Searching for cognitively optimal challenge point in physical activity for children with typical and atypical motor development

Accepted Manuscript

Searching for cognitively optimal challenge point in physical activity for children withtypical and atypical motor development

Caterina Pesce, Claudia Crova, Rosalba Marchetti, Ilaria Struzzolino, Ilaria Masci,Giuseppe Vannozzi, Roberta Forte

PII: S1755-2966(13)00030-6

DOI: 10.1016/j.mhpa.2013.07.001

Reference: MHPA 115

To appear in: Mental Health and Physical Activity

Received Date: 28 December 2012

Revised Date: 18 June 2013

Accepted Date: 5 July 2013

Please cite this article as: Pesce, C., Crova, C., Marchetti, R., Struzzolino, I., Masci, I., Vannozzi,G., Forte, R., Searching for cognitively optimal challenge point in physical activity for children withtypical and atypical motor development, Mental Health and Physical Activity (2013), doi: 10.1016/j.mhpa.2013.07.001.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service toour customers we are providing this early version of the manuscript. The manuscript will undergocopyediting, typesetting, and review of the resulting proof before it is published in its final form. Pleasenote that during the production process errors may be discovered which could affect the content, and alllegal disclaimers that apply to the journal pertain.

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Searching for cognitively optimal challenge point in physical activity

for children with typical and atypical motor development

Caterina Pesce1, Claudia Crova 1, Rosalba Marchetti 1, Ilaria Struzzolino 1, Ilaria Masci1,

Giuseppe Vannozzi1, Roberta Forte 1

1Italian University Sport and Movement, Department of Human Motion and Sport Science, Italy

Correspondence concerning this article should be addressed to:

Caterina Pesce, University of Rome ‘Foro Italico’ Piazza L. De Bosis 15, 00135 Rome, Italy Phone: +39 06 36733366 Fax: +39 06 36733362 e-mail : [email protected]

E-mail addresses of the non-corresponding authors: . [email protected] [email protected] [email protected] [email protected] [email protected] [email protected]

This research has received financial support by the Advanced Distribution S.p.A. The sponsor had no role in study design; collection, analysis and interpretation of data; in writing of the report; and in decision to submit the article for publication. There are no interests or activities that might be seen as influencing the research.

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Searching for cognitively optimal challenge point in physical activity

for children with typical and atypical motor development

Date of submission: December 28, 2012

Date of resubmission: June 18, 2013

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Abstract

Statement of problem. Growing evidence testifies that different types of physical activity (PA)

interventions promote cognitive development, but the specific impact of the cognitive demands inherent

in PA still remains underconsidered. This study investigated whether (1) increasing the cognitive

demands of PA positively impacts children’s executive function and (2) this ‘enrichment’ also matches

the ability/skill level of children with Developmental Coordination Disorder (DCD).

Methods. Two hundred and fifty children aged 5-10 years participated in different physical

education interventions, lasting six months, with or without special focus on cognitively demanding PA.

Before and after the intervention, children’s executive function was tested with the attention and

planning subscales of the Cognitive Assessment System and their motor developmental level classified

as typical, borderline, or DCD according to their performance evaluated by the Movement Assessment

Battery for Children.

Results. Among indices of executive function, those of Attention showed a differential effect of

PA type as a function of children’s motor developmental level: typically developing children gained

greatest attentional benefit from PA with additional cognitive demands, while children with

coordinative problems/impairment from the PA program without cognitive enrichment. Changes from

DCD to borderline or normal developmental status did not differ in frequency as a function of

intervention type.

Conclusions. Results showed that cognitively more or less challenging PA programs are

differently efficacious for promoting attention development and highlight the need to find and

continuously reset the degree of task complexity in PA to match the optimal challenge point of normal

and special children populations.

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Highlights

• We examine the cognitive benefits of physical activity (PA) interventions

• The qualitative aspects of physical exercise tasks may impact children’s cognition

• Adding cognitive demands to physical exercise promotes attention development

• Optimal challenge point depends on children’s typical/atypical motor development

• We need research on the ‘dose’ of cognitive demands in PA to gain greatest benefits

Key words: exercise, cognition, executive function, attention, developmental coordination

disorder, quality physical activity

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Searching for cognitively optimal challenge point in physical activity

for children with typical and atypical motor development

Strong evidence supports the benefits of physical activity (PA) for children’s physical health, as

indicated by cardiovascular and musculoskeletal health outcomes (Kristensen et al., 2010; Strong et al.,

2005) and for their mental health, as shown by self-perception, emotional, and cognitive outcomes

(Ahn & Fedewa, 2011; Biddle & Aasare, 2011). In the last decade, developmental researchers have

devoted increasing attention to cognitive functioning as a relevant mental health outcome of PA and

particularly to executive cognitive functions, which are responsible for self-regulation, goal-oriented

and health-related behaviours (Tomporowski, Davis, Miller, & Naglieri, 2008; Tomporowski,

Lambourne, & Okumura, 2011).

While such evidence testifies the importance of PA at pediatric age, there is alarming evidence

of secular decremental trends in children’s PA levels (e.g., Dolmann, Norton, & Norton, 2005) and

physical fitness test performance (e.g., Tomkinson, Leger, Olds, & Carzola, 2003) and an emergent

health concern with ‘exercise-deficit disorder’ (Faigenbaum, Stracciolini, & Myer, 2011). Secular

trends of decline have been also documented in children’s coordination and fundamental motor skills

proficiency (Raczek, 2002) with onset as early as at preschool age (Roth et al., 2010; Vandorpe et al.,

2011), but research regarding these trends is still scarce and geographically limited. The scarce interest

for secular trends in motor coordination at pediatric age is surprising if we consider the close

interrelation existing between cognitive and motor development and, correspondingly, between the

development of the brain substrates responsible for executive function and motor behaviour (Diamond,

2000; Pennequin, Sorel, & Fontaine, 2010). Also from the perspective of atypical motor development,

several decades of research have evidenced that children with severe motor clumsiness and impairments

in motor control and perceptual-motor functioning (i.e., Developmental Coordination Disorder, DCD;

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American Psychiatric Association, 2000) have co-occurring cognitive and attentional problems (Kirby

& Sudgen, 2007) and a strong association exists between DCD and deficits relying on executive

function impairment (i.e., Attention Deficit Hyperactivity Disorder, ADHD) (Sergeant, Piek, &

Oosterlaan, 2005).

As a consequence of the unbalanced attention devoted to secular trends in children’s fitness and

coordination, PA guidelines for young people scarcely consider aspects other than exercise quantity and

fitness-related health. This represents a problem particularly in childhood that has been defined as ‘skill

hungry years’ during which strongest emphasis should be put on PA experiences promoting motor and

cognitive development (Kirk, 2005). This problem may also reflect the general lack of specificity in

defining and measuring dimensions of PA for children from a qualitative point of view that goes beyond

the framework of intensity, duration and frequency of activity (Dwyer, Baur, & Hardy, 2009).

Recently, it has been pointed out that this unbalanced interest for PA quality and quantity in

favour of the latter extends to the area of exercise and cognition (Pesce, 2012). Also the attention of

investigators working on the relationship between PA and cognitive function during development still

mainly focuses on how the quantity of PA practiced by children and the resulting physical fitness affect

children’s cognition (Hillman, Erickson, & Kramer, 2008; Singh, Uijtdewilligen, Twisk, van Mechelen,

& Chinapaw, 2012). Instead, relatively little research has examined how the cognitive or social

interaction demands of PA (Best, 2012; Pesce, Crova, Cereatti, Casella, & Bellucci, 2009) and its motor

coordination demands (Budde, Voelcker-Rehage, Pietraßyk-Kendziorra, Ribeiro, & Tidow 2008;

Gallotta et al., 2011) impact children’s cognition independently of exercise intensity and duration (see

Best, 2010 for a review). These studies, exclusively regarding the transient effects of a single bout of

acute exercise, have lead to diverging results on the role of the amount of cognitive engagement by

movement. Cognitive engagement or effort may be conceived as the allocation of limited resources to

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an ongoing task requiring mental operations and information processing. It is determined by executive

processes that draw on mental resources, as when individuals perform novel or complex tasks requiring

to consider multiple response pathways, but are only scarcely or not at all needed to perform repetitive

responses that have been highly learned with extended practice (Tomporowski, McCullick, & Horvat,

2010). It remains to be tested whether cognitive engagement by complex and variable movement tasks

in chronic exercise interventions may aid the development of executive functions in the preschool and

primary school years in which such functions ‘come online’ (Garon, Bryson, & Smith, 2008; Huizinga,

Dolan, & van der Molen, 2006).

This lack of developmental intervention studies in which the cognitive engagement in PA is

manipulated by varying the cognitive and motor coordination demands of the physical exercise tasks is

surprising. As a relevant review of interventions indicates (Diamond & Lee, 2011) executive function

development can be aided in playful ways by mindfulness PA and sport practices, such as martial arts.

However, attempts to deliberately apply executive function training by integrating specific cognitive

demands into physical education (PE) games are still rare (Kubesch & Walk, 2009), as well as attempts

to promote the development of executive function in children with motor developmental problems by

capitalizing on the cognitive challenges of sport activities such as table tennis (Tsai, 2009).

The present study investigated the effects, on children’s executive functions, of school-based PA

interventions led by PE specialist teachers which either (1) included or (2) did not include additional

cognitive demands specifically tailored to challenge executive function. Since in many countries PE in

the early school years still is the responsibility of the classroom generalist teacher, we also assessed the

cognitive outcomes of PE when it was (3) taught by generalist teachers. We verified whether the

cognitive ‘enrichment’ of PA matches the ability/skill level of children with or without motor

developmental problems. Since acute exercise studies in which the cognitive and coordinative

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complexity of the PA tasks was manipulated have shown diverging effects on executive function (Best,

2012; Budde et al., 2008; Gallotta et al., 2012; Pesce et al., 2009), we hypothesized that the ‘dose’ of

cognitive and coordinative demands of the PA tasks may act as a moderator of the exercise-cognition

relationship and that the emergence of cognitive benefits depends on the interplay between individual

differences in motor development and amount of cognitive challenge in PA.

Methods

Participants

In the school year 2010/11, three kindergarten-primary schools of the Municipality of Rome

(Italy) participated in the study. They belonged to similar urban districts and had a homogeneous socio-

economic profile, as assessed using an area based measure. Within each school, seven gender-balanced

classes (two kindergarten classes with children aged 3-5 years and five first to fifth grade classes with

children aged 6 to 10 years) were selected according to teacher and class availability and randomly

assigned to different PE programs. Since in the school setting, random assignment of individuals to

different treatments is not feasible, we ‘traded’ the gold standard of fully randomized controlled trials

for the ecological validity of school class settings. The parents of all participants provided informed

written consent in conformity with the laws of the country and all children provided verbal assent

before involvement in the study. The study protocol was approved by the institutional ethics committee.

Of the total 530 children involved in the intervention, 250 (127 male and 123 female) children

aged 5-10 years, who were eligible for cognitive and/or motor coordination assessment, had no known

diagnosed disorder of cognition and no physical condition hindering them to participate in a school PE

program and did not miss any assessment session, represented the actual sample.

Baseline differences in PA levels and, given the young age of the children, differences in

spontaneous outdoor play between children assigned to the different PE interventions may influence the

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intervention outcomes on cognitive functioning. Thus, outdoor play and PA levels were evaluated prior

to the intervention period on a subsample of children (n=76), stratified for schools and classes. Parents

completed the Children’s Outdoor Play Assessment Questionnaire (Veitch, Salmon, Ball, 2009) and

older primary school children completed, under the supervision of the researchers, the Physical Activity

Questionnaire for Children (PAQ_C) (Kowalski, Crocker, & Donen, 2004). No significant differences,

as assessed by means of t-test for independent samples, emerged among children assigned to the three

types of intervention (Table 1). Generalists and PE specialists volunteered in the study. The generalists

had a basic qualification for primary school teaching, but never participated in specific teacher training

for PE, whereas the specialists were licensed to teach PE.

Intervention and allocation procedures

There were two types of experimental PE intervention and one standard PE program. The two

experimental interventions were directed by PE specialist teachers (specialist-led, S-led), whereas

standard PE was directed by classroom generalist teachers (generalist-led, G-led). Both the generalists

and the PE specialists taught PE according to the age-related PE goals defined in the Italian curriculum

for kindergarten and primary school (basically motor and social skills development). However, the

generalists did not receive any particular instruction by the researchers. This was done to obtain an

ecologically valid control condition. Instead, the specialists were provided with guidelines for and

received training in the experimental interventions. The researchers devised two intervention programs

both made of similar PA games that emphasized variability of practice and widely challenged motor

control and perceptual-motor adaptation abilities.

The two specialist-led PE programs differed from one another in that in one of them, the PA

games were altered to involve a higher amount of mental engagement and were specifically tailored to

challenge executive functions (cognitively challenging specialist-led—ceS-led—intervention). This was

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done by joining instructional principles of executive tasks used in cognitive developmental research

(Garon et al., 2008; Huizinga et al., 2006) with the principle of contextual interference as applied in

children’s motor learning (Tomporowski, et al., 2010). This principle, that following seminal research

(Shea and Morgan, 1979) has found large application in motor skill learning and sports training

(Vickers, 2007), affirms that learning is enhanced when interference during practice is high, as when

participants practice multiple tasks in a random order. In our intervention, for example, games were

altered in a way that children’s roles were no longer fixed, but fluctuated along the game. Also in

further games, children had to hold a rule in mind and respond according to this rule that randomly

required inhibiting a habitual response. Contextual interference is assumed to emerge because blocked

practice is not sufficiently demanding to produce optimal effort. Consistent with this view, contextual

interference is reduced or eliminated with more complex tasks (see Wulf & Shea, 2002). Therefore we

did not only use random practice as a mean to promote cognitive engagement, but also employed games

characterized by varying task complexity, with challenge incrementing, to keep children on the learning

curve (Tomporowski et al., 2010) and continuously stimulate executive control (Diamond & Lee,

2011). Also, open-ended tasks were employed in which only the starting point, the rule(s) and the task

goal were indicated and children were encouraged to find many possible solutions to perform it.

The intervention outcomes may depend on PE content and the delivery skills of the teachers as

well as on intensity and duration of physically active time in PE. Thus, PE sessions were observed

directly and videotaped in two randomly selected classes for each type of intervention to identify the

true characteristics of teachers’ individual instruction methods and teaching strategies and exercise

intensity was monitored by recording heart rate (HR) with HR monitors (Polar S610i) on a subsample

of children (n = 12 for each school) once a month. The qualitative intervention features were

categorized as teacher’s behavioural categories according to Rink’s Observation System for Content

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Development-Physical Education (OSCD-PE) and teaching strategies (Rink, 2006) (Table 2). The

outcomes of the categorization, quantified as percentage (%) of events for time unit (20 sec) during PE,

were submitted to reliability computation. A satisfactory intra- and inter-observer agreement, indicated

by a percentage of agreement [Agreements/(Agreements + Disagreements) x 100] ≥ .80, was reached.

The time spent in moderate to vigorous physical activity (MVPA) was operationalized as HR > 139

bpm (Wang, Pereira, & Mota, 2005). The qualitative characteristics of PE teaching, the intensity and

duration of physically active time are reported on Table 3 separately for the three intervention types.

Each school was randomly allocated to receive two of the three interventions (first school: three G-led

and four S-led classes; second school: four G-led and three ceS-led classes; third school: three S-led and

four ceS-led classes). All children participated in PE for 1 hour once a week, corresponding to the

National curricular PE time, and the intervention duration was 6 months. The teacher-student ratio was

about 1:25. Following familiarization to tests protocols, participants were assessed two times: at

baseline and post-intervention. The same procedures and schedule were applied for pre- and post-

intervention testing, with cognitive and motor testing being administered by a trained experimenter in

the morning, within the same week in the same order (cognitive testing first) and not preceded by PA

lessons to avoid acute exercise effects.

Insert Tables 1-3 about here

Cognitive assessment

To assess children’s cognitive performance, the Cognitive Assessment System (CAS) (Naglieri &

Das, 1997, Italian version 2005) was used. The CAS consists of 12 subtests that assess 4 aspects of

cognition: Planning, Attention, Simultaneous and Successive processes (PASS theory) (Das, Naglieri,

& Kirby, 1994). For the present study, because of school time constraints, participants only performed

the Planning and Attention tasks which are the test performances most strongly relying on executive

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functions. Also, we did not collect test-retest reliability data, since acceptable to good reliability data are

available for children of the age 5-10 years considered in this study (Naglieri & Das, 1997).

Planning. Planning is a cognitive process by which the individual determines, selects, and uses a

strategy to efficiently solve a problem.The Planning scale is composed of three subtests. The first

subtest, Matching Numbers, contains 4 items, each with 8 rows of numbers and 6 numbers per row,

with numbers increasing in digit length every four rows. The child must locate and underline the two

numbers in each row that are the same. The second subtest, Planned Codes, contains two items, each

within a matrix of 7 rows and 8 columns of letters with empty boxes. A caption is presented that shows

correspondence between letters and codes presented as a legend at the top of the page (e.g., A to OX

and B to XX). The child’s task is to fill in the empty boxes under each letter with the corresponding

codes discovering their internal organization to solve the task. The last subtest, Planned Connections,

contains 8 items. The first six require the child to join a series of numbers that are randomly distributed

in space in a sequential order, with an increasing length of numbers to be connected. The last two items

require the child to alternately connect numbers and letters serially (i.e., 1-A-2-B etc.). The items are

designed so that a child cannot complete a sequence by crossing one line over the other. To evaluate

performance on the first two subtests, the raw score is the ratio of the accuracy (total number correct)

and time to completion. For the third subtest, the raw score is the sum of the times required to complete

each item. All these scores are then converted to an age-based standard score and summed to obtain a

total scale value.

Attention. The Attention scale is composed of three subtests that require the child to use focal

attention to detect target stimuli and avoid distractions. The first subtest, Expressive Attention, is a

Stroop-like test composed of three items that measures attention selectivity and interference control

under time pressure. The first and the second items are without interference condition, while the third is

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with interference. There are two age-specific sets of items. For example, in the version for children 8

years and older, the non-interference conditions are reading color words (Blue, Yellow, Green, and Red)

all written in dark ink and naming the colors of a series of rectangles (printed in blue, yellow, green, and

red). In the interference condition, the words Blue, Yellow, Green, and Red are printed in a different

color ink than the colors the words name and the child is instructed to name the color ink the word is

printed in, rather than to read the word. Only this last item is used as the measure of attention. The

second subtest, Number Detection, measures selectiveness and capacity to resist distraction under time

pressure. It is comprised of pages of numbers where the child must underline the correct numbers

among a large quantity of distracters in different formats. For example, the child must find a particular

stimulus (the number 1, 2, and 3 printed in an open font) on a page containing many distracters (the

same numbers printed in a different font style). The raw score is the ratio of the accuracy (total number

correct minus the number of false detections) and the time to completion summed across the items. The

third subtest, Receptive Attention, is a two-page subtest that measures the ability to focus and then shift

attention between different stimulus dimensions under time pressure. On the first page, children 8 years

and older must identify and underline pairs of target letters that are physically identical (e.g., TT but not

Tt), whereas on the second, pairs of letters that have the same name (e.g.,, Aa not Ba) are targets to be

underlined. For all subtests, the raw score is the ratio of the accuracy (total number correct in the first

subtest and total number correct minus the number of false detections in the second and third subtests)

and time to completion summed across items/pages. The raw score for each subtest is converted to an

age-based standard score and summed to obtain a total scale value.

Motor assessment

To assess children’s motor coordination performance, the Italian version of the Movement

Assessment Battery for Children (M-ABC) developed by Henderson and Sudgen (1992) was used. This

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test evaluates movement competence providing objective quantitative data on both gross motor and fine

motor coordination of children aged from 4 to 12 years with eight tasks differentiated in four age-

related difficulty levels. The M-ABC has been proved to be a valid and reliable research and diagnostic

tool that covers the entire domain of motor ability and is used to identify motor problems and DCD

(Croce, Horvat, & McCarthy, 2001). The tasks are grouped under three subheadings: manual dexterity,

ball skills, and static and dynamic balance.

Manual dexterity. There are three tasks that slightly differ as a function of the child’s age. The

first is ‘posting coins’ (5 to 6 year-old), ‘placing pegs’ (7 to 8 year-old), or ‘shifting pegs by rows’ (9 to

10 year-old). The child must drop coins through the slot in a bank box, or place 12 plastic pegs in all

holes on a board, or move pegs from a given row to another, respectively, one at a time as quickly as

possible. The second task is ‘threading beads’ (5 to 6 year-old), ‘threading lace’ (7 to 8 year-old), or

‘threading nuts on bolt’ (9 to 10 year-old). The child must thread beads through a lace, or thread a lace

back and forth through the holes in a lacing board, or screw nuts down a bolt, respectively, one at a time

as quickly as possible. In both the first and second tasks, the examiner measures the seconds taken to

complete each task. The third task is ‘bicycle trail’ (5 to 6 year-old), or ‘flower trail’ (7 to 10 year-old).

The child must draw with the preferred hand one continuous line following the bicycle or flower trail on

a record form without crossing its boundaries. The examiner records the number of errors, i.e. the

number of times the drawn lines moves outside a boundary.

Ball skills. There are two tasks differing as a function of the child’s age. The first is ‘catching

bean bag’ (5 to 6 year-old), ‘one-hand bounce and catch’ (7 to 8 year-old), or ‘two-hand catch’ (9 to 10

year-old). The child must catch a bean bag tossed by the experimenter, or bounce a tennis ball on the

floor and catch it with the same hand, or throw a tennis ball at the wall form behind a marked distance

of 2 m and catch it at the return with both hands, respectively. The second task is ‘rolling ball into goal’

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(5 to 6 year-old), or ‘throwing bean bag into box’ (7 to 10 year-old). The child must roll a tennis ball

along the floor between two stands, 40 cm apart from one another and 2 m apart from the child, to score

a ‘goal’, or throw a bean bag into a target box on the floor form behind a marked distance of 2 m (7 to 8

year-old) or 2,5 m (9 to 10 year old), respectively. In both types of tasks, the examiner records the

number of correctly executed trials (successful catches and throws) out of ten attempts.

Static and dynamic balance. There are three tasks differing as a function of the child’s age: one

for static balance and two for dynamic balance. The task evaluating static balance is ‘one-leg balance’

(5 to 6 year-old), ‘stork balance’ (7 to 8 year-old), or ‘one-board balance’ (9 to 10 year-old). The child

must stand on one leg, with the arms held at the sides, or stand on a foot, place the sole of the other foot

against the side of the supporting knee and the hands on the hips, or balance on one foot on a balance

board, respectively. The examiner records the number of seconds, up to 20, the child maintains balance

without moving the standing and the non-standing foot. The second task is ‘jumping over cord’ (5 to 6

year-old), ‘jumping in squares’ (7 to 8 year-old), or ‘hopping in squares’ (9 to 10 year-old). The child

must jump over the cord from a stationary position, landing with feet together, or make five continuous

jumps forward from a starting square to further five squares, or make five continuous hops forward

from square to square on one foot, respectively. The examiner records if the child performs a successful

jump (‘jumping over cord’) or the number of correct consecutive jumps/hops completed over five

without performance errors (‘jumping or hopping in squares’). The third task is ‘walking heels raised’

(5 to 6 year-old), ‘heel-to-toe walking’ (7 to 8 year-old), or ‘ball balance’ (9 to 10 year-old). The child

must walk along a 4.5 m line with heels raised without stepping off the line, or walk on a line placing

the heel of one foot against the toe of the other, or walk around the outside of two stands 2.7 m apart

and return to the starting point while steadying a board with a ball in the middle of it, respectively. The

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examiner records the number of steps performed by the child without leaving space between toe and

heel or stepping off the line.

Data coding and scoring. The M-ABC data were standardized to compute average scores for the

three subheadings of manual dexterity, ball skills, and static and dynamic balance. The data were also

transformed into scores of impairment of motor function according to age-related normative data

(Henderson & Sudgen, 1992). Each impairment score indicates the extent to which a child falls below

the level of his/her age peers, while it does not differentiate between children who perform above this

level. A total score of impairment was computed as the sum of the scores obtained for each subheading

(manual dexterity, ball skills, and balance) in order to identify typically developing children and

children with movement problems or impairment. The 15th percentile is the threshold value for

coordinative developmental problems (borderline), the 5th percentile is the threshold value for

impairment (DCD). We did not collect test-retest reliability data, since high reliability results are

available for children across all age groups considered in this study (Croce et al., 2001; Henderson &

Sudgen, 1992).

Statistical analysis

Firstly, both physically active time in PE and percentage of active time spent in MVPA were

compared in the three intervention groups by means of univariate ANOVAs with group (G-led, S-led,

ceS-led) as factor followed by pairwise comparisons between groups (t-tests). Secondly, difference

values between pre- and post-intervention measures (pre-post delta) were computed for all CAS

measures of planning (Planning total score and Planned Codes, Matching Numbers, Planned

Connections scores) and attention (Attention total score and Expressive Attention, Number Detection

and Receptive Attention scores). Then a general linear model was applied to all delta scores with motor

developmental level (normal, borderline, DCD), group (G-led, S-led, ceS-led), and school (nested

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within group) as factors and age and baseline planning or attention scores as covariates. These

covariates were included to exclude that any difference in age and baseline levels of planning and

attention ability might be responsible for differential intervention outcomes. In the case of significant

effects, planned pairwise comparisons (t-tests) were performed when appropriate and Bonferroni

correction was applied for multiple comparisons. Also, data were coded as a function of whether

children’s motor developmental classification changed from pre- to post-intervention from

DCD/borderline to borderline/typically developing. Then chi square statistics were applied to verify

whether the frequency of improvement cases differed as a function of the type of intervention.

Results

The overall percentages of typically developing, borderline and DCD children were 67.6%,

18.4%, and 14.8% respectively. The prevalence of children with DCD was consistent with the literature

and intermediate between that reported in European and American surveys (Tsiotra et al., 2006).

Children’s compliance to the CAS and M-ABC, as well as to PE classes was generally very good.

Adjusted analyses from general linear models of pre-post delta (∆) of cognitive performance

variables, with age and baseline score as covariates and school nested within group, did not show

differential intervention effects as a function of group and/or motor developmental level in the total

Planning scale or any of the Planning subtest scores. Instead, significant Group x Developmental Level

interactions emerged for ∆ total Attention scale, F(2, 239) = 5.16, p=.006, ηp2=.04, ∆ Expressive

Attention, F(2, 239) = 2.94, p=.05, ηp2=.03, and ∆ Receptive Attention, F(2, 239) = 7.19, p=.001,

ηp2=.06, subtest scores. Post-hoc analyses (adjusted p for six pairwise comparisons = .008) showed that

the different interventions exerted differential effects on the attention of typically developing and

borderline/DCD children.

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Typically developing children assigned to the ceS-led intervention showed more pronounced pre-

to-post improvements (positive ∆ values) in the total Attention scale (9.2±7.4), than typically

developing children in the G-led (5.5±7.6) and the S-led (4.2±9.9) groups. Analysis of attention

subscales showed that this advantage of the ceS-led group as compared to the other two intervention

groups was attributable to amelioration in Receptive Attention performance (Figure 1, right).

In contrast, borderline/DCD children did not show significant differences between intervention

groups in the total Attention scale (7.4±7.0, 9.1±9.4 and 7.8±9.3, for the G-led, S-led and ceS-led

groups, respectively). The non-significantly higher ∆ Attention of borderline/DCD children in the S-led

group reached significance, as compared to the G-led group, in the analysis of Expressive Attention data

(Figure 1, left), but not in that of Receptive Attention performance (Figure 1, right).

Insert figure 1 about here

Chi square tests performed on frequency of post-intervention ameliorations in M-ABC

performance showed that the amount of children whose classification changed from DCD/borderline to

borderline/typically developing did not significantly differ between intervention groups, although a non-

significant larger amount of improvement cases was observed in the ceS-led group (Table 1).

Among the three intervention types, there were significant differences in physically active time,

F(2, 33) = 36.85, p<.001, ηp2=.69, and in % of active time in MVPA, F(2, 33) = 3.63, p=.038, ηp

2=.18.

Post-hoc tests (adjusted p for three pairwise comparisons = .016) showed that the active time in the S-

led PE lessons was significantly longer than in the G-led and ceS-led PE lessons, whereas the

percentage of active time spent in MVPA only differed between S-led and G-led groups (Table 3).

Considering the relatively short physically active time (about half an hour per 1 hour PE lesson), the %

active time spent in MVPA equated to approximately only 12 and 15 minutes per PE lesson in the G-led

and ceS-led groups, respectively, but to 23 minutes in the S-led group. As compared to generalist

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teachers, specialists – regardless of the presence or absence of additional cognitive demands – spent less

time for informing, but more for organizing the learning environment. As regards teaching styles, while

the generalist teachers made sometimes use of peer teaching, the PE specialists prioritized the

interactive style and, when they taught PA games with enhanced cognitive challenges, they also

adequately employed a cognitive teaching style (Table 3).

Discussion

The present study focused on whether qualitatively different types of PA interventions in school

settings may differently impact children’s executive function. The route by which PA impacts mental

functioning and particularly fosters executive function development is likely moderated by task

variables, such as physical exercise intensity, duration, and complexity, and individual characteristics,

such as physical fitness level, health status, and psycho-social factors (Pesce, 2009; Tomporowski et al.,

2011). We aimed to extend the notion of dose-response relationship (Pesce, 2012) examining whether

varying the amount of coordinative and cognitive complexity of the movement tasks we may meet the

need for an appropriate challenge point to induce executive function enhancement in children with

typical and atypical motor development.

On the whole, four main points emerged from the findings of this study.

(1) Attention development in the kindergarten and primary school years can be aided by specialist-

led PA experiences including targeted cognitive challenges. However, the efficacy of cognitive

engagement in PA for promoting attention development depends on the type and ‘dose’ of cognitive

challenges by movement and children’s motor developmental level.

(2) In typically developing children, attention selectivity and interference control, as reflected in

‘Expressive Attention’ data, did not show differential improvements following the three qualitatively

different types of intervention. PA per se, regardless of its cognitive challenges, increases physiological

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arousal, which in turn allows for greater allocation of attention to exert cognitive control over

interference and avoid distractions (Best, 2012; Hillman et al., 2009).

(3) In children with motor developmental problems/impairment, this pathway seems to be

particularly effective at higher exercise intensity. In fact, they reaped larger ‘Expressive Attention’

benefits from the specialist-led interventions than from the generalist-led intervention which differed in

%MVPA. Moreover, children with motor developmental problems belonging to the specialist-led

classes obtained largest benefits when assigned to the PA intervention without additional cognitive

challenges.

(4) Only typically developing children, but not borderline children or those with DCD, benefited

mostly from the cognitively enriched PA program for improving their ability to focus and shift

attention, as reflected in the ‘Receptive Attention’ performance.

In summary, the different attentional outcomes of specialist-led PA as compared to generalist-led

PA may be due to the observed differences in both quantitative (i.e., intensity) and qualitative exercise

characteristics (i.e., content and delivery). Instead, the diverging response of children with or without

motor developmental problems to specialist-led PA interventions which differed in cognitive content

and delivery strategy, but not in exercise intensity, suggests the existence of a specific pathway through

which PA may aid executive function development: the direct stimulation by movement (Tomporowski

et al., 2011). This is in line with the potential of action to affect cognitive development (Rakison &

Woodward, 2008) especially during the sensitive periods in the development of neural structures

subtending high-level cognitive function (Thomas & Johnson, 2008).

Specifically, a specialist-led PA program without cognitive enrichment, but tailored to

emphasize variability of practice and widely challenging motor control and perceptual-motor adaptation

abilities is most appropriate for children with motor developmental difficulties, while a cognitively

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enriched PA environment may represent an added value for typically developing children only.

Probably, children with atypical motor development need higher executive control to deal with

movement coordination difficulties and/or worse control over their gaze and visuospatial attention

underlying visuomotor control (Wilson, Miles, Vine, & Vickers, 2013). Since the games employed in

the cognitively challenging, specialist-led intervention often involved contextual interference and the

need to flexibly switch between visual stimulus-response associations, the low ability of children with

atypical motor development to pick-up task-relevant visual information may have led them to

ineffective task mastering and mental overload and challenged their executive function at a too high

degree. Carey, Bhatt, and Nagpal (2005) focused on the issue of proper level of cognitive engagement

and contextual interference in skill training, arguing that there may be a threshold above which any

increase in task complexity and cognitive effort is not beneficial. Our results suggest that such threshold

also exists in movement-based executive function training and must be fine-tuned with children’s motor

developmental level. This supports the importance to identify the optimal challenge point in PA as a

function of children’s typical/atypical motor development. The notion of optimal challenge point,

coined by Guadagnoli and Lee (2004), represents the degree of functional task difficulty an individual

of a specific skill level would need to optimize learning. Therefore, it takes into joint consideration the

skill level, task complexity, and task environment and will change as the individual’s abilities and skills

change. Our results suggest the opportunity to extend this notion from the challenges in the motor

domain to the cognitive challenges that may be inherent in movement tasks at different degrees.

The results obtained with children with atypical motor development confirm the appropriateness

to focus on PA intervention outcomes in the cognitive domain with this special children population

(Tsai, 2009). In adapted PA research, interventional studies with children with DCD are usually focused

on outcomes in the motor domain (Miyahara, Yamagichi & Green, 2008) also when the treatment is

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cognitive in nature (Sudgen, 2007; Wilson, 2005) In the present study, the cognitively enriched PA did

not result to be especially advantageous in the motor domain for reducing cases of children with motor

problems (borderline) or impairment (DCD), since differences between intervention groups were

statistically negligible. Thus, the three intervention types were similarly useful for dampening

coordinative problems, or factors different from the PA intervention, such as growth, maturation, out-

of-school motor experiences, and habituation and learning of the motor assessment tasks may have been

responsible for general ameliorations in motor test performance.

The present findings showed the above described effects on children’s attention, but no effects

on planning ability as evaluated by the CAS. This is at odds with the outcomes of other developmental

chronic exercise studies employing the CAS and showing no differences between intervention and

control group changes in any CAS score (Fisher et al., 2011), or beneficial effects only on planning

performance (Davis et al., 2011). This divergence may be due to the type of PA interventions and

reconciled focusing on the concept of optimal challenge point. The above mentioned studies focused on

enhanced PA, either manipulating the duration of several weekly sessions (Davis et al., 2011), or

manipulating exercise intensity by enhancing the physically active time in PE and percentage of PE

lesson in MVPA within the curricular PE time (Fisher et al., 2011). The aim of these studies was to

search for the right ‘dose’ of quantitative exercise parameters for normal or overweight children. In

contrast, we manipulated the quality of PE experiences and particularly the amount and type of

cognitive stimulation inherent in the proposed activities while controlling for exercise intensity.

Our findings support the call for further research exploring whether the effects of PA on

executive functions differ as a function of task difficulty and cognitive demand (Hill et al., 2010).

However, it is to consider that we employed a low-dose PE intervention (1 hr/week), as it is prescribed

in the Italian preschool and primary school system, and the effect size was relatively small (.03 ≤ ηp2 ≤

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.06). Thus on the one side, the evidence that even though embedded in a very low-dose PA program,

cognitively challenging movements may help obtain beneficial cognitive outcomes is encouraging. On

the other side, the small effect size calls for further interventional research exploring the cognitive

developmental outcomes that can be obtained joining high-dose PA (Davis et al., 2011) with an

appropriate level of cognitive challenge by movement (Crova et al., resubmitted after minor revisions).

In a recent study, Best (2012) examined the separate and combined effects of acute PA and

cognitive engagement on attentional interference control in children aged 6 to 10 years and found that

the combination of PA and cognitive effort did not have a stronger effect than PA alone. The

discrepancy of his results with the present findings may be due not only to differences between acute

and chronic exercise effects on cognition, but also to differences in attentional functions measured and

in manipulation of cognitive engagement. Best (2012) measured only one specific aspect of executive

attention (i.e., interference control) and used more interactive or repetitive video games to manipulate

children’s cognitive engagement. Instead in our study, we examined different aspects of attention and

tailored the PA games in the cognitively enriched program to elicit a specific engagement of executive

functions by matching the principles of neuropsychological executive function tasks (Garon et al., 2008;

Huizinga et al., 2006). The idea subtending our applied study on the cognitive outcomes of PA is that

cognitive engagement in PA should not be considered as a unitary construct. We consider the present

approach to the effects of exercise on cognition as a novel way to capitalize on quality PA, focusing on

cognitive functioning as a relevant mental health outcome of cognitively challenging PA.

A limitation of the study is the absence of a follow-up to control for the stability over time of the

benefits obtained by enhancing the cognitive challenges of the movement tasks in PA. To inform policy

development, more prospective field research is needed that joins measures of motor and cognitive

development to evaluate the goodness of quality PA interventions underpinned by sound theoretical

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framework. The results could help re-focus actual guidelines for PA prescription for children,

grounding them not only on evidence of a dose-response relationship in the physiological domain, but

also on evidence of a ‘quality-response relationship’ in the cognitive domain (Pesce, 2012).

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References

Ahn, S, Fedewa, A. L. (2011). A meta-analysis of the relationship between children’s physical activity

and mental health. Journal of Pediatric Psychology, 36, 385-397.

American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders (fourth

ed.). Washington, DC, USA: American Psychiatric Association.

Best, J. (2010). Effects of physical activity on children’s executive function: contributions of

experimental research on aerobic exercise. Developmental Review, 30, 331-351.

Best, J. (2012). Exergaming immediately enhances children’s executive function. Developmental

Psychology, 48, 1501–1510.

Biddle, S. J. H. & Asare, M. (2011). Physical activity and mental health in children and adolescents: a

review of reviews. British Journal of Sports Medicine, 45, 886–895.

Budde, H., Voelcker-Rehage, C., Pietraßyk-Kendziorra, S., Ribeiro, P., & Tidow, G. (2008). Acute

coordinative exercise improves attentional performance in adolescents. Neuroscience Letters,

441, 219-223.

Carey, J. R., Bhatt, E., & Nagpal, A. (2005). Neuroplasticity promoted by task complexity. Exercise and

Sport Sciences Review, 33, 24-31.

Croce, R. V., Horvat, M., & McCarthy, E. (2001). Reliability and concurrent validity of the movement

assessment battery for children. Perceptual and Motor Skills, 93, 275-280.

Crova, C., Struzzolino, I., Marchetti, R., Masci, I., Vannozzi, G., Forte, R., & Pesce, C. (resubmitted

after minor revisions). Benefits of cognitively challenging physical activity in overweight

children. Journal of Sports Sciences.

Das, J. P., Naglieri, J. A., & Kirby, J. R. (1994). Assessment of cognitive processes: the PASS theory of

intelligence. Needham Heights, MA: Allyn and Bacon.

MANUSCRIP

T

ACCEPTED

ACCEPTED MANUSCRIPTRunning head: COGNITIVELY OPTIMAL CHALLENGE POINT IN PA FOR CHILDREN 25

Davis, C. L., Tomporowski, P. D., Mc Dowell, J. E., Austin, B. P., Miller, P. H., Yanasak, N.

E.,…Naglieri, J. A. (2011). Exercise improves executive function and achievement and alters

brain activation in overweight children: a randomized, controlled trial. Health Psychology, 30, 91-

98.

Diamond, A. (2000). Close interrelation of motor development and cognitive development and of the

cerebellum and prefrontal cortex. Child Development, 71, 44-56.

Diamond, A., & Lee, K. (2011). Interventions shown to aid executive function development in children

4 to 12 years old. Science, 333, 954-969.

Dolmann, J., Norton K., Norton L. (2005). Evidence for the secular trends in children's physical activity

behavior. British Journal of Sports Medicine, 39, 892-897.

Dwyer, G., Baur, L. A., & Hardy, L. L. (2009). The challenge of understanding and assessing physical

activity in preschool-age children: thinking beyond the framework of intensity, duration and

frequency of activity. Journal of Science and Medicine in Sport, 12, 534-536.

Faigenbaum, A. Stracciolini, A., & Myer, G. D. (2011). Exercise deficit disorder in youth: a hidden

truth. Acta Paediatrica, 100, 1423–1425.

Fisher, A., Boyle, J. M. E., Paton, J. Y., Tomporowski, P., Watson, C., McColl, J. H., & Reilly, J. J.

(2011). Effects of a physical education intervention on cognitive function in young children:

randomized controlled pilot study. BMC Pediatrics, 11:97.

Gallotta, M. C., Guidetti, L., Franciosi, E., Emerenziani, G. P., Bonavolontà, V., & Baldari, C. (2012).

Effects of varying type of exertion on children’s attention capacity. Medicine & Science in Sports

& Exercise,44, 550-555.

Garon, N., Bryson, S., & Smith, I. M. (2008). Executive function in preschoolers: a review using an

integrative framework. Psychological Bulletin, 134, 31-60.

MANUSCRIP

T

ACCEPTED

ACCEPTED MANUSCRIPTRunning head: COGNITIVELY OPTIMAL CHALLENGE POINT IN PA FOR CHILDREN 26

Guadagnoli M. A., Lee T. D. (2004). Challenge point: a framework for conceptualizing the effects of

various practice conditions in motor learning. Journal of Motor Behavior, 36, 212-224.

Henderson, S.E., & Sudgen, D.A. (1992). Movement assessment battery for children. London, UK: The

Psychological Corporation. [Italian version (edited by Eu. Mercuri & El. Mercuri): Movement

ABC—Batteria per la valutazione motoria del bambino, 2000. Firenze (Italy): Giunti O.S.].

Hill, L., Williams, J. H. G., Aucott, L., Milne, J., Thomson, J., Greig, J,…Mon-Williams, M. (2010).

Exercising attention within the classroom. Developmental Medicine & Child Neurology, 52, 929-

934.

Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart, exercise your heart: exercise effects

on brain and cognition. Nature Review Neuroscience, 8, 58-65.

Hillman, C. H., Pontifex, M. B., Raine, L. B., Castelli, D. M., Hall, E. E., & Kramer, A. F. (2009). The

effect of acute treadmill walking on cognitive control and academic achievement in preadolescent

children. Neuroscience, 159, 1044–1054.

Huizinga, M., Dolan, C. V., & van der Molen, M. W. (2006). Age-related change in executive function:

developmental trends and a latent variable analysis. Neuropsychoogia, 44, 2017-2036.

Kirby, A., & Sudgen, D. A. (2007). Children with developmental coordination disorders. Journal of the

Royal Society of Medicine, 100, 182-186.

Kirk, D. (2005). Physical education, youth sport and lifelong participation: the importance of early

learning experiences. European Physical Education Review, 11, 239-255.

Kowalski, K. C., Crocker, P. R. E., & Donen, R. M. (2004). The Physical Activity Questionnaire for

Older Children (PAQ-C) and Adolescents (PAQ-A) Manual. Canada: College of Kinesiology

University of Saskatchewan.

MANUSCRIP

T

ACCEPTED

ACCEPTED MANUSCRIPTRunning head: COGNITIVELY OPTIMAL CHALLENGE POINT IN PA FOR CHILDREN 27

Kristensen, P. L., Moeller, N. C., Korsholm, L., Kolle, E., Wedderkopp, N., Froberg, K., & Andersen,

L. B. (2010). The association between aerobic fitness and physical activity in children and

adolescents: the European youth heart study. European Journal of Applied Physiology, 110, 267–

275.

Kubesch, S., & Walk, L. (2009). Körperliches und kognitives Training exekutiver Funktionen in

Kindergarten und Schule [Physical and cognitive training of executive functions in preschool and

school]. Sportwissenschaft 39, 309-317.

Miyahara, M., Yamagichi, M., Green, C. (2008). A review of 326 children with developmental and

physical disabilities, consecutively taught at the movement development clinic: prevalence and

intervention outcomes of children with DCD. Journal of Developmental and Physical

Disabilities, 20, 353-363.

Naglieri, J.A., & Das, J.P. (1997). Cognitive Assessment System. Itaca, IL: Riverside Publishing. [Italian

version (edited by S. Taddei): CAS Das-Naglieri Cognitive Assessment System - Una misura

dell'intelligenza basata sul modello dei processi cognitivi PASS, 2005. Firenze (Italy): Giunti

O.S.]

Pennequin, V, Sorel, O., & Fontaine, R. (2010). Motor planning between 4 and 7 years of age: changes

linked to executive functions. Brain and Cognition, 74, 107–111.

Pesce C. (2009). An integrated approach to the effect of acute and chronic exercise on cognition: the

linked role of individual and task constraints. In T. McMorris, P.D. Tomporowski, & M.

Audiffren (Eds.), Exercise and cognitive function (pp. 213-226). West Sussex: Wiley and Sons.

Pesce, C. (2012). Shifting the focus from quantitative to qualitative exercise characteristics in exercise

and cognition research. Journal of Sport and Exercise Psychology, 34, 766 – 786.

MANUSCRIP

T

ACCEPTED

ACCEPTED MANUSCRIPTRunning head: COGNITIVELY OPTIMAL CHALLENGE POINT IN PA FOR CHILDREN 28

Pesce, C., Crova, C., Cereatti, L., Casella, R., & Bellucci, M. (2009). Physical activity and mental

performance in preadolescents: effects of acute exercise on free-recall memory. Mental Health

and Physical Activity, 2, 16–22.

Raczek, J. (2002). Entwicklungsveraenderungen der motorischen Leistungsfaehigkeit der Schuljugend

in drei Jahrzehnten (1965-1995) [Changes in motor capability development of school children

during three decades (1965-1995)]. Sportwissenschaft, 32, 201-216.

Rakison, D. H., & Woodward, A. L.(2008). New perspectives on the effects of action on perceptual and

cognitive development. Developmental Psychology, 44, 1209–1213.

Rink, J.E. (2006). Teaching physical education for learning (5th ed.). Boston: McGraw Hill.

Roth, K., Ruf, K., Obinger, M., Mauer, S., Ahnert, J., Schneider, W, … Hebestreit, H. (2010). Is there a

secular decline in motor skills in preschool children? Scandinavian Journal of Medicine and

Science in Sports, 20, 670–678.

Sergeant, J. A., Piek, J. P., & Oosterlaan, J. (2005). ADHD and DCD: A relationship in need of

research. Human Movement Science

Shea, J., & Morgan, R. (1979). Contextual interference effects on the acquisition, retention, and transfer

of a motor skill. Journal of Experimental Psychology: Human Learning and Memory, 5, 179-187.

Singh, A., Uijtdewilligen, L., Twisk, J. W. R., van Mechelen, W., & Chinapaw, M. J. M. (2012).

Physical activity and performance at school. A systematic review of the literature including

a methodological quality assessment. Archives of Pediatric and Adolescent Medicine, 166, 49-55.

Strong, W. B., Malina, R. M., Blimkie, C. J. R., Daniels, S. R., Dishman, R. K., Gutin, B., … &

Trudeau, F. (2005). Evidence based physical activity for school-age youth. The Journal of

Pediatrics, 146, 732-737.

MANUSCRIP

T

ACCEPTED

ACCEPTED MANUSCRIPTRunning head: COGNITIVELY OPTIMAL CHALLENGE POINT IN PA FOR CHILDREN 29

Sudgen, D. (2007). Current approaches to intervention in children with developmental coordination

disorder. Developmental Medicine and Child Neurology, 49, 467-471.

Thomas, M. S. C. & Johnson, M. H. (2008). New advances in understanding sensitive periods in brain

development. Current Directions in Psycholoogical Science, 17, 1-5.

Tomkinson G. R., Leger, L. A., Olds, T. S. & Carzola, G. (2003). Secular trend in the performance of

children and adolescent (1980-2000): an analysis of 55 studies of the 20m shuttle run test in 11

countries. Sports Medicine, 33, 285-300.

Tomporowski, P. D., Davis, C. L., Miller, P. H., & Naglieri, J. A. (2008). Exercise and children’s

intelligence, cognition, and academic performance. Educational Psychology Review, 20, 111-131.

Tomporowski, P. D., Lambourne, K., Okumura, M. S. (2011). Physical activity interventions and

children's mental function: An introduction and overview. Preventive Medicine, 52, 3-9.

Tomporowski, P. D., McCullick, B. A., & Horvat, M. (2010). Role of contextual interference and

mental engagement on learning. New York: Nova Science Publishers, Inc.

Tsai, C.-L. (2009). The effectiveness of exercise intervention on inhibitory control in children with

developmental coordination disorder: Using a visuospatial attention paradigm as a model.

Research in Developmental Disabilities, 30, 1268–1280.

Tsiotra, G. D., Flouris, A. D., Koutedakis, Y., Faught, B. E., Nevill, A. M., Lane, A. M., & Skenteris,

N. (2006). A comparison of Developmental Coordination Disorder prevalence rates in Canadian

and Greek children. Journal of Adolescent Health, 39, 125–127.

Vandorpe, B., Vandendriessche, J., Lefevre, J., Pion, J., Vaeyens, R., Matthys, S., … Lenoir, M.

(2011). The Körperkoordinations Test für Kinder: reference values and suitability for 6–12-year-

old children in Flanders Scandinavian Journal of Medicine and Science in Sports, 21, 378–388.

MANUSCRIP

T

ACCEPTED

ACCEPTED MANUSCRIPTRunning head: COGNITIVELY OPTIMAL CHALLENGE POINT IN PA FOR CHILDREN 30

Veitch, J., Salmon, J., & Ball, K. (2009). The validity and reliability of an instrument to assess

children’s outdoor play in various locations. Journal of Science and Medicine in Sport, 12, 579–

582.

Vickers, J. N. (2007). Perception, cognition and decision training. The quiet eye in action. Champaign,

IL : Human Kinetics (pp. 179-194).

Wang, G.Y., Pereira, B., & Mota, J. (2005). Indoor physical education measured by heart rate monitor:

a case study in Portugal. Journal of Sports Medicine and Physical Fitness, 45, 171-177.

Wilson, P.H. (2005). Practitioner review: approaches to assessment and treatment of children with

DCD: an evaluative review. Journal of Child Psychology and Psychiatry, 46, 806–823.

Wilson, M. R., Miles, C. A., Vine, S. J., Vickers, J. N. (2013). Quiet eye distinguishes children of high

and low motor coordination abilities. Medicine and Science in Sports and Exercise, 45, 1144-

1151.

Wulf, G., & Shea, C. H. (2002). Principles derived from the study of simple skills do not generalize to

complex skill learning. Psychonomic Bulletin & Review, 9, 185-211.

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Figure Captions

Figure 1. Pre-to-post intervention improvements (pre-post delta) in Expressive Attention (left) and

Receptive Attention (right) in 5 to 10 year-old children as a function of PA intervention type and motor

developmental level.

Acknowledgements

We thank the Guest Editor and two anonymous reviewers for helpful and insightful comments on a

previous version of the manuscript.

This research has received financial support by the Advanced Distribution S.p.A.

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Table 1: Baseline characteristics of the sample of 5 to 10 year-old children divided as a function of intervention type.

generalist-led (G-led)

specialist-led (S-led)

cognitively enriched, specialist-led (ccS-led)

n 96 71 83

Age (years) 7.0 (±1.6) 6.8 (±1.5) 7.1 (±1.3)

Motor developmental level

Typically developing

65 (67.7%)

44 (62.0%)

62 (74.7%)

Borderline 16 (16.7%) 14 (19.7%) 11 (13.2%)

DCD 12 (12.5%) 13 (18.3%) 10 (12.0%) Post-intervention improved DCD or borderline cases

20/28 (71.4%) 15/27 (55.6%)

18/21 (85.7%)

PA habits

Spontaneous outdoor play (mean score ± SD)

28.2 (± 7.2) 25.2 (± 5.3) 26.9 (± 8.6)

PA level (mean std. score ± SD)

1.8 (± 0,4) 2.0 (±0.6) 1.8 (±0.6)

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Table 2: Category definitions for PE tasks according to the Observation System for Content Development-PE (OSCD-PE) and selected teaching strategies (Rink, 2006). PE Tasks

Informing

An informing task states or presents a motor task. It is usually the first task and merely describes what the students are to do.

Refining A refining task is aimed at improving a student’s motor performance through corrective feedback, appraisals, initiations or responses on how to perform better

Extending

An extending task seeks a variety of responses or adds complexity of difficulty to a previous task.

Applying An applying task asks students to use their motor skill in an applied, competitive, or assessment setting.

Conduct A conduct task is a disciplinary behaviour that structures, directs, or reinforces the behaviour code of a specific situation.

Organization An organization behaviour is a management behaviour that structures, directs, or reinforces the arrangement of people, time, or equipment to create appropriate conditions for learning.

Teaching Strategies

Interactive Teaching Teaching strategy most commonly used in PE. The instructional process is controlled by teacher who is responsible for the selection and progression of the content, for task communication (usually to an entire group), feedback and evaluation.

Peer Teaching Instructional strategy according to which some teacher’s responsibilities are transferred to the student. The teacher usually maintains responsibility for content selection and progression, but uses one student to show or ‘teach’ a skill to another and to provide reciprocal feedback and evaluation.

Cognitive Strategies Group of teaching strategies designed to engage the learner cognitively in the content by producing solutions rather than reproducing any movement pattern they have been shown by teacher. This is an umbrella term for problem solving, guided and divergent discovery, and teaching through questions.

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Table 3: Task characteristics, student organization modes and teaching styles (mean % of events for 20-sec time unit), during the three employed types of PE interventions: generalist-led (G-led), specialist-led (S-led), and cognitively enriched, specialist-led (ceS-led).

generalist-led (G-led)

specialist-led (S-led)

cognitively enriched, specialist-led (ccS-led)

% events % events % events

PE Tasks

Informing 15.5 0.7 5.6

Refining 3.3 61.9 28.8

Extending 0 0 3.1

Applying 0 0 0.3

Conduct 12.1 12.1 9.2

Organization 10.8 24.6 19.9

Teaching Strategies

Interactive 61.1 81.8 51.6

Cognitive 3.1 0 22.4

Peer teaching 16.4 0 0

Exercise intensity and duration

Physically active time per 1 hour PE (min ± SD)

27.4 (±2.7) 35.0 (±2.4) 28.7 (±3.8)

PE active time spent in MVPA (% ± SD)

44.4 (±12.6) 65.6 (±13.1) 53.6 (±18.9)

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Expressive Attention Receptive Attention