Article
Spatial Accuracy and Variability in Dart Throwing in Children
with Developmental Coordination Disorder and the Relationship
with Ball Skill Items
Faiçal Farhat 1, Achraf Ammar 2,3,4,5,* , Nourhen Mezghani 6, Mohamed Moncef Kammoun 1,2,
Khaled Trabelsi 1,2 , Haitham Jahrami 7 , Adnene Gharbi 2,8 , Lassad Sallemi 1,2, Haithem Rebai 2,9,
Wassim Moalla 1,2 and Bouwien Smits-Engelsman 10,11
1 Research Laboratory: Education, Motricity, Sport and Health, EM2S, LR19JS01, High Institute of Sport and
Physical Education of Sfax, University of Sfax, Sfax 3000, Tunisia; faical.farhat@isseps.usf.tn (F.F.);
moncef.kammoun@isseps.usf.tn (M.M.K.); khaled.trabelsi@isseps.usf.tn (K.T.);
lassadsallemi@gmail.com (L.S.); wassim.moalla@isseps.usf.tn (W.M.)
2 High Institute of Sport and Physical Education of Sfax, University of Sfax, Sfax 3000, Tunisia;
adnenegharbi@yahoo.fr (A.G.); haithem.rebai@isseps.usf.tn (H.R.)
3 Department of Training and Movement Science, Institute of Sport Science, Johannes-Gutenberg-University Mainz,
55122 Mainz, Germany
4 Research Laboratory, Molecular Bases of Human Pathology, LR19ES13, Faculty of Medicine of Sfax,
University of Sfax, Sfax 3000, Tunisia
5 Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology: Physical Activity, Health and
Learning (LINP2), UFR STAPS, UPL, Paris Nanterre University, 92000 Nanterre, France
6 Department of Sport Sciences, College of Education, Taif University, Taif 21974, Saudi Arabia;
nsmezghanni@tu.edu.sa
7 College of Medicine and Medical Science, Arabian Gulf University, Manama 293, Bahrain; hjahrami@health.gov.bh
8 Physical Activity, Sport and Health Research Unit, National Observatory of Sport, Tunis 1003, Tunisia
9
Citation: Farhat, F.; Ammar, A.; Sports Performance Optimization Research Laboratory (LR09SEP01), National Center for Sports Medicine
Mezghani, N.; Kammoun, M.M.; and Science (CNMSS), Tunis 1003, Tunisia
10 Physical Activity, Sport and Recreation, Faculty Health Sciences, North-West University,
Trabelsi, K.; Jahrami, H.; Gharbi, A.;
Potchefstroom 2520, South Africa; bouwiensmits@hotmail.com
Sallemi, L.; Rebai, H.; Moalla, W.; et al. 11 Department of Health and Rehabilitation Sciences, University of Cape Town, Cape Town 7925, South Africa
Spatial Accuracy and Variability in * Correspondence: acammar@uni-mainz.de
Dart Throwing in Children with
Developmental Coordination
Abstract: The present study aimed to examine precision and variability in dart throwing performance
Disorder and the Relationship with
and the relationships between these outcomes and bouncing, throwing and catching tasks in children
Ball Skill Items. Eur. J. Investig. Health
Psychol. Educ. 2024, 14, 1028–1043. with and without DCD. Children between the ages of 8 and 10 years (n = 165) were classified
https://doi.org/10.3390/ according to results obtained on the Movement Assessment Battery for Children (MABC-2) and
ejihpe14040067 divided into three groups: 65 children with severe DCD (s-DCD), 45 with moderate DCD (m-DCD)
and 55 typically developing children (TD). All children performed the dart throwing test and the
Academic Editor: Francisco
ball skill items of the Performance and Fitness Test (PERF-FIT). The accuracy and variability of dart
Manuel Morales Rodríguez
throwing tasks were significantly different between TD and s-DCD (p < 0.01), and also between
Received: 2 February 2024 m-DCD and s-DCD (p < 0.01). Participants with s-DCD were also found to perform significantly
Revised: 26 March 2024 worse on all PERF-FIT ball skill items than m-DCD (p < 0.001), and m-DCD were significantly poorer
Accepted: 9 April 2024 than TD (p < 0.001). The dart score and coefficient of variation of the long-distance task appear to be
Published: 16 April 2024 significant predictors for the ball skills and explain between 24 to 29% of their variance. In conclusion,
poor results in aiming tasks using darts in children with DCD corroborate with the explanation of
deficits in predictive control since the tasks require ballistic movements.
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland. Keywords: children; developmental coordination disorder; motor skill-related fitness; ball skills;
This article is an open access article dart throw; task difficulty
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Eur. J. Investig. Health Psychol. Educ. 2024, 14, 1028–1043. https://doi.org/10.3390/ejihpe14040067 https://www.mdpi.com/journal/ejihpe
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1029
1. Introduction
Children with developmental coordination disorder (DCD) exhibit slow, effortful,
imprecise, and ill-coordinated movements and are more depended on visual information [1].
The leading hypothesis that best explains motor coordination and skill learning deficits is
that children with DCD have difficulties with predictive motor control [2]. In this context,
studies examining predictive motor control, such as adaptations in grip force, anticipatory
postural adjustments, and predictive control of eye movements, have shown that motor
outcome prediction is impaired in children with DCD [2]. In addition to children with
DCD having less accurate, slower, and more variable motor performance [3], they also have
difficulties visually tracking moving objects [4], which is particularly important in active
playground games using balls, such as catching a ball or aiming [2].
The deficits in predictive control in children with DCD can manifest as problems with
fine and gross motor skills such as throwing and catching a ball, a set of skills that children
with DCD have considerable difficulty with [5]. Proficient ball skills are essential because
playground games and physical education classes often include aiming, throwing and
catching activities [6]. Indeed, problems with coordination in children with DCD often
restrict them from executing functional skills, which are needed for effective participation in
sports and leisure activities [7,8]. These difficulties with motor control during ball catching
lead to a large number of aiming and catching errors [9].
Motor control theories state that when an action is planned, the motor parameters
related to that action such as the trajectory, speed, and required precision are represented as
an internal model [10]. Internal models contribute to efficient, accurate and smooth motor
performance, limiting the requirement for the motor system to depend on slower varieties
of feedback-based control to correct the movement [11]. This ability permits children to
anticipate movement results, determine the required control functions and achieve desired
outcomes such as distance, timing and force [12]. Children with DCD have a limited ability
to utilize internal models for motor control [13]. Jucaite et al. [14] reported that postural
and manual forces could not be scaled in either the temporal or amplitude domains in
children with DCD. Their study demonstrated that children with DCD modified their grip
forces but exhibited temporal delays in the corresponding postural adaptations. Impaired
force control was shown to be related to timing [15] and fine-tuning of the force [16]. In
this context, Smits-Engelsman et al. [17] also showed that children with DCD produced
more variable force trajectories than controls did.
In clinical practice, ball skills are typically measured using tests such as M-ABC [18]
and BOT [19]. Standardized tests assess ball skills in a very predictable context, which
makes the tests reliable but more distant from real-world ball games where trajectory
prediction is one of the determining factors [20]. The spatial and temporal accuracy of the
movement patterns are crucial because the hands (thus the body) must catch and throw
the ball at the right time and place, or release a ball or dart with the right precision. This
requires motor control, which refers to an adaptive process of the variables given the motor
pattern, such as force, speed, and timing [4]. The recently developed Performance and
Fitness test (PERF-FIT) contains repetitive bouncing and catching, throwing and catching
items, where children can move freely around and adapt their body position when needed
based on available feedback [21].
A task in which fine-tuning of a skilled open-loop-controlled motor action can be
tested is throwing darts. For throwing movements including darts, control is related to
both the target distance and mass of the object manipulated. Likewise, in the current study,
dart throwing requires more end point precision than bouncing and catching, throwing
and catching, or a throw for distance (explosive power). On the other hand, less precise
executed bouncing or throwing movements could still be corrected for if hand and body
movements are adapted fast enough to the throwing error so the ball can still be caught,
while error correction is not possible once the dart has been released from the hand. Hence,
these tasks have both similarities and differences from a motor control perspective.
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1030
Many aspects of motor control and executive function determine the success of an
aiming movement. Darts are thrown overarm, with forward movement of the arm, mainly
elbow extension, but this also requires an adequate throwing position. The adjustment of
the movement properties (direction and velocity) and the temporal accuracy of the grip
opening during the hand’s forward movement to release the dart will regulate where it
lands. Moreover, these parameters need to be adapted with respect to the external frame of
reference defined by the target board. Hence, dart throws include, in addition to the ability
to process information to create the right movement pattern, the ability to grade forces with
extreme precision [22]. Thus, when throwing a dart or a ball, the online configuration of
several joints (i.e., shoulder, elbow, and wrist) must be monitored during the movement to
identify when the arm is in the right position to release the object.
In the present study, we investigated dart throwing as a typical example of an open-
loop (ballistic) aiming task, hence requiring predictive control. Predictive control is based
on prior knowledge of the dynamics of moving arms and the internal disturbances caused
by arm movements upon the body. The anticipated variables (such as force, timing, and
changes in visual input) are based on acquired associations between output signals and their
effects on effectors during repeated practice or experience [23]. Based on this knowledge,
the central nervous system can correctly program anticipatory postural adaptations [24].
Most studies comparing movement accuracy in children with DCD have used tasks where
visual correction during movement execution is possible. For instance, it has been found
that when children with DCD move toward a target in visually guided aiming movements,
they make considerable endpoint errors and have less fluent movement profiles than their
well-coordinated peers [16]. Importantly, in these visually guided aiming movements,
children may choose to move more slowly to be more accurate, which is not an option in
dart throwing. However, vision still plays an important role in a dart throw task. To hit a
specified target with a dart, movement parameters, which are determined in a body-related
frame of reference, must be calibrated relative to an external frame of reference. Generally,
vision establishes the link between these various points of reference [25].
To our knowledge, no empirical study has investigated the differences between chil-
dren with DCD and TD children in terms of throwing darts and ball skills. In these skills,
children must manipulate different objects (darts and balls) with different strategies under
various motor control conditions. Therefore, the purpose of the present study was to
examine the precision and variability of dart-throwing performance and the relationships
between these outcomes and ball skills, which have aiming and catching components, in
children with and without DCD.
Based on previous studies, we hypothesized that, compared with TD children, chil-
dren with DCD would be less accurate (as measured by the dart score) and have greater
variability (as measured by the coefficient of variation or CV) in performing a dart task.
We also expected that this difference would be greater in the more difficult version of the
task (standing further away from the target) and greater in the severe DCD group than in
the moderate DCD group and TD children. Moreover, moderate correlations are expected
between the dart outcomes and the ball skill-related activities of the PERF-FIT because they
only partly share a common underlying construct (aiming or throwing at a target) and
control modes (predictive versus online control).
2. Materials and Methods
2.1. Procedure
The protocol and study design were approved by the Ethical Committee of the Uni-
versity Hospital of Sfax, Tunisia (CPP SUD N◦ 0301/2021). Children were tested at their
schools. After a full explanation of the procedure and prior to testing, all the parents
provided written consent and signed child assent forms. Twelve assessors received 10 h
training on all the outcome measures. Children’s length and weight were measured before
testing. All tests were administered at a maximum of one week apart. Administration of the
MABC-2 took approximately 25–35 min. The PERF-FIT required approximately 25–45 min.
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1031
The dart throwing test took 15–25 min. Before scoring, each test item was explained to the
child, demonstrated, and practiced according to the manuals.
2.2. Participants
To select the participants, teachers and parents were asked to identify children with
motor coordination problems based on their observations on the playground, in class or at
home. Children with DCD were classified using the four DSM-5 criteria [26]. All the chil-
dren aged 7 to 10 years with an MABC-2 score at or below the 16th percentile (Criterion A);
identified by a parent or teacher as having a motor coordination impairment (Criterion B);
whose parents noted difficulty throughout the early developmental period (Criterion C);
where no medical condition or comorbidity known to interfere with motor abilities was
noted; and whose teacher confirmed the absence of intellectual or cognitive disability
(Criterion D) appeared to meet the DCD criteria. Through this procedure, 110 children with
DCD were selected to participate in this study. These children were age- and sex-matched
at a 2:1 ratio, with 55 TD children from the same grade. TD children were recruited from
the same classes in the school as the children with DCD were. No additional developmental
conditions such as attention deficit hyperactivity disorder, dyslexia, or autism spectrum
disorder were reported in any of the groups.
The inclusion criteria for the TD children were as follows: (1) no evidence of functional
motor problems as observed by their teacher or parent, (2) a score above the 16th percentile
on the MABC-2, (3) no diagnosis of a significant medical condition as reported by a parent
and (4) the absence of intellectual or cognitive impairment as confirmed by their teacher.
Based on their MABC-2 scores, the children with DCD were divided into moderate DCD
(n = 45) and severe DCD (n = 65) groups to examine the impact of DCD on the severity of
motor deficiencies.
2.3. The Movement Assessment Battery for Children-2 (MABC-2)
All the children completed the MABC-2 age band 2 (7- to 10-year-old children). The
MABC-2 test was used to measure motor coordination [18] and to confirm DSM-5 Criterion A
for DCD. The MABC-2 test consists of eight items that are evaluated on three different com-
ponents: manual dexterity, aiming and catching, and balance. A percentile score of five or
less indicates severe motor problems (we will refer to this group as severe DCD or s-DCD),
while a score between 9 and 16 suggests that the child is at risk of having movement difficul-
ties (we will refer to this group as moderate DCD or m-DCD), and a score > 16th percentile
indicates normal motor performance. The MABC-2 test has demonstrated good validity
and test–retest reliability, with ICC values ranging from 0.92 to 0.98 [26].
2.4. Performance and Fitness Test (PERF-FIT)
The PERF-FIT is a functional measure of motor skill-related fitness in children [27].
The PERF-FIT is the first standardized test to establish norms for African children and is
an affordable testing tool for low-resource areas. The test is suitable for this age group
(elementary school children). The items of the PERF-FIT were designed to be used through-
out the full age range. The PERF-FIT has good structural and ecological validity, excellent
content validity, and good reliability [28,29].
The PERF-FIT consists of two subscales. The power and agility subscale comprise
three agility items (running, stepping, and side jumping) and two explosive power items
(overhead throw and standing long jump). The motor skills performance subscale contains
five series of tasks with increasing difficulty: (1) bounce and catch ball (2), throw and catch
ball, (3) static balance and dynamic balance, (4) jumping, and (5) hopping. For this study,
only the ball skills items and the explosive power overhead throw were used because of
their expected relationship with the dart task and M-ABC. In an earlier study, throwing
and bouncing item series of the PERP-FIT were low to moderately related to the MABC-2
aiming and catching score [21].
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1032
2.5. Dart-Throwing Test
The dart throwing test started after the initial training period. This training period
included 15 darts thrown in five blocks of three from two distances (2.37 and 3.56 m) [30].
The task was to throw the darts as close to the bullseye as possible. The two distances
were marked by a line on the floor. The test runs consisted of six throws at each of the
two distances, in a randomized order; the height of the official dartboard was placed on
a wall so that its center was at eye level for each child. The children were required to
maintain the same throwing technique in both conditions.
Score Calculations
The throw was scored depending on its position on the board (0–10). A dart that
missed or bounced off the board received a score of zero. The target consisted of a series of
10 concentric rings. Two outcomes were used to measure the accuracy and consistency [31].
The first was the mean score of the six throws. This score can range from zero (all misses)
to ten (all bullseye); it can be considered a measure of accuracy, with a high score indicating
high accuracy. The second measure of performance was the coefficients of variation (CV) of
the score: SD score/mean score, a lower coefficient indicating a higher consistency.
2.6. Statistical Procedure
All variables were examined to determine whether the distributions were normal or
skewed. No outliers were present in the data. ANOVA was used to test for differences in
demographic variables among the three groups. The chi2 test was used to determine the
sex distribution across groups.
Repeated measures ANOVA were used to examine the effect of tasks (within subject: short
and long distance) and group (between subject: TD, m-DCD, s-DCD) and possible interactions.
One-way ANOVA was used to examine differences between the three groups on the PERF-FIT
measures. A post hoc test with Bonferroni correction was used if main effects for group or
interactions were found. The magnitude of the differences per group was determined using
Cohen’s d-values of 0.5 (moderate effect size) and 0.8 (large effect size) [32].
To test for task specificity of throwing skills, Pearson’s correlations were calculated to
assess the relationships between MABC-2 aiming and catching scores, PERF-FIT ball skill items
(raw scores) and dart throw performance. A stepwise multiple regression analysis was used to
determine the best set of predictor variables (dart outcomes) for the ball skill items.
The significance level was set at p < 0.05. All the statistical analyses were conducted
using the Statistical Package for the Social Sciences software (SPSS, version 28.0; SPSS, Inc.,
Chicago, IL, USA).
3. Results
3.1. Participants
The anthropometric data of the two DCD groups and the control group are shown in
Table 1. Significant differences in weight and body mass index were found between groups
(p < 0.001). Post hoc tests showed that the TD group was different from the DCD group,
but the m-DCD and s-DCD groups were not different in weight or BMI. There were no
significant group differences in age or height (p > 0.05). Differences in the total and subscale
scores on the MABC 2 between the groups are also shown in Table 1. The sex distributions
of the three groups were comparable (Chi2 1.19, p = 0.55) (Table 2).
Table 1. Demographic and background information of the three groups (TD, m-DCD and s-DCD).
s-DCD (n = 65) m-DCD (n = 45) TD (n = 55) Statistics
Mean SD Mean SD Mean SD F-Value p-Value
Age (years) 9.05 0.82 8.93 0.86 9.07 0.84 0.38 0.68
Height (m) 1.38 0.06 1.38 0.06 1.39 0.07 1.27 0.28
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1033
Table 1. Cont.
s-DCD (n = 65) m-DCD (n = 45) TD (n = 55) Statistics
Mean SD Mean SD Mean SD F-Value p-Value
Weight (kg) 38.3 4.47 34.3 4.93 31.8 4.54 30.45 <0.001
BMI (kg m2) 20.03 1.18 17.62 2.95 16.25 1.25 30.96 <0.001
Total Standard Scores 3.7 0.8 6.4 0.5 9.60 1.1 711.35 <0.001
Manual Dexterity 5.0 1.2 7.4 0.9 9.4 1.0 265.19 <0.001
Aiming and Catching 5.1 1.3 7.2 0.9 10.1 1.4 252.52 <0.001
Balance 4.8 0.9 7.1 0.9 9.5 1.2 58.41 <0.001
SD = standard deviation, TD = typically developing, m-DCD = moderate DCD, s-DCD = severe DCD.
Table 2. Gender distribution over groups (no significant differences).
Group n % Boys % Girls
TD 55 49.1 50.9
m-DCD 45 57.8 42.2
s-DCD 65 47.7 52.3
Total 165 50.9 49.1
TD = typically developing, m-DCD = moderate DCD, s-DCD = severe DCD.
3.2. Dart Throw Measurements
Dart Scores: Table 3 reports the means and standard deviations for the TD and the
DCD groups on dart scores and effect sizes.
Table 3. Means (M) ± standard deviations (SD) for the dart scores and effect sizes for the total
differences (eta squared) between the 3 groups and pair-wise comparison (Cohen’s d).
s-DCD (n = 65) m-DCD (n = 45) TD (n = 55) 3 Groups TD/m-DCD TD/s-DCD m-DCD/s-DCD
Mean SD Mean SD Mean SD Eta Squared Cohen’s d Cohen’s d Cohen’s d
Dart Score Short 2.87 0.39 3.70 0.63 4.15 0.79 0.45 0.62 2.11 1.64
Dart Score Long 2.30 0.38 3.36 0.45 3.49 0.59 0.58 0.25 2.44 2.58
SD = standard deviation, TD = typically developing, m-DCD = moderate DCD, s-DCD = severe DCD.
A repeated measures ANOVA revealed a significant main effect of group for dart
scores (F(2, 162) = 95.29, p < 0.001; Figure 1). Additionally, a large main effect of task was
found, showing that the 50% greater distance led to darts landing less close to the target
(F 1,162 = 275.91, p < 0.001). Importantly, the statistical analysis revealed a significant
interaction effect between group and task for dart score (F (2, 162) = 8.05, p < 0.001). Indicating
that the groups responded differently in the task conditions.
Post hoc analysis revealed that for the short-distance comparisons, dart score was
significantly different between the TD- and m-DCD, TD and s-DCD, and m-DCD and
s-DCD (all p ≤ 0.001). However, for long distance, the dart score was not different between
the TD and m-DCD groups (p = 0.52) but only for the comparisons between TD and s-DCD
(p < 0.001), and m-DCD and s-DCD (p < 0.001).
Coefficient of variation: Table 4 reports the means and standard deviations for the
TD and the DCD groups on CV and effect sizes. A repeated measures ANOVA revealed
a significant main effect of group for variability (F (2, 162) = 56.18, p < 0.001) (Figure 2).
Additionally, a large main effect of task was found, showing that the greater distance led to
more variability (F (1, 162) = 55,16, p < 0.001).
Moreover, the statistical analysis revealed significant interaction effects between group
and task for variability (F (2, 162) = 13.25, p < 0.001). Post hoc analysis of the CV showed that
TD and m-DCD did not differ either for the short- (p = 0.52) or for the long-distance tasks
(p = 0.33). The other post hoc comparisons for CV between TD and s-DCD and m-DCD and
s-DCD were significantly different (p < 0.001).
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dtaisstka cnocmeptaasrekdc toom thpea srheodrtt oditshtaensche.o The s-DCD group is poorest in the task. For the short-distance score, differences between TD and s-DrtCdDis, tTaDn caen.dT mh-eDsC-DDC, aDndg mro-uDpCiDs panodo rse-DstCiDn tahree stiagsnki.ficFaonrt the short-
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s-DCD = severe DCD, m-DCD = moderate DCD, TD = typically developing.
Table 3. Means (M) ± standard deviations (SD) for the dart scores and effect sizes for the total dif-
Tfearbelnece4s. (eMta esaqnuasr(eMd) )b±etwseteann dthaer d3 gdroeuvpiast aionnds pa(SirD-w) ifsoe rcotmhepaCriVsonsc (oCroehseann’sd d)e. ffect sizes for the total
  s-DCD (n = 65)d  ifmfe-rDeCncDe s(n( e=t a45s)q  uaTrDed (n)  b=e 5t5w) een the3 3Ggrorouupps s anTdDp/ma-iDr-wCDis e cToDm/ps-aDriCsoDn  (mC-oDhCeDn’/s-dD)C. D 
  Mean  SD  Mean  SD  Mean  SD  Eta Squared Cohen’s d    Cohen’s d  Cohen’s d 
Dart Score Shorts -D2.8C7D  (n =0.3695 ) 3.m70- DCD0(.n63=  45) 4.15T D (n =05.759)  0.435 Groups 0.62  TD/m-D2C.D11  TD/s-1D.6C4 D m-DCD/s-DCD
Dart Score LongM  2e.a3n0  S0.D38  3.M36e  an 0.4S5D  3.49M  ean 0.5S9D  0.5E8t a Square0d.25  Cohen’s2d.44  Cohe2n.’5s8d  Cohen’s d
CV Short 0.64 0.22 SD =0. 4st4andard0 d.1e7viation0, .T3D9  = typ0i.c1a8lly dev0e.2l7oping, m-DCD− =0 m.3o0derate DCD−,1 s.2-D9CD = seve−re1 .03
CV Long 0.81 0.19 DCD0..4 9 0.17 0.43 0.19 0.47 −0.33 −1.97 −1.73
Eur. J. Investig. Health Psychol. Educ. 2024, 14, x FOR PEER REVIEW  8 
  SD =Csotaenffidacridendt eovfi vatairoina,tioTD = typicallyCV = coefficient of variation. n: Table 4 repo
dretsv ethloep minega, nms -aDnCdD sta=nmdaordde rdaeteviaDtCioDn,s sf-oDrC thDe= TsDev ere DCD,
and  the DCD groups on CV and effect sizes. A repeated measures ANOVA revealed a 
significant main effect of group for variability (F (2, 162) = 56.18, p < 0.001) (Figure 2). Addi-
tionally, a large main effect of task was found, showing that the greater distance led to 
more variability (F (1, 162) = 55,16, p < 0.001). 
Moreover,  the  statistical  analysis  revealed  significant  interaction  effects  between 
group and task for variability (F (2, 162) = 13.25, p < 0.001). Post hoc analysis of the CV showed 
that TD and m-DCD did not differ either for the short- (p = 0.52) or for the long-distance 
tasks (p = 0.33). The other post hoc comparisons for CV between TD and s-DCD and m-
DCD and s-DCD were significantly different (p < 0.001). 
 
 
FFiigguurree 22. .CCooeffiefcfiiecniet notf ovfarviaatriioant iionn thine ttwheo tcwonodcitoionndsi tfioor nthsef othrrtehee gtrhoruepes.g Preorufoprsm. aPnecref oisr mmaornec e is more
variable in the long-distance task. Children with s-DCD are poorest in the task. CV in not different 
vbeatrwiaebelne TinD tahned lmon-DgC-dDis gtraonucpest. aBsukt. dCiffheirlednrceens win ivtharisa-bDilCitDy baertewpeeono TreDs tanind tsh-DeCtaDs,k a.nCd Vmi-nDCnDot  different
and s-DCD are significant (p < 0.001). s-DCD = severe DCD, m-DCD = moderate DCD, TD = typically 
developing, CV = coefficient of variation. 
Table 4. Means (M) ± standard deviations (SD) for the CV scores and effect sizes for the total differ-
ences (eta squared) between the 3 groups and pair-wise comparison (Cohen’s d). 
m-DCD/s-
  s-DCD (n = 65)  m-DCD (n = 45)  TD (n = 55)  3 Groups  TD/m-DCD TD/s-DCD DCD 
  Mean  SD  Mean  SD  Mean  SD  Eta Squared Cohen’s d  Cohen’s d  Cohen’s d 
CV Short  0.64  0.22  0.44  0.17  0.39  0.18  0.27  −0.30  −1.29  −1.03 
CV Long  0.81  0.19  0.49  0.17  0.43  0.19  0.47  −0.33  −1.97  −1.73 
SD = standard deviation, TD = typically developing, m-DCD = moderate DCD, s-DCD = severe 
DCD, CV = coefficient of variation. 
3.3. The PERF‐FIT Measures 
Significant differences in upper extremity muscle power, throwing and catching, and 
bouncing and catching were found between the groups (Table 5). Post hoc analysis also 
revealed that the three groups differed from each other in terms of these skills (p < 0.001). 
The children with s-DCD showed significantly lower scores than the m-DCD children did, 
and the m-DCD children had significantly poorer scores on all items than the TD children 
did; see Table 5 and Figure 3. 
Table 5. Results of the ANOVA for PERF-FIT measures. Data are presented as means (M) ± standard 
deviations (SD)m F and p-values and effect sizes (eta squared) between the 3 groups and pair-wise 
comparison (Cohen’s d). 
s-DCD    m-DCD    TD    m-DCD/s-
  (n = 65)  (n = 45)  (n = 55)  Statistics  3 Groups  TD/m-DCD TD/s-DCD DCD 
Eta Squa-
  Mean  SD  Mean  SD  Mean  SD  F  p-Value red  Cohen’s d  Cohen’s d  Cohen’s d 
Bouncing and   
38.40  1.82  40.60  2.04  42.49  2.36  58.41  <0.001  0.42  0.85  1.96  1.15 
Catching (#) 
Throwing and   
36.02  2.33  39.24  3.23  42.64  2.71  88.09  <0.001  0.52  1.15  2.64  1.18 
Catching (#) 
 
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1035
between TD and m-DCD groups. But differences in variability between TD and s-DCD, and m-DCD
and s-DCD are significant (p < 0.001). s-DCD = severe DCD, m-DCD = moderate DCD, TD = typically
developing, CV = coefficient of variation.
3.3. The PERF-FIT Measures
Significant differences in upper extremity muscle power, throwing and catching, and
bouncing and catching were found between the groups (Table 5). Post hoc analysis also
revealed that the three groups differed from each other in terms of these skills (p < 0.001).
The children with s-DCD showed significantly lower scores than the m-DCD children did,
and the m-DCD children had significantly poorer scores on all items than the TD children
did; see Table 5 and Figure 3.
Table 5. Results of the ANOVA for PERF-FIT measures. Data are presented as means (M) ± standard
deviations (SD)m F and p-values and effect sizes (eta squared) between the 3 groups and pair-wise
comparison (Cohen’s d).
s-DCD m-DCD TD
(n = 65) (n = 45) (n = 55) Statistics 3 Groups TD/m-DCD TD/s-DCD m-DCD/s-DCD
Mean SD Mean SD Mean SD F p-Value Eta Squared Cohen’s d Cohen’s d Cohen’s d
Eur. J. Investig. Health Psychol. Educ. 2024, 14, x FOR PEER REVIEW  9 
  Bouncing and
Catching (#) 38.40 1.82 40.60 2.04 42.49 2.36 58.41 <0.001 0.42 0.85 1.96 1.15
Throwing and
Catching (#) 36.02 2.33 39.24 3.23 42.64 2.71 88.09 <0.001 0.52 1.15 2.64 1.18
OOvevrehrheeaadd Throw  2082.08.0 111.51.5  231.6  .5  2 4.5    90.19  < 0.001  0.53  0.76  2.92  .49 (cTmh)r ow (cm) 231.6 20.5 244.5 13.6 90.19 <0.001 0.53 0.76 2.92 1.49
SD  =  sttaannddaardrdd edveiavtiiaotni,oTnD, T=Dty =p itcyaplliycadlelvye ldoepvineglo, pmi-nDgC, Dm=-DmCoDde =ra mteoDdCeDra, ste-D DCCDD=, sse-vDerCe D C= Dse. #veNrue mber
DofCbDal.l s#c Nauugmht.ber of balls caught. 
 
Figure 3.. BBalall lsksikllisll siteitmems fsofro trheth tehrteher egeroguropus.p Cs.hiCldhrieldn rwenithw sit-hDCs-D CarDe paroeorpeosto raets btoautnbcoinugn caindg 
caantdchciantgc,h  tihnrgo,wthinrogw aindg caantdchciantgc,h aingd, oavnedrhoevaedrh  tehardowth. rLoewf.t sLceafltes  fcoarl ebfoournbcoinugn caindg caantdchciantgc haindg 
tahnrdowthinrogw ainndg acantdchciantgch. iRnigg.hRt isgchaltes cfoarle ofvoerrohveaerdh ethardowth.r oSwco.rSecs oarrees dariffeedriefnfetr ebnettwbeeetwn eTeDn TanDda mnd-
DmC-DDC, TDD, T aDnda ns-dDsC-DD CaDnda anldsoa blseotwbeeetwn es-eDnCsD-D aCnDd amn-dDCmD-D gCroDupg r(opu <p 0(.p00<1)0. .s0-0D1C).Ds -=D sCevDer=e sDevCeDre, 
mDC-DDC,Dm -=D mCoDde=rmateo dDeCraDte, TDDC D= ,tyTpDic=altlyyp diecavlellyopdienvge.l oping.
3.4. Associations between Dart Performance and Ball‐Skill Items 
Moderate correlations were found between dart outcomes and ball skill outcomes. 
See Table 6 and Figures 4 and 5. High correlations for MABC aiming and catching scores 
were expected because these scores are part of the selection criteria for the classification 
of children into groups. For the other ball skills, associations with dart outcomes are in the 
comparable range (0.35–0.50) and are slightly greater for long-distance outcomes. The as-
sociation between explosive power and dart outcomes is remarkable because the two tasks 
have very different accuracy constraints. Results indicate that children who can generate 
more  power  in  the PERF-FIT  overhead  throw  test  also  exhibit  less  variability  in dart 
throws. Aiming a bean bag at a circle on the mat and aiming at the dart board were also 
moderately correlated. 
Table 6. Correlations between darts performance and ball-skill related items. 
Pearson Correlation  Dart Score Short CV Short  Dart Score Long CV Long 
PERF-FIT 
Bouncing and catching  0.36 **  −0.35 **  0.47 **  −0.45 ** 
Throwing and catching  0.39 **  −0.39 **  0.52 **  −0.51 ** 
All children 
n = 165  Overhead Throw  0.38 **  −0.41 **  0.49 **  −0.51 ** 
MABC-2 
Catching  0.41 **  −0.36 **  0.49 **  −0.50 ** 
Aiming    0.42 **  −0.34 **  0.46 **  −0.46 ** 
MABC-2 = Movement Assessment Battery for Children, CV = coefficient of variation. ** p < 0.001 
 
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1036
3.4. Associations between Dart Performance and Ball-Skill Items
Moderate correlations were found between dart outcomes and ball skill outcomes.
See Table 6 and Figures 4 and 5. High correlations for MABC aiming and catching scores
were expected because these scores are part of the selection criteria for the classification
of children into groups. For the other ball skills, associations with dart outcomes are
in the comparable range (0.35–0.50) and are slightly greater for long-distance outcomes.
The association between explosive power and dart outcomes is remarkable because the
two tasks have very different accuracy constraints. Results indicate that children who can
generate more power in the PERF-FIT overhead throw test also exhibit less variability in
dart throws. Aiming a bean bag at a circle on the mat and aiming at the dart board were
also moderately correlated.
Table 6. Correlations between darts performance and ball-skill related items.
Pearson Correlation Dart Score Short CV Short Dart Score Long CV Long
PERF-FIT
Bouncing and catching 0.36 ** −0.35 ** 0.47 ** −0.45 **
Throwing and catching 0.39 ** −0.39 ** 0.52 ** −0.51 **
All children Overhead Throw 0.38 ** −0.41 ** 0.49 ** −0.51 **
n = 165 MABC-2
Catching 0.41 ** −0.36 ** 0.49 ** −0.50 **
Eur. J. InvAesitmig.i nHgealth Psychol. Educ. 2024, 14, x 0F.O42R *P*EER REVIEW   −0.34 ** 0.46 ** −0.46 **
10 
MABC-2 = Movement Assessment Battery for Children, CV = coefficient of variation. ** p < 0.001
Figure 4. Scatterplot showing the association between the coefficient of variation of the dart score 
in the long-distFaingcuertea s4k. Sacnadttethrpeldoti ssthaonwceinthgr tohwe nasisnotchiaetoiovne rbheetwadeethnr tohwe coofetffiheciseanntd obfa vgar(eiaxtpiolons oivf ethe dart score in 
power item of ththeeP  lEoRnFg-FdIiTst)a.nLcaer gtearskv aarniadb itlhitey dcoisitnacnidce sthwriotwh nsh  ionr ttehred oisvtearnhceaodf  therotwhr oowf ,thleea dsaingdbag  (explosive 
to negative corrpeloawtioern ist.eTmD o=f tthyep PicEaRllyF-dFeITv)e.l oLpairngge,r mva-rDiaCbDili=tym coidnecriadtesD wCitDh, ssh-DorCteDr d=isteavnecre oDfC thDe. throw, leading 
CV = coefficienttoo nf evgaaritaivtieo cno. rrelations. TD = typically developing, m-DCD = moderate DCD, s-DCD = severe DCD. 
CV = coefficient of variation. 
Multiple regression (stepwise) was used to find the best set of predictors for the ball
skill-related items. In the first step of the analysis, the regression analysis showed that
BMI is not a significant predictor of dependent variables such as aiming, bouncing and
throwing. Therefore, we did not enter BMI as a possible predictor variable in the reported
 
Figure 5. Scatterplot showing the association between the dart score in the long-distance task and 
the number of points in the throwing and catching task of the PERF-FIT. More precision of the dart 
throws coincides with more caught balls in the throwing and catching task, leading to positive cor-
relations. TD = typically developing, m-DCD = moderate DCD, s-DCD = severe DCD. 
 
Eur. J. Investig. Health Psychol. Educ. 2024, 14, x FOR PEER REVIEW  10 
 
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1037
models. The results are summarized in Table 7. In the first model, all four dart outcomes
were entered as predictors. The dart scores and CV of the short-distance task did not
significantly predict the outcomes of any of the ball skill-related items; therefore, they were
not included in Model 2. The significance probability of Model 2 with only long-distance
outcomes was significant (p < 0.001), indicating that the regression model was suitable.
Furthermore, multicollinearity tests demonstrated that all the indicators had variance
inflation factor (VIF) values less than three, demonstrating that the explanatory variables 
in Model 2 were not highly linearly related. Throwing and bouncing outcomes were best
predicted by aFcicguurrae c4y. Sicnatttherepllootn sgh-odwisitnagn tchee atasssokci(adtiaornt bsectowree)e,na tnhed ctoheeffiCciVen, ta osf tvhaeriasteiocno nodf the dart score in 
predictor, addtehde olonnlyg-daisstmanaclel  ptaesrkc eanntda gthee. dFiosrtatnhcee MthrAowBCn -i2n ittheem osvaeirmheiandg  tahnrodwc aoft cthhien sganadbag  (explosive power item of the PERF-FIT). Larger variability coincides with shorter distance of the throw, leading 
beanbag, variatob inlietgyatiinvet hcoerrdealarttiorness.u TlDts =( CtyVpi)cawllays dtehveelbopeisntgp, rme-dDicCtDor =,  manoddetrhaeted DaCrtDs, ssc-DorCeD = severe DCD. 
added only apCpVro =x icmoeaffitecliyen2t% of. vTahreiastiaomn.e  pattern was observed for the overhead throws.
Figure 5. Scatterplot showing the association between the dart score in the long-distance task and the  
number of pointsFiignuthree t5h. rSocwattinegrpalnodt cshatocwhiinngg ttahsek aosfstohceiaPtEioRnF -bFeItTw. Meeonr ethper edcaisrito sncoofreth ien dtharet ltohnrogw-dsistance task and 
coincides with mthoer encuamugbhert obfa lplsoiinttsh ien tthhreo wthirnogwaingd acnatdc hciantcghtiansgk ,talesakd oinf gthteo PpEoRsiFti-vFeITc.o Mrroerlaet ipornesc.ision of the dart 
TD = typically dtehvreolwops icnogi,nmci-dDeCs Dwi=thm moodreer actaeuDghCtD b,asll-sD iCn Dth=e sthevroewreinDgC aDn.d catching task, leading to positive cor-
relations. TD = typically developing, m-DCD = moderate DCD, s-DCD = severe DCD. 
Table 7. Results of the regression analysis for Model 2.
Dependent Variable Predictor Adjusted R2 in % B t p Model Fit
Throwing (MABC-2) CV long-distance 26.9 −1.97 −2.77 0.006 F 31.2, p <0.001
  Score long-distance 0.60 2.43 0.016
Aiming (MABC-2) CV long-distance 22.9 −1.75 −2.49 0.015 F 25.35, p <0.001
Score long-distance 0.55 2.23 0.027
Bouncing and Catching Score long-distance 22.8 1.09 2.67 0.008 F 25.28, p <0.001
(PERF-FIT) CV long-distance −2.38 −2.11 0.046
Throwing and Score long-distance 28.6 1.61 2.84 0.005 F 33.8, p <0.001
Catching(PERF-FIT) CV long-distance −4.24 −2.58 0.011
CV long-distance 26.7 −27.57 −2.97 0.003 F 31.11, p <0.001
Overhead throw (PERF-FIT) Score long-distance 7.11 2.22 0.028
MABC-2 = Movement Assessment Battery for Children, PERF-FIT = Performance and Fitness Test, CV = coefficient
of variation, B: unstandardized value per variable, t; coefficient t-value. p: Calculated probability of each
independent variable. Model fit: test statistics from the F-test with p-value.
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1038
4. Discussion
Aiming a ball at a target or other person so that it can be caught is a task that includes
components that are common in many leisure and sports activities. Children with DCD
are known to have poor aiming and throwing skills. The causes of the less coordinated
movements in children with DCD are still unclear; only few studies have investigated
ballistic movement precision to an external focus point [33–35], in which the central nervous
system must predict the force and the final position of an object at which it must be released
(predictive control). As hypothesized, compared to TD children, children with s-DCD were
less accurate (as measured by the dart score) and had greater variability (as measured by
the coefficient of variation) in performing a dart task. Children with m-DCD were only
less accurate in the short-distance task. It was also confirmed that the task is harder if the
children are standing further away from the target. Importantly, children with severe and
more moderate coordination deficits differed in terms of the tested tasks, such as precision
throwing (dart) or generating explosive power (overhead throw with a heavy sandbag).
Not many studies looked at differences in performance between children with moderate
and severe DCD. Given that the effect sizes of the differences between m-DCD and s-DCD
indicate large differences (Cohen’s d are larger than 1) on all dart and ball skill items, this
signifies that the cutoff values used for classifying DCD will impact the degree of task
performance on other tasks.
Moderate correlations were found between the dart outcomes and the ball skill-
related activities. The accuracy and variability of the long-distance dart throws explained
approximately 25% of the variability in the ball skill-related activities. Both the correlations
and the regression results indicated that the long-distance task, in which a small initial
directional mistake will have large influence on the endpoint of the dart, best explain the
variance in the ball skills.
4.1. DCD and Aiming
Converging findings indicate that children with DCD make more errors when performing
goal-directed movements [36–38]. In our study, children with s-DCD also showed less accurate
performance in ballistic movements. Whether and where a dart will hit the target depend on
the combination of position, speed and direction of motion at the moment that it is released
from the hand. According to the current study, the performance of children with s-DCD was
significantly poorer for each dart outcome than that of their healthy peers. Children with
m-DCD only differed from TD in the number of times they were able to hit the target in the
short distance task but did not show more variability than their healthy peers.
Aiming with a dart at a target is clearly different from reaching for a target or object. It
has been hypothesized that children with DCD apply compensatory strategies to overcome
difficulties when reaching for an object by changing the initiation of the reaching phase and
grasping phase by a higher degree of both the intra- and interlimb coupling and fixating
the joints [39], as stiffness increases the ease of control [23]. The extra challenge in aiming is
that online correction of the aiming trajectory (dart in flight) is not possible, which increases
the sensitivity to end point errors. The ability to estimate the dynamic position of the
joints involved in the throw is critical for the timing and control of the dart. Children with
s-DCD may have been less able to properly sequence joint rotations, as they are known
to have deficits in kinesthetic information processing [40] and, to some extent, difficulties
integrating perceptual information into action.
The fact that ample explosive power needs to be generated for the dart to cover the
distance to the board can also be concluded based on the relationship with overhead
throw (r = 0.49), as the distance covered was significantly lower in children with DCD
(mean 208 cm for s-DCD and 245 cm for TD). This finding is consistent with previous
studies that indicated a significantly lower performance in upper limb power in children
with DCD [41–43] and a moderate relation (r = 0.50), between overhead throw and distance
thrown with a tennis ball [21].
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1039
In addition, compared to TD children, children with s-DCD had not only a less
accurate performance but also had a greater coefficient of variation. Previous research
reported children with DCD to be less accurate and more variable in their trial-to-trial
performance than their typically developing peers, regardless of the motor-based activity
under scrutiny [44–46]. Several studies have attributed this variability to different sources of
neuromotor noise. Neural variability or noise is present at all stages of sensorimotor control,
from sensory processing and central planning to the outputs of the motor system, leading
to uncertainty about the movement endpoint. Excessive neural noise in the motor system
has been associated with poor motor prediction in children with DCD [23]. Moreover,
Smits-Engelsman et al. [17] showed that children with DCD generate more variable force
than controls. A higher movement variability, lower movement accuracy and longer
movement duration could explain the observed performance problems [47]. Due to this
variability in performance, it will be much harder to distinguish statistical regularity from
all sensory information, leading to impairment in so-called ‘prior’ development, which is
needed for predictive control [48]. Due to inefficient predictive control, they rely heavily
on feedback mechanisms and exhibit slower processing speed and inefficient preparation
for movement [47].
4.2. DCD and Ball Skills
Our results are consistent with previous studies in which Brazilian children with DCD
performed worse on the PERF-FIT ball skill items than their healthy peers [28] Findings from
Schott [49] and Yu et al. [50] also pointed out their disadvantage in object control. Similarly,
we found that children with DCD scored significantly lower on the modified ball catching
item of the Test of Gross Motor Development, examining the movement patterns displayed,
than their peers did [51], as well as on a specifically developed ball catching test [52]. In the
last study, a significant correlation was found between the visual timing task and the ball
catching test in children with DCD. Our study confirmed the relationship between MABC-2
and PERF-FIT ball skills with the dart throwing test, comparable to the low to moderate
interrelations between different ball skills that were reported in earlier studies [41].
Children with DCD were as fast and as accurate as their peers in their initial perfor-
mance of the simple task. However, they were slower and less accurate when performing
complex and novel visual motor tasks [52]. This is in line with our results; the dart scores
and the CV of the more difficult long-distance throws significantly predicted scores on the
ball skill items, while the outcome of the easier task (short distance) did not.
Our results show that the dart scores in the more difficult condition (long distance)
was not different between TD and m-DCD; only differences between TD and S-DCD
and m-DCD and s-DCD were found. This result could be explained by the fact that for
the typically developing children too, the 50% increase in distance from the target made
it more difficult, leading to lower scores for that group (see Figure 1), diminishing the
difference between TD and m-DCD. Importantly large differences were found between
the three groups in all ball skill items. These findings suggest that children with m-DCD
and s-DCD experience difficulties when catching a ball, where online corrections are still
possible [53]. However, longer response times and deficits in visual motor integration
may limit the ability of these children to do so adequately [51]. This finding is in line with
findings that children with DCD also produce larger endpoint errors in visually controlled
upper limb aiming movements [54], which might partly be explained by deficits in visual
pursuit [55]. In accordance with these findings, Miles et al. [56] showed that quiet eye
training improved the ability of children with DCD to focus on a target on the wall prior to
the throw, followed by better anticipation and pursuit tracking of the ball, which in turn
led to improved catching technique.
4.3. Practical Implications
Precision performance difficulties are found to be a defining characteristic of DCD,
the presence of such a marker could be used to offer novel diagnostic avenues to be
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1040
explored in the future. Ensuring that specific attention in future research is allocated to
task requirements when designing experimental tasks will help to continue the exploration
of precision tasks in children with poor coordination. Our results also made clear that the
motor test cut off scores used will lead to studying or treating a different group of children.
Our findings support that the greatest differentiation of children with DCD from their peers
and between severity groups occurs when performing a complex task, like throwing and
catching. Efforts to help children with DCD gradually build up from simple to complex
tasks could potentially bridge the gap between their performance and that of their peers.
Moreover, our findings show that predictive control as needed in ballistic movements
only explains part of the ball skill performance in which online control of body and hand
position is needed to correct inaccuracies in the initial movement.
4.4. Limitations
In children with DCD, the literature seems to indicate that there is a clear association
between visual motor deficits and ball skills. No tests were included to verify this in the
current study. More trials in the dart experiment might have provided information on whether
the accuracy of the children would have improved if more practice was given. Future studies
could also look into eye movements during the dart task. To confirm whether the present
results can be explained by predictive control deficits, anticipatory modulation of muscular
activity during a dart throw needs to be measured in future studies. Insights into the timing
and control of the arm and eye movements are crucial for understanding the differences
between children with and without DCD. The quantitative data (scores and coefficient of
variation) only provide information about the outcomes and do not capture the specific actions
of the shoulders, arms, and hands during the throwing process. Further kinematic studies
could provide explanations regarding the relationship between these factors.
5. Conclusions
The present study showed deficits in aiming at a target, a ballistic movement, in
children with DCD. These children with more severe DCD showed a more variable per-
formance, which was not a feedback-based correction. Deficits were greater when the
children stood further away from the target, where smaller deviations had a greater impact
on the endpoint accuracy. These poor results corroborate the explanation of deficits in
predictive control since the task requires ballistic movements, which are different from
visual-guided goal-directed movements where online sensory feedback can be used to
accurately reach the target or object after the initiation of the movement. Motor ability
influenced the dart task, leading to a more pronounced effect in the s-DCD group and
task-dependent differences between the m-DCD and TD groups. Notably, for all the ball
skills tasks tested, the three groups were evidently different from each other.
Author Contributions: Conceptualization, F.F., W.M., H.R. and B.S.-E.; methodology, F.F., M.M.K.,
A.G., L.S., K.T., H.J., N.M., L.S. and A.G.; formal analysis, F.F., W.M., H.R. and B.S.-E.; writing—original
draft preparation, F.F., A.A., W.M., A.G., H.R., K.T., H.J., M.M.K., N.M., L.S., W.M., H.R. and B.S.-E.;
writing—review and editing, H.R., W.M., A.A. and B.S.-E.; supervision, H.R., W.M., A.A. and B.S.-E.;
project administration, F.F., A.A., W.M., H.R. and B.S.-E.; All authors have read and agreed to the
published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki, and approved by the Ethics Committee of the University Hospital of Sfax, Tunisia
(protocol code CPP SUD N◦ 0301/2021, date of approval: 27 January 2021).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Written informed consent has been obtained from the patient(s) to publish this paper.
Data Availability Statement: Data are available from the first author upon reasonable request.
Eur. J. Investig. Health Psychol. Educ. 2024, 14 1041
Acknowledgments: We acknowledge the support of parents, children, and management of the
participating schools.
Conflicts of Interest: The authors declare no conflicts of interest.
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