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Journal of Motor Behavior Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/vjmb20

Retention of Quiet Eye in Older Skilled Basketball Players a

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Lennart Fischer , Rebecca Rienhoff , Judith Tirp , Joseph Baker , Bernd Strauss & Jörg b

Schorer a

Institute of Sport and Exercise Sciences, University of Muenster, Germany

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Institute of Sport Science, University of Oldenburg, Germany

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School of Kinesiology and Health Science, York University, Toronto, Ontario, Canada Published online: 12 Feb 2015.

Click for updates To cite this article: Lennart Fischer, Rebecca Rienhoff, Judith Tirp, Joseph Baker, Bernd Strauss & Jörg Schorer (2015) Retention of Quiet Eye in Older Skilled Basketball Players, Journal of Motor Behavior, 47:5, 407-414, DOI: 10.1080/00222895.2014.1003780 To link to this article: http://dx.doi.org/10.1080/00222895.2014.1003780

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Journal of Motor Behavior, Vol. 47, No. 5, 2015 Copyright © Taylor & Francis Group, LLC

RESEARCH ARTICLE

Retention of Quiet Eye in Older Skilled Basketball Players € rg Schorer2 Lennart Fischer1, Rebecca Rienhoff1, Judith Tirp2, Joseph Baker3, Bernd Strauss1, Jo Institute of Sport and Exercise Sciences, University of Muenster, Germany. 2Institute of Sport Science, University of Oldenburg, Germany. 3School of Kinesiology and Health Science, York University, Toronto, Ontario, Canada.

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ABSTRACT. There is mounting research to suggest that cognitive and motor expertise is more resistant to age-related decline than more general capacities. The authors investigated the retention of skills in medium-aged skilled (n D 14) and older-aged skilled (n D 7) athletes by comparing them with medium-aged less skilled (n D 15) and older-aged less skilled (n D 15) participants. Participants performed basketball free throws and dart throws as a transfer task under standardized conditions. Motor performance (accuracy) and perceptual performance (quiet eye) were examined across the four groups. There were significant differences between skill groups and age groups in throwing accuracy on both throwing tasks. Skilled players outperformed less skilled and medium-aged players outperformed older-aged players in basketball and dart throws. There were no significant differences in quiet eye duration across the skill or age groups in either task. These results indicate expertise in a perceptual motor task such as the basketball free throw can be retained in older athletes and that present models of skill maintenance should be re-evaluated to consider the issue of transfer.

factors (i.e., declining involvement and declining performance) are inextricably linked (cf. Stine-Morrow, 2007). There is also mounting research to suggest that perceptuocognitive and motor expertise are more resistant to agerelated decline than more general capacities. For instance, the rate of decline in more technical skills, such as those required for sports such as golf, are considerably less than the 0.5% per year proposed by Bortz and Bortz (1996) ranging from 0.07% from the age of 35–50 years and 0.25% from 50–60 years of age (Baker, Deakin, Horton, & Pearce, 2007; Baker, Horton, Pearce, & Deakin, 2005). Similarly, Schorer and Baker (2009) suggested that skilled perceptual performance can be maintained to a very high degree despite advancing age. In their study on the anticipation of handball goal keepers, three former world class athletes with a mean age of 44 years showed similar performances as current national team goal keepers in a handball-specific temporal occlusion test. In other tests such as a reaction time, their motor performances were much worse than the current national team goal keepers. Two theoretical frameworks are commonly used to explain the maintenance of peak performance: compensation and selective maintenance (Baker & Schorer, 2010; Horton, Baker, & Schorer, 2008; Krampe & Charness, 2006). The basis of the compensation hypothesis is that although individual components of a skill decline with age, it is possible for overall performance to remain the same due to an increased reliance on other aspects of performance (Bosman, 1993; Salthouse, 1984). Put more simply, the theory suggests skilled performers strategically compensate for a decline in one skill area by developing or improving in another. Studies have found little decline in expert typing skill with advancing age (Bosman, 1993; Salthouse, 1984) with evidence indicating that expert typists compensate for age-related declines by scanning further ahead in the text, thereby allowing them to begin keystroke preparation earlier. As a result of this advanced planning, aging typists can offset a deficiency in one area by improving in another. In sport, compensations can happen on the perceptual or the motor side of performances. In their study of aging handball players, Schorer and Baker (2009) indicated that earlier anticipation of throwing directions was necessary due to age-related declines in movement speed in the older goal-keepers.

Keywords: aging, athlete, sport, maintenance

A

s the global population continues to age at a remarkable rate, issues concerning the maintenance of skill with age become increasingly important. Unfortunately, studies considering variables ranging from reaction time (Etnier, Sibley, Pomeroy, & Kao, 2003; Fozard, Vercruyssen, Reynolds, Hancock, & Quilter, 1994) to components of memory (Henry, MacLeod, Philips, & Crawford, 2004), muscular strength (Kallman, Plato, & Tobin, 1990), and flexibility (Einkauf, Gohdes, Jensen, & Jewell, 1987) imply a downward spiral of functional ability with age. After an analysis of evidence for age-related decline in areas as wide ranging and diversified as muscle cell number (Lexell, Henriksson-Larsen, Winblad, & Sj€ ostr€ om, 1983), rate of DNA repair (Wei, Matanoski, Farmer, Hedayati, & Grossman, 1993), fingernail growth (Orentreich, Markovskyi, & Vogelmer, 1979) and high performance data from running, rowing, and swimming, Bortz and Bortz (1996) concluded that a decline of 0.5% per year was a general biomarker of the aging process. Despite this evidence indicating physical and cognitive capabilities decline with age, there is contradictory evidence as to whether this is actually due to age (e.g., Baker & Schorer, 2010; Maharam, Baum, Kalman, Skolnik, & Perle, 1999). Many of the factors thought to explain the physical and cognitive declines associated with aging may actually result from sedentary lifestyles or disuse. This postulate is reinforced by tracking studies indicating that physical activity and exercise involvement declines with age (Malina, 2001). Present thinking is that these two

Correspondence address: J€ org Schorer, University of Oldenburg, Oldenburg, Germany, Institute of Sport Science, Ammerl€ ander Heerstr. 114-118, 26129 Oldenburg, Germany. e-mail: [email protected] 407

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L. Fischer et al.

The selective-maintenance hypothesis (Charness, Krampe, & Mayr, 1996; Krampe & Ericsson, 1996) is grounded in the notion that experts are able to develop domain-specific mechanisms through an extensive focus on appropriate training that allows them to circumvent general age-related limitations and these mechanisms are more resistant to degradation over time—as long as training persists (e.g., expert hockey players’ ability to read offensive patterns of play and predict their opponents’ actions; for a review of these domain-specific characteristics, see Starkes, Helsen, & Jack, 2001). Krampe and Ericsson found that older pianists, both amateurs and experts, showed the same pattern of age-related decline on general measures of performance, such as reaction time. However, domain-specific measures of performance, such as quality of performance, were maintained to a greater extent in older experts. So far, no study has considered this phenomenon via continuous training of perceptual processes, but one can assume that specific skills would be maintained to a greater extent if they are continuously trained. One specific perceptual skill associated with perceptualcognitive expertise is the quiet eye (Vickers, 1996b), a phenomenon representing an athlete’s gaze behavior before executing a movement. The quiet eye is defined as the final fixation or tracking gaze prior to movement initiation or motor response (Vickers, 2007). Duration and timing of the quiet eye are associated with skill in a range of tasks (Vine, Moore, & Wilson, 2012). Experts seem to hold their final fixation longer and at a different timing than their less skilled counterparts (for an overview, see Vickers, 2007). Against the background of experts’ effective quiet eye control, the phenomenon is seen as a key element of optimal perceptual motor coordination (Vickers, 2007; Williams, Singer, & Frehlich, 2002). For example, in basketball free shooting, the period of quiet eye has been investigated in several studies (e.g., Rienhoff, Fischer, Strauss, Baker, & Schorer, 2015; Vickers, 1996a, 1996b; Wilson, Vine, & Wood, 2009). Harle and Vickers (2001) showed that a specific quiet eye training program can lengthen the final fixation and improve free throw accuracy. The phenomenon of quiet eye seems robust, replicated within an expanding body of literature (Mann, Coombes, Mousseau, & Janelle, 2011), but even against this background there is a need for an extension of present findings for a better understanding of the phenomenon. Vickers (2011) postulated the need for more research on individual differences in the quiet eye. Additionally, the extent to which quiet eye can be retained with advancing age has so far not been examined directly. So far research has indicated that general abilities deterioriate with age (cf. Horton et al., 2010). However, domainspecific skills—in the words of Starkes and Deakin (1984) the software of human performance—such as the quiet eye might be retained (e.g., similar to results from sport-specific anticipation; cf. Schorer & Baker, 2009). This is indirectly supported by the results of Baker and colleagues (Baker et al., 2007; Baker et al., 2005), which showed that golf 408

putting can be maintain at a high level, as well as previous work showing that superior golf putting performance is associated with quiet eye (Vine et al., 2011, 2012). One of the main questions in expertise research is often how specific these skills are, in other words, their transferability. Generally, two theories consider the learning of transfer. The first considered transfer of learning on the basis of similarities in skill and context (Thorndike, 1914) while the second examines the phenomenon based on similarities in learning strategies and performance (Lee, 1988). However, most studies consider tasks that are intra-specific (i.e., the transfer within the same sport), with fewer considering interspecific tasks (i.e., the transfer from a domainspecific task to a fundamental task). Among these, some researchers have examined transferability between similar sport games in early adult experts (Abernethy, Baker, & C^ote, 2005; see also Smeeton, Ward, & Williams, 2004) and one investigation examined transfer between aiming tasks (Rienhoff et al., 2013); however, this issue has not been explored in older groups. Considering perceptual processes in inter-task transfer can provide a deeper understanding of the importance of perceptual processes in relation to with sporting peak performance, especially in targeting tasks. However, few studies of skill in older-aged athletes have considered this issue. If we consider transfer on the basis of theories explaining expertise in aging, the selective maintenance hypothesis proposes less transferability while the compensation hypotheses suggests greater transferability in aging populations. The primary aim of this study was to investigate the retention of perceptual motor skills in a self-paced task in elderly experts with continued training. So far, studies have looked either on real-world data on self-paced tasks like golf putting (Baker et al., 2007; Baker et al., 2005) or on time-constrained tasks (e.g., handball goalkeeping; Schorer & Baker, 2009), with perceptual skills like anticipation. Additionally, the experimental studies conducted to date have focused on young- or medium-aged participants. We wanted to extend this age range by comparing medium- and old-aged participants. Based on previous results in aiming sports (Baker et al., 2007), we expected better performances for aging experts in their domain-specific skill and some loss of performance with age. On the basis of previous results on perceptual expertise (Schorer & Baker, 2009), we hypothesized that highly skilled older athletes would outperform less skilled participants and have little decrement in their perceptual processes when compared with highly skilled younger athletes. Second, we wanted to explore the transferability of this very specific skill to a different domain. In both young and older cohorts, understanding transfer of skill can have important repercussions for athlete development policies as well has having implications for aging-related issues in general. We considered the transfer of throwing accuracy from the basketball free throw (domain-specific task) to dart throwing (transfer task) in older experts. Previous Journal of Motor Behavior

Retention of Quiet Eye

research shows that young-aged skilled players outperformed less skilled players in throwing accuracy in both domain-specific and transfer (dart throwing) tasks, but transfer of performance did not seem to result from transfer for perceptual processes (Rienhoff et al., 2013). Therefore, we hypothesized that perceptual skills would not be transferred in aging experts. In summary, we focused on the maintenance of throwing accuracy and perceptual processes with age in middle-aged and older-aged experts and their transferability. Method

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Participants Four groups of athletes participated in this study—2 Skill (skilled vs. less skilled) £ 2 Age Groups (40–50 years old vs. 65–80 years old). All participants were male right-handers, with normal or corrected-to-normal vision. The first group (medium-aged skilled) consisted of 14 skilled players with a mean age of 42.3 years (SD D 2.52 years) who were former members of elite teams with an average experience of 28 years (SD D 4.88 years) playing basketball and an average of 2.36 (SD D 0.97 years) training hours per week. All were still playing in the fifth to seventh divisions and participated in German championships for Masters Athletes of their age. The second group consisted of seven olderaged skilled players with a mean age of 74.9 years (SD D 2.50 years) who play in the highest German division for their age with an average experience of 57.4 years (SD D 2.80 years). All still participated in basketball training with an average of 1.6 hr per week (SD D 0.24 hr) and participated in German championships for Masters in their age group. The third group consisted of 15 medium-aged less skilled players with a mean age of 45.2 years (SD D 4.20 years). The fourth group consisted of 15 older-aged less skilled players with a mean age of 73.4 years (SD D 7.30 years). Both latter groups had no prior experience in basketball club training. All participants reported having no dart experience (transfer task) and provided informed consent prior to data collection. The study was conducted in accordance with the ethical principles described in the declaration of Helsinki (World Medical Association, 2008).

addition, an official regulation-sized FIBA basketball (Spalding, size 7) was used. For the dart throws, participants stood in front of a wooden board at a distance of 2.37 m. On the wooden board, a grid with a square target in the middle was presented to the participants. The centre of this grid was at the height of 1.73 m. These dimensions were based on the international dart rules of the World Darts Federation. The bull was represented by a squared field with a size of 1.5 £ 1.5 cm and included the bullseye of 0.5 £ 0.5 cm. Further, horizontal and vertical lines with a distance of 0.5 cm were drawn around the bullseye creating a squared grid of 31 fields in horizontal and vertical direction. Competition steel darts with a weight of 24 g were used by the participants for the dart throwing task. For both blocks, eye movements were analyzed using a lightweight head-mounted eye tracking system (Arrington Research, Inc., Scottsdale, AZ). By using this system, scene-related eye-positions could be captured with the additional 0.2 MB head mounted scene camera at a frequency of 30 Hz, an accuracy of 0.25–1.0 , and a resolution of 0.15 . The eye tracking system was linked to a host computer (AMD Athlon 64, processor 3500C; 1 GB RAM; Munich, Germany) via a 10 m cable and used View Point software (Version 2.8.3.0, Scottsdale, AZ). With this setup, participants could move freely and conduct their throwing tasks without being constrained in their movement. The camera system was adjusted and calibrated individually for every participant. The calibration included a nine-point calibration, conducted manually by the experimenter. Therefore, the participant kept their head still and followed a marker with their eyes that was presented by the experimenter. This marker corresponded to the scene-related picture on the host computer that represented the participant’s field of vision. During data collection, the calibration curser (fixation target) was monitored at the host computer, allowing a detailed on-line live monitoring and fine calibration of the perceptual behavior, even if no drift-correction prior to every single trial was conducted. In addition, an externally positioned digital camera at a frequency of 30Hz (Casio EX-F1 EXILIM, Hamburg, Germany) was placed 2.5 m to the left of the participant, recording the participants’ sagittal plane while performing the basketball free throw (including the participants’ preperformance routine) and the dart throwing task.

Apparatus and Tasks The experiment was performed in a laboratory setting where athletes performed two throwing tasks, one of basketball free throws and one of dart throws (cf. Rienhoff et al., 2013). The block containing the basketball free throws utilized a portable standard basketball hoop. The rim was 3.05 m high and the free throw line had a distance of 4.23 m to the middle of the hoop. These are the standard dimensions according to the international basketball rules by the International Basketball Federation (FIBA). In 2015, Vol. 47, No. 5

Measures of Performance In both blocks of throwing trials, participants throwing accuracy was measured. For the basketball free throw, shooting performance was scored as hit without board or rim contact (4), hit with board or rim contact (3), miss with board or rim contact (2), or miss without board or rim contact (1). Such a four-level scale represents a more detailed measurement, increasing the reliability of the skill differences (Vaughn, Lee, & Kamata, 2012). For the dart throwing 409

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task, the horizontal and vertical distance from the bullseye was measured by indicating the square from –15 to C15 relative to the bullseye. Measures of Quiet Eye Duration

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The quiet eye phenomenon is defined as the last fixation prior to initiation of the final movement toward the target (e.g., Vickers, 1996b, 2009). For both basketball and dart tasks this final movement can be identified as the beginning of the extension of the arm toward the target, operationalized by the last video frame of the external camera footage before the angle between the upper and lower arm starts to increase, as the shooting arm moves toward the target. The duration of the quiet eye could extend through the extension of the shooting arm; the location of the final fixation was on the rim or backboard/dart board for at least 100 ms with a saccadic threshold of 0.1 (cf. Rienhoff et al., 2013). Procedure After the participants were welcomed, they were given a brief information about the procedure and completed a questionnaire that included age and level of experience in basketball. Before the experiment began, the eye tracking system was individually adjusted to each participant. No part of the visual field was occluded and in both tasks monocular vision of the eye on the throwing arm side was recorded. At the beginning of every task block, a flash of light was presented to both camera systems to enable a retrospective synchronization of the raised eye movement data and the video recorded by the external camera. The order of the two blocks (i.e., either basketball free throws or dart throws) was counterbalanced. Switching between the two task-blocks was realized very quickly as the wooden dartboard was placed underneath the basketball hoop. Every task block included 15 throws with the throwing performance recorded after each trial and stored on a portable computer (Asus Eee R 101, Taipeh, Taiwan). As described previously, basketball throw performance was scored in four different levels and dart throwing performance was scored using the deviation of each dart on the xaxis and on the y-axis.

scores. Additionally, we ran two analyses of variance with x and y error in dart throwing accuracy with age and skill as between subject factors. Those analyses were conducted on the basis of the results in the study by Rienhoff et al. (2013). The skilled players showed significantly smaller deviations on the x-axis (horizontal axis) compared to the less skilled players, while the y-axis deviation (vertical axis) was similar for both skill groups. For all tests, the alpha level was set to .05. All analyses were conducted using SPSS 21.0 and G*Power 3.1.10 (D€ usseldorf, Germany; Faul, Erdfelder, Lang, & Buchner, 2007). Results Our first hypothesis considered differences in throwing results and perceptual processes between skill and age groups. An ANOVA tested for skill and age differences in the basketball task. There were significant differences in throwing accuracy between skills, F(1, 47) D 107.76, p < .01, f D 1.51; between age groups, F(1, 47) D 48.29, p < .01, f D 1.01; and the interaction of both factors, F(1, 47) D 8.98, p < .01, f D .44. As can be seen in Figure 1, the middle-aged skilled players outperformed the older athletes. Both skilled groups demonstrated superior performance to both less skilled groups. Furthermore the interaction showed that the difference between the two skilled age groups is much higher than for the less skilled ones. An ANOVA with quiet eye duration as the dependent variable revealed no significant differences for skill, F(1, 41) D 0.46, p D .50, f D .01, 1–b D .08, or age groups, F(1, 41) D 1.98, p D .17, f D .23, 1–b D .21. However, the interaction of both factors approached significance, F(1, 41) D 3.87, p D .056, f D .31, 1–b D .39, and demonstrated a medium effect size (cf. Cohen, 1988). As can be seen in Figure 2, the quiet eye duration decreased with age for the

Statistical Analysis The analyses for throwing performance and perceptual behavior were conducted separately for both tasks. First, two analyses of variance were administered to test for differences between two age and two skill groups (throwing accuracy and quiet eye). To analyze transfer we conducted a posteriori z transformation, because performance scales for basketball and dart were different. The comparison of throwing accuracy and quiet eye duration in the transfer task occurs with three factorial analyses of variance (ANOVAs; Task £ Age Group £ Skill), based on the z 410

FIGURE 1. Mean throwing accuracy in basketball free throws of medium-aged and older-aged basketball novices and experts (error bars indicate standard deviations). A score of 4 was a hit without board or rim contact, 3 was a hit with board or rim contact, 2 was a miss with board or rim contact, and 1 was a miss without board or rim contact.

Journal of Motor Behavior

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FIGURE 2. Mean quiet eye duration (in ms) in basketball free throws prior to the extension phase of the shooting arm in medium-aged and older-aged basketball novices and experts (error bars indicate standard deviations).

skilled groups, thus the medium-aged athletes outperformed the older ones, while in the less skilled groups quiet eye remained relatively similar given the large standard deviations. Our second hypotheses considered the transferability of throwing accuracy and perceptual processes from the domain-specific skill to a novel task. To investigate transfer, we performed three-way analyses of variance (2 Skill Group £ 2 Age Group £ 2 Task) as the between factors based on z scores. There were significant differences in the z scores of throwing accuracy between skills, F(1, 47) D 53.17, p < .01, f D 1.06, and between age groups, F(1, 47) D 59.90, p < .01, f D 1.13 (cf. Figure 3). The skilled players outperformed the less skilled and the middle-aged

FIGURE 3. Comparison of mean z scores for basketball and dart performances in medium-aged and older-aged basketball novices and experts (error bars indicate standard deviations). For a more intuitive understanding of the figure, we inverted the dart throwing performance z scores so that scores above zero indicate good performances.

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players had superior results in comparison to the older-aged players. As expected for comparisons on the basis of z scores, no significant differences between tasks were found, F(1, 47) D 0.30, p D .59, f D .08, 1–b D .12. For the interaction of task and skill groups significant differences were revealed, F(1, 47) D 10.63, p

Retention of quiet eye in older skilled basketball players.

There is mounting research to suggest that cognitive and motor expertise is more resistant to age-related decline than more general capacities. The au...
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