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. Author manuscript; available in PMC: 2021 Apr 1.
Published in final edited form as: Hum Mov Sci. 2020 Feb 8;70:102584. doi: 10.1016/j.humov.2020.102584

Gait Control in Children with Attention-Deficit/Hyperactivity Disorder

Roger W Simmons 1, Tenille C Taggart 2,3, Jennifer D Thomas 2, Sarah N Mattson 2, Edward P Riley 2
PMCID: PMC7307606  NIHMSID: NIHMS1595672  PMID: 32217203

Abstract

The current profile of gait control in children with ADHD is incomplete and predominately based on children walking forward at a self-selected pace. There are no studies of potential gait deficits in this clinical population when walking in different directions in combination with varying rates of stepping that are freely selected and entrained to an external stimulus. The purpose of the current study was to address this lack of information by assessing gait of children aged 7-17 years with (n = 17) and without (n = 26) ADHD. Participants walked forward and backward along an electronically instrumented carpet at a self-selected stepping rate and in synchrony to a metronome that dictated an increased and decreased stepping rate. Using repeated measures analysis of covariance (ANCOVA) to assess spatiotemporal gait parameters, results showed that children with ADHD exhibited a significantly exaggerated, toes ‘turned out,’ foot position for all walking conditions compared to typically developing children. When walking backward, children with ADHD produced an increased step width, higher stepping cadence, and increased velocity. Additionally, coefficient of variation ratios indicated that children with ADHD produced greater variability of velocity, cadence, and step time for all walking conditions, and greater variability for stride length when walking at an increased stepping rate. Results were interpreted in terms of clinical significance and practical ramifications that inform rehabilitation specialists in designing therapies that ameliorate the reported gait deficits.

Keywords: ADHD, gait, rehabilitation, motor skills, GAITrite

1. Introduction

Attention-deficit/hyperactivity disorder (ADHD) is the most common childhood neurobiological syndrome, affecting an estimated 6-12% of children and adolescents (Polanczyk, de Lima, Horta, Biederman, & Rohde, 2007; Polanczyk, Willcutt, Salum, Kieling, & Rohde, 2014). Children with ADHD experience core symptoms of inattention, hyperactivity, and poor response inhibition (American Psychiatric Association, 2013). Additionally, a significant proportion of children with the syndrome experience impaired fine and gross motor skills (Kaiser, Schoemaker, Albaret, & Geuze, 2015; Singh, Yeh, Verma, & Das, 2015), including static (Ren, Yang, Cheng, Feng, & Wang, 2014) and dynamic postural instability (Kim, Hyun, Jung, Son, Cho, Kee, & Han, 2017), impaired coordination, speed, and accuracy of limb movements, dysrhythmias, and motor overflow (Patankar, Sangle, Shah, Dave, & Kamath, 2012), increased reaction time variability (Weigard, Huang-Pollock, Brown, & Heathcote, 2018), and limited regulation of timing and force output (Pitcher, Piek, & Barrett, 2002).

Although the etiology of ADHD remains unclear, structural and functional anomalies in the central nervous system (CNS) of children with ADHD may contribute to the associated motor deficits. Reduced total brain volume (Dougherty, Evans, Myers, Moore, & Michael, 2016) has been reported together with volumetric reduction of the basal ganglia (Frodl and Skokaukas, 2012), corpus callosum (Schweitzer, Faber, & Grafton; 2000), cerebellum (Stroodley, 2016), and the frontal, parietal, and temporal lobe structures (Jacobsen, 2018). Appropriate planning and execution of motor skills is further hindered by attenuated neural connectivity between multiple brain structures (Kim et al., 2017; Rosch, Mostofsky, & Nebel, 2018), which also has the potential to negatively impact cognitive processes of attention and executive function.

Confirmation of atypical neural structure in children with ADHD via brain imaging has prompted predictions of motor skill dysfunction in a variety of actions, including walking. However, relatively few studies have examined gait control in children with ADHD and results have been equivocal. For instance, some studies report that children with ADHD walk with greater anterior pelvic angle (Naruse, Fujisawa, Yatsuga, Kubota, Takiguchi, Shimada, Imai, Hiratani, Kosaka, & Tomoda, 2017), exhibit idiopathic toe-walking (Insuga, Vinues, Losada del, Pozo, Morena, Gonzalez, Ruiz, & Carmen, 2018), have difficulty walking backward on a beam of decreasing width and produce imprecise synchronized stepping (Buderath, Gartner, Frings, Christiansen, Schoch, Konczak, Gizewski, Hebebrand, & Timmann, 2009), have greater velocity and cadence when walking at a self-selected fast speed (Papadopoulos, McGinley, Bradshaw, & Rinehart, 2014), and produce greater stride time and stride length variability (Manicolo, Grob, Lemola, & Hagmann-von Arx, 2016; Mohring, Klupp, & Grob, 2018). Conversely, other studies have found no differences between the gait of children with and without ADHD during forward self-paced walking (Leitner, Barak, Giladi, Peretz, Eshel, Gruendlinger, & Hausdorff, 2007; Manicolo, Grob, & Hagmann-von Arx, 2017) or when walking backward at a self-selected pace (Viggiano, Travaglio, Cacciola, & Di Costanzo, 2015).

With the exception of three studies that assessed backward walking (Viggiano et al., 2015), walking forward at different self-selected speeds (Papadopoulos et al., 2014), and stepping in place in synchrony to a tone (Buderath et al., 2009), investigations of gait in children with ADHD have been limited to assessing forward walking at a single self-selected speed. Little is known about gait of these children when walking in different directions in combination with different rates of stepping that are freely selected and entrained to an external stimulus, even though these walking conditions underpin numerous childhood activities such as marching, engaging in music based rhythm training and dancing.

Experiencing ADHD-related motor deficits, including gait, has significant practical ramifications. Compared to typically developing peers, ADHD children are less likely to exercise or participate in organized sports (Kim, Mutyala, Agiovlasitis, & Fernhall, 2011), which increases the risk for long-lasting adverse mental and physical health conditions, including obesity and depression (Kim et al., 2011; Nigg, 2013). Additionally, higher rates of accidental injuries (Barkley, 2014; Brook & Boaz, 2006) and increased use of medical and emergency services inflate economic costs (Birnbaum, et al., 2005; Matza, Paramore, & Prasad, 2005). Amelioration of ADHD-related motor deficits may have the effect of reducing the burden on public health services, however attempts to improve ADHD-related motor functioning can only occur when rehabilitation therapies are based on empirically derived data that identify specific motor anomalies.

In summary, the rationale for the present study stems from the following: a) the current profile of gait in ADHD children is incomplete, and b) identifying ADHD-related gait deficits serves to inform clinicians and rehabilitation specialists in formulating appropriate therapeutic exercises designed to ameliorate gait deficits, which in turn, addresses the negative long-term psycho-social and public health consequences of ADHD.

In the present study we used six spatiotemporal gait parameters (and variability of these parameters), to assess the gait of children with and without ADHD during forward and backward walking at a self-selected stepping rate and while stepping in synchrony with a metronome set at a decreased and increased rate. Gait spatiotemporal parameters were selected for the following reasons: (a) they are frequently cited in the gait literature for children with ADHD (Lythgo, Wilson, & Galea, 2011), (b) they have specific neural correlates that can be compromised in children with ADHD, including the cerebellum (Rao & Louis, 2016), prefrontal cortex (Burhan, Subramanian, Pallaveshi, Barnes, & Montero-Odasso, 2015), basal ganglia (Chastan, Westby, Yelnik, Bardinet, Do, Agid, & Welter, 2009), corpus callosum (Ryberg, Rostrup, Paulson, Barkhof, Scheltens, van Straaten, et al., 2011), and motor cortex (Annweiler, Beauchet, Bartha, Wells, Borrie, Hachinski, & Montero-Odasso, 2013), and (c) these parameters are sensitive to gait anomalies as reported for other neurodevelopmental disorders such as developmental coordination disorder (Biotteau, Chaix, Blais, Tallet, Peran, & Albaret, 2016) and fetal alcohol spectrum disorder (Taggart, Simmons, Thomas, & Riley, 2017). The use of multiple parameters of gait also facilitates assessment of the different time scales associated with gait (e.g., stepping in place produces zero time change in horizontal velocity but a discrete time value for each step) and spatial orientation (e.g., step width in the frontal plane versus the sagittal plane), especially when assessing gait variability (Socie & Sosnoff, 2013).

Based on previous results of ADHD-related gait studies of children with other neurodevelopmental syndromes, and our current understanding of the role played by neurological substrates in gait control, we hypothesize that in comparison to typically developing peers, children with ADHD will exhibit significant gait deficits across the six test conditions. Specifically, ADHD-related gait deficits are predicted in the form of increased walking velocity and stepping cadence, decreased stride length and step time, together with an accentuated global foot angle and step width. We also predict greater variability for all indices of gait performance for these children.

2. Methods

2.1. Participants

Participants aged 7-17 years with a clinical diagnosis of ADHD-Combined Type (ADHD group: n =17) and typically developing children (CON group: n =26) were enrolled at the Center for Behavioral Teratology (CBT) at San Diego State University. Children were required to have English as their primary language, were between the ages of 7-17 years of age, and have a Full scale IQ (FSIQ) greater than 70, as assessed by the Wechsler Intelligence Scale for Children - Third (Wechsler, 1991) or Fourth Editions (Wechsler, 2003), or the Differential Ability Scales-General Conceptual Ability (DAS-GCA; Mattson, Crocker, & Nguyen, 2011).

The ADHD group met DSM-IV diagnostic criteria for ADHD as assessed by the Computerized Version of the National Institute of Mental Health Diagnostic Interview Schedule for Children Version IV (C-DISC-4.0; National Institute of Mental Health, 1997), which has high reliability and validity in diagnosis of ADHD (Shaffer et al., 2000). Six children with ADHD were tested while on prescribed medication (e.g., methylphenidate) and eleven children were medication free. As medication may improve some gait anomalies (Leitner et al., 2007), we adopted the position that any aberration in gait would be exacerbated if medication were withheld. Children in the CON group did not meet diagnostic nor subclinical criteria for ADHD. The CON and ADHD groups were matched as closely as possible on age, height, FSIQ, and socioeconomic status (SES; assessed using Hollingshead’s [1975] four domains of marital status, retired/employed status, educational attainment, and occupational prestige).

2.2. Apparatus

Spatiotemporal parameters of gait were assessed using an electronically instrumented carpet (90 cm wide x 700 cm long × 3.2 mm high; Platinum GAITRite® Walkway system; CIR Systems Inc., Sparta, NJ). The walkway was embedded with 13,824 sensors that provided spatial and temporal resolution of 1.27 cm and 8 ms, respectively, with high levels of reliability (Thorpe, 2005) and validity (Bilney, Morris, & Webster, 2003) in gait assessment of children. Data were electronically collected in real time at a rate of 80 Hz and stored on a laptop computer for follow-up analysis.

2.3. Procedure

Participants walked along an electronically instrumented carpet walkway located in a quiet and windowless area. Acceleration and deceleration effects were minimized by having children begin and finish each walk from strips of blue masking tape placed on the floor 1 m from the front and back edge of the walkway, respectively. Participants completed six blocks of seven walking trials (42 trials total). Each trial produced several steps as participants traversed the walkway. In the first block of trials, children walked forward at a self-paced stepping rate along the length of the electronic walkway. The next two blocks of trials also involved forward walking while stepping in synchrony to a metronome-driven auditory signal set to an increased or decreased stepping rate of 20% higher or 20% lower than the participant’s average self-selected stepping rate recorded for the first trial block, respectively. Participants completed three additional blocks repeating this sequence while walking backward. The order in which participants completed the increased and decreased stepping rate trial blocks was counterbalanced across participants to reduce any potential confounds. For all walking trials, participants wore shoes and initiated walking in their own time. After testing, each child was provided a small monetary reward. Prior to all testing procedures participants and their legal guardians provided written assent and consent, respectively, in compliance with San Diego State University’s Institutional Review Board requirements.

2.4. Spatiotemporal gait parameters

Velocity (in centimeters per second [cm/s]), cadence (the number of steps per minute [steps/min]), stride length (the distance in centimeters [cms] between the heel points of two consecutive footprints of the same foot), global foot angle (the angle in degrees of the right foot measured relative to the line of the direction of travel), step width (the vertical distance in centimeters between the center of one footprint and the center of the previous footprint on the opposite foot), and step time (the time in milliseconds [ms] from first contact of one foot to first contact of the opposite foot) served as indices of gait performance. The effect of leg length on gait was controlled by normalizing data for each spatiotemporal parameter (with the exception of global foot angle, which is dimensionless) into dimensionless units according to methods described by Hof (1996). Variability of each gait parameter was indexed by the coefficient of variation (CV = [standard deviation/mean]*100) and expressed in percent (%).

2.5. Data analysis and statistics

Differences in average age, height, FSIQ and SES for each group were tested using t-tests for independent samples. The first two trials of each block of walking were considered practice trials and excluded from analysis. Data recorded for each step in the remaining five trials were used to produce aggregate mean and standard deviation scores for each gait parameter. Individual data values greater than 2.5 standard deviations from the within-group block mean were considered outliers and subsequently removed from analyses. Analyses were conducted using SPSS version 24.0 (SPSS Inc., Chicago, Illinois, USA).

Repeated measures analysis of covariance (ANCOVA) tested for within- and between-group differences using a 2 (Group) x 3 (Stepping Rate) x 2 (Direction) design with an alpha-level set to 0.05. Age was included as a covariate. Additionally, 95% confidence intervals (CI) were calculated for main effects of Group. Assumptions of sphericity and homogeneity of variance were examined using Mauchly’s and Levene’s test, respectively. Violations of sphericity prompted the use of the Greenhouse-Geisser conservative estimate of degrees of freedom, and violations of homogeneity of variance were addressed by using Games-Howell procedures for post hoc comparisons. Significant interactions of two or more variables were further analyzed using univariate ANOVAs and Bonferroni corrections were applied for post-hoc comparisons.

3. Results

3.1. Demographic data

No significant demographic differences emerged between children with ADHD and typically developing children for age, height, FSIQ and SES (see Table 1).

Table 1.

Demographic characteristics by Group.

ADHD (n = 17) CON (n = 26)
Sex (M:F; [M:F%]) 14:3 [82:18] 18:8 [69:31]
Age (years; M [SD]) 11.6 [2.4] 11.3 [3.2]
Height (cm; M [SD]) 154.1[14.5] 146.4 [19.9]
FSIQ1 (M [SD]) 106.4 [9.3] 112.1 [15.4]
SES2 (M [SD]) 50.2 [8.4] 49.2 [10.4]
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Notes. ADHD = attention-deficit/hyperactivity disorder group. CON = control group (i.e., typically developing children).

1

Intelligence scores were derived from the Wechsler Intelligence Scale for Children-III, the Wechsler Intelligence Scale for Children-IV, or the Differential Ability Scales-General Conceptual Ability (DAS-GCA) depending on time of enrolled.

2

Socioeconnomic status (SES) was estimated using the Hollingshead Four Factor Index of Social Status (Hollingshead 1975, unpublished data).

3.2. Gait performance

For each gait parameter we first present results for group mean values collapsed across Stepping Rate (Figure 1) and Walking Direction (Figure 2).

Fig 1.

Fig 1

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Mean dimensionless values (with standard errors) of gait parameters for the ADHD (black column) and CON (white column) groups by Stepping Rate condition. Data are collapsed across Walking Direction. A = Decreased Stepping Rate; B = Self-selected Stepping Rate; C = Increased Stepping Rate. Asterisk indicates a significant difference (p < .05) between groups (ADHD vs. CON) within the Stepping Rate condition.

Fig 2.

Fig 2

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Mean dimensionless values (with standard errors) of gait parameters for the ADHD (black column) and CON (white column) groups by Walking Direction. Data are collapsed across Stepping Rate. A = Backward walking: B = Forward walking. Asterisk indicates a significant difference (p < .05) between groups (ADHD vs. CON) within Walking Direction.

This section is followed by results for coefficient of variation data collapsed across Stepping Rate (Figure 3) and Walking Direction (Figure 4).

Fig 3.

Fig 3

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Coefficients of Variability (with standard errors) of gait parameters for the ADHD (black column) and CON (white column) groups by Stepping Rate condition. Data are collapsed across Walking Direction. A = Decreased Stepping Rate condition; B = Self-selected Stepping Rate condition; C = Increased Stepping Rate condition. Asterisk indicates a significant difference (p < .05) between groups (ADHD vs. CON) within the Stepping Rate condition.

Fig 4.

Fig 4

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Coefficients of Variability (with standard errors) of gait parameters for the ADHD (black column) and CON (white column) groups by Walking Direction. Data are collapsed across Stepping Rate. A = Backward walking; B = Forward walking. Asterisk indicates a significant difference (p < .05) between groups (ADHD vs. CON) within the Walking Direction condition.

3.3. Velocity

Children of both groups increased walking speed as mean Stepping Rate changed from decreased stepping (29.7) to self-paced stepping (37.9) to increased stepping (43.8) (F[1.9,75.5] = 13.6, p = .001,η² = .26). A main effect of Direction was also revealed (F[1,39] = 34.7, p = .001, η2 = .47) as well as a significant Group X Direction interaction (F[1,39] = 5.9, p = .02,η2 = .13). Post hoc analysis revealed that the ADHD group walked with greater velocity when moving backward (ADHD = 31.3: CON = 29.5) but not during forward walking (ADHD = 43.1: CON = 44.6).

Gait velocity variability was significantly greater for the ADHD group (6.2%, 95% CI [5.5, 6.9]) than the CON group (4.5%, 95% CI [3.9, 5.1]) for both walking Directions and all three Stepping Rates (F[1,33] = 14.7, p = .001,η2 = .31).

3.4. Cadence

Main effects and interactions of Direction and Stepping Rate were interpreted in terms of a higher order interaction between Group X Direction X Stepping Rate (F[1.9,69] = 3.6, p < .04,η2 = .09). Follow-up analysis revealed that the ADHD group (359.9) walked backward with greater cadence than the CON group (346.0) during the increased stepping condition (p = .03) but not during the decreased and self-paced Stepping Rate conditions.

Analysis of cadence variability indicated that the ADHD group (3.1%) was less consistent than the CON group (2.2%) across walking Direction and Stepping Rate conditions (F[1,32] = 7.7, p = .009,η2 = .20; ADHD 95% CI [3.1%, 2.6, 3.6], CON 95% CI [1.8, 2.6]). Both groups also produced greater cadence walking backwards than when walking forward (F[1,32] = 9.2, p = .005,η2 = .12).

3.5. Stride length

With data collapsed across groups, stride length was significantly smaller walking forward (1.3) than backward (1.7) (F[1,39] = 21.5, p = .001,η2 = .36).

Both groups walked with greater stride length variability when walking backward (7.5%) compared to forward walking (4.4%) (F[1,34] = 9.0, p = .005,η2 = .21). A significant Group X Stepping Rate interaction for stride length variability (F[1.9,66.1] = 5.8, p = .005,η2 = .15) was due to the ADHD group having greater stride length variability during the increased Stepping Rate condition (F[2,68] = 5.8, p = .005,η2 = .15; ADHD = 6.8%: CON = 5.6%) but not during the self-paced (ADHD = 5.7%: CON = 5.1%) and decreased Stepping Rate conditions (ADHD = 5.9%: CON = 6.7%).

3.6. Global Foot angle

For all walking conditions, the ADHD group demonstrated an exaggerated ‘turned out’ global foot angle (4.2, 95% CI [1.7, 6.7]) compared to the ‘neutral’ foot angle of the CON group that approximated the direction of travel (−0.2, 95% CI [−2.2, 1.8]; F[1,40] = 7.8, p = .008,η2 = .16).

No significant differences emerged for global foot angle variability (p >.05).

3.7. Step width

The ADHD group (0.19) produced greater step width during backward walking than the CON group (0.16; F[1,37] = 6.1, p < .02,η2 = .14) but there was no difference between the two groups when walking forward (ADHD = 0.12: CON = 0.13).

Variability of step width was comparable for the ADHD and CON groups across all testing conditions (p > .05).

3.8. Step time

Average step time duration for both groups was greatest when walking backward (.214) relative to forward walking (.199; F[1,36] = 4.6, p < .04,η2 = .11). Step time also significantly changed for both groups with Stepping Rate (F[1.5,52.8] = 25.8, p = .001,η2 = .42). The shortest step time occurred during the increased Stepping Rate condition (.172 ms), followed by the self-paced condition (.202 ms) and the decreased Stepping Rate condition (.246 ms).

Variability of step time was greater for both groups when walking backward (6.1%,) compared to forward walking (4.1%; F[1,35] = 33.6, p < .0001,η2 = .49). Additionally, a main effect of Group (F[1,35] = 6.1, p < .02,η2 = .15) indicated that the ADHD group (5.5%, 95% CI [5.0, 6.0]) produced greater step time variability than the CON group (4.7%, 95% CI [4.2, 5.1]) for both walking Directions and Stepping Rates.

4. Discussion

Results of the study partially supported the predictions that gait control in children with ADHD would be significantly different from that of typically developing children. With regard to the analysis of normalized mean data, the main differences between the groups primarily occurred during backward walking. When walking in this direction the ADHD group used greater step width, had greater stepping cadence during the increased stepping rate condition and walked with greater speed than control children. Additionally, the ADHD group used an exaggerated ‘toe out’ global foot angle regardless of walking Direction and Stepping Rate condition. This atypical foot position has been reported for one other clinical group (Taggart, et al., 2017), but to our knowledge this is the first time this gait anomaly has been observed in children with ADHD.

These gait aberrations typify the use of response strategies that increase the base of support when postural control is compromised, as is the case for children with ADHD (Mao, Kuo, Yang, & Su, 2014). However, the origin of postural instability in these children is likely more central in nature and related to previously noted structural changes in neural networks associated with ADHD that play a key role in maintaining balance (Singh, et al., 2015).

Results also indicated that children with ADHD walked with greater variability of gait velocity, cadence and step time for all testing conditions. The result for increased step time variability has not been previously reported for this clinical group but aligns with similar findings reported for stride time (i.e., the time elapsed between the first contact of two consecutive footsteps of the same foot) when children with ADHD walk forward at a self-selected pace (Mohring, et al., 2018; Manicolo, et al., 2016). In contrast to our results, other studies examining variability of velocity (Leitner et al., 2007; Manicolo et al., 2016; Manicolo et al., 2017; Papadopoulos et al., 2014) and cadence (Papadopoulus et al., 2014) indicate comparable performance for children with and without ADHD. The discrepancy between study outcomes may be partially explained by the use of different measures of gait variability (e.g., standard deviation, CV etc.) and procedures used to normalize gait velocity with respect to anthropometric features.

Increased variability of temporal gait parameters (e.g., step time) is an additional example of impaired motor timing in children with ADHD (Slater & Tate, 2018), that is likely attributable to a central, internally-based clock failing to establish and maintain an appropriate rhythm (Puyjarinet, Begel, Lopez, Dellacherie, & Della Bella, 2017). The notion of an impaired clock mechanism is supported by reports of structural and functional CNS anomalies in children with ADHD, all of which contribute to some extent to defining the temporal signature of a motor response, such as gait (Avanzino et al., 2016; Saenz et al., 2019). Whatever the source of inconsistent timing may be, our results reveal that in terms of a movement end-state, impairment equally impacts all walking conditions, whether the condition involves the relatively simple and well-practiced act of walking forward at a self selected pace or the more complex response of walking backward at a rate driven by an external signal.

When considered together, the gait aberrations we observed across all test conditions, whether temporal or spatial in nature, hint at the possibility that deficits in other gait parameters (e.g., relative timing between leg segments throughout the step cycle) occur in this clinical group and future studies should aim to confirm these behavioral ‘markers’ of ADHD.

4.1. Clinical significance

For therapists, clinicians and rehabilitation specialists it is relevant to determine if the study results have clinical as well as statistical significance. That is, do the observed gait deficits reported for the ADHD group meet the standard of a minimal clinically important difference (MCID), which is confirmed when the mean value and CI of the clinical group falls outside the CI range of the control group (Page, 2014). In our study, separation between the two groups for both walking directions and three stepping rates occurred for variability of velocity and cadence with marginal overlap of confidence intervals for variability of step time and mean global foot angle.

4.2. Practical Implications

The main practical implication of the present study centers on identifying components of gait that are adversely affected by ADHD. Knowledge of this information allows therapists and clinicians to design rehabilitation exercises in which the exercise and a known deficit share a specific motor quality, which is a central tenet of rehabilitation (Dahan et al., 2018). For example, interactive metronome training, which involves synchronizing movement with an externally driven rhythm, improves motor control (Shaffer, Jacokes, Cassily, Greenspan, Tuchman & Stemmer, 2001) and reaction time (Bartscherer & Dole, 2005; Cosper, Lee, Peters & Bishop, 2009) in this clinical group. Unfortunately, studies assessing the efficacy of rehabilitation therapies on ADHD motor related deficits are few in number and none have involved gait. However, with an improved profile of gait deficits in children with ADHD, research efforts should increasingly focus on how the deficits can be best ameliorated through rehabilitation.

4.3. Study limitations

The relatively small sample may have limited statistical power. However, some statistical and clinically significant differences are reported and are considered as reliable outcomes. To control for a potential maturational effect of age on gait performance (Manicolo et al., 2016), age was entered into all analyses as a covariate and gait parameters were normalized with respect to leg length. Furthermore, the fundamental gait pattern is established in typically developing children by three years of age (Sutherland, Olshen, Biden, & Wyatt, 1988), which is below the age of participants.

4.4. General conclusions

The present study identified several atypical gait characteristics that differentiate children with ADHD from typically developing children. For children with ADHD, backward walking was characterized by slower velocity, increased step width and stepping cadence. Additionally, these children exhibited an exaggerated, toes ‘turned out,’ foot position for all testing conditions. Gait velocity variability, cadence variability and step time variability were also greater across all walking conditions for children with ADHD, and stride length variability was greater when walking with an increased stepping rate. Additional work is required to examine how different environmental conditions affect the gait profile of children with ADHD, and the efficacy of rehabilitation exercises in treating specific gait anomalies identified by research investigations.

Acknowledgments

Funding: This study was supported by grant U01 AA014834 awarded by the National Institute on Alcohol Abuse and Alcoholism to Sarah N. Mattson.

Footnotes

Conflict of Interest: There are no conflicts of interest

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