Sensorimotor skills are critical to athletic performance, and athletes, coaches, and athletic trainers are constantly searching for ways to enhance these skills. So-called “sports vision training” (SVT) operates under the logic that practice with demanding visual perceptual and oculomotor tasks will improve vision, leading to quicker and more accurate motor movements, thereby improving athletic performance and also potentially reducing injury.1 Previous research testing the effectiveness of SVT for improving visual and visual-motor skills has led to mixed results, with some studies finding training-related improvements,2,3 whereas others did not.4–6
Although such discrepant findings call into question the effectiveness of traditional SVT drills,7 the past decade has seen a paradigm change in the types of approaches that are being implemented. In particular, SVT approaches have been advanced greatly by new digital technologies that can be deployed during natural training activities and by perceptual-learning-inspired training programs and simulations that are designed to promote certain sports-specific visual and cognitive abilities. Stroboscopic visual training is one such approach in which individuals practice athletic tasks, such as throwing and catching, under conditions where vision is intermittently disrupted. By wearing eyewear that induces a strobe-like experience, individuals only see brief snapshots of their environment and therefore have the opportunity to train under harder conditions than would otherwise be encountered. Several laboratory-based research studies comparing visual and sports-specific abilities of those who underwent stroboscopic training to those in control groups have shown that this approach enhances foveal perceptual abilities,8,9 anticipatory timing,10 and dynamic visual acuity and ball catching skills.11 In a pilot study comparing on-ice performance in a cohort of professional hockey players, stroboscopic training was found to improve puck placement accuracy relative to individuals who did not partake in stroboscopic training.12 Further, in a study using strobe training in conjunction with other analogue training methods, it was found that batting averages, slugging percentage, and on-base percentage in university baseball players all improved compared to the previous season when no vision training was performed.13
Based on the notion that specific domains of sports vision are important for athletic performance, Nike Inc. (Beaverton, OR) recently introduced a computerized assessment and training tool aimed at measuring and improving sports-relevant sensorimotor skills. The Nike Sensory Station is a digital device equipped with a battery of nine behavioral tasks that have been identified as important for sports performance.14,15 Nike SVT-certified trainers administer the assessment with instructions during an approximately 30-minute video. Research with this tool has demonstrated that certain tasks in the battery provide reliable16,17 and cross-validated18 measures that improve with practice19 and can be used to investigate sensorimotor abilities in relation to performance in real-world endeavors. For example, it has been found that better performance on measures of dynamic visual acuity and visual motor control accounted for nearly 70% of the variability in goals scored over two seasons in a sample of collegiate hockey players,20 whereas worse performance has been associated with an increased likelihood of sustaining head impacts for American collegiate football players,21 indicating a link between collision avoidance and visual-motor skills. Together, these studies suggest that the sensorimotor skills measured by the Nike Sensory Station may be directly related to athletic performance, and that training programs targeting these skills may lead to more optimal performance outcomes.
In the current study, we performed a secondary data analysis of an applied SVT intervention initiated and performed by the University of Texas varsity softball team. This intervention entailed multiple weeks of analogue and digital sports vision training activities that were completed in conjunction with typical team training drills, bookended by sensorimotor assessments using the Nike Sensory Station, and compared to a control group who did not participate in the SVT training drills. This intervention was designed and implemented by the team's athletic training staff based on previous evidence indicating that these approaches might engender better sensorimotor abilities in specific athletic cohorts12,13 and on the belief that such improvements might be beneficial for their team's performance. As such, this exploratory study aimed to gain a better understanding of the breadth of possible learning induced by SVT in this collegiate athlete population.
The current study was conducted with college softball athletes from the University of Texas varsity women's softball team. Twenty-five females between the ages of 19 and 22 years (mean = 19.96; SD = 1.46) who took part in softball team training activities between March 6, 2012 and October 3, 2014 were included in this investigation. One additional individual undertook the assessment and training activities, but was not included in this study because of technical problems with the data collection. All study activities were part of the team-organized activities conducted by the team's athletic trainer at Red and Charlene McCombs Field and the Sports Medicine Center on the campus of University of Texas–Austin. Data from these assessments and interventions were shared and analyzed under a secondary data research protocol approved by the Duke University Institutional Review Board.
Overview and Group Assignments
This study entailed a cohort design in which sensorimotor abilities were compared between a group of athletes who underwent SVT intervention in addition to their typical softball training drills and a control group who did not partake in these activities but did participate in softball team training drills. The SVT group included 15 individuals who participated in team practice during the fall of 2012 and the control group consisted of 10 individuals who participated in team practice during the fall 2013 (n = 7) and fall 2014 (n = 3) semesters. As described below, all participants took part in initial sensorimotor assessments at the beginning and end of the study activities, but the SVT group also took part in the vision training drills during the intervening time between assessments.
All SVT activities were performed during team softball practice or in the sports medicine center outside of practice. The eight drills listed in Table 1 were added into the team's practice regimen as additional training stations. For 11 weeks of the fall season of 2012, athletes who participated in SVT rotated through the added training stations, performing the drills that the athletic trainer deemed important targets of improvement for each individual (see Table 1 for detailed list). The time spent on each training drill was dictated by that day's practice schedule, and ranged from 5 to 10 minutes per athlete, twice each week (an average of 11.4 drills per week). The team's athletic trainer was present to facilitate, instruct, and coordinate each participant's session both during practice and in the sports medicine center where the Nike Sensory Station device was housed.
Sports Vision Training Drill List
Vision training comprised eight different training drills, each of which was designed to strengthen sensorimotor abilities that are important for athletic performance.
Strobe Softball. Participants in the SVT group wore the Nike Vapor Strobe eyewear while doing an assortment of softball training drills. These drills consisted of hitting and/or bunting off of a tee, catching foam balls and tennis balls barehanded, and fielding drills with gloves and softballs. Each athlete started on level three of the strobe eyewear (100 ms transparent, 150 ms opaque). As individuals became more adept at these drills, the difficulty of the exercise was increased by either raising the level of stroboscopic effect (ie, longer opaque state) or adding drill elements such as identifying letters on the ball while catching barehanded. When deciding to increase the stroboscopic effect, the athletic trainer instructed the athletes to increase to the next level if they were routinely making solid contact with the ball (ie, not fouling it off). Additionally, the athletic trainer observed the athletes performing strobe drills intermittently and, if appropriate, suggested that the athletes increase to the next level. The athletes were reminded that if they were unsuccessful at the next level, they could always return to the previous level for more practice.
Strobe Batting Cage. In addition to the fielding and batting drills described above that the team's athletic trainer oversaw, each athlete also used the strobe eyewear during one 3- to 5-minute cycle hitting in the batting cage twice each week. This batting practice was done against either the HomePlate Ultimate Fast Pitch pitching machine (Santa Ana, CA) or a teammate throwing front toss pitches. If the machine was used, the hitting coach had the freedom to select the type of pitches she wanted the athletes to work on that day (rise ball, drop ball, curve ball, etc.) and the athletic trainer monitored the hitters' performance and adjusted the difficulty of the strobe level accordingly. Each athlete started on level three of the strobe eyewear. Using feedback of perceived difficulty from the athlete and success in hitting the pitches, the level of difficulty was either increased or decreased throughout the 11-week program.
Near/Far Charts. The near/far accommodation drill aimed to improve the ability to rapidly shift visual attention between near and far distances by reducing lag of clarity and depth perception. The athletes held a small letter chart in their hands 16 inches from their face and moved their eyes back and forth between this “near” chart and a larger “far” chart at eye level on the wall in front of them. They read the first letter of the first row on the near chart and then the first letter on the first row on the far chart. They then read the second letter on the first row on the near chart and the second letter on the first row of the far chart, and proceeded in this manner. As the athletes advanced, they began to repeat this drill, reading the rows left-to-right and right-to-left, while shaking their head back-and-forth or up-and-down, or with the athletic trainer calling out random letters and numbers to provide distraction.
Brock String. The goal of this drill was to improve the athlete's ability to quickly and accurately judge the distance of a target and fixate on its location. A Brock String was used to work both eyes together to ensure no suppression of one eye and to learn where the eyes were pointing to make a correction if incorrectly calibrated. The athlete completed drills in which she progressed from the closest to the furthest bead, then from the furthest to the closest, and back again. After this, the order was randomized with the athletic trainer calling out bead colors. This activity progressed to using gaze positions where their head was held tilted down, up, left, and right. The athletes progressed from concentrating on accuracy to speed of precision, and from static to dynamic head movements.
Marsden Ball. The aim of the drill was to improve focus on and tracking of a moving object while the target was in motion to strengthen stamina, balance, and visual-motor control. The athletic trainer swung a Marsden Ball laterally and the athlete was asked to verbally identify letters on the ball. Participants then progressed to swinging the ball diagonally/laterally in a clockwise/counter-clockwise direction around their head while they rotated their trunk in the opposite direction. The final steps in the progression involved more dynamic components with the athletes shaking their head while tracking the ball or turning their body in the same direction of the ball while tracking.
Drills 6 through 8 were performed using the Nike Sensory Station, described in greater detail below. These drills were performed in the ‘training mode’ on the device and comprised similar procedures as the testing mode but for a shorter duration and at preset difficulty levels determined at the outset of each repetition.
Eye-Hand Coordination Drill. The Eye-Hand Coordination drill entailed practice responding as rapidly as possible to visually presented green targets distributed over the 106.7 cm touch screen. For the training, athletes started by completing two repetitions of this drill at the first (easiest) level for 30 seconds. As the athletes progressed, they completed two or three repetitions at each of levels one through three, for either 30 or 60 seconds. Progression through levels was based on score improvement given at the end of each trial and subjective information from the athletes regarding whether they felt ready to progress.
Go/No-Go. The Go/No-Go drill entailed responding to green ‘go’ targets while withholding responses to red ‘no-go’ distractors. Athletes started training by completing two repetitions of this drill at level one for 30 seconds. As the athletes progressed, they completed two or three repetitions on levels one through three, for either 30 or 60 seconds. Progression was based on score improvement and subjective information from the athletes regarding whether they felt ready to progress.
Depth Perception. The Depth Perception training drills used anaglyph glasses that created the appearance of depth in one of two dots presented on the Nike Sensory Station's 58.4 cm display. The dots were oriented vertically, one above the other, and the athletes were to report which dot appeared closer to them using the handheld iTouch device. Individuals completed two or three repetitions on the drill based on time available. This task was only used briefly in the overall training program and several individuals (4 of 6) subjectively reported that they did not experience a clear perception of depth in the stimuli and therefore felt that they were guessing as to the response.
Sensorimotor assessments were performed at the beginning and end of the study activities using the Nike Sensory Station. This device measures sports-relevant visual and visual-motor abilities through a battery of nine computerized tasks that are uniformly administered under standardized testing conditions and takes approximately 30-minutes to complete. Assessment procedures, duration, and location were identical in Session 1 and Session 2 for all participants. The time between the last training session and the Session 2 sensorimotor assessment ranged between 1 and 2 weeks based on the athlete's academic conflicts and availability.
During the Nike Sensory Station assessment, participants first registered a demographic profile that included general information about themselves (gender, age, and height), their sporting activities (primary/secondary sport, position, and level), and their vision correction and concussion history. This was followed by a battery of psychometric tasks that assessed sensorimotor abilities, which included Visual Clarity, Contrast Sensitivity, Depth Perception, Near-Far Quickness, Target Capture, Perception Scan, Eye-Hand Coordination, Go/No-Go, and Response Time. General procedures and descriptions for each task are provided below, and detailed descriptions of this battery can be found in Wang et al.18
To begin, participants stood 4.9 m away from the station and used a handheld Apple iPod touch (Apple Inc., Cupertino, CA) that was wirelessly connected to the Nike Sensory Station to complete the first five tasks. During the Visual Clarity, Contrast Sensitivity, Depth Perception, and Target Capture tasks, the difficulty of the stimuli changed according to a staircase procedure where stimulus difficulty increased subsequent to each correct response and decreased subsequent to each incorrect response. The task ended after participants scored two correct and two incorrect responses for two adjacent difficulty levels, and threshold values were taken as the highest level in which the participant scored two correct responses.
The Visual Clarity task measured visual acuity for fine details at a distance. In this task, a black ring with a gap, which could be located either at the top, bottom, left, or right of the ring, appeared on a white background in the center of the 58.4 cm display monitor. Participants were asked to swipe in the direction of the gap on the iPod touch screen. Using an occluder to cover the untested eye, the participants' right and left monocular and binocular acuities were measured. Visual Clarity thresholds were recorded in logMAR units, with smaller values representing better visual clarity.
The Contrast Sensitivity task measured the minimum resolvable difference in contrast, distinguishing lightness and darkness. Four black circles were presented on a light gray background on the 58.4 cm monitor, with one circle containing a pattern of concentric rings. Participants were asked to swipe the iPod in the direction of the circle with the concentric rings. The Contrast Sensitivity results were log transformed, with larger values indicating better contrast sensitivity.
The Depth Perception task measured how quickly and accurately participants were able to detect differences in depth at a distance. Four black rings were presented on the 58.4 cm monitor and participants were asked to swipe the iPod in the direction of the ring that appeared to have depth. This task required participants to wear liquid crystal glasses (NVIDIA 3D Vision, Santa Clara, CA) that simulated depth in one of the rings. Depth perception was tested with participants standing in three different positions: facing the front of the screen, facing to the left and looking over their right shoulder, and facing to the right while looking over their left shoulder. Participants were also asked to respond as quickly as possible because this task measured response speed.
The Near-Far Quickness task measured the number of near and far targets that were correctly reported in 30 seconds. Participants were asked to align the top of the handheld iPod with the bottom edge of the 58.4 cm monitor. A black ring with a gap was presented on either the iPod touch screen or the Nike Sensory Station screen, and alternated between each screen. The ring only moved to the next screen after the participant swiped in the correct direction of the gap. Participants were asked to swipe as quickly as possible. The scores for this task comprised the number of correct responses made under the time limit of 30 seconds.
The Target Capture task measured the speed at which participants could shift attention and recognize peripheral targets. A black ring was presented at one of the four corners of the 106.7 cm screen. The ring's presentation duration began at 250 ms and changed according to the correct (shorter) or incorrect (longer) responses the participant made. Participants were asked to swipe in the direction of the gap in the ring on the iPod touch screen. The final thresholds for Target Capture were the minimum amount of time the ring was presented in milliseconds such that the participant correctly identified the gap in the ring. Shorter amounts of time indicated better Target Capture scores.
The Perception Span task measured the capacity of spatial working memory. For this task, participants stood at arm's length and a grid of circles was presented on the 106.7 cm touch sensitive screen. In each trial, a certain number of circles were filled with green dots before disappearing. Participants were asked to recreate the pattern of green dots by touching the corresponding circles that had previously flashed green. There were a total of 11 levels possible, with increased grid sizes and more target dots in each successive level. The spatial pattern of the dots at each level was pseudo-randomized to ensure novel target patterns with equal spatial distributions. The task ended when participants could no longer achieve a passing score on two successive trials for a level. The final scores were computed as the total number of correctly identified dots minus the number of missed or incorrectly identified dots across all of the trials.
The Eye-Hand Coordination task measured the speed at which participants could make visually guided hand responses to rapidly changing targets. A grid of 48 equally spaced circles was presented on the 106.7 cm screen. When a green dot appeared in one of the circles, participants were asked to touch the dot as quickly as possible. When the dot was touched, it disappeared and reappeared at another location, and continued changing locations until a sequence of 96 dots was completed successfully. The Eye-Hand Coordination score was the total time it took to touch all 96 dots in the task.
The Go/No-Go task measured the ability to execute and inhibit visually guided hand responses in the presence of “go” and “no-go” stimuli. The set-up of this task was similar to the Eye-Hand Coordination task, but the dots could be either green or red. Participants were asked to touch the green dots as quickly as possible, but to not touch the red dots. Each dot would appear for only 500 ms before disappearing, leading to the emergence of a new dot. There were 96 total dots presented in a pseudo-randomized order. The final scores for the Go/No-Go task were computed as the total number of green “go” dots successfully touched minus the number of red “no-go” dots incorrectly touched.
The Response Time task measured how quickly participants reacted and responded to a simple visual stimulus. Two rings were presented on either side of the 106.7 cm screen. Participants were asked to place the fingertips of their dominant hand in the “starting” ring on the same side of the body as their dominant hand while standing facing the other “landing” ring. When the landing ring turned green, the participants removed their hand from the starting ring to touch the landing ring as quickly and accurately as possible. There were a total of seven trials, and participants had the possibility of repeating up to two of these trials if they were slower than two standard deviations from the mean. The Response Time score was the average time it took to move from the starting ring to the landing ring for all seven trials.
All data were preprocessed to remove a small number of outlier data points that fell more than three standard deviations below the group mean, and were likely due to technical difficulties in the connection between the iTouch and Sensory Station computer (Contrast Sensitivity = 1, Depth Perception = 1, and Target Capture = 1). Following preprocessing, analysis of covariance (ANCOVA) was performed for each task to assess the influence of the training group (SVT or control) on Session 2 performance, while controlling for Session 1 performance. Between-session correlations and residuals were computed for each task and partial η2 effect sizes were determined for the group means.
Behavioral performance on the nine Nike Sensory Station tasks produced means and distributions similar to previously reported performance.16,18,20Table 2 presents the individual task means and standard deviations, collapsed over the two groups for Sessions 1 and 2.
Performance Summaries of the Nine Sensory Station Tasks Collapsed Over Training Groups
Before comparing performance between the two groups, independent sample t tests were conducted to determine if the groups differed in age and height, whereas chi-square tests for association were used to determine if the groups differed in hand or foot dominance. These analyses demonstrated that the control group was significantly younger (18.8 years) and taller (172.9 cm) than the SVT group (20.6 years; 166.9 cm; P < .001; P = .03, respectively), but that the two groups did not differ in their dominant hand (chi-square test = 1.01, P = .315) or foot (chi-square test = 1.49, P = .229). Further, the interval between Sessions 1 and 2 was compared for the two groups, revealing no significant difference in the timing intervals between assessments for the two groups (SVT = 138 days; control = 118 days; P = .16).
Our primary goal in the current investigation was to test for differences in sensorimotor performance for those athletes who underwent SVT versus those who did not. For this purpose, we conducted ANCOVA to test for group differences in Session 2 performance, controlling for Session 1 performance. For each task, Homogeneity of Variance was first assessed between the two groups, indicating that equal variance was present within each group on each measure.
Group-by-session means are shown for each task in Figure 1, and ANCOVA results are shown in Table 3. These analyses revealed significant main effects of the training group for the Near-Far Quickness (P = .034, η2 = 0.19), Target Capture (P = .04, η2 = 0.18), and Go/No-Go (P = .03, η2 = 0.19) tasks, with the intervention group improving by 13%, 17%, and 23%, respectively, on these three tasks. In each of these cases, when controlling for Session 1 performance, the SVT group significantly improved relative to the control group, indicating that for these tasks, more learning occurred for those individuals who underwent SVT. Other tasks did not show a main effect of the training group.
Graphical comparison of performance for the intervention (solid) and control (dashed) groups on each of the 9 Nike Sensory Station (Nike, Inc., Beaverton, OR) tasks. Tasks indicated with (+) indicate that higher scores reflect better performance, whereas those marked with (−) indicate that lower scores reflect better performance.
Training Effects of Sensory Station Skills
Because the number of drills performed differed for the different participants in the SVT group (Table 1), additional analyses were conducted to determine if the number of drills performed related to changes in performance among those who were trained. For each task, participants' performance in Session 2 was predicted from Session 1 performance and the residual variances were calculated. These residuals were then correlated with the number of drills performed. As illustrated in Table 4, Session 1 performance was a strong predictor of Session 2 scores for five of the tasks (Visual Clarity, Near-Far Quickness, Target Capture, Eye-Hand Coordination, and Go/No-Go), but the number of trained drills did not correlate with the residual variance in any of the tasks.
Session and Drill Count Correlations
In the current investigation, we performed a secondary data analysis to assess the influence of SVT on sensorimotor function through an applied intervention by the University of Texas varsity softball team. This program involved the addition of several visual-sensory and visual-motor training drills to the athletes' typical softball drill circuit. These included fielding and batting with the Nike Vapor Strobe eyewear, Near-Far Charts, Brock String and Marsden Ball drills, and several digital training tasks performed on the Nike Sensory Station. To test for group differences, before and after training assessments collected on the Nike Sensory Station were compared for 15 athletes who underwent the intervention against 10 teammates who did not receive vision training. These analyses revealed significant main effects of the training group in the Near-Far Quickness, Target Capture, and Go/No-Go tasks. In each of these three tasks, group interactions were indicative of greater improvements from Session 1 to Session 2 for the group of individuals who undertook the SVT, relative to the control group. Effect size analyses show that this group factor accounted for 18% to 19% of the overall variance. However, no relationship was seen between the number of drills practiced and performance on the assessments.
These results suggest the potential influence of SVT on a set of sensorimotor abilities that are thought to be important for athletic performance. In the two sections below, we discuss relationships between the training drills and enhancements seen in sensorimotor abilities, the implications that these findings might have in applied situations, and the limitations present in this exploratory investigation.
Relationship Between SVT and Sensorimotor Learning
The SVT program undertaken in this study entailed eight different drills, all aimed at enhancing aspects of sensorimotor function important for softball. The significant improvements observed in the Near-Far Quickness, Target Capture, and Go/No-Go tasks among the SVT group indicates that these assessments are capturing learning engendered by the training drills. In evaluating the relationship between training and improvement in these measures, it is important to consider the overlap between the training drills and the assessment tasks. First, it is worth noting that the training intervention involved direct practice with two of the assessment tasks, namely the Eye-Hand Coordination and Go/No-Go tasks. In addition, training drills using the analogue Near-Far Charts held close correspondence to the digital Near-Far Quickness assessment task.
Based on previous reports of learning on the Near-Far Quickness, Eye-Hand Coordination, and Go/No-Go tasks,19 group effects were expected for all three of these measures; however, in the current study only performance for the Near-Far Quickness and Go/No-Go tasks improved. Although the absence of selective learning in the Eye-Hand Coordination task was unexpected, previously reported learning in this task was fairly small in relation to improvements in the Near-Far Quickness and Go/No-Go tasks (16% compared to 46% and 61% in the Krasich et al. study,19 respectively) and therefore the small sample size or limited practice exposure in the current study may not have offered sufficient sensitivity to capture learning in the Eye-Hand Coordination skills.
Despite this absence of specific learning for the Eye-Hand Coordination task, robust improvements were observed in the Near-Far Quickness and Go/No-Go tasks. These observations of specific sensorimotor learning are consistent with previous reports of learning in accommodation/vergence22 and response inhibition23 contexts. Although the Depth Perception drills and assessment presumably involved similar abilities, the anaglyph Depth Perception training differed from the assessment task that used monochromatic shutter glasses. Further, the anaglyph Depth Perception training drill was only used sparingly by four of the athletes and likely did not strongly contribute to any possible learning.
In addition to evidence for specific learning stemming from enhancements in the Near-Far Quickness and Go/No-Go tasks, the current findings also indicate some degree of generalized learning. The Target Capture assessment used here was not specifically trained on, and previous studies employing repeated practice with this task have not reported significant learning.16,19 As such, the observed group effects seen in this study likely resulted from generalized transfer from other aspects of the trained tasks undertaken by the SVT group. In fact, previous studies testing stroboscopic training have reported enhancements in transient visual attention8 using a task with similar temporal and spatial demands to the Target Capture task performed here, and this may be contributing to the generalized learning. Although these purported associations between training drills and learning effects may correspond, it is also interesting that the number of training drills did not significantly correlate with learning on any of the tasks. Future research with careful parameterization and control of the training regimen may help to understand the dynamics underlying sensorimotor learning in these skills.
The training program under consideration was designed and implemented by the team's athletic trainer and a sports vision optometrist to improve the athletes' visual and visual-motor skills, with the intention that these improvements would translate to better softball performance. Because the sensorimotor skills measured by the Nike Sensory Station have all previously been identified as important for sports performance,14,15 the selective improvement seen for the intervention group implies the possibility that these enhancements may result in improved on-field performance. Nonetheless, the current study did not look directly at softball performance statistics and therefore these implications still require further testing. Although comparison of game statistics would certainly have been advantageous and of benefit in evaluating the full efficacy of the SVT program, it was not possible in the current circumstance. In particular, the primary limitation preventing this evaluation resulted from the fact that many of the athletes in this program were new to the team (eg, first-year collegiate athletes). As such, comparable softball statistics before and after training were not available for comparison. A second limitation of this study stems from the non-random assignment of participants to the different drills in the experimental groups. Because of the applied nature of this intervention, participants took part in different but overlapping training drills that the team's athletic trainer deemed most relevant for each individual athlete. Because this report constitutes a secondary analysis of data acquired during the training program, it was not possible to completely randomize or make uniform the specific drills. Therefore, it may be useful for future studies to assign training drills in a uniform manner so that all athletes get the same training regimen. Finally, it is worth noting that testing of the SVT and control groups happened over different seasons and therefore it is possible that other factors such as differences in coaching staff or philosophy may have contributed to the differences observed here.
Implications for Clinical Practice
Despite these limitations, the current study offers a rare opportunity to evaluate the influence of a naturalistic SVT program and suggests that the program under consideration may have led to improvements in sensorimotor skills that are believed to be important for sports. In particular, the observed improvements in the Near-Far Quickness, Target Capture, and Go/No-Go assessments indicate that practice on dynamic SVT drills has the capacity to improve fundamental aspects of sensorimotor performance that are important for sporting performance with possible translation to other medical or occupational therapies.
- Erickson G. Sports Vision: Vision Care for the Enhancement of Sports Performance. St. Louis: Butterworth-Heinemann Elsevier; 2007.
- Balasaheb T, Maman P, Sandhu J. The impact of visual skills training program on batting performance in cricketers. Serbian Journal of Sports. 2008;2:17–23.
- Bressan ES. Effects of visual skills training, vision coaching and sports vision dynamics on the performance of a sport skill. African Journal for Physical, Health Education, Recreation and Dance. 2003;9:20–31. doi:10.4314/ajpherd.v9i1.24590 [CrossRef]
- Wood JM, Abernethy B. An assessment of the efficacy of sports vision training programs. Optom Vis Sci. 1997;74:646–659. doi:10.1097/00006324-199708000-00026 [CrossRef]
- Abernethy B, Wood JM. Do generalized visual training programmes for sport really work? An experimental investigation. J Sports Sci. 2001;19:203–222. doi:10.1080/026404101750095376 [CrossRef]
- Quevedo L, Solé J, Palmi J, Planas A, Soana C. Experimental study of visual training effects in shooting initiation. Clin Exp Optom. 1999;82:23–28. doi:10.1111/j.1444-0938.1999.tb06783.x [CrossRef]
- Hazel CA. The efficacy of sports vision practice and its role in clinical optometry. Clin Exp Optom. 1995;78:98–105. doi:10.1111/j.1444-0938.1995.tb00798.x [CrossRef]
- Appelbaum LG, Cain MS, Schroeder JE, Darling EF, Mitroff SR. Stroboscopic visual training improves information encoding in short-term memory. Atten Percept Psychophys. 2012;74:1681–1691. doi:10.3758/s13414-012-0344-6 [CrossRef]
- Appelbaum LG, Schroeder JE, Cain MS, Mitroff SR. Improved visual cognition through stroboscopic training. Front Psych. 2011;2:276.
- Smith TQ, Mitroff SR. Stroboscopic training enhances anticipatory timing. Int J Exerc Sci. 2012;5:344–353.
- Holliday J. Effect of stroboscopic vision training on dynamic visual acuity scores: Nike Vapor Strobe® Eyewear. In: All Graduate Plan B and Other Reports. Logan, UT: Utah State University; 2013.
- Mitroff SR, Friesen P, Bennett D, Yoo H, Reichow AW. Enhancing ice hockey skills through stroboscopic visual training: a pilot study. Athletic Training & Sports Health Care. 2013;5:1–5. doi:10.3928/19425864-20131030-02 [CrossRef]
- Clark JF, Ellis JK, Bench J, Khoury J, Graman P. High-performance vision training improves batting statistics for University of Cincinnati baseball players. PLoS One. 2012;7:e29109. doi:10.1371/journal.pone.0029109 [CrossRef]
- Hitzeman SA, Beckerman SA. What the literature says about sports vision. Optom Clin. 1993;3:145–169.
- Erickson GB. Give athletes a shot at better vision: whether they shoot foul shots or target rifles, your athletic patients require the best vision to stay at the top of their game. Review of Optometry. 2012;149:83–90.
- Erickson GB, Citek K, Cove M, et al. Reliability of a computer-based system for measuring visual performance skills. Optometry. 2011;82:528–542. doi:10.1016/j.optm.2011.01.012 [CrossRef]
- Gilrein TE. Reliable Change Indices of Visual and Sensory Performance Measures [thesis]. Chapel Hill, NC: University of North Carolina at Chapel Hill; 2014.
- Wang L, Krasich K, Bel-Bahar T, Hughes L, Mitroff SR, Appelbaum LG. Mapping the structure of perceptual and visual-motor abilities in healthy young adults. Acta Psychol (Amst). 2015;157:74–84. doi:10.1016/j.actpsy.2015.02.005 [CrossRef]
- et al. Sensorimotor learning in a computerized athletic training battery. Journal of Motor Behavior. In press.
- Poltavski D, Biberdorf D. The role of visual perception measures used in sports vision programmes in predicting actual game performance in Division I collegiate hockey players. Journal of Sports Sciences. 2015;33:597–608. doi:10.1080/02640414.2014.951952 [CrossRef]
- Harpham JA, Mihalik JP, Littleton AC, Frank BS, Guskiewicz KM. The effect of visual and sensory performance on head impact biomechanics in college football players. Ann Biomed Eng. 2014;42:1–10. doi:10.1007/s10439-013-0881-8 [CrossRef]
- Ciuffreda KJ. The scientific basis for and efficacy of optometric vision therapy in nonstrabismic accommodative and vergence disorders. Optometry. 2002;73:735–762.
- Ridderinkhof KR, van den Wildenberg WP, Segalowitz SJ, Carter CS. Neurocognitive mechanisms of cognitive control: the role of prefrontal cortex in action selection, response inhibition, performance monitoring, and reward-based learning. Brain Cogn. 2004;56:129–140. doi:10.1016/j.bandc.2004.09.016 [CrossRef]
Sports Vision Training Drill List
|TRAINING DRILLSA||SVT INTERVENTIONSB||CONTROLC|
|1. Strobe Softball (11)||Subject 1: 1,2,3||Subject 16: None|
|2. Strobe Batting Cage (15)||Subject 2: 2,3,4,5,6,7,8||Subject 17: None|
|3. Near/Far Charts (15)||Subject 3: 1,2,3,4,5,6,7||Subject 18: None|
|4. Brock String (9)||Subject 4: 1,2,3,4,6,7||Subject 19: None|
|5. Marsden Ball (7)||Subject 5: 2,3,4,5||Subject 20: None|
|6. Eye-Hand Coordination (11)||Subject 6: 1,2,3,4,5||Subject 21: None|
|7. Go/No-Go (11)||Subject 7: 1,2,3,6,7||Subject 22: None|
|8. Depth Perception (4)||Subject 8: 1,2,3,6,7,8||Subject 23: None|
|Subject 9: 2,3,4,5,6,7,8||Subject 24: None|
|Subject 10: 1,2,3,4,6,7||Subject 25: None|
|Subject 11: 1,2,3,6,7|
|Subject 12: 1,2,3,4,5,6,7|
|Subject 13: 1,2,3,6,7,8|
|Subject 14: 1,2,3,4,5,6,7,8|
|Subject 15: 2,3,8|
Performance Summaries of the Nine Sensory Station Tasks Collapsed Over Training Groupsa
|TASKS AND UNITS||SESSION 1||SESSION 2|
|Visual Clarity (− logMAR)||−0.12 (0.1)||−0.15 (0.08)|
|Contrast Sensitivity (+ log contrast)||1.97 (0.16)||1.86 (0.19)|
|Depth Perception (− arcsec)||39.4 (14.1)||50.6 (13.7)|
|Near-Far Quickness (+ score)||25.8 (5.9)||29.2 (6.8)|
|Target Capture (− ms)||294 (137)||244 (116)|
|Perception Span (+ score)||38.2 (11.2)||38.1 (13.5)|
|Eye-Hand Coordination (− sec)||53.03 (3.0)||52.84 (4.0)|
|Go/No-Go (+ score)||26.7 (11.9)||32.9 (11.9)|
|Response Time (− ms)||460 (31.5)||454 (28.7)|
Training Effects of Sensory Station Skills
|TASK||MAIN EFFECT OF TRAINING GROUP|
|Visual Clarity||F(1,22) = 1.28, P = .27, η2p = .06|
|Contrast Sensitivity||F(1, 22) = 1.6, P = .22, η2p = .07|
|Depth Perception||F(1, 22) = .18, P = .67, η2p = .01|
|Near-Far Quickness||F(1, 22) = 5.1, P = .034a, η2p = .19|
|Target Capture||F(1, 22) = 4.5, P = .04a, η2p = .18|
|Perception Span||F(1, 22) = .32, P = .58, η2p = .01|
|Eye-Hand Coordination||F(1, 22) = .27, P = .60, η2p = .01|
|Go/No-Go||F(1, 22) = 5.3, P = .03a, η2p = .19|
|Response Time||F(1, 22) = 1.2, P = .29, η2p = .05|
Session and Drill Count Correlations
|TASK||SESSION 1 VS SESSION 2 CORRELATION||RESIDUAL VS DRILL COUNT CORRELATION|
|Visual Clarity||r = 0.74, P < .001||r = 0.18, P = .39|
|Contrast Sensitivity||r = 0.23, P = .27||r = 0.12, P = .56|
|Depth Perception||r = 0.24, P = .27||r = 0.03, P = .88|
|Near-Far Quickness||r = 0.62, P = .001||r = 0.24, P = .24|
|Target Capture||r = 0.49, P = .016||r = 0.29, P = .17|
|Perception Span||r = 0.25, P = .28||r = 0.18, P = .37|
|Eye-Hand Coordination||r = 0.50, P = .28||r = 0.11, P = .59|
|Go/No-Go||r = 0.64, P = .001||r = 0.30, P = .14|
|Response time||r = 0.39, P = .05||r = 0.21, P = .30|