Motor Proficiency in School-Aged Children With ADHD: Inattentive Versus Combined Subtypes

Motor Proficiency in School-Aged Children With ADHD: Inattentive Versus Combined Subtypes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Motor Proficiency in School-Aged Children With ADHD: Inattentive Versus Combined Subtypes Ozgun Kaya Kara, Koray Kara, Hasan Atacan Tonak, Selcen Karademir, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8287956/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Children with attention deficit hyperactivity disorder (ADHD) often demonstrate poorer performance on motor assessments compared with typically developing peers. However, the motor skills of school-aged children with ADHD-Inattentive (ADHD-I) and ADHD-Combined (ADHD-C), as assessed by the Bruininks–Oseretsky Test of Motor Proficiency, Second Edition (BOT-2), remain insufficiently explored. This study aimed to compare motor skills between children with ADHD-I and ADHD-C, and their typically developing peers. Methods A total of 150 children with ADHD ( M = 8.8, SD = 1.6, 90 boys and 60 girls) and 75 typically developing peers ( M = 8.9, SD = 1.8 years, 56 boys and 44 girls), aged 6–12 years, were assessed using the BOT-2. Motor proficiency parameters were analyzed using One-Way ANOVA analysis with post hoc comparisons. Results The control group scored significantly higher across all BOT-2 domains compared with both ADHD groups. Significant differences between the ADHD subtypes were observed for manual dexterity (ω² = .17, p < .001), manual coordination (ω² = .14, p < .001), and balance (ω² = .22, p < .001), and favored the ADHD-C group. Conclusion Children with ADHD-C demonstrated better fine and gross motor skills—including manual dexterity, coordination, and balance—than those with ADHD-I. These findings underscore the importance of considering motor proficiency in children with ADHD, particularly those with the inattentive subtype, and may help guide clinical interventions and educational support. attention deficit hyperactivity disorder fine motor gross motor motor proficiency Figures Figure 1 Introduction Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in childhood, affecting around 5% of school-aged children worldwide [ 1 ]. Due to its core symptoms—including inattention and hyperactivity/impulsiveness—children with ADHD have challenges regarding academic achievement, peer relationships, and social functioning [ 2 ]. Moreover, ADHD is significantly linked to persistent functional impairments in cognitive, social, and physical areas, collectively resulting in substantial personal and social burdens [ 3 ]. Importantly, accumulating evidence suggests that 30%−60% of children with ADHD also experience fine and gross motor difficulties [ 4 ], which may have long-term implications for school performance and participation in daily living activities [ 5 ]. Recent studies have increasingly focused on the neurophysiological mechanisms underlying motor difficulties in children with ADHD [ 6 – 8 ]. Increasing evidence indicates abnormalities within frontostriatal structures, the frontal cortico-striatal network, the supplementary motor area, the superior temporal lobe, and the cerebellum, as well as microstructural anomalies in the corticospinal tract. These neural alterations may contribute to impairments in fine and gross motor performance including balance, gait, handwriting, manual dexterity, and timing of motor actions [ 6 – 8 ]. Notably, Saad et al. [ 6 ] have reported subtype-specific differences, showing a higher cerebellar network distribution in the combined (ADHD-C) subtype compared to the predominantly inattentive (ADHD-I) subtype, suggesting that distinct neural patterns may be associated with motor impairments across ADHD subtypes. These findings indicate that motor deficits are not secondary symptoms but may reflect core neurodevelopmental disruptions in ADHD. Many studies have shown that children with ADHD exhibit poor performance in motor evaluations [ 9 – 14 ]. They also tend to have poorer balance, lower motor speed, weaker postural stability, less automatic and rhythmic walking, and reduced motor coordination compared to typically developing peers [ 15 – 20 ]. Current meta-analysis further supports that children with ADHD perform poorly on standardized motor assessments indicating lower levels of manual dexterity, ball skills, bimanual coordination, motor planning, fine motor control, and strength and agility [ 21 ]. However, only a limited number of studies have examined motor performance by comparing different ADHD subtypes (ADHD-I vs. ADHD-C), and their findings remain inconsistent [ 22 – 25 ]. These inconsistencies may be explained by methodological limitations, including small sample sizes, a focus on only one motor domain (e.g., fine motor or visuomotor skills), and the use of assessment tools with limited sensitivity. Nevertheless, existing evidence suggests that individuals with ADHD-I tend to experience persistent deficits in fine-motor control and motor planning, whereas those with ADHD-C demonstrate more widespread impairments in gross-motor functioning, balance, and gait [ 25 , 26 ]. Such subtype-specific motor patterns underscore the need for differentiated assessment procedures and tailored rehabilitation interventions, highlighting the importance of further research into motor proficiency across ADHD subtypes [ 21 ]. The Bruininks–Oseretsky Test of Motor Proficiency—Second Edition (BOT-2) is the gold standard assessment tool to identify motor proficiency. Recent studies have suggested that the long version of the BOT-2 assessment can be used to measure motor skills in children with ADHD [ 27 , 28 ]. Recent studies have recommended that the motor proficiency of children with ADHD should be regularly assessed in the early period [ 29 , 30 ]. From a clinical perspective, early identification of motor difficulties may serve as a valuable complementary indicator in ADHD assessment, especially for children who do not yet display overt behavioral symptoms. Although core ADHD symptoms can be effectively managed with medication, motor interventions remain essential for improving functional motor skills, and pharmacological treatment alone may not address these deficits adequately [ 21 , 31 , 32 ]. Early detection of subtype-specific motor profiles could therefore support the development of tailored rehabilitation strategies, school-based interventions, and preventive programs aimed at promoting participation in activities of daily living. To the best of our knowledge, no study has examined the motor skills of school-aged children with the ADHD-I and ADHD-C subtypes using the long form of BOT-2. Investigating motor proficiency across ADHD subtypes is not only scientifically relevant but also clinically meaningful, as it may guide the development of more targeted assessment protocols and rehabilitation strategies. The objective of this study was to investigate the disparities in motor skills between children with ADHD-I and ADHD-C, in comparison to their typically developing peers. The first hypothesis of the study was that children with ADHD-I and ADHD-C would have poorer levels of motor proficiency compared to their typically developing peers. The second hypothesis was that children with ADHD-I would have poorer fine and gross motor functional skills than those with ADHD-C, as assessed by BOT-2. Method This cross-sectional study was conducted between September 2021 and December 2023 using a convenience sampling method among children referred to the child and adolescent psychiatry department. Ethical approval was obtained from the Clinical Research Ethics Committee of Health Sciences University Turkey, Antalya Training and Research Hospital (Project: 2021/339), and written informed consent was provided by all participants and/or their caregivers. Participants A total of 150 children diagnosed with ADHD ( M = 8.8 years, SD = 1.6, 90 boys and 60 girls) and 75 typically developing peers ( M = 8.9, SD = 1.8, 56 boys and 44 girls) aged 6–12 years were included in the study. The diagnostic criteria were identical to those used in our previous publication, except for the age range [ 33 ]. The inclusion criteria for the children with ADHD were as follows: (1) A clinical diagnosis of ADHD according to the DSM-5 criteria by a child and adolescent psychiatrist [ 34 ]. The diagnosis requires the appearance of at least six indicators of hyperactivity/impulsivity and/or inattention for over 6 six months in two or more environments (home, school, community), resulting in detrimental effects on social, academic, and occupational functioning, along with the presence of these signs prior to the age of 12 years. The exclusion criteria for the children with ADHD were as follows: (1) children with comorbid neurological or psychiatric disorders such as syndromic or chromosomal disorders, cerebral palsy, brain trauma, epilepsy, autism spectrum disorder, or psychotic symptoms, and (2) children with an IQ level below the 8th percentile (i.e., borderline range; IQ = 70–79) according to the Wechsler Intelligence Scale for Children-IV (WISC-IV). ADHD subtypes were determined by the child and adolescent psychiatrist (second author) and confirmed by the Conners’ Parent Rating Scale–Long Form. Participants were categorized into predominantly inattentive (ADHD-I) or combined (ADHD-C) subtypes. The control group consisted of typically developing children who were matched for age and gender and were referred from state schools. The exclusion criteria for the control group were as follows: (1) children with psychiatric/neurological diseases or chronic conditions, such as heart, hearing, vision, rheumatic, or orthopedic conditions, or severe behavioral issues. Measurements Demographic questionnaire The demographic characteristics of each participant were documented, and included the age, weight, height, gender, education level, and parents’ age. The Bruininks-Oseretsky Motor Proficiency Test-2 The Bruininks-Oseretsky Motor Proficiency Test-2 (BOT-2) is used to assess motor proficiency in children and adolescents aged 4–21 years [ 35 ]. This standardized test consists of four motor composite scores (fine manual control, manual coordination, body coordination, strength and agility) and eight subscales (fine motor precision, fine motor integration, manual dexterity, upper limb coordination, bilateral coordination, balance, running speed and agility, and strength). Internal consistency, validity and test-retest reliability and inter-rater reliability for this test have been found to be moderate to strong (> 0.80)[ 35 ]. The BOT-2 was used for the evaluation of gross and fine motor skills by the first and third authors, who had 16 and 14 years of experience, respectively, and were blinded to the ADHD-I and ADHD-C categorizations of the children. The intra-rater reliability of the researchers was found to be excellent (ICC = 0.95 − 0.94). The inter-rater reliability of the researchers was also found to be excellent (ICC = 0.96). In order to prevent any potential bias caused by the order of testing and to ensure consistent results from the investigator, the BOT-2 assessment was conducted on the same day for each child. Each child was instructed to stop using medications for at least one week before the examination to prevent any potential effects of the medication. The order of the assessment tasks was determined using a quasi-random method and performed by the same trained assessor. The BOT-2 took approximately 40 to 45 minutes to complete. Data analysis The SPSS version 28 for Macintosh software (IBM Corporation, Armonk, NY, USA) was used for the statistical analysis of the data collected in the study. Prior to choosing the statistical method, the Q-Q plots, histograms and Shapiro-Wilk test were employed to evaluate variable distribution, confirming that the data exhibited normality. GPower V.3.1.9 (University of Kiel, Kiel, Germany) was used to determine the sample size by using a partial eta squared (ηp² = 0.27), as given for the average frequency of school-related activities. To be able to detect a difference with 95% confidence using t tests, a minimum of 70 participants per group was required to reach 80% power. One-way ANOVA was used to compare BOT-2 sub parameters among the ADHD-I, ADHD-C, and control groups. When an overall significance was observed, the Tukey’s HSD post hoc test was used to show differences between the groups to control the family-wise error rate within each outcome (three pairwise group comparisons) [ 36 ]. A value of p < .05 was considered statistically significant. Eta squared (η²) is widely used, but it might overestimate effect size because of positive bias [ 37 ]. Omega squared (ω²) is regarded as a nearly unbiased alternative estimator. Therefore, effect sizes were calculated as omega-squared (ω²)[ 38 , 39 ]. A small effect is classified as small ( .01), medium ( .06), and large (≥ .14) [ 40 ]. Results The demographic aspects of the participants were not significantly different between the groups (see Table 1 ). Across all groups, more than half of the participants were male and attended primary school. Table 1 Demographic characteristics of the children with ADHD and their typically developing peers Variable ADHD-I ADHD-C Control N ( % )/ M ( SD ) N ( % )/ M ( SD ) N ( % )/ M ( SD ) Age (Years) 9.10 (1.74) 8.53 (1.56) 8.91 (1.83) Height (cm) 136.86 (12.28) 136.97 (12.38) 134.11 (12.34) Weight (kg) 32.63 (9.76) 33.61 (10.09) 32.79 (9.22) BMI (kg/m 2 ) 17.71 (5.87) 18.31 (6.39) 18.55 (5.83) Gender Boy 48 (64) 42 (56) 44 (58.7) Girl 27 (36) 33 (44) 31 (41.3) School Elementary 55 (73.3) 66 (88) 59 (58.7) Secondary 20 (26.7) 9 (12) 16 (21.3) Note. N = 225 ( n = 75 for each group). ADHD-I = attention deficit hyperactivity disorder-predominantly inattentive subtype; ADHD-C = attention deficit hyperactivity disorder-combined subtype; BMI = Body Mass Index; ANOVA = analysis of variance; Tukey’s HSD post hoc test was used to determine group differences. * p < .05. Table 2 presents the BOT-2 outcomes for the ADHD-I, ADHD-C, and control groups. The control group obtained significantly higher scores across all the BOT-2 parameters compared with both ADHD subtypes ( p < .004). Large effect sizes were observed for manual dexterity, F (2, 224) = 24.55, p < .001, ω 2 = .17, manual coordination, F (2, 224) = 18.84, p < .001, ω 2 = .14,, balance, F (2, 224) = 33.79, p < .001, ω 2 = .22, body coordination, F (2, 224) = 21.27, p < .001, ω 2 = .15, running speed and agility, F (2, 224) = 28.20, p < .001, ω 2 = .19, strength, F (2, 224) = 19.48, p < .001, ω 2 = .14, strength and agility, F (2, 224) = 28.96, p < .001, ω 2 = .19, and total motor composite score, F (2, 224) = 20.98, p < .001, ω 2 = .15. Table 2 Comparisons of the BOT-2 subscale scores between children with ADHD-I and ADHD-C, and typically developing peers Variable ADHD-I ADHD-C Control ANOVA M ( SD ) M ( SD ) M ( SD ) Post-Hoc F (2, 224) ω² Fine Manual Control 21.29 (7.20) 22.89 (7.00) 25.92 (7.57) 1 = 2 < 3 7.85 ** .06 Fine Motor Precision 10.00 (4.20) 11.16 (4.11) 12.92 (4.77) 1 = 2 < 3 8.49 ** .06 Fine Motor Integration 11.21 (3.91) 11.75 (3.92) 13.48 (4.85) 1 = 2 < 3 5.83 * .04 Manual Coordination 18.47 (6.93) 21.55 (7.95) 25.47 (5.98) 1 < 2 < 3 18.84 ** .14 Manual Dexterity 9.08 (3.69) 11.01 (2.87) 12.35 (1.70) 1 < 2 < 3 24.55 ** .17 Upper Limb Coordination 9.83 (4.34) 10.80 (4.34) 13.13 (4.98) 1 = 2 < 3 10.41 ** .07 Body Coordination 19.16 (7.39) 19.29 (7.80) 26.03 (6.90) 1 = 2 < 3 21.27 ** .15 Bilateral Coordination 8.93 (4.87) 8.52 (4.14) 12.59 (4.74) 1 = 2 < 3 17.79 ** .13 Balance 8.52 (2.67) 10.17 (4.46) 13.35 (3.60) 1 < 2 < 3 33.79 ** .22 Strength and Agility 19.91 (7.27) 20.11 (6.95) 27.68 (7.17) 1 = 2 < 3 28.96 ** .19 Running Speed and Agility 10.12 (4.12) 9.44 (3.74) 14.01 (4.20) 1 = 2 < 3 28.20 ** .19 Strength 9.81 (4.05) 10.96 (4.28) 13.80 (3.73) 1 = 2 < 3 19.48 ** .14 Total Motor Composite Score 35.24 (7.49) 37.41 (7.62) 43.20 (8.20) 1 = 2 < 3 20.98 ** .15 Note. N = 225 ( n = 75 for each group). ADHD-I = attention deficit hyperactivity disorder-predominantly inattentive subtype; ADHD-C = attention deficit hyperactivity disorder-combined subtype; ANOVA = analysis of variance; Tukey’s HSD post hoc test was used to determine group differences. Effect size interpretation based on Cohen’s guidelines (1988), small = 01–.05, medium = .06–.14, large = ≥ .14. * p < .05. ** p < .001 Medium effect sizes were found for fine motor precision, F (2, 224) = 8.49, p < .001, ω 2 = .06, fine motor control, F (2, 224) = 7.85, p < .001, ω 2 = .06, upper limb coordination, F (2, 224) = 10.41, p < .001, ηp 2 = .07, and bilateral coordination, F (2, 224) = 17.79, p < .001, ω 2 = .13 whereas small effect sizes were identified for fine motor integration, F (2, 224) = 5.83, p = .003, ω 2 = .04. Tukey’s HSD post-hoc comparisons revealed that the ADHD-C group performed significantly better than the ADHD-I group in manual dexterity, MD = − 1.93, SE = 0.46, 95% CI [–3.03, − 0.82], p < .001, manual coordination, MD = − 3.08, SE = 1.14, 95% CI [–5.77, − 0.38], p = .02, and balance, MD = − 5.771.65, SE = 0.59, 95% CI [–0.24, − 3.06], p = .01 (see Fig. 1). Discussion The primary objective of this study was to investigate the fine and gross motor abilities of children with ADHD-I and ADHD-C through comparisons with typically developing peers. The first hypothesis of the study that children with ADHD-I and ADHD-C have lower scores for all the sub-parameters of the BOT-2 compared to the typically developing peers was supported. The second hypothesis that children with ADHD-I have a lower level of performance in terms of manual dexterity, manual coordination, and balance than children with ADHD-C was almost supported. Differences in fine motor abilities between children with ADHD and typically developing peers Fine motor abilities are not only crucial for daily life activities but also for academic achievement [ 26 ]. Furthermore, school-aged children spend the majority of their day in the classroom, where the major parts of the activities necessitate fine motor abilities [ 41 ]. Many studies have demonstrated that children with ADHD experience challenges in fine motor skills including poor handwriting, less accurate line drawing resulting in more mistakes, lower performance of pegboard tasks, poor visual motor tasks, lower scores in manual dexterity, lower speed, poor movement quality, more jerky movements, poor movement rhythm, and longer reaction time compared to typically developing peers [ 9 , 11 , 12 , 22 – 24 , 42 – 45 ]. In a recent meta-analysis, Blanco-Martínez, González-Devesa [ 21 ] reported that only six studies had used the BOT to assess motor competence in children with ADHD compared with typically developing peers. Significantly, half of these studies used the short form of the BOT, which may overestimate performance and increase the risk of false-negative outcomes. Overall, previous findings have shown lower performance regarding fine manual control, manual coordination, fine motor precision, fine motor integration, manual dexterity, upper limb coordination, and bilateral coordination in children with ADHD [ 46 – 48 ]. However, some studies have failed to identify significant differences, leading to inconsistent conclusions in the literature [ 49 , 50 ]. These discrepancies underscore the need for high-quality research using comprehensive and standardized motor assessments to better understand the fine and gross motor skills of children with ADHD compared with their typically developing peers. In line with previous research, the current study results demonstrated that the children with ADHD-I and ADHD-C had poorer performance in terms of fine motor precision, fine motor integration, fine manual control, manual dexterity, upper limb coordination, and bilateral coordination. It has been suggested that alterations in posterior interhemispheric connections, particularly in the corpus callosum, might be responsible for impairments in fine motor abilities [ 51 ]. The corpus callosum is responsible for the regulation of motor function and predominantly connects the supplementary, premotor, and primary motor cortices in both hemispheres [ 52 ]. The splenium and corpus callosum body are altered in order to facilitate cognitive and motor skills that are impaired in ADHD [ 51 ]. Visuospatial information transfer, working speed, intelligence level, and behavior have all been linked to the splenium of the corpus callosum, which connects the temporal, occipital, and posterior parietal lobes of both hemispheres [ 52 , 53 ]. The fronto-parietal cognitive control connections and posterior cortical regions facilitate attention, thereby enhancing cognitive abilities including working memory, executive function, and attention, which are often impaired in ADHD [ 54 ]. Differences in gross motor abilities between children with ADHD and typically developing peers The current study findings showed that children with ADHD-I and ADHD-C had poorer gross motor abilities including balance, body coordination, strength, agility and total motor proficiency score than typically developing peers. Consistent with these findings, previous studies have also shown poor balance; lower locomotor and global motor ability, body schema, and spatial organization scores; and difficulties in postural stability, motor coordination, and walking [ 10 , 14 – 16 , 19 , 20 , 55 ]. Schoemaker et al. [ 56 ] indicated that motor abilities were weaker in children with ADHD, but this was not combined with developmental coordination disorder (DCD). Moreover, it has been reported that almost half of children with ADHD met diagnostic criteria for DCD [ 26 ]. Future studies should investigate the subtypes of ADHD based on the DCD criteria. A possible explanation for this is that alterations in the cerebellum and prefrontal cortex may contribute to the motor difficulties that are experienced by children with ADHD, when it is considered that the cerebellum is one of the primary structures responsible for the performance of motor movements and that the prefrontal cortex is responsible for motor planning [ 57 ]. Previous meta-analysis results have shown that the gray matter volume of the right caudate, prefrontal cortex, cerebellum, and cerebral volume was decreased in children with ADHD compared to typically developing peers [ 58 ]. Moreover, the difficulties in dynamic balance control in children with ADHD and alterations in the cerebellum affecting the fronto-striato-cerebellar connection may affect the balance in children with ADHD [ 58 ]. Dynamic balance control is associated with the neuromuscular system and sensorial system including vestibular, visual, and somatosensory systems [ 59 ]. During movement, the brain needs to organize different sensorial feedbacks at the same time as individual organization, to coordinate different extremity segment directions, and adjust timing and strength to maintain balance [ 60 ]. Some researchers have shown that children with ADHD cannot modulate the sensorial inputs and this causes challenges in finding the right strategy to protect balance [ 61 ]. In addition, Shabat et al [ 62 ] showed that the participation patterns of children with ADHD are restricted, which might limit opportunities to practice motor skills. Future studies should investigate the relationship between participation patterns and motor skills. Differences in fine motor abilities and balance between children with ADHD-I and ADHD-C The current research's findings demonstrated that children with ADHD-I experienced greater challenges in fine motor skills than those with ADHD-C. Children with ADHD-I showed a 17.5% decrease in manual dexterity and a 14.2% decrease in manual coordination compared to children with ADHD-C. Similar to these findings, Fenollar-Cortés, Gallego-Martínez [ 63 ] reported that worse fine motor performance was associated with the dimension of inattention, rather than hyperactivity or impulsive dimensions. One possible explanation is that children with ADHD often exhibit a lack of inhibition [ 64 ]. The absence of inhibition encompasses planning a reaction, inhibiting a response, stopping the continuing response, and regulating interference. Working memory, motivation, self-regulation of emotions, processing of speech, and reconstruction are all aspects of executive functioning that are impacted by these capacities. Problems in these executive functions might affect motor control [ 64 ]. Opposite to the findings of the present study, Egeland [ 24 ] and Meyer et al. [ 23 ] demonstrated that children with ADHD-C had poorer fine motor performance on a grooved pegboard test and visual motor integration. In addition, Pitcher et al. [ 22 ] showed no differences between ADHD-I and ADHD-C in respect of manual dexterity and ball skills. These differences could be attributed to the fact that the manual dexterity and manual coordination sub-parameters of BOT-2 were assessed more objectively in the current study than with previous assessment methods [ 27 ]. The BOT-2 included speed-related activities such as making dots in circles, transferring pennies, placing a peg into a pegboard, sorting cards, and stringing blocks to evaluate manual dexterity and manual coordination. The findings of this study highlighted that children with ADHD-I had a 16.2% decrease in balance compared to children with ADHD-C. In addition, children with ADHD-C had a 23.8% decrease in balance, and children with ADHD-I had a 36.1% decrease compared to typically developing peers. Similarly, Mao et al. [ 20 ] showed that children with ADHD demonstrated a 36.07% decrease in balance compared to typically developing peers according to BOTMP. Goulardins et al. [ 14 ] also showed a 9.3% decrease in balance in children with ADHD-C. The potential explanation for differences in manual dexterity, manual coordination, and balance between children with ADHD-I and ADHD-C stems from the distinct structural network features associated with the ADHD-C and ADHD-I subtypes. Saad et al. [ 65 ] demonstrated that the visual, limbic and ventral attention pathways are linked to ADHD-I, while the frontoparietal, motor, and default mode pathways are associated with ADHD-C. A recent meta-analysis indicated that functional impairments in fronto-striatal-thalamic circuitry and the default mode networks correlate with deficits in response inhibition, disorientation, impulsivity, directed activity, and concentration in the ADHD-C subtype. In addition, dysfunction in the frontoparietal region reflects deficits characteristic of the ADHD-I subtype, including received attention and motivational factors [ 6 ]. In the light of these findings, the current study results support the evidence that attention level could impact fine and gross motor performance. Strengths and Limitations The major strengths of this study were that comparisons were made of fine and gross motor abilities of children with ADHD-I and ADHD-C using the gold standard measurement, with a large sample size that also included girls. However, a limitation of the study was that comorbid disorders such as developmental coordination disorder and special learning disorders were not evaluated. Future studies should investigate the relationship between motor abilities and comorbid disorders according to ADHD-I and ADHD-C. In addition, future studies should also investigate the other factors that can impact the motor skills including receiving services (including occupational therapy/Physiotherapy), opportunities to practice motor skills, and physical activity participation. Conclusion Finally, both the ADHD-I and ADHD-C groups demonstrated lower levels of motor proficiency compared with their typically developing peers, consistent with prior research. Importantly, children with ADHD-C showed better performance in several fine and gross motor domains—particularly manual dexterity, manual coordination, and balance—than those with ADHD-I, suggesting a subtype-specific motor profile. Recent meta-analysis further indicates that children with ADHD exhibit substantially reduced motor competence, with manual dexterity being the most impaired subdimension [ 21 ], a skill closely linked to academic achievement and everyday functional tasks [ 66 ]. These findings highlighted the need for systematic assessment of motor abilities across ADHD subtypes. In clinical practice, subtype-sensitive intervention planning may be beneficial; for instance, dual-task–based training has been shown to enhance manual dexterity by concurrently engaging attentional and motor control processes [ 67 ]. Future studies should investigate how motor skill deficits relate to participation patterns and daily activity engagement in children with ADHD. Declarations Ethical approval Ethical approval was obtained from the Health Sciences University Turkey, Antalya Training and Research Hospital of Clinical Research Ethics Committee (Project: 2021/339). Written informed consent was obtained from all participants and/or their caregivers based on the principles stated in the Declaration of Helsinki. Informed consent All respondents and signed informed consent forms or participation. Consent for children was given by their parents. Child assent forms were also obtained. Competing interests The authors declare no competing interests. Funding The authors received no financial support for the research and/or authorship of this article. Author Contribution OKK: Writing- Original draft preparation, Investigation, Conceptualization, Methodology KK: Supervision, Investigation, Conceptualization, Methodology, HAT: Visualization, Investigation SK: Investigation MT: Data curation, Software, DD: Supervision, writing—review and editing phase Data Availability No datasets were generated or analysed during the current study. References Polanczyk GV, Willcutt EG, Salum GA et al (2014) ADHD prevalence estimates across three decades: an updated systematic review and meta-regression analysis. Int J Epidemiol 43(2):434–442 Association AP (2013) Diagnostic and statistical manual of mental disorders, 5th edition, DSM-5. 5th edition ed. 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J Atten Disord 21(9):783–795 Tseng MH, Henderson A, Chow SM et al (2004) Relationship between motor proficiency, attention, impulse, and activity in children with ADHD. Dev Med Child Neurol 46(6):381–388 Cak Esen H, Karaokur R, ATASAVUN UYSAL S et al (2018) Motor proficiency in children with attention deficit hyperactivity disorder: Associations with cognitive skills and symptom severity. Turk Psikiyatri Dergisi. ;29(2) Demircioğlu A, Uysal SA, Dumankaya BBŞ et al (2023) Do children with attention deficit and hyperactivity disorder present with different spatio-temporal gait parameters? An evaluation of the relationship between gait and gross motor skills. Alpha psychiatry 24(1):1 Parlatini V, Itahashi T, Lee Y et al (2023) White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis. Mol Psychiatry 28(10):4098–4123 Hofer S, Frahm J (2006) Topography of the human corpus callosum revisited—comprehensive fiber tractography using diffusion tensor magnetic resonance imaging. NeuroImage 32(3):989–994 Blaauw J, Meiners L (2020) The splenium of the corpus callosum: embryology, anatomy, function and imaging with pathophysiological hypothesis. Neuroradiology 62:563–585 Ramos AA, Hamdan AC, Machado L (2020) A meta-analysis on verbal working memory in children and adolescents with ADHD. Clin Neuropsychol 34(5):873–898 Leitner Y, Barak R, Giladi N et al (2007) Gait in attention deficit hyperactivity disorder: effects of methylphenidate and dual tasking. J Neurol 254:1330–1338 Schoemaker M, Ketelaars C, van Minderaa ZM, Mulder RB (2005) Deficits in motor control processes involved in production of graphic movements of children with attention-deficit-hyperactivity disorder. Dev Med Child Neurol 47:390–395 Crossman AR, Neary D (2018) Neuroanatomy E-book: an illustrated colour text. Elsevier Health Sciences Valera EM, Faraone SV, Murray KE et al (2007) Meta-analysis of structural imaging findings in attention-deficit/hyperactivity disorder. Biol Psychiatry 61(12):1361–1369 Hatzitaki V, Zlsi V, Kollias I et al (2002) Perceptual-motor contributions to static and dynamic balance control in children. J Mot Behav 34(2):161–170 Shumway-Cook A (2007) Motor control: translating research into clinical practice. Lippincoot Williams & Wilkins Lin C-Y, Yang A-L, Su C-T (2013) Objective measurement of weekly physical activity and sensory modulation problems in children with attention deficit hyperactivity disorder. Res Dev Disabil 34(10):3477–3486 Shabat T, Fogel-Grinvald H, Anaby D et al (2021) Participation Profile of Children and Youth, Aged 6–14, with and without ADHD, and the Impact of Environmental Factors. Int J Environ Res Public Health. ;18(2) Fenollar-Cortés J, Gallego-Martínez A, Fuentes LJ (2017) The role of inattention and hyperactivity/impulsivity in the fine motor coordination in children with ADHD. Res Dev Disabil 69:77–84 De Zeeuw P, Aarnoudse-Moens C, Bijlhout J et al (2008) Inhibitory performance, response speed, intraindividual variability, and response accuracy in ADHD. J Am Acad Child Adolesc Psychiatry 47(7):808–816 Saad JF, Griffiths KR, Kohn MR et al (2017) Regional brain network organization distinguishes the combined and inattentive subtypes of attention deficit hyperactivity disorder. NeuroImage: Clin 15:383–390 Giustino V, Patti A, Petrigna L et al (2023) Manual dexterity in school-age children measured by the Grooved Pegboard test: Evaluation of training effect and performance in dual-task. Heliyon. ;9(7) Raisbeck LD, Diekfuss JA (2015) Fine and gross motor skills: The effects on skill-focused dual-tasks. Hum Mov Sci 43:146–154 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":441814,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8287956/v1/27759097fef8482556f04a56.jpeg"},{"id":99797761,"identity":"ba62c22e-9705-43c8-8829-9d90d0c477be","added_by":"auto","created_at":"2026-01-08 13:46:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1231422,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8287956/v1/30341ac6-0380-4d0e-9f56-b1e056fab705.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Motor Proficiency in School-Aged Children With ADHD: Inattentive Versus Combined Subtypes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAttention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in childhood, affecting around 5% of school-aged children worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Due to its core symptoms\u0026mdash;including inattention and hyperactivity/impulsiveness\u0026mdash;children with ADHD have challenges regarding academic achievement, peer relationships, and social functioning [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Moreover, ADHD is significantly linked to persistent functional impairments in cognitive, social, and physical areas, collectively resulting in substantial personal and social burdens [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Importantly, accumulating evidence suggests that 30%\u0026minus;60% of children with ADHD also experience fine and gross motor difficulties [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], which may have long-term implications for school performance and participation in daily living activities [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent studies have increasingly focused on the neurophysiological mechanisms underlying motor difficulties in children with ADHD [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Increasing evidence indicates abnormalities within frontostriatal structures, the frontal cortico-striatal network, the supplementary motor area, the superior temporal lobe, and the cerebellum, as well as microstructural anomalies in the corticospinal tract. These neural alterations may contribute to impairments in fine and gross motor performance including balance, gait, handwriting, manual dexterity, and timing of motor actions [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Notably, Saad et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] have reported subtype-specific differences, showing a higher cerebellar network distribution in the combined (ADHD-C) subtype compared to the predominantly inattentive (ADHD-I) subtype, suggesting that distinct neural patterns may be associated with motor impairments across ADHD subtypes. These findings indicate that motor deficits are not secondary symptoms but may reflect core neurodevelopmental disruptions in ADHD.\u003c/p\u003e \u003cp\u003eMany studies have shown that children with ADHD exhibit poor performance in motor evaluations [\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. They also tend to have poorer balance, lower motor speed, weaker postural stability, less automatic and rhythmic walking, and reduced motor coordination compared to typically developing peers [\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Current meta-analysis further supports that children with ADHD perform poorly on standardized motor assessments indicating lower levels of manual dexterity, ball skills, bimanual coordination, motor planning, fine motor control, and strength and agility [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, only a limited number of studies have examined motor performance by comparing different ADHD subtypes (ADHD-I vs. ADHD-C), and their findings remain inconsistent [\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These inconsistencies may be explained by methodological limitations, including small sample sizes, a focus on only one motor domain (e.g., fine motor or visuomotor skills), and the use of assessment tools with limited sensitivity. Nevertheless, existing evidence suggests that individuals with ADHD-I tend to experience persistent deficits in fine-motor control and motor planning, whereas those with ADHD-C demonstrate more widespread impairments in gross-motor functioning, balance, and gait [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Such subtype-specific motor patterns underscore the need for differentiated assessment procedures and tailored rehabilitation interventions, highlighting the importance of further research into motor proficiency across ADHD subtypes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Bruininks\u0026ndash;Oseretsky Test of Motor Proficiency\u0026mdash;Second Edition (BOT-2) is the gold standard assessment tool to identify motor proficiency. Recent studies have suggested that the long version of the BOT-2 assessment can be used to measure motor skills in children with ADHD [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Recent studies have recommended that the motor proficiency of children with ADHD should be regularly assessed in the early period [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. From a clinical perspective, early identification of motor difficulties may serve as a valuable complementary indicator in ADHD assessment, especially for children who do not yet display overt behavioral symptoms. Although core ADHD symptoms can be effectively managed with medication, motor interventions remain essential for improving functional motor skills, and pharmacological treatment alone may not address these deficits adequately [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Early detection of subtype-specific motor profiles could therefore support the development of tailored rehabilitation strategies, school-based interventions, and preventive programs aimed at promoting participation in activities of daily living.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, no study has examined the motor skills of school-aged children with the ADHD-I and ADHD-C subtypes using the long form of BOT-2. Investigating motor proficiency across ADHD subtypes is not only scientifically relevant but also clinically meaningful, as it may guide the development of more targeted assessment protocols and rehabilitation strategies. The objective of this study was to investigate the disparities in motor skills between children with ADHD-I and ADHD-C, in comparison to their typically developing peers. The first hypothesis of the study was that children with ADHD-I and ADHD-C would have poorer levels of motor proficiency compared to their typically developing peers. The second hypothesis was that children with ADHD-I would have poorer fine and gross motor functional skills than those with ADHD-C, as assessed by BOT-2.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003eThis cross-sectional study was conducted between September 2021 and December 2023 using a convenience sampling method among children referred to the child and adolescent psychiatry department. Ethical approval was obtained from the Clinical Research Ethics Committee of Health Sciences University Turkey, Antalya Training and Research Hospital (Project: 2021/339), and written informed consent was provided by all participants and/or their caregivers.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA total of 150 children diagnosed with ADHD (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.8 years, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.6, 90 boys and 60 girls) and 75 typically developing peers (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.9, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.8, 56 boys and 44 girls) aged 6\u0026ndash;12 years were included in the study. The diagnostic criteria were identical to those used in our previous publication, except for the age range [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The inclusion criteria for the children with ADHD were as follows: (1) A clinical diagnosis of ADHD according to the DSM-5 criteria by a child and adolescent psychiatrist [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The diagnosis requires the appearance of at least six indicators of hyperactivity/impulsivity and/or inattention for over 6 six months in two or more environments (home, school, community), resulting in detrimental effects on social, academic, and occupational functioning, along with the presence of these signs prior to the age of 12 years. The exclusion criteria for the children with ADHD were as follows: (1) children with comorbid neurological or psychiatric disorders such as syndromic or chromosomal disorders, cerebral palsy, brain trauma, epilepsy, autism spectrum disorder, or psychotic symptoms, and (2) children with an IQ level below the 8th percentile (i.e., borderline range; IQ\u0026thinsp;=\u0026thinsp;70\u0026ndash;79) according to the Wechsler Intelligence Scale for Children-IV (WISC-IV). ADHD subtypes were determined by the child and adolescent psychiatrist (second author) and confirmed by the Conners\u0026rsquo; Parent Rating Scale\u0026ndash;Long Form. Participants were categorized into predominantly inattentive (ADHD-I) or combined (ADHD-C) subtypes. The control group consisted of typically developing children who were matched for age and gender and were referred from state schools. The exclusion criteria for the control group were as follows: (1) children with psychiatric/neurological diseases or chronic conditions, such as heart, hearing, vision, rheumatic, or orthopedic conditions, or severe behavioral issues.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasurements\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDemographic questionnaire\u003c/h2\u003e \u003cp\u003eThe demographic characteristics of each participant were documented, and included the age, weight, height, gender, education level, and parents\u0026rsquo; age.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe Bruininks-Oseretsky Motor Proficiency Test-2\u003c/h3\u003e\n\u003cp\u003eThe Bruininks-Oseretsky Motor Proficiency Test-2 (BOT-2) is used to assess motor proficiency in children and adolescents aged 4\u0026ndash;21 years [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This standardized test consists of four motor composite scores (fine manual control, manual coordination, body coordination, strength and agility) and eight subscales (fine motor precision, fine motor integration, manual dexterity, upper limb coordination, bilateral coordination, balance, running speed and agility, and strength). Internal consistency, validity and test-retest reliability and inter-rater reliability for this test have been found to be moderate to strong (\u0026gt;\u0026thinsp;0.80)[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The BOT-2 was used for the evaluation of gross and fine motor skills by the first and third authors, who had 16 and 14 years of experience, respectively, and were blinded to the ADHD-I and ADHD-C categorizations of the children. The intra-rater reliability of the researchers was found to be excellent (ICC\u0026thinsp;=\u0026thinsp;0.95\u0026thinsp;\u0026minus;\u0026thinsp;0.94). The inter-rater reliability of the researchers was also found to be excellent (ICC\u0026thinsp;=\u0026thinsp;0.96). In order to prevent any potential bias caused by the order of testing and to ensure consistent results from the investigator, the BOT-2 assessment was conducted on the same day for each child. Each child was instructed to stop using medications for at least one week before the examination to prevent any potential effects of the medication. The order of the assessment tasks was determined using a quasi-random method and performed by the same trained assessor. The BOT-2 took approximately 40 to 45 minutes to complete.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eThe SPSS version 28 for Macintosh software (IBM Corporation, Armonk, NY, USA) was used for the statistical analysis of the data collected in the study. Prior to choosing the statistical method, the Q-Q plots, histograms and Shapiro-Wilk test were employed to evaluate variable distribution, confirming that the data exhibited normality. GPower V.3.1.9 (University of Kiel, Kiel, Germany) was used to determine the sample size by using a partial eta squared (ηp\u0026sup2; = 0.27), as given for the average frequency of school-related activities. To be able to detect a difference with 95% confidence using t tests, a minimum of 70 participants per group was required to reach 80% power. One-way ANOVA was used to compare BOT-2 sub parameters among the ADHD-I, ADHD-C, and control groups. When an overall significance was observed, the Tukey\u0026rsquo;s HSD post hoc test was used to show differences between the groups to control the family-wise error rate within each outcome (three pairwise group comparisons) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. A value of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05 was considered statistically significant. Eta squared (η\u0026sup2;) is widely used, but it might overestimate effect size because of positive bias [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Omega squared (ω\u0026sup2;) is regarded as a nearly unbiased alternative estimator. Therefore, effect sizes were calculated as omega-squared (ω\u0026sup2;)[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. A small effect is classified as small ( .01), medium ( .06), and large (\u0026ge;\u0026thinsp;.14) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe demographic aspects of the participants were not significantly different between the groups (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Across all groups, more than half of the participants were male and attended primary school.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDemographic characteristics of the children with ADHD and their typically developing peers\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eADHD-I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eADHD-C\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e (\u003cem\u003e%\u003c/em\u003e)/ \u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e (\u003cem\u003e%\u003c/em\u003e)/ \u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e (\u003cem\u003e%\u003c/em\u003e)/ \u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (Years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.10 (1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.53 (1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.91 (1.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136.86 (12.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136.97 (12.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e134.11 (12.34)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.63 (9.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.61 (10.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.79 (9.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.71 (5.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.31 (6.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.55 (5.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44 (58.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31 (41.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSchool\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElementary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59 (58.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (21.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eNote. N\u003c/em\u003e\u0026thinsp;=\u0026thinsp;225 (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;75 for each group). ADHD-I\u0026thinsp;=\u0026thinsp;attention deficit hyperactivity disorder-predominantly inattentive subtype; ADHD-C\u0026thinsp;=\u0026thinsp;attention deficit hyperactivity disorder-combined subtype; BMI\u0026thinsp;=\u0026thinsp;Body Mass Index; ANOVA\u0026thinsp;=\u0026thinsp;analysis of variance; Tukey\u0026rsquo;s HSD post hoc test was used to determine group differences.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the BOT-2 outcomes for the ADHD-I, ADHD-C, and control groups. The control group obtained significantly higher scores across all the BOT-2 parameters compared with both ADHD subtypes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.004). Large effect sizes were observed for manual dexterity, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;24.55, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.17, manual coordination, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;18.84, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.14,, balance, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;33.79, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.22, body coordination, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;21.27, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.15, running speed and agility, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;28.20, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.19, strength, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;19.48, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.14, strength and agility, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;28.96, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.19, and total motor composite score, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;20.98, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.15.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eComparisons of the BOT-2 subscale scores between children with ADHD-I and ADHD-C, and typically developing peers\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eADHD-I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eADHD-C\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePost-Hoc\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e(2, 224)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eω\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Manual Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.29 (7.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.89 (7.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.92 (7.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.85\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Motor Precision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.00 (4.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.16 (4.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.92 (4.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.49\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Motor Integration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.21 (3.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.75 (3.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.48 (4.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.83\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManual Coordination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.47 (6.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.55 (7.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.47 (5.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u0026thinsp;\u0026lt;\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.84\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManual Dexterity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.08 (3.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.01 (2.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.35 (1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u0026thinsp;\u0026lt;\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.55\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper Limb Coordination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.83 (4.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.80 (4.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.13 (4.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.41\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody Coordination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.16 (7.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.29 (7.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.03 (6.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21.27\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBilateral Coordination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.93 (4.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.52 (4.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.59 (4.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.79\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBalance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.52 (2.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.17 (4.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.35 (3.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u0026thinsp;\u0026lt;\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33.79\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrength and Agility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.91 (7.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.11 (6.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.68 (7.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28.96\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRunning Speed and Agility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.12 (4.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.44 (3.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.01 (4.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28.20\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.81 (4.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.96 (4.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.80 (3.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19.48\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Motor Composite Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.24 (7.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.41 (7.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.20 (8.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.98\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote. N\u003c/em\u003e\u0026thinsp;=\u0026thinsp;225 (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;75 for each group). ADHD-I\u0026thinsp;=\u0026thinsp;attention deficit hyperactivity disorder-predominantly inattentive subtype; ADHD-C\u0026thinsp;=\u0026thinsp;attention deficit hyperactivity disorder-combined subtype; ANOVA\u0026thinsp;=\u0026thinsp;analysis of variance; Tukey\u0026rsquo;s HSD post hoc test was used to determine group differences.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eEffect size interpretation based on Cohen\u0026rsquo;s guidelines (1988), small\u0026thinsp;=\u0026thinsp;01\u0026ndash;.05, medium\u0026thinsp;=\u0026thinsp;.06\u0026ndash;.14, large\u0026thinsp;=\u0026thinsp;\u0026ge;\u0026thinsp;.14. * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05. ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMedium effect sizes were found for fine motor precision, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;8.49, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.06, fine motor control, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;7.85, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.06, upper limb coordination, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;10.41, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ηp\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.07, and bilateral coordination, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;17.79, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.13 whereas small effect sizes were identified for fine motor integration, \u003cem\u003eF\u003c/em\u003e(2, 224)\u0026thinsp;=\u0026thinsp;5.83, p\u0026thinsp;=\u0026thinsp;.003, ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.04.\u003c/p\u003e \u003cp\u003eTukey\u0026rsquo;s HSD post-hoc comparisons revealed that the ADHD-C group performed significantly better than the ADHD-I group in manual dexterity, \u003cem\u003eMD\u003c/em\u003e = \u0026minus;\u0026thinsp;1.93, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.46, 95% CI [\u0026ndash;3.03, \u0026minus;\u0026thinsp;0.82], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, manual coordination, \u003cem\u003eMD\u003c/em\u003e = \u0026minus;\u0026thinsp;3.08, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.14, 95% CI [\u0026ndash;5.77, \u0026minus;\u0026thinsp;0.38], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.02, and balance, \u003cem\u003eMD\u003c/em\u003e = \u0026minus;\u0026thinsp;5.771.65, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.59, 95% CI [\u0026ndash;0.24, \u0026minus;\u0026thinsp;3.06], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.01 (see Fig.\u0026nbsp;1).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe primary objective of this study was to investigate the fine and gross motor abilities of children with ADHD-I and ADHD-C through comparisons with typically developing peers. The first hypothesis of the study that children with ADHD-I and ADHD-C have lower scores for all the sub-parameters of the BOT-2 compared to the typically developing peers was supported. The second hypothesis that children with ADHD-I have a lower level of performance in terms of manual dexterity, manual coordination, and balance than children with ADHD-C was almost supported.\u003c/p\u003e\n\u003ch3\u003eDifferences in fine motor abilities between children with ADHD and typically developing peers\u003c/h3\u003e\n\u003cp\u003eFine motor abilities are not only crucial for daily life activities but also for academic achievement [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Furthermore, school-aged children spend the majority of their day in the classroom, where the major parts of the activities necessitate fine motor abilities [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Many studies have demonstrated that children with ADHD experience challenges in fine motor skills including poor handwriting, less accurate line drawing resulting in more mistakes, lower performance of pegboard tasks, poor visual motor tasks, lower scores in manual dexterity, lower speed, poor movement quality, more jerky movements, poor movement rhythm, and longer reaction time compared to typically developing peers [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR43 CR44\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In a recent meta-analysis, Blanco-Mart\u0026iacute;nez, Gonz\u0026aacute;lez-Devesa [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] reported that only six studies had used the BOT to assess motor competence in children with ADHD compared with typically developing peers. Significantly, half of these studies used the short form of the BOT, which may overestimate performance and increase the risk of false-negative outcomes. Overall, previous findings have shown lower performance regarding fine manual control, manual coordination, fine motor precision, fine motor integration, manual dexterity, upper limb coordination, and bilateral coordination in children with ADHD [\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. However, some studies have failed to identify significant differences, leading to inconsistent conclusions in the literature [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These discrepancies underscore the need for high-quality research using comprehensive and standardized motor assessments to better understand the fine and gross motor skills of children with ADHD compared with their typically developing peers. In line with previous research, the current study results demonstrated that the children with ADHD-I and ADHD-C had poorer performance in terms of fine motor precision, fine motor integration, fine manual control, manual dexterity, upper limb coordination, and bilateral coordination. It has been suggested that alterations in posterior interhemispheric connections, particularly in the corpus callosum, might be responsible for impairments in fine motor abilities [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The corpus callosum is responsible for the regulation of motor function and predominantly connects the supplementary, premotor, and primary motor cortices in both hemispheres [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. The splenium and corpus callosum body are altered in order to facilitate cognitive and motor skills that are impaired in ADHD [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Visuospatial information transfer, working speed, intelligence level, and behavior have all been linked to the splenium of the corpus callosum, which connects the temporal, occipital, and posterior parietal lobes of both hemispheres [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The fronto-parietal cognitive control connections and posterior cortical regions facilitate attention, thereby enhancing cognitive abilities including working memory, executive function, and attention, which are often impaired in ADHD [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDifferences in gross motor abilities between children with ADHD and typically developing peers\u003c/h2\u003e \u003cp\u003eThe current study findings showed that children with ADHD-I and ADHD-C had poorer gross motor abilities including balance, body coordination, strength, agility and total motor proficiency score than typically developing peers. Consistent with these findings, previous studies have also shown poor balance; lower locomotor and global motor ability, body schema, and spatial organization scores; and difficulties in postural stability, motor coordination, and walking [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Schoemaker et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] indicated that motor abilities were weaker in children with ADHD, but this was not combined with developmental coordination disorder (DCD). Moreover, it has been reported that almost half of children with ADHD met diagnostic criteria for DCD [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Future studies should investigate the subtypes of ADHD based on the DCD criteria. A possible explanation for this is that alterations in the cerebellum and prefrontal cortex may contribute to the motor difficulties that are experienced by children with ADHD, when it is considered that the cerebellum is one of the primary structures responsible for the performance of motor movements and that the prefrontal cortex is responsible for motor planning [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Previous meta-analysis results have shown that the gray matter volume of the right caudate, prefrontal cortex, cerebellum, and cerebral volume was decreased in children with ADHD compared to typically developing peers [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Moreover, the difficulties in dynamic balance control in children with ADHD and alterations in the cerebellum affecting the fronto-striato-cerebellar connection may affect the balance in children with ADHD [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Dynamic balance control is associated with the neuromuscular system and sensorial system including vestibular, visual, and somatosensory systems [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. During movement, the brain needs to organize different sensorial feedbacks at the same time as individual organization, to coordinate different extremity segment directions, and adjust timing and strength to maintain balance [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Some researchers have shown that children with ADHD cannot modulate the sensorial inputs and this causes challenges in finding the right strategy to protect balance [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. In addition, Shabat et al [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e] showed that the participation patterns of children with ADHD are restricted, which might limit opportunities to practice motor skills. Future studies should investigate the relationship between participation patterns and motor skills.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDifferences in fine motor abilities and balance between children with ADHD-I and ADHD-C\u003c/h2\u003e \u003cp\u003eThe current research's findings demonstrated that children with ADHD-I experienced greater challenges in fine motor skills than those with ADHD-C. Children with ADHD-I showed a 17.5% decrease in manual dexterity and a 14.2% decrease in manual coordination compared to children with ADHD-C. Similar to these findings, Fenollar-Cort\u0026eacute;s, Gallego-Mart\u0026iacute;nez [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] reported that worse fine motor performance was associated with the dimension of inattention, rather than hyperactivity or impulsive dimensions. One possible explanation is that children with ADHD often exhibit a lack of inhibition [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. The absence of inhibition encompasses planning a reaction, inhibiting a response, stopping the continuing response, and regulating interference. Working memory, motivation, self-regulation of emotions, processing of speech, and reconstruction are all aspects of executive functioning that are impacted by these capacities. Problems in these executive functions might affect motor control [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Opposite to the findings of the present study, Egeland [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and Meyer et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] demonstrated that children with ADHD-C had poorer fine motor performance on a grooved pegboard test and visual motor integration. In addition, Pitcher et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] showed no differences between ADHD-I and ADHD-C in respect of manual dexterity and ball skills. These differences could be attributed to the fact that the manual dexterity and manual coordination sub-parameters of BOT-2 were assessed more objectively in the current study than with previous assessment methods [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The BOT-2 included speed-related activities such as making dots in circles, transferring pennies, placing a peg into a pegboard, sorting cards, and stringing blocks to evaluate manual dexterity and manual coordination.\u003c/p\u003e \u003cp\u003eThe findings of this study highlighted that children with ADHD-I had a 16.2% decrease in balance compared to children with ADHD-C. In addition, children with ADHD-C had a 23.8% decrease in balance, and children with ADHD-I had a 36.1% decrease compared to typically developing peers. Similarly, Mao et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] showed that children with ADHD demonstrated a 36.07% decrease in balance compared to typically developing peers according to BOTMP. Goulardins et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] also showed a 9.3% decrease in balance in children with ADHD-C.\u003c/p\u003e \u003cp\u003eThe potential explanation for differences in manual dexterity, manual coordination, and balance between children with ADHD-I and ADHD-C stems from the distinct structural network features associated with the ADHD-C and ADHD-I subtypes. Saad et al. [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] demonstrated that the visual, limbic and ventral attention pathways are linked to ADHD-I, while the frontoparietal, motor, and default mode pathways are associated with ADHD-C. A recent meta-analysis indicated that functional impairments in fronto-striatal-thalamic circuitry and the default mode networks correlate with deficits in response inhibition, disorientation, impulsivity, directed activity, and concentration in the ADHD-C subtype. In addition, dysfunction in the frontoparietal region reflects deficits characteristic of the ADHD-I subtype, including received attention and motivational factors [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In the light of these findings, the current study results support the evidence that attention level could impact fine and gross motor performance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThe major strengths of this study were that comparisons were made of fine and gross motor abilities of children with ADHD-I and ADHD-C using the gold standard measurement, with a large sample size that also included girls. However, a limitation of the study was that comorbid disorders such as developmental coordination disorder and special learning disorders were not evaluated. Future studies should investigate the relationship between motor abilities and comorbid disorders according to ADHD-I and ADHD-C. In addition, future studies should also investigate the other factors that can impact the motor skills including receiving services (including occupational therapy/Physiotherapy), opportunities to practice motor skills, and physical activity participation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eFinally, both the ADHD-I and ADHD-C groups demonstrated lower levels of motor proficiency compared with their typically developing peers, consistent with prior research. Importantly, children with ADHD-C showed better performance in several fine and gross motor domains\u0026mdash;particularly manual dexterity, manual coordination, and balance\u0026mdash;than those with ADHD-I, suggesting a subtype-specific motor profile. Recent meta-analysis further indicates that children with ADHD exhibit substantially reduced motor competence, with manual dexterity being the most impaired subdimension [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], a skill closely linked to academic achievement and everyday functional tasks [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. These findings highlighted the need for systematic assessment of motor abilities across ADHD subtypes. In clinical practice, subtype-sensitive intervention planning may be beneficial; for instance, dual-task\u0026ndash;based training has been shown to enhance manual dexterity by concurrently engaging attentional and motor control processes [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Future studies should investigate how motor skill deficits relate to participation patterns and daily activity engagement in children with ADHD.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eEthical approval\u003c/h2\u003e \u003cp\u003e Ethical approval was obtained from the Health Sciences University Turkey, Antalya Training and Research Hospital of Clinical Research Ethics Committee (Project: 2021/339). Written informed consent was obtained from all participants and/or their caregivers based on the principles stated in the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eInformed consent\u003c/strong\u003e \u003cp\u003e All respondents and signed informed consent forms or participation. Consent for children was given by their parents. Child assent forms were also obtained.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors received no financial support for the research and/or authorship of this article.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eOKK: Writing- Original draft preparation, Investigation, Conceptualization, Methodology KK: Supervision, Investigation, Conceptualization, Methodology, HAT: Visualization, Investigation SK: Investigation MT: Data curation, Software, DD: Supervision, writing\u0026mdash;review and editing phase\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eNo datasets were generated or analysed during the current study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePolanczyk GV, Willcutt EG, Salum GA et al (2014) ADHD prevalence estimates across three decades: an updated systematic review and meta-regression analysis. 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J Am Acad Child Adolesc Psychiatry 47(7):808\u0026ndash;816\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaad JF, Griffiths KR, Kohn MR et al (2017) Regional brain network organization distinguishes the combined and inattentive subtypes of attention deficit hyperactivity disorder. NeuroImage: Clin 15:383\u0026ndash;390\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiustino V, Patti A, Petrigna L et al (2023) Manual dexterity in school-age children measured by the Grooved Pegboard test: Evaluation of training effect and performance in dual-task. Heliyon. ;9(7)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaisbeck LD, Diekfuss JA (2015) Fine and gross motor skills: The effects on skill-focused dual-tasks. Hum Mov Sci 43:146\u0026ndash;154\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"attention deficit hyperactivity disorder, fine motor, gross motor, motor proficiency","lastPublishedDoi":"10.21203/rs.3.rs-8287956/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8287956/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eChildren with attention deficit hyperactivity disorder (ADHD) often demonstrate poorer performance on motor assessments compared with typically developing peers. However, the motor skills of school-aged children with ADHD-Inattentive (ADHD-I) and ADHD-Combined (ADHD-C), as assessed by the Bruininks\u0026ndash;Oseretsky Test of Motor Proficiency, Second Edition (BOT-2), remain insufficiently explored. This study aimed to compare motor skills between children with ADHD-I and ADHD-C, and their typically developing peers.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 150 children with ADHD (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.8, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.6, 90 boys and 60 girls) and 75 typically developing peers (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.9, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.8 years, 56 boys and 44 girls), aged 6\u0026ndash;12 years, were assessed using the BOT-2. Motor proficiency parameters were analyzed using One-Way ANOVA analysis with post hoc comparisons.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe control group scored significantly higher across all BOT-2 domains compared with both ADHD groups. Significant differences between the ADHD subtypes were observed for manual dexterity (ω\u0026sup2; = .17, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), manual coordination (ω\u0026sup2; = .14, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and balance (ω\u0026sup2; = .22, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and favored the ADHD-C group.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eChildren with ADHD-C demonstrated better fine and gross motor skills\u0026mdash;including manual dexterity, coordination, and balance\u0026mdash;than those with ADHD-I. These findings underscore the importance of considering motor proficiency in children with ADHD, particularly those with the inattentive subtype, and may help guide clinical interventions and educational support.\u003c/p\u003e","manuscriptTitle":"Motor Proficiency in School-Aged Children With ADHD: Inattentive Versus Combined Subtypes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-22 10:38:39","doi":"10.21203/rs.3.rs-8287956/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de7ca098-5e88-46ef-8d10-e995577e6bf3","owner":[],"postedDate":"December 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-07T19:53:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-22 10:38:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8287956","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8287956","identity":"rs-8287956","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}