk-related treatment, but no difference in perception of team performance. Such team members also had a lowe r-quality LMX relationship. Van Breukelen et al (2012 ) concluded: "The results of the present study indica te that team leaders should, therefore, refrain from s ocial differential treatment" (p59). Van Breukelen et al admitted that the measures were all self-reports at one point in the season, and th e direction of causality could not be established.


3. HOME ADVANTAGE 3.1. Factors in home advantage 3.2. Research examples 3.3. Home disadvantage 3.4. Officiating 3.1. FACTORS IN HOME ADVANTAGE Teams perform better at home compared to away. This is known as the home advantage 12, and has been observed in many US professional sports (eg: basketball, bas eball) as well as elsewhere (eg: football in UK). Home tea ms win approximately 60% of games (compared to 50% by chan ce) (Jamieson 2010) 13. Research has found moderating variables for th e home advantage (Jamieson 2010): � Sport type - individual/team (both show home

advantage). � Level of competition - amateur/professional (both

show). � Time era - home advantage stronger before 1950. � Season length - longer season reduces advantage. � Game type - home advantage stronger for important

games. � Sport - less for baseball, golf, cricket, and US

football, and highest for football 14 15. An explanation for the home advantage includes factors associated with location which influence th e players', coaches' and officials' psychological sta te (Carron et al 2005) 16 17. This model includes:

12 Defined as "the term used to describe the consistent finding that home teams in sport competitions win over 50% of the games played under a balanced home and away schedule" (Courneya and Carron 1992 p13). 13 In the English football Premiership, home teams had an advantage on average of 1.5 goals to 1.1 by the away team (1992-2006 data) (Boyko et al 2007). 14 Courneya and Carron (1992) calculated the following percentage of wins for home teams - baseball 53.5%, US football 57.3%, ice hockey 61.1%, basketball 64.4%, and football 69.0%. 15 Carron et al (2005) included the following factors - gender (both show), international competitions (greater than national ones), and judged events (eg: figure skating) have more home advantage than objectively determined events (eg: speed skating). 16 Originally proposed by Courneya and Carron (1992) as feed-forward model.


� Game location - home/away. � Game location factors - crowd (size, density,

behaviour, noise, perception of competitors); learning/familiarity 18 (pitch size, pitch type - eg: artificial turf) 19; travel (distance, "jet lag", time together - eg: team stays in hotel); rule (local variations in playing conditions).

� Critical psychological states - players (eg: less

anxious, more self-confident), coaches (eg: belief that home support important), and officials.

� Critical behavioural states - players (eg: level of

aggression), coaches (eg: different tactics), and officials (eg: correct decisions).

� Performance outcomes - primary (fundamental level o f

performance - ie: skills involved in sport), second ary (scoring), and tertiary (ultimate outcome - win/los s).

3.2. RESEARCH EXAMPLES Balmar et al (2001) used data from twenty Wint er Olympics in twelve different countries between 1908 and 1988. Home advantage was calculated controlling for nation strength and number of medals on offer, and the removal of non-hosting nations. This left 12 sports and three countries to compare home and away - France ( host on three occasions), Norway (twice), and Japan (twi ce). Overall, there was a significant home advantage for both medals won and points (eg: gold = 3 points etc). In subjectively scored events, like figure skating, th ere was a stronger home advantage than for objectively measured sports (eg: time taken to complete race). Familiarity with local conditions had some effect i n alpine skiing, but not bobsled and luge. Distance travelled in terms of time zone crossed had no relationship to performance. Home advantage may be explained by social

17 Jamieson (2010) saw game-context factors (eg: season length, type of size) as influencing the size of the home advantage. 18 This variable is moderated by the quality of the team such that "moving to a new facility was beneficial for low-quality teams but reduced the home advantage of high-quality teams" (Carron et al 2005 p399). 19 Home advantage from familiarity with local conditions has not been found in sports where local conditions vary little, like basketball and baseball, but some advantage in football with artificial playing surfaces (eg: Barnett and Hilditch 1993) or unusual pitch characteristics (eg: Clark and Norman 1995). Variations in venue are prominent in alpine skiing, for example, where there is a clear home advantage (Bray and Carron 1993).


facilitation. Zajonc (1965) proposed that the prese nce of others improves dominant responses (ie: familiar/we ll-learned or simple tasks) and reduces non-dominant responses (ie: unfamiliar/novel or complex tasks). Based on this, Henningsen et al (2007)predicte d that high-ability basketball teams would have a stronger home advantage than low-ability teams. Data from the 200 0-1 US college basketball season were used. High-ability t eams had a greater home advantage for general shooting, but not for free-throw or three-point throwing. Studying real-life sports competition means th at researchers have limited control over variables com pared to artificial tasks in laboratory conditions. Howev er, there are circumstances when a "natural experiment" is possible. For example, due to a measles epidemic, t wo US university basketball teams had to play eleven game s without spectators. Their performance improved (eg: total points scored) compared to the presence of the spec tators (Moore and Brylinsky 1993). This challenged the ide a that the crowd explains the home advantage. Moore and Brylinsky (1995) seized the opportun ity to study US college basketball teams who had to play t heir home games at different venues while a new facility was being built. These teams still showed the home adva ntage, and this challenges the role of familiarity in it. 3.3. HOME DISADVANTAGE In high pressure situations like finals, home advantage can be detrimental as in the home "choke" (Baumeister and Steinhilber 1984). "In high-pressur e situations, where the outcome of the game is on the line, home team competitors may be attempting to carry ou t their performance, whilst worrying about the possib ility of disappointing and/or losing support from their f ans, trying to live up to perceived audience expectation s, and dealing with the physiological stress that arises i n such situations. This 'attention-induced disruption' has been shown to result in poor performances, as the elevat ed pressure may increase self-consciousness and anxiet y and/or result in a shift of attentional focus to distracting stimuli..." (McEwan et al 2012 p279). T his is less of an issue for away teams. There is contrary evidence about home advantag e and disadvantage. McEwan et al (2012) used data from th e National Hockey League (NHL) shootouts 20 in North America between 2006-7 and 2010-11. Only outcome-imminent g ames

20 This is like a penalty shootout in football when the scores are tied at full time, involving the best of three shots (ie: three shooters per team).


were used (ie: those that determine a team's season). The shootouts were categorised as loss-imminent (LI) (scoring ties the game and missing means a loss), win-imminent (WI) (scoring means a win), or non-outcome-imminent (NOI) (scoring or missing does not determine the outcome of the game) (table 3.1).

Y = score; X = miss; ? = shot to come; - = not take n yet

Table 3.1 - Examples of types of shots. Analysis of the data showed that away teams we re significantly worse than home teams in LI situation s (27% vs 36% success), but significantly better in WI situations (34% vs 27%) (figure 3.1). Thus there wa s a home advantage in the former situation (shooting to avoid a loss) and a home disadvantage in the shooting to win situation.

(Data from McEwan et al 2012 table 1 p581)

Figure 3.1 - Percentage success in shootouts.

Type of shot Team A Team B

Lose-imminent (one goal down) YYY YY?

Lose-imminent (two goals down) YY X?

Win-imminent (tied) YYX YY?

Win-imminent (one goal up) XY- XY?

Non-outcome-imminent Y ?


3.4. OFFICIATING It seems that subjective decisions by official s favour home teams, but this generalisation is limit ed by variables like differences in performance between h ome and away teams (Carron et al 2005). The key moderating factor in "referee bias" se ems to be crowd noise. Nevill et al (2005) showed this in a laboratory experiment. Forty qualified football ref erees (from North Staffordshire, England) made decisions on 47 incidents from the video-taped English Premier Leag ue match between Liverpool (home team) and Leicester C ity (away) (from 1998-9 season) in conditions of crowd noise or silence. Each incident was rated as home foul, a way foul, no foul, or uncertain. The number of fouls ca lled against the away team did not vary between the two conditions (mean: 9.9 with noise and 9.3 in silence ), but less fouls were given against the home team in the noise than the silent condition (mean: 12.5 vs 14.8). Boyko et al (2007) focused on the performance of 50 individual football referees in the English Premier ship between 1992 and 2006 (using data from statistical databases). Overall, home teams received fewer caut ions and dismissals than away teams (1.2 vs 1.6 yellow c ards, and 0.06 vs 0.09 red cards per game) 21. Increasing crowd size led to significantly less yellow cards to home teams, and increasing crowd density (number of peop le in crowd relative to stadium's capacity) produced more yellow cards to away teams. At an individual level, referees varied in the number of cautions/dismissals and penalty kicks giv en to home and away teams, such that some referees were "responsible for at least some of the observed home advantage" (Boyko et al 2007 p1192). But this effec t declined with years of refereeing experience. Boyko et al (2007) concluded: "Most commentato rs accept home advantage as a legitimate and fair part of the game, presumably because most people assume tha t the crowd's main effect is to inspire their players to perform better. While subconscious referee bias doe s not necessarily make home advantage unfair, our finding of significant variation in home advantage by referee is hard to accept as fair" (p1193). Ansorge and Scheer (1988) observed that the "e ffects of biased officiating are potentially most dramatic in sports in which the officials actually score the po ints through judging the performance of athletes with so me combination of objective and subjective criteria" ( quoted

21 Yellow cards are given in football as a first offence, and two yellow cards equal a red card (dismissal from the game). A red card can be given immediately for certain offences (eg: dangerous tackles).


in Balmer et al 2001). Gymnastics is one such sport . Ansorge and Scheer (1988) reported that, in the 198 4 Olympic Games, judges scored their own gymnasts hig her than the mean of the other judges 282 times and low er only 29 times. Furthermore, in the case of gymnasts in close competition to their own country's, they scor ed the other country's athlete lower than the mean 399 tim es and higher 190 times.


4. INDIVIDUAL DIFFERENCES BETWEEN PERFORMERS 4.1. Cognitive abilities 4.2. Anxiety and confidence 4.3. Mental toughness 4.3.1. Techniques to help confidence and performance 4.4. Extreme sports 4.1. COGNITIVE ABILITIES "In sport, as in other domains such as science , music and the arts, the attainment of excellence is the primary goal of many individuals. Spectators marvel at expert performance, coaches endeavour to nurture th eir proteges towards new heights of achievement and ath letes aspire to reach 'greatness'" (Williams and Reilly 2 000 p657). Talent is a scarce commodity, which has an i nnate element as well as being able to be developed if sp otted early. Its detection is "the discovery of potential performers who are currently not involved in the sp ort in question" (Williams and Reilly 2000). "Talent identification" is the general name gi ven in sports psychology to the search for particular trai ts or variables that predict successful sport behaviour 22. The variables studied include body type and size 23, speed and endurance, and anxiety. "However, as for personalit y traits, no clear correlations between these variabl es and sport success have been established" (Vestberg et a l 2012). Perceptual-cognitive skills are another set of variables studied. These relate to how information is processed, particularly in a complex and quickly ch anging environment (eg: pattern recognition, strategic dec ision-making, and "knowing where and when to look"; Mann et al 2007) 24. Sport specific cognitive skills have been compared in novices and experts. For example, exper t footballer players can recognise and recall pattern s of

22 Williams and Reilly (2000) defined talent identification specifically as "the process of recognising current participants with the potential to become elite players". Talent development is the provision of a suitable environment to help the individual reach their potential, and talent selection "involves the ongoing process of identifying players at various stages who demonstrate pre-requisite levels of performance for inclusion in a given squad or team" (Williams and Reilly 2000). 23 For example, young players have "greater biological age" (ie: physically mature), and have better physiological fitness (Williams and Reilly 2000). 24 Mann et al (2007) defined perceptual-cognitive skills as "the ability to identify and acquire environmental information for integration with existing knowledge such that appropriate responses can be selected and executed" (p457).


play better than inexperienced players (Williams 20 00) 25. Vestberg et al (2012) were interested in the difference between novices and experts in general cognitive skills - for example, "executive function s", which include the division of attention, the abilit y to adapt quickly, multi-tasking, and dealing with nove lty. The researchers recruited male (n = 14) and fe male (n = 15) players from the top football league in Sw eden (high division - HD), and male (n = 17) and female (n = 11) players from the lower leagues (lower division - LD). The players completed standard tests of executive functions including joining all the dots in a squar e with one line in sixty seconds (known as "design fluency "). This was done several times, which tested creativit y, memory and inhibition of automatic responses as the same solution could not be used twice. The HD players had significantly higher scores (mean: 15.52) than the LD players (mean: 13.18), wh o, in turn, were higher than the population means (mean: 10.0) (figure 4.1).

(* = significantly different; p<0.0005) (Source: doi:10.1371/journal.pone.0034731.g001)

Figure 4.1 - Mean scores on design fluency test.

25 Skilled players as compared to less skilled ones: � Have faster and more accurate recognition and recall of patterns of play; � Anticipate better opponents' actions from visual cues; � Have more effective visual search behaviours (eg: spotting player available to receive pass); � Have a more accurate assessment of outcomes from certain circumstances (Williams and Reilly

2000).


Then data on the players' goals scored and ass ists in the next two seasons were collected. The scores on the executive function tests significantly correlated w ith goals and assists (r = 0.54). Thus general executiv e functions are important in success in football. "In ball-sports like soccer there are large amounts of infor mation for the players to consider in every new moment. Th e successful player must constantly assess the situat ion, compare it to past experiences, create new possibil ities, make quick decisions to action, but also quickly in hibit planned decisions. Thus, several core-features of executive functions such as planning, sustained and divided attention, suppression of previous response s, and working memory capacity are important for a team pl ayer in soccer" (Vestberg et al 2012). In a meta-analysis of 42 studies, Mann et al ( 2007) reported that experts in different sports were bett er than non-experts in picking up perceptual cues (eg: measured by response accuracy and response time 26), and in visual search behaviours (eg: measured by fewer visual fixations of longer duration). "These findings supp ort the interpretation that experts in sport extract mo re task-relevant information from each fixation than d o lesser skilled performers" (Mann et al 2007). 4.2. ANXIETY AND CONFIDENCE Competitive sportspeople face stress in compet ition. Martens et al (1990a) defined stress as "the proces s that involves the perception of a substantial inbalance between environmental demand and response capabilit ies under conditions in which a failure to meet demands is perceived as having important consequences and is responded to with increased levels of cognitive and somatic state anxiety". These anxieties can sometim es produce a decline in performance, and this is calle d "choking" at the extreme. Thus the interest in understanding anxiety in sport. Initially, performance was seen as an inverted -U on sports anxiety (or arousal) (Yerkes and Dodson 1908 ). Too much or too little anxiety/arousal produced poor performance, and a moderate level was optimal. This view saw anxiety as unidimensional. Martens et al (1990a) argued that sports anxie ty was multi-dimensional, and involved different relations hips with performance. Cognitive anxiety has a negative

26 There was a larger difference between experts and non-experts in response time in interceptive sports (eg: tennis) and strategic sports (eg: football), but the type of sport had no effect on response accuracy. Larger differences were also found in more realistic studies (Mann et al 2007).


correlation with performance, and is the "mental component of anxiety" caused by "negative expectati ons about success or by negative self-evaluation" (Mart ens et al 1990a). Somatic anxiety, defined as "the physiol ogical and affective elements of the anxiety experience th at develop directly from autonomic arousal" (Martens e t al 1990a), has a relationship to performance similar t o Yerkes and Dodson's idea (Craft et al 2003). Martens et al (1990b) added self-confidence as a third component 27, and performance has a positive correlation with it (figure 4.2).

Figure 4.2 - Predicted relationship between three components of CSAI-2 and performance. The Competitive State Anxiety Inventory-2 (CSA I-2) (Martens et al 1990b) was designed to measure these three components. It has 27 items, like "I am concerned a bout this competition" (cognitive anxiety), "I feel tens e in my stomach" )somatic anxiety), and "I feel at ease" (self-confidence), which are answered on a four-poi nt Likert scale 28. A number of studies have investigated the relationship between CSAI-2 scores and performance, with some supporting the reliability and validity of the

27 Vealey (1986) defined sport confidence as "the belief or degree of certainty individuals possess about their ability to be successful in sport" (p222), and divided it into trait (general) and state (situational). 28 Lane et al (1999) criticised the use of the word "concerned" in many items. "An athlete may respond as being concerned about the competition, but that concern may represent the athlete’s acknowledgment of the competition as an important challenge rather than anxiety. Lane et al. argue that using a term such as 'worried' would better assess anxiety, as this term is more reflective of the negative thoughts or expectations associated with anxiety" (Craft et al 2003 p49). Jones and Hanton (2001) argued that the CSAI-2 did not measure anxiety, only the symptoms associated with anxiety, "and that due to the wording of the inventory, it may actually be measuring other 'mislabelled' affective states" (Craft et al 2003).


questionnaire, and others not. One criticism has be en that "cognitive and somatic anxiety may not be independent of one another, and that cognitive anxi ety can have either a facilitative or a debilitative ef fect on performance, depending on the performer's level of physiological arousal" (Craft et al 2003). For example, Edwards and Hardy (1996) found th at, for self-reported netball performance among female players over a season, as self-confidence increased , more cognitive anxiety was perceived as helping performa nce. In studies with the CSAI-2, the operationalisa tion of "performance" is an issue. It can be measured by objective outcomes (eg: finishing time in a race), subjective outcomes (eg: evaluation by a judge), or self-perceptions. Each type of measure could correlate i n a different way with anxiety (Craft et al 2003). Anxiety and performance may also vary with team/individual sports, the type of skill involved in the sport, the amount of contact with an opponent (eg: tennis is directly facing them while gymnastics is competi ng against them without contact), and when the CSAI-2 is administered (Craft et al 2003). Craft et al's (2003) meta-analysis of 29 studi es (up to October 1999) found only a weak correlation betw een the three components of the CSAI-2 and performance. The overall correlation between cognitive anxiety and performance was 0.01 29, between somatic anxiety and performance was -0.03, and 0.25 for self-confidence and performance. Self-confidence and performance was the strong est relationship, particularly for individual sports, a nd for administration of the CSAI-2 at 31-59 minutes prior to competition 30 31. In terms of individual variables, the relationship between anxiety and performance was st ronger for "open skills" (those performed in changing environments; eg: tennis, basketball, netball) than "closed skills" (those performed in unchanging

29 Craft et al (2003) proposed a number of reasons for this finding including that there is no negative relationship between cognitive anxiety and performance, the CSAI-2 is unable to measure the relationship, or cognitive anxiety in isolation is not a good predictor of performance. 30 Craft et al (2003) wondered why the CSAI-2 was not predictive if completed just prior to competition: "Perhaps, in the time just before competition, athletes are not focused on answering the questionnaire or are already cognitively immersed in game preparation, game strategy, etc.... [or] athletes may be reluctant to report feelings of anxiety just prior to competition when they are planning for the performance at hand or trying to reach some favourable pre-performance state. In addition, for practical purposes the CSAI-2 could be distracting to the athlete if administered too close to competition" (p61). 31 Soyer (2012) found that sport confidence correlated with particularly strategies for coping with stress - namely, "refuge in religion" (eg: praying), "external assistance" (eg: asking for help), "cognitive restructuring" (eg: thinking about the problem in a different way), and "active planning". The latter two are problem-focused strategies, and the first two are emotion-focused strategies.


environments; eg: golf, gymnastics, rowing, weightlifting). While among higher-level sportspeop le (eg: elite/professional), cognitive anxiety had a positive correlation with performance (but no relationship for lower-level athletes) (Craft et al 2003). 4.3. MENTAL TOUGHNESS Mental toughness (MT) has its origins in the personality dimension, toughmindedness (tenderminde dness) proposed in Cattell's (1957) 16PF theory, and in Ko basa's (1979) hardiness in response to stress (Crust 2007) 32. MT "represents the ability of a person to cope with the demands of training and competition, increased determination, focus, confidence, and maintaining c ontrol under pressure" (Nicholls et al 2008 p1183) 33. Mentally tough individuals "tend to be sociable and outgoing ; as they are able to remain calm and relaxed, they are competitive in many situations and have lower anxie ty levels than others. With a high sense of self-belie f and an unshakeable faith that they control their own de stiny, these individuals can remain relatively unaffected by competition and adversity" (Clough et al 2002 p38 q uoted in Crust 2007 p275) 34 35. Overall, the characteristics attributed to MT by researchers, players, and coaches include coping effectively with pressure and adversity, recovering or rebounding from setbacks, persistence, being compet itive, having unshakeable self-belief, and being resilient (Crust 2007) 36. Middleton et al (2004 quoted in Crust 2007) di vided twelve characteristics found through interviews wit h elite athletes and coaches into "mental toughness orientations" (personality characteristics like sel f-belief) and "mental toughness strategies" (actions like emotion control). The latter being easier to train 37.

32 Clough et al (2002) saw MT as a "sport-specific form of hardiness" (Crust 2007). Kobasa (1979) described three elements to hardiness - commitment (involvement in task), control (feeling of influence over events), and challenge (belief that change is a challenge). 33 MT is "one of the most overused but least understood terms" in sports psychology (Crust 2007). 34 Many coaches see MT as the key characteristic in sporting success (eg: 82% of wrestling coaches; Gould et al 1987). Among Olympic champions, MT was rated as the most important mental skill in sporting success (Gould et al 2002). 35 For example, Jones et al (2002) listed twelve attributes of MT, with the most important being unshakeable self-belief in ability, and bouncing back from setbacks. 36 Thelwell et al (2005) asked professional footballers to rate the attributes of MT, and "having total self-belief at all times that you will achieve success" was most popular. Clough et al (2002) confirmed the perceived importance of such confidence among elite coaches and players of rugby league. 37 Though there is a nature-nurture debate about MT (Crust 2007).


Furthermore, these researchers saw different combin ations of attributes for different sports with a core set of characteristics. For example, tolerating physical p ain will be more important in rowing than snooker, wher eas coping with the emotional pain of failure is releva nt to

both (Crust 2007). Bull et al (2005) preferred the existence of different types of MT. For example, "'final-putt' mental toughness in golf is likely to be more related to mind-set and perhaps coping skills, whereas the mental toughness of a racing car driver taking calculated risks in a dangerous sport requires a somewhat different form of mental toughness. Furthermore, according

to Bull et al, an aspiring Olympic swimmer would ne ed to show yet another form of mental toughness to endure high volumes of training and peak in a one-off event (in contrast to season-long sports) in order to achieve his or her goals" (Crust 2007 p278). One measure of MT is the Psychological Perform ance Inventory (PPI) (Loehr 1986). It has 42 items 38 and seven sub-scales of self-confidence (in abilities), negat ive energy control (dealing with feelings like frustrat ion and coping with events outside of own control), att ention control (ability to focus), visualisation and image ry control (eg: picturing success), motivation (eg: perseverance), positive energy (eg: enjoyment), and attitude control (eg: positive thinking). Each item is scored on a five-point Likert scale giving a minimu m score of 42 (low MT) and a maximum score of 210 (hi gh MT) (table 4.1). Middleton et al (2004 quoted in Crust 2007) questioned the validity of the PPI. Golby and Sheard (2004) compared 115 rugby le ague players on MT and hardiness. Three levels of players were recruit ed with convenience sampling. International players came fr om four teams in the quarter finals of the 2000 Rugby League World C up, and SuperLeague and Division One players from clubs wit hout international players. MT was measured by the PPI, and hardiness by the Personal Views Survey III-R (PVS III-R) (Maddi and Khoshaba 2001), which has eighteen items, each rated on a four-point Likert s cale.

38 Eg: "I believe in myself as a player" (self-confidence); "I can remain calm during competition when confused by problems" (negative energy control); "I can clear interfering emotion quickly and regain my focus" (attention control); "Before competition, I picture myself performing perfectly" (visualisation and imagery control); "I can keep strong positive emotion flowing during competition" (positive energy control); "I am a positive thinker during competition" (attitude control).


International players scored significantly hi gher than other players on two elements of MT - negative energy con trol and attention control - and on hardiness. There were no significa nt differences between SuperLeague and Division One players.

(Data from Golby and Sheard 2004 table 1 p937) Figure A - Mean scores of three groups of rugby pla yers. Table 4.1 - Example of study using PPI. Middleton et al (2004 quoted in Crust 2007) developed the Mental Toughness Inventory (MTI) with 67 items based on twelve characteristics of MT 39. Clough et al (2002) produced the Mental Toughn ess Questionnaire 48 (MTQ48) with forty-eight items 40 focused on four areas - control (perceived control of circumstances), commitment (becoming involved in an event), challenge (to view change as an opportunity ), and confidence (high self-belief) 41. High scores on the MTQ48 significantly correla te with physical endurance (criterion validity) (eg: C lough and Earle 2002; table 4.2). Crust and Clough (2005) reported a significant positive correlation between MTQ48 scores and endurance time when forty-one undergradu ate male sports students were asked to hold a weight (1 .5% of body weight) for as long as possible. Levy et al (2006) compared athletes undergoing sport injury rehabilitation on the MTQ48. Higher scorers (ie: higher levels of MT) were more positive about the challenge of recovery, able to cope with pain more, and

39 Eg: "I focus on the task without getting distracted" and "I turn negatives into positives". 40 Eg: "I generally feel in control" and "I am generally confident in my own abilities". 41 An alternative measure of MT to the self-reported questionnaires is observation. Davis and Zaichkowsky (1998) asked coaches and talent scouts to rate ice-hockey players on behaviours like response to adversity, effort, and enthusiasm. These ratings, however, are subjective (Crust 2007).


had a better attendance at a clinic for physical th erapy than low scorers. Clough et al (2002) tested the resilience elem ent in an experimental task. High MT scorers performed the same whether given false positive or negative feedback, whereas low scorers performed significantly worse a fter negative feedback. MT correlates with coping strategies for deali ng with stressful events as well as optimism (Nicholls et al 2008). Norlander and Archer (2002) reported that op timism ("continual striving" rather than "giving up and tu rning away"; Scheier and Carver 1985) was the best predic tor of performance in young elite skiers, ski-marksman, an d

swimmers. Among ten-pin bowlers, higher skilled players (average ≥170 pins) showed higher MT than lower skilled players (average ≤135 pins), along with more planning, greater confidence in equipment and technique, more competitiveness, and fewer attributions to luck (Thomas et al 1996).

The individual VO² Max (maximum oxygen uptake ) was determined for 23 participants, who had to cycle for thirty mi nutes at 30%, 50%, and 70% VO² Max. They were asked at five, fifteen, and 25 minutes during the task to report the perceived physical de mands of exercise, the perceived mental demands, and overall effort re quired. Based on MTQ48 scores, the participants were divided into tw o groups for analysis (a split at the median score). High and low MTQ48 scorers did not vary on th eir perceptions of the task during the easiest workload condition (30% VO² Max). In the middle condition, there was some difference, but it was significant in the hardest workload condition (70% VO² Max) wit h the high MTQ48 scorers reporting less perceived physical and menta l demands and less effort required.

Figure B - Mean ratings of overall effort (out of 2 0) in two conditions.


Crust (2007) listed some limitations with the study: � No details about the participants (which limits ext rapolation to

different groups). � No details of controls for confounding variables (e g: some

participants may have undergone mental skills train ing). � Relatively small sample. � Split of group into two for analysis, whereas it wo uld have been

better to compare the highest and the lowest scorer s only. Two individuals close to the median may be in different groups but have scores very close together.

� The study is a correlation (which means that it is not possible to

say that MT caused perceptions. Crust (2007) pointe d out that "although differences are noted between the high an d low toughness groups at the high workload, it is not clear whethe r this is due to those who possess high levels of mental toughnes s under-rating the demands of the task, the low mental toughness g roup overrating, or a combination of the two" (p284).

Table 4.2 - Clough and Earle (2002). Nicholls et al (2008) recruited 677 athletes o f varying ages (15-58 years), abilities (beginner - international level), sports, and gender (454 males and 223 females) in the UK and Iceland. The volunteers completed a number of questionnaires including the coping inventory for competitive sport (CICS) (Gaudreau an d Blondin 2002), the MTQ48, and the Life Orientation Test (LOT) (Scheier and Carver 1985). The CICS has 39 it ems that cover different strategies for coping - task-orientated (thought control, mental imagery, relaxa tion, effort expenditure, logical analysis, and seeking support), distraction-orientated (distancing, and m ental distraction), and disengagement-orientated (disengagement/resignation, and venting of unpleasa nt emotions). The LOT has four positively worded items to measure optimism and four negatively worded for pes simism (and four fillers) (table 4.3).

Table 4.3 - Details of questionnaires used by Nicho lls et al (2008).

QUESTIONNAIRE NUMBER OF ITEMS

RESPONSE OPTIONS SCORE RANGE

CICS 39 5 point scale: (1) "does not correspond"; (5) "corresponds very strongly"

min = 39 max = 195

MTQ48 48 5 point scale: (1) strongly disagree; (5) strongly agree

min = 48 max = 200

LOT 12 4 point scale: (1) agree a little; (4) totally agree

optimism: min = 4; max = 16 pessimism: min = 4; max = 16


MT (high MTQ48 score) was significantly correl ated with more task-orientated coping and less of the ot her two types (figure 4.3). MT was also significantly positively correlated with optimism on the LOT (r = 0.56) and significantly negatively correlated with pessim ism (r = -0.46).

(Rectangle = p<0.01; oval = p<0.05; no box = not si gnificant) (Data from Nicholls et al 2008 p1187 table 2)

Figure 4.3 - Correlations between MTQ48 and differe nt types of coping with stress. Among forty Wushu (martial arts) at the 2006 Malaysian Intervarsity championships, medallists sc ored significantly higher on the self-confidence and neg ative energy control sub-scales of the PPI than non-medal lists (Kwan and Roy 2007). This study also looked at goal profiles of the athletes. Nicholls (1989) explained behaviour in a compe titive situation, say, as influenced by personal goals (described as task or ego related). Task (T) relate d goals are focused on the self (eg: "I work really h ard") and the ego (E) related ones on beating others (eg: "I can do better than may friends"). Together these tw o types of goals produce four goal profiles - high T/ high E, high T/low E, low T/high E, and low T/low E. Kwan and Roy (2007) found no difference in competition success in Wushu between the different goal profiles 42. However, a high T/moderate E profile was significantly correlated with better negative energ y control and better positive energy control (figure 4.4). This profile also had a higher overall PPI score th an

42 These were measured by the Task and Ego Orientation in Sport Questionnaire (TEOSQ) (Duda and Nicholls 1992). It has 13 items measured on a five-point Likert scale.


moderate T/low E and moderate T/moderate E profiles .

(A higher score = more self-confidence and greater control over negative energy) (Data from Kwan and Roy 2007)

Figure 4.4 - Mean scores on two sub-scales of PPI. Crust (2007) felt that, overall, MT "appears t o be multidimensional and most often associated with unshakeable self-belief, the ability to rebound aft er failures (resilience), persistence or refusal to qu it, coping effectively with adversity and pressure, and retaining concentration in the face of many potenti al distractions" (p288). 4.3.1. Techniques to Help Confidence and Performance Sport confidence can be improved by mental ima gery 43. But the type of imagery varies with the skill lev el of the athlete. Callow and Hardy (2001) explored the relations hip between confidence and imagery with 110 female netb all players in the UK. All the players had represented their county (one level below international), and they we re divided into those from lower ranked counties (lowe r skill level) and those from higher ranked counties (higher skill level). The State Sport-Confidence Inventory (SSCI) (Vealey 1986) was used to measure sport confidence. This has thirteen items (scored on a ni ne-point Likert scale) on beliefs about sporting abili ty. The Sport Imagery Questionnaire (SIQ) (Hall et al 1 998) was used to measure how often (from rarely (1) to o ften

43 Sport confidence was predicted from belief in internal locus of control, subjective well-being, and optimism among over 400 athletes in Turkey (including football, badminton, boxing, and volleyball). Internal locus of control was most important (Sar and Isiklar 2012).


(7) that five different types of mental imagery (ta ble 4.4) are used prior to a match. � Cognitive-general (CG) - strategies of the game (eg : "I can

imagine executing entire plays/programs/sections ju st the way I want them to happen in an event/game").

� Cognitive-specific (CS) - specific skills (eg: "I c an easily

change an image of a skill"). � Motivational general-mastery (MG-M) - dealing with challenging

situations (eg: "I imagine myself working successfu lly through tough situations").

� Motivational general-arousal (MG-A) - arousal and a nxiety (eg: "I

imagine the excitement associated with competing"). � Motivational specific (MS) - goal achievement orien ted (eg: "I

image myself winning a championship"). Table 4.4 - Five types of mental imagery. For lower skilled players, sport confidence wa s linked to MG-M and CG types of imagery, while highl y confident higher skilled players used more MS image ry than lower confidence players in this group. State sport-confidence can be influenced by "s elf-talk" - positive or negative thoughts of the athlet e. Self-talk also includes thoughts about an opponent, which can be viewed as "facts". For example, a tennis pla yer about to serve thinks that the opponent knows where the server will serve the ball. This is negative self-t alk or "mind-reading" in neuro-linguistic programming; NLP ). The server's performance is affected because they subsequently change their behaviour. NLP (Bandler and Grinder 1975) proposes differ ent techniques to deal with behaviours like negative se lf-talk. For example, the meta-model method challenges and re-structures the language used in negative self-ta lk in order to replace it with more positive ideas (eg: h ow do you know the opponent knows that?). Savardelavar and Bagheri (2012) taught this technique to half of thirty boxers at a club in Ind ia. The SSCI was used as the outcome measure. The SSCI score of the experimental group showed a significant improvement between baseline and post-NLP training. 4.4. EXTREME SPORTS Extreme sports with the large risk-taking elem ent are becoming increasingly popular. In terms of indi vidual differences between participants and non-participan ts,


sensation-seeking scores are significantly higher ( as measured by Zuckerman's Sensation Seeking Scale 44). Sensation-seeking is "the need for varied, novel an d complex sensations and experiences and the willingn ess to take physical and social risks for the sake of such experience" (Zuckerman 1983). Castanier et al (2010) found that men particip ating in high-risk sports like downhill skiing, rock clim bing, and skydiving, had low conscientiousness scores wit h high extraversion and/or high neuroticism scores compare d to controls. Monasterio et al (2012) explored the personali ty of 68 BASE jumpers who were recruited through one of t he researchers being a BASE jumper 45. BASE jumping involved jumping off fixed objects with an adapted parachute 46. It is much riskier (5-16 times) than skydiving, and ha s an average of one death per sixty participants (Monast erio et al 2012). Personality was measured with Cloninger's Temperament and Character Inventory (TCI) (Cloninge r et al 1994a), which is a 235-item questionnaire (TCI-2 35) that assesses four dimensions of temperament and th ree of character (table 4.5) 47. Items include (Cloninger et al 1993): � I often feel that I am the victim of circumstances

(self-directedness); � People involved with me have to learn how to do thi ngs

my way (cooperativeness); � I seem to have a "sixth sense" that sometimes allow s me

to know what is going to happen (self-transcendence );

44 Respondents choose from two options for each item - eg: "when I go on a vacation I prefer the comfort of a good room and bed" vs "when I go on a vacation I prefer the change of camping out"; "I enjoy the thrills on watching car races" vs "I find car races unpleasant" (Zuckerman et al 1964). 45 87% were male and 58% single with a mean age of 34 years old (range 21 - 68 years). The mean number of years jumping was 5.8 (range 0.5 - 17 years) with the mean total jumps being 286 (range 12- 2300). 46 BASE = building, antenna, span (of bridges, for example), or earth (eg: cliffs). 47 Cloninger (1987) argued for a genetic basis to these dimensions. For example, novelty seeking has been linked to differences in dopamine transmission (as in the DRD4 gene) (Keltikangas-Jarvinen et al 2004). In a large-scale study in Finland, Keltikangas-Jarvinen et al (2004) showed an interaction between the DRD4 gene and the environment during childhood. A NS score (as measured by the TCI) was collected from 2149 20-35 year-olds on the 1997 Cardiovascular Risk in Young Finns Study. The top 10% highest scorers and the 10% lowest scores (n = 154) were further analysed. Mothers reported details of the childhood environment of this sample including emotional distance, disciplinary strictness, and level of tolerance of child's normal activity. Completed data were only available for 92 individuals. There was a significant interaction between the environment and the DRD4 gene. Children raised in a more hostile environment, who had a particular version of the DRD4 gene, were more likely to be high NS scorers, but not if the environment was not hostile.


� Often I feel that my life has little purpose or mea ning (self-directedness).

(Source: Monasterio et al 2012 p392-393)

Table 4.4 - Dimensions of personality measured by T CI-235. The BASE jumpers showed significant difference s to 181 age-matched controls (Cloninger et al 1994b) (f igure 4.5): � Higher - novelty-seeking (NS) (p<0.001) 48, self-

directedness (SD) (p<0.05) 49. � Lower - harm avoidance (HA) (p<0.001), reward

dependence (RD) (p<0.05) 50, self-transcendence (ST) (p<0.001) 51.

48 These individuals enjoy exploring unfamiliar places and situations, are easily bored, and are impulsive, seeking out thrills. 49 "As SD refers to self-determination and maturity, or the ability of an individual to control, regulate and adapt behaviour to fit the situation in accord with individually chosen goals and values, it is unsurprising that BASE jumpers scored high on this measure. High SD with an emphasis on discipline and skill acquisition may also help to explain why BASE jumpers engage in risk-taking behaviours by normative rather than impulsive/disorganised antisocial means (such as drug use and criminal behaviour)" (Monasterio et al 2012 p397).. 50 Manifest as less concern about the approval of others. 51 "ST is a character trait that in general denotes a propensity to religious and transpersonal experience, and a tendency to self-forgetfulness. As BASE jumping requires a high level of performance under extreme stress, meticulous attention to detail and split-second decision-making, a capacity for sustained focus over prolonged periods of time, and in situations of physical and psychological stress is

TEMPERAMENT CHARACTER

� Novelty seeking (NS) - a tendency to activate or initiate new behaviours with a propensity to seek out new or novel experiences, impulsive decision-making, extravagance, quick loss of temper, and active avoidance of frustration.

� Harm avoidance (HA) - a tendency to

inhibit behaviours with a propensity to worry in anticipation of future problems, fear of uncertainty, rapid fatigability, and shyness in the company of strangers.

� Reward dependence (RD) - a tendency

to maintain behaviours manifested by dependency on the approval of others, social attachments, and sentimentality.

� Persistence (P) - a tendency to be

hard-working, industrious, and persistent despite frustration and fatigue.

� Self-directedness (SD) - which refers to self-determination, personal integrity, self-integrity, and willpower.

� Cooperativeness (C) - which refers to

individual differences in identification with and acceptance of other people.

� Self-transcendence (ST) - which

refers to feelings of religious faith, or viewing oneself as an integral part of the universe in other ways.


(Data from Monasterio et al 2012 table 3 p395)

Figure 4.5 - Mean scores of BASE jumpers and age-ma tched controls on seven dimensions. However, the spread of scores among the jumper s was quite large, which meant that the researchers could not establish a "tightly defined personality profile". The exception was harm avoidance (HA), where 40% of the jumpers had a score of 4 or less (compared to 5% of the general population) 52. Low scorers are described as "carefree, relaxed, daring, courageous, composed, a nd optimistic even in situations that worry most peopl e. These individuals are described as outgoing, bold, and confident. Their energy levels tend to be high, and they impress others as dynamic, lively, and vigorous. Th e advantages of low HA are confidence in the face of danger and uncertainty, leading to optimistic and energeti c efforts with little or no distress. The disadvantag es are related to unresponsiveness to danger, which can le ad to foolhardy optimism" (Monasterio et al 2012). This attitude is seen in that 72% of the jumpers had wit nessed a serious or fatal accident, and 42% had suffered a severe but not life-threatening injury (eg: broken arm,

important. High ST with its attendant propensity for self-forgetfulness and openness to transpersonal experience is likely to be disadvantageous to BASE jumpers as it may lead to distractibility and diminished focus on a highly specific task. Individuals who score low on ST tend to be proud, impatient, unfulfilled, self-aware, and generally struggle to accept failure..." (Monasterio et al 2012 p397). 52 Five individuals scored 0, five scored 1 and 2, and seven individuals three (Monasterio et al 2012).


leg, ribs) from their sport. The methodology of the study can be evaluated on two issues - the sample and the personality questionnai re. a) Sample � Not random sample, but volunteers who had a minimum of

ten jumps and/or six months doing the sport. � Only active jumpers - not those who had stopped

voluntarily (who may have been more cautious) or di ed (who may have been riskier).

� Sample small, but it was 5-10% of the total BASE

jumping population (estimated at 700; Monasterio et al 2012).

� Sample recruited via an "insider" (researcher who B ASE

jumped) which might have increased the willingness to participate in the study more than if approached by an "outsider".

� Recruitment occurred at jump meetings, via personal

communication among the jumping community, and on adventure website forums.

b) TCI � Establish validity and reliability. � Each item only offered a forced choice response of

true/false, which limited the options, particularly if the respondent wanted a "maybe" or "sometimes" answ er or could not decide.

� A lot of questions (235) to complete, particular fo r

individuals who are sensation-seekers and get bored easily.

Monasterio, Alamri and Mei-Dan (2012; quoted i n Monasterio et al 2012) reported that experienced mountaineers scored higher on NS and SD and lower o n HA and ST than population means on the TCI. The TCI has been given to non-extreme sports players. For example, high school students involved in endurance, combat, power or team sports had higher HA scores than non-athletes (Han et al 2006). While Fr ench elite racing cyclists scored than higher on RD than control cyclists (Seznec et al 2003).


5. EXERCISE AND HEALTH 5.1. Introduction 5.2. Improvements in exercise 5.2.1. Encouraging physical activity in childr en 5.1. INTRODUCTION Cardio-respiratory fitness (CRF) is declining among English schoolchildren in recent years (Sandercock et al 2010), and the reasons given are increased body mas s and decreased physical activity. In the latter case, it is due to more sedentary behaviour including "screen-t ime" (time spent in front of television or computer for leisure purposes). In a two-year study, Aggio et al (2012) founde d lower CRF among schoolchildren reporting more than two hours daily screen-time. The sample of 1500 11-12 y ear-olds at baseline were assessed in 2008 and 2010 (as part of the East of England Healthy Hearts Study). Physi cal activity and screen-time were self-reported for a s even-day period. CRF was measured using incremental twen ty-metre shuttle runs until exhausted or unable to mai ntain required pace. Low physical activity and high screen-time at baseline and follow-up were associated with over tw ice as likely to be unfit (low CRF). Over the period of th e study, 6% of participants became unfit and individu als with more than two hours daily screen-time were twi ce as likely to be in that group than lower screen-time. 5.2. IMPROVEMENTS IN EXERCISE Physical activity has health benefits. However , structured exercise programmes for adults have high drop-out rates (up to 50% within six months) (Burke et a l 2006). This has led to interest in the context of physical exercise - ie: group or individual-based. Burke et al (2006) undertook a meta-analysis o f 44 studies of programmes to increase physical activity/exercise using categories of outcome like adherence to programme, quality of life, and physiological effectiveness. The types of programme were divided into four contexts: � Home-based alone. � Home-based with contact from health-care profession als. � Group exercise classes. � Group exercise classes that encourage social

interaction and group identity ("true groups").


The effectiveness of the context was a continu um with the "true group" as best through to home-based alone as poorest. Put simply, social support and contact produces better adherence to exercise programmes. The intention to exercise is a predictor of ac tual exercise, and the intention is influenced by attitu de towards exercise, perceived behavioural control (eg : how easy or difficult to do it), and subjective norms ( eg: social pressure/social support). This is according to the theory of planned behaviour (Ajzen 1991) (figure 5. 1).

Figure 5.1 - Theory of planned behaviour. Plotnikoff et al (2012) applied this model in a long-term follow-up of 1427 participants of the 198 1 Canadian Fitness Survey (CFS) (table 5.1). Physical activity was measured by average time in last twelv e months in nineteen activities, while intention to exercise referred to the coming year (from "never" to "six or more times per week"). Participants were al so asked how easily they could participate in exercise three or more times a week for at least twenty minutes ea ch time (on five-point scale), and about the degree of support to exercise from family and friends (seven- point scale). Data were collected in 1988 and 2003. The intention to be active in 1988 significant ly correlated with physical activity in 1988 (r = 0.29 ) and 2003 (r = 0.24). The intention to be active signifi cantly correlated with attitudes towards exercise, perceiv ed behavioural control, and subjective norms. But this model was more predictive for women than men. The level of exercise is an important variable . Moderate and regular exercise boosts the immune sys tem whereas regular strenuous exercise produces immunosuppression and the increased risk of upper respiratory tract infections (URTI) (a "J-curve") (Moreira et al 2009). In a literature search, Moreira et al (2009) f ound thirty studies of physical activity and URTI, which


Table 5.1 - Main strengths and weaknesses of Plotni koff et al (2012). included 8595 athletes and 1798 non-athletes. Among non-athletes, increasing physical activity was found to reduce the risk of URTI, whereas athletes had highe r rates of URTI after training and competition than l ess active individuals. However, elite athletes may hav e a reduced risk due to factors like genetics, and nutr ition (eg: vitamin supplements). 5.2.1. Encouraging Physical Activity in Children Physical activity (PA) and exercise by childre n is influenced by their parent(s) in a number of ways including (Edwardson and Gorely 2010): � Parental encouragement. � Role modelling. � Practical aid (eg: transport to activity venue). Studies, however, are inconsistent in their fi ndings on the relationship between parental support and th e child's PA at home. Most of them are cross-sectiona l studies comparing different groups at one point in time. Lin and Biddle (2012) saw longitudinal studies as b etter, and they set out to review such studies. The litera ture review found eleven relevant studies 53, of which the majority involved White middle-class individuals in Europe or the Americas. Three sets of parental variables were found to correlate with children's PA:

53 The length of the studies varied from less than 1 year to 12 years, and the sample size was anything up to 5000.

STRENGTHS WEAKNESSES

1. Random, national representative sample. The CFS was a multi-stage representative cluster sample of Canadian households, and this study used a random sample of 20%. 2. Prospective design (eg: intention in 1988 predicted exercise in 2003). 3. Fifteen-year follow-up. 4. Separate analysis based on gender.

1. Self-reports of physical activity only. 2. Asking about previous year difficult to recall accurately. 3. Relatively small number completed study compared to original sample (23 397 individuals approached and 1427 provided completed data in 1988 and 2003). 4. The intention to exercise asked about the coming year whereas data collected after fifteen years: "...time referent... not specifically aligned to prospective behaviour measure..." (Plotnikoff et al 2012 p526).


a) Demographic correlates � Higher socio-economic status (SES) positively

correlated with PA, especially father's SES. � Mother's employment negatively correlated with PA,

especially for girls' PA. b) Behavioural correlates � Parent(s)' participation in PA encouraged children' s PA

(example). � Parent(s)' transport support encouraged PA (ie: dri ving

child to venue). c) Psychological correlates � Children's PA was associated with parent(s)' percep tion

of their child as competent, and independent. � Parent(s)' enjoyment of PA encouraged active childr en

54. Lin and Biddle (2012) noted that many of the s tudies used volunteers: " It can be assumed that this method recruited mostly families/parents who are either concerned with the level of physical activity their child is involved in or are conscious of health issues th ey felt PA are related to" (p217). Other studies have found that social variables , like ethnicity and SES, are important. For example, Kimm et al (2002) found that Black girls were less influenced by parent(s)' PA than White girls. Example - Yang et al (1996) Yang et al (1996) reported the results of a t welve-year follow-up of 1881 9-15 year-olds in 1980 on the "Cardiovas cular Risk in Young Finns" study (aged 21-27 in 1992). Offspring of active parents, particularly fathers, were more physically active as children, adolescents, and young adults than of non-active pa rents (figure). This finding is used as evidence of social learning (ie: imitation and modelling). Children imitate the behaviour mode lled by their parents. Yang et al measured physical activity of the children with a series of questions about frequency and time spent, for example, giving the physical activity index (PAI), whereas t he parents'

54 Parents' expectations of their children's participation in sport can be a positive encouragement particularly if moderate, but cause a reduction in motivation if too high (Yang et al 1996).


activity was only measured on a three-point scale ( from "a little" to "regularly"). The participants were interviewed eve ry three years from 1980 (baseline) - 1983, 1986, 1989, and 1992. Overall, physical activity among boys/men dec lined with age, while it was stable after age 15 for girls/women.

(Data from Yang et al 1996 table 2 p279) Figure C - Significant correlations between parents ' physical activity in 1980 and offspring's physical activity.


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Five Topics in Sports Psychology