Abstract The main criteria in the diagnosis of Autism spectrum disorder


Abstract
The main criteria in the diagnosis of Autism spectrum disorder (ASD) emphasize social impairment (American Psychiatric Association, 2013) . There are also several studies who describe motor impairments in children with a diagnosis of ASD (Downey & Rapport, 2012; Setoh et al., 2017). This study aimed to investigate the extent to which motor impairments can predict social skills and the extent to which social impairments can predict motor skills. It is hypothesized that a greater impairment in social or motor skills will lead to more problems with motor or social abilities. A group of 46 children between two to eight years old participated. A multiple and logistic regression model was conducted. The results showed clear motor and social impairments in children with ASD. Furthermore presence of motor difficulties was a strong predictor for diagnosis of ASD. However, the variables motor and social skills did not display significant predictive capability in the presence of the other as outcome.

Introduction
Autism spectrum disorder (ASD) is a pervasive developmental disorder, described by two main features. First, individuals with ASD are characterized by persistent deficits in social communication and social interaction across multiple contexts. Second, restricted, repetitive patterns of behaviour, interests, or activities are described. The symptoms cause clinically significant impairment in social, occupational, or other important areas of current functioning (American Psychiatric Association, 2013). Studies in Asia, Europe, and North America determined an average prevalence between 1% and 2% (Autism and Developmental Disabilities Monitoring Network, 2012a).
As mentioned above children with ASD have an increased likelihood of impairment in social development. It is manifested in problems such as social-emotional reciprocity, nonverbal communicative behaviours (e.g. reduced eye contact, facial expression and body gesture) and in developing and maintaining relationships (American Psychiatric Association, 2013; Sharmila Banerjee Mukherjee, 2017; Park et al., 2016). It seems social motivation (Calder, Hill, & Pellicano, 2013; Chevallier, Kohls, Troiani, Brodkin, & Schultz, 2012) and sensory dysfunction (Corbett, Muscatello, & Blain, 2016) impact negatively social behaviour. According to the literature, only 20% of the children with ASD have friends (Chang, Shih, & Kasari, 2016; Kasari, Locke, Gulsrud, & Rotheram-Fuller, 2011). Furthermore, less accurate processing of faces at school age (Eussen et al., 2015) and the amount of eye contact during conversations (Jones et al., 2016) is associated with higher ASD severity.
The Diagnostic and statistical manual of mental disorders version 5 (DSM-5) describes repetitive stereotyped motor patterns, but they are not considered to be a core characteristic of ASD (American Psychiatric Association, 2013). Restricted and repetitive behaviours are observed at young age (Bhat, Landa, & Galloway, 2011; Elison et al., 2014; Hattier, Matson, Macmillan, & Williams, 2013; Malhi & Singhi, 2014) and may be identified as early as social communication deficits in children with ASD (Elison et al., 2014). To continue, motor problems in individuals with ASD are the rule rather than the exception (Setoh et al., 2017). Reviews remarked motor impairments appearing at early age, in ASD (Bhat et al., 2011; Matson, Matson, & Beighley, 2011; Memari, Ghanouni, Shayestehfar, & Ghaheri, 2014; Setoh et al., 2017; Van Damme, Simons, Sabbe, & van West, 2015).
Depending on the study, 20% to 90% of children with ASD demonstrated motor impairments (Dewey, Cantell, & Crawford, 2007; D. Green et al., 2009; C. L. Hilton, Zhang, Whilte, Klohr, & Constantino, 2012; Hirata et al., 2015; Malhi & Singhi, 2014; Pusponegoro et al., 2016a). Clumsiness in children with ASD is often seen (Fournier, Hass, Naik, Lodha, & Cauraugh, 2010; Setoh et al., 2017). Moreover, praxis difficulties is common in these children. They can experience problems in motor planning, sensorimotor integration and motor execution (Bhat et al., 2011; Chukoskie, Townsend, & Westerfield, 2013; Downey & Rapport, 2012; Fournier et al., 2010; J. P. McCleery, N. A. Elliott, D. S. Sampanis, & C. A. Stefanidou, 2013; Memari et al., 2014; Sacrey, Germani, Bryson, & Zwaigenbaum, 2014). Consequently, concerning their motor difficulties altered sensory input, altered motor output and difficulties in organizing motor knowledge, may have a significant role in people with ASD (Gowen & Hamilton, 2013).
According to standardized motor evaluations, they have difficulties in achieving motor milestones at the same rate as typical developing children (Harris, 2017). The motor impairments involve gross and fine motor skills (Bhat et al., 2011; Chukoskie et al., 2013; Gowen & Hamilton, 2013; Memari et al., 2014; Sacrey et al., 2014; Setoh et al., 2017) and appear in upper and lower extremities (Bhat et al., 2011; Fournier et al., 2010).
Reviews regarding more specific motor features indicate deficits in: manual dexterity (Bhat et al., 2011; Gowen & Hamilton, 2013), handedness (Mosconi & Sweeney, 2015), coordination (Bhat et al., 2011; Fournier et al., 2010; Gowen & Hamilton, 2013; Kindregan, Gallagher, & Gormley, 2015; Memari et al., 2014), postural instability (Bhat et al., 2011; Downey & Rapport, 2012; Fournier et al., 2010; Gowen & Hamilton, 2013; Memari et al., 2014), imitation (Bhat et al., 2011; J. P. McCleery et al., 2013; Setoh et al., 2017) and gait (Bhat et al., 2011; Fournier et al., 2010; Gowen & Hamilton, 2013; Kindregan et al., 2015; Memari et al., 2014; Mosconi & Sweeney, 2015; Setoh et al., 2017). Moreover, these reviews often report a gait pattern that is similar to Parkinson Disease or Cerebellar ataxia (Bhat et al., 2011; Fournier et al., 2010; Gowen & Hamilton, 2013; Kindregan et al., 2015; Memari et al., 2014; Mosconi & Sweeney, 2015; Setoh et al., 2017).
A child with more play and motor experiences may develop better in other domains (Van Damme et al., 2015). Several studies postulate that motor skills may play an important role in promoting social engagement, social interaction and social skills (Bedford, Pickles, & Lord, 2016; Bhat et al., 2011; Sacrey et al., 2014; Sipes, Matson, & Horovitz, 2011). There is growing interest and empirical evidence regarding the relation between motor skills and social functioning in individuals with ASD. This could be important because the depth and reason of a relationship must be further examined in the future (Hirata et al., 2015; M. MacDonald, C. Lord, & D. A. Ulrich, 2013b). Motor impairments could clarify problems in social functioning in these children (Casartelli, Molteni, & Ronconi, 2016). In turn, the existence of a relationship can be important for clarifying the pathogenesis of ASD (Estes et al., 2015). According literature, shared neurobiology is a likely contributor to the frequent occurrence of motor and social dysfunction in ASD (Ariane M. Dowd et al., 2010).
To continue, sensorimotor symptoms in children with ASD are noticed before social communication deficits (Estes et al., 2015). These motor markers could be used for early ASD detection (Casartelli et al., 2016). Additionally, early determination of the degree of motor deficits may predict the severity of ASD. Consequently, this can improve social and motor targeted interventions. These interventions may be important, because we assume that children with delayed motor or social skills participate less in sport-related activities, which could aggravate their motor ( or ) social skills delay versus peers. As cited in (Bremer, Balogh, & Lloyd, 2014) children with ASD may not be physically able to engage in active play partially due to their poor motor skills. Play is reported to be essential for the development of joint attention, sharing, empathy, cooperation, and emotional regulation through the peer interactions that play can provide (Bremer et al., 2014). Finally, since children with ASD are 40% more likely to be overweighed compared to their peers, providing physical activity may be crucial (Curtin et al., 2010).
Some previous studies suggest a relationship between motor skill impairment levels and socialization impairments and consequently ASD severity scores (Dziuk et al., 2007; Estes et al., 2015; C. Hilton et al., 2007; C. L. Hilton et al., 2012; Hirata et al., 2015; MacDonald et al., 2013b; M. MacDonald, C. Lord, & D. A. Ulrich, 2014; Mody et al., 2016; Pusponegoro et al., 2016a; Sipes et al., 2011). Moreover, the quality of early fine and gross motor skills seems to be associated with the rate of expressive language development (Bedford et al., 2016; Gernsbacher, Sauer, Geye, Schweigert, & Goldsmith, 2008; Lebarton & Iverson, 2013; Leonard, Bedford, Pickles, & Hill, 2015; Mody et al., 2016). On the contrary, adverse evidence exists concerning the influence of motor development on receptive language (Bedford et al., 2016; Leonard et al., 2015; Mody et al., 2016). Furthermore, it has been suggested that interventions targeting motor skills promoted both, motor and social behaviour (Bremer et al., 2014; Bremer & Lloyd, 2016; Ketcheson, Hauck, & Ulrich, 2016).
Regarding this evidence several studies used a sample of children minimum 6 years old (Dziuk et al., 2007; C. Hilton et al., 2007; Hirata et al., 2015; MacDonald et al., 2013b). This study targeted either for younger children assuming school setting, leisure activities and therapies may have an effect on their further development of motor and social skills. These experiences could influence the results by underestimation of initial motor and social problems. Some of the studies mentioned above (Estes et al., 2015; Megan MacDonald, Catherine Lord, & Dale A. Ulrich, 2014; Sipes et al., 2011), examined infants and preschool children. The present study included children aged 2 years and older, suspecting these children have better communication, concentration, work skills, and have achieved already the motor milestones what may improve reliability of motor examinations. Furthermore a significant gap in the literature concerning the motor skills of preschool-aged children with ASD exist (Bremer et al., 2014). Another remark of some studies mentioned above is the number and type of instruments used. As suggested in M. MacDonald, C. Lord, and D. Ulrich (2013a) more sensitive motor skill assessments need to be implemented, such as Peabody Motor Developmental Scales – second edition. Consequently, reliable and valid motor assessments were thoroughly selected. Moreover a combination of standardised instruments and parent questionnaires was conducted, contrary to several studies (Bedford et al., 2016; Dziuk et al., 2007; Gernsbacher et al., 2008; Leonard, Elsabbagh, & Hill, 2014; MacDonald et al., 2013b; Megan MacDonald et al., 2014; Mody et al., 2016; Pusponegoro et al., 2016a; Sipes et al., 2011). In contrast with various studies Movement Assessment Battery for Children-2 (MABC-2) and Test of Gross Motor Development-2 (TGMD-2) were combined with each other and sometimes the Beery Buktenica Developmental test of Visual-Motor Integration (Beery VMI) was added, obtaining a comprehensive motor skill evaluation (C. Hilton et al., 2007; Hirata et al., 2015; MacDonald et al., 2013b).
Estes et al. (2015); Pusponegoro et al. (2016a) did find a trend among children with lower motor skills to obtain lower socialization scores, but in fact they did not search for an association between gross motor impairments and socialization skills. Moreover, in the study of MacDonald et al. (2013b) only object control skills, and not locomotor skills, predicted social skills in one out of the two social skill measurements. But the total score on TGMD-2 could not predict standardized social skills. In addition, no significant relation of Beery VMI Performance and the level of social impairment was found in a study from R. R. Green et al. (2016).
In conclusion the purpose of this study is to investigate the extent to which motor skills, measured by questionnaires and standardised motor assessment instruments predict social behaviour and skills in children with a (suspected) diagnosis of ASD and vice versa. Based on previous research a reciprocal influence is hypothesized (Sacrey et al., 2014). We expect that children with higher motor scores will obtain better social scores and children with better social skills, will have better motor abilities.
Methods
Participants
A population of 46 children, 10 girls and 36 boys, age 2-8-year-old, suspected of ASD, participated in this study. Children between 2 and 18 years old were gathered by means of consecutive sampling for a larger study about the determinants of adaptive behaviour, family quality of life and behavioural problems in children with (suspected) ASD. Participants were excluded if they met the following exclusion criteria: (a) Children who did not fulfil the criteria of calendar age. (b) Children with a developmental age less than 2 years, (c) Children whose parents do not speak sufficient Dutch, (d) Children with substantial physical, sensory and neurological disabilities, evaluated by physical examination. Psychomotor performance and other abilities were examined in the Centre of Developmental Disorders (COS) and the Centre of Expertise for Autism Spectrum Disorder in Leuven, Belgium. All parents of the subjects signed a written consent form prior to participation in accordance with the Declaration of Helsinki. The study was approved by the local ethics committee (KU Leuven Medical Ethics Committee).
Measures
Motor assessment
The Peabody Developmental Motor Scales-2 (PDMS-2) is a valid and reliable assessment of fine and gross motor skills for children aged 0 to 6 years 11 months (Folio, 2000). It consists of six subscales: reflexes (for children birth through 11 months), stationary, object control (for children 12 months and older), locomotion (gross motor subtest), grasping and visual motor integration (fine motor subtest). Raw scores on the PDMS-2 are converted to age equivalent scores, percentiles, and standard scores for each of the subtests (Folio, 2000). All the PDMS-2 subtests contribute to a Total Motor Quotient (TMQ) (Tavasoli, Azimi, & Montazari, 2014). Usually this score is considered to be the best estimate of overall motor abilities (Tavasoli et al., 2014). In addition, there consists a Gross and Fine Motor Quotient. Subtests reflexes/stationary, object control and locomotion contribute to the Gross Motor Quotient (GMQ) (Tavasoli et al., 2014). Fine Motor Quotient includes the grasping and visual motor integration subtests (Tavasoli et al., 2014). The PDMS-2 has a high to excellent test-retest reliability (r = 0.89-0.96), interrater reliability (r = 0.96-0.99) and internal consistency (r = 0.89-0.97), for subtest and total test scores (Folio, 2000). Regarding validity, performance increases with age and PDMS-2 discriminates between typical developing children and children with motor problems (Folio, 2000). van Hartingsveldt, Cup, and Oostendorp (2005) found high test-retest (r=0,84-0,98) and inter-rater reliability (r=0,94-0,99) and excellent convergent validity with the M-ABC (r=0,69), for fine motor scale of PDMS-2. High concurrent validity with Bayley-III was found for age-equivalent scores in children above 18 months (Connolly, McClune, & Gatlin, 2012).
The Beery Buktenica Developmental test of Visual-Motor Integration (Beery VMI), sixth edition is a valid and reliable instrument for children from two years to 18y 11 months. It comprises three subtests: visual motor integration, visual perception and motor coordination. Moderate to excellent internal consistency (? = 0.82-0.87), high test-retest reliability (r = 0.88) and excellent interrater reliability (r = 0.93) is reported (Beery & Beery, 2010; Brown & Hockey, 2013). Harvey et al. (2017) found strong interrater correlations (r = 0.75-0.88) and moderate test-retest correlations (r = 0.54-0.58). Regarding validity, moderate correlations with the Wide Range Assessment of Visual Motor Ability (WRAVMA) and the Developmental Test of Visual Perception exist (DTVP-2) (Beery & Beery, 2010; Simons, 2004).
The Test of Gross Motor Development-2 (TGMD-2) is a valid and reliable assessment of gross motor development for children between 3 years and 10y 11 months. The TGMD-2 consists of 2 subtests: locomotor skills and object-control skills. Raw scores are converted into standardised scores, percentiles and a gross motor quotient. TGMD-2 raw scores and Gross motor quotient (GMQ) have moderate to excellent interrater reliability (ICC = 0.71-0.94 & 0.98), test-retest reliability (r = 0.88-0.96) and internal consistency (ICC = 0.80-0.88) (Barnett, Minto, Lander, & Hardy, 2014; Ulrich, 2000). There exists a moderate correlation between performance subtest and chronological age and good construct validity was found. Furthermore this test discriminates between typical developed children (TD) and children with a developmental delay (Simons, 2004; Ulrich, 2000).
The Movement Assessment Battery for Children-2 (MABC-2) has been developed for screening motor impairment in children between 3 months and 16y 11 months. The MABC-2 quantitative test consists of three components: manual dexterity, aiming and catching, and balance (static & dynamic). Scores are evaluated with the traffic light method representing definite motor impairment, borderline motor impairment or no motor impairment. Raw scores are converted into standardised scores and percentiles. The sum of the eight item standard scores makes the total test score (S.E. Henderson, Sugden, Barnett, & Smits-Engelsman, 2010; Schoemaker, Niemeijer, Flapper, & Smits-Engelsman, 2012; Simons, 2004). Interrater reliability is reported to be good to excellent (ICC = 0.94-1.00) (Sheila E Henderson & Barnett, 2007). The test-retest reliability of the three component scores is good to very good (r = 0.73, r = 0.79, r = 0.84) (Brown & Lalor, 2009; Sheila E Henderson & Barnett, 2007). The test-retest reliability of the total test score is very good (r = 0.80) (Sheila E Henderson & Barnett, 2007; S.E. Henderson et al., 2010; Schoemaker et al., 2012). Content and criterion validity is reported to be high, but there is a lack in construct validity (Brown & Lalor, 2009; Sheila E Henderson & Barnett, 2007; Saracho, 2014).
The questionnaire for motor skills of preschool children (VMVK) is a Belgian 28-item questionnaire about daily activities of children aged 3-5 years. The VMVK consist of age-specific norm scores. If the child obtains a higher score, this child has probably more difficulties performing daily activities compared to children of same age. Also, the motor developmental age can be derived from these scores. Reliability and validity scores are good. Test-retest reliability and internal consistency are excellent. Interrater reliability is high, except for children aged 5 years. A high correlation exists with the MABC-2 in the children aged 3-4 years, in five years moderate correlation exists. (see http://www.ugent.be/ge/revaki/nl/onderzoeksgroepen/pedia/wetmat/vmvk-pdf)
The Coördinatie Vragenlijst voor Ouders (CVO) is the Dutch translated version of the Developmental Coordination Disorder Questionnaire (DCD-Q) (Wilson et al., 2009). This is a 15-item questionnaire for screening motor problems in children aged 5-15 years. The questionnaire exists of three subscales: control during movement, fine motor/handwriting and general coordination. Scores are divided in three age categories and interpreted as suspected DCD or probably no DCD (Simons, 2004). The internal consistency of the DCD-Q is high (? = 0.88) and validity is good (Parmar, Kwan, Rodriguez, Missiuna, & Cairney, 2014; van der Linde et al., 2014). For the CVO the internal consistency is high (? = 0.90). The discriminant validity is good (Schoemaker et al., 2006).
Socio-affective assessment
The Child Behavior Checklist (CBCL) is a widely used parent report questionnaire to assess behavioural and emotional problems in children aged between 1,5 and 18 years (Mazefsky, Anderson, Conner, & Minshew, 2011). The CBCL’s questions are associated with problems on a syndrome scale in eight different categories: anxious/depressed, withdrawn/depressed, somatic complaints, social problems, thought problems, attention problems, rule-breaking behaviour, and aggressive behaviour (Mazefsky et al., 2011). The CBCL is a valid and reliable measurement (T. Achenbach, 2001). The test-retest reliability is excellent (r = .89) for the syndrome scales. The between-parents reliability (inter-parent reliability) is good (r = .65 – .75). Cronbach’s alpha values range from low to excellent (? = .46 to .93) on the various subscales. Evidence for construct validity is extensive (r = .59-.88) with the Conners Parent Questionnaire and with the Revised Behavior Problem Checklist with clinically-referred children (T. M. Achenbach, 1991; Mazefsky et al., 2011).
The Social Responsiveness Scale (SRS) is administered to determine the severity of autism spectrum disorders, in particular measuring social ability and impairment. The SRS is a 65 items parents or teacher questionnaire, for children aged 4-18 years. It provides an understanding of individual’s social impairments, social information processing, ability to reciprocate social communication, anxiety/avoidance and preoccupations. Scores on the SRS range from 0 to 195. Higher scores indicate more severe impairments and more risk for ASD (J.N. Constantino, Gruber, Noens, De la Marche, ; Scholte, 2012; Moody et al., 2017; Wigham, McConachie, Tandos, ; Le Couteur, 2012). The SRS has good overall psychometric properties (Moody et al., 2017). The SRS shows strong internal consistency (J. Constantino ; Gruber, 2005; J. N. Constantino et al., 2003), test-retest reliability (J. N. Constantino et al., 2003) and inter-rater reliability (Pine, Luby, Abbacchi, ; Constantino, 2006). In addition, it has good discriminant validity.
IQ assessment
Intelligence quotient (IQ) measurements are conducted with Wechsler Preschool and Primary Scale of Intelligence-III-Dutch version (WPPSI-III-NL) and the Snijders Oomen Non-verbal Intelligence test-Revised (SON-R). The WPPSI-III-NL (Hendriksen ; Hurks, 2009; Wechsler, 2002) is a sufficient to good reliable and valid instrument, measuring total IQ (TIQ) and indexscores for different age categories (Hendriksen ; Hurks, 2009). Total IQ is a sum of the scores on different subtests. The indexscores verbal IQ and performal IQ are each obtained by the sum of three different subtests. The Cronbach ? (TIQ = .86-.94, indexscores = .73-.93) and test-retest reliability (corrected subtests r =.60-.83, corrected IQ -and indexscores r = .75-.84) is generally good (Hendriksen ; Hurks, 2009). It’s internal and content validity has been established (Hendriksen & Hurks, 2009) (see https://www.pearsonclinical.be/media/whitepapers/Whitepaper_WPPSI-III-NL.pdf ).
The SON-R 2,5-7 and the SON-R 5,5-7 have very good mean reliability for total IQ score (r = 0.90 & 0.93) and sufficient mean reliability for the subtests (r = 0.72 & 0.76) (Snijders, Tellegen, & Laros, 1989; P. Tellegen, Winkel, Wijnberg-Williams, & Laros, 1998; P. Tellegen, Winkel, Wijnberg-Williams, & Laros, 2005; P. J. Tellegen & Laros, 2004; Winkel, 1999). Convergent and divergent validity in SON-R 2,5-7 is supported but there exist highly varying correlations (P. Tellegen et al., 1998; Winkel, 1999).
Concerning the total IQ scores, children were classified in to different categories. Table 1 shows the different categories and percentages of the study population.
Table 1 Intelligence Quotient (IQ) classification and descriptives (n=46)
IQ range Frequency %
131 1 2 .2
Note: IQ= Intelligence Quotient
Diagnosis of ASD
The Autism Diagnostic Observation Scale-2, Dutch version (ADOS-2, NL) is a semi-structured, standardized assessment tool for individuals with suspected autism spectrum disorder (ASD) and is deemed to be part of the gold standard for diagnostic evaluation (Kamp-Becker et al., 2018). It is an internationally well-established but complex diagnostic instrument that consists of five modules to be administered based on the individuals level of expressive language and chronological age as well as the appropriateness of assessment materials (Kamp-Becker et al., 2018). Each module provides different tasks including playful elements and activities as well as verbal tasks intended to provide the examiner with information on social, communicative, play and stereotyped behaviour (Kamp-Becker et al., 2018). Studies examining the validity of the ADOS have produced mixed findings (Dorlack, Myers, & Kodituwakku, 2018). The ADOS-2 has a high interrater and test-retest reliability (Chojnicka & Pisula, 2017; Lord et al., 2012).
Procedure
As mentioned previously, the sample consisted of 46 children aged 2- 8 years, with suspected ASD. They were recruited through consecutive sampling from the Centre of Developmental Disorders (COS) and the Centre of Expertise For Autism Spectrum Disorder (ECA) in Leuven. These children participated in a more comprehensive study, investigating characteristics of children with ASD. Children were seen and measured by different therapists or trained master students in psychology or physiotherapy. A paediatrician, remedial educationalist, speech therapist, psychologist and a physical therapist examined the child and consultations in the ambulatory setting were spread across approximately six months. Therapists were experienced with these different measurements and questionnaires. The master students got an education and training before executing the measurements. The standardization procedures of the guidelines of these instruments were followed rigorously.
The ADOS-2 NL was used to determine indications of potential ASD. IQ was measured with the WPPSI-III-NL or SON-R. These instruments were selected by experienced psychologists.
To measure social skills and psychological problems, SRS and CBCL questionnaires were used. To get an idea of motor functioning of these children during activities of daily life and their impact on daily functioning, the VMVK and CVO questionnaires were completed by parents. Most of the children 2-5y were assessed with the VMVK. In the children aged 5-8 years, the Dutch version of the DCDQ was preferred.
Furthermore, the PDMS-II, Beery VMI, TGMD-2 and Movement ABC-2 were administered to evaluate the motor skills in a standardised setting. Due to a clinical setting, the decision was dependent of the protocol and the choice of the therapist working in the institution. But in general motor skills in children aged 5-8 years was measured mainly using the TGMD-2, the MABC-2 and Beery VMI. PDMS-II was administered mainly in children aged 3-5 years to assess their motor abilities.
Next to these, playground observation, physical examination and language examination (RTOS: Reynell language developmental scale) were executed.

Statistical analysis
Data analysis was conducted to examine the extent to which motor impairment can predict socialization skills in children with ASD and vice-versa. This analysis was done with the statistical software SPSS, version 24 for Mac. First, descriptive analysis was executed. Subsequently multiple regression was conducted. Finally, logistic regression was performed for the categorical variables.
There were different multiple regression models created with SRS standard scores as dependent variable. The first two models included IQ as independent variable, but low predictability was found in these models. Hence, we excluded IQ as an independent variable in the other two models. These last two models are explained below. CBCL standard scores and motor problems were integrated as predictors for the outcome of the first model. CBCL standard scores and no motor problems were integrated as predictors for the outcome of the second model. The variable motor problems was divided into three dummy variables: no motor problems (pc >15), at risk motor (pc 5-15) and clear motor problem (pc 15)
SS on SRS SS on total CBCL scale At risk motor No motor problem
SS on SRS 1 .00 0 .51* 0 .28 -0 .16
SS on total CBCL scale 1 .00 0 .25 -0 .10
At risk motor 1 .00 -0 .49*
No motor problem 1 .00
* p < 0.05

The analysis indicated a significant positive moderate correlation between the standard score on SRS and the standard score on total CBCL scale. Positive but weak and no significant correlations were found between the at risk motor and SRS and total CBCL scale.
In the multiple regression model the three variables (standard score on total CBCL scale, at risk motor and no motor problem) explain 28.8% (r² = 0.288, adj r² = 0.199) of the variance of the standard score on SRS. A significant regression equation was found (F(3,24)=3.233, p