Handwriting-based model for identification of developmental disorders among North Indian children

Abstract

Handwriting execution is based on the cognitive, kinesthetic, motor skills, and manual co-ordination skills of an individual. The deterioration in handwriting quality is a common implication of neurological disorders. Difficulty and degradation in handwriting has been attributed to the sensory motor deficits prevalent in developmental disorders. In spite of the association between developmental disorders and handwriting ability, the diagnostic potential of handwriting characteristics remains untapped. The present case control study was conducted among 300 subjects aged 6- to 11-years-old of North Indian origin to measure the potentials of handwriting characteristics to identify the selected developmental disorders namely ADHD, AD/HD, CD and DCD. A significant difference was obtained in the kinematics, relative size, number of handwriting defects, spatial orientation, line quality, and the mirror image presence between children with developmental disorders and typically developing (TD) children. A logistic model based on selected handwriting characteristics showed a cross validated 94.9% accuracy rate for diagnosis of developmental disorders. Receiver operator characteristic curve (ROC) analysis was conducted to assess the diagnostic potential of the model as presented by the area under curve was found to be 98.5%. The method is non-invasive, operationally easy and useful for an early identification of developmental disorders by parents and educators.

Keywords

Child psychology developmental disorders handwriting motor cognition North Indian children

Uniqueness and natural variation are the two crucial fundamental principles of handwriting identification (Saunders, Davis, & Buscaglia, 2011). Handwriting is considered as the manifestation of cognitive, psychomotor, and biophysical processes, characterized by motor equivalence and involving finger, wrist, and arm movements (Galen, 1991). The complex process of an individual’s execution of handwriting skills involving the cognitive, kinesthetic, motor skills, and manual co-ordination skills (Werner, Rosenblum, On, Heinik, & Korczyn, 2006) starts developing early in childhood at the onset of the scribbling period (Feder & Majnemer, 2007). The complex nature of handwriting execution is evident from the lack of proficient handwriting among children. Handwriting deterioration due to the lack of sensory-motor skills and cognitive abilities has been studied extensively. The findings of such studies have shown that various characteristics of handwriting such as isolation, timing, and grading of movements are affected by lack of fine motor control and cognitive abilities (Feder & Majnemer, 2007). Wing (2000) provided a flow chart model for elucidating the processes involved in writing. It was reported that the visual input leads to the orthographic analysis, followed by graphemic buffer, allographic store, and sequentially using the motor output, and thus handwriting is produced. The association of visual motor integration and eye-hand coordination is said to govern the line quality of handwriting (Kaiser, Albaret, & Doudin, 2009). Hence, a failure in visual motor integration governing the visual learning skill affects letter formation capacity of an individual (Daly, Kelley, & Krauss, 2003).

In the early 19th century it was posited that handwriting is related to brain functions and can be used to determine mental stability (Sulner, 1959). Hence it is not surprising that handwriting difficulties are more prevalent in certain clinical syndromes (Hellinckx, Roeyers, & Waelvelde, 2013). Implications of neurological disorders for handwriting has been demonstrated in depression, obsessive-compulsion disorder, Parkinson’s disease, schizophrenia, and developmental disorders (Racine, Majnemer, Shevell, & Snider, 2008). The handwriting of individuals with Asperger’s syndrome has been characterized with reduced legibility, poor quality, and deformed letter formations and erroneous size (Hellinckx et al., 2013). Poor visual motor coordination results in spacing defects among children with cerebral palsy (Bumin & Kevak 2008). Kinematic examination has been utilized as a marker for basal ganglia disease (Gallucci, Phillips, Bradshaw, Vaddadi, & Pantelis 1997).

Developmental disorders refer to deviant behavior, conduct, or biology. Such disorders appear particularly in childhood or early adolescence (Piek & Dyck, 2004). Attention Deficit Hyperactivity Disorders (ADHD), Attention Deficit without Hyperactivity Disorders (AD/HD), Conduct Disorders (CD), Autism and Development Coordination Disorders (DCD) are commonly occurring developmental disorders, which often exhibit various co-morbidities. The neural basis of these disorders vary from perinatal brain lesions to the developmental processes of life course (Piek & Dyck, 2004). Individuals with developmental disorders often exhibit lack of fine motor skills and cognitive deficits (Flapper, Howen, & Schoemaker, 2006). These deficits are associated with certain anatomical (Diamond, 2003) and functional brain anomalies (Volkow et al., 1998) and may further effect the information processing systems.

Sensory motor deficits responsible for degraded writing abilities have been reported among children with developmental disorders (Piek & Dyck, 2004). Fuentes, Mostofsky, and Bastian (2009) suggested training targeting letter formations and motor control for improvement of handwriting among children with Autism. Motor restlessness, inattention and impulsiveness implicated in ADHD result in academic difficulties and handwriting development. A study among Australian children reported poor handwriting in 58% of ADHD patients (Doyle, Wallen, & Whitmont, 1995). Another study affirmed the presence of poor organization of written material, spacing defects, poor legibility, inconsistent letter size and shape, alignment defects, frequent erasures and grotesque letter forms among ADHD children (Lerer, Artner, & Lerer, 1979). Force, timing of agonist and antagonist muscles, and pen pressure are apparently weak among ADHD children (Schoemaker, Ketelaars, Zonneveld, Minderaa, & Mulder, 2005). Chang and Yu (2010) observed difficulties in open loop and closed loop movements in children with DCD. Engelsman, Niemeijer, and Galen (2001) hypothesized that low quality handwriting among DCD diagnosed children is attributed to the neuromotor condition, lack of inhibition of co-movements and lack of fine motor skills. In a case control study among DCD and typically developing (TD) children, a significant difference between handwriting process measures and handwriting product characteristics was observed (Rosenblum & Zirinski, 2008). A recent study conducted an examination of handwriting speed among TD children and those with DCD and confirmed that the less text produced by the DCD children is attributed to the increased pausing time rather than the slow movement (Prunty, Barnett, Wilmut & Plumb, 2013). In their subsequent study Prunty et al. demonstrated a lack of automaticity in the handwriting of DCD children (Prunty, Barnett, Wilmut, & Plumb, 2014).

It is known that the identification of developmental disorders imposes challenges mainly due to the varied typologies, frequent comorbidities, and divergent severities (Abrams & Goodman, 1998; Nicolson & Fawcett, 2007). The assessment of developmental disorders involves comprehensive evaluation based on neuroimaging, behavioral scales, neurological and psychological tests and interviews of parents and educators. Previous studies have affirmed the link between developmental disorders, motor and cognitive deficits, and handwriting execution (Engelsman et al., 2001; Piek & Dyck, 2004). The disorder of written expression has been incorporated as one of the secondary parameters in the diagnostic criteria IV. However, the assessment involves the mere presence of dysgraphia (Harris, 1998). The effected handwriting characteristics in the developmental disorders have not been examined sufficiently. And the potential of handwriting characteristics as one of the early non-invasive diagnostic parameter remains untapped.

Research question

The research question generated in the present study was: Can selected handwriting characteristics be used as an early identification marker for developmental disorder?

Objective of the study

In spite of the association between developmental disorders and handwriting ability, the diagnostic potential of handwriting characteristics have not been examined sufficiently. And the strong association between developmental disorders and handwriting characteristics as one of the predictive or identification marker remains untapped. The present study examines the association of handwriting characteristics with early developmental disorders namely Attention Deficit Hyperactivity Disorders, Attention Deficit Without Hyperactivity Disorders, Conduct Disorders, Development Coordination Disorders and their comorbidities. A handwriting based logistic model has been developed for the identification of developmental disorders among North Indian children aged 6- to 11-years-old.

Method

Participants

A total of 150 cases and an equal number of controls aged 6- to 11-years-old from North India participated in the study. Considering the age minority, informed consent was taken from the legal guardians of all the selected subjects. The cases were recruited from the special education division of selected schools and psychology department of selected hospitals in the Delhi region. As part of the inclusion criteria, cases were selected on the basis of their previous medical diagnosis history with one or more selected developmental disorders namely Attention Deficit Hyperactivity Disorders, Attention Deficit Without Hyperactivity Disorders, Conduct Disorders, Development Coordination Disorders or their comorbidities. Presence of any other neurological, developmental, or behavioral disorder was set as an exclusion criterion. Another major inclusion criteria was right handedness. Healthy participants with no history of any developmental or neurological disorder comprised the control group.

Handwriting collection and examination

Both collected as well as dictated methods of handwriting investigation were used. Collected samples refer to previous handwritings done for the natural course of school and daily work and, as the name suggests, the dictated samples were requested to be executed as per the dictation. Medium paced dictation was carried out so as to ascertain that the subjects chose their comfortable speed of writing. Dictated samples were used for kinematic assessment since it requires ‘on the spot examination’. However, for other qualitative and quantitative measurements, collected samples were used. In the collected sampling method, handwriting samples dated prior to the diagnosis of the disorder were collected. It was ascertained that the time lag between diagnosis of the disorder and sample execution was not more than one year. The advantage of collected samples was the examination of sufficient writing material. A minimum of five pages of collected samples were obtained from the school together with the daily work records for each child in addition to one page of dictated sample from each subject. The samples displaying the commonly occurring letters (a), simple (e, I and o) as well as complex letters (k, p, f and h) and the selected combinations (‘ad’ and ‘th’) were obtained. It was also ascertained that the same type of pencil and the writing surface (blank A4 paper) were given to the subjects in case of dictated samples. For the collection of handwriting samples, all the necessary precautions were taken (Hilton, 1992).

The digital images of writing samples were captured using D3100 Nikon SLR and stored in jpeg form. Table 1 presents the handwriting characteristics examined in the present study. Speed of writing, presence of mirror image, spatial analysis, and quality assessments were made manually under 4X magnification while the relative size, slant, pressure, breaks, and bigram correlation distance coefficients were determined using the Image J 1.45 (Image Processing and Analysis in Java) software by National Institute of Health (NIH), USA. Prior to the software analysis, image processing was conducted using Image J 1.45. For the analysis of bi-gram correlation distance coefficients, case-control and control-control groups were constructed and random comparisons were made (Srihari, Huang, & Srinivasan, 2008). Visual assessment of the collected handwriting samples for letter ‘k’ was conducted among cases and controls to obtain the master patter or the intra-individual variability. Alphabet ‘k’ was chosen to study the variability since it conforms to complex letter formations. The schematic flow chart of the methodology is displayed in Figure 1. The quantitative measurements of the selected handwriting characteristics using Image J 1.45 are presented in Figures 2–4 (see Supplemental Materials).

Data analysis

The data were analysed using SPSS Version 16.0 for Windows, SPSS Inc., Chicago, Illinois, USA. The significance level was tested at the 95% level. Descriptive statistics of the quantitative variables were presented and comparisons between cases and controls were evaluated with t-test analysis. The qualitative variables were assessed with the Mann–Whitney U-test. The differences in the selected handwriting characteristics were also evaluated between males and females. Analysis of variance (ANOVA) test and Kruskal-Wallis test were conducted to evaluate differences in handwriting characteristics with respect to age. The variation in the distribution pattern between 136 case-control and 136 control-control bigram correlation distance coefficients was studied. Logistic regression analysis was performed to attain a predicting equation for developmental disorders from the selected handwriting variables. The model was evaluated at 0.5 limit value. The values less than 0.5 were evaluated as the controls while more than 0.5 as the cases. Receiver operator characteristic curve analysis was performed and area under curve (AUC) and cut off value were determined for the evaluation of the logistic model.

Results

The results in the present study showed that the handwriting characteristics displayed no significant difference with respect to the age or gender. The selected variables are useful measures of early diagnosis of developmental disorders. Table 2 provides the descriptive statistics of the selected quantitative handwriting characteristics among case and controls. Significant differences were observed between cases and controls in the kinematics, relative size, and number of handwriting defects. The participants with a developmental disorder spent a significantly more time in writing the same amount of subject matter. They also exhibited a significantly higher pen pressure. It was also seen that the relative size of ‘a’ and ‘d’ was closer to the copybook form among healthy participants and in contrast, the subjects with developmental disorder exhibited more deviation. No significant difference was observed in slant between cases and controls. The Mann–Whitney U-test results showed significant difference in the spatial orientation, line quality, and the mirror image presence among cases and controls. The disorientations and presence of mirror images was significantly more among the cases. Line quality differences suggest that poor line quality is significantly less frequent among the healthy subjects. No significant difference was observed between the groups with respect to the slant classification. A distinctive bigram correlation distance coefficient distribution pattern between case-control and control-control group was observed (Figure 5). The varied bigram coefficients indicate a wider master pattern among the cases. The master pattern obtained for letter ‘k’ from the visual assessment of the collected handwriting samples of a subject with DCD is presented in Figure 6 (See Supplemental Materials for figures).

Table 3 presents the association of selected handwriting characteristics and the developmental disorders. The Neagelkerke’s R² showed that the model fits sufficiently well. The criteria for inclusion of variables was an improved model fit. It was found that the relative size and line quality exhibited non-significant odds. It was evident that the kinematic variables were the most useful predictors. After cross validation, 94.9% of accuracy rate was attained from the model. The logit equation was computed in the dataset and ROC analysis was performed to evaluate the diagnostic potential of the developed model (Figure 7). The diagnostic potential of the model as presented by the area under curve was found to be 98.5% (lower bound: 0.970, upper bound: 0.999) and a cut off value of 1.895 was obtained (see Supplemental Materials for figures).

Discussion

The high prevalence of handwriting difficulties is attributed to the precise co-ordination, fine motor skills, cognitive ability, and high precision force regulation required for handwriting execution. Hence the comorbidity of developmental disorders and handwriting difficulties are persistent (Engelsman et al., 2001). There is no ‘gold standard’ to identify ADHD (Gillberg et al., 2004), DCD (Rosenblum & Zirinski, 2008) and CD (Rogeness, Hernandez, Macedo, & Mitchell, 1982) or their comorbidity. Furthermore ADHD is often under-diagnosed due to the overshadowing of its somatic, physical, and syndromal features (Hendriksen, Peijnenborgh, Aldenkamp, & Vles, 2015). It is further characterized with heterogeneity in symptomatology, neuropsychology, and neurobiology (Heidbreder, 2015). The brain imaging, biochemical tests and the psychological tests can be conducted only after a correct assessment by the parents or educators. Hence a non-invasive and operationally easy method is essential for the identification or diagnosis of these disorders.

The aim of the study was to conduct a case-control examination of selected fundamental, inconspicuous and unique characteristics of handwriting among North Indian children diagnosed with one or more developmental disorders (ADHD, AD/HD, CD, DCD) and TD children to establish the handwriting characteristics for diagnosis of selected developmental disorders. A high prevalence of 3% to 10% of developmental disorders has been reported among Indian children (Arun, Chavan, Bhargava, Sharma, & Kaur, 2013). Despite the high prevalence, studies pertaining to developmental disorders among North Indian children are sparse and sporadic. Moreover, the awareness of developmental disorders is low in India and only speech delays are considered important by parents (Kaur et al., 2006). Likewise, only a few studies have been conducted on ADHD and its comorbidities among North Indian children (Sivakumar, Agarwal, & Sitholey 2013). Reports on the clinical correlates of conduct disorders among North Indians are also scanty (Malhotra, Aga, Balraj, & Gupta, 1999). No study has previously been reported on handwriting characteristics with regard to the developmental disorders in the population selected for the present study.

A significant difference was observed in the kinematics, relative size, and number of handwriting defects between children diagnosed with developmental disorders and TD children. The significant difference in the kinematics has also been reported in a study conducted on mild Alzheimer’s disease and mild cognitive impairment (Werner et al., 2006). The results also support previous findings that motor and cognitive interactions affect handwriting (Berninger, Mizokawa, & Bragg, 1991). The difference in kinematics in the present study groups support the previous finding of association between dysgraphia and typical kinematic profiles produced as a result of poor muscular initiation process (Galen, Portier, Engelsman, & Schomaker, 1993). The mean difference between the two study groups of the present examination was maximum for the writing defects (Table 2). The finding corroborates the work of Rosenblum and Zirinski (2008), in which they reported erasures/omissions to be the single most discriminant factor between the handwriting of DCD and TD children. Relative size is an inconspicuous fundamental handwriting characteristic extensively used in forensic investigations (Pervouchine & Leedham, 2007) but has not been examined in any of the previous studies on developmental disorders. Similarly, Slant has been employed in the discriminability of handwriting of twins but has not, however, been examined with respect to neurological and developmental disorders. Likewise, the bi-gram correlation is a potential characteristic for discriminating handwritings of children with cognitive impairments or developmental disorders. Significant difference with respect to spatial orientation, line quality, and mirror image presence supports the evidence of motor deficits in developmental disorders (Engelsman et al., 2001; Piek & Dyck, 2004). The wider master pattern among cases as noticed from the bi-gram correlation coefficients and a visual assessment is parallel with the evidence of higher intra-individual variability in the handwriting of children with ADHD (Borella, Chicherio, Maria Re, Sensini, & Cornoldi, 2011).

Logistic regression and ROC analysis were performed to assess the association of selected handwriting characteristics with developmental disorders and further establish the elements of handwriting for objective evaluation and identification or diagnosis of developmental disorders The significant odds for the defects, kinematics, mirror image presence and spatial orientation support the evidence of the lack of visual-motor coordination abilities, cognitive skills, and kinesthetic sensitivities among cases (Feder & Majnemer, 2007).

The findings of the present study are in concordance with the previous reports of spacing and alignment defects (Lerer, Artner, & Lerer, 1979), poor quality (Engelsman et al., 2001), weak pen pressure (Schoemaker et al., 2005) among children with ADHD. The previous examinations have highlighted the correlation of these handwriting characteristics with developmental disorders, however no study was found to report a handwriting-based diagnostic model for early and non-invasive identification of developmental disorders and their comorbidities.

The model developed in the present study is suitable for English script. Hence, the handwriting-based tool will be suitable for different populations worldwide following the same script and not varying significantly from the study population in terms of writing methodologies. However, it is known that handwriting is affected by demographic characteristics (Chapran, Fairhurst, Guest, & Ujam, 2008). It is thus suggested that more such studies should be peformed among different populations to devise uniform standard handwriting characteristics as one of the possible diagnostic tools for developmental disorders.

Implications for school psychological practice

The expansion of the role of school psychologists have made it imperative for them to provide protective and preventive factors essential for child growth and development. Ensuring effective and early childhood special education service is another crucial responsibility of the school psychologists. For fulfilling these key responsibilities, a correct assessment and evaluation of child’s mental health and its needs are of utmost importance.

A host of evidence suggests a strong link between handwriting difficulties, developmental disorders and academic performance (Nicolson & Fawcett, 2007). Hence, handwriting abilities are correlated with improved school performance. The present study provides a handwriting-based model for early identification and assessment of selected developmental disorders (ADHD, AD/HD, CD, and DCD). This handwriting-based model is a useful tool for school psychologists. The suitable and effective interventions can be designed by school psychologists only subsequent to a holistic and a comprehensive assessment. Apart from identification, the handwriting characteristics will be informative regarding the effected motor, cognitive and kinaesthetic ability. Subsequent visual feedback, kinaesthetic feedback, and cognitive tests can be conducted by the school psychologists for devising effective and necessary interventions and imparting relevant skills to affected students. School psychologists can further use the handwriting model to build suitable strategies and impart awareness regarding it amongst the educators and parents.

Significance of the current study

The past decade has witnessed sustained efforts to develop diagnostic tools or models for developmental disorders. However no definitive insights have been attained on motor behavior and its implications in disorders (Engelsman et al., 2001). And the diagnosis of developmental disorders remains a challenging task. Moreover a systematic clinical diagnosis is mostly conducted only if the parents or the educators correctly perceive a problem. In spite of the cognitive and psychomotor nature of handwriting execution (Galen, 1991) only dysgraphia has been given attention (Harris, 1998). However, the potential of selected handwriting characteristics as one of the markers for diagnosis of developmental disorders remain untapped. The present study provides an insight on the use of handwriting as one of the diagnostic parameters for developmental disorders and their comorbidities. The study provides the selected handwriting characteristics exhibiting maximum accuracy for diagnosing developmental disorders. The selected handwriting characteristics can thus serve as an early non-invasive marker for assessment of developmental disorders and their comorbidities. Though it is necessary to examine the efficacy of the model with regard to the population variation, the method is applicable among different populations practicing ‘English’ script. Another advantage of the method is that the selected characteristics can be easily tested by parents and educators. When used alongside other psychological tests, cognitive assessment and motor control tasks, the model will increase the discriminatory power of the assessment. The present handwriting-based tool will also aid in pointing out related cognitive, visual, motor, and kinaesthetic deficits among the children. The study provides useful insights for school psychologists. Apart from the early recognition of the handwriting-based risk factors, the psychologists can provide suitable aid for improving the affected handwriting skills of students and guide educators to strengthen and enhance the related cognitive and motor skills.

Limitations of the study

The present examination provides novel findings with regard to developmental disorder diagnosis, however, there are certain limitations in the study. Though different disorders, namely, ADHD, AD/HD, CD, and DCD and their comorbidities were studied, the sample size pertaining to each disorder was insufficient. Hence the handwriting characteristics pertaining to each disorder were not analysed. Nevertheless, the aim of the study was to develop a handwriting-based diagnostic model for the selected developmental disorders and their comorbidities rather than individual disorders. Another limitation of the study is the low sample size (300 subjects) for logistic regression especially considering that seven predicting variables were used.

Conclusion

There is a significant difference in the selected handwriting characteristics between patients of developmental disorders and healthy individuals belonging to the age group of 6-11 years. The study suggests the use of selected handwriting characteristics as one of the diagnostic markers for developmental disorders. Handwriting is a potential biomarker for diagnosis of developmental disorders and can be highly useful for parents and educators. The method is non-invasive, operationally easy, and can provide an early identification of developmental disorders by parents and educators.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author biography

Jasmine Kaur Dhall received her doctorate in Forensic Anthropology from the University of Delhi in 2015 and is currently working on an independent research project in the Department of Anthropology, University of Delhi. She was awarded the Junior Research Fellowship Award (2010–2012) and the Senior Research Fellowship Award (2012–2014) by the University Grants Commission. Her current research interests include juvenile criminal behavior, child development, and victimology.

References

Abrams

E. Z.

Goodman

J. F.

(1998) Diagnosing developmental problems in children: Parents and professionals negotiate bad news. Journal of Pediatric Psychology 23(2): 87–98. doi: 10.1093/jpepsy/23.2.87.

Arun

Chavan

B. S.

Bhargava

Sharma

Kaur

(2013) Prevalence of specific developmental disorder of scholastic skill in school students in Chandigarh, India. Indian Journal of Medical Research 138(1): 89–98.

Berninger

V. W.

Mizokawa

D. T.

Bragg

(1991) Theory based diagnosis and remediation of writing disabilities. Journal of School Psychology 29(1): 57–79. doi:10.1016/0022-4405(91)90016-K.

Borella

Chicherio

Maria Re

Sensini

Cornoldi

(2011) Increased intraindividual variability is a marker of ADHD but also of dyslexia: A study on handwriting. IET Computer Vision 77(1): 33–39. doi: 10.1016/j.bandc.2011.06.005.

Bumin

Kevak

S. T.

(2008) An investigation of the factors affecting handwriting performance in children with hemiplegic cerebral palsy. Disability and Rehabilitation 30(8): 1374–1385. doi: 10.1080/09638280701673609.

Chang

H. S.

N. Y.

(2010) Characterization of motor control in handwriting difficulties in children with or without developmental coordination disorder. Developmental Medicine and Child Neurology 52(3): 244–250. doi: 10.1111/j.1469-8749.2009.03478.x.

Chapran

Fairhurst

M. C.

Guest

R. M.

Ujam

(2008) Task related population characteristics in handwriting analyses. IET Computer Vision 2(2): 75–87. doi: 10.1059/iet-cvi:20070069.

Daly

C. J.

Kelley

G. T.

Krauss

(2003) Relationship between visual-motor integration and handwriting skills of children in kindergarten: A modified replication study. The American Journal of Occupational Therapy 57(4): 459–462. doi: 10.5014/ajot.57.4.459.

Diamond

(2003) Close interrelation of motor development and cognitive development and of the cerebellum and prefrontal cortex. Child Development 71(1): 44–56. doi: 10.1111/1467-8624.00117.

10.

Doyle

Wallen

Whitmont

(1995) Motor skills in Australian children with attention deficit hyperactivity disorder. Occupational Therapy International 2(4): 229–240. doi:10.1002/oti.6150020403.

11.

Engelsman

B. C. M. S.

Niemeijer

A. S.

Galen

G. P. V.

(2001) Fine motor deficiencies in children wdiagnosed as DCD based on poor grapho-motor ability. Human Movement Science 20(1–2): 161–182. doi: 10.1016/S0167-9457(01)00033-1.

12.

Feder

K. P.

Majnemer

(2007) Handwriting development, competency, and intervention. Developmental Medicine and Child Neurology 49(4): 312–317. doi: 10.1111/j.14698749.2007.00312.x.

13.

Flapper

B. C. T.

Howen

Shoemaker

M. M.

(2006) Fine motor skills and effects of methylphenidate in children with attention-deficit-hyperactivity disorder and developmental coordination disorder. Developmental Medicine and Child Neurology 48(3): 165–169. doi: 10.1017/S0012162206000375.

14.

Fuentes

C. T.

Mostofsky

S. H.

Bastian

A. J.

(2009) Children with autism show specific handwriting impairments. Neurology 73(19): 1532–1537. doi: 10.1212/WNL.0b013e3181c0d48c.

15.

Galen

G. P. V.

(1991) Handwriting: Issues for a psychomotor theory. Human Movement Science 10(2–3): 165–191. doi: 10.1016/0167-9457(91)90003-G.

16.

Galen

G. P. V.

Portier

S. J.

Engelsman

B. C. M. S.

Schomaker

L. R. B.

(1993) Neuromotor noise and poor handwriting in children. Acta Psychologica 82(1–3): 161–178. doi: 10.1016/0001-6918(93)90010-O.

17.

Gallucci

R. M.

Phllips

J. G.

Bradshaw

J. L.

Vaddadi

K. S.

Pantelis

(1997) Kinematic analysis of handwriting movements in schizophrenic patients. Biological Psychiatry 41(7): 830–833. doi: 10.1016/S0006-3223(96)00544-6.

18.

Gillberg

I. C.

Rasmussen

Kadesjo

Henrik

Rastam

Johnson

(2004) Co-existing disorders in ADHD––implications for diagnosis and intervention. European Child and Adolescent Psychiatry 13(1): i80–i92. doi: 10.1007/s00787-004-1008-4.

19.

Harris

J. C.

(1998) Developmental neuropsychiatry: Assessment, diagnosis and treatment of developmental disorders, New York, NY: Oxford University Press.

20.

Heidbreder, R. (2015). ADHD symptomatology is best conceptualized as a spectrum: A dimensional versus unitary approach to diagnosis. ADHD Attention Deficit Hyperactivity Disorders. doi: 10.1007/s12402-015-0171-4.

21.

Hellinckx

Roeyers

Waelvelde

H. V.

(2013) Predictors of handwriting in children with autism spectrum disorder. Research in Autism Spectrum Disorders 7(1): 176–186. doi: 10.1016/j.rasd.2012.08.009.

22.

Hendrikson

J. G.

Peijnenborgh

J. C.

Aldenkamp

A. P.

Vles

J. S.

(2015) Diagnostic overshadowing in a population of children with neurological disabilities: A crosssectional descriptive study on acquired ADHD. European Journal of Pediatric Neurology 19(5): 521–524. doi: 10.1016/j.ejpn.2015.04.004.

23.

Hilton

(1992) Scientific examination of questioned documents, New York, NY: CRC Presss.

24.

Kaiser

M. L.

Albaret

J. M.

Doudin

P. A.

(2009) Relationship between visual-motor integration, eye-hand coordination, and quality of handwriting. Journal of Occupational Therapy, Schools and Early Intervention 2(2): 87–95. doi: 10.1080/19411240903146228.

25.

Kaur

Chavan

B. S.

Lata

Kaur

Tinku

Arora

Ratnam

(2006) Early intervention in developmental delay. Indian Journal of Pediatrics 73: 31–34.

26.

Lerer

R. J.

Artner

Lerer

M. P.

(1979) Handwriting deficits in children with minimal brain dysfunction: Effects of methylphenidate (Ritalin) and placebo. Journal of Learning Disabilities 12(7): 450–455. doi: 10.1177/002221947901200704.

27.

Malhotra

Aga

V. M.

Balraj Gupta

(1999) Comparison of conduct disorder and hyperkinetic conduct disorder: A retrospective clinical study from North India. Indian Journal of Psychiatry 41(2): 111–121.

28.

Nicolson

R. I.

Fawcett

A. J.

(2007) Procedural learning difficulties: Reuniting the developmental disorders. Trends in Neurosciences 30(4): 135–141. doi: 10.1016/j.tins.2007.02.003.

29.

Pervouchine

Leedham

(2007) Extraction and analysis of forensic document examiner features used for writer identification. Pattern Recognition 40(3): 1004–1013. doi: 10.1016/j.patcog.2006.08.008.

30.

Piek

J. P.

Dyck

M. J.

(2004) Sensory-motor deficits in children with developmental coordination disorder, attention deficit hyperactivity disorder and autistic disorder. Human Movement Science 23(3–4): 475–488. doi: 10.1016/j.humov.2004.08.019.

31.

Prunty

Barrnett

A. L.

Wilmut

Plumb

(2013) Handwriting speed in children with developmental coordination disorder. Are they really slower? Research in Developmental Disabilities 34(9): 2927–2936. doi: 10.1016/j.ridd.2013.06.005.

32.

Prunty

Barrnett

A. L.

Wilmut

Plumb

(2014) An examination of writing pauses in the handwriting of children with developmental coordination disorder. Research in Developmental Disabilities 35(11): 2849–2905. doi: 10.1016/j.ridd.2014.07.033.

33.

Racine

M. B.

Majnemer

Shevell

Snider

(2008) Handwriting performance in children with attention deficit hyperactivity disorder (ADHD). Journal of Child Neurology 23(4): 399–406. doi: 10.1177/0883073807309244.

34.

Rogeness

G. A.

Hernandez

J. M.

Macedo

C. A.

Mitchell

E. L.

(1982) Biochemical differences in children with conduct disorder socialized and unsocialized. The American Journal of Psychiatry 139(3): 307–311.

35.

Rosenblum

Zirinski

(2008) Handwriting process and product characteristics of children diagnosed with developmental coordination disorder. Human Movement Science 27(2): 200–214. doi: 10.1016/j.humov.2008.02.011.

36.

Saunders

C. P.

Davis

L. J.

Buscaglia

(2011) Using automated comparisons to quantify handwriting individuality. Journal of Forensic Sciences 56(3): 683–689. doi: 10.1111/j.1556-4029.2011.01713.x.

37.

Schoemaker

M. M.

Ketelaars

C. E.

Zonneveld

Minderaa

Mulder

(2005) Deficits in motor control processes involved in production of graphic movements of children with attention-deficit-hyperactivity disorder. Developmental Medicine and Child Neurology 47(6): 390–395. doi: 10.1111/j.1469-8749.2005.tb01159.x.

38.

Sivakumar

Agarwal

Sitholey

(2013) Comorbidity of attention-deficit/hyperactivity disorder and bipolar disorder in North Indian clinical children and adolescents. Asian Journal of Psychiatry 6(3): 235–242. doi: 10.1016/j.ajp.2012.12.011.

39.

Srihari

Huang

Srinivasan

(2008) On the discriminability of the handwriting of twins. Journal of Forensic Sciences 53(2): 430–446. doi: 10.1111/j.1556-4029.2008.00682.x.

40.

Sulner

H. F.

(1959) Mental disorders: Their effects upon handwriting. American Bar Association Journal 45(9): 931–934.

41.

Volkow

N. D.

Gur

R. C.

Wang

G. J.

Fowler

J. S.

Moberg

P. J.

Ding

Y. S.

, (1998) Association between decline in brain dopamine activity with age and cognitive and motor impairment in healthy individuals. The American Journal of Psychiatry 155(3): 344–349.

42.

Werner

Rosenblum

G. B.

Heinik

Korczyn

(2006) Handwriting process variables discriminating mild Alzheimer’s disease and mild cognitive impairment. Journal of Gerontology 61B(4): 228–236. doi: 10.1093/geronb/61.4.P228.

43.

Wing

A. M.

(2000) Motor control: Mechanisms of motor equivalence in handwriting. Current Biology 10(6): 245–248. doi: 10.1016/S0960-9822(00)00375-4.