Developmental coordination disorder (DCD) can be defined as motor performances that are substantially below the expected levels of the child’s ability, considering the child’s chronological age and previous opportunities for gaining skills (American Psychiatric Association [APA] 2013). Furthermore, DCD is defined as a neuro-motor developmental disorder, which includes a ‘significant delay in the acquisition and execution of coordinated motor skills as expected for the child’s chronological age and opportunities for learning’ (APA 2013; Blank et al. 2012). The definition clearly states that DCD is a motor skill disorder, which influences a child’s activities during daily routines, learning performance and coordinated skill development.

The diagnosis of DCD is based on its description in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) (APA 2013). Learners may only be diagnosed with DCD if the learner meets the four diagnostic criteria determined by the APA (APA 2013). The following criteria are used:

However, the literature clearly states that the prevalence of DCD will be referred to as possible DCD, suspected DCD or at risk for DCD if all four DSM-5 criteria have not been used (Alesi, Pecoraro & Pepi 2019; Delgado-Lobete et al. 2019; Lingam et al. 2009; Valentini, Clark & Whitall 2015). For this reason, the term possible DCD was used in this study. De Souza (2015) conducted a systematic review regarding the four criteria to diagnose DCD and identified the Movement Assessment Battery for Children-2nd edition (MABC-2) as the most frequently used tool to assess criterion A, the Developmental Coordination Disorder Questionnaire (DCDQ) for criterion B and no specific instrument for criteria C and D. However, according to Blank et al. (2012), the European Academy of Childhood Disability (EACD) recommends that a medical practitioner should rule out criteria C before a diagnosis can be made and criteria D should be kept in mind if mental retardation is present.

The DSM-5 and previous researchers identified DCD in 5% – 6% of school-aged learners worldwide (APA 2013; Cairney & Streiner 2011; Goyen & Lui 2009; Rivard et al. 2014) between 6 and 12 years of age (Barnhart et al. 2003). It can therefore be ranked as one of the most common neuro-motor developmental disorders among school-aged learners (Lingam et al. 2010). The prevalence of DCD is well documented and varies within different countries and according to the diagnostic criteria used to identify this condition (Cardoso, Magalhães & Rezende 2014; De Milander, Coetzee & Venter 2014; Tsiotra et al. 2006; Valentini et al. 2012). In some countries, the incidence of DCD is high. In southern Brazil, 19.9% of learners between 4 and 12 years of age were identified with possible DCD (Valentini et al. 2012). These findings were similar to those in earlier research reporting that 16.6% of learners aged 7–11 years in a high socio-economic environment in Japan had DCD (Miyahara et al. 1998). Tsiotra et al. (2006) reported that in Greece, 19% of learners with a mean age of 11.3 years were identified with possible DCD. On the contrary, a low prevalence of DCD ranging between 0.8% and 4.3% was also reported among 7–8-year-old learners in Brazil (Cardoso et al. 2014) and 0.8% of Indian learners between 6 and 15 years of age (Girish, Raja & Kamath 2016) living in different socio-economic environments.

With regard to previous research in South Africa, De Milander et al. (2014) found a prevalence of 15% of possible DCD among 6–8-year-old learners in Bloemfontein, South Africa. Similar results were reported by Venter, Pienaar and Coetzee (2015), who found that DCD occurred in 11.3% of learners aged 3–5 years in the North West Province, South Africa. However, another study in the North West Province on learners aged 8–10 in different socio-economic environments identified a lower prevalence of possible DCD (6.3%) (Pienaar & Kemp 2014). In addition, a more recent study in the North West Province of South Africa on learners with a mean age of 10.05 years reported that 21.3% of the learners in the sample were identified with DCD. It is, however, important to note that this was a longitudinal study, and data were collected in 2013 (De Waal, Pienaar & Coetzee 2018).

Different results regarding the prevalence of DCD in gender have also been found. According to Lingam et al. (2009) and Pienaar and Lennox (2006), the prevalence of DCD is higher in boys than in girls. The DSM-5 (APA 2013) and Lingam et al. (2009) further suggested boy–girl ratios ranging from 2:1 to 7:1. Table 1 shows the comparison of the prevalence of DCD among boys and girls as reported previously from different studies. It is clear that contradicting results regarding the prevalence of DCD among boys and girls have been found. In addition, limited data on the prevalence of DCD in various socio-economic environments are available (Valentini et al. 2015).

Low socio-economic environments in South Africa are found in townships, inner cities and peri-urban areas (Ndebele 2015). These areas are identified on the basis of poverty, income, education, environmental factors, working conditions and health conditions (Isaacs-Martin 2015; Narsai et al. 2013; Pappin et al. 2015; Pienaar & McKay 2014). According to Senekal et al. (2015), learners and educators living in these environments have fewer opportunities and activities such as sport, playground spaces, equipment and extramural physical activities. Learners living in low socio-economic environments experience motor difficulties and developmental deficits in comparison with learners of the same age from more privileged environments (Pienaar 2004; Pienaar, Labuschagne & Peens 2007). Research conducted in South Africa by Cloete, Pienaar and Coetzee (2006) on 10–12-year-old learners and De Waal et al. (2018) on 10-year-old learners found that learners from low socio-economic environments had a high tendency to have DCD and showed motor skill difficulties. Even though motor skill difficulties are apparent in learners with DCD, no two learners with this disorder are the same and therefore experience different secondary problems.

Secondary problems associated with DCD are physical performance, such as impaired strength and flexibility (Batey et al. 2014; Rihtman, Wilson & Parush 2011; Wuang, Su & Su 2012) and increased obesity (Rihtman et al. 2011; Tsiotra et al. 2006). Learners may show difficulty in academic performance (Cantell, Smyth & Ahonen 2003) and completing activities of daily living (Cairney et al. 2012; Zhu et al. 2010), which include activities such as dressing themselves (home activities), writing and reading (school activities) and play activities, for example, ball skills and balance (Asonitou et al. 2012; Edwards et al. 2011; Schoemaker, Smits-Engelsman & Jongmans 2003). These secondary problems result in emotional and social problems, such as low self-esteem and poor social acceptance (Missiuna et al. 2006). Other problems related to DCD are difficulties with fine motor skills (Zwicker, Missiuna & Boyd 2009), visual impairments (Gomez & Sirigu 2015), attention deficit hyperactivity disorder (ADD/ADHD) and speech or language impairments (Gaines & Missiuna 2007; Missiuna 2003). Because of these difficulties (fine motor, visual and speech impairment), it is important to identify learners with DCD at an early stage.

According to our knowledge, limited research on the prevalence of DCD in different socio-economic environments in South Africa has been conducted. The aim of the study was to determine the prevalence of possible DCD among Grade 1 (Gr. 1) learners living in low socio-economic environments in Mangaung, Motheo District, Free State Province, South Africa, and to establish whether a significant difference between boys and girls could be observed.

Descriptive statistics, namely frequencies and percentages, were calculated for categorical data, and medians and ranges for numerical data. The prevalence of Gr. 1 learners with possible DCD was determined and described by means of 95% confidence interval (CI). The total number of learners identified either with or without DCD, further separated into boys and girls in both groups, was determined. The learners were compared per gender by means of the chi-square test, or when necessary the Fisher’s exact test for small samples, for categorical data. A probability level of 0.05 or less (p ≤ 0.05) was accepted to indicate statistical significance.

Learners were recruited after approval from the provincial Department of Basic Education and the Health Sciences Research Ethics Committee (UFS-HSD2017/1363) at the University of the Free State was obtained. The headmasters of each school and the parents or legal guardians of the learners completed an informed consent form and gave permission for their child to participate in the study. The learners agreed to take part by completing an assent form.

The learners agreed to take part by completing an assent form. The MABC-2 Performance Test was conducted by 11 trained movement specialists. All movement specialists underwent extensive training that included a minimum of 8 hours preparatory training and at least 6 hours of in-field training. To guarantee consistency within the study, each movement specialist conducted one subtest item. Testing took place during school hours in the second term and was conducted over a period of one month. The parents of the learners were provided with a feedback report regarding their child’s motor proficiency results as well as exercises to address the problem, if necessary. The hard copies of each learner’s data sheets were stored in a locked safety cabinet by the principal investigator. The electronic data on the computer were stored by using a protective password, which can only be accessed by the principal investigator.

Table 2 displays the frequency distribution of the total sample in terms of gender and age. In total, 242 Gr. 1 learners participated in the study, with the group being composed of an approximately equal number of boys and girls. The majority of the learners were 6 years of age (n = 174; 71.9%). The median age was 6.66 years (range 6.0–8.75 years).

Table 3 displays the results according to the percentile cut-off values of the MABC-2. In total, 90.1% of the learners (n = 218) fell in the group above the 15th percentile, which identified them within the non-DCD group, whereas 9.9% of the learners (n = 24) scored equal or below the 15th percentile, indicating possible DCD. With regard to gender, the percentage of boys with possible DCD was similar to the girls (10.5% and 9.3%, respectively). The 95% CI for the prevalence of DCD is further illustrated in Table 3.

Table 4 shows the distribution of the total group of learners within the three MABC-2 subtests, with 27.7% of learners’ scores for manual dexterity indicating possible DCD, opposed to their scores for aiming and catching (5.0% of learners) and balance (8.7% of learners). Of the total group, 72.3% fell in the non-DCD group for manual dexterity, 95.0% for aiming and catching and 91.3% for balance. The results indicated that the learners struggled more with the fine motor component of the MABC-2 performance test.

In Table 5, the differences between boys and girls with possible DCD are shown for the total test score and the individual MABC-2 subtests. No statistically significant differences between the boys’ and girls’ scores on the total test score (p = 0.9439) and the different subtests were observed (manual dexterity, p = 0.26; aiming and catching, p = 0.16; balance, p = 1.0).

The aim of this study was to determine the prevalence of possible DCD in Gr.1 learners between the age of 6 and 8 years, living in low socio-economic environments in the Motheo District of Mangaung, South Africa, and compare the findings of boys and girls participating in the study. To the authors’ knowledge, this is the first study to assess the prevalence of possible DCD in the low socio-economic environment in Mangaung, which adds to the limited information on the prevalence of possible DCD in South Africa as a whole, especially with regard to low socio-economic environments. Consequently, comparison of this study with previous research on the prevalence of DCD in low socio-economic environments was restricted.

In this study, 9.9% of Gr. 1 learners were identified with possible DCD, and according to the parents, there was no medical DCD diagnosis before. Research in different countries, such as Israel (Engel-Yeger, Rosenblum & Josman 2010) and Brazil (Valentini et al. 2015), found a high prevalence of possible DCD in low-income families and socio-economic environments. Research conducted by Prinsloo and Pienaar (2003) in the North West Province of South Africa in a low socio-economic environment, supported these findings and indicated a low occurrence of DCD in 7- to 8-year-old learners. In addition, a more recent study in the same province indicated that the prevalence of possible DCD in a low (38.7%) and high (40.9%) socio-economic environment was similar (Venter et al. 2015).

However, when using the 5th percentile as cut-off score for severe DCD with the MABC-2 performance test, it was noted that the high socio-economic environment had a higher incidence (22.7%) than the low socio-economic environment (3.2%) (Venter et al. 2015). Furthermore, another study in the North West Province identified 429 of 645 learners (10–12 years) with possible DCD when using the MABC-2. In addition to Venter et al. (2015), Cloete et al. (2006) reported that the lower the socio-economic environment, the lower the MABC scores. Therefore, it is clear that conflicting results regarding possible DCD in socio-economic environments may be found.

Delgado-Lobete et al. (2019) were of the opinion that the difference in the prevalence rates of DCD depended on the assessment used to identify and/or diagnose DCD. Previous research found results that were similar to those in this study by making use of the DSM-4 and/or DSM-5 and considering only one of the criteria. These findings are summarised in Table 6, and a comparison of the findings of this study with previously reported findings on studies where the socio-economic status of the participants had not been indicated is shown.

Hua et al. (2014) used all four criteria of the DSM-4 with 3–6-year-old learners from China and reported similar results (8.9%) compared with those in this study (9.9%). However, Lingam et al. (2009) indicated a very low prevalence of 1.8% when conducting a large cohort study of learners between 7 and 8 years of age in the United Kingdom. From the literature it is clear that findings vary extensively, even when the full DSM-5 criteria have been applied. It is furthermore important to note the discrepancies in the literature with regard to research conducted in South Africa where no socio-economic environment has been stated. Although De Milander et al. (2014) indicated that 12–15% of 6–8-year-old learners in Bloemfontein could have possible DCD, a very low incidence (1.6%) was reported in Gr.1 learners by Pienaar and Kemp (2014) in the North West Province, South Africa.

With regard to gender, the prevalence of DCD in this study indicated no statistically significant differences (p = 0.9439) between boys (10.5%) and girls (9.3%), showing a boy-to-girl ratio of 1:1. Similar results were reported by Cairney et al. (2005) and Dewey et al. (2002), where no differences between 12- and 14-year-old boys and girls were reported. Comparable findings of a study on Italian learners were reported (Alesi et al. 2019). On the contrary, Delgado-Lobete et al. (2019) indicated that the prevalence of DCD among boys was higher than in girls (16.2% and 8.6%, respectively). Similar to Delgado-Lobete et al. (2019), Gillberg (2003) reported a boy-to-girl ratio of 3–5:1, although Carslaw (2011) found an even higher boy–girl ratio of 9:1. These studies provided evidence of a higher prevalence of DCD in boys than in girls. Research conducted in South Africa showed results that were contrary to this study. Pienaar and Lennox (2006) found a boy–girl ratio of 2–6:1 in a North West Province study, and De Milander et al. (2014) found a boy–girl ratio of 1.6:1 in Bloemfontein. In addition, another study in the North West Province found that mostly girls were identified with possible DCD (Venter et al. 2015).

It has been reported that boys were at greater risk for DCD than girls (Wade & Kazeck 2018), and girls outperformed boys with regard to their overall motor proficiency (Pienaar & Kemp 2014). Amador-Ruiz et al. (2018), however, argued that the occurrence of DCD could be influenced by the tool used to evaluate the learners. Boys tend to be more skilful with ball activities, which increases their aiming and catching performance, whereas girls perform better on fine motor skills (Cardoso & Magalhães 2009). Furthermore, it has been suggested that factors such as cultural differences might have an impact on motor skill abilities (Blank et al. 2012), and also socio-demographic variables (Delgado-Lobete et al. 2019), and should be considered before evaluating a learner for possible DCD.

Disadvantaged educational, social and family circumstances are one of the main reasons for low socio-economic conditions in South Africa and could contribute to a lack of motor skill proficiencies and experience (Isaacs-Martin 2015; Narsai et al. 2013; Pappin et al. 2015; Pienaar & McKay 2014). Tsiotra et al. (2006) concluded that lifestyle differences, such as neighbourhood, environment and culture, should be taken into account when identifying motor skill difficulties or possible DCD. Barba et al. (2017) and Valentini et al. (2015) supported the argument of Tsiotra et al. (2006), confirming that a low socio-economic environment and family status are risk factors for DCD and increase the risk for motor skill difficulties.

The prevalence of DCD among Gr. 1 learners in low socio-economic environments in the Motheo District of the Free State Province is high in comparison with previously reported South African findings. This finding highlights the need to identify learners as early as possible and enhance motor competencies to prevent further motor skill difficulties. Screening tools for the identification of possible DCD, such as the MABC-2 Checklist and the DCDQ’07, should be investigated in low socio-economic environments to increase early identification to assist these learners. Although it has been found that the prevalence of DCD may be higher among boys, the difference in gender ratio has been reported in recent studies to be decreasing. Although socio-economic status might be a reason for a higher prevalence of DCD, limited research has been conducted in South Africa. Given the contradicting prevalence of DCD in this study and other studies in South Africa, it is clear that the prevalence of DCD in South Africa, especially with regard to low socio-economic status, is unknown and not fully identified, warranting further research in this area. Furthermore, it is important to make use of all four criteria of the DSM-5 when identifying DCD and ensure early identification to establish timely intervention. Finally, it is important to evaluate the role that socio-economic situations play on the development of DCD in learners.

This study increased our knowledge of the importance to establish the prevalence of DCD in all provinces of South Africa to ensure a thorough knowledge of the occurrence of this disorder. Furthermore, increased awareness of prevalence of DCD in South Africa can assist in treating this disorder at an earlier stage by means of appropriate interventions. These interventions will contribute to improved motor proficiency levels in learners necessary for activities of daily living in addition to the school environment. Lastly, increasing the awareness of DCD in South Africa, especially in low socio-economic environments, increases our ability to attend to this disorder in future by means of implementing strategies for teachers to improve learners’ motor abilities.

Although the research was performed on a randomly selected sample, only one province and one district in South Africa were included in the study. Therefore, the findings could not provide a comprehensive reflection of the actual prevalence of possible DCD in all the low socio-economic environments of South Africa. It is therefore recommended that a larger sample group should be used in other parts of low socio-economic environments in South Africa to further investigate the prevalence of possible DCD.

It has to be noted further that DCD studies within various socio-economic environments are limited, and therefore, the results of this study could not be used to make comparisons or evaluate differences. Furthermore, it should be kept in mind that the daily living activities of the learners in this study could not be established and was therefore a limitation. It is probable that several learners with possible DCD in this study might have a functionality challenge at home, but because of the language challenge parents were not able to complete a standardised questionnaire such as the DCDQ’07 and the MABC-2 checklist.

Lastly, criteria C and D of the DSM-5 were assessed by using feedback from parents and did not follow the recommendations of the EACD by making use of a medical doctor to ensure that physical and neurological disorders were not present, as well as a psychological evaluation to confirm that cognitive and intellectual problems were absent. Although limitations were recognised in the present study, the opportunity was created to evaluate more learners and establish the extent of DCD in learners living in low socio-economic environments.