Deciphering developmental dysgraphia: evidence of a verbal advantage

Deciphering developmental dysgraphia: evidence of a verbal advantage | 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 Article Deciphering developmental dysgraphia: evidence of a verbal advantage Aude JOFFROY-FRIXONS, Marieke LONGCAMP, Michel HABIB This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6938106/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 Developmental dysgraphia (DG) affects children’s handwriting despite adequate learning opportunities and intellectual potential. Although not recognized as a distinct clinical entity in international classifications, DG significantly impacts academic performance and wellness. In addition, it often co-occurs with neurodevelopmental disorders (NDDs) such as ADHD, developmental coordination disorder (DCD), and dyslexia (DL). To move beyond deficit-based perspectives and account for the complexity of cognitive functions, mechanisms and associated disorders, the cognitive profiles of DG examined using a strengths-and-weaknesses framework. DG were compared both to reference population and to children with other disorders. 366 children followed by the health network “Resodys”, completed the French adaptation of the Wechsler Intelligence Scale for Children (WISC V). Socioeconomic status was controlled. DG was defined as a significant difficulty in graphic movements impacting academic achievement without assumptions about the origin of the disorder. DL, DCD, and ADHD were diagnosed per ICD-10 criteria. Results revealed that DG outperformed their peers in verbal comprehension, particularly on the “Similarities” subtest. This verbal advantage was unique to DG, distinguishing it from other NDDs and suggesting its potential specificity. The findings are discussed in relation to handwriting models, linguistic and executive functions, and their neuroanatomical underpinnings. Health sciences/Neurology/Neurological disorders/Neurodevelopmental disorders Biological sciences/Neuroscience/Cognitive neuroscience Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Although complete mastery of handwriting takes several years, most children are able to produce letters and words accurately after a few months of practice. Learning how to write involves a complex interplay of processes, from planning ideas to manual motor control [ 1 ][ 2 ]. For instance, executive functions [ 3 ][ 4 ][ 5 ]; fine motor skills [ 6 ], proprioception [ 7 ], visuospatial integration [ 8 ][ 9 ] and orthographic processes [ 10 ][ 11 ][ 12 ][ 13 ] are considered crucial contributors to handwriting acquisition. Between 6% and 33% of children experience persistent difficulties in developing their writing skills, a condition known as developmental dysgraphia [ 14 ][ 15 ][ 16 ][ 17 ]. Although developmental dysgraphia is not classified as a specific learning disorder, dysgraphic children (DG) face significant challenges at the educational level and in daily activities requiring handwriting, and their self-esteem can be deteriorated [ 14 ]. Developmental dysgraphia has been attributed to various underlying causes, including motor coordination deficits linked to visuo-constructive or proprioceptive disorders (peripheral dysgraphia; [ 18 ]), visuo-perceptual deficits (spatial dysgraphia; [ 19 ]), working memory deficits affecting orthographic encoding (linguistic dysgraphia; [ 20 ]), or inaccurate orthographic representations [ 21 ]. In this study, we focus on so-called “graphomotor” aspects of handwriting. We consider developmental dysgraphia as a persistent difficulty in acquiring the handwriting gesture despite adequate learning opportunities and sufficient intellectual potential, without presupposing any specific underlying deficit [ 16 ][ 22 ][ 23 ]. At a graphomotor level, developmental dysgraphia is characterized by a significant impairment in writing quality (e.g., unevenness or irregularity of letters, control of the graphic space, and overall legibility) and/or writing speed, which is markedly below what is expected based on the child's chronological age, intellectual level, general psychomotor development, and age-appropriate education [ 24 ][ 16 ][ 25 ][ 26 ] Developmental dysgraphia often occurs alongside one or more neurodevelopmental disorders (NDD; [ 27 ])like attention deficit hyperactivity disorder (ADHD; [ 28 ][ 29 ][ 30 ][ 31 ][ 32 ][ 33 ][ 34 ][ 35 ]), developmental coordination disorder (DCD; [ 36 ][ 37 ]) or reading disorders (DL; [ 38 ][ 39 ][ 40 ]). Thus, the coexistence of these neurodevelopmental disorders must be taken into accound in order to fully understanding developmental dysgraphia. Recent literature emphasizes the need to adopt a more comprehensive view of the cognitive profiles of NDD, as well as the importance of considering comorbidities [ 41 ][ 42 ][ 43 ]. Here, we analyzed the DGs’ cognitive profiles through the lens of the “pattern of strengths and weaknesses” approach. This framework, developed by Compton et al. (2012)[ 44 ], was designed for application to Specific Language and Learning Disabilities and later applied to other disorders [ 45 ][ 46 ][ 47 ][ 48 ][ 49 ][ 50 ][ 51 ] Our objective was to map the deficits and/or strengths of DG in various cognitive domains, by comparing these children to typically developing children and to NDD. To this end, we analyzed data from the WISC-V test administered to children in the “Résodys” cohort. Resodys is a specialized care system in southern France that provides second-tier intervention for individuals with persistent NDD after an initial unsuccessful attempt. Children in the cohort undergo systematic assessments across cognitive and praxis domains, revealing frequent co-occurring impairments in language, attention, executive functions, and motor coordination. Assessment of writing skills of 366 children with one or more diagnoses (ICD-10 criteria) taken from the cohort revealed dysgraphia in 248 cases. We first compared the cognitive profiles of DG to the WISC-V normative population to determine their specific strengths and weaknesses. Next, we conducted the same analyses to isolate the cognitive specificities of DG in comparison to children with other NDDs (DL, DCD, ADHD). Finally, we examined, from both quantitative and qualitative perspectives, the interactions between different disorders and the previously identified cognitive specificities of DG. MATERIALS AND METHODS The Résodys Cohort In France, specific language and learning disorders are primarily managed in private practice, with social security covering only language disorders. As a result, families must finance neuropsychological assessments, psychomotor, and occupational therapies. To fill this gap, the state-funded Resodys regional health network provides free access to paramedical professionals and a coordinating physician, facilitating the diagnosis of NDDs. Between 2020 and 2022, the Resodys healthcare network supported 1,514 children. These interventions align with the Level 2 guidelines outlined in the French National Health Authority (HAS) care pathway guide for children with specific learning disorders [ 52 ]. This study included children with WISC-V neuropsychological assessments and praxic/writing evaluations. Exclusion criteria were neurological conditions (e.g., head trauma, epileptic syndrome), psychiatric disorders (e.g., non-autistic pervasive developmental disorder), intellectual disability (full-scale WISC-V score < 80), and non-school enrollment. (Fig. 1 ). All children in the sample spoke French as either their native or second language. The final sample consisted of 366 children (253 boys and 113 girls) with an average age of 9 years and 7 months (SD = 2 years and 3 months) at the time of the neuropsychological assessment. All methods were carried out in accordance with relevant guidelines and regulations. The data were processed in accordance with the MR04 reference methodology provided by the French Commission Nationale de l'Informatique et des Libertés (CNIL) for the processing of retrospective personal data. Procedures and methods were approved by the data protection office of the french national center for scientific research under the registration number 2024-UMR7077-10. Only data that was strictly necessary and relevant to the research objectives was included in the database and used. Informed consent was obtained from a parent or a legal guardian for study participation. The datasets generated and/or analysed during the current study are not publicly available due to the protection of personal health data implied by the application of the MR04 methodology but are available from the corresponding author on reasonable request. Diagnoses Clinical evaluations were conducted by specialized health professionals. Given that dysgraphia does not yet fall under a specific diagnostic category, the presence of developmental dysgraphia was assessed through a systematic review of case files. Diagnosis of Dysgraphia To categorize a child as DG, we systematically reviewed all writing-related elements in their case file. In most files included in the sample, handwriting was assessed using the French adaptation of the BHK Test for the rapid assessment of handwriting for children [ 53 ] or for adolescents (BHK-Ado,[ 54 ]). Two key measures were used based on the 5-minutes text copying task: the overall degradation qualitative score and the number of words written. These scores were converted into deviation scores based on age-standardized norms and expressed as standard deviations. To identify deficits in writing quality and/or speed [ 55 ], we calculated the absolute difference between the two standardized scores (degradation – speed) and applied a threshold of 2 standard deviations, in line with established practice. This criterion was systematically crossed with : A concern about writing speed and legibility, expressed by teachers, parents, and/or the child Complaints regarding pain or difficulty, as expressed by children during consultations with healthcare professionals or assessed through the French adaptation of the Children’s Questionnaire for Handwriting Proficiency (CHaP) [ 56 ]. In the absence of a BHK assessment (30 files), we relied on the observations made by the medical coordinator. One file was excluded from the DG group due to an uncorrected visual impairment affecting fixation and eye tracking at the time of the handwriting assessment. Diagnoses of NDD NDD diagnoses were established by the network’s head physician based on ICD-10 criteria. Children were categorized as having dyslexia (DL) or not (noDL), having developmental coordination disorder (DCD) or not (noDCD), and having attention deficit hyperactivity disorder (ADHD) or not (noADHD). Additional diagnoses, including oral language disorder, dysorthographia, dyscalculia, and autism spectrum disorder, were recorded but not considered in this study. Table 1 Characteristics of the sample: size, girl/boy ratio, average ages (in years and months), social position index of the family (SPI family) and social position index of the school (SPI school) of the sample according to diagnoses DG, DL, TDC, ADHD. diagnoses Total headcount ratio girl/boy age (mean +/- standard deviation in year) SPI family SPI school Total sample 366 23/50 9,6+-2,2 104+-30 108+-15 DG / noDG 248 / 118 8/23 19/25 9,4 +-2,2 9,11+-2,3 105+-30 / 103+-30 108+-15 / 108+-13 DL / noDL 225 / 141 23/52 12/25 9,8+-2,2 9,3+-2,3 105+-29 / 103+-31 107+-15 / 109+-14 DCD/noDCD 164 / 202 21/50 33/68 9,6+-2,2 9,7+-2,2 102+-29 / 106+-30 108+-15 / 108+-16 ADHD/noADHD 223 / 143 2/5 4/7 9,3+-2,2 10,2+-2,2 104+-30 / 105+-29 108+-15 / 107+-15 DG + DL 148 3/10 9,6+-2,2 107+-29 108+-16 DG + DCD 131 2/5 9,6+-2,1 100+-29 107+-16 DG + ADHD 156 1/4 9,3+-2,1 106+-29 107+-15 DG + DL + DCD 74 8/25 9,7+-2,1 105+-29 107+-17 DG + DL + ADHD 89 3/10 9,5+-2,2 110+-28 107+-16 DG + DCD + ADHD 82 9/25 9,4+-2,3 103+-30 106+-15 DG + DL + DCD + ADHD 47 1/4 9,9+-2,3 109+-28 108+-17 Final composition of the sample: Of the 366 children in the sample, 248 were diagnosed DG, 225 DL, 164 DCD and 223 ADHD. The social position index (SPI) of the family and the school attended by each child was included as a control variable, and no significant differences between groups (at α = .1) were observed in the comparisons across the diagnostic categories (DG/noDG, DL/noDL, DCD/noDCD, ADHD/noADHD) (Table 1 ). Assessment of Cognitive Abilities: All children completed the French adaptation of the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V) [ 57 ], with age-adjusted scores. The WISC-V is a widely used intelligence test for children aged 6–16 years, normed on a French reference sample of 1,100 children to reflect IQ distribution in the general population. It includes ten primary and five secondary subtests, enabling the calculation of five primary and five supplementary index scores (for details see supplementary materials 1). Raw scores from subtests are converted to standard scores with a mean of 10 (SD = 3). The indexes are normally distributed with a mean of 100 (SD = 15). This study focused on the standard scores for the ten primary subtests and five primary indexes. The Full-Scale IQ (FSIQ), derived from SIM, VOC, BD, DS, MAT, FW, and COD subtests, represents general cognitive efficiency but provides limited insight into specific skills. Therefore, it was excluded from this analysis. Data Analysis Software RStudio version 2024.04.2+ [ 58 ] and JASP version 0.19.1[ 59 ] were used for statistical analysis. The data were processed using the BioStatR [ 60 ], Bolstad [ 61 ], stats [ 62 ], lawstat [ 63 ], pastecs [ 64 ], forecast [ 65 ], and Matrix [ 66 ] packages. Preprocessing and Statistical Comparisons Qualitative variables indexing the presence of the neurodevelopmental disorders (NDD) of interest (DG, DL, DCD, ADHD) were coded into binary code (1: presence of the disorder / 0: absence of the disorder). For each child, the standard scores of WISC-V subtests, indexes, and IQ scores (FSIQ) were extracted. The normality of the FSIQ was verified by observing the quantile-quantile graph. There was no evidence that the FSIQ exhibited any skewness or kurtosis different from the normal distribution according to the Jarque-Bera normality test [ 67 ]. Statistical analysis . STEP 1: Comparison of indexes and subtest distributions between DG and the reference population (REF) Distributions of DG and REF indexes and subtests scores were compared using the WISC-V manual tables (A2–A7, B2, B4, B6), and differences in group dispersion were assessed via χ² tests of homogeneity and/or Kolmogorov tests. STEP 2: Effect of the presence of DG on the subtests scores The means of the WISC-V subtests of the DG and noDG groups were compared using inferential and Bayesian Student t-tests. The Bayes Factor (BF) quantifies the strength of the evidence for a standardized mean difference between the two groups. The strength of the evidence was qualified according to Jeffrey's (1961) [ 68 ] scale: not very important for 1 < BF < 3; substantial for 3 < BF < 10, strong for 10 < BF < 30, very strong for 30 < BF 100. STEP 3: Effect of the presence of other disorders (DL, DCD and ADHD) on the subtests scores The means of the WISC-V subtests of the various pairs of subsamples (DL/noDL; DCD/noDCD; ADHD/noADHD) were compared using inferential and Bayesian Student's t-tests. This comparison was limited to the scores showing significant difference between DG /no DG and a BF > 3 in STEP 2. STEP 4: Interaction effects of the presence of disorders The final step aimed to assess the combined effects of the four disorders on the subtests which were found to be specific to the DG/noDG comparison in the previous steps. We conducted a Generalized Linear Model (GLM), followed by a factorial ANOVA including interactions and post-hoc tests. Data normality and homoscedasticity (assessed via Levene’s test; [ 69 ][ 70 ]) satisfy the validity conditions of gaussian family at p = .05 . RESULTS STEP 1: Comparison of indexes and subtest distributions between DG and the reference population (REF) All the distribution comparisons of the index scores (VCI, VSI, FRI, WMI, PSI) showed significant differences (Fig. 2 ). To complete these observations, an analysis of heterogeneity based on the discrepancy between all pairs of subtests comparing to critical values from the WISC-V manual is detailed in supplementary materials 2. STEP 2: Effect of the presence of DG on the subtests scores Frequentist analyses showed that DG had higher standard scores than noDG on the VCI subtests (SIM and VOC); DG had lower scores than noDG on the PSI subtests (SYM and COD; DG had higher scores than noDG on the FW and PS substests. No significant differences were found for the other subtests. Significant frequentist analyses (SIM, VOC, FW, PS, COD and SYM subtests) were supplemented by Bayesian analyses. The comparison yielded decisive evidence for the SIM and VOC subtests (BF SIM =10 12 >100; BF VOC =10 5 >100), very strong evidence for the COD subtest (30 < BF COD =44 < 100) and negligible evidence for the other subtests (BF FW = 2 < 3; BF PS =2 < 3; BF SYM = 1 < 3). Taken together, frequentist results and Bayesian evidence indicate that DG show a significant advantage in verbal processing (SIM, VOC) and slower processing speed (COD) compared to noDG. STEP 3: Effect of the presence of other disorders (DL, DCD and ADHD) on the subtests scores To check whether these differences were specific to DG, the same comparisons of means were carried out between the DL/noDL, DCD/noDCD and ADHD/noADHD subgroups. These comparisons were limited to the subsets that differed between DG/noDG (SIM, VOC and COD). For the VOC subtest, scores were significatively higher in the ADHD than in the noADHD group (M_ VOC ADHD =11.0; M_ VOC noADHD =9.9; 10 < BF VOC_ADHD = 28 < 30); t(364)=-3.4, p < .001). They were lower in the DL than in the noDL group (M_VOC DL =10.2; M_VOC noDL =11.2; t(364) = 3.2, p < .001; 10 < BF VOC_DL = 17 < 30). Scores of the DCD and noDCD groups did not significantly differ. For the COD subtest, scores were significatively lower in the DCD than in the noDCD group (M_COD DCD =7.5 ; M_COD noDCD =9.0); t(364) = 5.1, p 100) For the SIM subtest scores were significatively lower in the DL than in the noDL group (M_SIM DL =10.4; M_SIM noDL =11.3; t(364) = 3.0, p < .01; 10 < BF VOC−DL = 17 < 30). These results show a specific verbal advantage on the SIM subtest only for DG group. All results of steps 2 and 3 are detailed in supplementary materials 3 STEP 4: Interaction effects of the presence of disorders The previous analyses showed that higher scores on the SIM subtest are a unique feature of DG. Step 4 was thus focused on the SIM scores. The generalized linear model (GLM) confirmed a significant overall effect of neurodevelopmental disorders (NDDs) on SIM scores: DG was associated with significantly higher SIM scores; DL and DCD were associated with significantly lower SIM scores; ADHD did not significantly affect SIM scores (Fig. 3 A). Specifically, the effect of the presence of DG on SIM subtest performance is estimated to be 2.9 points higher than that of DL, and 2.4 points higher than that of DCD. Moreover, the factorial ANOVA (DL * DG * TDC * TA) revealed a significant simple interaction effect of DG*DCD (F(1,350) = 0.043; p < .001; η 2 = 0.02). Post hoc tests following the ANOVA indicated significant pairwise differences for the DG*DCD interaction, with the exception of the noDCD + noDG / DCD + noDG contrast (Fig. 3 B and 3 C). The mean scores for the SIM subtest of all groups are presented in supplementary material 4. DISCUSSION The aim of this study was to uncover the mechanisms underlying developmental dysgraphia by mapping of the cognitive strengths and weaknesses of DG children. Developmental dysgraphia was operationally defined as a difficulty in graphic movements without any presupposition as to the origin of the disorder. Given the high comorbidity rate, we considered dysgraphia together with associated disorders, without attempting to isolate it [ 41 ][ 42 ][ 43 ]. The main finding was an advantage of DG over noDG in the cohort specifically on the SIM subtest. In parallel, DG displayed a deficit in processing speed mainly reflected in the COD subtest. This pattern was not found when the children were categorized according to the presence of DL, DCD or ADHD. Conversely, DL was associated to verbal deficits and no impairment in COD, DCD was associated to a more marked deficit in COD and no verbal advantage, and ADHD was associated to a verbal advantage only on the VOC subtest with no advantage on SIM or deficit in COD. Of note, the verbal advantage was also found when DG were compared with the reference population, while the scores of DG to most non-verbal subtests were inferior to those of the general population. In sum, DG showed a specific dissociation between verbal and non-verbal skills, with good verbal conceptualization along with standard or poor nonverbal skills. Compared to the other children of the cohort, they were not more impaired in any of the subtests except COD. Our finding of a pattern of high proficiency in one domain along with deficits in another domain in DG is consistent with recent accounts of NDD that attempt to move beyond deficit-based approaches [ 71 ]. The exceptional verbal abilities of DG were found for both the SIM and VOC subtests, but the SIM subtest was the only one to specifically characterize DG. Conversely, other disorders were associated with decreased performance. Beyond the main effect of DG on SIM scores, a single specific interaction between DG and DCD was identified. This clearly indicates that the additional presence of extra disorders to DG does not eliminate this verbal advantage. While the verbal advantage is reduced when DG is associated with DCD, it remains present. Conversely, DCD but without DG display degraded verbal scores. The cognitive profile of DG whether or not comorbid with DCD, differ from that of DCD alone. How can this verbal advantage of DG be interpreted? A first possible explanation is that it results from a recruitment bias. For instance, the use of a second-tier facility could be linked to a better family socio-economic level, which favours performance on certain WISC subtests [ 72 ]. The free care provided by the facility disqualifies this interpretation and there does not seem to be any valid reason why this advantage in verbal reasoning should concern only DG to the exclusion of all other forms of NDD. Besides, the index of social position did not differ between the families of DG compared to noDG. An alternative explanation is that DG weaker non-verbal processing may result from their reliance on a preexisting verbal advantage [ 73 ]. This disinvestment in writing could stem from a lack of practice [ 74 ][ 75 ]; however, this seems unlikely given their prior pedagogical remediation. Another possibility is that their academic environment is less demanding, yet no significant school-related differences were found between DG and noDG. Another possible explanation could be an over-investment of the DG in the verbal domain, to compensate a weakness in other cognitive domains, especially in processing speed. Recent accounts of neurodevelopmental disorders emphasize altered connectivity patterns leading to an imbalance in the neural systems supporting cognitive functions that could generate dissociations between severely impaired functions and paradoxically high performance in other domains [ 71 ]. The alterations in one network could also lead to resource allocation to a distinct compensatory network, which could explain specific cognitive profiles with extremely high-functionning domains associated to massive impairments in other domains. Although it cannot be formally refuted, this hypothesis is not fully supported by our results. Accordingly, one would expect that DCD would exhibit an even greater compensatory effect. However, contrary to this expectation, our findings suggest that DCD is not linked to improved verbal performance. On the other hand, there are compelling arguments for an early developmental origin of the dissociation between verbal and other cognitive skills in DG. For example, it may have a genetic or a fetal neurodevelopmental origin, as observed in autism spectrum disorder [ 76 ][ 77 ], Williams syndrome [ 78 ] and childhood early epilepsy [ 79 ]. The verbal advantage in DG might be related to an imbalance between the early development of verbal and nonverbal brain substrates. Earlier maturation of the right hemisphere could increase the vulnerability of nonverbal networks while promoting verbal development. Neuroimaging studies [ 80 ][ 81 ] suggest that verbal/nonverbal discrepancies correlate with cortical thickness and connectivity in frontal regions, particularly the inferior frontal gyri. These areas, crucial for executive functions like conflict monitoring, inhibitory control, and working memory [ 82 ][ 83 ][ 84 ], also play a key role in handwriting development [ 5 ][ 85 ]. Dysfunction in this system has been observed in dyslexic children with handwriting difficulties [ 38 ] and atypical connectivity in executive and sensory-motor networks during handwriting tasks has been reported [ 40 ]. Altogether, this body of literature points towards a common neurodevelopmental origin of unusually high verbal skills and deficient motor control of handwriting occurring through atypical functioning of brain networks supporting executive control in DG. Further structural and functional imaging studies are needed to confirm this interpretation. Our study only focused on the different domains of the subtest of the WISC-V. Several perceptual, motor and executive functions were not explored which should be done in future studies to explore more precisely the impact of executive functions in developmental dysgraphia. Finaly, the processing speed deficit in DG, despite unaffected reasoning and working memory, should be interpreted cautiously, as processing speed tests require graphical responses that may disadvantage DG. Future research should use alternative tests without graphical responses to better assess processing speed in DG. If a bias is confirmed, the validity of the WISC processing speed index and similar cognitive tests requiring graphic responses for children with writing difficulties may need reconsideration. This study is the first to examine the cognitive performance of DG, as assessed by the WISC-V, within a cohort of children with neurodevelopmental disorders. A key contribution of this research is the identification of a robust and specific verbal advantage in DG, in addition to a processing speed deficit. This distinctive pattern sets apart these children both from their typically developing peers and from children with other disorders. Our findings thus suggest a potential specificity of DG among NDD. These findings are particularly important, as difficulties in automating writing can lead to slow and illegible output, significantly increasing the risk of poor academic performance and low self-esteem [ 86 ], and impacting the teachers' evaluations [ 87 ][ 88 ]. Thus, gaining a deeper understanding of writing difficulties and their developmental origins is essential for supporting these children and enhancing their academic success. This study paves the way for clinical interventions that leverage the identified verbal strengths to develop targeted remediation strategies for DG. Declarations Author Contribution "All authors wrote the main manuscript text and A.J-F prepared figures. All authors reviewed the manuscript." Data Availability The data were processed in accordance with the MR04 reference methodology provided by the French Commission Nationale de l'Informatique et des Libertés (CNIL) for the processing of retrospective personal data. Procedures and methods were approved by the data protection office of the french national center for scientific research under the registration number 2024-UMR7077-10. Only data that was strictly necessary and relevant to the research objectives was included in the database and used. Informed consent was obtained from a parent or a legal guardian for study participation. The datasets generated and/or analysed during the current study are not publicly available due to the protection of personal health data implied by the application of the MR04 methodology but are available from the corresponding author on reasonable request. References Geertsen, S. S. et al. Motor Skills and Exercise Capacity Are Associated with Objective Measures of Cognitive Functions and Academic Performance in Preadolescent Children. PLOS ONE . 11 (8), e0161960 (2016). Lopez, C. & Vaivre-Douret, L. Les grandes fonctions cérébrales en jeu dans le développement graphomoteur typique et pathologique de l’écriture manuscrite. Rev. Neuropsychol. 13 (4), 255–277 (2021). Alamargot, D., Lambert, E. & Chanquoy, L. La production écrite et ses relations avec la mémoire. Approche Neuropsychol. Apprentiss Chez Enfant ; (2005). (81). Berninger, V., Abbott, R., Cook, C. R. & Nagy, W. Relationships of Attention and Executive Functions to Oral Language, Reading, and Writing Skills and Systems in Middle Childhood and Early Adolescence. J. Learn. Disabil. 50 (4), 434–449 (2017). Palmis, S. et al. The handwriting brain in middle childhood. Dev. Sci. 24 (2), e13046 (2021). Schneck, C. M. Comparison of Pencil-Grip Patterns in First Graders With Good and Poor Writing Skills. Am. J. Occup. Ther. 45 (8), 701–706 (1991). Cornhill, H. & Case-Smith, J. Factors that relate to good and poor handwriting. Am. J. Occup. Ther. Off Publ Am. Occup. Ther. Assoc. 50 (9), 732–739 (1996). Hong, S. Y., Jung, N. H. & Kim, K. M. The correlation between proprioception and handwriting legibility in children. J. Phys. Ther. Sci. 28 (10), 2849–2851 (2016). Malloy-Miller, T., Polatajko, H. & Anstett, B. Handwriting Error Patterns of Children with Mild Motor Difficulties. Can. J. Occup. Ther. 62 (5), 258–267 (1995). Bourdin, B. & Fayol, M. Even in adults, written production is still more costly than oral production. Int. J. Psychol. 37 (4), 219–227 (2002). Kandel, S. & Perret, C. How does the interaction between spelling and motor processes build up during writing acquisition? Cognition 136 , 325–336 (2015). Maurer, M., Truxius, L., Sägesser Wyss, J. & Eckhart, M. From Scribbles to Script: Graphomotor Skills’ Impact on Spelling in Early Primary School. Children 10 , 1886 (2023). Nottbusch, G., Weingarten, R. & Sahel, S. From written word to written sentence production. Writ Cogn Res Appl [Internet]. [cited 2021 Apr 14]; (2007). Available from: https://pub.uni-bielefeld.de/record/1897903 Chung, P. J., Patel, D. R. & Nizami, I. Disorder of written expression and dysgraphia: definition, diagnosis, and management. Transl Pediatr. 9 (S1), S46–54 (2020). Döhla, D., Willmes, K. & Heim, S. Cognitive Profiles of Developmental Dysgraphia. Front. Psychol. 9 , 2006 (2018). Hamstra-Bletz, L. & Blöte, A. W. A longitudinal study on dysgraphic handwriting in primary school. J. Learn. Disabil. 26 (10), 689–699 (1993). Overvelde, A. & Hulstijn, W. Handwriting development in grade 2 and grade 3 primary school children with normal, at risk, or dysgraphic characteristics. Res. Dev. Disabil. 32 (2), 540–548 (2011). del Castillo, M. C., Maldonado Belmonte, M. J., Ruiz-Falcó Rojas, M. L., López Pino, M. A. & Bernabeu Verdú, J. Fournier, Suárez Rodríguez JM. Cerebellum atrophy and development of a peripheral dysgraphia: a paediatric case. Cerebellum Lond Engl. ;9(4):530–6. (2010). Deuel, R. K. Developmental dysgraphia and motor skills disorders. J. Child. Neurol. 10 (Suppl 1), S6–8 (1995). Berninger, V. W. Defining and differentiating dysgraphia, dyslexia, and language learning disability within a working memory model. In: Brain, behavior, and learning in language and reading disorders. New York, NY, US: The Guilford Press; 103–134. (2008). (Challenges in language and literacy). McCloskey, M. & Rapp, B. Developmental dysgraphia: An overview and framework for research. Cogn. Neuropsychol. 34 (3–4), 65–82 (2017). Lopez, C. & Vaivre-Douret, L. Exploratory Investigation of Handwriting Disorders in School-Aged Children from First to Fifth Grade. Children 10 (9), 1512 (2023). Richards, R. G. The Writing Dilemma: Understanding Dysgraphia [Internet]. Richards Educational Therapy Center, inc; 1998 [cited 2025 Jan 24]. 86 p. Available from: http://archive.org/details/writingdilemmaun0000regi Asselborn, T. et al. Automated human-level diagnosis of dysgraphia using a consumer tablet. Npj Digit. Med. 1 (1), 1–9 (2018). Paz-Villagrán, V., Danna, J. & Velay, J. L. Lifts and stops in proficient and dysgraphic handwriting. Hum. Mov. Sci. 33 , 381–394 (2014). Rosenblum, S., Weiss, P. & Parush, S. Product and Process Evaluation of Handwriting Difficulties. Educ. Psychol. Rev. 15 , 41–81 (2003). Jover, M. & Huau, A. A Dimensional Approach to Comorbidity Between Developmental Coordination Disorder and Dyslexia: A Study of Graphomotor Abilities. ANAE Approche Neuropsychol. Apprentiss Chez Enfant . 175 (33), 673–688 (2021). Adi-Japha, E. et al. ADHD and Dysgraphia: Underlying Mechanisms. Cortex. ;43(6):700–9. (2007). Brossard-Racine, M. et al. Persistent Handwriting Difficulties in Children With ADHD After Treatment With Stimulant Medication. J. Atten. Disord . 19 (7), 620–629 (2015). Capodieci, A., Lachina, S. & Cornoldi, C. Handwriting difficulties in children with attention deficit hyperactivity disorder (ADHD). Res. Dev. Disabil. 74 , 41–49 (2018). DuPaul, G. J., Gormley, M. J. & Laracy, S. D. Comorbidity of LD and ADHD: Implications of DSM-5 for Assessment and Treatment. J. Learn. Disabil. 46 (1), 43–51 (2013). Laniel, P., Faci, N., Plamondon, R., Beauchamp, M. H. & Gauthier, B. Kinematic analysis of fast pen strokes in children with ADHD. Appl. Neuropsychol. Child. 9 (2), 125–140 (2020). Racine, M. B., Majnemer, A., Shevell, M. & Snider, L. Handwriting performance in children with attention deficit hyperactivity disorder (ADHD). J. Child. Neurol. 23 (4), 399–406 (2008). Schoemaker, M. M., Ketelaars, C. E. J., van Zonneveld, M., Minderaa, R. B. & Mulder, T. Deficits in motor control processes involved in production of graphic movements of children with attention-deficit-hyperactivity disorder. Dev. Med. Child. Neurol. 47 (6), 390–395 (2005). Tucha, O. & Lange, K. Handwriting and Attention in Children and Adults with Attention Deficit Hyperactivity Disorder. J. Psychophysiol. 18 , 216–216 (2004). Lopez, C., Hemimou, C., Golse, B. & Vaivre-Douret, L. Developmental dysgraphia is often associated with minor neurological dysfunction in children with developmental coordination disorder (DCD). Neurophysiol. Clin. 48 (4), 207–217 (2018). Nicolson, R. I. & Fawcett, A. J. Dyslexia, dysgraphia, procedural learning and the cerebellum. Cortex 47 (1), 117–127 (2011). Gosse, C., Dricot, L. & Van Reybroeck, M. Evidence of graphomotor dysfunction in children with dyslexia: A combined behavioural and fMRI experiment. Cortex 148 , 68–88 (2022). Jolly, C., Jover, M. & Danna, J. Dysgraphia Differs Between Children with Developmental Coordination Disorder and/or Reading Disorder. J. Learn. Disabil. 57 (6), 397–410 (2024). Yang, Y. et al. The brain basis of handwriting deficits in Chinese children with developmental dyslexia. Dev. Sci. 25 (2), e13161 (2022). McGrath, L. M., Peterson, R. L. & Pennington, B. F. The Multiple Deficit Model: Progress, Problems, and Prospects. Sci. Stud. Read. Off J. Soc. Sci. Study Read. 24 (1), 7–13 (2020). Moll, K. et al. Interpreting the Comorbidity of Learning Disorders. Front Hum Neurosci [Internet]. 2021 Dec 9 [cited 2025 Jan 7];15. Available from: https://www.frontiersin.org/journals/human-neuroscience/articles/ 10.3389/fnhum.2021.811101/full Pennington, B. F. From single to multiple deficit models of developmental disorders. Cognition 101 (2), 385–413 (2006). Compton, D. L., Fuchs, L. S., Fuchs, D., Lambert, W. & Hamlett, C. The Cognitive and Academic Profiles of Reading and Mathematics Learning Disabilities. J. Learn. Disabil. 45 (1), 79–95 (2012). Audras-Torrent, L. et al. WISC-V Profiles and Their Correlates in Children with Autism Spectrum Disorder without Intellectual Developmental Disorder: Report from the ELENA Cohort. Autism Res. 14 (5), 997–1006 (2021). Becker, A., Daseking, M. & Kerner auch Koerner, J. Cognitive Profiles in the WISC-V of Children with ADHD and Specific Learning Disorders. Sustainability 13 (17), 9948 (2021). Giofrè, D., Toffalini, E., Altoè, G. & Cornoldi, C. Intelligence measures as diagnostic tools for children with specific learning disabilities. Intelligence 61 , 140–145 (2017). Giofrè, D. & Cornoldi, C. The structure of intelligence in children with specific learning disabilities is different as compared to typically development children. Intelligence 52 , 36–43 (2015). Joffroy-Frixons, A., Longcamp, M., Velay, J. L. & Habib, M. Avantage cognitif dans une cohorte d’enfants dysgraphiques: Analyse préliminaire de la base de données «Résodys». ANAE Approche Neuropsychol Apprentiss Chez Enfant [Internet]. [cited 2025 Jan 27];186. (2023). Available from: https://amu.hal.science/hal-04296001 Okada, S., Iiri, C., Azumi, Y. & Ohtani, K. Cognitive Profiles of Children With Autism Spectrum Disorder on the Japanese Version of WISC-IV. Jpn J. Educ. Psychol. 69 (3), 254–267 (2021). Toffalini, E., Giofrè, D. & Cornoldi, C. Strengths and Weaknesses in the Intellectual Profile of Different Subtypes of Specific Learning Disorder: A Study on 1,049 Diagnosed Children. Clin. Psychol. Sci. 5 (2), 402–409 (2017). HAS. Guide parcours de santé: Comment améliorer le parcours de santé d’un enfant avec troubles spécifiques du langage et des apprentissages ? (2017). Charles, M., Régis, S. & Albaret, J. M. BHK – Echelle d’évaluation rapide de l’écriture chez l’enfant (ECPA, 2003). Soppelsa, R. & Albaret, J. M. BHK Ado. ECPA; (2013). Casteran, L. et al. Identification de deux sous-types de dysgraphies à partir de l’analyse de paramètres cinématiques et statiques de l’écriture d’enfants typiques et porteurs d’une dysgraphie. Approche Neuropsychol. Apprentiss Chez Enfant . 172 , 337 (2021). Barray, V. Écriture manuelle et dyspraxie/ trouble de l’acquisition de la coordination, partie 2: intérêt à long terme. Développements 12 (3), 6–17 (2012). Wechsler, W. I. S. C. V - Échelle d’intelligence de Wechsler pour enfants et adolescents - [Internet]. 5ème édition. ECPA par Pearson; 2016 [cited 2023 Jun 29]. Available from: https://www.pearsonclinical.fr/wisc-v RStudio Team & RStudio Integrated Development Environment for R}, author = {{RStudio Team}}, organization = {RStudio, PBC.}, address = {Boston, MA}, year = {2020}, url = (2020). {http://www.rstudio.com/} , } [Internet]. Boston, MA; Available from: www.rstudio.com. JASP Team. JASP (Version 0.19.3)[Computer software] [Internet]. (2024). Available from: https://jasp-stats.org/ Bertrand, F., Maumy-Bertrand, M. & BioStatR Initiation à La Statistique Avec R [Internet]. 2009 [cited 2024 Dec 9]. p. 4.0.1. Available from: https://CRAN.R-project.org/package=BioStatR Curran, J. & Bolstad Functions for Elementary Bayesian Inference [Internet]. 2005 [cited 2024 Dec 9]. p. 0.2.42. Available from: https://CRAN.R-project.org/package=Bolstad R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; (2013). Available from: http://www.R-project.org/ Gastwirth, J. L. et al. lawstat: Tools for Biostatistics, Public Policy, and Law [Internet]. 2006 [cited 2024 Dec 9]. p. 3.6. Available from: https://CRAN.R-project.org/package=lawstat Grosjean, P. & Ibanez, F. pastecs: Package for Analysis of Space-Time Ecological Series [Internet]. 2002 [cited 2024 Dec 9]. p. 1.4.2. Available from: https://CRAN.R-project.org/package=pastecs Hyndman, R. et al. forecast: Forecasting Functions for Time Series and Linear Models [Internet]. 2009 [cited 2024 Dec 9]. p. 8.23.0. Available from: https://CRAN.R-project.org/package=forecast Bates, D., Maechler, M., Jagan, M. & Matrix Sparse and Dense Matrix Classes and Methods [Internet]. 2000 [cited 2024 Dec 9]. p. 1.7-1. Available from: https://CRAN.R-project.org/package=Matrix Jarque, C. M. & Bera, A. K. Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Econ. Lett. 6 (3), 255–259 (1980). Jeffreys, H. Theory of probability. 3d ed. Oxford: Clarendon Press; 447 p. (1961). Fox, J. Applied regression analysis and generalized linear models. Third Edition. Los Angeles: SAGE; 791 p. (2016). Fox, J. & Weisberg, S. An R companion to applied regression. Third edition. Los Angeles: SAGE; 577 p. (2019). Sokolowski, H. M. & Levine, B. Common neural substrates of diverse neurodevelopmental disorders. Brain 146 (2), 438–447 (2022). Takeuchi, H. et al. Childhood socioeconomic status is associated with psychometric intelligence and microstructural brain development. Commun. Biol. 4 (1), 1–19 (2021). Cavalli, E. et al. Vocabulary skills are well developed in university students with dyslexia: Evidence from multiple case studies. Res. Dev. Disabil. 51–52 , 89–102 (2016). Estienne, F., De Barelli, T., Huchet, F. & De Barelli, F. Dysorthographie et dysgraphie: comprendre, évaluer, agir plus de 400 exercices. 4e éd. entièrement revue et enrichie (Elsevier Masson, 2023). (Collection Orthophonie). Jolly, C. & Gentaz, E. Évaluation des effets d’entraînements avec tablette tactile destinés à favoriser l’écriture de lettres cursives chez des enfants de Cours Préparatoire. Sci. Technol. Inf. Commun. Pour LÉducation Form. 20 (1), 495–512 (2013). Charman, T. et al. IQ in children with autism spectrum disorders: data from the Special Needs and Autism Project (SNAP). Psychol. Med. 41 (3), 619–627 (2011). Schmitz, N. et al. Neural correlates of executive function in autistic spectrum disorders. Biol. Psychiatry . 59 (1), 7–16 (2006). Farran, E. K. et al. Cross-sectional and longitudinal assessment of cognitive development in Williams syndrome. Dev. Sci. 27 (1), e13421 (2024). van Iterson, L., de Jong, P. F. & Zijlstra, B. J. Pediatric epilepsy and comorbid reading disorders, math disorders, or autism spectrum disorders: impact of epilepsy on cognitive patterns. Epilepsy Behav. 44 , 159–168 (2015). Margolis, A. E. et al. Using IQ Discrepancy Scores To Examine the Neural Correlates of Specific Cognitive Abilities. J. Neurosci. 33 (35), 14135–14145 (2013). Margolis, A. E. et al. Verbal–spatial IQ discrepancies impact brain activation associated with the resolution of cognitive conflict in children and adolescents. Dev. Sci. 21 (2), e12550 (2018). Dosenbach, N. U. F. et al. A core system for the implementation of task sets. Neuron 50 (5), 799–812 (2006). Ham, T., Leff, A., de Boissezon, X., Joffe, A. & Sharp, D. J. Cognitive Control and the Salience Network: An Investigation of Error Processing and Effective Connectivity. J. Neurosci. 33 (16), 7091–7098 (2013). Ruffini, C., Osmani, F., Martini, C., Giera, W. K. & Pecini, C. The relationship between executive functions and writing in children: a systematic review. Child. Neuropsychol. J. Norm Abnorm. Dev. Child. Adolesc. 30 (1), 105–163 (2024). Cachia, A. et al. The sulcal patterns of the occipito-temporal and anterior cingulate cortices influence reading and writing in children and adults. Cerebral Cortex.. Feder, K. P. & Majnemer, A. Handwriting development, competency, and intervention. Dev. Med. Child. Neurol. 49 (4), 312–317 (2007). Connelly, V., Dockrell, J. E., Walter, K. & Critten, S. Predicting the quality of composition and written language bursts from oral language, spelling, and handwriting skills in children with and without specific language impairment. Writ. Commun. 29 (3), 278–302 (2012). Santangelo, T. & Graham, S. A comprehensive meta-analysis of handwriting instruction. Educ. Psychol. Rev. 28 (2), 225–265 (2016). Additional Declarations No competing interests reported. Supplementary Files supplementarymaterials1.docx supplementarymaterials2.docx Supplementarymaterials3.docx Supplementarymaterials4.docx 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6938106","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":489756628,"identity":"977befe8-c2ac-455f-9140-f518af318c5f","order_by":0,"name":"Aude JOFFROY-FRIXONS","email":"data:image/png;base64,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","orcid":"","institution":"Aix-Marseille University","correspondingAuthor":true,"prefix":"","firstName":"Aude","middleName":"","lastName":"JOFFROY-FRIXONS","suffix":""},{"id":489756631,"identity":"fdb899f4-c78a-4326-b23b-281cef49081a","order_by":1,"name":"Marieke LONGCAMP","email":"","orcid":"","institution":"Aix-Marseille University","correspondingAuthor":false,"prefix":"","firstName":"Marieke","middleName":"","lastName":"LONGCAMP","suffix":""},{"id":489756632,"identity":"1243783b-ad3f-43f9-a82f-abaf220b00ee","order_by":2,"name":"Michel HABIB","email":"","orcid":"","institution":"Neurodys-PACA Institute","correspondingAuthor":false,"prefix":"","firstName":"Michel","middleName":"","lastName":"HABIB","suffix":""}],"badges":[],"createdAt":"2025-06-20 10:38:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6938106/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6938106/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87732983,"identity":"a0811efd-0e56-41a2-886e-2e5ad86c1f59","added_by":"auto","created_at":"2025-07-28 11:53:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":133154,"visible":true,"origin":"","legend":"\u003cp\u003ePresentation of the selection process for the subgroup analyzed in the current study\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6938106/v1/857899b7724242d4f481e9ed.png"},{"id":87731649,"identity":"25fb4a2d-93cd-4b51-903f-a82d853ae70d","added_by":"auto","created_at":"2025-07-28 11:45:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":136461,"visible":true,"origin":"","legend":"\u003cp\u003eDensity curves of the distribution and mean of measurements of the 5 indices in DG and REF. A: Verbal Comprehension Index; B: Visuo-Spatial Index; C: Fluid Reasoning Index D: Working Memory Index; E: Processing Speed Index\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6938106/v1/fed28d64c2abdf5ee5d818de.png"},{"id":87731651,"identity":"b7f8e6c2-aac9-43c6-b8d6-30b352613227","added_by":"auto","created_at":"2025-07-28 11:45:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":137641,"visible":true,"origin":"","legend":"\u003cp\u003eA: Results of the GLM on the SIM subtest \u0026nbsp;; B: simple interaction DG*DCD for the Post-hoc analysis of the four-factor ANOVA (DG, DL, DCD and ADHD) on the SIM subtest; red arrows indicate significant interactions. Significance level of the p Bonferroni : * \u0026lt;.10, ** \u0026lt;.05, *** \u0026lt;.01 ; C : Interaction between the présence of DG and DCD (attention c’est marqué TDC sur le plot) on the the SIM subtest scores\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6938106/v1/251c20e8904c53bd345432d8.png"},{"id":98623988,"identity":"1ec5485e-6d32-4296-8a19-3852a2f44b55","added_by":"auto","created_at":"2025-12-19 17:07:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1124625,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6938106/v1/89ee72d7-1f65-46d6-bb4d-e522ec118baf.pdf"},{"id":87731643,"identity":"c79779af-d345-4435-a3f5-da8af9eca290","added_by":"auto","created_at":"2025-07-28 11:45:49","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15036,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarymaterials1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6938106/v1/bd772705e4a22875ca28b8c1.docx"},{"id":87731646,"identity":"8f1d87f6-aff7-4169-b8c3-713d9a706890","added_by":"auto","created_at":"2025-07-28 11:45:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":186194,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarymaterials2.docx","url":"https://assets-eu.researchsquare.com/files/rs-6938106/v1/c5db74ba1a7d78c928bfe5fb.docx"},{"id":87731655,"identity":"b0b3a4c9-5f26-49d4-afd6-26fe11c7c8e8","added_by":"auto","created_at":"2025-07-28 11:45:50","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":278249,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials3.docx","url":"https://assets-eu.researchsquare.com/files/rs-6938106/v1/41306d43fbca5ab76133fe09.docx"},{"id":87732984,"identity":"6abae2b6-44f4-4cb2-bda1-6883eaec9f1b","added_by":"auto","created_at":"2025-07-28 11:53:50","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":235468,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials4.docx","url":"https://assets-eu.researchsquare.com/files/rs-6938106/v1/618a52a996c9aaefc412f5bb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Deciphering developmental dysgraphia: evidence of a verbal advantage","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAlthough complete mastery of handwriting takes several years, most children are able to produce letters and words accurately after a few months of practice. Learning how to write involves a complex interplay of processes, from planning ideas to manual motor control [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. For instance, executive functions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]; fine motor skills [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], proprioception [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], visuospatial integration [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and orthographic processes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e][\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] are considered crucial contributors to handwriting acquisition.\u003c/p\u003e\u003cp\u003eBetween 6% and 33% of children experience persistent difficulties in developing their writing skills, a condition known as developmental dysgraphia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e][\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e][\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e][\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Although developmental dysgraphia is not classified as a specific learning disorder, dysgraphic children (DG) face significant challenges at the educational level and in daily activities requiring handwriting, and their self-esteem can be deteriorated [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDevelopmental dysgraphia has been attributed to various underlying causes, including motor coordination deficits linked to visuo-constructive or proprioceptive disorders (peripheral dysgraphia; [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]), visuo-perceptual deficits (spatial dysgraphia; [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]), working memory deficits affecting orthographic encoding (linguistic dysgraphia; [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]), or inaccurate orthographic representations [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In this study, we focus on so-called \u0026ldquo;graphomotor\u0026rdquo; aspects of handwriting. We consider developmental dysgraphia as a persistent difficulty in acquiring the handwriting gesture despite adequate learning opportunities and sufficient intellectual potential, without presupposing any specific underlying deficit [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e][\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e][\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAt a graphomotor level, developmental dysgraphia is characterized by a significant impairment in writing quality (e.g., unevenness or irregularity of letters, control of the graphic space, and overall legibility) and/or writing speed, which is markedly below what is expected based on the child's chronological age, intellectual level, general psychomotor development, and age-appropriate education [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e][\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e][\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e][\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eDevelopmental dysgraphia often occurs alongside one or more neurodevelopmental disorders (NDD; [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e])like attention deficit hyperactivity disorder (ADHD; [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e][\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e][\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e][\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e][\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e][\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e][\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e][\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]), developmental coordination disorder (DCD; [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e][\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]) or reading disorders (DL; [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e][\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e][\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]). Thus, the coexistence of these neurodevelopmental disorders must be taken into accound in order to fully understanding developmental dysgraphia.\u003c/p\u003e\u003cp\u003eRecent literature emphasizes the need to adopt a more comprehensive view of the cognitive profiles of NDD, as well as the importance of considering comorbidities [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e][\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e][\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Here, we analyzed the DGs\u0026rsquo; cognitive profiles through the lens of the \u0026ldquo;pattern of strengths and weaknesses\u0026rdquo; approach. This framework, developed by Compton et al. (2012)[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], was designed for application to Specific Language and Learning Disabilities and later applied to other disorders [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e][\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e][\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e][\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e][\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e][\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e][\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] Our objective was to map the deficits and/or strengths of DG in various cognitive domains, by comparing these children to typically developing children and to NDD. To this end, we analyzed data from the WISC-V test administered to children in the \u0026ldquo;R\u0026eacute;sodys\u0026rdquo; cohort. Resodys is a specialized care system in southern France that provides second-tier intervention for individuals with persistent NDD after an initial unsuccessful attempt. Children in the cohort undergo systematic assessments across cognitive and praxis domains, revealing frequent co-occurring impairments in language, attention, executive functions, and motor coordination.\u003c/p\u003e\u003cp\u003eAssessment of writing skills of 366 children with one or more diagnoses (ICD-10 criteria) taken from the cohort revealed dysgraphia in 248 cases. We first compared the cognitive profiles of DG to the WISC-V normative population to determine their specific strengths and weaknesses. Next, we conducted the same analyses to isolate the cognitive specificities of DG in comparison to children with other NDDs (DL, DCD, ADHD). Finally, we examined, from both quantitative and qualitative perspectives, the interactions between different disorders and the previously identified cognitive specificities of DG.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003eThe R\u0026eacute;sodys Cohort\u003c/p\u003e\n\u003cp\u003eIn France, specific language and learning disorders are primarily managed in private practice, with social security covering only language disorders. As a result, families must finance neuropsychological assessments, psychomotor, and occupational therapies. To fill this gap, the state-funded Resodys regional health network provides free access to paramedical professionals and a coordinating physician, facilitating the diagnosis of NDDs.\u003c/p\u003e\n\u003cp\u003eBetween 2020 and 2022, the Resodys healthcare network supported 1,514 children. These interventions align with the Level 2 guidelines outlined in the French National Health Authority (HAS) care pathway guide for children with specific learning disorders [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThis study included children with WISC-V neuropsychological assessments and praxic/writing evaluations. Exclusion criteria were neurological conditions (e.g., head trauma, epileptic syndrome), psychiatric disorders (e.g., non-autistic pervasive developmental disorder), intellectual disability (full-scale WISC-V score\u0026thinsp;\u0026lt;\u0026thinsp;80), and non-school enrollment. (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). All children in the sample spoke French as either their native or second language.\u003c/p\u003e\n\u003cp\u003eThe final sample consisted of 366 children (253 boys and 113 girls) with an average age of 9 years and 7 months (SD\u0026thinsp;=\u0026thinsp;2 years and 3 months) at the time of the neuropsychological assessment.\u003c/p\u003e\n\u003cp\u003eAll methods were carried out in accordance with relevant guidelines and regulations. The data were processed in accordance with the \u003cem\u003eMR04 reference methodology\u003c/em\u003e provided by the French Commission Nationale de l'Informatique et des Libert\u0026eacute;s (CNIL) for the processing of retrospective personal data. Procedures and methods were approved by the data protection office of the french national center for scientific research under the registration number 2024-UMR7077-10. Only data that was strictly necessary and relevant to the research objectives was included in the database and used. Informed consent was obtained from a parent or a legal guardian for study participation.\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to the protection of personal health data implied by the application of the MR04 methodology but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eDiagnoses\u003c/p\u003e\n\u003cp\u003eClinical evaluations were conducted by specialized health professionals. Given that dysgraphia does not yet fall under a specific diagnostic category, the presence of developmental dysgraphia was assessed through a systematic review of case files.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eDiagnosis of Dysgraphia\u003c/h2\u003e\n\u003cp\u003eTo categorize a child as DG, we systematically reviewed all writing-related elements in their case file. In most files included in the sample, handwriting was assessed using the French adaptation of the BHK Test for the rapid assessment of handwriting for children [\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e] or for adolescents (BHK-Ado,[\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e]). Two key measures were used based on the 5-minutes text copying task: the overall degradation qualitative score and the number of words written. These scores were converted into deviation scores based on age-standardized norms and expressed as standard deviations.\u003c/p\u003e\n\u003cp\u003eTo identify deficits in writing quality and/or speed [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e], we calculated the absolute difference between the two standardized scores (degradation \u0026ndash; speed) and applied a threshold of 2 standard deviations, in line with established practice. This criterion was systematically crossed with :\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eA concern about writing speed and legibility, expressed by teachers, parents, and/or the child\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eComplaints regarding pain or difficulty, as expressed by children during consultations with healthcare professionals or assessed through the French adaptation of the Children\u0026rsquo;s Questionnaire for Handwriting Proficiency (CHaP) [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eIn the absence of a BHK assessment (30 files), we relied on the observations made by the medical coordinator.\u003c/p\u003e\n\u003cp\u003eOne file was excluded from the DG group due to an uncorrected visual impairment affecting fixation and eye tracking at the time of the handwriting assessment.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eDiagnoses of NDD\u003c/h3\u003e\n\u003cp\u003eNDD diagnoses were established by the network\u0026rsquo;s head physician based on ICD-10 criteria. Children were categorized as having dyslexia (DL) or not (noDL), having developmental coordination disorder (DCD) or not (noDCD), and having attention deficit hyperactivity disorder (ADHD) or not (noADHD). Additional diagnoses, including oral language disorder, dysorthographia, dyscalculia, and autism spectrum disorder, were recorded but not considered in this study.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" style=\"width: 1003px;\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCharacteristics of the sample: size, girl/boy ratio, average ages (in years and months), social position index of the family (SPI family) and social position index of the school (SPI school) of the sample according to diagnoses DG, DL, TDC, ADHD.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003ediagnoses\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 84px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eTotal headcount\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 30px;\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth style=\"width: 66.1597px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eratio girl/boy\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 478.752px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eage (mean +/- standard deviation in year)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eSPI family\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 107.65px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eSPI school\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 120.162px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eTotal sample\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e366\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\n\u003cp\u003e23/50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 31px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 478.752px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e9,6+-2,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e104+-30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 107.65px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e108+-15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 120.162px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDG / noDG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e248\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e118\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e8/23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e19/25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 139px;\" align=\"left\"\u003e\n\u003cp\u003e9,4 +-2,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 299.317px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e9,11+-2,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e105+-30 / 103+-30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 197.812px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e108+-15 / 108+-13\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDL / noDL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e225\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e141\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e23/52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e12/25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 139px;\" align=\"left\"\u003e\n\u003cp\u003e9,8+-2,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 299.317px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e9,3+-2,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e105+-29 / 103+-31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 197.812px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e107+-15 / 109+-14\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDCD/noDCD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e164\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e202\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e21/50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e33/68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 139px;\" align=\"left\"\u003e\n\u003cp\u003e9,6+-2,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 299.317px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e9,7+-2,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e102+-29 / 106+-30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 197.812px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e108+-15 / 108+-16\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eADHD/noADHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e223\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e143\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e2/5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e4/7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 139px;\" align=\"left\"\u003e\n\u003cp\u003e9,3+-2,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 299.317px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e10,2+-2,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e104+-30 / 105+-29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 197.812px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e108+-15 / 107+-15\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDG\u0026thinsp;+\u0026thinsp;DL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e148\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\n\u003cp\u003e3/10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 442.317px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e9,6+-2,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e107+-29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 133.764px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e108+-16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 84.0486px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDG\u0026thinsp;+\u0026thinsp;DCD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e131\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\n\u003cp\u003e2/5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 442.317px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e9,6+-2,1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e100+-29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 133.764px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e107+-16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 84.0486px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDG\u0026thinsp;+\u0026thinsp;ADHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e156\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\n\u003cp\u003e1/4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 442.317px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e9,3+-2,1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e106+-29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 133.764px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e107+-15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 84.0486px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDG\u0026thinsp;+\u0026thinsp;DL\u0026thinsp;+\u0026thinsp;DCD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\n\u003cp\u003e8/25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 442.317px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e9,7+-2,1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e105+-29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 133.764px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e107+-17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 84.0486px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDG\u0026thinsp;+\u0026thinsp;DL\u0026thinsp;+\u0026thinsp;ADHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\n\u003cp\u003e3/10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 442.317px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e9,5+-2,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e110+-28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 133.764px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e107+-16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 84.0486px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDG\u0026thinsp;+\u0026thinsp;DCD\u0026thinsp;+\u0026thinsp;ADHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\n\u003cp\u003e9/25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 442.317px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e9,4+-2,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e103+-30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 133.764px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e106+-15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 84.0486px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 122px;\" align=\"left\"\u003e\n\u003cp\u003eDG\u0026thinsp;+\u0026thinsp;DL\u0026thinsp;+\u0026thinsp;DCD\u0026thinsp;+\u0026thinsp;ADHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\n\u003cp\u003e47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 28px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 33.1597px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 32px;\" align=\"left\"\u003e\n\u003cp\u003e1/4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77.4352px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 442.317px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e9,9+-2,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 219.85px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e109+-28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 133.764px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e108+-17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 84.0486px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFinal composition of the sample:\u003c/p\u003e\n\u003cp\u003eOf the 366 children in the sample, 248 were diagnosed DG, 225 DL, 164 DCD and 223 ADHD. The social position index (SPI) of the family and the school attended by each child was included as a control variable, and no significant differences between groups (at \u0026alpha;\u0026thinsp;=\u0026thinsp;.1) were observed in the comparisons across the diagnostic categories (DG/noDG, DL/noDL, DCD/noDCD, ADHD/noADHD) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAssessment of Cognitive Abilities:\u003c/p\u003e\n\u003cp\u003eAll children completed the French adaptation of the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V) [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e], with age-adjusted scores. The WISC-V is a widely used intelligence test for children aged 6\u0026ndash;16 years, normed on a French reference sample of 1,100 children to reflect IQ distribution in the general population. It includes ten primary and\u003c/p\u003e\n\u003cp\u003efive secondary subtests, enabling the calculation of five primary and five supplementary index scores (for details see supplementary materials 1). Raw scores from subtests are converted to standard scores with a mean of 10 (SD\u0026thinsp;=\u0026thinsp;3). The indexes are normally distributed with a mean of 100 (SD\u0026thinsp;=\u0026thinsp;15). This study focused on the standard scores for the ten primary subtests and five primary indexes.\u003c/p\u003e\n\u003cp\u003eThe Full-Scale IQ (FSIQ), derived from SIM, VOC, BD, DS, MAT, FW, and COD subtests, represents general cognitive efficiency but provides limited insight into specific skills. Therefore, it was excluded from this analysis.\u003c/p\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003eData Analysis\u003c/h2\u003e\n\u003cp\u003eSoftware\u003c/p\u003e\n\u003cp\u003eRStudio version 2024.04.2+ [\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e] and JASP version 0.19.1[\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e] were used for statistical analysis. The data were processed using the BioStatR [\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e], Bolstad [\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e], stats [\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e], lawstat [\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e], pastecs [\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e], forecast [\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e], and Matrix [\u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e] packages.\u003c/p\u003e\n\u003cp\u003ePreprocessing and Statistical Comparisons\u003c/p\u003e\n\u003cp\u003eQualitative variables indexing the presence of the neurodevelopmental disorders (NDD) of interest (DG, DL, DCD, ADHD) were coded into binary code (1: presence of the disorder / 0: absence of the disorder).\u003c/p\u003e\n\u003cp\u003eFor each child, the standard scores of WISC-V subtests, indexes, and IQ scores (FSIQ) were extracted. The normality of the FSIQ was verified by observing the quantile-quantile graph. There was no evidence that the FSIQ exhibited any skewness or kurtosis different from the normal distribution according to the Jarque-Bera normality test [\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSTEP 1: Comparison of indexes and subtest distributions between DG and the reference population (REF)\u003c/h3\u003e\n\u003cp\u003eDistributions of DG and REF indexes and subtests scores were compared using the WISC-V manual tables (A2\u0026ndash;A7, B2, B4, B6), and differences in group dispersion were assessed via \u0026chi;\u0026sup2; tests of homogeneity and/or Kolmogorov tests.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eSTEP 2: Effect of the presence of DG on the subtests scores\u003c/h2\u003e\n\u003cp\u003eThe means of the WISC-V subtests of the DG and noDG groups were compared using inferential and Bayesian Student t-tests. The Bayes Factor (BF) quantifies the strength of the evidence for a standardized mean difference between the two groups. The strength of the evidence was qualified according to Jeffrey's (1961) [\u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e] scale: not very important for 1\u0026thinsp;\u0026lt;\u0026thinsp;BF\u0026thinsp;\u0026lt;\u0026thinsp;3; substantial for 3\u0026thinsp;\u0026lt;\u0026thinsp;BF\u0026thinsp;\u0026lt;\u0026thinsp;10, strong for 10\u0026thinsp;\u0026lt;\u0026thinsp;BF\u0026thinsp;\u0026lt;\u0026thinsp;30, very strong for 30\u0026thinsp;\u0026lt;\u0026thinsp;BF\u0026thinsp;\u0026lt;\u0026thinsp;100 and decisive for BF\u0026thinsp;\u0026gt;\u0026thinsp;100.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSTEP 3: Effect of the presence of other disorders (DL, DCD and ADHD) on the subtests scores\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe means of the WISC-V subtests of the various pairs of subsamples (DL/noDL; DCD/noDCD; ADHD/noADHD) were compared using inferential and Bayesian Student's t-tests. This comparison was limited to the scores showing significant difference between DG /no DG and a BF\u0026thinsp;\u0026gt;\u0026thinsp;3 in STEP 2.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSTEP 4: Interaction effects of the presence of disorders\u003c/h3\u003e\n\u003cp\u003eThe final step aimed to assess the combined effects of the four disorders on the subtests which were found to be specific to the DG/noDG comparison in the previous steps. We conducted a Generalized Linear Model (GLM), followed by a factorial ANOVA including interactions and post-hoc tests. Data normality and homoscedasticity (assessed via Levene\u0026rsquo;s test; [\u003cspan class=\"CitationRef\"\u003e69\u003c/span\u003e][\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e]) satisfy the validity conditions of gaussian family at p\u0026thinsp;=\u0026thinsp;.05 .\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSTEP 1: Comparison of indexes and subtest distributions between DG and the reference population (REF)\u003c/h2\u003e\u003cp\u003eAll the distribution comparisons of the index scores (VCI, VSI, FRI, WMI, PSI) showed significant differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo complete these observations, an analysis of heterogeneity based on the discrepancy between all pairs of subtests comparing to critical values from the WISC-V manual is detailed in supplementary materials 2.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSTEP 2: Effect of the presence of DG on the subtests scores\u003c/h2\u003e\u003cp\u003eFrequentist analyses showed that DG had higher standard scores than noDG on the VCI subtests (SIM and VOC); DG had lower scores than noDG on the PSI subtests (SYM and COD; DG had higher scores than noDG on the FW and PS substests.\u003c/p\u003e\u003cp\u003eNo significant differences were found for the other subtests.\u003c/p\u003e\u003cp\u003eSignificant frequentist analyses (SIM, VOC, FW, PS, COD and SYM subtests) were supplemented by Bayesian analyses. The comparison yielded decisive evidence for the SIM and VOC subtests (BF\u003csub\u003eSIM\u003c/sub\u003e=10\u003csup\u003e12\u003c/sup\u003e \u0026gt;100; BF\u003csub\u003eVOC\u003c/sub\u003e=10\u003csup\u003e5\u003c/sup\u003e \u0026gt;100), very strong evidence for the COD subtest (30\u0026thinsp;\u0026lt;\u0026thinsp;BF\u003csub\u003eCOD\u003c/sub\u003e=44\u0026thinsp;\u0026lt;\u0026thinsp;100) and negligible evidence for the other subtests (BF\u003csub\u003eFW\u003c/sub\u003e= 2\u0026thinsp;\u0026lt;\u0026thinsp;3; BF\u003csub\u003ePS\u003c/sub\u003e=2\u0026thinsp;\u0026lt;\u0026thinsp;3; BF\u003csub\u003eSYM\u003c/sub\u003e= 1\u0026thinsp;\u0026lt;\u0026thinsp;3).\u003c/p\u003e\u003cp\u003e Taken together, frequentist results and Bayesian evidence indicate that DG show a significant advantage in verbal processing (SIM, VOC) and slower processing speed (COD) compared to noDG.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSTEP 3: Effect of the presence of other disorders (DL, DCD and ADHD) on the subtests scores\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo check whether these differences were specific to DG, the same comparisons of means were carried out between the DL/noDL, DCD/noDCD and ADHD/noADHD subgroups. These comparisons were limited to the subsets that differed between DG/noDG (SIM, VOC and COD).\u003c/p\u003e\u003cp\u003eFor the VOC subtest, scores were significatively higher in the ADHD than in the noADHD group (M_ VOC\u003csub\u003eADHD\u003c/sub\u003e =11.0; M_ VOC\u003csub\u003enoADHD\u003c/sub\u003e =9.9; 10\u0026thinsp;\u0026lt;\u0026thinsp;BF\u003csub\u003eVOC_ADHD\u003c/sub\u003e= 28\u0026thinsp;\u0026lt;\u0026thinsp;30); t(364)=-3.4, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). They were lower in the DL than in the noDL group (M_VOC\u003csub\u003eDL\u003c/sub\u003e =10.2; M_VOC\u003csub\u003enoDL\u003c/sub\u003e =11.2; t(364)\u0026thinsp;=\u0026thinsp;3.2, p\u0026thinsp;\u0026lt;\u0026thinsp;.001; 10\u0026thinsp;\u0026lt;\u0026thinsp;BF\u003csub\u003eVOC_DL\u003c/sub\u003e= 17\u0026thinsp;\u0026lt;\u0026thinsp;30). Scores of the DCD and noDCD groups did not significantly differ.\u003c/p\u003e\u003cp\u003eFor the COD subtest, scores were significatively lower in the DCD than in the noDCD group (M_COD\u003csub\u003eDCD\u003c/sub\u003e =7.5 ; M_COD\u003csub\u003enoDCD\u003c/sub\u003e =9.0); t(364)\u0026thinsp;=\u0026thinsp;5.1, p\u0026thinsp;\u0026lt;\u0026thinsp;.001; BF\u003csub\u003eCOD_DCD\u003c/sub\u003e= 10\u003csup\u003e4\u003c/sup\u003e\u0026gt;100)\u003c/p\u003e\u003cp\u003eFor the SIM subtest scores were significatively lower in the DL than in the noDL group (M_SIM\u003csub\u003eDL\u003c/sub\u003e =10.4; M_SIM\u003csub\u003enoDL\u003c/sub\u003e =11.3; t(364)\u0026thinsp;=\u0026thinsp;3.0, p\u0026thinsp;\u0026lt;\u0026thinsp;.01; 10\u0026thinsp;\u0026lt;\u0026thinsp;BF\u003csub\u003eVOC\u0026minus;DL\u003c/sub\u003e= 17\u0026thinsp;\u0026lt;\u0026thinsp;30).\u003c/p\u003e\u003cp\u003e These results show a specific verbal advantage on the SIM subtest only for DG group.\u003c/p\u003e\u003cp\u003eAll results of steps 2 and 3 are detailed in supplementary materials 3\u003c/p\u003e\u003cp\u003eSTEP 4: Interaction effects of the presence of disorders\u003c/p\u003e\u003cp\u003eThe previous analyses showed that higher scores on the SIM subtest are a unique feature of DG. Step 4 was thus focused on the SIM scores.\u003c/p\u003e\u003cp\u003eThe generalized linear model (GLM) confirmed a significant overall effect of neurodevelopmental disorders (NDDs) on SIM scores: DG was associated with significantly higher SIM scores; DL and DCD were associated with significantly lower SIM scores; ADHD did not significantly affect SIM scores (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Specifically, the effect of the presence of DG on SIM subtest performance is estimated to be 2.9 points higher than that of DL, and 2.4 points higher than that of DCD.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eMoreover, the factorial ANOVA (DL * DG * TDC * TA) revealed a significant simple interaction effect of DG*DCD (F(1,350)\u0026thinsp;=\u0026thinsp;0.043; p\u0026thinsp;\u0026lt;\u0026thinsp;.001; η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.02). Post hoc tests following the ANOVA indicated significant pairwise differences for the DG*DCD interaction, with the exception of the noDCD\u0026thinsp;+\u0026thinsp;noDG / DCD\u0026thinsp;+\u0026thinsp;noDG contrast (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eThe mean scores for the SIM subtest of all groups are presented in supplementary material 4.\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe aim of this study was to uncover the mechanisms underlying developmental dysgraphia by mapping of the cognitive strengths and weaknesses of DG children. Developmental dysgraphia was operationally defined as a difficulty in graphic movements without any presupposition as to the origin of the disorder. Given the high comorbidity rate, we considered dysgraphia together with associated disorders, without attempting to isolate it [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e][\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e][\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe main finding was an advantage of DG over noDG in the cohort specifically on the SIM subtest. In parallel, DG displayed a deficit in processing speed mainly reflected in the COD subtest. This pattern was not found when the children were categorized according to the presence of DL, DCD or ADHD. Conversely, DL was associated to verbal deficits and no impairment in COD, DCD was associated to a more marked deficit in COD and no verbal advantage, and ADHD was associated to a verbal advantage only on the VOC subtest with no advantage on SIM or deficit in COD. Of note, the verbal advantage was also found when DG were compared with the reference population, while the scores of DG to most non-verbal subtests were inferior to those of the general population. In sum, DG showed a specific dissociation between verbal and non-verbal skills, with good verbal conceptualization along with standard or poor nonverbal skills. Compared to the other children of the cohort, they were not more impaired in any of the subtests except COD. Our finding of a pattern of high proficiency in one domain along with deficits in another domain in DG is consistent with recent accounts of NDD that attempt to move beyond deficit-based approaches [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e The exceptional verbal abilities of DG were found for both the SIM and VOC subtests, but the SIM subtest was the only one to specifically characterize DG. Conversely, other disorders were associated with decreased performance. Beyond the main effect of DG on SIM scores, a single specific interaction between DG and DCD was identified. This clearly indicates that the additional presence of extra disorders to DG does not eliminate this verbal advantage. While the verbal advantage is reduced when DG is associated with DCD, it remains present. Conversely, DCD but without DG display degraded verbal scores. The cognitive profile of DG whether or not comorbid with DCD, differ from that of DCD alone.\u003c/p\u003e\u003cp\u003e How can this verbal advantage of DG be interpreted? A first possible explanation is that it results from a recruitment bias. For instance, the use of a second-tier facility could be linked to a better family socio-economic level, which favours performance on certain WISC subtests [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. The free care provided by the facility disqualifies this interpretation and there does not seem to be any valid reason why this advantage in verbal reasoning should concern only DG to the exclusion of all other forms of NDD. Besides, the index of social position did not differ between the families of DG compared to noDG.\u003c/p\u003e\u003cp\u003eAn alternative explanation is that DG weaker non-verbal processing may result from their reliance on a preexisting verbal advantage [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. This disinvestment in writing could stem from a lack of practice [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e][\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]; however, this seems unlikely given their prior pedagogical remediation. Another possibility is that their academic environment is less demanding, yet no significant school-related differences were found between DG and noDG.\u003c/p\u003e\u003cp\u003e Another possible explanation could be an over-investment of the DG in the verbal domain, to compensate a weakness in other cognitive domains, especially in processing speed. Recent accounts of neurodevelopmental disorders emphasize altered connectivity patterns leading to an imbalance in the neural systems supporting cognitive functions that could generate dissociations between severely impaired functions and paradoxically high performance in other domains [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. The alterations in one network could also lead to resource allocation to a distinct compensatory network, which could explain specific cognitive profiles with extremely high-functionning domains associated to massive impairments in other domains. Although it cannot be formally refuted, this hypothesis is not fully supported by our results. Accordingly, one would expect that DCD would exhibit an even greater compensatory effect. However, contrary to this expectation, our findings suggest that DCD is not linked to improved verbal performance.\u003c/p\u003e\u003cp\u003e On the other hand, there are compelling arguments for an early developmental origin of the dissociation between verbal and other cognitive skills in DG. For example, it may have a genetic or a fetal neurodevelopmental origin, as observed in autism spectrum disorder [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e][\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e], Williams syndrome [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e] and childhood early epilepsy [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. The verbal advantage in DG might be related to an imbalance between the early development of verbal and nonverbal brain substrates. Earlier maturation of the right hemisphere could increase the vulnerability of nonverbal networks while promoting verbal development. Neuroimaging studies [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e][\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e] suggest that verbal/nonverbal discrepancies correlate with cortical thickness and connectivity in frontal regions, particularly the inferior frontal gyri. These areas, crucial for executive functions like conflict monitoring, inhibitory control, and working memory [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e][\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e][\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e], also play a key role in handwriting development [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. Dysfunction in this system has been observed in dyslexic children with handwriting difficulties [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and atypical connectivity in executive and sensory-motor networks during handwriting tasks has been reported [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Altogether, this body of literature points towards a common neurodevelopmental origin of unusually high verbal skills and deficient motor control of handwriting occurring through atypical functioning of brain networks supporting executive control in DG. Further structural and functional imaging studies are needed to confirm this interpretation.\u003c/p\u003e\u003cp\u003eOur study only focused on the different domains of the subtest of the WISC-V. Several perceptual, motor and executive functions were not explored which should be done in future studies to explore more precisely the impact of executive functions in developmental dysgraphia.\u003c/p\u003e\u003cp\u003eFinaly, the processing speed deficit in DG, despite unaffected reasoning and working memory, should be interpreted cautiously, as processing speed tests require graphical responses that may disadvantage DG. Future research should use alternative tests without graphical responses to better assess processing speed in DG. If a bias is confirmed, the validity of the WISC processing speed index and similar cognitive tests requiring graphic responses for children with writing difficulties may need reconsideration.\u003c/p\u003e\u003cp\u003eThis study is the first to examine the cognitive performance of DG, as assessed by the WISC-V, within a cohort of children with neurodevelopmental disorders. A key contribution of this research is the identification of a robust and specific verbal advantage in DG, in addition to a processing speed deficit. This distinctive pattern sets apart these children both from their typically developing peers and from children with other disorders. Our findings thus suggest a potential specificity of DG among NDD.\u003c/p\u003e\u003cp\u003eThese findings are particularly important, as difficulties in automating writing can lead to slow and illegible output, significantly increasing the risk of poor academic performance and low self-esteem [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e], and impacting the teachers' evaluations [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e][\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. Thus, gaining a deeper understanding of writing difficulties and their developmental origins is essential for supporting these children and enhancing their academic success. This study paves the way for clinical interventions that leverage the identified verbal strengths to develop targeted remediation strategies for DG.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003e\"All authors wrote the main manuscript text and A.J-F prepared figures. All authors reviewed the manuscript.\"\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data were processed in accordance with the MR04 reference methodology provided by the French Commission Nationale de l'Informatique et des Libert\u0026eacute;s (CNIL) for the processing of retrospective personal data. Procedures and methods were approved by the data protection office of the french national center for scientific research under the registration number 2024-UMR7077-10. Only data that was strictly necessary and relevant to the research objectives was included in the database and used. Informed consent was obtained from a parent or a legal guardian for study participation. The datasets generated and/or analysed during the current study are not publicly available due to the protection of personal health data implied by the application of the MR04 methodology but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGeertsen, S. S. et al. Motor Skills and Exercise Capacity Are Associated with Objective Measures of Cognitive Functions and Academic Performance in Preadolescent Children. \u003cem\u003ePLOS ONE\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (8), e0161960 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLopez, C. \u0026amp; Vaivre-Douret, L. Les grandes fonctions c\u0026eacute;r\u0026eacute;brales en jeu dans le d\u0026eacute;veloppement graphomoteur typique et pathologique de l\u0026rsquo;\u0026eacute;criture manuscrite. \u003cem\u003eRev. Neuropsychol.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e (4), 255\u0026ndash;277 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlamargot, D., Lambert, E. \u0026amp; Chanquoy, L. La production \u0026eacute;crite et ses relations avec la m\u0026eacute;moire. \u003cem\u003eApproche Neuropsychol. Apprentiss Chez Enfant\u003c/em\u003e ; (2005). (81).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerninger, V., Abbott, R., Cook, C. R. \u0026amp; Nagy, W. Relationships of Attention and Executive Functions to Oral Language, Reading, and Writing Skills and Systems in Middle Childhood and Early Adolescence. \u003cem\u003eJ. Learn. Disabil.\u003c/em\u003e \u003cb\u003e50\u003c/b\u003e (4), 434\u0026ndash;449 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePalmis, S. et al. The handwriting brain in middle childhood. \u003cem\u003eDev. Sci.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e (2), e13046 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchneck, C. M. Comparison of Pencil-Grip Patterns in First Graders With Good and Poor Writing Skills. \u003cem\u003eAm. J. Occup. Ther.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e (8), 701\u0026ndash;706 (1991).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCornhill, H. \u0026amp; Case-Smith, J. Factors that relate to good and poor handwriting. \u003cem\u003eAm. J. Occup. Ther. Off Publ Am. Occup. Ther. Assoc.\u003c/em\u003e \u003cb\u003e50\u003c/b\u003e (9), 732\u0026ndash;739 (1996).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHong, S. Y., Jung, N. H. \u0026amp; Kim, K. M. The correlation between proprioception and handwriting legibility in children. \u003cem\u003eJ. Phys. Ther. Sci.\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e (10), 2849\u0026ndash;2851 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMalloy-Miller, T., Polatajko, H. \u0026amp; Anstett, B. Handwriting Error Patterns of Children with Mild Motor Difficulties. \u003cem\u003eCan. J. Occup. Ther.\u003c/em\u003e \u003cb\u003e62\u003c/b\u003e (5), 258\u0026ndash;267 (1995).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBourdin, B. \u0026amp; Fayol, M. Even in adults, written production is still more costly than oral production. \u003cem\u003eInt. J. Psychol.\u003c/em\u003e \u003cb\u003e37\u003c/b\u003e (4), 219\u0026ndash;227 (2002).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKandel, S. \u0026amp; Perret, C. How does the interaction between spelling and motor processes build up during writing acquisition? \u003cem\u003eCognition\u003c/em\u003e \u003cb\u003e136\u003c/b\u003e, 325\u0026ndash;336 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaurer, M., Truxius, L., S\u0026auml;gesser Wyss, J. \u0026amp; Eckhart, M. From Scribbles to Script: Graphomotor Skills\u0026rsquo; Impact on Spelling in Early Primary School. \u003cem\u003eChildren\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e, 1886 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNottbusch, G., Weingarten, R. \u0026amp; Sahel, S. From written word to written sentence production. Writ Cogn Res Appl [Internet]. [cited 2021 Apr 14]; (2007). Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pub.uni-bielefeld.de/record/1897903\u003c/span\u003e\u003cspan address=\"https://pub.uni-bielefeld.de/record/1897903\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChung, P. J., Patel, D. R. \u0026amp; Nizami, I. Disorder of written expression and dysgraphia: definition, diagnosis, and management. \u003cem\u003eTransl Pediatr.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e (S1), S46\u0026ndash;54 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eD\u0026ouml;hla, D., Willmes, K. \u0026amp; Heim, S. Cognitive Profiles of Developmental Dysgraphia. \u003cem\u003eFront. Psychol.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, 2006 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHamstra-Bletz, L. \u0026amp; Bl\u0026ouml;te, A. W. A longitudinal study on dysgraphic handwriting in primary school. \u003cem\u003eJ. Learn. Disabil.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e (10), 689\u0026ndash;699 (1993).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOvervelde, A. \u0026amp; Hulstijn, W. Handwriting development in grade 2 and grade 3 primary school children with normal, at risk, or dysgraphic characteristics. \u003cem\u003eRes. Dev. Disabil.\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e (2), 540\u0026ndash;548 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003edel Castillo, M. C., Maldonado Belmonte, M. J., Ruiz-Falc\u0026oacute; Rojas, M. L., L\u0026oacute;pez Pino, M. A. \u0026amp; Bernabeu Verd\u0026uacute;, J. Fournier, Su\u0026aacute;rez Rodr\u0026iacute;guez JM. Cerebellum atrophy and development of a peripheral dysgraphia: a paediatric case. Cerebellum Lond Engl. ;9(4):530\u0026ndash;6. (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDeuel, R. K. Developmental dysgraphia and motor skills disorders. \u003cem\u003eJ. Child. Neurol.\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e (Suppl 1), S6\u0026ndash;8 (1995).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerninger, V. W. Defining and differentiating dysgraphia, dyslexia, and language learning disability within a working memory model. In: Brain, behavior, and learning in language and reading disorders. New York, NY, US: The Guilford Press; 103\u0026ndash;134. (2008). (Challenges in language and literacy).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcCloskey, M. \u0026amp; Rapp, B. Developmental dysgraphia: An overview and framework for research. \u003cem\u003eCogn. Neuropsychol.\u003c/em\u003e \u003cb\u003e34\u003c/b\u003e (3\u0026ndash;4), 65\u0026ndash;82 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLopez, C. \u0026amp; Vaivre-Douret, L. Exploratory Investigation of Handwriting Disorders in School-Aged Children from First to Fifth Grade. \u003cem\u003eChildren\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e (9), 1512 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRichards, R. G. The Writing Dilemma: Understanding Dysgraphia [Internet]. Richards Educational Therapy Center, inc; 1998 [cited 2025 Jan 24]. 86 p. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://archive.org/details/writingdilemmaun0000regi\u003c/span\u003e\u003cspan address=\"http://archive.org/details/writingdilemmaun0000regi\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAsselborn, T. et al. Automated human-level diagnosis of dysgraphia using a consumer tablet. \u003cem\u003eNpj Digit. Med.\u003c/em\u003e \u003cb\u003e1\u003c/b\u003e (1), 1\u0026ndash;9 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePaz-Villagr\u0026aacute;n, V., Danna, J. \u0026amp; Velay, J. L. Lifts and stops in proficient and dysgraphic handwriting. \u003cem\u003eHum. Mov. Sci.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e, 381\u0026ndash;394 (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRosenblum, S., Weiss, P. \u0026amp; Parush, S. Product and Process Evaluation of Handwriting Difficulties. \u003cem\u003eEduc. Psychol. Rev.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e, 41\u0026ndash;81 (2003).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJover, M. \u0026amp; Huau, A. A Dimensional Approach to Comorbidity Between Developmental Coordination Disorder and Dyslexia: A Study of Graphomotor Abilities. \u003cem\u003eANAE Approche Neuropsychol. Apprentiss Chez Enfant\u003c/em\u003e. \u003cb\u003e175\u003c/b\u003e (33), 673\u0026ndash;688 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdi-Japha, E. et al. ADHD and Dysgraphia: Underlying Mechanisms. Cortex. ;43(6):700\u0026ndash;9. (2007).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrossard-Racine, M. et al. Persistent Handwriting Difficulties in Children With ADHD After Treatment With Stimulant Medication. \u003cem\u003eJ. Atten. Disord\u003c/em\u003e. \u003cb\u003e19\u003c/b\u003e (7), 620\u0026ndash;629 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCapodieci, A., Lachina, S. \u0026amp; Cornoldi, C. Handwriting difficulties in children with attention deficit hyperactivity disorder (ADHD). \u003cem\u003eRes. Dev. Disabil.\u003c/em\u003e \u003cb\u003e74\u003c/b\u003e, 41\u0026ndash;49 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDuPaul, G. J., Gormley, M. J. \u0026amp; Laracy, S. D. Comorbidity of LD and ADHD: Implications of DSM-5 for Assessment and Treatment. \u003cem\u003eJ. Learn. Disabil.\u003c/em\u003e \u003cb\u003e46\u003c/b\u003e (1), 43\u0026ndash;51 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLaniel, P., Faci, N., Plamondon, R., Beauchamp, M. H. \u0026amp; Gauthier, B. Kinematic analysis of fast pen strokes in children with ADHD. \u003cem\u003eAppl. Neuropsychol. Child.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e (2), 125\u0026ndash;140 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRacine, M. B., Majnemer, A., Shevell, M. \u0026amp; Snider, L. Handwriting performance in children with attention deficit hyperactivity disorder (ADHD). \u003cem\u003eJ. Child. Neurol.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (4), 399\u0026ndash;406 (2008).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchoemaker, M. M., Ketelaars, C. E. J., van Zonneveld, M., Minderaa, R. B. \u0026amp; Mulder, T. Deficits in motor control processes involved in production of graphic movements of children with attention-deficit-hyperactivity disorder. \u003cem\u003eDev. Med. Child. Neurol.\u003c/em\u003e \u003cb\u003e47\u003c/b\u003e (6), 390\u0026ndash;395 (2005).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTucha, O. \u0026amp; Lange, K. Handwriting and Attention in Children and Adults with Attention Deficit Hyperactivity Disorder. \u003cem\u003eJ. Psychophysiol.\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e, 216\u0026ndash;216 (2004).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLopez, C., Hemimou, C., Golse, B. \u0026amp; Vaivre-Douret, L. Developmental dysgraphia is often associated with minor neurological dysfunction in children with developmental coordination disorder (DCD). \u003cem\u003eNeurophysiol. Clin.\u003c/em\u003e \u003cb\u003e48\u003c/b\u003e (4), 207\u0026ndash;217 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNicolson, R. I. \u0026amp; Fawcett, A. J. Dyslexia, dysgraphia, procedural learning and the cerebellum. \u003cem\u003eCortex\u003c/em\u003e \u003cb\u003e47\u003c/b\u003e (1), 117\u0026ndash;127 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGosse, C., Dricot, L. \u0026amp; Van Reybroeck, M. Evidence of graphomotor dysfunction in children with dyslexia: A combined behavioural and fMRI experiment. \u003cem\u003eCortex\u003c/em\u003e \u003cb\u003e148\u003c/b\u003e, 68\u0026ndash;88 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJolly, C., Jover, M. \u0026amp; Danna, J. Dysgraphia Differs Between Children with Developmental Coordination Disorder and/or Reading Disorder. \u003cem\u003eJ. Learn. Disabil.\u003c/em\u003e \u003cb\u003e57\u003c/b\u003e (6), 397\u0026ndash;410 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang, Y. et al. The brain basis of handwriting deficits in Chinese children with developmental dyslexia. \u003cem\u003eDev. Sci.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e (2), e13161 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcGrath, L. M., Peterson, R. L. \u0026amp; Pennington, B. F. The Multiple Deficit Model: Progress, Problems, and Prospects. \u003cem\u003eSci. Stud. Read. Off J. Soc. Sci. Study Read.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e (1), 7\u0026ndash;13 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoll, K. et al. Interpreting the Comorbidity of Learning Disorders. Front Hum Neurosci [Internet]. 2021 Dec 9 [cited 2025 Jan 7];15. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.frontiersin.org/journals/human-neuroscience/articles/\u003c/span\u003e\u003cspan address=\"https://www.frontiersin.org/journals/human-neuroscience/articles/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnhum.2021.811101/full\u003c/span\u003e\u003cspan address=\"10.3389/fnhum.2021.811101/full\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePennington, B. F. From single to multiple deficit models of developmental disorders. \u003cem\u003eCognition\u003c/em\u003e \u003cb\u003e101\u003c/b\u003e (2), 385\u0026ndash;413 (2006).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCompton, D. L., Fuchs, L. S., Fuchs, D., Lambert, W. \u0026amp; Hamlett, C. The Cognitive and Academic Profiles of Reading and Mathematics Learning Disabilities. \u003cem\u003eJ. Learn. Disabil.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e (1), 79\u0026ndash;95 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAudras-Torrent, L. et al. WISC-V Profiles and Their Correlates in Children with Autism Spectrum Disorder without Intellectual Developmental Disorder: Report from the ELENA Cohort. \u003cem\u003eAutism Res.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (5), 997\u0026ndash;1006 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBecker, A., Daseking, M. \u0026amp; Kerner auch Koerner, J. Cognitive Profiles in the WISC-V of Children with ADHD and Specific Learning Disorders. \u003cem\u003eSustainability\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e (17), 9948 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiofr\u0026egrave;, D., Toffalini, E., Alto\u0026egrave;, G. \u0026amp; Cornoldi, C. Intelligence measures as diagnostic tools for children with specific learning disabilities. \u003cem\u003eIntelligence\u003c/em\u003e \u003cb\u003e61\u003c/b\u003e, 140\u0026ndash;145 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiofr\u0026egrave;, D. \u0026amp; Cornoldi, C. The structure of intelligence in children with specific learning disabilities is different as compared to typically development children. \u003cem\u003eIntelligence\u003c/em\u003e \u003cb\u003e52\u003c/b\u003e, 36\u0026ndash;43 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJoffroy-Frixons, A., Longcamp, M., Velay, J. L. \u0026amp; Habib, M. Avantage cognitif dans une cohorte d\u0026rsquo;enfants dysgraphiques: Analyse pr\u0026eacute;liminaire de la base de donn\u0026eacute;es \u0026laquo;R\u0026eacute;sodys\u0026raquo;. ANAE Approche Neuropsychol Apprentiss Chez Enfant [Internet]. [cited 2025 Jan 27];186. (2023). Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://amu.hal.science/hal-04296001\u003c/span\u003e\u003cspan address=\"https://amu.hal.science/hal-04296001\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOkada, S., Iiri, C., Azumi, Y. \u0026amp; Ohtani, K. Cognitive Profiles of Children With Autism Spectrum Disorder on the Japanese Version of WISC-IV. \u003cem\u003eJpn J. Educ. Psychol.\u003c/em\u003e \u003cb\u003e69\u003c/b\u003e (3), 254\u0026ndash;267 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eToffalini, E., Giofr\u0026egrave;, D. \u0026amp; Cornoldi, C. Strengths and Weaknesses in the Intellectual Profile of Different Subtypes of Specific Learning Disorder: A Study on 1,049 Diagnosed Children. \u003cem\u003eClin. Psychol. Sci.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e (2), 402\u0026ndash;409 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHAS. Guide parcours de sant\u0026eacute;: Comment am\u0026eacute;liorer le parcours de sant\u0026eacute; d\u0026rsquo;un enfant avec troubles sp\u0026eacute;cifiques du langage et des apprentissages ? (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCharles, M., R\u0026eacute;gis, S. \u0026amp; Albaret, J. M. \u003cem\u003eBHK \u0026ndash; Echelle d\u0026rsquo;\u0026eacute;valuation rapide de l\u0026rsquo;\u0026eacute;criture chez l\u0026rsquo;enfant\u003c/em\u003e (ECPA, 2003).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSoppelsa, R. \u0026amp; Albaret, J. M. BHK Ado. ECPA; (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCasteran, L. et al. Identification de deux sous-types de dysgraphies \u0026agrave; partir de l\u0026rsquo;analyse de param\u0026egrave;tres cin\u0026eacute;matiques et statiques de l\u0026rsquo;\u0026eacute;criture d\u0026rsquo;enfants typiques et porteurs d\u0026rsquo;une dysgraphie. \u003cem\u003eApproche Neuropsychol. Apprentiss Chez Enfant\u003c/em\u003e. \u003cb\u003e172\u003c/b\u003e, 337 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarray, V. \u0026Eacute;criture manuelle et dyspraxie/ trouble de l\u0026rsquo;acquisition de la coordination, partie 2: int\u0026eacute;r\u0026ecirc;t \u0026agrave; long terme. \u003cem\u003eD\u0026eacute;veloppements\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e (3), 6\u0026ndash;17 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWechsler, W. I. S. C. V - \u0026Eacute;chelle d\u0026rsquo;intelligence de Wechsler pour enfants et adolescents - [Internet]. 5\u0026egrave;me \u0026eacute;dition. ECPA par Pearson; 2016 [cited 2023 Jun 29]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.pearsonclinical.fr/wisc-v\u003c/span\u003e\u003cspan address=\"https://www.pearsonclinical.fr/wisc-v\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRStudio Team \u0026amp; RStudio Integrated Development Environment for R}, author = {{RStudio Team}}, organization = {RStudio, PBC.}, address = {Boston, MA}, year = {2020}, url = (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e{http://www.rstudio.com/}\u003c/span\u003e\u003cspan address=\"http://{http://www.rstudio.com/}\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, } [Internet]. Boston, MA; Available from: www.rstudio.com.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJASP Team. JASP (Version 0.19.3)[Computer software] [Internet]. (2024). Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://jasp-stats.org/\u003c/span\u003e\u003cspan address=\"https://jasp-stats.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBertrand, F., Maumy-Bertrand, M. \u0026amp; BioStatR Initiation \u0026agrave; La Statistique Avec R [Internet]. 2009 [cited 2024 Dec 9]. p. 4.0.1. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://CRAN.R-project.org/package=BioStatR\u003c/span\u003e\u003cspan address=\"https://CRAN.R-project.org/package=BioStatR\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCurran, J. \u0026amp; Bolstad Functions for Elementary Bayesian Inference [Internet]. 2005 [cited 2024 Dec 9]. p. 0.2.42. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://CRAN.R-project.org/package=Bolstad\u003c/span\u003e\u003cspan address=\"https://CRAN.R-project.org/package=Bolstad\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; (2013). Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.R-project.org/\u003c/span\u003e\u003cspan address=\"http://www.R-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGastwirth, J. L. et al. lawstat: Tools for Biostatistics, Public Policy, and Law [Internet]. 2006 [cited 2024 Dec 9]. p. 3.6. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://CRAN.R-project.org/package=lawstat\u003c/span\u003e\u003cspan address=\"https://CRAN.R-project.org/package=lawstat\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGrosjean, P. \u0026amp; Ibanez, F. pastecs: Package for Analysis of Space-Time Ecological Series [Internet]. 2002 [cited 2024 Dec 9]. p. 1.4.2. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://CRAN.R-project.org/package=pastecs\u003c/span\u003e\u003cspan address=\"https://CRAN.R-project.org/package=pastecs\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHyndman, R. et al. forecast: Forecasting Functions for Time Series and Linear Models [Internet]. 2009 [cited 2024 Dec 9]. p. 8.23.0. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://CRAN.R-project.org/package=forecast\u003c/span\u003e\u003cspan address=\"https://CRAN.R-project.org/package=forecast\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBates, D., Maechler, M., Jagan, M. \u0026amp; Matrix Sparse and Dense Matrix Classes and Methods [Internet]. 2000 [cited 2024 Dec 9]. p. 1.7-1. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://CRAN.R-project.org/package=Matrix\u003c/span\u003e\u003cspan address=\"https://CRAN.R-project.org/package=Matrix\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJarque, C. M. \u0026amp; Bera, A. K. Efficient tests for normality, homoscedasticity and serial independence of regression residuals. \u003cem\u003eEcon. Lett.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e (3), 255\u0026ndash;259 (1980).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJeffreys, H. Theory of probability. 3d ed. Oxford: Clarendon Press; 447 p. (1961).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFox, J. Applied regression analysis and generalized linear models. Third Edition. Los Angeles: SAGE; 791 p. (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFox, J. \u0026amp; Weisberg, S. An R companion to applied regression. Third edition. Los Angeles: SAGE; 577 p. (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSokolowski, H. M. \u0026amp; Levine, B. Common neural substrates of diverse neurodevelopmental disorders. \u003cem\u003eBrain\u003c/em\u003e \u003cb\u003e146\u003c/b\u003e (2), 438\u0026ndash;447 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTakeuchi, H. et al. Childhood socioeconomic status is associated with psychometric intelligence and microstructural brain development. \u003cem\u003eCommun. Biol.\u003c/em\u003e \u003cb\u003e4\u003c/b\u003e (1), 1\u0026ndash;19 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCavalli, E. et al. Vocabulary skills are well developed in university students with dyslexia: Evidence from multiple case studies. \u003cem\u003eRes. Dev. Disabil.\u003c/em\u003e \u003cb\u003e51\u0026ndash;52\u003c/b\u003e, 89\u0026ndash;102 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEstienne, F., De Barelli, T., Huchet, F. \u0026amp; De Barelli, F. \u003cem\u003eDysorthographie et dysgraphie: comprendre, \u0026eacute;valuer, agir plus de 400 exercices. 4e \u0026eacute;d. enti\u0026egrave;rement revue et enrichie\u003c/em\u003e (Elsevier Masson, 2023). (Collection Orthophonie).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJolly, C. \u0026amp; Gentaz, E. \u0026Eacute;valuation des effets d\u0026rsquo;entra\u0026icirc;nements avec tablette tactile destin\u0026eacute;s \u0026agrave; favoriser l\u0026rsquo;\u0026eacute;criture de lettres cursives chez des enfants de Cours Pr\u0026eacute;paratoire. \u003cem\u003eSci. Technol. Inf. Commun. Pour L\u0026Eacute;ducation Form.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e (1), 495\u0026ndash;512 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCharman, T. et al. IQ in children with autism spectrum disorders: data from the Special Needs and Autism Project (SNAP). \u003cem\u003ePsychol. Med.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e (3), 619\u0026ndash;627 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchmitz, N. et al. Neural correlates of executive function in autistic spectrum disorders. \u003cem\u003eBiol. Psychiatry\u003c/em\u003e. \u003cb\u003e59\u003c/b\u003e (1), 7\u0026ndash;16 (2006).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFarran, E. K. et al. Cross-sectional and longitudinal assessment of cognitive development in Williams syndrome. \u003cem\u003eDev. Sci.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e (1), e13421 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Iterson, L., de Jong, P. F. \u0026amp; Zijlstra, B. J. Pediatric epilepsy and comorbid reading disorders, math disorders, or autism spectrum disorders: impact of epilepsy on cognitive patterns. \u003cem\u003eEpilepsy Behav.\u003c/em\u003e \u003cb\u003e44\u003c/b\u003e, 159\u0026ndash;168 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMargolis, A. E. et al. Using IQ Discrepancy Scores To Examine the Neural Correlates of Specific Cognitive Abilities. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e (35), 14135\u0026ndash;14145 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMargolis, A. E. et al. Verbal\u0026ndash;spatial IQ discrepancies impact brain activation associated with the resolution of cognitive conflict in children and adolescents. \u003cem\u003eDev. Sci.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e (2), e12550 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDosenbach, N. U. F. et al. A core system for the implementation of task sets. \u003cem\u003eNeuron\u003c/em\u003e \u003cb\u003e50\u003c/b\u003e (5), 799\u0026ndash;812 (2006).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHam, T., Leff, A., de Boissezon, X., Joffe, A. \u0026amp; Sharp, D. J. Cognitive Control and the Salience Network: An Investigation of Error Processing and Effective Connectivity. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e (16), 7091\u0026ndash;7098 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRuffini, C., Osmani, F., Martini, C., Giera, W. K. \u0026amp; Pecini, C. The relationship between executive functions and writing in children: a systematic review. \u003cem\u003eChild. Neuropsychol. J. Norm Abnorm. Dev. Child. Adolesc.\u003c/em\u003e \u003cb\u003e30\u003c/b\u003e (1), 105\u0026ndash;163 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCachia, A. et al. The sulcal patterns of the occipito-temporal and anterior cingulate cortices influence reading and writing in children and adults. Cerebral Cortex..\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeder, K. P. \u0026amp; Majnemer, A. Handwriting development, competency, and intervention. \u003cem\u003eDev. Med. Child. Neurol.\u003c/em\u003e \u003cb\u003e49\u003c/b\u003e (4), 312\u0026ndash;317 (2007).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eConnelly, V., Dockrell, J. E., Walter, K. \u0026amp; Critten, S. Predicting the quality of composition and written language bursts from oral language, spelling, and handwriting skills in children with and without specific language impairment. \u003cem\u003eWrit. Commun.\u003c/em\u003e \u003cb\u003e29\u003c/b\u003e (3), 278\u0026ndash;302 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSantangelo, T. \u0026amp; Graham, S. A comprehensive meta-analysis of handwriting instruction. \u003cem\u003eEduc. Psychol. Rev.\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e (2), 225\u0026ndash;265 (2016).\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":"","lastPublishedDoi":"10.21203/rs.3.rs-6938106/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6938106/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDevelopmental dysgraphia (DG) affects children\u0026rsquo;s handwriting despite adequate learning opportunities and intellectual potential. Although not recognized as a distinct clinical entity in international classifications, DG significantly impacts academic performance and wellness. In addition, it often co-occurs with neurodevelopmental disorders (NDDs) such as ADHD, developmental coordination disorder (DCD), and dyslexia (DL). To move beyond deficit-based perspectives and account for the complexity of cognitive functions, mechanisms and associated disorders, the cognitive profiles of DG examined using a strengths-and-weaknesses framework. DG were compared both to reference population and to children with other disorders.\u003c/p\u003e\u003cp\u003e366 children followed by the health network \u0026ldquo;Resodys\u0026rdquo;, completed the French adaptation of the Wechsler Intelligence Scale for Children (WISC V). Socioeconomic status was controlled. DG was defined as a significant difficulty in graphic movements impacting academic achievement without assumptions about the origin of the disorder. DL, DCD, and ADHD were diagnosed per ICD-10 criteria.\u003c/p\u003e\u003cp\u003e Results revealed that DG outperformed their peers in verbal comprehension, particularly on the \u0026ldquo;Similarities\u0026rdquo; subtest. This verbal advantage was unique to DG, distinguishing it from other NDDs and suggesting its potential specificity. The findings are discussed in relation to handwriting models, linguistic and executive functions, and their neuroanatomical underpinnings.\u003c/p\u003e","manuscriptTitle":"Deciphering developmental dysgraphia: evidence of a verbal advantage","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 11:45:45","doi":"10.21203/rs.3.rs-6938106/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":"63c5a09a-4dae-4117-bf78-a5332957ec50","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51996885,"name":"Health sciences/Neurology/Neurological disorders/Neurodevelopmental disorders"},{"id":51996886,"name":"Biological sciences/Neuroscience/Cognitive neuroscience"}],"tags":[],"updatedAt":"2025-12-18T02:24:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-28 11:45:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6938106","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6938106","identity":"rs-6938106","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}