Journal of Clinical and Experimental Neuropsychology

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A novel approach to sports concussion assessment: Computerized multilimb reaction times and balance control testing Matti V. Vartiainen, Anu Holm, Jani Lukander, Kristian Lukander, Sanna Koskinen, Robert Bornstein & Laura Hokkanen To cite this article: Matti V. Vartiainen, Anu Holm, Jani Lukander, Kristian Lukander, Sanna Koskinen, Robert Bornstein & Laura Hokkanen (2016) A novel approach to sports concussion assessment: Computerized multilimb reaction times and balance control testing, Journal of Clinical and Experimental Neuropsychology, 38:3, 293-307, DOI: 10.1080/13803395.2015.1107031 To link to this article: http://dx.doi.org/10.1080/13803395.2015.1107031

Published online: 08 Dec 2015.

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Date: 26 February 2016, At: 03:33

JOURNAL OF CLINICAL AND EXPERIMENTAL NEUROPSYCHOLOGY, 2016 VOL. 38, NO. 3, 293–307 http://dx.doi.org/10.1080/13803395.2015.1107031

A novel approach to sports concussion assessment: Computerized multilimb reaction times and balance control testing Matti V. Vartiainena,b, Anu Holmc, Jani Lukanderd, Kristian Lukanderd, Sanna Koskinena, Robert Bornsteine and Laura Hokkanena

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a Institute of Behavioural Sciences, Division of Cognitive Psychology and Neuropsychology, University of Helsinki, Helsinki, Finland; bValidia Rehabilitation Helsinki, Finland, Helsinki, Finland; cDepartment of Clinical Neurophysiology, Satakunta Central Hospital, Pori, Finland; dBrain Work Research Center, Finnish Institute of Occupational Health, Helsinki, Finland; eCollege of Medicine, The Ohio State University, Columbus, OH, USA

ABSTRACT

ARTICLE HISTORY

Introduction: Mild traumatic brain injuries (MTBI) or concussions often result in problems with attention, executive functions, and motor control. For better identification of these diverse problems, novel approaches integrating tests of cognitive and motor functioning are needed. The aim was to characterize minor changes in motor and cognitive performance after sports-related concussions with a novel test battery, including balance tests and a computerized multilimb reaction time test. The cognitive demands of the battery gradually increase from a simple stimulus response to a complex task requiring executive attention. Method: A total of 113 male ice hockey players (mean age = 24.6 years, SD = 5.7) were assessed before a season. During the season, nine concussed players were retested within 36 hours, four to six days after the concussion, and after the season. A control group of seven nonconcussed players from the same pool of players with comparable demographics were retested after the season. Performance was measured using a balance test and the Motor Cognitive Test battery (MotCoTe) with multilimb responses in simple reaction, choice reaction, inhibition, and conflict resolution conditions. Results: The performance of the concussed group declined at the postconcussion assessment compared to both the baseline measurement and the nonconcussed controls. Significant changes were observed in the concussed group for the multilimb choice reaction and inhibition tests. Tapping and balance showed a similar trend, but no statistically significant difference in performance. Conclusion: In sports-related concussions, complex motor tests can be valuable additions in assessing the outcome and recovery. In the current study, using subtasks with varying cognitive demands, it was shown that while simple motor performance was largely unaffected, the more complex tasks induced impaired reaction times for the concussed subjects. The increased reaction times may reflect the disruption of complex and integrative cognitive function in concussions.

Received 26 January 2015 Accepted 7 October 2015

Concussions are common neurological injuries in many sports, involving body contact, collisions, or high speed. It is estimated that in the United States alone, 1.6–3.8 million people suffer sport-related concussions every year (Langlois, Rutland-Brown, & Wald, 2006). According to the definition in the latest consensus statement on concussion in sport (McCrory et al., 2013), concussion: (1) May be caused by a direct blow to the head, face, or elsewhere on the body with an “impulsive” force transmitted to the head. CONTACT Matti Vartiainen © 2015 Taylor & Francis

[email protected]

KEYWORDS

Concussion; processing speed; motor performance; reaction time; multilimb

(2) Typically results in the rapid onset of shortlived impairment of neurological function that resolves spontaneously. In some cases, symptoms and signs may evolve over a period of minutes to hours. (3) May result in neuropathological changes, but the acute clinical symptoms largely reflect a functional disturbance rather than a structural injury, and, as such, no abnormality is seen on standard structural neuroimaging studies.

Räisäläntie 24a, 02140 Espoo, Finland.

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(4) Results in a graded set of clinical symptoms that may or may not involve loss of consciousness (LOC). Resolution of the clinical and cognitive symptoms typically follows a sequential course. However, it is important to note that in some cases symptoms may be prolonged (McCrory et al., 2013). Concussions fall in the mild end of traumatic brain injuries (TBI) when LOC, if present, is shorter than 30 minutes, and the Glasgow Coma Scale falls between 13 and 15 (Vos et al., 2012). Patients with mild TBI (MTBI) may have normal magnetic resonance imaging (MRI) and computed tomography (CT) scans but still suffer from cognitive and physical symptoms or behavioral and emotional alterations that can persist for varying lengths of time (Khurana & Kaye, 2012). Decrements in cognitive performance may persist even in athletes no longer reporting subjective symptoms (Broglio, Macciocchi, & Ferrara, 2007). Conventional neurological tests screening motor, sensory, balance, or mental status, typically used in acute phase, may leave these milder symptoms unrecognized (Geiger, Allen, O’Keefe, & Hicks, 2001). Several studies have found that neuropsychological assessment can reveal more subtle changes in performance (Broglio & Puetz, 2008; De Monte, Geffen, May, & McFarland, 2010; De Monte et al., 2005; Lau, Collins, & Lovell, 2011; Moser et al., 2007; Putukian, 2011). Most severe impairment is found at the first day post injury, with improvement of the cognitive problems by 5 to 10 days post injury (Iverson, Brooks, Collins, & Lovell, 2006). Neuropsychological assessment of cognition has therefore been recommended as one of the tools in making the decision on return to play (RTP) after injury (Doolan, Day, Maerlender, Goforth, & Gunnar Brolinson, 2012; McCrory et al., 2009; Shuttleworth-Edwards, 2009). Traditional paper and pencil tests can be used but require skilled personnel, whereas computerized test batteries allow automatized administration and scoring as well as the measurement of more precise reaction times (RTs) (Allen & Gfeller, 2011; Putukian, 2011). Computerized RT measurements are helpful in the detection of subtle changes, and their test–retest reliability has generally found to be good (Broglio et al., 2007; Collie, Darby, & Maruff, 2001; Schatz, 2010). Divided attention has long been studied in MTBI (Stuss et al., 1989). In a recent meta-

analysis, executive functions were identified as the domain most sensitive to multiple MTBI (Karr, Areshenkoff, & Garcia-Barrera, 2014). There is overlap in the domains, and relevant networks of attention can include those of alerting, orienting, and executive control, described by Posner and Petersen (Petersen & Posner, 2012). Both attention and executive functions, along with mental processing speed, are among the most often assessed domains following concussion (Allen & Gfeller, 2011; Belanger & Vanderploeg, 2005; Putukian, 2011). Among concussed athletes, the performance of patients with neurological symptoms has been found to decline on computerized tests of simple, choice, and complex RTs when compared to both a group of concussed patients without symptoms and a group of nonconcussed controls (Collie, Makdissi, et al., 2006). Other affected cognitive domains have included orientation, memory acquisition, delayed memory, and global cognitive ability (Belanger & Vanderploeg, 2005; Karr et al., 2014). Balance and gait abnormalities are frequent after sport-related concussions (Guskiewicz, Ross, & Marshall, 2001; Khurana & Kaye, 2012). Sensomotor and balance testing have become an important part of concussion evaluation, along with tests of cognition, particularly in the acute stage (Broglio & Puetz, 2008; Davis, Iverson, Guskiewicz, Ptito, & Johnston, 2009; Eckner, Kutcher, & Richardson, 2010; Harmon et al., 2013; Khurana & Kaye, 2012; Mayers & Redick, 2012; McCrory et al., 2013; McCrory et al., 2009; Sosnoff, Broglio, & Ferrara, 2008). Balance deficits are mainly reported to resolve in 3 to 7 days after concussion (Guskiewicz et al., 2001; McCrea et al., 2005). Commonly used methods in evaluating balance deficits are the Balance Error Scoring System (BESS), which assesses static balance, and the Sensory Organization Test (SOT), which uses a technical force board to measure postural sway (Giza et al., 2013; Guzkiewicz, 2001; Harmon et al., 2013; McCrory et al., 2013). In addition to static balance, also dynamic balance, gait, and rhythmic coordination have been found to be impaired following traumatic brain injury (Basford et al., 2003; Rinne et al., 2006). By varying the task difficulty level and by engaging both sides of the body separately and in combination, tests of motor performance can be used as sensitive indicators of the integrity of brain function and action control (Serrien, Ivry, & Swinnen, 2007).

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Comparison to population norms alone can be insufficient due to the individual variation in both cognitive skills and balance (Putukian, 2011; Shuttleworth-Edwards, 2009). To overcome this problem, an often-used methodological paradigm in sports injury assessment is baseline testing where preinjury baseline results are used in comparisons with the results after head injury (McCrory et al., 2013; Shuttleworth-Edwards, 2011). Decrements in test performance or greater intraindividual variability in performance may indicate prolonged or persisting impairment (Collie, Makdissi, et al., 2006; Majerske et al., 2008). Despite some critical views towards baseline testing (Mayers & Redick, 2012; Randolph, 2011; Randolph, Lovell, & Laker, 2011; Randolph, McCrea, & Barr, 2005), it has been strongly recommended by many supporting studies (McCrory et al., 2013; Shuttleworth-Edwards, 2009, 2011). When properly used and interpreted, baseline testing may add useful information to the management of sport concussion by giving access to preinjury levels of cognitive functioning (McCrory et al., 2013; Shuttleworth-Edwards, 2011). There is increasing interest in examining motor and cognitive performance in combination as well as in isolation (Register-Mihalik, Littleton, & Guskiewicz, 2013; Serrien et al., 2007; Sosnoff et al., 2008). These studies of motor–cognitive association have been done mostly using examinations of dualtask performance—for example, cognitive tasks during walking or balancing. According to recent systematic review, assessing motor performance in a dual-task paradigm may add test sensitivity allowing improvements in the detection of longer lasting effects of concussion (Lee, Sullivan, & Schneiders, 2013). Gait stability has been studied simultaneously with cognitive tasks requiring attention such as spelling words, reciting months, or subtracting by 7s (Parker, Osternig, Van Donkelaar, & Chou, 2007), or a modified Stroop (Catena, Van Donkelaar, & Chou, 2011). In addition, fine motor performance in a dual task—for example, finger tapping combined with word repetition—has been found to decrease following acute mild TBI (De Monte et al., 2010; De Monte et al., 2005). The decreased motor function and balance as well as slower responses in dual-task performance following TBI reflect a slowing of central processing as well as problems in divided attention in the face of increased cognitive load (Battistone, Woltz & Clark,

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2008; Dell’Acqua, Pashler, & Stablum, 2003; Dell’Acqua, Sessa, & Pashler, 2006; De Monte et al., 2010; Incoccia, Formisano, Muscato, Reali, & Zoccolotti, 2004; Register-Mihalik et al., 2013). One hypothesis is that in cognitive function and concurrent motor tasks, MTBI reduces the attentional resources required to perform each task separately (Sosnoff et al., 2008). However, the research on performance in multilimb reaction time tasks during cognitive processes is still lacking. The present pilot study will make it possible to measure the time of making choices in between four limbs, and in inhibitory and choice conflict situations. This may contribute to future MTBI studies. Within this framework, the primary aim was to study how increasing cognitive demands within the reaction time task affect performance, and whether the performance of the concussed players deteriorates compared to their baseline measurement and to the retest performance of the nonconcussed players. A novel approach integrating the tests of cognitive and motor functioning is used. It is hypothesized that tasks requiring more complex cognitive and motor control will show a larger performance difference than the simpler reaction time tasks when compared to the intraindividual baseline and to the test–retest change in the control group. The secondary aim was to compare these results to performance indicators suggested to be sensitive to MTBI following a sports-related concussion— namely, simple multilimb reaction times, tapping speed, and balance control.

Method Subjects Four Finnish national ice hockey league teams participated in the study, and 113 male players aged 17 to 38 years (M = 24.6, SD = 5.7) were assessed. All the participants were healthy professional ice hockey players. The exclusion criterion was any concussions or limb injuries present one month or less prior to testing. The subjects’ body mass indexes (BMIs) were within the normal range. Their dominant side was rated in terms of writing and kicking a ball, and 101 (89%) of the participants were right-handed. All the players volunteered for the study and signed an informed consent form. The study was approved by the

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TABLE 1. Demographics of the participants and the statistical comparison between the concussed and the nonconcussed groups. Demographics Age (years) Height (cm) Weight (kg) Previous concussions (number) Time since last concussion (months)

All (n = 16) M (SD)

Concussed (n = 9) M (SD)

Nonconcussed (n= 7) M (SD)

U

Z

r

p

23.4 (5.1) 183.5 (4.4) 85.4 (5.7)

24.4 (6.4) 183.8 (3.2) 84.7 (4.6)

22.1 (2.4) 183.3 (6.0) 86.4 (7.0)

28.50 23.00 26.00

–0.323 –0.907 –0.587

–.080 –.227 –.146

0.747 0.364 0.557

19.00 6.50

–1.371 –0.926

–.343 –.232

0,170 0.355

1.4 (1.4) 25.0 (19.5)

1.8 (1.4) 21.1 (15.6)

0.9 (1.2) 34.0 (28.4)

Note. SD = standard deviation.

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Ethics Committee of the Helsinki Uusimaa Hospital District (Dnr: HUS 220/13/03/01/12).

Study procedure All participants underwent the baseline assessment before the start of the season. Relevant clinical information, such as prior history of concussions and time since last medically verified concussion, was obtained. The study period was one hockey season between August 2009 and May 2010. All game-related concussions during this time were recorded. A concussion was defined as head trauma resulting in alteration of the mental state or the onset of clinical symptoms or both. The medical staffs of the teams were trained to follow the Zurich consensus guidelines when diagnosing concussion (McCrory et al., 2009). The severity, type, and time of the injury were later verified from the medical files and confirmed by a neurologist. Details of the injury, LOC, posttraumatic amnesia (PTA), and the number and type of symptoms experienced by the athlete were recorded using the Sport Concussion Assessment Tool (SCAT; McCrory et al., 2009). Postconcussion assessment was administered three times by one of the study investigators: within 36 hours, within four to six days after the concussion, and finally after the season. During the season 2009–2010, 13 athletes sustained a head/neck-related injury in the participating teams. Nine (mean age 24.4 years, SD = 6.4) were followed up according to the study protocol, while four were unavailable for assessment within the required time frame (36 hours). The injury mechanisms were boarding (4), open ice tackle (2), falling after losing balance (2), and hockey stick hitting the face (1). In neurological screening, immediately after concussion, two subjects suffered LOC, seven had PTA (mean duration

12 min), seven had balance or walking problems, seven were confused, and one had difficulties in gaze shifting. The mean SCAT score was 7.7 (SD = 7.2) after the concussion, 5.1 (SD = 4.2) at the second measurement, and 0 (data for one case missing) in the after-season test. Only one player had symptoms at the three months’ follow-up; the mean duration of symptoms for others was 6.3 days (SD = 4.6). A control group of seven nonconcussed volunteer players of similar age and dominance was formed from the original pool of players, and they underwent a follow-up assessment after the season. See Table 1 for the comparison of the concussion and the control groups on age, height, and weight, the number of previous concussions, and the time since last concussion. No statistical differences were found between the groups in these background variables.

Outcome measures The evaluation of multilimb reaction times and tapping speeds was carried out using a computerized Motor Cognitive Test battery (MotCoTe, developed within the project). The MotCoTe is a computer-based reaction time test battery, programmed with the Delphi development environment at the Finnish Institute of Occupational Health. MotCoTe consists of six multilimb reaction time tests and a tapping speed test. In each reaction time test, a frame (5 cm × 15 cm) with a fixation cross at the center is shown on screen (see Figure 1). Arrows appear at the corners of the frame, each corner representing the respective limb: An arrow in the upper right corner represents the right hand, an arrow in the upper left corner the left hand, and arrows in the lower right and left corners of the frame the right and left foot, respectively. Two hand and two foot switches, one for each limb, are interfaced with the

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Figure 1. Motor Cognitive Test battery (MotCoTe): Visualization of the reaction time and tapping speed test position.

computer with millisecond precision. The subject is instructed to press the switch indicated by the arrow as quickly as possible. Each subtest with each limb consists of a set of 10 stimuli. The interstimulus interval varies randomly between 1500 and 3000 ms. In each reaction time test, the median response time for the 10 reaction stimuli is used in the analyses. For each participant, anticipatory responses (defined as responses faster than 100 ms) were excluded from further analysis. The data were collected by three persons who were familiar with the test with the first author always present. The tests were carried out in a quiet environment with the subject sitting at a desk with his shoes removed for foot pedal use (Figure 1). The participants familiarized themselves with each subtest and were instructed to press the switches with the palm of the hand or the ball of their foot (requiring the movement of the wrist joint or ankle joint), rather than a finger or a toe. The participants were encouraged to adjust their posture, stretch their hands and take

deep breaths during breaks between different parts of the test. They were also asked to avoid speaking during actual testing. The participants were instructed to report the presence or increase of any symptoms at the time of the assessment. Each session lasted approximately 30 minutes. At the start of the test, the examiner gave an overall demonstration of the test. Participants were allowed to rest between trials. The reaction time tests with varying attentional demands (simple, choice, inhibition, and conflict RT in single limb and double limb conditions) are described in Figure 2. All tests were done with all limbs and limb combinations. In the first set of analyses (unpooled data, see below), the results of the right hand are reported for the single limb conditions. In double limb conditions, the results of left and right hand (LH+RH) representing bilateral motor processing, right hand and foot (RH +RF) representing unilateral motor processing, and right hand and left foot (RH+LF) representing cross-lateral motor processing are reported.

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Figure 2. Visual description of the Motor Cognitive Test battery (MotCoTe) reaction time test conditions. Single limb: 2.1 Simple; 2.2 Choice; 2.3 Inhibition; 2.4 Conflict. Double limb: 2.5 Simple double; 2.6 Choice double.

A second set of analyses was carried out, and the reaction times of different limbs and limb combinations (unilateral, bilateral, and cross-lateral) were pooled for each case. For the simple, choice, inhibition, and conflict conditions, each of the four limbs was analyzed, increasing the observations four-fold. For the double limb simple and choice conditions, unilateral, bilateral, and cross-lateral combinations

of limbs were analyzed, increasing the observations two-fold. Additionally, the pooling should remove possible side effects from limb dominance. In the tapping speed tests, the same switches were used. In the single limb condition, each limb is used for tapping as fast as possible for 10 s. The user is prompted to start tapping with an onscreen indication “Start.” During the 10 s, a

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track bar indicates the remaining time, and “Stop” instructs the user to cease tapping. Participants were allowed to rest between trials. The test started with the right hand, proceeding to the left hand, right foot, and left foot. In the double limb condition, two limbs are used for tapping as fast as possible for 10 s: first, the upper limbs, then the lower limbs, then the upper and lower limbs unilaterally on the same side, and, lastly, upper and lower limbs cross laterally. The tapping speed score—that is, the number of taps in 10 s—was computed for each limb and limb pair separately. The system rejected any consecutive taps with the same limb and counted only the number of alternating taps. Balance control was measured using a computerized platform (HUR-labs Oy, Kokkola, Finland). The participants stood quietly for 30 s overall in conditions with a closed stance, eyes either open or closed, on either hard or soft foam (see Table 2). In the balance test, the measured parameters for sway were: area (SA, mm2), length (SL, mm), and standard deviation of speed (SS, mm s–1). Only eyes open hard foam (EOHF) and eyes closed soft foam (ECSF) results are reported here for clarity. The test conditions were performed in the following order: reaction time tests, tapping speed test, and balance tests (see Table 2).

Data analyses The means and standard deviations (SDs) are presented as descriptive statistics. A RT difference (change score) between the first (baseline) and the second measurement is calculated by subtracting the time used for the first measurement from the time used for the second in each subtest. A positive value indicates an increase in the performance time, Table 2. The sequence of tests conducted. Tests

Condition

Reaction time tests

Single limb reaction time Simple Choice Inhibition Conflict Double limb reaction time Simple double Choice double Single limb Double limb Eyes open on hard foam (EOHF) Eyes closed on hard foam (ECHF) Eyes open on soft foam (EOSF) Eyes closed on soft foam (ECSF)

Tapping speed tests Balance tests

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suggesting reduced performance. Due to the small group sizes and non-normal distributions, the differences between the concussion group and the control group are analyzed using nonparametric Wilcoxon rank-sum and Mann–Whitney U tests. Comparing the calculated RT difference between the groups gives an indication of the interaction of groups versus measurements. To study how increasing cognitive demands within the RT tasks affect the performance, four single limb data was pooled into one limb data for different conditions forming variables simple, choice, inhibition, and conflict for single limb conditions and variables simple bilateral, simple unilateral, simple cross-lateral, choice bilateral, choice unilateral, and choice cross-lateral for double limb conditions. Differences in reaction times between the pooled limb groups were compared with the independent group t test and repeated measures analysis of variance (ANOVA) with task difficulty (simple vs. choice vs. inhibition vs. conflict) and time of testing (first vs. second test) as within-subjects and study group (concussion vs. control) as between-subjects variables. Group demographics were compared using the Mann– Whitney U test. All statistical tests were two-tailed with exact significances, and the level for significance was set at p < .05. For the group comparisons, the effect size r and the z score are also reported. Effect sizes around .1 are considered small, those above .3 medium, and those above .5 large (Field, 2013, p. 227). Confidence intervals for the effect sizes were also calculated, to verify their relevance. The analyses were performed with IBM SPSS 19.0.0.1 v101.

Results The concussion group and the control group did not differ in their baseline reaction time or tapping speed performance (Mann–Whitney U not significant). As can be seen in Figure 3 (3a and 3b), the concussion group showed a subtle trend of increased reaction times from the preinjury baseline to the postconcussion measurement and an improved performance from the postconcussion to the following retests, while in the control group the reaction times tended to decrease in retesting, possibly indicating learning. Table 3 shows the RT differences (change scores) from baseline to the second test compared between the concussion and the control group. All effect sizes are medium to large. In the single limb

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Figure 3. (a) Motor Cognitive Test battery (MotCoTe) single limb reaction time results. Means and the standard errors of mean (SEM), at baseline (before season), in 36 hours, 4–6 days, and postseason test. Results of the tests conducted with the right hand. (b) MotCoTe double limb reaction time results. Means and the standard errors of mean (SEM), at baseline (before season), in 36 hours, 4–6 days, and postseason test. Results of the selected limb combinations: RH = right hand; RF = right foot; LH = left hand; LF = left foot.

condition, the inhibition change score differed significantly between the groups (p < .05); the reaction time in the concussion group increased between measurements, while in the control group it decreased. In the double limb RT condition, the choice double RH+LH reaction time differed significantly between the concussion and the control group. Again, the concussion group performed slower and the control group faster in follow-up than at baseline (Table 3). In the second set of analyses, using the pooled RT data of all limbs, the inhibition and conflict change scores differed statistically significantly

between the groups (p < .05 and p < .001, respectively) in the single limb condition (Table 4). In the double limb RTs, all the conditions, except simple bilateral, significantly differed between the groups (p < .05 or p < .01 in all). In all tests, the reaction time in the concussion group increased, while in the control group it decreased in follow-up. Table 5 shows the results in multilimb tapping speed and balance tests. The effect sizes were medium for the upper limb tapping tests and small to medium for the balance tests. No significant differences between the two groups were found in the calculated change scores. A trend for the balance,

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Table 3. Motor Cognitive Test battery: Reaction time differences. RT difference (ms)

Tests

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Single limb Simple RH Choice RH Inhibition RH Conflict RH Double limb Simple RH+LH Simple RH+RF Simple RH+LF Choice RH+LH Choice RH+RF Choice RH+LF

Concussion (n = 9) Mean (SD)

Control (n = 7) Mean (SD)

U

Z

r

p

CI

14.6 18.4 42.6 54.6

(28.7) (50.3) (110.9) (126.9)

–12.4 –35.1 –57.6 –55.1

(35.5) (61.1) (109.7) (81.2)

20.00 17.00 12.00 15.00

–1.217 –1.536 –2.064 –1.747

–.304 –.384 –.516 –.437

.252 .134 .042* .091

–0.22 –0.12 –0.17 –0.10

1.83 1.95 1.89 1.99

27.9 18.1 27.3 48.8 23.0 26.3

(58.9) (20.8) (48.3) (57.9) (74.5) (92.5)

–4.3 –20.6 –17.4 –55.8 –36.0 –62.4

(82.8) (47.5) (68.7) (118.2) (108.8) (72.7)

20.00 15.00 21.50 11.00 22.00 14.00

–1.217 –1.747 –1.059 –2.170 –1.006 –1.852

–.304 –.436 –.264 –.543 –.252 –.463

.252 .091 .252 .031* .351 .071

–0.57 0.00 –0.29 0.05 –0.40 –0.05

1.43 2.10 1.75 2.17 1.62 2.04

Note. Group comparison of reaction time (RT) differences between first (baseline) and second reaction time test session calculated by subtracting the first from the second. Positive values represent a decrease and negative values an increase in performance speed. CI = confidence interval for effect size; RH = right hand; RF = right foot; LH = left hand; LF = left foot. *p < .05.

Table 4. Motor Cognitive Test battery: Reaction time differences using pooled data. RT difference (ms) Concussion Tests Single limb Simple Choice Inhibition Conflict Double limb Simple bilateral Simple unilateral Simple cross-lateral Choice bilateral Choice unilateral Choice cross-lateral

n 36

Mean (SD) 16.7 18.0 13.2 41.7

(36.8) (53.1) (95.1) (114.7)

18.0 13.1 29.0 22.7 32.4 7.9

(42.3) (25.2) (40.3) (56.5) (89.2) (85.3)

18

Control n 28

14

CI

Mean (SD)

t

r

p

Lower

Upper

–1.0 –3.8 –32.3 –52.9

(56.5) (64.0) (77.7) (72.6)

–1.52 –1.49 –2.06 –3.81

.189 .186 .253 .435

.134 .142 .044* .000*

–0.12 –0.13 0.01 0.43

0.87 0.87 1.01 1.47

–18.8 –26.0 –14.1 –41.4 –42.0 –66.4

(67.8) (51.1) (53.8) (95.3) (84.1) (71.0)

–1.88 –2.84 –2.59 –2.37 –2.40 –2.62

.325 .461 .428 .398 .401 .432

.069 .008* .015* .024* .023* .014*

0.16 0.48 0.39 0.32 0.33 0.41

1.17 1.52 1.43 1.35 1.36 1.44

Note. Group comparison of pooled limb reaction time (RT) differences between first (baseline) and second reaction time test session calculated by subtracting the first from the second.Positive values represent a decrease and negative values an increase in performance speed. CI = confidence interval for effect size. *p < .05 (two-tailed).

especially for ECSF, was observed, however, suggesting decreased performance in the concussion group but improved performance in the control group in follow-up. A repeated measures ANOVA revealed that in the single limb RT condition, the difficulty (simple vs. choice vs. inhibition vs. conflict) had a statistically significant main effect on reaction times F(2.013, 124.833) = 862.874, p < .001, showing that in the conflict task participants had longer reaction times than in simple, choice, and inhibition tasks, p < .001 in all. Time of testing (first vs. second test) showed no main effect on single limb reaction times, F(1, 62) = 0, p = .996. The interaction between time of testing and study group (concussion vs. control) showed a statistically significant difference, F(1, 62) = 9.979, p = .002.

In the concussion group, the reaction times increased, while in the control group they decreased from the first to the second test.

Discussion The primary aim was to study how increasing cognitive demands within the reaction time task affect performance, and whether the performance of the concussed players deteriorates. The secondary aim was to compare these results with performance changes in simple RT tasks, tapping speed, and balance. In total, 113 hockey players were assessed before the season. Nine athletes were assessed following a concussion. Compared to the baseline measurements, a trend of reduced performance

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Table 5. Tapping speed and balance test.

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Concussion group (n = 9) 1st test Tests Mean (SD) Single-tapping speed (taps) Right hand 72.9 (14.3) Left hand 69.1 (11.9) Right foot 46.3 (15.1) Left foot 54.0 (18.4) Double-tapping speed (taps) Bilateral RH+LH 85.1 (12.6) Unilateral RH+RF 36.3 (23.1) Cross-lateral RH+LF 46.2 (21.0) a Balance 1 2 Area (mm ) 261.8 (67.7) Length (mm) 331.2 (74.0) Speed SD (mm/s) 6.0 (1.4) Balance 4b 2 Area (mm ) 923.9 (376.7) Length (mm) 944.1 (194.0) Speed SD (mm/s) 17.8 (4.0)

Control group (n = 7)

2nd test Mean (SD)

1st test Mean (SD)

2nd test Mean (SD)

70.1 69.0 49.0 49.6

70.7 65.6 54.0 58.9

76.2 73.9 58.4 57.0

(14.0) (9.3) (12.6) (13.0)

(6.7) (12.0) (18.4) (8.9)

U

Z

r

p

(16.5) (9.7) (10.4) (9.5)

17.00 19.50 31.00 28.50

–1.185 –1.275 –0.053 –0.318

–.296 –.319 –.013 –.080

.258 .219 .979 .779

26.50 18.50 27.50

–0.530 –1,379 –0.424

–.132 –.345 –.106

.874 .168 .672

–.252 –.199 –.331

.210

–.410 –.384 –.252

.142 .351

80.1 (23.9) 40.1 (13.2) 48.2 (16.1)

79.9 (33.2) 52.9 (14.4) 49.1 (15.3)

85.7 (11.0) 47.0 (10.6) 54.0 (14.1)

287.9 (118.1) 347.8 (61.5) 6.5 (1.2)

321.3 (101.0) 356.3 (83.3) 6.3 (1.5)

282.9 (127.4) 355.3 (114.7) 6.1 (1.9)

19.00

–1.006 –0.794 –1.323

1309.9 (769.8) 1039.2 (258.2) 19.2 (5.7)

1031.1 (583.1) 891.5 (204.6) 16.7 (4.9)

834.3 (270.3) 796.5 (134.4) 15.0 (2.5)

17.00 22.00

–1.641 –1.535 –1.006

Note. Group results (mean and standard deviation) of tapping speed and balance variables in first (baseline) and second test (postconcussion/ postseason). The differences between second and first test (calculated by subtracting the first from the second) were compared in the two groups. U: Mann Whitney U, Z: z-score, r: Effect size, p: Statistical significance. a EOHF: Eyes open, hard foam. b ECSF: Eyes closed soft foam. *p < .05.

seen in increased reaction times after concussion was observed. Supporting the initial hypothesis, statistical differences between the concussion group and the control group of nonconcussed athletes were found in subtests with higher cognitive load in both single and double limb conditions, especially after pooling the data from separate limbs. Tapping speed and balance scores failed to show a significant difference between the groups. The findings, however, should be considered preliminary due to the small sample size. Computerized neuropsychological test batteries such as ImPACT and CogSport (currently renamed as Axon Sports test) are widely used, and they have been suggested to be good indicators of cognitive deficits following concussion (Collie et al., 2003; Elbin, Schatz, & Covassin, 2011; Schatz, 2010). The debate over their reliability, validity, and their ability to correctly classify players’ cognitive status is still ongoing (Mayers & Redick, 2012; Randolph et al., 2011; Schatz, Kontos, & Elbin, 2012; Shuttleworth-Edwards, 2011), indicating a need for further study. A novel approach MotCoTe was used, which integrates multilimb motor performance and attention processes in an effort to add sensitivity to the traditional tests. As was hypothesized, results showed an increase of multilimb reaction times after concussion, similar to other computerized tests (Broglio et al., 2007; Collie, McCrory, & Makdissi, 2006; Schatz & Putz, 2006). The

assessments were carried out first within 36 hours and then 4–6 days post injury. By the second postinjury assessment, the subjective symptoms still had not resolved in all cases, and also the reaction times still partly remained slower. Although previous literature mainly suggests cognitive recovery within 7 days post injury (Belanger & Vanderploeg, 2005; Iverson et al., 2006), prolonged symptoms in individual cases are known to exist. Similar to many previous studies (Collie et al., 2001; Collie, Makdissi, et al., 2006; ShuttleworthEdwards, Radloff, Whitefield-Alexander, Smith, & Horsman, 2014) the present study revealed a trend of a learning effect (decrease in the reaction times in retesting) in control subjects, but a slight increase in reaction times in the concussion group. Concern has been raised that the learning effect generated by the repeated measurements in the baseline testing paradigm may mask the subtle impairments following concussion (Mayers & Redick, 2012; Randolph, 2011; Randolph, McCrea, et al., 2005). To overcome this, an attenuation of the practice effect after a concussion, even in the absence of significant performance decrement, should be taken into account when interpreting the results. Returning to baseline may not be a reliable indicator of full recovery in all cases. Athletes who show either a decrease or no change in performance compared to baseline, in contrast with the

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improvement observed in asymptomatic and noninjured athletes, should be evaluated further (Collie, Makdissi, et al., 2006). In the present study, the tasks that demanded higher attentional control (choice inhibition reaction times as well as multilimb conditions) were found to be more indicative of a performance decrease, while the simpler RT tasks were less sensitive. Based on the meta-analysis by Belanger and Vanderploeg (2005), attention has been the domain most often assessed in concussion studies, but the effect size for the difference between concussion and control group has remained modest. The tasks in MotCoTe increased in their cognitive load from a single RT to a choice RT, then to one requiring inhibition, and finally to a condition where conflicting information is given, and high level attentional control is demanded. In addition to the traditional single limb performance, the simple and choice reaction times were also tested using upper or lower limbs bilaterally, upper and lower limbs unilaterally, and finally upper and lower limbs cross-laterally. In neuropsychological assessments, the Stroop and other inhibition or conflict-related tests such as spatial, flanker and pictorial conflict tasks have been used for assessing executive attention (Petersen & Posner, 2012). Different RT and divided attention tasks are included also in the ImPACT, HeadMinder, and CogSport batteries (Schatz & Putz, 2006). Novel in the approach used in the present study was the use of tests that require inhibitory and conflict resolution ability while also engaging the full motor system with all four limbs and choice reaction simultaneously. In this study, balance and tapping tests failed to differentiate between the groups. Similar findings have been reported by others (Incoccia et al., 2004; Ozen & Fernandes, 2012). Balance impairments typically resolve quickly, within the first few days after injury (Guskiewicz et al., 2001; McCrea et al., 2005). The assessments in the present study were conducted within 36 hours post injury so it is possible that some of the effect had already been lost. The technical force plate that was used allowed for detailed measurement of the area and speed of postural sway, but the surface was fixed instead of tilted. In SOT performed on the NeuroCom Smart Balance Master, both the somatosensory and visual inputs are altered, which disrupts the sensory selection process and adds to the

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task difficulty (Guskiewicz, 2001; Guskiewicz et al., 2001). In analyzing the underlying components of a variety of psychomotor tests and abilities, Chaiken, Kyllonen, and Tirre (2000) identified six distinct cognitive factors, of which two, a general working-memory capacity and a time estimation factor, were found to be orthogonal. They also concluded that practiced psychomotor skill is additionally limited by processing speed (Chaiken, Kyllonen, & Tirre, 2000). Even in experimental conditions, it is difficult to analyze all factors influencing a particular performance. For motor performance assessment, it is important to note how many muscles or joints are being mobilized and take into consideration any temporal or spatial requirements as well as other perceptual or attentional factors playing a part (Serrien et al., 2007). The motor response in the current study was modified in a controlled fashion so that the effect of increasing cognitive demands to the reaction times could be analyzed. The results indicate that processing speed depends on the amount of tasks involved in the response situation from a motor, psychomotor, or cognitive point of view. It is common to have multiple system involvement in traumatic brain injuries affecting postural control, vision, or cognitive processing abilities. The injury mechanism and symptoms in concussion overlap, for instance, with whiplash type of injuries (Greenwald & Gurley, 2013; Leslie & Craton, 2013); therefore both possibilities should be kept in mind after a sport-related head injury (Hynes & Dickey, 2006). The assessment of motor as well as cognitive functions both separately and in combination may prove to have value in differential diagnostics. If the acuity of the injury is carefully considered along with effective management, the rehabilitation result could be optimized (Gurley, Hujsak, & Kelly, 2013). In assessing symptoms and recovery and making return-to-play decisions, a multifaceted approach to assessment is recommended, where clinical evaluation, selfreported symptom appraisal, and objective tests of different modalities are combined. The development of a new test is always time consuming. Before it can be introduced into wider clinical use its reliability and validity need to be carefully examined. Also, before competing with existing tests with many user friendly features, issues of expense, group test administration, and

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easy interpretation of results need to be resolved. The work with MotCoTe is in early stages, and the results are presented as exploratory. The already existing tests cover several cognitive domains that all need to be evaluated following concussion. For instance, the acute effects (within the first 24 hours) of concussion have been found to be greatest for delayed memory, memory acquisition, and global cognitive functioning (Belanger & Vanderploeg, 2005). A battery, such as MotCoTe, measuring attention or RT alone clearly is not sufficient. Adding a multilimb approach similar to the one presented here might, however, prove useful in increasing the test sensitivity. One clear advantage to this method is the interpretation. The decrease of the performance can be seen in absolute slowness of reaction time, indicating decreased capacity of cognitive performance. Further study is needed to compare the results acquired with the present method to those acquired with other, more standard methods. The first main limitation to this study is related to the small sample size. The number of subjects was limited by the amount of sustained concussions during the season. As a result, the small sample size decreased statistical power. To overcome this, two separate sets of analyses were performed, also adding to the number of statistical comparisons. However, as the first set of analyses were conducted using a nonparametric statistical approach, which is often conservative and may lead to false-negative rather than false-positive findings (Field, 2013, p. 551), no further corrections for multiple comparisons were conducted in analyzing the nonpooled data. The analysis of the pooled data was conducted using a parametric t test without applying the Bonferroni correction. Applying the correction would have eliminated the obtained significances but the use of Bonferroni can be seen problematic, and it should not be used mechanically (Brandt, 2007; Perneger, 1998). Findings were all in the same direction, which makes it less likely that the results were generated by chance. Obviously, the findings only serve as preliminary evidence, and larger samples are needed to verify the results. The second limitation is the lack of data on education or general cognitive level of the sample. All subjects were professional athletes with a uniform focus on sports career. Still, individual cognitive abilities, the cognitive reserve, may moderate the effects of concussion (Putukian, 2011; Stern,

2003), and this could not be controlled in the present study. The third limitation is related to the follow-up period, which should have been defined similarly for all subjects. The control group was retested only after the season, which resulted in a longer interval between the assessments in their case than in the concussion group. This has probably decreased the learning effect for the controls, diminishing the difference between the two groups. Also, the control group was retested only once, whereas the concussion group was retested three times. Having a similar protocol for both groups would probably have intensified the learning effect in the control group, thus further enlarging the differences between the groups.

Conclusion In conclusion, concussed subjects showed a trend of slowing processing speed and motor control that later resolved with recovery from the trauma. While simple reaction time tests in this study did not appear to detect the subtle changes typically resulting from minor head trauma, tests with higher cognitive processing requirements and double limb action were more sensitive. Although the results are very preliminary, the novel approach presented here may be a useful addition in assessing performance changes. The sensitivity increase is likely due to the integrative requirements of the processes: Multilimb coordination requires complex, integrative motor control, and increasing the associated cognitive challenge requires an integrated effort between different brain areas. More research is needed to delineate the benefits of measuring simultaneously motor and cognitive performance after concussion. If proven reliable, this approach could also be applied to monitoring the rehabilitation process.

Disclosure statement No potential conflict of interest was reported by the author(s).

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