Psychiatry Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎
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An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study Nicole Papadopoulos a,d,n, Jennifer L. McGinley b,c, John L. Bradshaw a, Nicole J. Rinehart a,d a
Centre for Developmental Psychiatry & Psychology, School of Psychology and Psychiatry, Monash University, Australia The University of Melbourne, Australia c Clinical Research Centre for Movement and Gait Disorders, Southern Health, Australia d Deakin Child Study Centre, School of Psychology, Deakin University, Australia b
art ic l e i nf o
a b s t r a c t
Article history: Received 28 February 2013 Received in revised form 17 April 2014 Accepted 26 April 2014
This study aimed to compare the gait of children with ADHD – Combined Type (ADHD-CT) to typically developing (TD) children. Children with ADHD-CT (n ¼ 14; mean age 10 years 4 months) and a TD group (n ¼13; mean age 10 years 9 months) walked at self-selected slow, preferred and fast speed on an electronic walkway system. Participants completed a total of 15 walking trials; 5 trials per walking condition. Groups were matched on age, intellectual functioning, height and weight. In the preferred walking condition, there was no difference in spatio-temporal gait variables between the ADHD-CT and TD control groups. At self-selected fast speed, children with ADHD-CT were faster and walked with a higher cadence. The subtle alterations in gait pattern that may reflect a timing deficit is consistent with previous ADHD motor studies. In addition, this study extends previous studies in characterising the unique gait profile of non-medicated children with ADHD-CT where a diagnosis of autism spectrum disorder has been ruled out. & 2014 Published by Elsevier Ireland Ltd.
Keywords: ADHD Autism Gait Social-communication disturbance Inattention
1. Introduction Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood onset psychiatric disorder characterised by clinically significant symptoms of inattention, hyperactivity and impulsiveness that are present before 7 years of age (American Psychological Association, 2000). The Diagnostic and Statistical Manual 4th Edition Revised (DSM-IV-TR) defines three subtypes of ADHD; ADHD – Predominantly Inattentive subtype (ADHD-PI), ADHD – Predominantly Hyperactive-Impulsive (ADHD-HI) and ADHD – Combined Type (ADHD-CT) (APA, 2000). In addition to core clinical symptoms, motor disturbance is common in ADHD-CT (Harvey and Reid, 1997; Piek et al.,1999; Reiersen et al., 2008). Indeed, up to 50% of children with ADHD meet diagnostic criteria for Developmental Coordination Disorder (DCD), and individuals with a co-morbid diagnosis of ADHD and DCD experience greater motor difficulties (Pitcher et al., 2003). However, the specific pattern of motor disturbance that characterises ADHD is only emerging in the literature, far more is known about the cognitive profile of the disorder.
n Corresponding author at: School of Psychology, Deakin University Burwood Campus, Melbourne Burwood Campus, 221 Burwood Highway, Burwood, VIC 3125, Australia. Tel.: þ61 3 9244 5295. E-mail address: [email protected] (N. Papadopoulos).
Children with ADHD present with an uneven executive function profile, characterised by difficulties on tasks measuring inhibition and sustained attention (Barkley, 2001; Johnson et al., 2007), which occur in the context of relatively intact planning ability and cognitive flexibility (Ozonoff and Jensen, 1999). Given the close overlap in neural networks that underpin cognitive and motor abilities (Diamond, 2000), it is not surprising that the ADHD motor profile is also characterised by specific areas of motor impairment which occur in the context of areas of preserved motor function. For example, the nature of motor problems commonly reported for individuals with ADHD range from poorer motor performance on standardized measures of fundamental movement skills and fitness (Harvey and Reid, 2003) to mild balance problems on posturography tasks (Buderath et al., 2009), and it has been proposed that these motor problems may be associated with core ADHD symptoms. Pitcher et al., (2003) reported that a greater proportion of individuals with ADHD-PI subtype experienced motor difficulties (58% of n ¼50) compared to ADHD-HI (49% of n ¼ 16) and ADHDCT (47% of n¼ 38) subtypes. More specifically, Piek et al. (1999) found that children with ADHD-PI (N ¼16) had greater fine motor skill difficulties on the manual dexterity subscale of the Movement Assessment Battery for Children (MABC) compared to individuals with ADHD-CT (N ¼16), whereas children with ADHD-CT experienced greater difficulties with gross motor tasks (balance subscale of the MABC) compared to the ADHD-PI group. Furthermore a
http://dx.doi.org/10.1016/j.psychres.2014.04.037 0165-1781/& 2014 Published by Elsevier Ireland Ltd.
Please cite this article as: Papadopoulos, N., et al., An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study. Psychiatry Research (2014), http://dx.doi.org/10.1016/j.psychres.2014.04.037i
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N. Papadopoulos et al. / Psychiatry Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎
study conducted by Reiersen et al. (2008) reported an association between inattentive symptoms and parent reported motor problems measured on the Child Behaviour Checklist. Despite this, there are very few studies that have investigated the association between ADHD symptomatology (inattention, hyperactivity and impulsivity) and motor performance in ADHD. In addition to the association between inattentive symptoms and motor features, autistic features have also been shown to be associated with greater motor impairment in children with ADHD (Reiersen et al., 2008). Indeed, this pattern compliments the association found between the severity of core social-communicative features and motor impairment in Autism Spectrum Disorders (ASD) (Qiu et al., 2010; Papadopoulos et al., 2012b). It has been suggested that overlap in social-communicative and motor difficulties in ASD may reflect disruption to common underlying brain pathways thought to develop in parallel (Qiu et al., 2010). It is therefore important for future ADHD motor research to consider co-occurring developmental factors such as DCD and ASD (Reiersen et al., 2008). There is some overlap in the literature reporting disruption to motor brain regions, specifically fronto-striatal-cerebellar brain circuitry in ASD and ADHD (Bradshaw, 2001). Upper limb motor studies have provided insight in understanding fronto-striatal and cerebellar type motor impairment in these disorders using a range of tasks (Rinehart et al., 2001, 2006a; Papadopoulos et al., 2012a, 2012b). Numerous gait studies have also considered basal ganglia and cerebellar type motor anomalies in children with ASD (Ambrosini et al., 1998; Rinehart et al., 2006b, 2006c; Calhoun et al., 2011; Nobile et al., 2011; Nayate et al., 2012). Quantitative gait analysis techniques report that the gait pattern of children with autism at a preferred walking pace is characterised by a wide base of support (Nayate et al., 2012; Nobile et al., 2011), variation (both increases and decreases) in stride length and stride time variability (Rinehart et al., 2006a, 2006b; Nobile et al., 2011) as well as increased cadence (Calhoun et al., 2011). Investigations using qualitative gait methods in ASD have also reported a wide base of support (Ambrosini et al., 1998) and reduced smoothness of gait and postural abnormalities of the head and trunk (Rinehart et al., 2006c). Unlike children with ASD who may show characteristic gait disturbances from an early age (Teitelbaum et al., 2004), there have been relatively fewer investigations of gait in children with ADHD. To our knowledge only two studies have measured gait variables in children with ADHD (Leitner et al., 2007; Buderath et al., 2009) using instrumented gait analysis techniques. In a study by Buderath et al. (2009) the gait and postural abnormalities of children with ADHD-CT (on medication; n ¼10) were compared to a cerebellar lesion and typically developing (TD) group. No differences between the ADHD group and TD controls were found in stride length, cadence or stride timing on a treadmill walking task, however ADHD participants scored significantly lower than TD controls when walking backwards on a beam. In a paced stationary stepping task with an external cue (metronome), the ADHD group was slightly slower than TD controls in the fast paced condition. This pattern was consistent with the cerebellar lesion group, providing preliminary support that ADHD may be associated with cerebellar dysfunction. Another study by Leitner et al. (2007) investigated the effect of dual tasking on gait function in children with ADHD without significant motor impairment (9–16 years; n¼ 16), off methylphenidate. They reported no difference between the ADHD and TD groups in the preferred walking condition (single task condition; off medication), although a trend to higher stride time variability was noted in the ADHD group (p ¼0.09). In the dual task condition, stride time variability significantly reduced in the ADHD group compared to the baseline (single task) condition. Stride time variability also reduced when ADHD individuals were medicated compared to baseline. It was
concluded that methylphenidate had a positive effect on gait, reducing the mildly increased stride time variability in the ADHD group. The aim of the current study is to characterise the gait of children with ADHD using the same protocol used in Nayate et al.'s (2012) study of gait in children diagnosed with autism and Asperger's disorder to further inform our understanding of disrupted underlying neural circuitry in ADHD. It was hypothesised that there would be no difference in gait variables (speed, stride length, cadence, base of support and double support time) between the ADHD group and the TD group in the preferred baseline walking condition. Further based on the gait studies conducted by Leitner et al. (2007) and Buderath et al. (2009) it was hypothesised that the ADHD group may display subtle timing anomalies. In addition, based on previous research in ASD that indicates a significant relationship between motor disturbance and social-communicative disturbance (Qiu et al., 2010; Papadopoulos et al., 2012b) we predicted a positive association between gait variables characteristic of ASD such as a wider base of support and increased stride length variability and social-communication symptoms in children with ADHD-CT. Lastly, based on the finding that children with ADHD-inattentive type may experience more motor difficulties than other subtypes (Pitcher et al., 2003), the association between inattentive symptoms measured on the Conner's Rating Scale and spatio-temporal gait variables was explored.
2. Method 2.1. Participants Informed consent was obtained from parents/guardians of all participants, in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Human Research Ethics committee at Southern Health and Monash University, Melbourne Australia. Fourteen boys diagnosed with ADHD – Combined type (ADHD-CT) aged between 7 and 13 years were recruited from Private Paediatricians in Melbourne. The paediatricians specialised in ADHD with 10–20 years of clinical experience in the field, and undertook further assessment and diagnosis of ADHD-CT. These children fulfilled DSM-IV-TR (APA, 2000) criteria for ADHD – Combined type (ADHD-CT). Diagnosis of ADHD-CT was further confirmed by a doctoral-level trained graduate student (author N.P.) under the supervision of a clinical psychologist (author N.R.) using the Conners Rating Scale (Conners, 2001), parent interviews, direct child observations and information from teachers and therapists. Paediatricians also confirmed that children with a diagnosis of ADHD-CT did not have a co-morbid diagnosis of autistic disorder, Asperger's disorder or pervasive developmental disorder not otherwise specified based on their assessment and medical records. Participants who entered the study were further screened for a possible diagnosis of ASD using the Autism Diagnostic Observation Scale (ADOS) by a qualified researcher. No participants were excluded based on elevated ADOS scores (ASD cut off score¼7). Additional exclusion criteria included co-morbid medical (e.g., tuberous sclerosis), hearing or visual impairments, or genetic (e.g., Fragile X syndrome) disorders. The majority of participants in the study (12/14) was on stimulant medication such as methylphenidate (Ritalin). Participants on medication discontinued medication at least 24 h before testing commenced. A reference sample of 13 typically developing (TD) boys aged between 7 and 14 years were recruited from local schools and the community. The TD children had no prior history of psychological, neurological or psychiatric diagnosis. This was confirmed by researchers via interview with children's parents, from whom information on developmental, medical and psychiatric history was obtained (i.e. whether children had any previous diagnoses or had received any intervention). All participants in the TD group were also screened for ADHD-CT symptoms using the Conner's Rating Scale (Conners, 2001) and for autistic symptoms using the Social Responsiveness Scale (Constantino and Gruber, 2005). One TD child was excluded for having Social Responsiveness Scale (SRS) scores indicative of clinically elevated (t score476) social responsiveness difficulties. The intellectual functioning of TD boys was assessed using the Wechsler Abbreviated Scale of Intelligence (WASI) (Wechsler, 1999) or the Wechsler Intelligence Scale for children 4th edition (WISC-IV) (Wechsler, 2005), and the intellectual functioning of children with ADHD-CT was assessed using the WISC-IV. The WASI and WISC-IV are highly compatible with.87 correlation between their full scale IQ scores (Wechsler, 1999). Motor proficiency was assessed and children were screened for DCD using the Movement Assessment Battery for Children
Please cite this article as: Papadopoulos, N., et al., An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study. Psychiatry Research (2014), http://dx.doi.org/10.1016/j.psychres.2014.04.037i
N. Papadopoulos et al. / Psychiatry Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎ Table 1 Demographic information for ADHD-CT and typically developing (TD) control groups.
Age (months) Height (cms) Leg length (cms) Weight (kg) FSIQ VCI PRI
ADHD-CT (n¼14)
Typically developing controls (n¼13)
129.8 147.6 76.1 43.0 97.5 94.8 102.5
129.2 150.7 77.9 46.9 105.4 105.0 107.6
(24.5) (10.4) (6.4) (14.8) (12.5) (13.4) (14.5)
(33.7) (21.4) (12.2) (23.0) (17.5) (17.4) (17.5)
(2nd edition) with a cut-off of o 15th percentile (Henderson et al., 2007). No participants were excluded for experiencing significant motor impairment. Independent measures t-tests were conducted to investigate the effect of age, intelligence, height and weight between groups. There was no significant difference in age (t(25)¼ 0.056, p ¼ 0.956), intellectual functioning; (Full Scale IQ (FSIQ) t(25) ¼ 1.36, p ¼0.188, Perceptual Reasoning Index (PRI) t(25) ¼ 0.829, p¼ 0.415, Verbal Comprehension Index (VCI) t(25)¼ 1.717, p¼ 0.098), height t(25)¼ 0.482, p ¼0.634 and weight t(25)¼ 0.527, p ¼ 0.603 between groups (see Table 1 for participant characteristics). 2.2. Measures 2.2.1. Conners Rating Scale The inattention and hyperactivity-impulsivity subscales from the parent reported Conners Rating Scale (CRS – long form) (Conners, 2001) were utilised in this study. The CRS is a commonly used standardized screening instrument that measures DSM-IV-TR ADHD symptomatology. The parent long form consists of 80 items, measuring indices of oppositional behaviour problems, cognitive/inattentive behaviour, hyperactivity, anxious-shy behaviour, perfectionism, social problems, psychosomatic problems for children aged 3–17 years. Test–retest reliability ranges from 0.47 to 0.85 and internal consistency ranges from 0.73 to 0.91 (Conners, 2001). 2.2.2. Developmental Behavioural Checklist Communication disturbance was assessed using the Developmental Behavioural Checklist –Parent Report (DBC-P) (Einfeld and Tonge, 2002). The DBC is a 96 item quantitative measure of behavioural and emotional disturbance in young people aged 4–18 years, is comprised of five subscales, and has demonstrated good validity and reliability (Einfeld and Tonge, 1995). The behavioural subscales include disruptive/antisocial behaviour, self absorbed, communication disturbance (a measure of communication deviance), anxiety and social relating. Items are scored on a Likert scale ranging from 0—“not true as far as you know” to 3–“often true or very true”. The DBC generates a rating of overall behavioural disturbance, as well as a rating on the five behavioural subscales mentioned above.
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to the line of progression of the opposite foot). A Y-axis range (maximum distance travelled laterally in the horizontal plane of the mat during a walk) was also calculated. Mean values for each walk were calculated and averaged across all trials in that condition, to produce a global mean for each gait variable in each condition. Step to step variability was calculated as the mean standard deviation from each trial for speed, cadence, stride length, double support and base of support. Data were analysed using independent samples t-tests to examine group differences. The data for each of these variables were tested for normal distributions using box plots and the Kolmogorov–Smirnov statistical test. Assumptions of normality were met for all variables except cadence in the fast walking condition. A Mann–Whitney U test was therefore conducted to investigate group differences for this condition. To control for anthropometric differences, data were normalised for each walk in accordance with the methods described in Hof (1996). Effect sizes for gait variables were calculated using Cohen's d. Spearman's correlations were conducted to investigate any significant relationships between communication disturbance measured on the DBC and the five subscale scores as well as inattentive symptoms measured on the CRS and the five gait variables.
3. Results There was no significant difference between the ADHD-CT group and the TD group in the baseline preferred walking or slow condition for speed, cadence, stride length, double support or base of support. However, large and moderate effect sizes were reported for cadence (0.84) and y-axis range (0.65) respectively. At self selected fast speed, the ADHD-CT group was faster (t(25) ¼ 2.31, p ¼0.030) than the TD group, due to increased cadence (U¼33, p ¼0.005) with large effect sizes (0.92) reported (see Table 2 for all effect sizes). Notably, in all conditions, children with ADHD walked with comparable stride length but higher cadence than the TD group, with the increased cadence in the ADHD group also nearing significance in the preferred (p ¼0.052) and slow conditions (p ¼0.066). Normalisation of the data according to Hof (1996) did not alter any of the findings. Variability did not differ between groups in any of the walking conditions, although a strong trend for increased variability in cadence was evident in the preferred (p¼ 0.07) and fast condition (p ¼0.058) in the ADHD group. Moderate effect sizes were reported for cadence in the preferred walking condition and moderate effect sizes were reported for variability in most spatio-temporal gait variables (speed, cadence, stride length, and double support) in the fast walking condition (see Table 3 for all effect sizes). Table 2 Spatio-temporal gait parameters.
2.3. Procedure Condition Participants attended a single 60 min session at the Clinical Research Centre for Movement Disorders & Gait, Kingston Centre Cheltenham. Gait was measured using the GAITRites system (CIR system Inc, Clifton, N.J): an electronic walkway 830 cm 89 cm, with pressure sensors spaced 1.27 cm apart embedded in a horizontal grid. A 2 m non-recordable zone was added on each end of the walkway to minimise the effects of acceleration and deceleration. After each walk, data were analysed using GAITRite software. Anthropometric measures (height, weight and leg length) were taken before the commencement of walking conditions. All participants completed five trials of the three walking conditions in the following order: (1) Preferred walkingparticipants were instructed to walk at their preferred speed, (2) fast walkingparticipants were instructed to walk at a faster pace than their preferred speed, but not to run, and (3) slow walking- participants were instructed to walk at a pace slower than their preferred speed. Participants were given one demonstration trial and a practice trial prior to the commencement of each different walking condition to make sure that they understood the task. 2.4. Data analysis For each walk the GAITRite software generated step-to-step values for a range of gait variables. Spatial-temporal parameters (average of left and right) were extracted which included: speed (cm walked per second), cadence (steps taken per minute), stride length (combined left and right footfalls in full gait cycle), double support (percentage of time both feet are grounded in a complete gait cycle), heelto-heel base of support (perpendicular distance from the heel point in one footfall
ADHD-CT (n¼ 14)
TD controls (n¼ 13)
P-value
Effect size
Preferred Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double Support % gait cycle Base of support (cm) Y-axis range (cm)
130.7 122.3 128.4 23.5 8.7 23.3
(13.9) (7.4) (10.3) (3.1) (2.1) (3.4)
126.9 115.0 133.4 24.4 8.6 21.6
0.531 0.052 0.428 0.447 0.926 0.114
0.254 0.843 0.322 0.309 0.038 0.656
Slow Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double support % gait cycle Base support (cm) Y-axis range (cm)
95.8 104.0 109.6 26.7 8.8 23.7
(19.5) 86.5 (24.8) (11.2) 93.95 (15.81) (12.7) 109.4 (23.1) (3.3) 29.1 (5.3) (2.2) 8.3 (2.4) (3.9) 22.1 (3.3)
0.288 0.066 0.985 0.175 0.619 0.283
0.435 0.769 0.007 0.559 0.202 0.440
Fast Speed (cm/s) Cadence (steps/min) Stride length (cm) Double support % gait cycle Base support (cm) Y-axis range (cm)
180.6 147.0 147.7 19.5 9.5 22.9
(18.6) (12.1) (12.6) (2.8) (2.1) (2.6)
0.030n 0.005n 0.830 0.052 0.140 0.165
0.923 1.094 0.089 0.816 0.610 0.572
n
157.1 129.9 146.0 21.9 8.2 21.5
(17.3) (10.4) (20.8) (3.0) (2.5) (1.6)
(33.0) (19.7) (26.7) (3.4) (2.2) (2.6)
P o 0.05.
Please cite this article as: Papadopoulos, N., et al., An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study. Psychiatry Research (2014), http://dx.doi.org/10.1016/j.psychres.2014.04.037i
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Table 3 Variability (S.D.) for gait parameters. Condition
ADHD-CT (n ¼14)
TD controls (n ¼13)
P-value
Effect size
Preferred Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double Support % gait cycle Base of support (cm)
7.5 4.5 3.9 1.0 1.1
(5.2) (4.3) (1.8) (0.4) (0.8)
5.7 1.9 4.1 1.0 1.1
(3.3) (1.61) (2.2) (0.3) (0.3)
0.318 0.070 0.685 0.985 0.735
0.408 0.701 -0.164 -0.007 -0.137
Slow Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double Support % gait cycle Base support (cm)
8.2 5.2 6.2 1.6 1.4
(4.9) (4.2) (3.2) (1.0) (0.5)
6.6 3.3 5.8 1.6 1.2
(3.6) (2.3) (2.5) (1.1) (0.6)
0.336 0.148 0.734 0.881 0.290
0.393 0.484 0.138 0.060 0.433
Fast Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double Support % gait cycle Base support (cm)
14.4 9.4 5.7 1.7 1.4
(15.2) (8.2) (4.4) (1.3) (0.7)
7.1 4.1 3.4 1.1 1.3
(5.3) (5.0) (1.1) (0.5) (0.7)
0.106 0.058 0.088 0.089 0.591
0.665 0.759 0.708 0.702 0.217
3.1. Association between social-communication and gait variables A series of Spearman's correlations were conducted to investigate the relationship between gait variables in all walking conditons and emotional behavioural disturbance (total DBC score) as well as the DBC subscales for the ADHD-CT group. Only communication disturbance (a measure of social communication deviance) was significantly positively correlated with base of support (rs ¼ 0.56, p ¼0.037). There were no other significant correlations between any of the gait variables and DBC subscales. 3.2. Association between ADHD symptoms and gait variables The severity of Inattentive symptoms on the CRS was significantly correlated with speed (rS ¼ 0.55, p¼0.04) and cadence (rS ¼ 0.60, p¼0.02) in the fast walking condition, although not in the slow (speed; rS ¼ 0.06, p¼ 0.753, cadence; rS ¼ 0.07, p¼0.727) or preferred (speed; rS ¼ 0.05, p¼0.808, cadence rS ¼0.19, p¼ 0.353) walking conditions. There were no other significant correlations between inattentive symptoms and any other gait variables. There were also no significant correlations between the hyperactivity-impulsivity subscales of the CRS and any of the gait variables.
4. Discussion This study aimed to investigate the gait profile of a sample of children diagnosed with ADHD-CT who had been screened for DCD and ASD. The finding of no significant difference in spatiotemporal gait variables between the ADHD and TD groups in the preferred walking condition is largely consistent with previous gait studies (Leitner et al., 2007; Buderath et al., 2009). In addition, differences in timing regulation with reported large effect sizes for the preferred, slow and fast walking conditions support previous motor studies (see Hart et al., 2012) that consistently report timing deficits in children (Luman et al., 2009) and adults (Valera et al., 2010) with ADHD. Difficulties in timing regulation have long been attributed to cerebellar dysfunction (Ivry and Keele, 1989); a brain region consistently implicated in ADHD (Berquin et al., 1998). However, the current study extends previous ADHD motor
research in defining the gait profile characteristic of children with ADHD without clinically significant symptoms of ASD and DCD. It has previously been documented that up to 30% of individuals with ADHD experience clinically significant autistic symptoms (Reiersen et al., 2007). Further, in our previous study of motor functioning that comprised a sub-set of participants from this study (Papadopoulos et al., 2012c), social responsiveness measured on the Social Responsiveness Scale (SRS) was found to be related to error variability on a repetitive upper limb Fitts' aiming task. The current study found a moderate positive correlation between increased levels of communication disturbance measured on the DBC and a wider base of support in ADHD. Inattentive symptoms were also found to be associated with increased speed and cadence in the fast walking condition. This finding partially supports previous parent- reported motor studies (Reiersen et al., 2008) as well as motor studies using standardized assessment batteries (Piek et al., 1999;Pitcher et al., 2003). The link between inattention and motor problems is also apparent in ADHD studies that report an improvement in motor performance when children are on medication (e.g., methylphenidate) (Leitner et al., 2007; Brossard-Racine et al., 2012). Despite this, it is currently unclear whether a particular ADHD subtype (e.g., ADHD-PI) is associated with a different gait profile. More broadly, larger scale gait studies including well-defined groups of children with neurodevelopmental disorders will be necessary to see if gait characteristic differ according to diagnosis (e.g., ADHD, ASD), and degree of comorbidity. The current gait study is a cross sectional study, and although it allows an investigation of motor performance at a time point it does not provide a picture of motor performance across the developmental trajectory. Future research should therefore endeavour to investigate motor performance in ADHD longitudinally. Secondly, the small sample size, as well as multiple statistical tests limits the power of the current study and our ability to generalise our findings. Inadequate power may have limited our ability to detect significant differences in variability of some gait variables. Specifically, moderate effect sizes were reported for speed, cadence, stride length and double support time in the fast walking condition which may provide some evidence of a more variable gait pattern at fast walking speed for the ADHD-CT group. Large effect sizes for cadence across all walking conditions (preferred, slow and fast) may also indicate that cadence may be affected in all walking conditions and requires further exploration. Future research is necessary to investigate the gait profile of clearly defined groups of children diagnosed with autism, AD and ADHD at the same time point. Replication of the current study using larger sample sizes to increase power is also necessary. Lastly, the use of blinded investigators conducting the gait trials and sensitive gait paradigms such as 3D motion analysis may allow a more comprehensive unbiased investigation of whole body movement across time and space and enable greater detection of gait anomalies. These preliminary findings indicate that the gait profile of nonmedicated children with ADHD without ASD and DCD reflects a deficit in timing regulation when children are asked to walk at a fast pace, consistent with cerebellar disruption. Future research should investigate whether the unique profile of gait disturbance characteristic of individuals with ADHD may be useful in objectively distinguishing between children with autism, Asperger's disorder, and other neurodevelopmental conditions.
Appendix A. Supplementary materials Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.psychres.2014.04.037.
Please cite this article as: Papadopoulos, N., et al., An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study. Psychiatry Research (2014), http://dx.doi.org/10.1016/j.psychres.2014.04.037i
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neuromotor function. Journal of Autism & Developmental Disorders 42 (5), 707–717. Nobile, M., Perego, P., Piccinini, L., Mani, E., Rossi, A., Bellina, M., Molteni, M., 2011. Further evidence of complex motor dysfunction in drug naïve children with autism using automatic motion analysis of gait. Autism 15 (3), 263–283. Ozonoff, S., Jensen, J., 1999. Brief report: specific executive function profiles in three neurodevelopmental disorders. Journal of Autism & Developmental Disorders 29, 171–177. Papadopoulos, N., McGinley, J.L., Tonge, B.J., Bradshaw, J.L., Saunders, K., Rinehart, N.J., 2012a. An investigation of upper limb motor function in high functioning autism and Asperger's disorder using a repetitive Fitts' aiming task. Research in Autism Spectrum Disorders 6 (1), 286–292. Papadopoulos, N., McGinley, J., Tonge, B.J., Bradshaw, J., Saunders, K., Murphy, A., Rinehart, N.J., 2012b. Motor proficiency and emotional-behavioural disturbance in autism and Asperger's disorder: another piece of the Neurological puzzle? Autism 16 (6), 627–640. Papadopoulos, N., Rinehart, N., Bradshaw, J.L., Taffe, J., McGinley, J., 2012c. Is there a link between motor performance variability and social-communicative impairment in children with ADHD-CT: a kinematic study using an upper limb Fitts’ aiming task. Journal of Attention Disorders, http://dx.doi.org/ 1087054712454569. Piek, J., Pitcher, T., Hay, D., 1999. Motor coordination and kinaesthesis in boys with attention deficit-hyperactivity disorder. Developmental Medicine & Child Neurology 41, 159–165. Pitcher, T., Piek, J., Hay, D., 2003. Fine and gross motor ablity in males with ADHD. Developmental Medicine and Child Neurology 45, 525–535. Qiu, A., Adler, M., Crocetti, D., Miller, M., Mostofsky, S., 2010. Basal ganglia shapes predict social, communication, and motor dysfunctions in boys with autism spectrum disorder. Journal of the American Academy of Child and Adolescent Psychiatry 49 (6), 539–551. Reiersen, A.M., Constantino, J.N., Volk, H.E., Todd, R.D., 2007. Autistic traits in a population based ADHD twin sample. Journal of Child Psychology and Psychiatry 48, 464–472. Reiersen, A., Constantino, M., Todd, R., 2008. Co-occurrence of motor problems and autistic symptoms in Attention-Deficit/Hyperactivity Disorder. Journal of American Academy of Child Adolescent Psychiatry 47 (6), 662–672. Rinehart, N.J., Bradshaw, J.L., Brereton, A.V., Tonge, B.J., 2001. Movement Preparation in high-functioning autism and Asperger's disorder: a serial choicereaction time task involving motor reprogramming. Journal of Autism and Developmental Disorders 31 (1), 79–88. Rinehart, N.J., Bellgrove, M.A., Tonge, B.J., Brereton, A.V., Howells-Rankin, D., Bradshaw, J.L., 2006a. An examination of movement kinematics in young people with high-functioning autism and Asperger's disorder: further evidence for a motor planning deficit. Journal of Autism Developmental Disorders 36, 757–767. Rinehart, N.J., Tonge, B., Bradshaw, J.L., Iansek, R., Enticott, P., McGinley, J., 2006b. Gait function in chldren with high-functioning autism and Asperger's disorder: evidence for basal ganglia and cerebellar involvement? European Journal of Child and Adolescent Psychiatry 15 (5), 256–264. Rinehart, N.J., Tonge, B.J., Iansek, R., McGinley, J., Brereton, A.V., Enticott, P., Bradshaw, J.L., 2006c. Gait function in newly diagnosed children with autism: cerebellar and basal ganglia related motor disorder. Developmental Medicine and Child Neurology 48, 819–824. Teitelbaum, O., Benton, T., Shah, P.K., Prince, A., Kelly, J.L., Teitelbaum, P., 2004. Eshkol Wachman movement notation in diagnosis: the early detection of Asperger's syndrome. Proceedings of the National Academy of Sciences of the United States of America 101 (32), 11909–11914. Valera, E.M., Spencer, R.M., Zeffiro, T.A., Makris, N., Spencer, T.J., Faraone, S.V., Biederman, J., Seidman, L.J., 2010. Neural substrates of impaired sensorimotor timing in adult attention deficit hyperactivity disorder. Biological Psychiatry 68, 359–367. Wechsler, D., 1999. WASI – Wechsler Abbreviated Scale of Intelligence Manual. Harcourt Assessment, USA. Wechsler, D., 2005. Manual for the Wechsler Intelligence Scale for Children – Fourth edition – Australian Adaptation. The Psychological Corporation, San Antonio, TX.
Please cite this article as: Papadopoulos, N., et al., An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study. Psychiatry Research (2014), http://dx.doi.org/10.1016/j.psychres.2014.04.037i
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Psychiatry Research journal homepage: www.elsevier.com/locate/psychres
An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study Nicole Papadopoulos a,d,n, Jennifer L. McGinley b,c, John L. Bradshaw a, Nicole J. Rinehart a,d a
Centre for Developmental Psychiatry & Psychology, School of Psychology and Psychiatry, Monash University, Australia The University of Melbourne, Australia c Clinical Research Centre for Movement and Gait Disorders, Southern Health, Australia d Deakin Child Study Centre, School of Psychology, Deakin University, Australia b
art ic l e i nf o
a b s t r a c t
Article history: Received 28 February 2013 Received in revised form 17 April 2014 Accepted 26 April 2014
This study aimed to compare the gait of children with ADHD – Combined Type (ADHD-CT) to typically developing (TD) children. Children with ADHD-CT (n ¼ 14; mean age 10 years 4 months) and a TD group (n ¼13; mean age 10 years 9 months) walked at self-selected slow, preferred and fast speed on an electronic walkway system. Participants completed a total of 15 walking trials; 5 trials per walking condition. Groups were matched on age, intellectual functioning, height and weight. In the preferred walking condition, there was no difference in spatio-temporal gait variables between the ADHD-CT and TD control groups. At self-selected fast speed, children with ADHD-CT were faster and walked with a higher cadence. The subtle alterations in gait pattern that may reflect a timing deficit is consistent with previous ADHD motor studies. In addition, this study extends previous studies in characterising the unique gait profile of non-medicated children with ADHD-CT where a diagnosis of autism spectrum disorder has been ruled out. & 2014 Published by Elsevier Ireland Ltd.
Keywords: ADHD Autism Gait Social-communication disturbance Inattention
1. Introduction Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood onset psychiatric disorder characterised by clinically significant symptoms of inattention, hyperactivity and impulsiveness that are present before 7 years of age (American Psychological Association, 2000). The Diagnostic and Statistical Manual 4th Edition Revised (DSM-IV-TR) defines three subtypes of ADHD; ADHD – Predominantly Inattentive subtype (ADHD-PI), ADHD – Predominantly Hyperactive-Impulsive (ADHD-HI) and ADHD – Combined Type (ADHD-CT) (APA, 2000). In addition to core clinical symptoms, motor disturbance is common in ADHD-CT (Harvey and Reid, 1997; Piek et al.,1999; Reiersen et al., 2008). Indeed, up to 50% of children with ADHD meet diagnostic criteria for Developmental Coordination Disorder (DCD), and individuals with a co-morbid diagnosis of ADHD and DCD experience greater motor difficulties (Pitcher et al., 2003). However, the specific pattern of motor disturbance that characterises ADHD is only emerging in the literature, far more is known about the cognitive profile of the disorder.
n Corresponding author at: School of Psychology, Deakin University Burwood Campus, Melbourne Burwood Campus, 221 Burwood Highway, Burwood, VIC 3125, Australia. Tel.: þ61 3 9244 5295. E-mail address: [email protected] (N. Papadopoulos).
Children with ADHD present with an uneven executive function profile, characterised by difficulties on tasks measuring inhibition and sustained attention (Barkley, 2001; Johnson et al., 2007), which occur in the context of relatively intact planning ability and cognitive flexibility (Ozonoff and Jensen, 1999). Given the close overlap in neural networks that underpin cognitive and motor abilities (Diamond, 2000), it is not surprising that the ADHD motor profile is also characterised by specific areas of motor impairment which occur in the context of areas of preserved motor function. For example, the nature of motor problems commonly reported for individuals with ADHD range from poorer motor performance on standardized measures of fundamental movement skills and fitness (Harvey and Reid, 2003) to mild balance problems on posturography tasks (Buderath et al., 2009), and it has been proposed that these motor problems may be associated with core ADHD symptoms. Pitcher et al., (2003) reported that a greater proportion of individuals with ADHD-PI subtype experienced motor difficulties (58% of n ¼50) compared to ADHD-HI (49% of n ¼ 16) and ADHDCT (47% of n¼ 38) subtypes. More specifically, Piek et al. (1999) found that children with ADHD-PI (N ¼16) had greater fine motor skill difficulties on the manual dexterity subscale of the Movement Assessment Battery for Children (MABC) compared to individuals with ADHD-CT (N ¼16), whereas children with ADHD-CT experienced greater difficulties with gross motor tasks (balance subscale of the MABC) compared to the ADHD-PI group. Furthermore a
http://dx.doi.org/10.1016/j.psychres.2014.04.037 0165-1781/& 2014 Published by Elsevier Ireland Ltd.
Please cite this article as: Papadopoulos, N., et al., An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study. Psychiatry Research (2014), http://dx.doi.org/10.1016/j.psychres.2014.04.037i
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study conducted by Reiersen et al. (2008) reported an association between inattentive symptoms and parent reported motor problems measured on the Child Behaviour Checklist. Despite this, there are very few studies that have investigated the association between ADHD symptomatology (inattention, hyperactivity and impulsivity) and motor performance in ADHD. In addition to the association between inattentive symptoms and motor features, autistic features have also been shown to be associated with greater motor impairment in children with ADHD (Reiersen et al., 2008). Indeed, this pattern compliments the association found between the severity of core social-communicative features and motor impairment in Autism Spectrum Disorders (ASD) (Qiu et al., 2010; Papadopoulos et al., 2012b). It has been suggested that overlap in social-communicative and motor difficulties in ASD may reflect disruption to common underlying brain pathways thought to develop in parallel (Qiu et al., 2010). It is therefore important for future ADHD motor research to consider co-occurring developmental factors such as DCD and ASD (Reiersen et al., 2008). There is some overlap in the literature reporting disruption to motor brain regions, specifically fronto-striatal-cerebellar brain circuitry in ASD and ADHD (Bradshaw, 2001). Upper limb motor studies have provided insight in understanding fronto-striatal and cerebellar type motor impairment in these disorders using a range of tasks (Rinehart et al., 2001, 2006a; Papadopoulos et al., 2012a, 2012b). Numerous gait studies have also considered basal ganglia and cerebellar type motor anomalies in children with ASD (Ambrosini et al., 1998; Rinehart et al., 2006b, 2006c; Calhoun et al., 2011; Nobile et al., 2011; Nayate et al., 2012). Quantitative gait analysis techniques report that the gait pattern of children with autism at a preferred walking pace is characterised by a wide base of support (Nayate et al., 2012; Nobile et al., 2011), variation (both increases and decreases) in stride length and stride time variability (Rinehart et al., 2006a, 2006b; Nobile et al., 2011) as well as increased cadence (Calhoun et al., 2011). Investigations using qualitative gait methods in ASD have also reported a wide base of support (Ambrosini et al., 1998) and reduced smoothness of gait and postural abnormalities of the head and trunk (Rinehart et al., 2006c). Unlike children with ASD who may show characteristic gait disturbances from an early age (Teitelbaum et al., 2004), there have been relatively fewer investigations of gait in children with ADHD. To our knowledge only two studies have measured gait variables in children with ADHD (Leitner et al., 2007; Buderath et al., 2009) using instrumented gait analysis techniques. In a study by Buderath et al. (2009) the gait and postural abnormalities of children with ADHD-CT (on medication; n ¼10) were compared to a cerebellar lesion and typically developing (TD) group. No differences between the ADHD group and TD controls were found in stride length, cadence or stride timing on a treadmill walking task, however ADHD participants scored significantly lower than TD controls when walking backwards on a beam. In a paced stationary stepping task with an external cue (metronome), the ADHD group was slightly slower than TD controls in the fast paced condition. This pattern was consistent with the cerebellar lesion group, providing preliminary support that ADHD may be associated with cerebellar dysfunction. Another study by Leitner et al. (2007) investigated the effect of dual tasking on gait function in children with ADHD without significant motor impairment (9–16 years; n¼ 16), off methylphenidate. They reported no difference between the ADHD and TD groups in the preferred walking condition (single task condition; off medication), although a trend to higher stride time variability was noted in the ADHD group (p ¼0.09). In the dual task condition, stride time variability significantly reduced in the ADHD group compared to the baseline (single task) condition. Stride time variability also reduced when ADHD individuals were medicated compared to baseline. It was
concluded that methylphenidate had a positive effect on gait, reducing the mildly increased stride time variability in the ADHD group. The aim of the current study is to characterise the gait of children with ADHD using the same protocol used in Nayate et al.'s (2012) study of gait in children diagnosed with autism and Asperger's disorder to further inform our understanding of disrupted underlying neural circuitry in ADHD. It was hypothesised that there would be no difference in gait variables (speed, stride length, cadence, base of support and double support time) between the ADHD group and the TD group in the preferred baseline walking condition. Further based on the gait studies conducted by Leitner et al. (2007) and Buderath et al. (2009) it was hypothesised that the ADHD group may display subtle timing anomalies. In addition, based on previous research in ASD that indicates a significant relationship between motor disturbance and social-communicative disturbance (Qiu et al., 2010; Papadopoulos et al., 2012b) we predicted a positive association between gait variables characteristic of ASD such as a wider base of support and increased stride length variability and social-communication symptoms in children with ADHD-CT. Lastly, based on the finding that children with ADHD-inattentive type may experience more motor difficulties than other subtypes (Pitcher et al., 2003), the association between inattentive symptoms measured on the Conner's Rating Scale and spatio-temporal gait variables was explored.
2. Method 2.1. Participants Informed consent was obtained from parents/guardians of all participants, in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Human Research Ethics committee at Southern Health and Monash University, Melbourne Australia. Fourteen boys diagnosed with ADHD – Combined type (ADHD-CT) aged between 7 and 13 years were recruited from Private Paediatricians in Melbourne. The paediatricians specialised in ADHD with 10–20 years of clinical experience in the field, and undertook further assessment and diagnosis of ADHD-CT. These children fulfilled DSM-IV-TR (APA, 2000) criteria for ADHD – Combined type (ADHD-CT). Diagnosis of ADHD-CT was further confirmed by a doctoral-level trained graduate student (author N.P.) under the supervision of a clinical psychologist (author N.R.) using the Conners Rating Scale (Conners, 2001), parent interviews, direct child observations and information from teachers and therapists. Paediatricians also confirmed that children with a diagnosis of ADHD-CT did not have a co-morbid diagnosis of autistic disorder, Asperger's disorder or pervasive developmental disorder not otherwise specified based on their assessment and medical records. Participants who entered the study were further screened for a possible diagnosis of ASD using the Autism Diagnostic Observation Scale (ADOS) by a qualified researcher. No participants were excluded based on elevated ADOS scores (ASD cut off score¼7). Additional exclusion criteria included co-morbid medical (e.g., tuberous sclerosis), hearing or visual impairments, or genetic (e.g., Fragile X syndrome) disorders. The majority of participants in the study (12/14) was on stimulant medication such as methylphenidate (Ritalin). Participants on medication discontinued medication at least 24 h before testing commenced. A reference sample of 13 typically developing (TD) boys aged between 7 and 14 years were recruited from local schools and the community. The TD children had no prior history of psychological, neurological or psychiatric diagnosis. This was confirmed by researchers via interview with children's parents, from whom information on developmental, medical and psychiatric history was obtained (i.e. whether children had any previous diagnoses or had received any intervention). All participants in the TD group were also screened for ADHD-CT symptoms using the Conner's Rating Scale (Conners, 2001) and for autistic symptoms using the Social Responsiveness Scale (Constantino and Gruber, 2005). One TD child was excluded for having Social Responsiveness Scale (SRS) scores indicative of clinically elevated (t score476) social responsiveness difficulties. The intellectual functioning of TD boys was assessed using the Wechsler Abbreviated Scale of Intelligence (WASI) (Wechsler, 1999) or the Wechsler Intelligence Scale for children 4th edition (WISC-IV) (Wechsler, 2005), and the intellectual functioning of children with ADHD-CT was assessed using the WISC-IV. The WASI and WISC-IV are highly compatible with.87 correlation between their full scale IQ scores (Wechsler, 1999). Motor proficiency was assessed and children were screened for DCD using the Movement Assessment Battery for Children
Please cite this article as: Papadopoulos, N., et al., An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study. Psychiatry Research (2014), http://dx.doi.org/10.1016/j.psychres.2014.04.037i
N. Papadopoulos et al. / Psychiatry Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎ Table 1 Demographic information for ADHD-CT and typically developing (TD) control groups.
Age (months) Height (cms) Leg length (cms) Weight (kg) FSIQ VCI PRI
ADHD-CT (n¼14)
Typically developing controls (n¼13)
129.8 147.6 76.1 43.0 97.5 94.8 102.5
129.2 150.7 77.9 46.9 105.4 105.0 107.6
(24.5) (10.4) (6.4) (14.8) (12.5) (13.4) (14.5)
(33.7) (21.4) (12.2) (23.0) (17.5) (17.4) (17.5)
(2nd edition) with a cut-off of o 15th percentile (Henderson et al., 2007). No participants were excluded for experiencing significant motor impairment. Independent measures t-tests were conducted to investigate the effect of age, intelligence, height and weight between groups. There was no significant difference in age (t(25)¼ 0.056, p ¼ 0.956), intellectual functioning; (Full Scale IQ (FSIQ) t(25) ¼ 1.36, p ¼0.188, Perceptual Reasoning Index (PRI) t(25) ¼ 0.829, p¼ 0.415, Verbal Comprehension Index (VCI) t(25)¼ 1.717, p¼ 0.098), height t(25)¼ 0.482, p ¼0.634 and weight t(25)¼ 0.527, p ¼ 0.603 between groups (see Table 1 for participant characteristics). 2.2. Measures 2.2.1. Conners Rating Scale The inattention and hyperactivity-impulsivity subscales from the parent reported Conners Rating Scale (CRS – long form) (Conners, 2001) were utilised in this study. The CRS is a commonly used standardized screening instrument that measures DSM-IV-TR ADHD symptomatology. The parent long form consists of 80 items, measuring indices of oppositional behaviour problems, cognitive/inattentive behaviour, hyperactivity, anxious-shy behaviour, perfectionism, social problems, psychosomatic problems for children aged 3–17 years. Test–retest reliability ranges from 0.47 to 0.85 and internal consistency ranges from 0.73 to 0.91 (Conners, 2001). 2.2.2. Developmental Behavioural Checklist Communication disturbance was assessed using the Developmental Behavioural Checklist –Parent Report (DBC-P) (Einfeld and Tonge, 2002). The DBC is a 96 item quantitative measure of behavioural and emotional disturbance in young people aged 4–18 years, is comprised of five subscales, and has demonstrated good validity and reliability (Einfeld and Tonge, 1995). The behavioural subscales include disruptive/antisocial behaviour, self absorbed, communication disturbance (a measure of communication deviance), anxiety and social relating. Items are scored on a Likert scale ranging from 0—“not true as far as you know” to 3–“often true or very true”. The DBC generates a rating of overall behavioural disturbance, as well as a rating on the five behavioural subscales mentioned above.
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to the line of progression of the opposite foot). A Y-axis range (maximum distance travelled laterally in the horizontal plane of the mat during a walk) was also calculated. Mean values for each walk were calculated and averaged across all trials in that condition, to produce a global mean for each gait variable in each condition. Step to step variability was calculated as the mean standard deviation from each trial for speed, cadence, stride length, double support and base of support. Data were analysed using independent samples t-tests to examine group differences. The data for each of these variables were tested for normal distributions using box plots and the Kolmogorov–Smirnov statistical test. Assumptions of normality were met for all variables except cadence in the fast walking condition. A Mann–Whitney U test was therefore conducted to investigate group differences for this condition. To control for anthropometric differences, data were normalised for each walk in accordance with the methods described in Hof (1996). Effect sizes for gait variables were calculated using Cohen's d. Spearman's correlations were conducted to investigate any significant relationships between communication disturbance measured on the DBC and the five subscale scores as well as inattentive symptoms measured on the CRS and the five gait variables.
3. Results There was no significant difference between the ADHD-CT group and the TD group in the baseline preferred walking or slow condition for speed, cadence, stride length, double support or base of support. However, large and moderate effect sizes were reported for cadence (0.84) and y-axis range (0.65) respectively. At self selected fast speed, the ADHD-CT group was faster (t(25) ¼ 2.31, p ¼0.030) than the TD group, due to increased cadence (U¼33, p ¼0.005) with large effect sizes (0.92) reported (see Table 2 for all effect sizes). Notably, in all conditions, children with ADHD walked with comparable stride length but higher cadence than the TD group, with the increased cadence in the ADHD group also nearing significance in the preferred (p ¼0.052) and slow conditions (p ¼0.066). Normalisation of the data according to Hof (1996) did not alter any of the findings. Variability did not differ between groups in any of the walking conditions, although a strong trend for increased variability in cadence was evident in the preferred (p¼ 0.07) and fast condition (p ¼0.058) in the ADHD group. Moderate effect sizes were reported for cadence in the preferred walking condition and moderate effect sizes were reported for variability in most spatio-temporal gait variables (speed, cadence, stride length, and double support) in the fast walking condition (see Table 3 for all effect sizes). Table 2 Spatio-temporal gait parameters.
2.3. Procedure Condition Participants attended a single 60 min session at the Clinical Research Centre for Movement Disorders & Gait, Kingston Centre Cheltenham. Gait was measured using the GAITRites system (CIR system Inc, Clifton, N.J): an electronic walkway 830 cm 89 cm, with pressure sensors spaced 1.27 cm apart embedded in a horizontal grid. A 2 m non-recordable zone was added on each end of the walkway to minimise the effects of acceleration and deceleration. After each walk, data were analysed using GAITRite software. Anthropometric measures (height, weight and leg length) were taken before the commencement of walking conditions. All participants completed five trials of the three walking conditions in the following order: (1) Preferred walkingparticipants were instructed to walk at their preferred speed, (2) fast walkingparticipants were instructed to walk at a faster pace than their preferred speed, but not to run, and (3) slow walking- participants were instructed to walk at a pace slower than their preferred speed. Participants were given one demonstration trial and a practice trial prior to the commencement of each different walking condition to make sure that they understood the task. 2.4. Data analysis For each walk the GAITRite software generated step-to-step values for a range of gait variables. Spatial-temporal parameters (average of left and right) were extracted which included: speed (cm walked per second), cadence (steps taken per minute), stride length (combined left and right footfalls in full gait cycle), double support (percentage of time both feet are grounded in a complete gait cycle), heelto-heel base of support (perpendicular distance from the heel point in one footfall
ADHD-CT (n¼ 14)
TD controls (n¼ 13)
P-value
Effect size
Preferred Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double Support % gait cycle Base of support (cm) Y-axis range (cm)
130.7 122.3 128.4 23.5 8.7 23.3
(13.9) (7.4) (10.3) (3.1) (2.1) (3.4)
126.9 115.0 133.4 24.4 8.6 21.6
0.531 0.052 0.428 0.447 0.926 0.114
0.254 0.843 0.322 0.309 0.038 0.656
Slow Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double support % gait cycle Base support (cm) Y-axis range (cm)
95.8 104.0 109.6 26.7 8.8 23.7
(19.5) 86.5 (24.8) (11.2) 93.95 (15.81) (12.7) 109.4 (23.1) (3.3) 29.1 (5.3) (2.2) 8.3 (2.4) (3.9) 22.1 (3.3)
0.288 0.066 0.985 0.175 0.619 0.283
0.435 0.769 0.007 0.559 0.202 0.440
Fast Speed (cm/s) Cadence (steps/min) Stride length (cm) Double support % gait cycle Base support (cm) Y-axis range (cm)
180.6 147.0 147.7 19.5 9.5 22.9
(18.6) (12.1) (12.6) (2.8) (2.1) (2.6)
0.030n 0.005n 0.830 0.052 0.140 0.165
0.923 1.094 0.089 0.816 0.610 0.572
n
157.1 129.9 146.0 21.9 8.2 21.5
(17.3) (10.4) (20.8) (3.0) (2.5) (1.6)
(33.0) (19.7) (26.7) (3.4) (2.2) (2.6)
P o 0.05.
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Table 3 Variability (S.D.) for gait parameters. Condition
ADHD-CT (n ¼14)
TD controls (n ¼13)
P-value
Effect size
Preferred Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double Support % gait cycle Base of support (cm)
7.5 4.5 3.9 1.0 1.1
(5.2) (4.3) (1.8) (0.4) (0.8)
5.7 1.9 4.1 1.0 1.1
(3.3) (1.61) (2.2) (0.3) (0.3)
0.318 0.070 0.685 0.985 0.735
0.408 0.701 -0.164 -0.007 -0.137
Slow Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double Support % gait cycle Base support (cm)
8.2 5.2 6.2 1.6 1.4
(4.9) (4.2) (3.2) (1.0) (0.5)
6.6 3.3 5.8 1.6 1.2
(3.6) (2.3) (2.5) (1.1) (0.6)
0.336 0.148 0.734 0.881 0.290
0.393 0.484 0.138 0.060 0.433
Fast Speed (cm/s) Cadence (steps/min) Stride Length (cm) Double Support % gait cycle Base support (cm)
14.4 9.4 5.7 1.7 1.4
(15.2) (8.2) (4.4) (1.3) (0.7)
7.1 4.1 3.4 1.1 1.3
(5.3) (5.0) (1.1) (0.5) (0.7)
0.106 0.058 0.088 0.089 0.591
0.665 0.759 0.708 0.702 0.217
3.1. Association between social-communication and gait variables A series of Spearman's correlations were conducted to investigate the relationship between gait variables in all walking conditons and emotional behavioural disturbance (total DBC score) as well as the DBC subscales for the ADHD-CT group. Only communication disturbance (a measure of social communication deviance) was significantly positively correlated with base of support (rs ¼ 0.56, p ¼0.037). There were no other significant correlations between any of the gait variables and DBC subscales. 3.2. Association between ADHD symptoms and gait variables The severity of Inattentive symptoms on the CRS was significantly correlated with speed (rS ¼ 0.55, p¼0.04) and cadence (rS ¼ 0.60, p¼0.02) in the fast walking condition, although not in the slow (speed; rS ¼ 0.06, p¼ 0.753, cadence; rS ¼ 0.07, p¼0.727) or preferred (speed; rS ¼ 0.05, p¼0.808, cadence rS ¼0.19, p¼ 0.353) walking conditions. There were no other significant correlations between inattentive symptoms and any other gait variables. There were also no significant correlations between the hyperactivity-impulsivity subscales of the CRS and any of the gait variables.
4. Discussion This study aimed to investigate the gait profile of a sample of children diagnosed with ADHD-CT who had been screened for DCD and ASD. The finding of no significant difference in spatiotemporal gait variables between the ADHD and TD groups in the preferred walking condition is largely consistent with previous gait studies (Leitner et al., 2007; Buderath et al., 2009). In addition, differences in timing regulation with reported large effect sizes for the preferred, slow and fast walking conditions support previous motor studies (see Hart et al., 2012) that consistently report timing deficits in children (Luman et al., 2009) and adults (Valera et al., 2010) with ADHD. Difficulties in timing regulation have long been attributed to cerebellar dysfunction (Ivry and Keele, 1989); a brain region consistently implicated in ADHD (Berquin et al., 1998). However, the current study extends previous ADHD motor
research in defining the gait profile characteristic of children with ADHD without clinically significant symptoms of ASD and DCD. It has previously been documented that up to 30% of individuals with ADHD experience clinically significant autistic symptoms (Reiersen et al., 2007). Further, in our previous study of motor functioning that comprised a sub-set of participants from this study (Papadopoulos et al., 2012c), social responsiveness measured on the Social Responsiveness Scale (SRS) was found to be related to error variability on a repetitive upper limb Fitts' aiming task. The current study found a moderate positive correlation between increased levels of communication disturbance measured on the DBC and a wider base of support in ADHD. Inattentive symptoms were also found to be associated with increased speed and cadence in the fast walking condition. This finding partially supports previous parent- reported motor studies (Reiersen et al., 2008) as well as motor studies using standardized assessment batteries (Piek et al., 1999;Pitcher et al., 2003). The link between inattention and motor problems is also apparent in ADHD studies that report an improvement in motor performance when children are on medication (e.g., methylphenidate) (Leitner et al., 2007; Brossard-Racine et al., 2012). Despite this, it is currently unclear whether a particular ADHD subtype (e.g., ADHD-PI) is associated with a different gait profile. More broadly, larger scale gait studies including well-defined groups of children with neurodevelopmental disorders will be necessary to see if gait characteristic differ according to diagnosis (e.g., ADHD, ASD), and degree of comorbidity. The current gait study is a cross sectional study, and although it allows an investigation of motor performance at a time point it does not provide a picture of motor performance across the developmental trajectory. Future research should therefore endeavour to investigate motor performance in ADHD longitudinally. Secondly, the small sample size, as well as multiple statistical tests limits the power of the current study and our ability to generalise our findings. Inadequate power may have limited our ability to detect significant differences in variability of some gait variables. Specifically, moderate effect sizes were reported for speed, cadence, stride length and double support time in the fast walking condition which may provide some evidence of a more variable gait pattern at fast walking speed for the ADHD-CT group. Large effect sizes for cadence across all walking conditions (preferred, slow and fast) may also indicate that cadence may be affected in all walking conditions and requires further exploration. Future research is necessary to investigate the gait profile of clearly defined groups of children diagnosed with autism, AD and ADHD at the same time point. Replication of the current study using larger sample sizes to increase power is also necessary. Lastly, the use of blinded investigators conducting the gait trials and sensitive gait paradigms such as 3D motion analysis may allow a more comprehensive unbiased investigation of whole body movement across time and space and enable greater detection of gait anomalies. These preliminary findings indicate that the gait profile of nonmedicated children with ADHD without ASD and DCD reflects a deficit in timing regulation when children are asked to walk at a fast pace, consistent with cerebellar disruption. Future research should investigate whether the unique profile of gait disturbance characteristic of individuals with ADHD may be useful in objectively distinguishing between children with autism, Asperger's disorder, and other neurodevelopmental conditions.
Appendix A. Supplementary materials Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.psychres.2014.04.037.
Please cite this article as: Papadopoulos, N., et al., An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study. Psychiatry Research (2014), http://dx.doi.org/10.1016/j.psychres.2014.04.037i
N. Papadopoulos et al. / Psychiatry Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎
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Please cite this article as: Papadopoulos, N., et al., An investigation of gait in children with Attention Deficit Hyperactivity Disorder: A case controlled study. Psychiatry Research (2014), http://dx.doi.org/10.1016/j.psychres.2014.04.037i
