1

Internalising symptoms and executive

function difficulties in adolescents with

and without Developmental Coordination

Disorder

Serif Omer

Submitted for the Degree of

Doctor of Psychology (Clinical Psychology)

School of Psychology Faculty of Health and Medical Sciences

University of Surrey

Guildford, Surrey

United Kingdom

September 2018

2

Abstract

Background: There is growing evidence that individuals with Developmental

Coordination Disorder (DCD) experience elevated internalising symptoms and

executive function (EF) difficulties compared to their typically developing (TD)

peers. Research also suggests that EFs are important for psychological wellbeing.

Aims: This study aimed to explore whether adolescents with DCD experience

greater levels of internalising symptoms and everyday EF difficulties than their TD

peers. It also explored whether EF difficulties mediate the relationship between DCD

status and internalising symptoms. Methods and procedures: Fourteen adolescents

with a diagnosis of DCD and 29 TD adolescents (ages 12-15) participated. A cross-

sectional survey was conducted to collect parent-reported EF difficulties and self-

reported internalising symptoms. Outcomes and results: Self-reported internalising

symptoms and parent-reported EF difficulties were significantly higher in the DCD

group compared to the TD group. A bias-corrected, bootstrapped mediation analysis

identified that the effect of DCD on internalising symptoms was mediated by parent-

reported EF difficulties. Exploratory analyses identified that this indirect effect was

greatest for symptoms of depression through behavioural regulation difficulties.

Conclusions and implications: These findings support previous research indicating

that adolescents with DCD experience greater levels of internalising symptoms and

EF difficulties than their TD peers. This highlights the need for increased awareness,

routine screening, and intervention for mental health and EF difficulties in people

with DCD. The findings also highlight the potential benefits of targeting EF deficits

in people with DCD to improve emotional wellbeing. However, larger scale,

longitudinal research is needed.

3

Keywords: Developmental Coordination Disorder, DCD, internalising

symptoms, depression, anxiety, executive functions

4

Acknowledgements

I would like to express thanks to my research supervisor, Dr Hayley Leonard,

for her support and expertise throughout all aspects of this research project. I would

also like to acknowledge Ana M. Jijon for her assistance with the data

collection/extraction for the literature review and Dr Harriet Tenenbaum who

provided critical feedback on the meta-analysis.

I am very grateful to the Dyspraxia Foundation for their help distributing

recruitment advertisements for the empirical research study. I would also like to

thank the schools and youth clubs that supported with data collection. I would like to

thank all the young people and their parents who kindly volunteered their time to

participate in my research.

Finally, I would like to thank my university tutors and placement supervisors

who have supported me throughout the clinical training programme.

5

Publications and presentations

Parts of this thesis have been published in:

Omer, S. (2018, June). Executive function and internalising problems in adolescents

with Developmental Coordination Disorder. Paper presented at the UK’s 7th

biennial academic and practitioner conference on Developmental

Coordination Disorder, Brunel University London, London.

Omer, S., Jijon, A.M., & Leonard, H.C. (In press). Internalising symptoms in

Developmental Coordination Disorder: A systematic review and meta-

analysis. Journal of Child Psychology and Psychiatry.

6

Table of Contents

Page

Abstract 2

Acknowledgements 4

Publications and presentations 5

Part 1: Major Research Project Empirical Paper - Internalising symptoms

and executive function difficulties in adolescents with and without

Developmental Coordination Disorder

7

Abstract 8

Introduction 10

Method 19

Results 27

Discussion 37

References 50

List of appendices 70

Appendices 71

Part 2: Major Research Project Literature review - Internalising symptoms

in Developmental Coordination Disorder: A systematic review and meta

analysis

122

Abstract 123

Introduction 125

Method 129

Results 135

Discussion 154

References 160

Appendix 173

Part 3: Summary of Clinical Experience 174

Part 4: Table of Assessments Completed During Training 177

7

Part 1: Major Research Project Empirical Paper

Internalising symptoms and executive function difficulties in adolescents

with and without Developmental Coordination Disorder

Word count: 9420

Statement of Journal Choice

Research in Developmental Disabilities

“Research in Developmental Disabilities” primarily publishes empirical studies of an

interdisciplinary nature that contribute to the understanding of problems associated with

developmental disabilities. It has published numerous cross-sectional studies

investigating the impact of Developmental Coordination Disorder. See Appendix A for

more details.

8

Abstract

Background: There is growing evidence that individuals with Developmental

Coordination Disorder (DCD) experience elevated internalising symptoms and executive

function (EF) difficulties compared to their typically developing (TD) peers. Research

also suggests that EFs are important for psychological wellbeing. Aims: This study

aimed to explore whether adolescents with DCD experience greater levels of

internalising symptoms and everyday EF difficulties than their TD peers. It also

explored whether EF difficulties mediate the relationship between DCD status and

internalising symptoms. Methods and procedures: Fourteen adolescents with a

diagnosis of DCD and 29 TD adolescents (ages 12-15) participated. A cross-sectional

survey was conducted to collect parent-reported EF difficulties and self-reported

internalising symptoms. Outcomes and results: Self-reported internalising symptoms

and parent-reported EF difficulties were significantly higher in the DCD group

compared to the TD group. A bias-corrected, bootstrapped mediation analysis identified

that the effect of DCD on internalising symptoms was mediated by parent-reported EF

difficulties. Exploratory analyses identified that this indirect effect was greatest for

symptoms of depression through behavioural regulation difficulties. Conclusions and

implications: These findings support previous research indicating that adolescents with

DCD experience greater levels of internalising symptoms and EF difficulties than their

TD peers. This highlights the need for increased awareness, routine screening, and

intervention for mental health and EF difficulties in people with DCD. The findings also

highlight the potential benefits of targeting EF deficits in people with DCD to improve

emotional wellbeing. However, larger scale, longitudinal research is needed.

9

Keywords: Developmental Coordination Disorder, DCD, internalising

symptoms, depression, anxiety, executive functions

10

Introduction

Developmental Coordination Disorder (DCD) is a neurodevelopmental disorder

affecting between 5-6% of children (American Psychiatric Association, 2013). It is

characterised by significant impairment in motor coordination which interferes with

everyday life, is evident in the early developmental period, and cannot be explained by

another medical condition or intellectual disability. Individuals with DCD might have

difficulties with self-care (e.g. tying shoe laces, brushing teeth), leisure activities (e.g.

catching a ball, balancing) and academic tasks (e.g. handwriting). However, the impact

of DCD also extends beyond these difficulties with motor tasks. Research has identified

that DCD can impact on a wide range of physical, social, and psychological domains

(Zwicker, Harris, & Klassen, 2013) and that difficulties can continue through childhood

into adulthood (Cousins & Smyth, 2003; Hill, Brown, & Sorgardt, 2011). Given the

relatively high prevalence of DCD, and evidence that it is often poorly understood by

healthcare and education professionals (Gaines, Missiuna, Egan, & McLean, 2008; B. N.

Wilson, Neil, Kamps, & Babcock, 2013), research exploring the wider impact of the

condition is important to develop more effective, holistic interventions for this

population.

DCD and internalising symptoms

One area that has recently received increased attention is the impact of DCD on

an individual’s mental health, specifically internalising symptoms (Mancini, Rigoli,

Cairney, Roberts, & Piek, 2016). ‘Internalising’ is a broader construct referring to

symptoms of both depression and anxiety, which have been found to commonly overlap

11

in childhood and adolescence (Eaton et al., 2013; Kovacs & Devlin, 1998). A systematic

review and meta-analysis of the literature identified that children and adolescents with

DCD experience greater levels of internalising symptoms than their TD peers (see Part

2). Although the reviewed studies tended to adopt a cross-sectional design, two

longitudinal studies were identified that found that a diagnosis of DCD in childhood

predicted internalising symptoms later on in adolescence (Harrowell, Hollén, Lingam, &

Emond, 2017; Wagner, Jekauc, Worth, & Woll, 2016). Research investigating this

relationship in community samples of children (i.e. not specifically focusing on

individuals diagnosed with DCD) has also identified that poor motor skills in childhood,

measured as a continuous construct, predict internalising symptoms in adolescence

(Piek, Barrett, Smith, Rigoli, & Gasson, 2010; Sigurdsson et al., 2002) and adulthood

(Poole et al., 2015). Additionally, there is evidence that interventions focused on

improving motor skills can have a positive effect on mental health (Piek et al., 2015).

Together, these findings would suggest a causal relationship between DCD and mental

health difficulties.

The Environmental-Stress Hypothesis was introduced as a framework to

understand this relationship (Cairney, Rigoli, & Piek, 2013). It proposes that the motor

impairments in DCD can expose an individual to a range of secondary psychosocial

stressors which, over time, can result in greater levels of internalising symptoms. Recent

research has explored a number of these secondary stressors, providing support for the

Environmental-Stress Hypothesis. For example, there is evidence that increased peer

victimisation (Campbell, Missiuna, & Vaillancourt, 2012), reduced leisure activities

(Raz-Silbiger et al., 2015), poorer self-esteem (Rigoli, Piek, & Kane, 2012), physical

12

inactivity (Li et al., 2018), reduced social support (Rigoli et al., 2017), and lower

perceived academic performance (Lingam et al., 2012) may all mediate the relationship

between motor difficulties and internalising symptoms. The findings would suggest that

targeting these psychosocial factors, in addition to the motor difficulties, could have

beneficial outcomes for the emotional wellbeing of people with DCD. As such, further

research exploring the mediating factors through which DCD might impact on

internalising symptoms will have important implications for treatment in this population.

DCD and executive function

Recent research has also investigated the role of executive functions (EF) in

DCD. EFs refer to a set of higher-order cognitive processes that regulate, monitor and

control cognition, emotions and behaviour in order to achieve a particular goal

(Diamond, 2013). Three core EFs have been identified consisting of inhibition (i.e. the

ability to control natural responses or ignore irrelevant stimuli), working memory (i.e.

the ability to temporarily hold information in mind whilst simultaneously manipulating

information) and cognitive flexibility (i.e. the ability to switch between thinking about

different concepts or tasks), which together underlie more complex EFs including

planning, problem solving and reasoning (Miyake et al., 2000).

It has been highlighted that there is an important overlap in the development of

motor skills and EFs, with both sharing underlying neural pathways involving the

prefrontal cortex and cerebellum (Diamond, 2000; Koziol, Budding, & Chidekel, 2012).

Compromise to these neural pathways has been implicated in the motor difficulties

experienced by people with DCD (Biotteau et al., 2016). As such, research has also

13

found that individuals with DCD perform worse on a wide range of EF tasks compared

to their TD peers (Leonard & Hill, 2015; P. H. Wilson, Ruddock, Smits-Engelsman,

Polatajko, & Blank, 2013). This includes performance-based tasks of inhibition

(Mandich, Buckolz, & Polatajko, 2002), working memory (Alloway, 2007), cognitive

flexibility (Wuang, Su, & Su, 2011) and planning (Piek et al., 2004). Individuals with

DCD also self-report greater difficulties with EF in their everyday life compared to TD

controls (Tal Saban, Ornoy, & Parush, 2014). Additionally, findings from longitudinal

studies have found motor difficulties in childhood predict EF difficulties at a later age

(Bernardi, Leonard, Hill, Botting, & Henry, 2018; Michel, Roethlisberger,

Neuenschwander, & Roebers, 2011). This would suggest that EF impairments are a

significant feature of DCD and may be inextricably linked to the motor difficulties that

characterise the disorder.

Executive function and internalising symptoms

Despite growing evidence that individuals with DCD experience greater levels of

both internalising symptoms and EF difficulties compared to their TD peers, there has

been no attempt to explore the relationship between the two within this population. The

Environmental-Stress Hypothesis has been an important contribution to the field in

understanding how motor difficulties can contribute to elevated internalising symptoms,

however it only considers the role of physical and psychosocial factors. Given the

impact of DCD on EFs, it is important to consider how these higher-order cognitive

processes might also impact on the mental health of individuals with DCD.

14

There is a growing body of literature highlighting the importance of EFs for

mental health. Meta-analytic reviews have identified EF deficits in both children

(Wagner, Müller, Helmreich, Huss, & Tadić, 2015) and adults (Snyder, 2013; Snyder,

Kaiser, Warren, & Heller, 2014) with depression and anxiety disorders. Neuroimaging

studies have also found the brain networks involved in EF to be atypical in individuals

with mood disorders (Koenigs & Grafman, 2009; Price & Drevets, 2010). Additionally,

there is evidence to suggest that EF difficulties precede internalising symptoms in

children and adolescents. For example, working memory (Evans, Kouros, Samanez-

Larkin, & Garber, 2016; Letkiewicz et al., 2014), inhibitory control (Lengua, 2006;

Martel et al., 2007; Nigg, Quamma, Greenberg, & Kusche, 1999; Riggs, Blair, &

Greenberg, 2003), cognitive flexibility (Evans et al., 2016) and global EF difficulties

(Han et al., 2016) measured during childhood have been found to prospectively predict

internalising symptoms. In support of this relationship, improvements in EF have been

found to mediate the positive effects of neurocognitive intervention programmes on

reducing internalising symptoms in children (Riggs, Greenberg, Kusché, & Pentz, 2006).

Together, these findings highlight the role of EF in mental health and the potential

importance it has for people with DCD.

The relationship between EFs and internalising symptoms can be understood

through a variety of possible pathways. One explanation is the role of EFs in emotion

regulation. Emotion regulation refers to the process of actively changing the intensity or

duration of an emotional response (Koole, 2009). High levels of maladaptive emotion

regulation strategies (e.g. avoidance, rumination, worry) and low levels of adaptive

emotion regulation strategies (e.g. problem solving, cognitive reappraisal) have been

15

associated with internalising symptoms (Garber, Braafladt, & Weiss, 1995; Mezulis,

Priess, & Hyde, 2011; Silk, Steinberg, & Morris, 2003). It has been suggested that EFs

play a key role in the effective use of these strategies (Joormann & D’Avanzato, 2010;

Schmeichel & Tang, 2015; Wante, Mezulis, Beveren, & Braet, 2017). For example,

cognitive flexibility impairments have been linked to increased internalising symptoms

through perseveration of negative thinking, such as worry and rumination (Brosschot,

Gerin, & Thayer, 2006; Demeyer, De Lissnyder, Koster, & De Raedt, 2012; Johnson,

2009). Difficulties with inhibition have been associated with depression through

increased rumination and reduced reappraisal strategies (Joormann & Gotlib, 2010).

Difficulties in updating working memory have also been linked with depression and

anxiety through increased rumination and worry (Meiran, Diamond, Toder, & Nemets,

2011; Owens, Stevenson, Hadwin, & Norgate, 2012). Generally, this research indicates

that individuals with EF deficits find it harder to shift their attention away from negative

emotional information and use fewer adaptive strategies, which contributes to higher

levels of depression and anxiety. In addition to emotion regulation, EFs are also

important for academic functioning (Best, Miller, & Naglieri, 2011) and social skills

(Dawson, Shear, & Strakowski, 2012). Difficulties with each of these areas can also

have implications for emotional wellbeing (Ende, Verhulst, & Tiemeier, 2016; Nilsen,

Karevold, Røysamb, Gustavson, & Mathiesen, 2013; Zhang, Zhang, Chen, Ji, & Deater-

Deckard, 2018).

16

The present study

Given the emerging evidence that individuals with DCD experience deficits in

EF abilities and the role that these higher-order cognitive processes have in

psychological wellbeing, it is likely that these deficits have important implications for

the mental health of people with DCD. To date, no research has investigated this

potential relationship between EF difficulties and internalising symptoms in DCD.

However, parallels can be drawn from research with other neurodevelopmental disorders

that impact on EF. For example, Gardiner and Iarocci (2018) found an association

between parent-rated EF difficulties and depression in children with an autism spectrum

disorder (ASD), suggesting that improving EFs could be an important target for reducing

internalising symptoms. More specifically, Lawson et al. (2015) found that a diagnosis

of ASD, compared to a TD group, predicted difficulties with cognitive flexibility which

in turn predicted higher levels of anxiety and depression. This suggests that individuals

with ASD experience greater levels of internalising symptoms than their TD peers and

that this relationship may be mediated through EF difficulties. EFs have been found to

have a similar explanatory role for the high levels of internalising symptoms

experienced in other childhood disorders, including spina bifida (Kelly et al., 2012).

The purpose of the present study, therefore, was to investigate EF difficulties and

internalising symptoms in adolescents with and without DCD to better understand these

difficulties in the disorder. First, the study set out to replicate previous research findings

that adolescents with DCD have higher levels of both EF difficulties and internalising

symptoms compared to TD adolescents. Second, it explored whether the impact of DCD

on internalising symptoms is mediated through the difficulties in EF that are often

17

reported in this population (see Figure 1). Adolescents were chosen as the focus for this

study given that much of the research into internalising symptoms in DCD has focused

on pre-adolescent children (see Part 2). Furthermore, there is some suggestion that the

impact of DCD on mental health may be greater for adolescents compared to younger

children (Missiuna, Moll, King, King, & Law, 2007; Skinner & Piek, 2001). Given that

adolescence is also generally considered a time of high risk for mental health difficulties

and an important period for the ongoing development of EFs (Blakemore & Choudhury,

2006; Ernst, Pine, & Hardin, 2006; Twenge & Nolen-Hoeksema, 2002), focusing the

present study on this age group was deemed highly relevant.

Figure 1. Mediation model depicting the indirect effect of DCD status on internalising

symptoms through EF difficulties

18

Previous research into EFs in DCD has focused predominantly on performance-

based measures of EF (Leonard & Hill, 2015; P. H. Wilson et al., 2013). Although these

tasks are useful for assessing the specific impact of DCD on individual components of

EF in controlled conditions, there is an argument that they do not always represent

functioning in the ‘real-world’ environment (Burgess et al., 2006; Toplak, West, &

Stanovich, 2013). Therefore, studies adopting more ecological measures of EF

difficulties, such as behaviour rating scales, are also necessary to complement the

findings from standardised, laboratory-based tasks. Indeed, Tal Saban et al. (2014) found

greater EF deficits in adults with DCD compared to TD adults based on self-report of

everyday EF difficulties. However, no prior research has explored everyday EF

difficulties in adolescents with DCD using such measures. Therefore, the present study

adopted a behaviour rating scale as its measure of EF (Gioia, Isquith, Guy, &

Kenworthy, 2000) to better understand how EF difficulties in day-to-day life are

impacted by DCD in adolescents.

A self-report measure of internalising symptoms (Ebesutani et al., 2012) was

adopted for the present study, given that parents may under-report the emotional

difficulties of adolescents (Cantwell, Lewinsohn, Rohde, & Seeley, 1997; Hope et al.,

1999; Smith, 2007; Sourander, Helstelä, & Helenius, 1999). A parent-reported measure

of everyday EF difficulties was used to minimise the impact of common method bias

that could otherwise be problematic for mediation analyses if self-report measures are

used for both the mediator and dependent variable (Podsakoff, MacKenzie, Lee, &

Podsakoff, 2003; Podsakoff, MacKenzie, & Podsakoff, 2012).

19

The present study, therefore, had three main hypotheses: (1) adolescents with

DCD would have greater self-reported internalising symptoms than TD adolescents; (2)

adolescents with DCD would have greater parent-reported EF difficulties than TD

adolescents; and (3) parent-reported EF difficulties would mediate the relationship

between DCD status (i.e. DCD vs. TD) and self-reported internalising symptoms (see

Figure 1).

Method

Design

The study adopted a quantitative cross-sectional design to measure EF

difficulties and internalising symptoms in a group of adolescents with DCD and a group

of TD adolescents at one point in time.

Participants

DCD group. Participants were eligible for the DCD group if they met the

following criteria: (i) a diagnosis of DCD which was confirmed by the researchers

through inspection of clinical reports, (ii) aged 12-years-0-months to 15-years-11-

months, (iii) scored ≤57 on the Developmental Coordination Disorder Questionnaire –

07 (DCDQ-07) to confirm the current presence of motor difficulties (see measures), and

(iv) had a parent/guardian willing to complete questionnaire measures. Adolescents were

excluded if they had a comorbid diagnosis of Attention Deficit Hyperactivity Disorder

(ADHD) or ASD, as reported by their parents, so that findings could be more easily

attributed to DCD. They were also excluded if they lived outside the United Kingdom

20

(UK), due to international variations in diagnosis and intervention, or if any of the

questionnaire measures were missing. Participants with DCD were recruited through

advertisements distributed via a national charity, registers of participants from previous

studies, a secondary school in England specialising in specific learning difficulties, and

word of mouth. Thirty-nine adolescents and their parents responded to the

advertisements, of which 30 went on to complete the initial screening questionnaire.

Fifteen were subsequently excluded due to the adolescent being older than 16 (n = 4),

reporting a diagnosis of ADHD (n = 2), reporting a diagnosis of ASD (n = 7), living

outside the UK (n = 1), or not providing clinical reports to confirm their diagnosis (n =

1). Of the remaining 15 participants that went on to complete the questionnaire

measures, the Revised Child Anxiety and Depression Scale – Short Version (RCADS-

25) was missing for one participant. As such, the DCD sample consisted of 14

adolescents and their parents.

TD group. Participants were eligible for the TD group if they met the following

criteria: (i) aged 12-years-0-months to 15-years-11-months, (ii) scored ≥58 on the

DCDQ-07, and (iii) had a parent/guardian willing to complete questionnaire measures.

Adolescents were excluded if they had a diagnosis of DCD, ADHD or ASD, as reported

by their parents. They were also excluded if they lived outside the UK or if any of the

questionnaire measures were missing. TD participants were recruited through

advertisements distributed via secondary schools and youth clubs in south-east England,

registers of participants from previous studies, and word of mouth. Forty adolescents

and their parents responded to the advertisements, of which 37 went on to complete the

initial screening questionnaire. Four were subsequently excluded due to the adolescent

21

being older than 16 (n = 2), reporting a diagnosis of ADHD (n = 1), and reporting a

diagnosis of ASD (n = 1). Of the remaining 33 participants that went on to complete the

questionnaire measures, three had scores below the cut-off on the DCDQ-07 and one did

not complete the RCADS-25. As such, the TD sample consisted of 29 adolescents and

their parents.

Measures

Motor coordination difficulties. The Developmental Coordination Disorder

Questionnaire (DCDQ-07; Wilson et al., 2009) is a 15-item parent-report questionnaire

that measures motor coordination in children and adolescents (see Appendix B). It

consists of three subscales that measure control during movement, fine motor skills, and

general coordination. It provides a total score ranging from 15 to 75 with higher scores

indicating better motor coordination. The DCDQ-07 is commonly used as a screening

measure for DCD. In adolescents, a cut-off of 57 or below indicates the possible

presence of DCD. The DCDQ-07 has been found to have high internal consistency

(Cronbach’s alpha, α = .94), concurrent validity with performance-based measures of

motor ability (r = .55), and a good ability to detect DCD (sensitivity: 88.5%; specificity:

75.6%) (Wilson et al., 2009). In the current study, all parents were asked to complete the

DCDQ-07 to confirm group assignment and to obtain a measure of the severity of motor

difficulties in both study groups. Cronbach’s alpha for the DCDQ-07 Total score in the

current study was high (α = .98).

Internalising symptoms. The Revised Child Anxiety and Depression Scale –

Short Version (RCADS-25; Ebesutani et al., 2012) is a 25-item self-report questionnaire

22

that assesses depression (10 items) and anxiety (15 items) in children and adolescents

(see Appendix C). Adolescents are asked to rate how often they have been experiencing

difficulties on a four-point Likert-type scale from 0 (Never) to 3 (Always). The RCADS-

25 provides a total internalising symptoms score, in addition to separate subscale scores

for depression and anxiety. Raw scores are converted to age- and gender-standardised T-

scores based on normative reference groups (M = 50, SD = 10). T-scores of 65 or more

can be considered borderline clinically significant. The RCADS-25 has been found to

have acceptable internal reliability in both community (Anxiety, α = .94; Depression, α

= .79) and clinic-referred samples (Anxiety, α = .96; Depression, α = .80), and can

discriminate children with anxiety disorders and depression (Ebesutani et al., 2012). All

adolescents were asked to complete the RCADS-25 as a measure of internalising

symptoms. Cronbach’s alpha for the total score and the subscale scores in the current

study were high (Total, α = .92; Depression, α = .86; Anxiety, α = .90).

EF difficulties. The Behaviour Rating Inventory of Executive Function (BRIEF;

Gioia, Isquith, Guy, & Kenworthy, 2000) is an 86–item questionnaire that assesses EF

deficits in everyday life (see Appendix D). Parents are asked to rate their child’s

behaviour on a three-point Likert-type scale (‘Never a problem’, ‘Sometimes a

problem’, ‘Often a problem’). The BRIEF consists of eight clinical subscales that form

two composite indexes, the Behavioural Regulation Index (BRIEF BRI; i.e. inhibition,

shifting, emotional control) and the Metacognitive Index (BRIEF MCI; i.e. initiation,

working memory, planning, organisation of materials, monitoring). It also provides an

overall General Executive Composite (BRIEF GEC). Raw scores are converted to age-

and gender-standardised T-scores based on normative reference groups (M = 50, SD =

23

10). T-scores of 65 or more are suggested as the threshold for clinical significance

(Gioia et al., 2000). The BRIEF has been found to have high internal consistency (α =

.82-.98), test-retest reliability (r = .72-.84), and demonstrates predictive, convergent, and

divergent validity (Gioia et al., 2000). The Cronbach’s alpha for the BRIEF GEC and the

two subscale indexes in the present study were high (GEC, α = .98; BRI, α = .96; MCI, α

= .98).

Procedure

Advertisements for the study were distributed widely, as described in the

participants section (see Appendix E). This included via email, newsletters, social

media, and word of mouth. Interested participants were asked to read an information

sheet containing the study details (see Appendix F). Parents were asked to sign informed

consent whilst adolescents were asked to sign informed assent (see Appendices G and

H). Parents then completed an initial eligibility questionnaire (see Appendix I). Those

meeting criteria for the study were asked to complete the main questionnaires as part of

a survey. This included a section for the parent-report questionnaires and a section for

the adolescent self-report questionnaire. A survey containing the questionnaires was

available in paper form and online using Qualtrics survey software, depending on

participant preferences. At the end of the survey, participants were provided an

opportunity to enter a prize draw for a £100 Amazon voucher. The study received a

favourable ethical opinion from the University of Surrey Faculty of Health and Medical

Sciences Ethics Committee (see Appendix J).

24

Data analysis

Preliminary analyses. Data were analysed using IBM SPSS Statistics version

24. Scale and subscale scores were calculated for each of the questionnaire measures.

Missing data on the questionnaires were imputed using the mean of the available scores

for that scale. The data were screened for univariate outliers and parametric assumptions

within the DCD and TD groups separately. Homogeneity of variance was explored for

independent samples t-tests. Additionally, multivariate outliers, independence of errors,

linearity, homoscedasticity, normally distributed errors, homogeneity of regression, and

multicollinearity were explored for regression analyses. Descriptive statistics were

calculated to characterise the demographics for each group, with differences explored

using independent samples t-tests and chi-square tests. For each group, one-sample t-

tests were conducted to compare the RCADS-25 and BRIEF scores to the normative

samples for each measure.

Group comparisons. To test Hypotheses 1 and 2, internalising symptoms

(RCADS-25 Total) and EF difficulties (BRIEF GEC) were compared between the DCD

and TD groups using separate independent samples t-tests with alpha values set at .05.

Where parametric assumptions were not met, 95% bias-corrected and accelerated (BCa)

bootstrapped confidence intervals were calculated for the mean difference, based on

10,000 samples. If confidence intervals did not cross zero, then the difference can be

interpreted as significant. Based on guidelines, it was not deemed appropriate to adjust

for multiple comparisons since only a small number of pre-planned, specific hypotheses

were explored (Streiner & Norman, 2011). Instead, the exact p-values and confidence

intervals are reported to enable appropriate interpretation. Cohen’s d was also calculated

25

for each comparison as a measure of the effect size, whereby 0.3, 0.5 and 0.8 equate to

small, medium and large effect sizes respectively (Cohen, 1992).

Mediation analysis. A simple mediation analysis was conducted to test for an

indirect effect of DCD status on internalising symptoms through EF difficulties

(Hypothesis 3). DCD Status was dummy coded for these analyses (TD = 0, DCD = 1).

First, Pearson’s correlation coefficients were calculated to explore zero-order

correlations between all study variables and to determine whether demographics should

be included as covariates. 95% BCa bootstrap confidence intervals were calculated for

the correlation coefficients due to deviations from normality in some study variables.

The mediation analysis was then conducted using the PROCESS macro for SPSS

(Hayes, 2013). A bootstrapping approach was used based on 10,000 samples with

replacement, to calculate a 95% bias-corrected confidence interval for the indirect effect

(path ab; see Figure 1). If the confidence interval for the indirect effect does not cross

zero, then it can be considered significant. This approach makes no assumptions about

the sampling distribution of the indirect effect, increases power, minimises the risk of

Type II error, and is recommended for small samples (Fritz & MacKinnon, 2007;

Preacher & Hayes, 2004, 2008). The partially standardised effect size was calculated

which represents the number of standard deviations on the dependent variable (RCADS-

25 Total) by which the DCD and TD groups differ because of the indirect path. Given its

ease of interpretation, this measure is recommended for use in mediation analyses with a

dichotomous independent variable (Hayes, 2013; Lachowicz, Preacher, & Kelley, 2018).

Post-hoc analyses. Additional post-hoc analyses were conducted to better

understand the nature of any significant findings. This includes further independent

26

samples t-tests and mediation analyses using the subscales of the RCADS-25 and

BRIEF. These further analyses were exploratory to develop additional hypotheses and

therefore, based on guidelines, no adjustment for multiple testing was made (Streiner &

Norman, 2011). Again, p-values and confidence intervals are reported to enable

appropriate interpretation.

Power calculation

Based on previous research, a medium-large effect size (d = 0.6) was expected

for the group differences in internalising symptoms (Missiuna et al., 2014; see also Part

2) and a large effect (d = 0.8) for EF difficulties (Tal-Saban, Ornoy, & Parush, 2014; P.

H. Wilson et al., 2013). Power calculations, conducted using G Power v.3.1 (Faul,

Erdfelder, Lang, & Buchner, 2007) identified that a sample size of 90 would be required

to detect an effect size of 0.6 with 80% power and a 5% significance level. As such, the

study sample size of 43 was underpowered to detect a medium-large effect for

Hypotheses 1 and 2.

Power calculations for mediation analyses can be calculated based on the effect

size of path a and path b (Fritz & MacKinnon, 2007). As described above, a large effect

was expected for path a. A medium-large effect was also expected for path b, based on

previous research into the relationship of the BRIEF with internalising symptoms

(Ghassabian et al., 2014; White, Jarrett, & Ollendick, 2012). Fritz & MacKinnon (2007)

estimated that, for bias-corrected bootstrapping analyses, a minimum sample of 54 is

required to detect an indirect effect, with 80% power, when the effect of path a is large

27

and path b is medium (a conservative estimate). As such, the study sample size of 43

was slightly underpowered to detect the expected indirect effect.

Results

Preliminary analysis and descriptive statistics

The final sample consisted of 14 adolescents in the DCD group and 29

adolescents in the TD group. The BRIEF was missing a single item for three participants

which were imputed using the mean values of the available scores. The data were

screened for parametric assumptions (see Appendices K and L). No univariate or

multivariate outliers were identified. Both the RCADS-25 and BRIEF scores were

positively skewed in the TD group and negatively skewed in the DCD group.

Table 1. Summary of the demographics in the DCD and TD groups

Variable DCD

(n = 14)

TD

(n = 29)

Age, M (SD) years 13.84 (1.13) 13.72 (1.08)

Gender

Male, n (%) 9 (64.3%) 16 (55.2%)

Female, n (%) 5 (35.7%) 13 (44.8%)

DCDQ-07 Total, M (SD) 28.64 (8.54) 69.90 (4.86)

DCDQ-07 Control, M (SD) 12.50 (4.62) 28.10 (2.55)

DCDQ-07 Fine, M (SD) 7.71 (2.46) 18.17 (1.83)

DCDQ-07 General, M (SD) 8.43 (2.71) 22.93 (1.96)

DCD: Developmental Coordination Disorder; DCDQ-07: Developmental Coordination Disorder

Questionnaire – 07; TD: Typically developing

28

Table 1 summarises the descriptive statistics of the sample. Overall, there were

more males than females in the sample. There was a higher percentage of males in the

DCD group, however this difference was not significant, χ2 (1) = 3.22, p = 0.57. There

was also no significant difference in ages between the two groups, t (41) = -3.50; p =

0.74. Age and gender were, therefore, not included as covariates in group comparisons.

As expected, the DCD group had significantly lower total scores on the DCDQ-07, t

(41) = -20.23, p < .001, than the TD group.

The scores for the study measures are summarised in Table 2. Overall, the mean

total score on the RCADS-25 was lower in the TD group compared to the normative

sample and higher in the DCD group. One sample t-tests within each group found this

difference to be significant in the TD group, t (28) = -4.12, p < .001, but not significantly

different in the DCD group, t (13) = 0.69, p = .50. Within the TD group, one participant

(3.4%) scored above the clinical cut-off (T ≥ 65) for anxiety, but no participants scored

above cut-off for depression or overall internalising symptoms. Within the DCD group,

one participant (7.1%) scored above the clinical cut-off for depression, two for anxiety

(14.3%), and four (28.6%) for overall internalising symptoms.

The mean scores on the BRIEF GEC in the TD group were broadly comparable

with the normative samples, though the scores in the DCD group were higher. This

difference was significant in the DCD group, t (13) = 15.26, p = <.001, but not in the TD

group, t (27) = -2.01, p = .055. Only one participant (3.4%) scored above the clinical

cut-off (T ≥ 65) on the BRIEF GEC in the TD group. However, thirteen (93%) of the

DCD participants scored above the cut-off, indicating that the clear majority experienced

significant EF difficulties according to parent report.

29

Group differences

Independent samples t-tests were conducted to compare the two groups on

internalising symptoms (RCADS Total, Hypothesis 1) and EF difficulties (BRIEF GEC,

Hypothesis 2). Given that the distribution of the variables deviated from normality (see

Appendix K), bootstrapping with 10,000 samples was used to generate BCa 95%

confidence intervals for the mean difference.

Table 2. Summary of the scores for study variables

Variable DCD

(n = 14)

TD

(n = 29)

Mean

difference BCa 95% CI

RCADS-25 Total, M (SD) 52.23 (12.09) 41.98 (10.29) 10.24 2.96, 17.24*

RCADS-25 Depression, M (SD) 54.12 (9.64) 41.19 (9.33) 12.93 6.78, 18.78*

RCADS-25 Anxiety, M (SD) 50.49 (12.83) 44.19 (10.83) 6.30 -0.91, 13.64

BRIEF GEC, M (SD) 77.07 (6.64) 46.69 (8.80) 30.38 25.65, 34.77*

BRIEF BRI, M (SD) 75.36 (8.88) 48.28 (9.37) 27.08 21.42, 32.75*

BRIEF MCI, M (SD) 74.50 (7.21) 46.97 (9.13) 27.53 22.31, 32.44*

* 95% BCa bootstrapped confidence interval is significant

BCa: Bias-corrected and accelerated; BRI: Behavioural Regulation Index; BRIEF: Behaviour Rating

Inventory of Executive Function; CI: Confidence interval; DCD: Developmental Coordination Disorder;

GEC: Global Executive Composite; MCI: Metacognitive Index; RCADS-25: Revised Child Anxiety and

Depression Scale – Short version; TD: Typically developing

Internalising symptoms. Adolescents in the DCD group reported greater levels

of internalising symptoms (M = 52.23; SE = 3.23) compared to adolescents in the TD

group (M = 41.98; SE = 1.91). This difference, 10.24, BCa 95% CI [2.96, 17.24], was

significant, t (41) = 2.89, p = 0.006 and represents a large effect size, d = 0.90.

EF difficulties. Adolescents in the DCD group reported greater levels of EF

difficulties (M = 77.07; SE = 1.77) compared to adolescents in the TD group (M = 46.69;

30

SE = 1.63). This difference, 30.38, BCa 95% CI [25.65, 34.77]; p < .001) was

significant, t (41) = 11.42, p < .001 and represents a large effect size, d = 3.57.

Intercorrelations:

Intercorrelations between the study variables were computed using Pearson’s

correlation coefficients. Bootstrapped BCa 95% confidence intervals were calculated,

given the deviation from normality for some variables. There were significant

correlations between the independent, mediator and dependent variables as expected (see

Table 3). However, no significant correlation was identified between DCD status and the

RCADS-25 Anxiety subscale. Neither age nor gender were significantly correlated with

any of the study variables and were, therefore, not included as covariates in the

mediation analyses.

Mediation analysis

A simple mediation analysis was conducted to test each of the paths in the

mediation model. As shown in Figure 2 and Table 4, adolescents with a diagnosis of

DCD had higher levels of self-reported internalising symptoms, c = 10.24, p = .006, and

higher levels of parent-reported EF difficulties, a = 30.38, p <.001, compared to TD

adolescents. Adolescents with higher levels of parent-reported EF difficulties also self-

reported higher levels of internalising symptoms after controlling for DCD status, b =

0.55, p = .007. A bias-corrected (BC) bootstrap confidence interval for the indirect

effect, based on 10,000 bootstrap samples, did not cross zero, ab = 16.62, BC 95% CI

31

Table 3. Pearson correlation coefficients of variables with 95% bias-corrected and accelerated bootstrapped confidence intervals

* 95% BCa bootstrapped confidence interval is significant

BCa: Bias-corrected and accelerated; BRI: Behavioural Regulation Index; BRIEF: Behaviour Rating Inventory of Executive Function; CI: Confidence

interval; DCD: Developmental Coordination Disorder; GEC: Global Executive Composite; MCI: Metacognitive Index; RCADS-25: Revised Child Anxiety

and Depression Scale – Short version.

Variable 1 2 3 4 5 6 7 8

1. DCD status -

2. BRIEF GEC .87*

(.78, .94)

-

3. BRIEF BRI .82*

(.70, .90)

.93*

(.88, .97)

-

4. BRIEF MCI .84*

(.73, .92)

.96*

(.92, .99)

.83*

(.73, .90)

-

5. RCADS-25 Total .41*

(.10, .66)

.54*

(.33, .73)

.54*

(-.32, .73)

.49*

(.26, .69)

-

6. RCADS-25 Depression .55*

(.28, .77)

.62*

(.40, .79)

.63*

(.42, .80)

.57*

(.34, .75)

.86*

(.74, .94)

-

7. RCADS-25 Anxiety .25

(-.08, .55)

.40*

(.16, .63)

.40*

(.14, .64)

.36*

(.10, .60)

.94*

(.90, .97)

.64*

(.40, .82)

-

8. Age .06

(-.26, .38)

.15

(-.41, .17)

.07

(-.23, .36)

.16

(-.16, .47)

.02

(-.28, .33)

.07

(-.24, .39)

-.02

(-.29, .26)

-

9. Gender -.09

(-.36, .20)

.76

(-.33, .25)

-.02

(-.30, .28)

-.06

(-.35, .23)

.13

(-.16, .41)

.15

(-.15, .43)

.10

(-.20, .39)

-.11

(-.41, .17)

32

[4.10, 27.05]. The direct effect of DCD status on internalising symptoms was also no

longer significant after accounting for EF difficulties, c’ = -6.38, p = .346. The partially

standardised indirect effect was 1.41, BC 95% CI [0.30, 2.37]. These results indicate that

adolescents with DCD reported internalising symptoms that, on average, were 1.41

standard deviations (approximately 17 points on the RCADS-25) higher compared to TD

adolescents because of the indirect effect through parent-reported EF difficulties.

Table 4. Results of the mediation analysis using the RCADS-25 Total scores and BRIEF

GEC

* 95% bias-corrected bootstrapped confidence interval significant

BRIEF GEC: Behaviour Rating Inventory of Executive Function – Global Executive Composite; DV:

Dependent variable (RCADS-25); IV: Independent variable (group status); M: Mediator (BRIEF

GEC); RCADS-25: Revised Child Anxiety and Depression Scale – Short version.

Post-hoc analyses

Exploratory analyses were conducted using the subscales of the RCADS-25 and

BRIEF. Independent samples t-tests were conducted to compare the two groups. Given

that the distribution of the variables deviated from normality (see Appendix M),

bootstrapping with 10,000 samples was used to generate bias-corrected and accelerated

95% confidence intervals for the mean differences.

B

coefficient

SE t p-value Bias-corrected bootstrap

95% CI

Effect of IV on M (Path a) 30.38 2.66 11.42 <.001

Effect of M on DV (Path b) 0.55 0.19 2.85 .007

Total Effect (Path c) 10.24 3.54 2.89 .006

Direct effect (Path c’) -6.38 6.69 -0.95 .346

Indirect Effect (a x b) 16.62 [4.16, 27.04]*

33

Figure 2. Results of the mediation analysis using the RCADS-25 Total scores and

BRIEF GEC

RCADS-25 subscales. On the RCADS-25, adolescents in the DCD group

reported greater levels of depression (M = 54.12; SE = 2.58) compared to adolescents in

the TD group (M = 41.19; SE = 1.73). This difference, 12.93, BCa 95% CI [6.78, 18.78],

was significant, t (41) = 4.21, p < .001, and represents a large effect size, d = 1.32.

Adolescents in the DCD group also reported greater levels of anxiety (M = 50.49; SE =

3.43) compared to adolescents in the TD group (M = 44.19; SE = 2.01). This difference,

6.30, BCa 95% CI [-0.91, 13.64], was not significant t (41) = 1.68, p = .100. However, it

did represent a medium effect size (d = 0.52).

BRIEF subscales. On the BRIEF, adolescents in the DCD group had greater

levels of parent-reported behavioural regulation difficulties (M = 75.36; SE = 2.37)

compared to adolescents in the TD group (M = 48.28; SE = 1.74). This difference, 27.08,

BCa 95% CI [21.42, 32.75], was significant, t (41) = 9.03, p < .001, and represents a

34

large effect size, d = 2.82. Adolescents in the DCD group also had greater levels of

parent-reported metacognitive difficulties (M = 74.50; SE = 1.93) compared to

adolescents in the TD group (M = 46.99; SE = 1.70). This difference, 27.53, BCa 95%

CI [22.31, 32.44], was significant t(41) = 9.87, p < .001, and represents a large effect

size (d = 3.08).

Subscale mediator models. Two parallel multiple mediation models were

conducted to explore the relationship between DCD status and each subscale of the

RCADS-25 (Depression and Anxiety) separately. For both models, the separate

subscales on the BRIEF (BRIEF BRI and BRIEF MCI) were included as parallel

mediators (path ab1 and ab2, respectively). This allowed further exploration of the

potential paths through which EF difficulties mediate the relationship between DCD and

internalising symptoms. The relevant assumptions were confirmed for each model prior

to analysis (see Appendix N). The results are summarised in Table 5.

Depression symptoms: A parallel multiple mediation model was conducted to

explore the effect of DCD status on depression through both behavioural regulation

difficulties and metacognitive difficulties. Bias-corrected bootstrap confidence intervals

for the indirect effects, based on 10,000 bootstrap samples, found a significant indirect

effect of behavioural regulation difficulties, a1 = 9.77, 95% CI [1.81, 17.74], but not

metacognitive difficulties, a2 = 2.05, 95% CI [-8.59, 12.87]. The partially standardised

indirect effect through behavioural regulation difficulties was 0.88, BC 95% CI [0.12,

1.56]. The findings did not change when investigating the mediators independently in

two simple mediation models.

35

Anxiety symptoms: Although no significant difference between the two groups in

levels of anxiety symptoms was identified, evidence of an association between the

independent and dependent variables is not a requirement for mediation (Zhao, Lynch,

& Chen, 2010). Therefore, a parallel multiple mediation model was also conducted to

explore the effect of DCD status on anxiety through both behavioural regulation

difficulties and metacognitive difficulties. Bias-corrected bootstrap confidence intervals

for the indirect effects, based on 10,000 bootstrap samples, crossed zero for both

behavioural regulation difficulties, a1 = 8.84, 95% CI [-3.09, 20.48] and metacognitive

difficulties, a2 = 6.07, 95% CI [-8.82, 21.84], suggesting no significant indirect effect.

Table 5. Results of the parallel multiple mediation models using the subscales of the

BRIEF and RCADS-25

B

coefficient

SE t p-value Bias-corrected bootstrap

95% CI

DV: RCADS-25 Depression

Path a1: IV-M1 27.08 3.00 9.03 <.001

Path b1: M1-DV 0.36 0.17 2.13 .040

Path a2: IV-M2 27.53 2.79 9.87 <.001

Path b2: M2-DV 0.07 0.18 0.41 .686

Path c: Total Effect 12.93 3.07 4.21 <.001

Path c’: Direct effect 1.11 5.81 0.19 .849

a1b1: Indirect effect 9.77 [1.81, 17.74]*

a2b2: Indirect effect 2.05 [-8.59, 12.87]

DV: RCADS-25 Anxiety

Path a1: IV-M1 27.08 3.00 9.03 <.001

Path b1: M1-DV 0.33 0.21 1.56 .126

Path a2: IV-M2 27.53 2.79 9.87 <.001

Path b2: M2-DV 0.22 0.22 0.98 .333

Path c: Total Effect 6.30 3.74 1.68 .100

Path c’: Direct effect -8.61 7.15 -1.20 .236

a1b1: Indirect effect 8.84 [-3.09, 20.48]

a2b2: Indirect effect 6.07 [-8.82, 21.84]

* 95% bias-corrected bootstrapped confidence interval significant

36

BRIEF: Behaviour Rating Inventory of Executive Function; DV: Dependent variable; IV:

Independent variable (group status); M1: Mediator (BRIEF Behaviour Regulation Index); M2:

Mediator (BRIEF Metacognitive Index); RCADS-25: Revised Child Anxiety and Depression Scale –

Short version.

TD sample. Due to the small sample in the DCD group and the potential

heterogeneity between the two groups due to differing sampling strategies, the mediation

analysis was repeated in the TD group only (see Table 6). For this model, the total score

on the DCDQ-07 was used as a continuous independent variable. The three TD

participants excluded from the main analysis due to scoring below the cut-off on the

DCDQ-07 were included in this analysis (n = 32; see Appendix O for exploration of

assumptions). The results found that poorer motor coordination in TD adolescents was

associated with higher levels of self-reported internalising symptoms, c = -0.53, p =

.028, and higher levels of parent-reported EF difficulties, a = -0.66, p <.001. TD

adolescents with higher levels of parent-reported EF difficulties also self-reported higher

levels of internalising symptoms after controlling for motor coordination, b = 0.71, p =

.001. A bias-corrected bootstrap confidence interval for the indirect effect, based on

10,000 bootstrap samples, did not cross zero, ab = -0.47, BC 95% CI [-0.84, -0.16]. The

direct effect of motor coordination on internalising symptoms was also no longer

significant after accounting for EF difficulties, c’ = -0.06, p = .787. The completely

standardised indirect effect was -0.34, 95% BC CI [-0.57, -0.13]. These results indicate

that, in TD adolescents, a decrease of one standard deviation in motor coordination skills

is associated with, on average, an increase of 0.34 standard deviations in self-report

internalising symptoms because of the indirect effect through parent-reported EF

difficulties.

37

Table 6. Results of the mediation analysis based on the TD group only

* 95% bias-corrected bootstrapped confidence interval significant

BRIEF: Behaviour Rating Inventory of Executive Function; DV: Dependent variable (Revised Child

Anxiety and Depression Scale – Short version); IV: Independent variable (Developmental Coordination

Disorder Questionnaire – 07 Total Score); M: Mediator (Behaviour Rating Inventory of Executive

Function).

Discussion

The aim of this study was to investigate internalising symptoms and EF

difficulties in adolescents with and without DCD. As hypothesised, adolescents with

DCD had greater levels of self-reported internalising symptoms (Hypothesis 1) and

greater levels of parent-reported EF difficulties (Hypothesis 2) compared to TD

adolescents. The results also identified that parent-reported EF difficulties mediated the

relationship between DCD status and internalising symptoms (Hypothesis 3). Further

exploratory analyses identified that the difference in internalising symptoms between the

two groups was greatest for symptoms of depression and that this effect was mediated

by behavioural regulation difficulties, but not metacognitive difficulties.

Internalising symptoms in DCD

The findings replicate previous research identifying that individuals with DCD

experience greater levels of internalising symptoms than their TD peers (Mancini et al.,

2016; Missiuna & Campbell, 2014, see Part 2 for a review). More specifically, the

B

coefficient

SE t p-value Bias-corrected bootstrap

95% CI

Effect of IV on M (Path a) -0.66 0.18 -3.60 .001

Effect of M on DV (Path b) 0.71 0.19 3.70 .001

Total Effect (Path c) -0.53 0.23 -2.31 .028

Direct effect (Path c’) -0.06 0.23 -0.27 .787

Indirect Effect (a x b) -0.47 [-0.84, -0.16]*

38

findings are consistent with the few existing studies that have investigated internalising

symptoms in adolescents with the disorder (Harrowell et al., 2017; Li et al., 2018;

Skinner & Piek, 2001; Wagner et al., 2016). The magnitude of this effect was also large,

with adolescents in the DCD group scoring almost one standard deviation higher on self-

reported internalising symptoms compared to the TD adolescents. This difference can be

considered clinically significant (Norman, Sloan, & Wyrwich, 2003) and would equate

to the adolescents with DCD reporting one point higher on at least ten items of the

RCADS-25.

However, the magnitude of the difference in the present study was greater than

might be expected based on past research, since meta-analytic findings suggest the

difference to be around half a standard deviation (see Part 2). It is likely that the effect in

the present study was inflated due to the use of convenience sampling, which has been

found to result in greater effect sizes (Crane, Sumner, & Hill, 2017; Hill & Brown, 2013;

Pratt & Hill, 2011; Wagner, Bos, Jascenoka, Jekauc, & Petermann, 2012; Watson &

Knott, 2006) compared to studies using a population-based screening strategy (Campbell

et al., 2012; Francis & Piek, 2003; Harrowell et al., 2017; Missiuna et al., 2014; Skinner

& Piek, 2001; Wagner et al., 2016). Indeed, the TD group in the present study reported

significantly lower internalising symptoms than the normative population (Chorpita,

Moffitt, & Gray, 2005) with no participants scoring above the clinical threshold,

suggesting it was an unrepresentative sample. Despite the potentially inflated effect size,

the direction of the effect is consistent with higher quality studies suggesting individuals

with DCD experience greater levels of internalising symptoms than their TD peers

(Harrowell et al., 2017; Wagner et al., 2016).

39

These findings are in line with the growing consensus that the impact of DCD

extends beyond the core motor difficulties that characterise the disorder and includes

significant implications for the mental health of those affected. The environmental-stress

hypothesis (Cairney et al., 2013) would suggest that the motor difficulties experienced

by the DCD group impacts on their mental health indirectly through a variety of

secondary psychosocial stressors. Although these stressors were not measured in the

present study, they might include increased peer victimisation (Campbell et al., 2012),

reduced leisure activities (Raz-Silbiger et al., 2015), poorer self-esteem (Rigoli, Piek, &

Kane, 2012), physical inactivity (Li et al., 2018), reduced social support (Rigoli et al.,

2017), and lower perceived academic performance (Lingam et al., 2012).

Interestingly, the findings revealed that the two groups differed significantly on

symptoms of depression but not anxiety. This contradicts previous research that has

found DCD to impact on specific measures of both depression (Campbell et al., 2012;

Francis & Piek, 2003; Harrowell et al., 2017; Hill & Brown, 2013; Missiuna et al., 2014;

Piek et al., 2007; Watson & Knott, 2006) and anxiety (Hill & Brown, 2013; Missiuna et

al., 2014; Pratt & Hill, 2011; Schoemaker & Kalverboer, 1994). The failure to detect a

difference in anxiety symptoms likely reflects insufficient power in the present study,

since a medium effect size was still found. However, these preliminary findings do

suggest that the impact of DCD on internalising symptoms in adolescents may be greater

for depressive symptoms than anxiety symptoms. Indeed, Missiuna et al. (2014) reported

a greater effect size for self-reported depressive symptoms than for self-reported anxiety

symptoms in adolescents with DCD compared to their TD peers. This suggestion would

fit with findings that some of the secondary psychosocial stressors proposed in the

40

environmental-stress hypothesis are more often linked with depression than they are

with anxiety, including reduced self-esteem (Sowislo & Orth, 2013) and peer

victimisation (Hawker & Boulton, 2000).

EF difficulties in DCD

The present findings are also consistent with previous research highlighting EF

deficits in DCD (Alloway, 2007; Bernardi et al., 2018; Leonard & Hill, 2015; Mandich

et al., 2002; P. H. Wilson et al., 2013; Wuang et al., 2011). The DCD group was found

to have significantly higher levels of EF difficulties for both behavioural regulation and

metacognitive functions. This is in line with past research highlighting difficulties for

people with DCD across a wide range of EF task, including inhibition, cognitive

flexibility, working memory and planning (Leonard & Hill, 2015). These difficulties can

be understood through the shared underlying neurological mechanisms for both motor

skills and EFs, which include the prefrontal cortex and cerebellum (Diamond, 2000). As

such, the underdevelopment of motor skills that characterise DCD are closely

interrelated with the EF deficits (Koziol et al., 2012; Rigoli, Piek, Kane, & Oosterlaan,

2012).

This study is also the first to identify EF difficulties in adolescents with DCD

using a behaviour rating scale of EF. This suggests that the EF deficits observed on

performance-based measures in adolescents with DCD also generalises to EF difficulties

in everyday life, supporting similar findings in an adult sample (Tal Saban et al., 2014).

The effect size in the present study was also very large, with parent-reported EF

difficulties in the DCD group being over 3 standard deviations higher than in the TD

41

group. Although a large effect was expected based on past research (Tal Saban et al.,

2014; P. H. Wilson et al., 2013), the magnitude was even greater in the present study. It

is again possible that the effect was inflated due to design limitations, especially the use

of a convenience sampling strategy. However, these preliminary findings might suggest

that the EF difficulties experienced by adolescents with DCD may be even more marked

in day-to-day life than has been previously identified on highly structured, laboratory-

based tasks.

Internalising symptoms in DCD are mediated by EF difficulties

A notable finding in the present study is that the elevated internalising symptoms

in adolescents with DCD, compared to their TD peers, was mediated by EF difficulties.

This is consistent with expectations, given evidence that EF deficits are associated with

mental health difficulties (Evans et al., 2016, 2016; Han et al., 2016; Lengua, 2006;

Letkiewicz et al., 2014; Martel et al., 2007; Nigg et al., 1999; Riggs et al., 2003). This

mediating effect also sits alongside the findings of research with other childhood

disorders that impact on both EFs and internalising symptoms (Kelly et al., 2012;

Lawson et al., 2015). Research has identified that EFs are important for the effective use

of appropriate emotion regulation strategies (Joormann & D’Avanzato, 2010;

Schmeichel & Tang, 2015). It is possible that the EF impairments in the adolescents

with DCD contributed to an increased use of maladaptive emotion regulation strategies

such as rumination (Demeyer et al., 2012; Johnson, 2009; Meiran et al., 2011), worry

(Brosschot et al., 2006) and withdrawal (Wante et al., 2017), and a reduced use of

adaptive strategies such as reappraisal (Joormann & Gotlib, 2010) and distraction

42

(Wante et al., 2017). This, in turn, may have contributed to increased levels of

internalising symptoms. EF deficits may also have impacted on other areas of

functioning, including academic performance (Best et al., 2011) and social functioning

(Dawson et al., 2012), which may have contributed to elevated internalising symptoms

(Ende et al., 2016; Nilsen et al., 2013; Zhang et al., 2018).

It is also of note that, after accounting for the indirect effect through EF

difficulties, the direct effect of DCD on internalising symptoms was no longer

significant. Additionally, the effect size of the mediation analysis indicated that the

adolescents with DCD reported internalising symptoms that were over one standard

deviation higher, compared to TD adolescents, due to the indirect effect through EF

difficulties. This highlights that the role of EF deficits in explaining internalising

symptoms in DCD may be a major one. Yet previous attempts to explain the increased

risk of internalising symptoms in DCD (i.e. the environmental-stress hypothesis) have

failed to include these higher-order cognitive abilities in their model (Cairney et al.,

2013; Mancini et al., 2016). The environmental-stress hypothesis may benefit from the

inclusion of EFs as another mediating factor between DCD and internalising symptoms.

This might be through previously untested pathways, including its impact on emotion

regulation, academic functioning or social skills. Additionally, it is possible that EFs

may moderate and mediate the other identified pathways in the model. For example, EFs

may influence self-perceptions (Hughes & Ensor, 2011), social support (Beauchamp &

Anderson, 2010) and resilience against peer victimisation (Agoston & Rudolph, 2016).

Exploratory analyses identified that the indirect effect can be best explained as

DCD impacting on depressive symptoms through behavioural regulation difficulties. No

43

indirect effect was found for depression through metacognitive difficulties. Additionally,

no indirect effect was found for anxiety through either type of EF. The failure to find an

indirect effect through these other paths could be due to insufficient power in the present

study, since only a medium-large indirect effect could be detected with the sample size.

However, the results would suggest that difficulties in behavioural regulation may be

most pertinent to the mental health difficulties in DCD, especially depression. To some

extent, these findings would fit with the proposed explanation that emotion regulation

deficits underlie the link between EF difficulties and internalising symptoms. This is

because the BRI on the BRIEF measures a person’s ability to shift and modulate

behaviours and emotions via appropriate inhibitory control (Gioia et al., 2000).

Emotional control is a key aspect of the BRI, as is inhibition and cognitive flexibility

which have been implicated in emotion regulation strategies (Demeyer et al., 2012;

Johnson, 2009; Joormann & Gotlib, 2010; Meiran et al., 2011). The MCI, on the other

hand, measures a person’s cognitive ability to problem-solve, monitor performance and

self-manage tasks. There is generally less research linking these metacognitive abilities

to emotion regulation. Instead, metacognitive abilities may be important for more

practical and social skills (Gilotty, Kenworthy, Sirian, Black, & Wagner, 2002; Pugliese

et al., 2015). Consistent with this, Gardiner and Iarocci (2018) found that behavioural

regulation difficulties predicted depressive symptoms in adolescents, whereas

metacognitive difficulties were a better predictor of daily living skills, communication

skills and socialisation abilities. It is, therefore, a plausible finding that deficits in EFs

related to behavioural regulation are most important in explaining the link between DCD

and internalising symptoms, particularly depression.

44

Finally, EFs were also found to mediate the relationship between motor

difficulties and internalising symptoms in the TD adolescents. This is consistent with the

emerging literature investigating motor difficulties as a dimensional construct in

community samples, including its relationship with internalising symptoms (Piek et al.,

2010; Poole et al., 2015; Sigurdsson E et al., 2002) and EF difficulties (Rigoli, Piek,

Kane, et al., 2012). This would suggest that subclinical symptoms of DCD, and motor

difficulties in general, can impact on internalising symptoms and that this may also be

mediated by EF difficulties. This finding also provides extra support for the main results

of this study. It suggests that the findings cannot be explained solely by the potential

bias arising through the unrepresentativeness of the TD sample.

Strengths and Limitations

There are several limitations in the present study and so the results should be

interpreted with caution. Given the cross-sectional design, it is not possible to establish

causality in the relationships identified. Although prior longitudinal research suggests

that DCD predicts both EF difficulties and internalising symptoms, and that EF

difficulties predict internalising symptoms, these directional relationships could not be

confirmed in the present study. For example, there is evidence that internalising

symptoms can exacerbate EF difficulties (Vilgis, Silk, & Vance, 2015). Alternatively,

the relationship between variables might be better explained by their shared associations

with another untested variable.

Despite attempts to recruit participants across a wide range of sources, the

response rate in both the DCD and TD groups was very low. This resulted in a small

45

sample size with insufficient power to detect medium effect sizes. As such,

interpretations could only be made about the larger effects and are somewhat tentative.

The low response rate, and the use of a convenience sampling strategy, also raises the

question of how representative the sample was of the populations studied. It is possible

that only a certain subgroup of parents and adolescents volunteered to participate in the

study. In the DCD group, this may have included parents and adolescents who were

closely involved with the organisations that aided in advertising the study. Given the

supportive nature of these organisations, these volunteers may benefit from greater

protective resources than those with no links to such support. Indeed, the internalising

symptoms in the DCD group were not found to differ significantly from the normative

population, suggesting the difficulties in mental health were less apparent than might be

expected in the DCD population. On the contrary, internalising symptoms in the TD

group were significantly lower than the normative population, suggesting the sample

was unrepresentative. The use of a convenience sampling strategy likely provided less

accurate estimates of the effects compared to a population screening strategy.

Although the two groups did not differ significantly in age and gender, and the

results did not change when controlling for these confounders, other untested

confounders may have influenced the results. For example, socioeconomic status (SES)

was not measured, though it has been linked to both internalising symptoms

(Letourneau, Duffett-Leger, Levac, Watson, & Young-Morris, 2013) and EFs (Hackman

& Farah, 2009). However, the reported effects of SES are small and inconclusive (Gioia

et al., 2000; Twenge & Nolen-Hoeksema, 2002). Other factors that could potentially be

important are maternal depression (Harrowell et al., 2017), ethnicity (Twenge & Nolen-

46

Hoeksema, 2002) and IQ (Lingam et al., 2012), though the use of IQ as a covariate in

studies investigating neurodevelopmental disorders is controversial (Dennis et al., 2009).

These potential confounding factors often go unmeasured in research into DCD since

recruitment is often challenging and the primary measures take priority. Additionally,

although adolescents with comorbid disorders were excluded based on self-reported

diagnoses, it is also unclear to what extent undiagnosed difficulties or subclinical

symptoms of ADHD or ASD could have contributed to the findings.

Another limitation is that internalising symptoms were based only on self-report

and EF difficulties on parent-report. Although clinical cut-offs could be used, only

diagnostic interviews could establish the rates of psychiatric diagnoses in each group.

Additionally, behaviour rating scales of EF only correlate modestly with performance-

based measures of EF. It is, therefore, unclear if similar findings would be found using

more structured, controlled measures of EF. Related to this, the present study relied on

parent-report and a screening measure to rule out a diagnosis of DCD in the TD group.

A more rigorous, independent assessment based on performance-based measures and a

clear developmental history would be more accurate. This is especially important given

that DCD is often undiagnosed (Gaines et al., 2008), placing greater needs on

researchers to assess this independently.

However, this is the first study to investigate whether difficulties in EFs mediate

the relationship between DCD and internalising symptoms. This is an important factor

that has not been included in previous explanations for this relationship (Cairney et al.,

2013; Mancini et al., 2016). It is also the first study to investigate everyday EF

difficulties in adolescents with DCD compared to their TD peers. The use of different

47

respondents for the mediator and dependent variables minimises common method bias

which is often a major limitation among studies investigating mediation models.

Generally, the effect sizes were also of a large magnitude, suggesting that further

exploration of these relationships in future research could have important theoretical and

clinical implications.

Clinical implications

These findings echo previous research indicating that the impact of DCD extends

beyond the motor difficulties that characterise the disorder. They highlight the need for

healthcare and education professionals to become more aware of the impact the disorder

has on both internalising symptoms and on EF. This is especially important given that

the condition is poorly understood among professionals (Gaines et al., 2008; B. N.

Wilson et al., 2013) and given the difficulties families report in obtaining the right

support (Stephenson & Chesson, 2008). It suggests that individuals with DCD would

benefit from further assessment of their EF abilities and appropriate support with this in

both education and healthcare settings. Indeed, individuals diagnosed with DCD in

adulthood have highlighted their EF difficulties as being amongst their main concerns

and reasons for seeking support, as opposed to the motor difficulties itself (Purcell,

Scott-Roberts, & Kirby, 2015). The findings also support the practice of routine

screening of mental health difficulties in individuals with DCD to identify potentially

undiagnosed comorbid difficulties, especially depression. Given the numerous pathways

through which DCD might impact on internalising symptoms (Mancini et al., 2016),

these suggestions would require close collaboration among teachers, educational

48

psychologists, occupational therapists, medical practitioners, social workers and mental

health professionals to meet an individual’s needs holistically.

The findings also suggest that EF deficits may play a key role in the increased

risk of internalising symptoms in people with DCD. Given that research has found

interventions can improve EFs if targeted during childhood (Diamond & Lee, 2011), this

provides an important area of treatment for individuals with DCD and comorbid mental

health difficulties. Although the findings are only preliminary, it would suggest that this

may be most important for depressive symptoms in adolescents with DCD. It also

suggests that a focus on behavioural regulation strategies may be most effective. This

might include learning to shift attention away from negative emotional stimuli (e.g.

negative thoughts), inhibit negative behavioural and emotional responses, and develop

more effective emotion regulation strategies. The findings would also suggest that, for

mental health professionals presented with a client with DCD and comorbid depression,

it would be helpful to be aware of these behavioural regulation difficulties and perhaps

consider them as part of their intervention. For example, there is some suggestion that

third-wave cognitive-behavioural models may improve behavioural regulation, including

elements of mindfulness training (Flook et al., 2010), promoting psychological

flexibility (Whiting, Deane, Simpson, McLeod, & Ciarrochi, 2017), and developing

emotion regulation strategies (McMain, Korman, & Dimeff, 2001). On the contrary,

attempts to improve metacognitive skills such as problem-solving, planning and

organisation may be less helpful.

49

Future research

Given the limitations of the present study, further research is needed to support

the current findings. Longitudinal studies, controlling for the stability of EF difficulties

and internalising symptoms over time, are necessary to better understand the causal

pathways linking DCD, EFs, and internalising symptoms. Future research could also

explore the specific pathways through which EF difficulties lead to internalising

symptoms in DCD. This might include indirect effects through emotion regulation

strategies and through the existing pathways suggested in the environmental stress

hypothesis (e.g. peer victimisation, social support, self-esteem). More complex

analytical techniques, such as structural equation modelling, could provide further

insight into the complexity of the relationships between these variables. These future

studies should also adopt large-scale, population-based screening strategies controlling

for a range of potential confounders to maximise the quality of their findings. The

addition of performance-based measures of various EFs would also allow for more in-

depth analyses into the specific EF abilities that are important in these relationships. It

would also be important to replicate findings across the age groups, including younger

children and adults. Additionally, there is a need for intervention studies to determine

whether targeting EF deficits in DCD can improve the mental health of this population.

Conclusion

This study supports the findings of previous research indicating that adolescents

with DCD experience greater levels of internalising symptoms and EF difficulties

compared to their TD peers. It is also the first study to identify EF difficulties as a key

50

explanatory factor in the link between DCD and mental health problems. Although these

findings are considered preliminary, it suggests that EF difficulties could be an

important addition to previous attempts at conceptualising the elevated internalising

symptoms in this population (Cairney et al., 2013; Mancini et al., 2016). It also

highlights EFs as a potential intervention target for improving the emotional wellbeing

of adolescents with DCD. However, further research is needed to support these findings.

References

Agoston, A. M., & Rudolph, K. D. (2016). Interactive contributions of cumulative peer

stress and executive function deficits to depression in early adolescence. The

Journal of Early Adolescence, 36(8), 1070–1094.

Alloway, T. P. (2007). Working memory, reading, and mathematical skills in children

with developmental coordination disorder. Journal of Experimental Child

Psychology, 96(1), 20–36.

American Psychiatric Association. (2013). DSM-5: Diagnostic and Statistical Manual of

Mental Disorders. (5th ed.). Washington, DC: American Psychiatric Press.

Beauchamp, M. H., & Anderson, V. (2010). SOCIAL: An integrative framework for the

development of social skills. Psychological Bulletin, 136(1), 39–64.

Bernardi, M., Leonard, H. C., Hill, E. L., Botting, N., & Henry, L. A. (2018). Executive

functions in children with developmental coordination disorder: A 2-year follow-

up study. Developmental Medicine and Child Neurology, 60(3), 306–313.

51

Best, J. R., Miller, P. H., & Naglieri, J. A. (2011). Relations between executive function

and academic achievement from ages 5 to 17 in a large, representative national

sample. Learning and Individual Differences, 21(4), 327–336.

Biotteau, M., Chaix, Y., Blais, M., Tallet, J., Péran, P., & Albaret, J. M. (2016). Neural

signature of DCD: A critical review of MRI neuroimaging studies. Frontiers in

Neurology, 7, 227.

Blakemore, S. J., & Choudhury, S. (2006). Development of the adolescent brain:

Implications for executive function and social cognition. Journal of Child

Psychology and Psychiatry, 47(3–4), 296–312.

Bowerman, B. L., & O’Connell, R. T. (1990). Linear statistical models: An applied

approach. (2nd ed.). Belmont, CA: Duxbury.

Brosschot, J. F., Gerin, W., & Thayer, J. F. (2006). The perseverative cognition

hypothesis: A review of worry, prolonged stress-related physiological activation,

and health. Journal of Psychosomatic Research, 60(2), 113–124.

Burgess, P. W., Alderman, N., Forbes, C., Costello, A., Coates, L. M. A., Dawson, D.

R., … Channon, S. (2006). The case for the development and use of

‘ecologically valid’ measures of executive function in experimental and clinical

neuropsychology. Journal of the International Neuropsychological Society,

12(2), 194–209.

Cairney, J., Rigoli, D., & Piek, J. (2013). Developmental coordination disorder and

internalizing problems in children: The environmental stress hypothesis

elaborated. Developmental Review, 33(3), 224–238.

52

Campbell, W. N., Missiuna, C., & Vaillancourt, T. (2012). Peer victimization and

depression in children with and without motor coordination difficulties.

Psychology in the Schools, 49(4), 328–341.

Cantwell, D. P., Lewinsohn, P. M., Rohde, P., & Seeley, J. R. (1997). Correspondence

between adolescent report and parent report of psychiatric diagnostic data.

Journal of the American Academy of Child and Adolescent Psychiatry, 36(5),

610–619.

Chorpita, B. F., Moffitt, C. E., & Gray, J. (2005). Psychometric properties of the

Revised Child Anxiety and Depression Scale in a clinical sample. Behaviour

Research and Therapy, 43(3), 309–322.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.

Cook, R. D. (1977). Detection of Influential Observation in Linear Regression.

Technometrics, 19(1), 15–18.

Cousins, M., & Smyth, M. M. (2003). Developmental coordination impairments in

adulthood. Human Movement Science, 22(4–5), 433–459.

Crane, L., Sumner, E., & Hill, E. L. (2017). Emotional and behavioural problems in

children with Developmental Coordination Disorder: Exploring parent and

teacher reports. Research In Developmental Disabilities, 70, 67–74.

Dawson, E. L., Shear, P. K., & Strakowski, S. M. (2012). Behavior regulation and mood

predict social functioning among healthy young adults. Journal of Clinical and

Experimental Neuropsychology, 34(3), 297–305.

Demeyer, I., De Lissnyder, E., Koster, E. H. W., & De Raedt, R. (2012). Rumination

mediates the relationship between impaired cognitive control for emotional

53

information and depressive symptoms: A prospective study in remitted depressed

adults. Behaviour Research and Therapy, 50(5), 292–297.

Dennis, M., Francis, D. J., Cirino, P. T., Schachar, R., Barnes, M. A., & Fletcher, J. M.

(2009). Why IQ is not a covariate in cognitive studies of neurodevelopmental

disorders. Journal of the International Neuropsychological Society, 15(3), 331–

343.

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

development and of the cerebellum and prefrontal cortex. Child Development,

71(1), 44–56.

Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64, 135–168.

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

development in children 4 to 12 years old. Science, 333(6045), 959–964.

Durbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares

regression. I. Biometrika, 37(3–4), 409–428.

Durbin, J., & Watson, G. S. (1951). Testing for serial correlation in least squares

regression. II. Biometrika, 38(1–2), 159–178.

Eaton, N. R., Krueger, R. F., Markon, K. E., Keyes, K. M., Skodol, A. E., Wall, M., …

Grant, B. F. (2013). The structure and predictive validity of the internalizing

disorders. Journal of Abnormal Psychology, 122(1), 86–92.

Ebesutani, C., Reise, S. P., Chorpita, B. F., Ale, C., Regan, J., Young, J., … Weisz, J. R.

(2012). The Revised Child Anxiety and Depression Scale-Short Version: Scale

reduction via exploratory bifactor modeling of the broad anxiety factor.

Psychological Assessment, 24(4), 833–845.

54

Ende, J. V. der, Verhulst, F. C., & Tiemeier, H. (2016). The bidirectional pathways

between internalizing and externalizing problems and academic performance

from 6 to 18 years. Development and Psychopathology, 28(3), 855–867.

Ernst, M., Pine, D. S., & Hardin, M. (2006). Triadic model of the neurobiology of

motivated behavior in adolescence. Psychological Medicine, 36(3), 299–312.

Evans, L. D., Kouros, C. D., Samanez-Larkin, S., & Garber, J. (2016). Concurrent and

short-term prospective relations among neurocognitive functioning, coping, and

depressive symptoms in youth. Journal of Clinical Child & Adolescent

Psychology, 45(1), 6–20.

Faul, F., Erdfelder, E., Lang, A., & Buchner, A. (2007). G*Power 3: A flexible

statistical power analysis program for the social, behavioral, and biomedical

sciences. Behavior Research Methods, 39(2), 175–191.

Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). London,

England: Sage.

Flook, L., Smalley, S. L., Kitil, M. J., Galla, B. M., Kaiser-Greenland, S., Locke, J., …

Kasari, C. (2010). Effects of Mindful Awareness Practices on executive

functions in elementary school children. Journal of Applied School Psychology,

26(1), 70–95.

Francis, M., & Piek, J. (2003). The effects of perceived social support and self-worth on

depressive symptomatology in children with and without Developmental

Coordination Disorder (DCD). Australian Journal of Psychology, 55(S), 180.

Fritz, M. S., & MacKinnon, D. P. (2007). Required sample size to detect the mediated

effect. Psychological Science, 18(3), 233–239.

55

Gaines, R., Missiuna, C., Egan, M., & McLean, J. (2008). Educational outreach and

collaborative care enhances physician’s perceived knowledge about

Developmental Coordination Disorder. BMC Health Services Research, 8, 21–

21.

Garber, J., Braafladt, N., & Weiss, B. (1995). Affect regulation in depressed and

nondepressed children and young adolescents. Development and

Psychopathology, 7(1), 93–115.

Gardiner, E., & Iarocci, G. (2018). Everyday executive function predicts adaptive and

internalizing behavior among children with and without autism spectrum

disorder. Autism Research: Official Journal of the International Society for

Autism Research, 11(2), 284–295.

Ghassabian, A., Székely, E., Herba, C. M., Jaddoe, V. W., Hofman, A., Oldehinkel, A.

J., … Tiemeier, H. (2014). From positive emotionality to internalizing problems:

The role of executive functioning in preschoolers. European Child & Adolescent

Psychiatry, 23(9), 729–741.

Gilotty, L., Kenworthy, L., Sirian, L., Black, D. O., & Wagner, A. E. (2002). Adaptive

skills and executive function in autism spectrum disorders. Child

Neuropsychology: A Journal on Normal and Abnormal Development in

Childhood and Adolescence, 8(4), 241–248.

Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2000). TEST REVIEW

Behavior Rating Inventory of Executive Function. Child Neuropsychology, 6(3),

235–238.

56

Hackman, D. A., & Farah, M. J. (2009). Socioeconomic status and the developing brain.

Trends in Cognitive Sciences, 13(2), 65–73.

Han, G., Helm, J., Iucha, C., Zahn-Waxler, C., Hastings, P. D., & Klimes-Dougan, B.

(2016). Are executive functioning deficits concurrently and predictively

associated with depressive and anxiety symptoms in adolescents? Journal of

Clinical Child & Adolescent Psychology, 45(1), 44–58.

Harrowell, I., Hollén, L., Lingam, R., & Emond, A. (2017). Mental health outcomes of

developmental coordination disorder in late adolescence. Developmental

Medicine And Child Neurology, 59(9), 973–979.

Hawker, D. S., & Boulton, M. J. (2000). Twenty years’ research on peer victimization

and psychosocial maladjustment: A meta-analytic review of cross-sectional

studies. Journal of Child Psychology and Psychiatry, 41(4), 441–455.

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process

analysis: A regression-based approach. New York, NY: Guilford Press.

Hill, E. L., & Brown, D. (2013). Mood impairments in adults previously diagnosed with

developmental coordination disorder. Journal of Mental Health, 22(4), 334–340.

Hill, E. L., Brown, D., & Sorgardt, K. S. (2011). A preliminary investigation of quality

of life satisfaction reports in emerging adults with and without Developmental

Coordination Disorder. Journal of Adult Development, 18(3), 130–134.

Hope, T. L., Adams, C., Reynolds, L., Powers, D., Perez, R. A., & Kelley, M. L. (1999).

Parent vs. self-report: Contributions toward diagnosis of adolescent

psychopathology. Journal of Psychopathology and Behavioral Assessment,

21(4), 349–363.

57

Hughes, C., & Ensor, R. (2011). Individual differences in growth in executive function

across the transition to school predict externalizing and internalizing behaviors

and self-perceived academic success at 6 years of age. Journal of Experimental

Child Psychology, 108(3), 663–676.

Johnson, D. R. (2009). Emotional attention set-shifting and its relationship to anxiety

and emotion regulation. Emotion, 9(5), 681–690.

Joormann, J., & D’Avanzato, C. (2010). Emotion regulation in depression: Examining

the role of cognitive processes. Cognition and Emotion, 24(6), 913–939.

Joormann, J., & Gotlib, I. H. (2010). Emotion regulation in depression: Relation to

cognitive inhibition. Cognition and Emotion, 24(2), 281–298.

Kelly, N. C., Ammerman, R. T., Rausch, J. R., Ris, M. D., Yeates, K. O., Oppenheimer,

S. G., & Enrile, B. G. (2012). Executive functioning and psychological

adjustment in children and youth with spina bifida. Child Neuropsychology,

18(5), 417–431.

Koenigs, M., & Grafman, J. (2009). The functional neuroanatomy of depression:

Distinct roles for ventromedial and dorsolateral prefrontal cortex. Behavioural

Brain Research, 201(2), 239–243.

Koole, S. L. (2009). The psychology of emotion regulation: An integrative review.

Cognition and Emotion, 23(1), 4–41.

Kovacs, M., & Devlin, B. (1998). Internalizing disorders in childhood. The Journal of

Child Psychology and Psychiatry, 39(1), 47–63.

58

Koziol, L. F., Budding, D. E., & Chidekel, D. (2012). From movement to thought:

Executive function, embodied cognition, and the cerebellum. Cerebellum, 11(2),

505–525.

Lachowicz, M. J., Preacher, K. J., & Kelley, K. (2018). A novel measure of effect size

for mediation analysis. Psychological Methods, 23(2), 244–261.

Lawson, Rachel A., Papadakis, A. A., Higginson, C. I., Barnett, J. E., Wills, M. C.,

Strang, J. F., … Kenworthy, L. (2015). Everyday executive function impairments

predict comorbid psychopathology in autism spectrum and attention deficit

hyperactivity disorders. Neuropsychology, 29(3), 445–453.

Lengua, L. J. (2006). Growth in temperament and parenting as predictors of adjustment

during children’s transition to adolescence. Developmental Psychology, 42(5),

819–832.

Leonard, H. C., & Hill, E. L. (2015). Executive difficulties in developmental

coordination disorder: Methodological issues and future directions. Current

Developmental Disorders Reports, 2(2), 141–149.

Letkiewicz, A. M., Miller, G. A., Crocker, L. D., Warren, S. L., Infantolino, Z. P.,

Mimnaugh, K. J., & Heller, W. (2014). Executive function deficits in daily life

prospectively predict increases in depressive symptoms. Cognitive Therapy and

Research, 38(6), 612–620.

Letourneau, N. L., Duffett-Leger, L., Levac, L., Watson, B., & Young-Morris, C.

(2013). Socioeconomic status and child development: A meta-analysis. Journal

of Emotional and Behavioral Disorders, 21(3), 211–224.

59

Li, Y. C., Kwan, M. Y. W., Clark, H. J., Hay, J., Faught, B. E., & Cairney, J. (2018). A

test of the Environmental Stress Hypothesis in children with and without

Developmental Coordination Disorder. Psychology of Sport and Exercise, 37,

244–250.

Lingam, R., Jongmans, M. J., Ellis, M., Hunt, L. P., Golding, J., & Emond, A. (2012).

Mental health difficulties in children with developmental coordination disorder.

Pediatrics, 129(4), e882–e891.

Mancini, V. O., Rigoli, D., Cairney, J., Roberts, L. D., & Piek, J. P. (2016). The

Elaborated Environmental Stress Hypothesis as a framework for understanding

the association between motor skills and internalizing problems: A mini-review.

Frontiers In Psychology, 7, 239–239.

Mandich, A., Buckolz, E., & Polatajko, H. (2002). On the ability of children with

developmental coordination disorder (DCD) to inhibit response initiation: The

Simon effect. Brain and Cognition, 50(1), 150–162.

Martel, M. M., Nigg, J. T., Wong, M. M., Fitzgerald, H. E., Jester, J. M., Puttler, L. I.,

… Zucker, R. A. (2007). Childhood and adolescent resiliency, regulation, and

executive functioning in relation to adolescent problems and competence in a

high-risk sample. Development and Psychopathology, 19(2), 541–563.

McMain, S., Korman, L. M., & Dimeff, L. (2001). Dialectical behavior therapy and the

treatment of emotion dysregulation. Journal of Clinical Psychology, 57(2), 183–

196.

Meiran, N., Diamond, G. M., Toder, D., & Nemets, B. (2011). Cognitive rigidity in

unipolar depression and obsessive compulsive disorder: Examination of task

60

switching, Stroop, working memory updating and post-conflict adaptation.

Psychiatry Research, 185(1–2), 149–156.

Menard, S. (1995). Applied logistic regression analysis. Thousand Oaks, CA: Sage.

Mezulis, A. H., Priess, H. A., & Hyde, J. S. (2011). Rumination mediates the

relationship between infant temperament and adolescent depressive symptoms.

Depression Research and Treatment, 2011, 487873.

Michel, E., Roethlisberger, M., Neuenschwander, R., & Roebers, C. M. (2011).

Development of cognitive skills in children with motor coordination impairments

at 12-month follow-up. Child Neuropsychology: A Journal on Normal and

Abnormal Development in Childhood and Adolescence, 17(2), 151–172.

Missiuna, C., Cairney, J., Pollock, N., Campbell, W., Russell, D. J., Macdonald, K., …

Cousins, M. (2014). Psychological distress in children with developmental

coordination disorder and attention-deficit hyperactivity disorder. Research In

Developmental Disabilities, 35(5), 1198–1207.

Missiuna, C., & Campbell, W. N. (2014). Psychological aspects of Developmental

Coordination Disorder: Can we establish causality? Current Developmental

Disorders Reports, 1(2), 125–131.

Missiuna, C., Moll, S., King, S., King, G., & Law, M. (2007). A trajectory of troubles:

Parents’ impressions of the impact of developmental coordination disorder.

Physical & Occupational Therapy in Pediatrics, 27(1), 81–101.

Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T.

D. (2000). The unity and diversity of executive functions and their contributions

61

to complex ‘Frontal Lobe’ tasks: A latent variable analysis. Cognitive

Psychology, 41(1), 49–100.

Myers, R. (1990). Classical and modern regression with applications (2nd ed.). Boston,

MA: Duxbury.

Nigg, J. T., Quamma, J. P., Greenberg, M. T., & Kusche, C. A. (1999). A two-year

longitudinal study of neuropsychological and cognitive performance in relation

to behavioral problems and competencies in elementary school children. Journal

of Abnormal Child Psychology, 27(1), 51–63.

Nilsen, W., Karevold, E., Røysamb, E., Gustavson, K., & Mathiesen, K. S. (2013).

Social skills and depressive symptoms across adolescence: Social support as a

mediator in girls versus boys. Journal of Adolescence, 36(1), 11–20.

Norman, G., Sloan, J., & Wyrwich, K. (2003). Interpretation of changes in health-related

quality of life: The remarkable universality of half a standard deviation. Medical

Care, 41(5), 582–592.

Owens, M., Stevenson, J., Hadwin, J. A., & Norgate, R. (2012). Anxiety and depression

in academic performance: An exploration of the mediating factors of worry and

working. School Psychology International, 33(4), 433–449.

Piek, J. P., Barrett, N. C., Smith, L. M., Rigoli, D., & Gasson, N. (2010). Do motor skills

in infancy and early childhood predict anxious and depressive symptomatology

at school age? Human Movement Science, 29(5), 777–786.

Piek, J. P., Dyck, M. J., Nieman, A., Anderson, M., Hay, D., Smith, L. M., …

Hallmayer, J. (2004). The relationship between motor coordination, executive

62

functioning and attention in school aged children. Archives of Clinical

Neuropsychology, 19(8), 1063–1076.

Piek, J. P., Kane, R., Rigoli, D., McLaren, S., Roberts, C. M., Rooney, R., … Straker, L.

(2015). Does the Animal Fun program improve social-emotional and behavioural

outcomes in children aged 4-6 years? Human Movement Science, 43, 155–163.

Piek, J. P., Rigoli, D., Pearsall-Jones, J. G., Martin, N. C., Hay, D. A., Bennett, K. S., &

Levy, F. (2007). Depressive symptomatology in child and adolescent twins with

attention-deficit hyperactivity disorder and/or developmental coordination

disorder. Twin Research And Human Genetics, 10(4), 587–596.

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common

method biases in behavioral research: A critical review of the literature and

recommended remedies. The Journal of Applied Psychology, 88(5), 879–903.

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias

in social science research and recommendations on how to control it. Annual

Review of Psychology, 63, 539–569.

Poole, K. L., Schmidt, L. A., Missiuna, C., Saigal, S., Boyle, M. H., & Van Lieshout, R.

J. (2015). Motor coordination and mental health in extremely low birth weight

survivors during the first four decades of life. Research in Developmental

Disabilities, 43–44, 87–96.

Pratt, M. L., & Hill, E. L. (2011). Anxiety profiles in children with and without

developmental coordination disorder. Research in Developmental Disabilities,

32(4), 1253–1259.

63

Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect

effects in simple mediation models. Behavior Research Methods, Instruments, &

Computers, 36(4), 717–731.

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for

assessing and comparing indirect effects in multiple mediator models. Behavior

Research Methods, 40(3), 879–891.

Price, J. L., & Drevets, W. C. (2010). Neurocircuitry of mood disorders.

Neuropsychopharmacology, 35(1), 192–216.

Pugliese, C. E., Anthony, L., Strang, J. F., Dudley, K., Wallace, G. L., & Kenworthy, L.

(2015). Increasing adaptive behavior skill deficits from childhood to adolescence

in autism spectrum disorder: Role of executive function. Journal of Autism and

Developmental Disorders, 45(6), 1579–1587.

Purcell, C., Scott-Roberts, S., & Kirby, A. (2015). Implications of DSM-5 for

recognising adults with developmental coordination disorder (DCD). The British

Journal of Occupational Therapy, 78(5), 295–302.

Raz-Silbiger, S., Lifshitz, N., Katz, N., Steinhart, S., Cermak, S. A., & Weintraub, N.

(2015). Relationship between motor skills, participation in leisure activities and

quality of life of children with Developmental Coordination Disorder: Temporal

aspects. Research in Developmental Disabilities, 38, 171–180.

Riggs, N. R., Blair, C. B., & Greenberg, M. T. (2003). Concurrent and 2-year

longitudinal relations between executive function and the behavior of 1st and 2nd

grade children. Child Neuropsychology: A Journal on Normal and Abnormal

Development in Childhood and Adolescence, 9(4), 267–276.

64

Riggs, N. R., Greenberg, M. T., Kusché, C. A., & Pentz, M. A. (2006). The mediational

role of neurocognition in the behavioral outcomes of a social-emotional

prevention program in elementary school students: Effects of the PATHS

curriculum. Prevention Science, 7(1), 91–102.

Rigoli, D., Kane, R. T., Mancini, V., Thornton, A., Licari, M., Hands, B., … Piek, J.

(2017). The relationship between motor proficiency and mental health outcomes

in young adults: A test of the Environmental Stress Hypothesis. Human

Movement Science, 53, 16–23.

Rigoli, D., Piek, J. P., & Kane, R. (2012). Motor coordination and psychosocial

correlates in a normative adolescent sample. Pediatrics, 129(4), e892–e900.

Rigoli, D., Piek, J. P., Kane, R., & Oosterlaan, J. (2012). An examination of the

relationship between motor coordination and executive functions in adolescents.

Developmental Medicine & Child Neurology, 54(11), 1025–1031.

Schmeichel, B. J., & Tang, D. (2015). Individual differences in executive functioning

and their relationship to emotional processes and responses. Current Directions

in Psychological Science, 24(2), 93–98.

Schoemaker, M. M., & Kalverboer, A. F. (1994). Social and affective problems of

children who are clumsy: How early do they begin? Adapted Physical Activity

Quarterly, 11, 140.

Sigurdsson E, van Os J, Fombonne E, Sigurdsson, E., Van Os, J., & Fombonne, E.

(2002). Are impaired childhood motor skills a risk factor for adolescent anxiety?

Results from the 1958 U.K. birth cohort and the National Child Development

Study. American Journal of Psychiatry, 159(6), 1044–1046.

65

Silk, J. S., Steinberg, L., & Morris, A. S. (2003). Adolescents’ emotion regulation in

daily life: Links to depressive symptoms and problem behavior. Child

Development, 74(6), 1869–1880.

Skinner, R. A., & Piek, J. P. (2001). Psychosocial implications of poor motor

coordination in children and adolescents. Human Movement Science, 20(1–2),

73–94.

Smith, S. R. (2007). Making sense of multiple informants in child and adolescent

psychopathology: A guide for clinicians. Journal of Psychoeducational

Assessment, 25(2), 139–149.

Snyder, H. R. (2013). Major depressive disorder is associated with broad impairments

on neuropsychological measures of executive function: A meta-analysis and

review. Psychological Bulletin, 139(1), 81–132.

Snyder, H. R., Kaiser, R. H., Warren, S. L., & Heller, W. (2014). Obsessive-compulsive

disorder is associated with broad impairments in executive function: A meta-

analysis. Clinical Psychological Science, 3(2), 301-330.

Sourander, A., Helstelä, L., & Helenius, H. (1999). Parent-adolescent agreement on

emotional and behavioral problems. Social Psychiatry and Psychiatric

Epidemiology, 34(12), 657–663.

Sowislo, J. F., & Orth, U. (2013). Does low self-esteem predict depression and anxiety?

A meta-analysis of longitudinal studies. Psychological Bulletin, 139(1), 213–

240.

Stephenson, E. A., & Chesson, R. A. (2008). ‘Always the guiding hand’: parents’

accounts of the long-term implications of developmental co-ordination disorder

66

for their children and families. Child: Care, Health and Development, 34(3),

335–343.

Stevens, J. P. (2002). Applied multivariate statistics for the social sciences (4th ed.).

Hillsdale, NJ: Erlbaum.

Streiner, D. L., & Norman, G. R. (2011). Correction for multiple testing: Is there a

resolution? Chest, 140(1), 16–18.

Tal Saban, M., Ornoy, A., & Parush, S. (2014). Executive function and attention in

young adults with and without Developmental Coordination Disorder – A

comparative study. Research in Developmental Disabilities, 35(11), 2644–2650.

Tal-Saban, M., Ornoy, A., & Parush, S. (2014). Young adults with Developmental

Coordination Disorder: A longitudinal study. American Journal of Occupational

Therapy, 68(3), 307.

Toplak, M. E., West, R. F., & Stanovich, K. E. (2013). Practitioner Review: Do

performance-based measures and ratings of executive function assess the same

construct? Journal of Child Psychology and Psychiatry, 54(2), 131–143.

Twenge, J. M., & Nolen-Hoeksema, S. (2002). Age, gender, race, socioeconomic status,

and birth cohort differences on the children’s depression inventory: A meta-

analysis. Journal of Abnormal Psychology, 111(4), 578–588.

Vilgis, V., Silk, T. J., & Vance, A. (2015). Executive function and attention in children

and adolescents with depressive disorders: A systematic review. European Child

& Adolescent Psychiatry, 24(4), 365–384.

67

Wagner, M., Jekauc, D., Worth, A., & Woll, A. (2016). Elaboration of the

environmental stress hypothesis-Results from a population-based 6-year follow-

up. Frontiers In Psychology, 7, 1904.

Wagner, M. O., Bos, K., Jascenoka, J., Jekauc, D., & Petermann, F. (2012). Peer

problems mediate the relationship between Developmental Coordination

Disorder and behavioral problems in school-aged children. Research In

Developmental Disabilities, 33(6), 2072–2079.

Wagner, S., Müller, C., Helmreich, I., Huss, M., & Tadić, A. (2015). A meta-analysis of

cognitive functions in children and adolescents with major depressive disorder.

European Child & Adolescent Psychiatry, 24(1), 5–19.

Wante, L., Mezulis, A., Beveren, M.-L. V., & Braet, C. (2017). The mediating effect of

adaptive and maladaptive emotion regulation strategies on executive functioning

impairment and depressive symptoms among adolescents. Child

Neuropsychology, 23(8), 935–953.

Watson, L., & Knott, F. (2006). Self-Esteem and coping in children with Developmental

Coordination Disorder. British Journal of Occupational Therapy, 69(10), 450–

456.

White, B. A., Jarrett, M. A., & Ollendick, T. H. (2012). Self-regulation deficits explain

the link between reactive aggression and internalizing and externalizing behavior

problems in children. Journal of Psychopathology and Behavioral Assessment,

35(1), 1–9.

Whiting, D. L., Deane, F. P., Simpson, G. K., McLeod, H. J., & Ciarrochi, J. (2017).

Cognitive and psychological flexibility after a traumatic brain injury and the

68

implications for treatment in acceptance-based therapies: A conceptual review.

Neuropsychological Rehabilitation, 27(2), 263–299.

Wilson, B. N., Neil, K., Kamps, P. H., & Babcock, S. (2013). Awareness and knowledge

of developmental co‐ordination disorder among physicians, teachers and parents.

Child: Care, Health and Development, 39(2), 296–300.

Wilson, Brenda N., Crawford, S. G., Green, D., Roberts, G., Aylott, A., & Kaplan, B. J.

(2009). Psychometric properties of the revised Developmental Coordination

Disorder Questionnaire. Physical & Occupational Therapy in Pediatrics, 29(2),

182–202.

Wilson, P. H., Ruddock, S., Smits-Engelsman, B., Polatajko, H., & Blank, R. (2013).

Understanding performance deficits in developmental coordination disorder: A

meta-analysis of recent research. Developmental Medicine and Child Neurology,

55(3), 217–228.

Wuang, Y. P., Su, C.-Y., & Su, J. H. (2011). Wisconsin Card Sorting Test performance

in children with developmental coordination disorder. Research In

Developmental Disabilities, 32(5), 1669–1676.

Zhang, W., Zhang, L., Chen, L., Ji, L., & Deater-Deckard, K. (2018). Developmental

changes in longitudinal associations between academic achievement and

psychopathological symptoms from late childhood to middle adolescence.

Journal of Child Psychology and Psychiatry

Zhao, X., Lynch, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and

truths about mediation analysis. Journal of Consumer Research, 37(2), 197–206.

69

Zwicker, J. G., Harris, S. R., & Klassen, A. F. (2013). Quality of life domains affected in

children with developmental coordination disorder: A systematic review. Child:

Care, Health and Development, 39(4), 562–580.

70

List of appendices

Appendix A: Guidelines for authors 71

Appendix B: Developmental Coordination Disorder Questionnaire – 07 (DCDQ-

07)

72

Appendix C: Revised Child Anxiety and Depression Scale – Short version

(RCADS-25)

73

Appendix D: Behaviour Rating Inventory of Executive Function (BRIEF) 74

Appendix E: Study advertisement 75

Appendix F: Information sheets 77

Appendix G: Parent consent forms 90

Appendix H: Adolescent assent forms 93

Appendix I: Eligibility screening questionnaire 95

Appendix J: Favourable ethical opinion 96

Appendix K: Assumptions for independent samples t-tests 97

Appendix L: Assumptions for simple mediation analysis 102

Appendix M: Assumptions for subscale analyses using independent samples t-

tests

107

Appendix N: Assumptions for parallel multiple mediation analysis based on

subscales

114

Appendix O: Assumptions for simple mediation analysis within the TD sample 117

71

Appendix A: Guidelines for authors

[Appendix removed for E-Thesis submission]

72

Appendix B: Developmental Coordination Disorder Questionnaire – 07 (DCDQ-07)

[Appendix removed for E-Thesis submission]

73

Appendix C: Revised Child Anxiety and Depression Scale – Short version

(RCADS-25)

[Appendix removed for E-Thesis submission]

74

Appendix D: Behaviour Rating Inventory of Executive Function (BRIEF)

[Appendix removed for E-Thesis submission]

75

Appendix E: Study advertisements

A copy of the advertisement distributed for participants with DCD is displayed below:

University of Surrey research

We are researchers at the University of Surrey looking to understand the mental health and thinking abilities in adolescents with and without Developmental Coordination

Disorder (also known as Dyspraxia).

In this study, we will ask parents to complete some questionnaires about their child’s motor ability and thinking abilities (e.g. planning and memory). Your child will also be asked to complete a questionnaire about their mental health.

Your child can take part if he/she is aged between 12 and 15 and has a diagnosis of Developmental Coordination Disorder / Dyspraxia. All your responses will be anonymous and you will be given the chance to enter a raffle to win a £100 Amazon voucher!

If interested, please email Serif at s.omer@surrey.ac.uk for more information.

This study has received a favourable ethical opinion from the Faculty of Health and Medical

Sciences Ethics Committee, at the University of Surrey

76

A copy of the advertisement distributed for TD participants is displayed below:

University of Surrey research

Hi! My name is Serif Omer. We are conducting a research project to find out more about the link between motor coordination, thinking skills, and mental health. As part of this project, we are looking for young people (age 12-15) and their parents/guardians to complete some brief online questionnaires. They take about 15 minutes for parents/guardians and 5 minutes for the young person. All your responses will be anonymous and you will be given the chance to enter a raffle to win a £100 Amazon voucher! Please visit the following web link to access the survey: https://surreyfahs.eu.qualtrics.com/jfe/form/SV_a2wl5KRUw0vNXX7 Paper copies can also be provided. Please feel free to contact me if you have any questions: s.omer@surrey.ac.uk. Thank you very much!

77

Appendix F: Information sheets

Separate information sheets were produced for parents and adolescents in each study

group. Copies of these information sheets are provided on the following pages.

78

Parent Information Sheet (DCD group; 07.11.2017; Version 2) Title of Project

Executive function and internalizing problems in adolescents with and without Developmental Coordination Disorder Introduction

We would like to invite you and your child to take part in a research project. Before you and your child decide to take part, you need to understand why the research is being done and what it will involve. Please take the time to read the following information carefully. Talk to others about the study if you wish. This study is being conducted by Serif Omer (Trainee Clinical Psychologist), under the supervision of Dr Hayley Leonard (Lecturer in Developmental Psychology and Neurodevelopmental Disorders). Please ask questions if there is anything you do not understand. What is the purpose of the study? We know that adolescents with Developmental Coordination Disorder (DCD; sometimes also called ‘Dyspraxia’) often have difficulties with high-level thinking abilities, such as planning and memory. They also often report increased symptoms of anxiety and depression compared to others their age without the disorder. The current project aims to investigate this further by understanding how these difficulties may be related to each other. Why have I been invited to take part in the study? As part of this study, we are seeking adolescents (between the age of 12 and 16) with a diagnosis of DCD / dyspraxia and one of their parents/guardians. You and your child have been invited to take part because you might meet these criteria. Do I have to take part? No, neither you nor your child has to participate. There will be no adverse consequences if you decide not to participate. You can also withdraw your participation at any time without giving a reason.

79

What will my involvement require?

As the child’s parent or guardian, you will be asked to complete a consent form. You will then be asked a set of questions. These can be completed online, by post, over the phone, or face-to-face if we visit you at home. This should take no more than 30 minutes in total and will include questions about your child’s movement abilities (such as sports skills, handwriting, etc.) and their high-level thinking skills (such as planning and memory). You will also be asked to provide a copy of the clinical report confirming your child’s diagnosis of DCD. This will be checked by the research team to ensure your child is eligible and any relevant scores on diagnostic tests will be recorded. You will not receive any payment for taking part. You will be given the option at the end of the survey to enter a prize draw for a £100 Amazon voucher. The winner will be contacted by email at the end of study in April 2018. What will my child’s involvement require?

If you consent for your child to take part and they are suitable for the study, then they will be asked to independently complete a questionnaire concerning their moods and emotions. It should take approximately 10 minutes and can be completed online, over the phone, or on paper. Your child will not receive any payment for taking part. What will I have to do?

If you and your child would like to take part, please contact the research team on s.omer@surrey.ac.uk (Serif Omer) or using the contact details below. A researcher will then be in contact to obtain consent and administer the questionnaires. Please feel free to contact the research team if you have any questions. What are the possible disadvantages or risks of taking part?

There is a possibility that some of the questions may highlight sensitive issues for you or your child. If you want to talk about the questions or your answers, please contact the research team. If your child appears to experience any distress, the session will be terminated immediately and the research team will alert you. What are the possible benefits of taking part? It is unlikely that you or your child will benefit directly from taking part. However, it is hoped that the study will improve our understanding of mental health and

80

thinking abilities in people with motor coordination difficulties, which could have clinical implications for improving the lives of this group of people. What happens when the research study stops?

You may receive a summary of the research findings at the end of the study (after February 2018). You can indicate if and how you would like to receive this on the initial screening questionnaire. This summary will only include the overall findings of the study. We will not provide individual feedback on your child’s or your own responses. What if there is a problem? Any complaint or concern about any aspect of the way you have been dealt with during the course of the study will be addressed; please contact Dr Hayley Leonard (Research Supervisor) on 01483 686888 or h.leonard@surrey.ac.uk. You may also contact the Head of School, Professor Derek Moore, on 01483 686933 or d.g.moore@surrey.ac.uk. Will taking part in the study be kept confidential? Yes. All of the information that you and your child give will be anonymised so that those reading reports from the research will not know who has contributed to it. All project data will be held for at least 6 years and all research data for at least 10 years in accordance with University policy. Data will be stored securely in accordance with the Data Protection Act 1998. However, should you or your child disclose information that suggests your child is at risk then the researcher may need to report this to an appropriate authority. This would usually be discussed with you first. Contact details

Serif Omer Dr Hayley Leonard Trainee Clinical Psychologist Lecturer School of Psychology School of Psychology AD Building AD Building University of Surrey University of Surrey Guildford Guildford GU2 7XH GU2 7XH s.omer@surrey.ac.uk h.leonard@surrey.ac.uk 01483 686888 Who is organising and funding the research?

81

This research is unfunded and is being completed by Serif Omer as part of a Doctorate in Clinical Psychology at the University of Surrey. Who has reviewed the project?

The study has been reviewed and received a Favourable Ethical Opinion (FEO) from the Faculty of Health and Medical Sciences Ethics Committee, at the University of Surrey. Thank you for taking the time to read this Information Sheet.

82

Adolescent Information Sheet (DCD group; 17.11.17; Version 2)

Title of Project

Executive function and internalizing problems in adolescents with and without

Developmental Coordination Disorder

Introduction

Hi, my name is Serif Omer and I would like to invite you to take part in a research study.

At the University of Surrey, we are trying to learn more about the effect of

Developmental Coordination Disorder on young people. People with Developmental

Coordination Disorder (DCD), which is sometimes called ‘Dyspraxia’, have difficulties

with movement tasks (such as handwriting and sports). However, they may also have

difficulties with their mood and some thinking skills (such as memory and planning

ahead). We would like to know more about whether young people with DCD have

differences in their mood and thinking skills compared to young people without DCD and

why this might be.

Why is this study being done?

We hope that this research will help to better understand the effect of DCD/dyspraxia

on young people which could help to improve their lives. This research could also help to

better understand difficulties with mood and thinking skills in young people that do not

have DCD.

Why have I been invited to take part? As part of this study, we are looking for young people with a diagnosis of DCD/dyspraxia

between the age of 12 and 16. You have been invited to take part because you might be

suitable. Your parent/guardian has also agreed for you to take part.

Do I have to take part?

Remember, being in this study is up to you. Even if your parents give their permission

for you to participate in this study, you still can decide for yourself if you want to take

part. You don’t have to be in this study if you don’t want to! Even if you agree to take

part in the study, you can still stop at any time without giving a reason. If you decide

not to take part, this will not affect you negatively in any way.

What will happen if I take part?

If you agree to be in this study, we will ask you to sign a consent form. We will then ask

you to complete a questionnaire which asks you about your mood and emotions. It should

take approximately 10 minutes and can be completed online, over the phone, or on paper.

83

Unfortunately, you will not receive any money or reward for taking part. Your

parent/guardian will be given the option at the end of the survey to enter a prize draw

for a £100 Amazon voucher. The winner will be contacted by email at the end of study

in April 2018.

Will information about me be available to anyone?

The information that we collect from you is confidential and anonymous. Only members

of our team will be able to see this information. Your school and your parents/guardians

will not have access to the information we collect. In our findings we will discuss the

results of many young people - we do not single out or name any one participant.

The only other time that we will tell somebody else about something you have said is if

we think you or someone else may be at risk of harm.

This research study has been reviewed and given a Favourable Ethical Opinion by Faculty

of Health and Medical Sciences Ethics Committee, at the University of Surrey. This

means that the study has been checked and it is ethical for it to be conducted.

What if I have a question or there is a problem?

You can ask any questions that you have about the study at any time. If you have a

question you can contact me or other people in my team using the contact details below.

Serif Omer Dr Hayley Leonard

Trainee Clinical Psychologist Lecturer

School of Psychology School of Psychology

AD Building AD Building

University of Surrey University of Surrey

Guildford Guildford

GU2 7XH GU2 7XH

s.omer@surrey.ac.uk h.leonard@surrey.ac.uk

01483 686888

Thank you for taking the time to read this Information Sheet.

84

Parent Information Sheet (TD group; 07.11.17; Version 2) Title of Project Executive function and internalizing problems in adolescents with and without Developmental Coordination Disorder Introduction We would like to invite you and your child to take part in a research project. Before you and your child decide to take part, you need to understand why the research is being done and what it will involve. Please take the time to read the following information carefully. Talk to others about the study if you wish. This study is being conducted by Serif Omer (Trainee Clinical Psychologist), under the supervision of Dr Hayley Leonard (Lecturer in Developmental Psychology and Neurodevelopmental Disorders). Please ask questions if there is anything you do not understand. What is the purpose of the study? We know that adolescents with Developmental Coordination Disorder (DCD; sometimes also called ‘Dyspraxia’) often have difficulties with high-level thinking abilities, such as planning and memory. They also often report increased symptoms of anxiety and depression compared to others their age without the disorder. The current project aims to investigate this further by understanding how these difficulties may be related to each other. To understand this, we need to also recruit adolescents without dyspraxia, which is why we are inviting your child to participate in the study. Why have I been invited to take part in the study?

As part of this study, we are seeking to recruit adolescents without a diagnosis of DCD / dyspraxia between the age of 12 and 16 and one of their parents/guardians. You and your child have been invited to take part because you might meet these criteria. Do I have to take part? No, neither you nor your child has to participate. There will be no adverse consequences if you decide not to participate. You can also withdraw your participation at any time without giving a reason.

85

What will my involvement require?

As the child’s parent or guardian, you will be asked to complete a consent form and some initial information about your child (e.g. date of birth). You will then be asked a set of questions which can be completed on paper or, if preferred, online or over the phone. This should take no more than 30 minutes in total and will include questions about your child’s movement abilities (such as sports skills, handwriting, etc.) and their high-level thinking skills (such as planning and memory). You will not receive any payment for taking part. You will be given the option at the end of the survey to enter a prize draw for a £100 Amazon voucher. The winner will be contacted by email at the end of study in April 2018. What will my child’s involvement require?

If you consent for your child to take part and they are suitable for the study, they will be asked to complete a questionnaire concerning their moods and emotions. In total this should take no more than 10 minutes. They can complete this questionnaire online, over the phone, or on paper. Your child will not receive any payment for taking part. What will I have to do?

If you and your child would like to take part, please complete the enclosed consent form and questionnaires. Please feel free to contact the research team if you have any questions. What are the possible disadvantages or risks of taking part? There is a possibility that some of the questions may highlight sensitive issues for you or your child. If you want to talk about the questions or your answers, please contact the research team. If your child appears to experience any distress, the session will be terminated immediately and the research team will alert you and/or their teachers. What are the possible benefits of taking part? It is unlikely that you or your child will benefit directly from taking part. However, it is hoped that the study will improve our understanding of people with DCD/dyspraxia, which could have clinical implications for improving the lives of this group of people. Understanding the moods and emotions of adolescents without DCD/dyspraxia, and how they affect skills that are central to learning such as planning and memory, will also be of great use to teachers and researchers.

86

What happens when the research study stops?

You may receive a summary of the research findings at the end of the study (after February 2018). You can indicate if and how you would like to receive this on the initial screening questionnaire. This summary will only include the overall findings of the study. We will not provide individual feedback on your child’s or your own responses. What if there is a problem?

Any complaint or concern about any aspect of the way you have been dealt with during the course of the study will be addressed; please contact Dr Hayley Leonard (Research Supervisor) on 01483 686888 or h.leonard@surrey.ac.uk. You may also contact the Head of School, Professor Derek Moore, on 01483 686933 or d.g.moore@surrey.ac.uk. Will taking part in the study be kept confidential? Yes. All of the information that you and your child give will be anonymised so that those reading reports from the research will not know who has contributed to it. All project data will be held for at least 6 years and all research data for at least 10 years in accordance with University policy. Data will be stored securely in accordance with the Data Protection Act 1998. However, should you or your child disclose information that suggests your child is at risk then the researcher may need to report this to an appropriate authority. This would usually be discussed with you first. Contact details

Serif Omer Trainee Clinical Psychologist s.omer@surrey.ac.uk Dr Hayley Leonard Lecturer h.leonard@surrey.ac.uk School of Psychology AD Building University of Surrey Guildford GU2 7XH 01483 686888

87

Who is organising and funding the research?

This research is unfunded and is being completed by Serif Omer as part of a Doctorate in Clinical Psychology at the University of Surrey. Who has reviewed the project? The study has been reviewed and received a Favourable Ethical Opinion (FEO) from the Faculty of Health and Medical Sciences Ethics Committee, at the University of Surrey. Thank you for taking the time to read this Information Sheet.

88

Adolescent Information Sheet (TD group; 07.11.17; Version 2)

Title of Project

Executive function and internalizing problems in adolescents with and without

Developmental Coordination Disorder

Introduction

Hi, my name is Serif Omer and I would like to invite you to take part in a research

study. At the University of Surrey, we are trying to learn more about the effect of

movement skills on young people’s mood and thinking. We are comparing young people

with no movement difficulties, like you, with young people who do have movement

difficulties.

Why is this study being done?

People with Developmental Coordination Disorder (DCD), which is sometimes called

‘Dyspraxia’, have difficulties with movement tasks (such as handwriting and sports).

However, they may also have difficulties with their mood and some thinking skills (such

as memory and planning ahead). We would like to know more about whether young

people with DCD have differences in their mood and thinking skills compared to young

people without DCD and why this might be. We hope that this research will help to

better understand the effect of DCD on young people which could help to improve

their lives. This research could also help to better understand difficulties with mood

and thinking skills in young people, like you, that do not have DCD.

Why have I been invited to take part?

As part of this study, we are looking for young people between the age of 12 and 16

who do not have DCD/dyspraxia. You have been invited to take part because you might

be suitable. Your parent/guardian has also agreed for you to take part.

Do I have to take part?

Remember, being in this study is up to you. Even if your parents give their permission

for you to participate in this study, you still can decide for yourself if you want to

take part. You don’t have to be in this study if you don’t want to! Even if you agree to

take part in the study, you can still stop at any time without giving a reason. If you

decide not to take part, this will not affect you negatively in any way.

What will happen if I take part?

If you agree to be in this study, I will ask you to sign a consent form. I will also ask you

to complete a questionnaire which asks you about your mood and emotions.

Unfortunately, you will not receive any money for taking part. Your parent/guardian

will be given the option at the end of the survey to enter a prize draw for a £100

89

Amazon voucher. The winner will be contacted by email at the end of study in April

2018.

Will information about me be available to anyone?

The information that we collect from you is confidential and anonymous. Only members

of our team will be able to see this information. Your school and your

parents/guardians will not have access to the information we collect. In our findings

we will discuss the results of many young people - we do not single out or name any one

participant.

However, if your parent/guardian has a concern, we may share a report of your

strengths and weaknesses with them which they can pass on to a professional if they

so choose. The only other time that we will tell somebody else about something you

have said is if we think you or someone else may be at risk of harm.

This research study has been reviewed and given a Favourable Ethical Opinion by

Faculty of Health and Medical Sciences Ethics Committee, at the University of Surrey.

This means that the study has been checked and it is ethical for it to be conducted.

What if I have a question or there is a problem?

You can ask any questions that you have about the study at any time. If you have a

question you can contact me or other people in my team using the contact details

below.

Serif Omer

Trainee Clinical Psychologist

s.omer@surrey.ac.uk

Dr Hayley Leonard

Lecturer

h.leonard@surrey.ac.uk

School of Psychology

AD Building

University of Surrey

Guildford

GU2 7XH

01483 686888

Thank you for taking the time to read this Information Sheet.

90

Appendix G: Parent consent form

A copy of the parent consent form is provided on the following page.

91

Parent Consent Form [version 1, date 26.09.2016] Executive function and internalizing problems in adolescents with and without Developmental Coordination Disorder Please initial each box

I have read and understood the Information Sheet provided (version 2, date xx/xx/xx). I have been given a full explanation by the investigators of the nature, purpose, location and likely duration of the study, and of what my child and I will be expected to do.

I have been advised about the potential for some questions to be of a sensitive nature for my child and/or myself. I have been given the opportunity to ask questions on all aspects of the study and have understood the advice and information given as a result.

I agree to comply with the requirements of the study as outlined to me to the best of my abilities. I shall inform the investigators immediately if I have any concerns.

I agree for my child’s and my own anonymised data to be used for this study that will have received all relevant ethical approvals.

I understand that all project data will be held for at least 6 years and all research data for at least 10 years in accordance with University policy and that my personal data is held and processed in the strictest confidence, and in accordance with the UK Data Protection Act (1998).

I understand that my child and I are free to withdraw from the study at any time without needing to justify our decision, without prejudice and without our legal rights and school education being affected.

I understand that I can request for my data and my child’s data to be withdrawn until publication of the data and that following my request all personal data already collected from us can be destroyed.

Optional. I agree for the researchers to contact me to provide me with a study results summary.

Optional. I agree for the researchers to contact me about future studies.

92

I confirm that I have read and understood the above and freely consent to participating in this study. I have been given adequate time to consider my participation.

Name of child: …….............................................. (BLOCK CAPITALS) Name of parent/guardian …….............................................. (BLOCK CAPITALS) Signed: …….............................................. Date: ……..............................................

Name of researcher taking consent: ……..............................................

(BLOCK CAPITALS) Signed: ……..............................................

Date: ……..............................................

93

Appendix H: Adolescent assent form

A copy of the adolescent assent form is provided on the following page.

94

Adolescent Assent Form [version 1, date 08.08.2016] Executive function and internalizing problems in adolescents with and without Developmental Coordination Disorder Please tick yes or no

Have you read (or been read to) about this research study? Yes No

Has somebody explained this research study to you? Yes No

Do you understand what the research study is about? Yes No

Have you asked all the questions you want? Yes No

Have you had your questions answered in a way you Yes No understand?

Do you understand it’s okay to say you don’t want to Yes No take part?

Do you understand it’s okay to stop taking part at any time? Yes No

Are you happy to take part? Yes No

If any answers are ‘no’ or you don’t want to take part, don’t sign your name on this form. If you do want to take part, please write your name and today’s date.

Your name: …….............................................. Date: …….............................................. Name of researcher taking consent:

……..............................................

Signed: .................................................... Date: …………………………………………………

95

Appendix I: Eligibility screening questionnaire

Please answer the following questions about your child:

1. Date of birth: …………………………………………………………….

2. Gender: Male Female Other

3. a. Have they received a diagnosis of Developmental Coordination Disorder

(sometimes also known as Dyspraxia); or have they been referred for an

assessment of Developmental Coordination Disorder?

Yes, diagnosed Awaiting assessment No

b. If yes, are you able to provide a diagnostic report to the research team? Yes No

4. Have they received a diagnosis of an Attention Deficit Hyperactivity Disorder

(ADHD); or have they been referred for an assessment of Attention Deficit

Hyperactivity Disorder?

Yes, diagnosed Awaiting assessment No

5. Have they received a diagnosis of an Autism Spectrum Disorder (ASD)

(sometimes also known as Asperger’s syndrome); or have they been referred

for an assessment Autism Spectrum Disorder?

Yes, diagnosed Awaiting assessment No

6. Would you like to be contacted after the study to receive a summary of the

overall findings?

Yes, by email Yes, by post No

96

Appendix J: Favourable ethical opinion

Chair’s Action Proposal Ref: 1214-PSY-16

Names of Student/Trainee:

SERIF OMER

Title of Project: Executive function and internalizing problems in adolescents with and without Development Coordination Disorder

Supervisors: Dr Hayley Leonard

Date of submission: Date of resubmission:

16th August, 2016 27th September 2016

The above Research Project has been re-submitted to the Faculty of Health and Medical Sciences Ethics Committee and has received a favourable ethical opinion on the basis described in the protocol and supporting documentation. The final list of documents reviewed by the Committee is as follows: Ethics Application Form Detailed protocol for the project Participant Information sheet Consent Form Risk Assessment Insurance Documentation (If appropriate)

All documentation from this project should be retained by the student/trainee in case they are notified and asked to submit their dissertation for an audit.

Signed and Dated: _27/09/2016________________

Dr Anne Arber, Professor Bertram Opitz Co-Chairs, Ethics Committee

Please note: If there are any significant changes to your proposal which require further scrutiny, please contact the Faculty of Health and Medical Sciences Ethics Committee before proceeding with your Project.

97

Appendix K: Assumptions for independent samples t-tests

Data plots

Histograms, Q-Q plots, and boxplots were created for each of the study groups to

explore the data for outliers and normality.

(i) Internalising symptoms (RCADS Total):

TD group DCD group

98

(ii) Executive function difficulties (BRIEF GEC):

TD group DCD group

99

Outliers

The data was explored for univariate outliers prior to further analyses. No

outliers were identified on inspection of histograms or boxplots. Z-scores were also

calculated for each variable, where 5% of the total sample (n = 2.15) were expected to

exceed +/-1.98, 1% (n = 0.43) were expected to exceed +/-2.58, and 0% expected to

exceed +/-3.29 (Field, 2013). On the RCADS Total, only one data point exceeded a Z-

score of +/-1.98 (fewer than the 5% cut-off) and no data points exceeded +/-2.58. On

the BRIEF GEC, two data points exceeded +/-1.98 (at the expected level) and no data

points exceeded +/-2.58. This suggests that no univariate outliers were present.

Normality

The data were explored for normality. Inspection of histograms and Q-Q plots

indicated that the data was skewed for both the RCADS Total and BRIEF GEC in both

100

study groups. Skewness and kurtosis scores were calculated for each variable and

divided by their standard error to obtain z-scores (see Table K1). All scores were within

the cut-off for significance (1.96) suggesting the distributions did not differ significantly

from a normal distribution. Both the Kolmogorov-Smirnov test and Shapiro-Wilk test

were conducted to explore whether the sample differed significantly from a normal

distribution. These tests identified that both the RCADS Total and BRIEF GEC differed

significantly form a normal distribution in the TD group, but not in the DCD group.

Considering all this information, the data for both the RCADS Total and BRIEF GEC

were not considered to meet the assumption of normal distribution. As such,

bootstrapping was used in the analyses which is considered robust to violations of this

assumption (Field, 2013).

Table K1. Normality statistics for study variables

Variable Skewness z-

score

Kurtosis z-score Kolmogorov-

Smirnov test (p)

Shapiro-Wilk test

(p)

TD DCD TD DCD TD DCD TD DCD

RCADS-25

Total

1.53 0.040 -0.97 -1.142 .018* .200 .012* .466

BRIEF GEC 1.8 -1.382 -0.37 -0.049 .070 .140 .011* .195

*Significantly different from a normal distribution (p < .05) BRIEF GEC: Behaviour Rating Inventory of Executive Function – Global Executive Index; DCD:

Developmental Coordination Disorder; RCADS-25: Revised Child Anxiety and Depression Scale – Short

version; TD: Typically developing

101

Homogeneity of variance / homoscedasticity

The variance of the outcome variable was explored for homogeneity. The

variance ratios between the two groups indicated that the variances were approximately

equal (RCADS Total: 1.38; BRIEF GEC: 1.76). In support of this, Levene’s test was not

significant for both the RCADS Total, F (1, 41) = 1.033, p = .315, and BRIEF GEC, F

(1, 41) = 1.720, p = .197). This suggests that the variance was stable at each level of the

independent variable (DCD Status).

102

Appendix L: Assumptions for simple mediation analysis

The main assumptions for linear regression were explored for each path in the mediation

analysis (i.e. path a, b and c).

Multivariate outliers / influential cases

For each regression, the standardised residuals (z-scores) were calculated. It was

expected that 2.15 cases (5% of total sample) would have standardised residuals

exceeding +/-1.96 standard deviations from the mean, 0.43 cases (1%) would exceed +/-

2.58, and zero cases (0%) would exceed +/- 3.29 (Field, 2013). Each regression was also

explored for influential cases. Cook’s distance was calculated, whereby scores greater

than 1 indicate the case is having an undue influence on the model (Cook, 1977).

Leverage values were calculated, whereby values greater than three times the average

leverage indicate undue influence (Stevens, 2002). Finally, Mahalanobis distances were

calculated, whereby values exceeding 11 were deemed as having undue influence (the

cut-off suggested for very small sample sizes with two predictors; Field, 2013).

Path a: One case (2.3%) exceeded +/-1.96 standard deviations from the mean

and zero cases exceeded +/- 2.58 standard deviations from the mean. This is within

expected levels, given the small sample size. Further examination indicated that no cases

had a Cook’s distance higher than 1 (highest value = 0.13). Zero cases had leverage

values larger than three times the average Leverage (Average Leverage = 0.05; highest

value = 0.05). No values had a Mahalanobis value greater than 11 (highest value = 2.02).

Given the above, no cases were deemed to have had any undue influence on the model.

103

Path b: One case (2.3%) exceeded +/-1.96 standard deviations from the mean

and zero cases exceeded +/- 2.58 standard deviations from the mean. This is within

expected levels, given the small sample size. Further examination indicated that no cases

had a Cook’s distance higher than 1 (highest value = 0.14). Zero cases had leverage

values larger than three times the average Leverage (Average Leverage = 0.07; highest

value = 0.18). No values had a Mahalanobis value greater than 11 (highest value = 7.43).

Given the above, no cases were deemed to have had any undue influence on the model.

Path c: Zero cases (0%) exceeded +/-1.96 standard deviations from the mean.

Further examination indicated that no cases had a Cook’s distance higher than 1 (highest

value = 0.13). Zero cases had leverage values larger than three times the average

Leverage (Average Leverage = 0.05; highest value = 0.05). No values had a

Mahalanobis value greater than 11 (highest value = 2.02). Given the above, no cases

were deemed to have had any undue influence on the model.

Independence of errors

Durbin-Watson statistics were calculated for each regression model to explore

the assumption of independent errors (i.e. the residuals within the model are

uncorrelated). This assumption was met if values were close to 2 (Durbin & Watson,

1950, 1951).

Path a: The data met the assumption of independent errors as the Durbin-

Watson statistic lay very close to 2 (Durbin-Watson = 1.904).

Path b: The data met the assumption of independent errors as the Durbin-

Watson statistic lay very close to 2 (Durbin-Watson = 1.971).

104

Path c: The data met the assumption of independent errors as the Durbin-Watson

statistic lay very close to 2 (Durbin-Watson = 1.771).

Linearity and homoscedasticity

A graph depicting the standardised residuals against the standardised predicted

values was plotted for the model including both the independent variable (IV) and

mediator (M) as predictors (i.e. path b). Data points were generally dispersed randomly

and evenly throughout the plot indicate that linearity and homoscedasticity can be

assumed. Homogeneity of variance was previously explored and assumed for paths a

and c prior to conducting t tests (see Appendix K).

105

Normally distributed errors

Histograms and P-P plots of the standardised residuals were created for each

regression model to explore the distribution of errors (see below). They show that the

distribution of errors was approximately normally distributed, at least sufficiently for

bootstrapping analyses.

Path a:

Path b:

106

Path c:

Homogeneity of regression

The data were tested to check that the relationship between the mediator and

dependent variable (DV) were not dependent on the IV. When including the interaction

between DCD status and BRIEF GEC in the model, the interaction was not significant (p

= .192).

Multicollinearity

The data was assessed for multicollinearity prior to conducting the mediation

analysis. Pearson’s correlation coefficients between the key predictor variables indicated

no correlations were higher than .90. Correlations of .90 or more are suggestive of

multicollinearity (Field, 2013). Further tests also indicated that the VIF level was below

10 (Bowerman & O’Connell, 1990; Myers, 1990) and tolerance was above 0.2 (Menard,

1995) when entering both predictors (DCD status and BRIEF GEC) into the model

(VIF= 4.182; tolerance = 0.239.

107

Appendix M: Assumptions for subscale analyses using independent samples t-tests

Data plots

Histograms, Q-Q plots, and boxplots were created for each subscale of the

RCADS-25 and BRIEF across each study group to explore the data for outliers and

normality.

(i) Depression symptoms (RCADS-25 Depression):

TD group DCD group

108

Anxiety symptoms (RCADS-25 Anxiety):

TD group DCD group

109

(ii) Behavioural regulation difficulties (BRIEF BRI):

TD group DCD group

110

(iii) Metacognitive difficulties (BRIEF MCI):

TD group DCD group

111

Outliers

The data was explored for univariate outliers prior to further analyses. No

significant outliers were identified on inspection of histograms or boxplots. Z-scores

were also calculated for each variable, where 5% of the total sample (n = 2.15) were

expected to exceed +/-1.98, 1% (n = 0.43) were expected to exceed +/-2.58, and 0%

expected to exceed +/-3.29 (Field, 2013). On the RCADS-25 Depression subscale, only

one data point exceeded a Z-score of +/-1.98 (fewer than the 5% cut-off) and no data

points exceeded +/-2.58. On the RCADS-25 Anxiety subscale, two data points exceeded

+/-1.98 (at the expected level) and no data points exceeded +/-2.58. Zero cases exceeded

a z-score of +/-1.96 on both the BRIEF BRI and BRIEF MCI. This suggests that no

univariate outliers were present.

Normality

The data were explored for normality. Inspection of histograms and Q-Q plots

indicated that the data was skewed for all subscales in both study groups. Skewness and

112

kurtosis scores were calculated for each variable and divided by their standard error to

obtain z-scores (see Table M1). The RCADS-25 Anxiety subscale in the TD group

exceeded the cut-off for significance (+/-1.96), indicating that it was significantly

negatively skewed. Both the Kolmogorov-Smirnov test and Shapiro-Wilk test were

conducted to explore whether the samples differ significantly from a normal distribution.

A combination of these tests indicated that all subscales differed significantly from a

normal distribution in the TD group, but not in the DCD group. Considering all this

information, the data for the subscales were not considered to meet the assumption of

normal distribution. As such, bootstrapping was used in the analyses which is considered

robust to violations of this assumption (Field, 2013).

Table M1. Normality statistics for subscale variables

Variable Skewness z-score Kurtosis z-score Kolmogorov-

Smirnov test (p)

Shapiro-Wilk

test (p)

TD DCD TD DCD TD DCD TD DCD

RCADS-25

Depression

1.94 -1.05 -0.22 -0.48 .025* .200 .021* .296

RCADS-25 Anxiety 2.47* 0.94 0.63 -0.66 .018* .184 .008* .195

BRIEF BRI 0.74 -0.76 -1.40 -0.82 .200 .200 .049* .471

BRIEF MCI 1.83 -1.21 -0.33 0.67 .170 .200 .009* .683

*Significantly different from a normal distribution (p < .05)

BRI: Behavioural Regulation Index; BRIEF: Behaviour Rating Inventory of Executive Function; DCD:

Developmental Coordination Disorder; MCI: Metacognitive Index; RCADS-25: Revised Child Anxiety

and Depression Scale – Short version; TD: Typically developing

113

Homogeneity of variance / homoscedasticity

The variance of the outcome variable was explored for homogeneity. The

variance ratios between the two groups indicated that the variances were approximately

equal (RCADS-25 Depression: 1.07; RCADS-25 Anxiety: 1.40; BRIEF BRI: 1.11;

BRIEF MCI: 1.60). In support of this, Levene’s test was not significant for all outcomes,

largest: F (1, 41) = 1.38, p = .247. This suggests that the variance was stable at each

level of the independent variable (DCD Status).

114

Appendix N: Assumptions for parallel multiple mediation analysis based on

subscales

The assumptions for linear regression were explored for each path in the parallel

multiple mediation analyses (i.e. paths a1, a2, b1, b2, c). This included separate analyses

with the RCADS-25 Depression and RCADS-25 Anxiety scores as the DV.

Multivariate outliers / influential cases

For each regression, the standardised residuals (z-scored) were calculated. The

models ranged from having 0 to 1 cases exceeding +/-1.96 standard deviations from the

mean. Among all models, no cases had a Cook’s distance higher than 1 (highest values:

0.13 to 15). No cases had Leverage value greater than three times the average Leverage

(highest values: 0.05 to 0.17). No cases had a Mahalanobis value greater than 11

(highest values: 2.02 to 7.02). Given the above, no cases were deemed to have had any

undue influence on any of the models.

Independence of errors

Durbin-Watson statistics were close to 2 for all models (range: 1.693 to 2.147).

Linearity and homoscedasticity

A graph depicting the standardised residuals against the standardised predicted

values was plotted for the models including all predictors. Data points were generally

dispersed randomly and evenly throughout the plots indicating that linearity and

115

homoscedasticity can be assumed for both models. Homogeneity of variance was

previously explored and assumed for paths a and c prior to conducting t-tests (see

Appendix M).

RCADS-25 Depression RCADS-25 Anxiety

Normally distributed errors

Histograms and P-P plots of the standardised residuals were created for each

regression model. They show that the distribution of errors was approximately normally

distributed. Plots of the models including all predictors are displayed below.

RCADS-25 Depression RCADS-25 Anxiety

116

Homogeneity of regression

The data were tested to check that the relationship between the mediators and

DV’s were not dependent on the IV. When including the interaction between IV and

M’s, the interaction was not significant (range of p = .068 to .248).

Multicollinearity

The VIF level was below 10 (Bowerman & O’Connel, 1990; Myers, 1990) and

tolerance was above 0.2 (Menard, 1995) for all variables (range, VIF= 3.77-4.27;

tolerance = 0.234-2.65).

117

Appendix O: Assumptions for simple mediation analysis within the TD sample

The main assumptions for linear regression were explored for each path in the

mediation analysis (i.e. path a, b and c) with the DCDQ-07 as the IV (TD group only).

Multivariate outliers / influential cases

For each regression, the standardised residuals (z-scores) were calculated. It was

expected that 1.60 cases (5% of total sample) would have standardised residuals

exceeding +/-1.96 standard deviations from the mean, 0.32 cases (1%) would exceed +/-

2.58, and zero cases (0%) would exceed +/- 3.29 (Field, 2013). Cook’s distance,

leverage values, and Mahalanobis distances were also calculated.

Path a: Two cases (6.25%) exceeded +/-1.96 standard deviations from the mean

and zero cases exceeded +/- 2.58 standard deviations from the mean. No cases had a

Cook’s distance higher than 1 (highest value = 0.12). Zero cases had leverage values

larger than three times the average Leverage (Average Leverage = 0.03; highest value =

0.09). No values had a Mahalanobis value greater than 11 (highest value = 6.07). Given

the above, no cases were deemed to have had any undue influence on the model.

Path b: One case (3.13%) exceeded +/- 2.58 standard deviations. No cases had a

Cook’s distance higher than 1 (highest value = 0.21). One case had a leverage value

larger than three times the average Leverage (Average Leverage = 0.06; highest value =

0.22). No values had a Mahalanobis value greater than 11 (highest value = 6.71). Given

the above, no cases were deemed to have had any undue influence on the model.

118

Path c: One case (3.13%) exceeded +/-1.96 standard deviations from the mean

and no cases exceeded +/-2.58 standard deviations. Further examination indicated that

no cases had a Cook’s distance higher than 1 (highest value = 0.14). Two cases had

leverage values larger than three times the average Leverage (Average Leverage = 0.03;

highest value = 0.19). No values had a Mahalanobis value greater than 11 (highest value

= 6.07). Given the above, no cases were deemed to have had any undue influence on the

model.

Independence of errors

The data met the assumption of independent errors as the Durbin-Watson statistic

lay very close to 2 (Durbin-Watson range = 1.792-2.14).

Linearity and homoscedasticity

A graph depicting the standardised residuals against the standardised predicted

values was plotted for each path. Data points were dispersed randomly and

approximately evenly throughout the plot indicating that linearity and homoscedasticity

can be assumed.

119

Path a:

Path b:

Path c:

120

Normally distributed errors

Histograms and P-P plots of the standardised residuals were created for each

regression model to explore the distribution of errors (see below). They show that the

distribution of errors was approximately normally distributed, at least sufficiently for

bootstrapping analyses.

Path a:

Path b:

121

Path c:

Multicollinearity

The data was assessed for multicollinearity prior to conducting the mediation

analysis. Pearson’s correlation coefficients between the key predictor variables indicated

no correlations were higher than .65. Further tests also indicated that the VIF level was

below 10 (Bowerman & O’Connell, 1990; Myers, 1990) and tolerance was above 0.2

(Menard, 1995) when entering both predictors (DCDQ-07 and BRIEF GEC) into the

model (VIF= 1.00; tolerance = 1.00).

122

Part 2: Major Research Project Literature review

Internalising symptoms in Developmental Coordination Disorder: A

systematic review and meta-analysis

Word count: 6175

Statement of Journal Choice

The Journal of Child Psychology and Psychiatry

‘The Journal of Child Psychology and Psychiatry’ publishes research that advances the

understanding of developmental psychopathology and that informs theory and clinical

practice. It is a leading journal for child and adolescent psychology and psychiatry. The

journal has confirmed interest in this paper for submission to their ‘Research Reviews’

section. See Appendix for more details.

123

Abstract

Background: Developmental Coordination Disorder (DCD) affects 5-6% of children.

There is growing evidence that DCD is associated with greater levels of internalising

symptoms (i.e. depression and anxiety). This is the first systematic review and meta-

analysis to explore the magnitude of this effect, the quality of the evidence, and potential

moderators. Methods: A systematic search was conducted to identify studies reporting a

comparison between individuals with DCD/probable DCD and typically developing

(TD) individuals on measures of internalising symptoms. A pooled effect size (Hedges

g) was calculated using random effects meta-analysis. Study quality, publication bias

and potential moderators of the effect were explored. Results: Twenty studies, including

a total of 23 subsamples, met the inclusion criteria, of which 22 subsamples were

included in the meta-analysis (DCD: n = 1123; TD: n = 7346). A significant, moderate

effect of DCD on internalising symptoms was found (g = 0.61). This effect remained

robust after accounting for publication bias and excluding lower quality studies. The

effect was significantly larger in studies utilizing a cross-sectional design (vs.

longitudinal), convenience sampling (vs. population screening) and a majority male

sample. Conclusions: The findings demonstrate that individuals with DCD experience

greater levels of internalising symptoms than their peers. This highlights the importance

of routine screening for emotional difficulties in DCD, raising awareness of the

condition in mental health services, and developing psychosocial interventions that

extend beyond a focus on motor impairments. However, there is a need for higher

quality, longitudinal studies to better understand the causal relationship between DCD

and internalising symptoms.

124

Keywords: Developmental Coordination Disorder, DCD, Internalising

symptoms, depression, anxiety, mental health, meta-analysis.

125

Introduction

Developmental Coordination Disorder (DCD) is a neurodevelopmental disorder

affecting between 5-6% of children and is characterised by significant impairment to an

individual’s ability to perform everyday motor tasks (American Psychiatric Association

[APA], 2013). This can include difficulties with self-care (e.g. tying shoelaces, brushing

teeth), academic tasks (e.g. handwriting), and leisure activities (e.g. catching a ball,

balancing). A diagnosis of DCD is based on four criteria (APA, 2013): (a) performance

in motor coordination tasks is substantially below expectation given the person’s age

and opportunities; (b) the motor coordination difficulties significantly interfere with

activities of daily living or academic achievement; (c) difficulties began in the early

developmental period; and (d) the difficulties cannot be attributed to an intellectual

disability or neurological condition (e.g. cerebral palsy). DCD is sometimes referred to

as ‘dyspraxia’. However, there is no internationally agreed definition for the term

dyspraxia, it is not included in diagnostic manuals and it is sometimes used to refer to a

broader range of difficulties beyond those characterising DCD. As such, the term DCD

is used hereafter.

Despite its prevalence, DCD often goes unrecognised and is poorly understood

among healthcare and education professionals (Gaines, Missiuna, Egan, & McLean,

2008; B. N. Wilson, Neil, Kamps, & Babcock, 2013). This is of concern given that DCD

has been found to have a significant impact not just on an individual’s motor abilities,

but across a wide range of psychological, cognitive, physical and social domains

(Zwicker, Harris, & Klassen, 2013). For example, children with DCD have been found

to engage in less physical activity (Cairney, Hay, Veldhuizen, Missiuna, & Faught,

126

2010), to be at an increased risk of obesity (Cairney & Veldhuizen, 2013), to

underachieve in academic performance (Gomez et al., 2015), to be more socially

isolated (Chen & Cohn, 2003) and to have lower self-esteem (Miyahara & Piek, 2006)

compared to their typically developing (TD) peers. There is also evidence that the

impact of DCD across these domains persists through childhood and into adulthood

(Cousins & Smyth, 2003; Hill, Brown, & Sorgardt, 2011; Kirby, Sugden, Beveridge, &

Edwards, 2008). DCD also often co-occurs with other developmental disorders,

including Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum

Disorder (ASD; Pieters, et al. 2012).

One area that has received increasing attention is the impact of DCD on mental

health, specifically internalising symptoms. ‘Internalising’ is a broad construct referring

to symptoms of both depression and anxiety, which have been found to commonly

overlap in childhood and adolescence (Eaton et al., 2013; Kovacs & Devlin, 1998).

There is growing evidence that individuals with DCD have elevated levels of

internalising symptoms compared to their TD peers (Mancini, Rigoli, Cairney, Roberts,

& Piek, 2016). Research has also found associations between motor abilities and

internalising symptoms in community samples of TD children and adults (Poole et al.,

2016; Rigoli, Piek, & Kane, 2012; A. Wilson, Piek, & Kane, 2013), an increased risk of

psychiatric disorders in individuals with DCD (Rasmussen & Gillberg, 2000), and

impaired motor abilities in individuals with common psychiatric disorders (Damme,

Simons, Sabbe, & van West, 2015). The Environmental Stress Hypothesis is a

framework that was introduced to account for this relationship between DCD and mental

health (Cairney, Rigoli, & Piek, 2013). It suggests that the motor impairments in DCD

127

can expose an individual to a variety of secondary psychosocial stressors which over

time can lead to poorer mental health (see Figure 1). These proposed mediators include

physical (e.g. physical inactivity), social (e.g. interpersonal conflict, reduced social

resources), and personal factors (e.g. reduced self-esteem).

Figure 1. Diagram depicting the Environmental Stress Hypothesis as an explanation for

internalising symptoms in DCD (from Mancini et al. 2016).

Understanding the link between DCD and mental health has important

implications for assessment and intervention with this population, including at schools,

physical health services and mental health services. To date, several reviews have

summarised the findings on internalising symptoms in DCD (Caçola, 2016; Mancini et

al., 2016; Missiuna & Campbell, 2014). However, they consist of narrative summaries

only. There are also inconsistent findings, with some studies finding no significant effect

128

(Davis, Ford, Anderson, & Doyle, 2007; King-Dowling, Missiuna, Rodriguez,

Greenway, & Cairney, 2015) and others a large effect (Dewey, Kaplan, Crawford, &

Wilson, 2002; Pratt & Hill, 2011). A systematic search, synthesis and critical appraisal

of the evidence can provide a more rigorous understanding of this relationship. A meta-

analysis to pool the findings would provide a more accurate understanding of whether

individuals with DCD do indeed experience greater internalising symptoms than their

peers and would provide insight into the magnitude of this difference.

Studies also vary greatly in their design, participants, measures, and

methodological quality. Whereas some studies have recruited participants with a

confirmed diagnosis of DCD, others have included only those identified as ‘probable

DCD’ based on screening measures. Studies also differ in how well they controlled for

confounding variables, whether they employed a longitudinal or cross-sectional design,

and whether they recruited participants through population-based screening or

convenience sampling. There is also some evidence to suggest the impact may be greater

in adolescents compared to younger children (Piek et al., 2007; Skinner & Piek, 2001),

in males compared to females (Sigurdsson et al., 2002), and in individuals with

comorbid ADHD (Missiuna et al., 2014; Piek et al., 2007). A meta-analytic approach

allows for an investigation into the potential sources of heterogeneity across studies,

which could help to guide future research and intervention.

The aim of this paper was, therefore, to conduct a systematic review and meta-

analysis of studies that compared individuals with DCD to TD individuals on measures

of internalising symptoms; to appraise the quality of the evidence; and to explore which

factors moderate the effect. The focus was on severity levels of internalising symptoms,

129

as opposed to rates of actual diagnosis, given that most studies have adopted severity

outcome measures, and given that data on diagnostic rates may obscure important

differences in actual symptoms.

Method

The review was protocol-driven and carried out in accordance with

recommended guidelines for systematic reviews (Moher, Liberati, Tetzlaff, Altman, &

The Prisma Group, 2009) and meta-analyses of observational studies (Stroup et al.,

2000).

Eligibility criteria

In line with recommended guidelines, broad inclusion criteria were used with the

aim to later explore the impact of specific design features. Articles were eligible if they:

(a) included participants, of any age, with a confirmed diagnosis of DCD according to

DSM-IV or DSM-5 criteria; or who were identified as having motor coordination

difficulties consistent with DCD (i.e. ‘probable DCD’); (b) included a comparison group

of TD individuals, as defined by the absence of diagnosed or suspected developmental

disorders; (c) measured levels of internalising symptoms (i.e. depression and/or anxiety)

for each group using self-report, parent-report, teacher-report, direct observation or

clinical interview; (d) reported statistics that could be transformed into a standardised

mean difference (e.g. mean and standard deviations); and (e) were available in full text

in English. Studies involving participants with a comorbid diagnosis (e.g. ADHD) were

also eligible if the motor coordination difficulties were clearly described and used as the

130

basis for group comparison (as the first criterion above). Studies were excluded if

participants’ motor difficulties were attributed to another developmental difficulty or

medical diagnosis (e.g. cerebral palsy). For studies using the label ‘dyspraxia’, they were

required to refer to overall motor impairment and not just oro-motor difficulties and

gesture. Studies were also excluded if the outcome only included rates of psychiatric

diagnoses (i.e. they did not report on a measure of the severity of internalising

symptoms).

If separate studies included overlapping samples, priority was given to the study

with the best control of important confounders (i.e. age and gender) or the study that

allowed for the most detailed exploration of moderating factors (e.g. outcomes reported

separately by gender or age group). Where the same participants were included but

different subtests reported, data were combined (Borenstein, Hedges, Higgins, &

Rothstein, 2009).

Search strategy

Studies were identified through a systematic search of Medline, PsychInfo,

CINAHL, ERIC, and Web of Science. To minimise the impact of publication bias,

unpublished studies were also searched using ProQuest Dissertations and Theses and

Open Grey. The latest search was completed on 3rd March 2018.

The search included terms related to DCD (developmental coordination disorder,

DCD, dyspraxi*, motor skills disorder, coordination difficult*, coordination problem*,

clumsy, clumsiness, motor proficiency, motor competence, motor difficult*, motor

impairment, motor dysfunction, perceptual motor difficult*, perceptual motor

131

impairment, motor skills disorder, motor learning difficult*, motor learning problem*,

motor problem*, movement disorder, psychomotor disorder) combined with terms

related to internalising symptoms (internali*, anxi*, depress*, mood, mental health,

mental illness, mental disorder, emotional problem*, psychopatholog*). Titles and

abstracts were screened by one reviewer (SO), with 25% cross-checked by a second

(AMN; percent agreement = 97.5%, Cohen’s kappa = 0.65). The full texts of all

potentially relevant articles were then screened independently by two reviewers (SO &

AMN), with disagreement resolved by consensus and discussion with a third (HL;

percent agreement = 94.5%, kappa = 0.87). The bibliographies of the included studies

and relevant review articles were screened and their citations tracked to identify

additional studies. The first authors of the included articles were also contacted to

identify any further eligible studies or to clarify missing information.

Data extraction

Data on each study were extracted into an electronic pro forma. Two researchers

(SO & AMN) performed data extraction for all included studies and inconsistencies

were discussed until consensus was reached. Interrater reliability was good for both

categorical (percent agreement = 91-100%; kappa = 0.82-1.00) and continuous

(intraclass correlation coefficient = 1.00) data.

The following information was extracted for each study: author, publication year,

country, design (cross-sectional; longitudinal), population, sampling procedure

(population-based screening; selective/convenience sample), criteria for DCD

(confirmed DCD; probable DCD), criteria for TD, number of participants, gender

132

(percentage male), age (mean and range), comorbid ADHD diagnosis (ADHD assessed

and excluded from the sample; ADHD assessed and included; ADHD not assessed),

measure of internalising symptoms, internalising construct (depression; anxiety; overall

internalising), reporter (self-report; parent-report; teacher-report; clinician/researcher-

report), and scores (means and standard deviations, other relevant statistics).

If multiple informants or measures were used to assess internalising symptoms,

they were extracted separately so that they could be pooled (see Statistical Analysis).

Preference was given to data adjusted for important confounders (e.g. gender, age) if not

matched by design. However, where studies also adjusted for additional variables (e.g.

intelligence), the unadjusted scores were preferred to ensure comparability across studies

(Voils, Crandell, Chang, Leeman, & Sandelowski, 2011). Where findings were reported

separately for subgroups (e.g. gender, age groups) these data were extracted separately

as subsamples to facilitate the moderation analysis. Where separate groups were

included for confirmed and probable DCD, only the confirmed DCD group was

extracted. Where separate groups were included for comorbid DCD/ADHD and DCD

only, the DCD only group was extracted. This allowed for a better understanding of the

specific effect of DCD on internalising problems.

Study quality

An adapted version of the Newcastle-Ottawa Scale (NOS) was used to assess

study quality (Wells et al., 2011). Each study was rated on representativeness of the

DCD group (i.e. population screening), selection of the control group (i.e. same

population as DCD), ascertainment of DCD diagnosis (i.e. confirmed DCD); control for

133

baseline internalising (for longitudinal studies), comparability of groups (i.e. control for

confounders), measurement of internalising symptoms (i.e. validated measures), length

of follow-up (i.e. at least one year follow-up), and completeness of follow-up (i.e. ≥80%

follow-up rate or <80% but unlikely to introduce bias).

For the DCD criteria to be rated as ‘confirmed DCD’, the study must have

assessed motor skills as being below the 15th percentile using performance-based

measures (Criterion A; Blank, Smits-Engelsman, Polatajko, & Wilson, 2012), as having

a significant impact on activities of daily living or academic achievement (e.g.

questionnaires or interview; Criterion B), and ruled out intellectual disability and other

neurological conditions (e.g. by interview, performance measures, medical reports;

Criterion D). Alternatively, they could have cross-checked medical records for

diagnosis. Given that many studies were published prior to publication of the DSM-5

and the introduction of Criterion C, it was not essential that studies established whether

difficulties began in the early developmental period. The confounders considered most

important for comparability of study groups were age and gender (Twenge & Nolen-

Hoeksema, 2002). The NOS satisfies relevant guidelines for quality assessment of non-

randomised studies (Sanderson, Tatt, & Higgins, 2007) and is recommended for

systematic reviews of observational studies (Deeks et al., 2003).

Statistical Analysis

The main analysis was performed using Review Manager 5 software.

Summary effect: The standardised mean difference (SMD; Hedges g) between

the DCD group and the TD group and its 95% confidence interval were calculated for

134

each study (or subsample) separately. SMD’s around 0.2 can be considered small, 0.5

moderate, and 0.8 large. Where studies reported data on multiple measures of

internalising, a pooled effect size and variance was calculated (assuming a correlation

between measures of 1, which provides a conservative estimate of the variance;

Borenstein, Hedges, Higgins, & Rothstein, 2009). Effect sizes were weighted according

to the inverse of their variance to ensure that more precise estimates influence overall

effect size most heavily and to reduce the effect of the upwardly biased estimates of

smaller studies (Hedges & Olkin, 1985). Random-effects meta-analysis was used to

calculate a summary effect for total internalising symptoms across all studies and its

95% confidence interval.

Heterogeneity: Q-statistics were used to assess for heterogeneity and the I2

statistic to quantify the proportion of the variance due to heterogeneity. Moderators were

explored to identify potential sources of heterogeneity. The following moderators were

explored: year of publication (pre-2010 vs. post-2010), design (longitudinal vs. cross-

sectional), gender (>50% male vs. ≤50% male in the DCD group), age (included

adolescents ≥12 vs. no adolescents), comorbid ADHD (assessed and excluded vs. not

assessed, or assessed but included), sampling strategy (population screen versus

selective/convenience); selection of DCD group (confirmed vs. probable DCD),

controlled for confounders (age and gender controlled vs. uncontrolled), reporter (self-

report versus informant-report), and type of internalising (overall internalising vs.

depression vs. anxiety). The significance of moderators was tested using Q-statistics.

Publication bias: Publication bias was assessed visually using a funnel plot,

where an asymmetrical distribution indicates the presence of publication bias. Egger’s

135

test was used to statistically check for publication bias (Egger, Smith, Schneider, &

Minder, 1997). Duval and Tweedie’s trim-and-fill procedure was used to compute an

adjusted effect size by imputing the effect of smaller, unpublished studies (Duval &

Tweedie, 2000). Finally, Rosenthal's (1979) Fail-safe N was calculated to determine the

number of studies with an average effect size of 0 that would have to be included to

produce a non-significant result. This number should exceed 5k + 10 (where k is the

number of studies).

Sensitivity analysis: A sensitivity analysis was conducted to calculate a pooled

effect size excluding lower quality studies (i.e. those not meeting at least five criteria on

the NOS).

Results

Search results

The search identified a total of 20 studies meeting the inclusion criteria,

consisting of 23 eligible subsamples (two studies reported outcomes separately for males

and females, one study reported separate outcomes for children and adolescents;

hereafter these are treated as separate studies). The search process is summarised in

Figure 2.

It should be noted that two articles reported outcomes at multiple time points for

the same longitudinal study (Harrowell, Hollén, Lingam, & Emond, 2017; Lingam et al.,

2012). The data from the latter time point was used (Harrowell et al., 2017) because

separate outcomes were reported for males and females, allowing for better exploration

of moderators. Two articles reported data on the same cross-sectional study (Pearsall-

136

Figure 2. PRISMA flow diagram summarising the search process.

Records identified through

database searching

(n = 4697)

Additional records identified through other sources

Grey literature (n = 160)

Bibliographies (n = 7)

Records after duplicates removed

(n = 3081)

Records screened by titles

and abstracts

(n = 3081)

Articles excluded after title and abstract screening

(n = 3008)

Full-text articles assessed for

eligibility

(n = 73)

Articles excluded after full-text screen, with reasons (n = 53)

Review / commentary (n = 14) No DCD group / based on community sample (n = 15)

No TD group / used reference group only (n = 4)

Book chapter (n = 3)

Single item outcome (n = 3)

No measure of internalising symptoms (n = 6)

Investigated motor ability in psychiatric disorders (n = 3)

Additional articles on included studies (n =2)

Outcome based on diagnosis rates, not severity (n = 1)

Met eligibility criteria, but extreme data values reported

(n= 1)

No English full text (n = 1) Articles included in

qualitative synthesis

(n = 20)

Samples included (n = 23)

Articles included in meta-

analysis (n = 19)

Samples included (n = 22)

Articles excluded from meta-analysis

(n = 1)

Based on an adult sample (n = 1)

137

Jones, Piek, Rigoli, Martin, & Levy, 2011; Piek et al., 2007), so the larger sample was

included (Piek et al., 2007). One eligible study reported extreme values for the outcome,

raising concerns around its accuracy, and was subsequently excluded (Tseng, Howe,

Chuang, & Hsieh, 2007).

Characteristics of the included studies

The characteristics of the included studies are summarised in Table 1. A total of

8469 participants were included (1123 DCD, 7346 TD). The studies were published

between 1994 and 2018. Most were from developed countries, with one study from

Taiwan. Three prospective cohort studies were identified that screened for DCD in a

cohort and assessed their internalising symptoms at a later follow-up (Harrowell et al.,

2017, male & female samples; Wagner, Jekauc, Worth, & Woll, 2016). The remaining

20 studies adopted a cross-sectional design.

Sixteen studies identified individuals with and without DCD/probable DCD via

population-based screening of community samples (Campbell, Missiuna, &

Vaillancourt, 2012; Chen, Tseng, Hu, & Cermak, 2009; Dewey et al., 2002; Francis &

Piek, 2003; Harrowell et al., 2017; King-Dowling et al., 2015; Li et al., 2018; Missiuna

et al., 2014; Piek, Bradbury, Elsley, & Tate, 2008; Schoemaker & Kalverboer, 1994;

Skinner & Piek, 2001; van den Heuvel, Jansen, Reijneveld, Flapper, & Smits-

Engelsman, 2016; Wagner et al., 2016). Of the remaining studies, five recruited DCD

participants through selective or convenience samples such as clinical referrals or

138

support groups (Crane, Sumner, & Hill, 2017; Hill & Brown, 2013; Pratt & Hill, 2011;

Wagner, Bös, Jascenoka, Jekauc, & Petermann, 2012; Watson & Knott, 2006), one

recruited participants through screening a clinical population of children born with

extremely low birth weight (Davis et al., 2007), and one sampled from a monozygotic

twin population (Piek et al., 2007).

The studies varied in their operationalisation of the DCD group. Ten studies

confirmed a DCD diagnosis via independent assessment of diagnostic criteria (Chen et

al., 2009; Harrowell et al., 2017; Missiuna et al., 2014; van den Heuvel et al., 2016;

Wagner et al., 2012) or via clinical reports (Crane et al., 2017; Hill & Brown, 2013; Pratt

& Hill, 2011; Watson & Knott, 2006). Thirteen studies identified those as probable DCD

based on performance-based tests of motor function (Davis et al., 2007; Dewey et al.,

2002; Francis & Piek, 2003; King-Dowling et al., 2015; Li et al., 2018; Piek et al., 2008;

Schoemaker & Kalverboer, 1994; Skinner & Piek, 2001; Wagner et al., 2016) or by

parent-report questionnaires (Campbell et al., 2012; Piek et al., 2007).

Most studies recruited children and adolescents, with only one study conducted

with adults (Hill & Brown, 2013). Of the child and adolescent studies, ten included

adolescents aged 12 or over (Dewey et al., 2002; Harrowell et al., 2017; Li et al., 2018;

Missiuna et al., 2014; Piek et al., 2007; Pratt & Hill, 2011; Skinner & Piek, 2001,

adolescent sample; Wagner et al., 2016; Watson & Knott, 2006). There was a mix of

male and female participants across the studies, with fourteen having majority male

participants (Campbell et al., 2012, male sample; Crane et al., 2017; Davis et al., 2007;

Dewey et al., 2002; Francis & Piek, 2003; Harrowell et al., 2017, male sample; King-

139

Table 1. Summary of characteristics of the included studies

Study Year Population DCD

assessment

DCD

sample, n

TD sample,

n

DCD age,

mean (range)

TD age,

mean (range)

DCD

gender,

% male

TD

gender,

% male

Excluded

ADHD?

(measure)

Confounders

controlled

Internalising measures,

(type)

Longitudinal studies

Harrowell et

al. (male

sample)

2017 Population screening: Birth

cohort in south-west

England, motor skills

assessed age 7.

Confirmed

DCD

(researcher

assessment)

SDQ: 109;

SMFQ: NR

(total sample

for SMFQ:

1374)

SDQ: 1780;

SMFQ: NR

(total sample

for SMFQ:

1374)

NR

(SMFQ

collected at

17.5 years;

SDQ at 16.5

years)

NR

(SMFQ

collected at

17.5 years;

SDQ at 16.5

years)

100% 100% No

(measured,

but not

excluded)

Age, gender.a

SMFQ (self-rated

depression); SDQ -

emotional subscale (self-

rated internalising)

Harrowell et

al. (female

sample)

2017 Population screening: Birth

cohort in south-west

England, motor skills

assessed age 7.

Confirmed

DCD

(researcher

assessment)

SDQ: 59

SMFQ: NR

(total sample

for SMFQ:

1803)

SDQ: 1970

SMFQ: NR

(total sample

for SMFQ:

1803)

NR

SMFQ

collected at

17.5 years;

SDQ at 16.5

years

NR

SMFQ

collected at

17.5 years;

SDQ at 16.5

years

0% 0% No

(measured,

but not

excluded)

Age, gender.a SMFQ (self-rated

depression); SDQ -

emotional subscale (self-

rated internalising)

Wagner et

al.

2016 Population screening:

Cohort of 6-10 year olds

across Germany. Motor

skills assessed age 6-10.

Probable DCD

(performance-

based test)

114 823 14.35 (12-16) 14.38 (12-16)

47.8% 49.3% No

(assessed,

not

excluded)

Gender, age,

baseline

internalising

symptoms

SDQ (parent-rated

internalising)

140

Cross-sectional Studies

Campbell et

al. (male

sample)

2012 Population screening: Fifth

grade students from

previous longitudinal study

in Ontario, Canada.

Probable DCD

(screening

questionnaire)

77 77 10.9 (10-11)b 10.9 (10-11)b 100% 100% No (not

assessed)

Age, gender BASC-2 – depression

subscale (self-rated

depression)

Campbell et

al. (female

sample)

2012 Population screening: Fifth

grade students from

previous longitudinal study

in Ontario, Canada.

Probable DCD

(screening

questionnaire)

82 82 10.9 (10-11)b 10.9 (10-11)b 0% 0% No (not

assessed)

Age, gender BASC-2 – depression

subscale (self-rated

depression)

Chen et al. 2009 Population screening: 1st-3rd

grade children in greater

Taipei area, Taiwan.

Confirmed

DCD

(researcher

assessment)

61 209 7.93 (NR)

(range for

total sample:

6.25-10.08

7.68 (NR)

(range for

total sample:

6.25-10.08

59.0% 59.8% No

(measured,

not

excluded)

None CBCL – Chinese version -

withdrawn, somatic

complaints,

depressed/anxious subscales

(parent-rated internalising)

Crane et al. 2017 Convenience sample:

children with DCD via

primary schools and charity;

TD via primary schools in

South London, UK.

Confirmed

DCD (medical

report and

researcher

assessment)

30 35 8.61 (7-10) 9.12 (7-10) 70.0% 74.3% Yes (self-

/parent-

report)

None SDQ-Teacher - Emotional

subscale (teacher-rated

internalising)

Davis et al. 2007 Screening of clinical

sample: Cohort of children

born with ELBW or very

preterm in Victoria,

Australia.

Probable DCD

(performance-

based tests)

20 190 NR (8-9) NR (8-9) 75.0% 40.5% No (not

assessed)

None

BASC-parent: internalising

subscale (parent-rated

internalising); BASC-

teacher rated (teacher-rated

internalising)

141

Dewey et al. 2002 Population screening: public

and private schools in

Calgary, Canada.

Probable DCD

(performance-

based tests,

screening

questionnaires)

45 78 11.8 (NR) 11.4 (NR) 55.7% 75.6% No

(measured,

not

excluded)

None CBCL - internalising

(parent-rated internalising)

Francis &

Piek

2003 Population screening:

Grades 3-5 in primary

schools in Perth, Australia.

Probable DCD

(performance-

based test)

42 42 NR (7-11) NR (7-11) 52% 52% No (not

assessed)

Age and

gender

CDI (self-rated depression)

Hill &

Brown

2013 Convenience sample: DCD

adults via support groups

and higher education

institutions.

TD adults via higher

education institutions and

local community centres

across UK.

Confirmed

DCD (medical

report)

36 49 29.28 (19-59) 27.84 (18-56) 42% 49% Yes (self-

report)

None STAI-Trait (self-rated

anxiety); STAI-State (self-

rated anxiety); BDI (self-

rated depression)

King-

Dowling et

al.

2015 Population screening:

community organizations in

Southern Ontario, Canada.

Probable DCD

(performance-

based tests)

37 117 4.92 (NR) 4.92 (NR) 78% 42% No (not

assessed)

None CBCL (parent-rated

internalising)

Li et al. 2018 Population screening:

Participants from the

Physical Health and

Activity Study Team project

from schools in Canada.

Probable DCD

(performance-

based test)

79 1127 13.45 (12-14) 13.40 (12-14) 38.0% 51.6% No (not

assessed)

None Kessler-6 Scale (self-rated

internalising)

142

Missiuna et

al.

2014 Population screening:

Grades 4-8 from schools

within two health boards

regions in Canada.

Confirmed

DCD

(researcher

assessment)

68 91 11.8 (NR) 12.0 (NR) 60% 51% Yes (parent-

/school-

report)

None CDI (self-rated depression);

CDI (parent-rated

depression); SCARED (self-

rated anxiety); SCARED

(parent-rated anxiety)

Piek et al. 2007 Screening of a twin sample:

Monozygotic twins

discordant for DCD on the

Australian Twin Registry.

Probable DCD

(screening

questionnaire)

24 24 11.91 (6.45-

16.99)

11.91 (6.45-

16.99)

45.8% 45.8% Yes

(screening

measure)

Age, gender,

(also genes

and shared

environmental

factors)

Twin and Sibling

Questionnaire - Sad Affect

subscale (parent rated

depression)

Piek et al. 2008 Population screening:

Kindergarten children in a

primary school in Western

Australia.

Probable DCD

(performance-

based tests)

14 26 NR;

Total sample

mean = 4.3

(3.75-5.33)

NR;

Total sample

mean = 4.3

(3.75-5.33)

71.4% NR No (not

assessed)

Noned CBCL - anxious/depressed

subscale (parent-rated

internalising)

Pratt & Hill 2011 Convenience sample: DCD

from support groups,

existing research, schools

within London and south-

east England; TD from

existing research and

schools within London and

south-east England.

Confirmed

DCD (medical

report)

27 35 10.08 (6-15) 9.38 (6-15) 74.1% 51.4% Yes

(medical

report and/or

screening

measure)

None SCAS-Parent (parent-rated

anxiety)

Schoemaker

&

Kalverboer

1994 Population screening: Dutch

mainstream schools.

Probable DCD

(performance-

based test)

18 18 7.3 (6.1-9.0) 7.3 (6.0-9.1) 83.3% 83.3% No (not

assessed)

Age, gender STAIC-Trait (child-rated

anxiety); STAIC-State

(child-rated anxiety)

143

Skinner &

Piek (child

sample)

2001 Population screening:

Primary schools in Western

Australia.

Probable DCD

(performance-

based tests)

58 58 NR (8-10) NR (8-10) 31% 31% No (not

assessed)

Age, gender STAIC-Trait (self-rated

anxiety); STAIC-State (self-

rated anxiety)

Skinner &

Piek

(adolescent

sample)

2001 Population screening: High

schools in Western

Australia.

Probable DCD

(performance-

based tests)

51 51 NR (12-14) NR (12-14) 43% 43% No (not

assessed)

Age, gender STAIC-Trait (self-rated

anxiety); STAIC-State (self-

rated anxiety)

van den

Huevel et al.

2016 Population screening:

Primary schools in middle

and eastern Netherlands.

Confirmed

DCD

(researcher

assessment)

TRF: 20;

SDQ 22

TRF: 307;

SDQ: 339

NR;

For total

sample (not all

included in

analysis): 7.0

(4.3-10.3)

NR

For total

sample (not all

included in

analysis): 7.2

(4.0–10.8)

NR;

For total

sample

(not all

included

in

analysis):

69.6%

NR;

For total

sample

(not all

included

in

analysis):

49.1%

No

(measured,

not

excluded)

None TRF- internalising subscale

(teacher-rated internalising)

SDQ-teacher- Emotional

subscale (teacher-rated

internalising)

Wagner et

al.

2012 DCD: Clinical sample from

occupational therapy groups

in Germany;

TD: elementary schools in

Germany.

Confirmed

DCD

(researcher

assessed)

35 35 7.69 (5-11) NR “matched” 77.1% 77.1% No (not

assessed)

Age, gender IDS – Internalising scale

(parent-rated internalising)

144

Watson &

Knott

2006 DCD: Clinical sample from

Occupational therapy

department in West of

Scotland;

TD: Primary schools in

West of Scotland.

Confirmed

DCD (medical

report)

15 30 10.2 (8-12) 10.25 (NR) 80% 80% Yes (self-

report or

medical

report)

Age and

gender

Birleson Depression

Measure (self-rated

depression)

BASC: Behaviour Assessment System for Children; BDI: Beck Depression Inventory; CBCL: Child Behaviour Checklist; CDI: Children’s Depression Inventory; ELBW: Extremely Low Birth Weight; IDS: Intelligence and Developmental Scales; NR: Not reported; SCARED: Screen for Child Anxiety Related Disorders; SCAS: Spence Chi ldren's Anxiety Scale; SDQ: Strengths and Difficulties Questionnaire; SMFQ: Short Moods and Feelings Questionnaire; STAI: State-Trait Anxiety Inventory for Adults; STAIC: State-Trait Anxiety Inventory for Children; TRF: Teacher Report Form. a Additional confounders included in adjusted analysis: maternal depression, family adversity, IQ, social communication. b Based on reported age for combined male and female subsamples. c Study reports two alternative performance-based measures for determining DCD. Criteria based on the MABC were used for comparability with other studies. d Adjusted for gender and IQ, but unadjusted data used in meta-analysis.

145

Dowling et al., 2015; Missiuna et al., 2014; Piek et al., 2008; Pratt & Hill, 2011;

Schoemaker & Kalverboer, 1994; van den Heuvel et al., 2016; Wagner et al., 2012;

Watson & Knott, 2006). Six studies explicitly excluded DCD participants with ADHD

based on self-/parent-/school-reported diagnoses (Crane et al., 2017; Hill & Brown,

2013; Missiuna et al., 2014; Watson & Knott, 2006) or based on scores on standardised

screening questionnaires (Piek et al., 2007) or either of the two (Pratt & Hill, 2011). The

remaining studies either did not assess for ADHD (Campbell et al., 2012; Davis et al.,

2007; Francis & Piek, 2003; King-Dowling et al., 2015; Li et al., 2018; Piek et al., 2008;

Schoemaker & Kalverboer, 1994; Skinner & Piek, 2001; Wagner et al., 2012) or

measured symptoms but did not exclude those above the clinical cut-off (Chen et al.,

2009; Dewey et al., 2002; Harrowell et al., 2017; van den Heuvel et al., 2016; Wagner et

al., 2016).

All outcome measures of internalising symptoms were based on questionnaires.

Most studies measured overall internalising symptoms using the Child Behaviour

Checklist (Chen et al., 2009; Dewey et al., 2002; King-Dowling et al., 2015a), Strengths

and Difficulties Questionnaire (Crane et al., 2017; Harrowell et al., 2017; van den

Heuvel et al., 2016; Wagner et al., 2016), Behaviour Assessment System for Children

(BASC; Davis, Ford, Anderson, & Doyle, 2007), Teacher Report Form (van den Heuvel

et al., 2016), Kessler-6 (Li et al., 2018), or the Intelligence and Developmental Scales

(Wagner et al., 2012). Nine studies specifically measured depressive symptoms using

the Children’s Depression Inventory (Francis & Piek, 2003; Missiuna et al., 2014), Beck

Depression Inventory (Hill & Brown, 2013), Short Mood and Feelings Questionnaire

(Harrowell et al., 2017), BASC – Depression subscale (Campbell et al., 2012), Twin and

146

Sibling Questionnaire – Sad Affect subscale (Piek et al., 2007), or the Birleson

Depression Measure (Watson & Knott, 2006). Six studies specifically measured levels

of anxiety symptoms using the State-Trait Anxiety Inventory for Children (Schoemaker

& Kalverboer, 1994; Skinner & Piek, 2001), State-Trait Anxiety Inventory for Adults

(Hill & Brown, 2013), Screen for Child Anxiety Related Disorders (Missiuna et al.,

2014), or Spence Children's Anxiety Scale (Pratt & Hill, 2011). Overall, the outcome

measures were based on parent-report in seven studies (Chen et al., 2009; Dewey et al.,

2002; King-Dowling et al., 2015; Piek et al., 2007, 2008; Pratt & Hill, 2011; Wagner et

al., 2016; Wagner et al., 2012), teacher-report in two studies (Crane et al., 2017; van den

Heuvel et al., 2016), self-report in eleven studies (Campbell et al., 2012; Francis & Piek,

2003; Harrowell et al., 2017; Hill & Brown, 2013; Li et al., 2018; Schoemaker &

Kalverboer, 1994; Skinner & Piek, 2001; Watson & Knott, 2006), and a combination in

two studies (Davis et al., 2007; Missiuna et al., 2014).

Risk of bias

The risk of bias in the included studies is summarised in Table 2. Selection bias

was variable. The use of a population screening method in 16 studies ensured the DCD

sample was somewhat representative of the population studied. However, seven studies

recruited the DCD sample from a selective group or convenience sample, which may be

at greater risk of bias. This included children born very preterm or with extremely low

birth weight (Davis et al., 2007), volunteer samples from DCD support groups (Crane et

al., 2017; Hill & Brown, 2013; Pratt & Hill, 2011), monozygotic twin samples (Piek et

al., 2007), or clinical samples from occupational therapy services (Wagner et al., 2012;

147

Watson & Knott, 2006). In most studies, the TD group was drawn from the same

community (e.g. school, geographical location) as the DCD group, except for four

studies that were from a different source (Crane et al., 2017; Hill & Brown, 2013; Pratt

& Hill, 2011; Wagner et al., 2012) and thus had an increased risk from selection bias.

Additionally, while 10 studies confirmed diagnoses of DCD by independent assessment

or clinical reports (Chen et al., 2009; Crane et al., 2017; Harrowell et al., 2017; Hill &

Brown, 2013; Missiuna et al., 2014; Pratt & Hill, 2011; van den Heuvel et al., 2016;

Wagner, 2017; Watson & Knott, 2006), 13 did not confirm key diagnostic criteria

(Campbell et al., 2012; Davis et al., 2007; Dewey et al., 2002; Francis & Piek, 2003;

King-Dowling et al., 2015; Li et al., 2018; Piek et al., 2007, 2008; Schoemaker &

Kalverboer, 1994; Skinner & Piek, 2001; Wagner et al., 2016). Caution should be taken,

therefore, when attributing differences in internalising symptoms in these studies to

DCD. Most studies were cross-sectional and, therefore, unable to account for the

stability of internalising symptoms over time. Of the longitudinal studies, one controlled

for baseline internalising symptoms (Wagner et al., 2016).

The studies varied in the comparability of study groups and control for important

confounders. Age and gender were controlled in 11 studies through either matched

groups (Campbell et al., 2012; Francis & Piek, 2003; Piek et al., 2007; Schoemaker &

Kalverboer, 1994; Skinner & Piek, 2001; Wagner et al., 2012; Watson & Knott, 2006) or

adjusted analyses (Harrowell et al., 2017; Wagner et al., 2016). The study by Piek et al.

(2007) adopted a monozygotic twin design which also controls for a wide range of

genetic and shared environmental factors. The remaining studies failed to sufficiently

148

Table 2. Summary of risk of bias

Study DCD

representative of

population

TD from the

same population

DCD diagnosis

confirmed

Prior internalising

symptoms

controlled

Controls for

gender

Controls for age Standardised

outcome

measure

Sufficient

length of

follow-up

Sufficient

follow-up rate

Campbell et al. (2012, male) * *

* * *

Campbell et al. (2012, female) * *

* * *

Chen et al. (2009) * * * *

Crane et al. (2017) * *

Davis et al. (2007)

*

*

Dewey et al. (2002) * *

*

Francis and Piek (2003) * *

* * *

Harrowell et al. (2017, male) * * * * * * *

Harrowell et al. (2017, female) * * * * * * *

Hill and Brown (2013)

*

*

King-Dowling et al. (2015) * *

*

Li et al. (2018) * * *

Missiuna et al. (2014) * * *

*

Piek et al. (2007)

*

* * *

Piek et al. (2008) * *

*

Pratt and Hill (2011)

*

*

Schoemaker and Kalverboer (1994) * *

* * *

Skinner & Piek (2001, adolescent) * * * * *

Skinner & Piek (2001, child) * * * * *

van den Huevel (2016) * * *

*

Wagner et al. (2012)

* * * *

Wagner et al. (2016) * * * * * * *

Watson and Knott (2016)

* * * * *

149

control for age and gender. Although one such study did adjust for differences in gender

in the analysis (Piek et al., 2008), it also included intellectual ability as a covariate, and

so the unadjusted difference between the groups was used in the meta-analysis to ensure

comparability (Voils et al., 2011).

All studies utilised outcome measures with established validity and reliability

psychometrics. It should be noted that three studies only reported specific narrow-band

depression or anxiety subscales, as opposed to using the broad-band internalising scales

(Campbell et al., 2012; Piek et al., 2008). These might raise concerns around selective

reporting.

Finally, only three studies included a longitudinal follow-up (Harrowell et al.,

2017, male & female sample; Wagner et al., 2016). This was over a year in all three

studies. However, there were high rates of attrition in all three.

Internalising symptoms

Since only one study based on an adult sample was identified (Hill & Brown,

2013), that study was excluded from the remaining analyses to minimise heterogeneity.

Across the 22 studies with children and adolescents, those with DCD or probable DCD

were found to have higher levels of internalising symptoms than TD controls with a

medium effect size (g = 0.61; 95% CI: 0.48-0.74; see Figure 3 for forest plot). There was

significant moderate heterogeneity among the studies (I2 = 56%; χ2 = 47.84; p = 0.0007).

150

Figure 3. Forest plot for total internalising symptoms across all studies

151

Moderator analysis

The results of the moderator analyses are summarised in Table 3. The results

revealed that the effect size was significantly larger in studies that utilised a cross-

sectional design (versus longitudinal), that included a majority male sample in the DCD

group (versus majority female) and that recruited a selective or convenience sample of

participants (as opposed to population-based screening). There was also a trend (p = .05)

towards a greater effect size in studies that did not control for important confounders and

in studies that excluded individuals with a diagnosis of ADHD. No significant effect was

found for publication year, age, confirmation of DCD diagnosis, outcome respondent, or

type of internalising measure.

Sensitivity analysis

A sensitivity analysis was conducted to include only those studies meeting five

or more criteria on the NOS. A moderator analysis identified a significant difference

between the high-quality and low-quality studies (Q = 4.42; p = 0.04). Analysis of the

higher quality studies (k = 10) found a smaller, but still moderate, effect of DCD on

internalising symptoms (g = 0.46; 95% CI: 0.34 to 0.58). There was also no evidence of

significant heterogeneity among these ten studies (Q = 5.95; p = 0.55; I2 = 0%).

Publication bias

The funnel plot (see Figure 4) displayed some asymmetry, with smaller studies

tending to report larger effect sizes, possibly indicative of publication bias. Eggers test

was statistically significant, supporting the presence of publication bias (Egger’s bias =

152

Table 3. Summary of results for moderators

Moderator k Total n g 95% CI Q p

Year of publication

0.31 0.58

- Post-2010 12 3388 0.58 0.39 to 0.77

- Pre-2010 10 1074 0.65 0.49 to 0.81

Design

9.33 0.002

- Longitudinal 3 937 0.29 0.09 to 0.49

- Cross-sectional 20 3645 0.67 0.54 to 0.80

Age

0.02 0.88

- Included adolescents 10 2682 0.60 0.39 to 0.80

- Not included adolescents 12 1780 0.62 0.44 to 0.79

Gender

4.72 0.03

- >50% male 15 1889 0.71 0.52 to 0.91

- >50% female 7 2573 0.46 0.33 to 0.58

Confirmed diagnoses

2.30 0.13

- Confirmed DCD 9 998 0.75 0.48 to 1.01

- Probable DCD 13 3434 0.52 0.39 to 0.65

Population-based design

5.06 0.02

- Population screening 17 4176 0.52 0.41 to 0.62

- Selective sample 4 286 1.02 0.59 to 1.45

ADHD

3.70 0.05

- Excluded ADHD 5 379 0.97 0.53 to 1.41

- Did not exclude ADHD 17 4083 0.52 0.41 to 0.63

Controlled for confounding

3.81 0.05

- Age and gender controlled 12 1752 0.48 0.36 to 0.60

- Age and gender not controlled 10 2710 0.74 0.51 to 0.97

Outcome respondent a

2.18 0.14

- Self-report 10 1907 0.50 0.39 to 0.62

- Parent/teacher-report 12 2396 0.71 0.46 to 0.97

153

Outcome measure type

1.13 0.57

- Total internalising 12 3492 0.59 0.39 to 0.78

- Depression only 5 495 0.54 0.36 to 0.72

- Anxiety only 4 316 0.77 0.38 to 1.16

Sensitivity analyses

Study quality

4.42 0.04

- High quality 10 1638 0.46 0.34 to 0.58

- Low quality 12 2800 0.72 0.51 to 0.93

ADHD: Attention Deficit Hyperactivity Disorder.

a Missiuna et al. (2014) excluded from analysis due to using both self-and observer-report. Inclusion of each type of measure from

this study, independently, did not significantly change the results.

Figure 4. Funnel plot of effect sizes and standard error

154

2.38; 95% CI: 0.20 to 4.56; p = 0.02). However, Duval and Tweedie’s Trim and Fill

procedure did not impute additional studies and, therefore, the effect size adjusted for

publication bias was identical to the non-adjusted effect size. Rosenthal’s Fail-safe N,

suggested that the number of studies with null results that would have to be included to

produce a non-significant combined effect size is 1076. This is substantially larger than

the minimum required when applying Rosenthal’s (1979) formula (i.e. 120).

Discussion

The present systematic review and meta-analysis indicates that children and

adolescents with DCD or probable DCD experience greater levels of internalising

symptoms compared to their TD peers. The magnitude of this difference suggests a

moderate effect size, with individuals with DCD scoring over half a standard deviation

higher. This moderate effect, although reduced slightly, remained robust after excluding

lower quality studies. Publication bias is also unlikely to have substantially influenced

the result. Several methodological and participant factors that may moderate the

magnitude of this effect have also been identified.

DCD and internalising symptoms

The findings are in line with the emerging consensus that DCD can have a

significant impact on an individual’s mental health (Caçola, 2016; Mancini et al., 2016;

Missiuna & Campbell, 2014). Notably, the magnitude of the effect identified is

comparable, if not greater, than that found in meta-analyses of a wide range of chronic

155

physical health conditions including fibromyalgia, cleft lip and palate, migraine

sufferers, diabetes, spina bifida, and epilepsy (Pinquart & Shen, 2011a, 2011b).

The Environmental-Stress Hypothesis was proposed to account for this

relationship between DCD and internalising symptoms (Cairney, Rigoli, & Piek, 2013).

It suggests that the motor impairments in DCD can expose an individual to a variety of

secondary stressors, which over time can lead to poorer mental health. Although

potential mediators were not explored in this review, they have been outlined previously

(Mancini et al., 2016). They include peer victimisation (Campbell et al., 2012), reduced

leisure activities (Raz-Silbiger et al., 2015), impaired social skills (A. Wilson et al.,

2013), poorer self-esteem (Rigoli et al., 2012), physical inactivity (Li et al., 2018),

reduced social support (Rigoli et al., 2017), and lower perceived academic competence

(Lingam et al., 2012). Individuals with DCD may also experience impairments to

various cognitive abilities, including executive functions (Wilson, Ruddock, Smits-

Engelsman, Polatajko, & Blank, 2013) and social cognition (Cummins, Piek, & Dyck,

2005). This may further impact on self-regulation and mental wellbeing (Lantrip,

Isquith, Koven, Welsh, & Roth, 2016; Letkiewicz et al., 2014). Future meta-analyses

regarding the magnitude of the effects for these potential mediators will be important,

providing further opportunities for intervention.

Moderating factors

The present review has identified several methodological factors which might

moderate the degree to which DCD is associated with internalising symptoms. As

expected, the effect size was likely over-estimated in cross-sectional compared to

156

longitudinal studies, and in convenience or clinic-referred samples compared to samples

recruited via population-based screening. Such methodologies have less control of

confounding factors and a less representative selection of DCD participants (e.g. more

severe impairments in clinical samples). There was also a trend towards larger effect

sizes in studies that failed to control for age and gender. Again, the magnitude of the

effect sizes in these studies were likely inflated by confounding (Deeks et al., 2003). No

significant effect was found for the DCD criteria used. This suggests that, although

establishing all DCD diagnostic criteria is important for the quality of research in this

area (Zwicker et al., 2013), failing to do this might not have a substantial impact on the

results. Population-based screening, longitudinal design and control for confounders

should take priority.

Participant factors that might moderate the effect of DCD on internalising

symptoms were also identified. The effect was larger in studies with a majority male

sample. This would suggest that DCD has a greater impact on the mental health of males

and is in line with the findings of Sigurdsson et al. (2002). This is particularly important

given the prevalence of DCD may be greater in males (Kirby & Sugden, 2007;

Missiuna, 1994). It has been suggested that male children attribute greater value to

physical activity and sports compared to females, which might account for the larger

impact of DCD on their wellbeing (Poulsen, Ziviani, & Cuskelly, 2006; Poulsen,

Ziviani, Cuskelly, & Smith, 2007). However, although significant, the difference in

magnitude of the effect sizes were minimal. Additionally, only two of the included

studies reported direct comparisons of the impact of DCD on males and females, with

one suggesting no difference (Campbell et al., 2012) and the other suggesting a greater

157

impact for females (Harrowell et al., 2017). Regardless of which gender experiences the

larger effect, there is evidence that DCD can impact on the mental health of both and

perhaps it is the mechanisms by which this occurs that differ (Li et al., 2018).

There was also a trend towards larger effect sizes in studies that specifically

excluded participants with ADHD. This contradicts what might have been expected

from previous research (Martin, Piek, & Hay, 2006; Missiuna et al., 2014; Rasmussen &

Gillberg, 2000). One possible explanation for this finding is that children with comorbid

ADHD are more likely to be diagnosed and to subsequently receive support for their

difficulties (Heath, Toste, & Missiuna, 2005; Rivard, Missiuna, Hanna, & Wishart,

2011). Participants with DCD only, on the other hand, may have continued through

childhood for a long time with the motor difficulties going unrecognised and

unsupported (Gaines et al., 2008). However, it should also be noted that there were only

five studies included in the meta-analysis that specifically excluded participants with

ADHD. All five studies were also of a lower quality. It is a more plausible explanation

that methodological limitations inflated their combined effect size and, therefore,

caution should be taken when drawing any conclusions about the moderating effect of

comorbid ADHD.

Contrary to what might be expected, no significant moderating effect was found

for age. This is somewhat surprising, given that previous research has suggested the

impact of DCD on internalising symptoms may increase as children transition into

adolescence (Missiuna, Moll, King, King, & Law, 2007; Skinner & Piek, 2001).

However, only one study included in the present review reported separate outcomes for

adolescents and children. The moderator categories for the meta-analysis were based on

158

somewhat arbitrary criteria (i.e. studies that included adolescents in their sample, as

opposed to studies with a pure adolescent sample) which may have prevented the

detection of differences between the age groups.

Finally, no significant effect was found for the type of outcome measure or

respondent, suggesting that DCD may be associated with elevated levels of depression,

anxiety, and overall internalising symptoms, regardless of the person rating it.

Strengths and limitations

There are several limitations of this review that should be considered when

interpreting the findings. First, the quality of the included studies was variable. Most

studies were based on cross-sectional data only, which makes it difficult to establish

causality. Although three longitudinal studies were included, only one controlled for

baseline measures of internalising symptoms and all reported a high rate of attrition.

Many of the studies also failed to control for important confounders (i.e. age and gender)

and to establish all DCD diagnostic criteria.

The moderator analysis should also be interpreted with caution. As outlined

above, there were an insufficient number of studies within some of the moderator

categories to reliably explore their impact (including age and comorbid ADHD). Most of

the studies were also conducted in western, developed countries and, therefore,

generalisation to other countries is limited. Additionally, only one study with adults was

identified and this study failed to meet many of the quality criteria. Therefore, the extent

159

to which elevated internalising symptoms persist into adulthood in people with DCD is

unclear.

However, this review is the first attempt to systematically synthesise the

evidence on internalising symptoms in individuals with DCD and provide a pooled

summary of the effect size. Publication bias is unlikely to have a substantial impact on

the findings. Additionally, despite methodological limitations of the included studies,

potential moderating factors have been identified. The effect size also remained

substantial, and heterogeneity reduced, after excluding lower quality studies.

Implications and conclusion

Despite some limitations, the findings of this review have important clinical and

research implications. It can be concluded that individuals with DCD may have an

increased risk of developing elevated levels of internalising symptoms. The difference of

half a standard deviation between individuals with DCD and their peers could be

considered clinically important (Norman, Sloan, & Wyrwich, 2003). This would support

the practice of routine screening of mental health difficulties in individuals with DCD

and motor impairment. Given that DCD is poorly understood among professionals

(Gaines et al., 2008; B. N. Wilson et al., 2013) and that families often report difficulties

obtaining support (Stephenson & Chesson, 2008), such routine screening could be useful

across a range of services (including schools, occupational therapy, physical healthcare,

and mental healthcare). The findings also highlight the need for professionals in mental

health services to be aware of the disorder and how it impacts their patients.

Additionally, the findings support the need for the development of psychosocial

160

interventions for DCD with a focus on the secondary stressors that might mediate the

link between motor difficulties and emotional wellbeing (Missiuna et al., 2012).

Future research should focus on high-quality longitudinal studies to better

understand the causal link between DCD and internalising symptoms, including the role

of important mediators. It is recommended that studies include probability sampling

strategies and control for confounders and the stability of internalising symptoms over

time. This review has also highlighted the need for more research investigating mental

health in adults with DCD, especially given that the impact of DCD has been found to

continue into adulthood, including negative effects on higher education, employment

and mental wellbeing (Cousins & Smyth, 2003; Hill et al., 2011; Kirby, Williams,

Thomas, & Hill, 2013). Research investigating the effectiveness of routine screening for

mental health difficulties in DCD and psychosocial interventions would also provide

insight into the improved management of DCD. Given the major economic impact of

poor mental health (Trautmann, Rehm, & Wittchen, 2016) and the increasing focus on

improving psychological wellbeing in government policy (Department of Health, 2011),

the need to identify and support those individuals most at risk of mental health

difficulties is crucial.

References

American Psychiatric Association (2013). Diagnostic and statistical manual of mental

disorders, (5th edn.) Washington, DC: Author.

Blank, R., Smits-Engelsman, B., Polatajko, H., & Wilson, P. (2012). European Academy

for Childhood Disability (EACD): Recommendations on the definition, diagnosis

161

and intervention of developmental coordination disorder (long version).

Developmental Medicine & Child Neurology, 54(1), 54–93.

Borenstein, M., Hedges, L.V., Higgins, J.P.T., & Rothstein, H.R. (2009). Introduction to

Meta-Analysis. West Sussex, UK: Wiley.

Caçola, P. (2016). Physical and mental health of children with Developmental

Coordination Disorder. Frontiers In Public Health, 4, 224.

Cairney, J., Rigoli, D., & Piek, J. (2013). Developmental coordination disorder and

internalizing problems in children: The environmental stress hypothesis

elaborated. Developmental Review, 33(3), 224–238.

Cairney, J., & Veldhuizen, S. (2013). Is developmental coordination disorder a

fundamental cause of inactivity and poor health-related fitness in children?

Developmental Medicine & Child Neurology, 55, 55–58.

Cairney, J., Veldhuizen, S., & Szatmari, P. (2010). Motor coordination and emotional-

behavioral problems in children. Current Opinion in Psychiatry, 23(4), 324–329.

Campbell, W.N., Missiuna, C., & Vaillancourt, T. (2012). Peer victimization and

depression in children with and without motor coordination difficulties.

Psychology in the Schools, 49(4), 328–341.

Chen, H.F., & Cohn, E.S. (2003). Social participation for children with developmental

coordination disorder: Conceptual, evaluation and intervention considerations.

Physical & Occupational Therapy In Pediatrics, 23(4), 61–78.

Chen, Y.W., Tseng, M.H., Hu, F.C., & Cermak, S.A. (2009). Psychosocial adjustment

and attention in children with developmental coordination disorder using

different motor tests. Research in Developmental Disabilities, 30(6), 1367–1377.

162

Cousins, M., & Smyth, M.M. (2003). Developmental coordination impairments in

adulthood. Human Movement Science, 22(4–5), 433–459.

Crane, L., Sumner, E., & Hill, E.L. (2017). Emotional and behavioural problems in

children with Developmental Coordination Disorder: Exploring parent and

teacher reports. Research In Developmental Disabilities, 70, 67–74.

Cummins, A., Piek, J.P., & Dyck, M.J. (2005). Motor coordination, empathy, and social

behaviour in school-aged children. Developmental Medicine and Child

Neurology, 47(7), 437–442.

Damme, T.V., Simons, J., Sabbe, B., & van West, D. (2015). Motor abilities of children

and adolescents with a psychiatric condition: A systematic literature review.

World Journal of Psychiatry, 5(3), 315–329.

Davis, N.M., Ford, G.W., Anderson, P.J., & Doyle, L.W. (2007). Developmental

coordination disorder at 8 years of age in a regional cohort of extremely-low-

birthweight or very preterm infants. Developmental Medicine and Child

Neurology, 49(5), 325–330.

Deeks, J.J., Dinnes, J., D’Amico, R., Sowden, A.J., Sakarovitch, C., Song, F., Petticrew,

M., & Altman, D. (2003). Evaluating non-randomised intervention studies.

Health Technology Assessment, 7(27), 1–179.

Department of Health. (2011). No Health Without Mental Health: A Cross-Government

Mental Health Outcomes Strategy For People Of All Ages. Department of

Health: London, UK.

163

Dewey, D., Kaplan, B.J., Crawford, S.G., & Wilson, B.N. (2002). Developmental

coordination disorder: Associated problems in attention, learning, and

psychosocial adjustment. Human Movement Science, 21(5–6), 905–918.

Duval, S., & Tweedie, R. (2000). Trim and fill: A simple funnel-plot–based method of

testing and adjusting for publication bias in meta-analysis. Biometrics, 56(2),

455–463.

Eaton, N. R., Krueger, R. F., Markon, K. E., Keyes, K. M., Skodol, A. E., Wall, M., …

Grant, B. F. (2013). The structure and predictive validity of the internalizing

disorders. Journal of Abnormal Psychology, 122(1), 86–92.

Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis

detected by a simple, graphical test. BMJ, 315(7109), 629-634.

Francis, M. & Piek, J. (2003). The effects of perceived social support and self-worth on

depressive symptomatology in children with and without developmental

coordination disorder (DCD). Paper presented at the 38th APS Annual

Conference, Perth, Western Australia.

Gaines, R., Missiuna, C., Egan, M., & McLean, J. (2008). Educational outreach and

collaborative care enhances physician’s perceived knowledge about

Developmental Coordination Disorder. BMC Health Services Research, 8, 21–

21.

Gomez, A., Piazza, M., Jobert, A., Dehaene-Lambertz, G., Dehaene, S., & Huron, C.

(2015). Mathematical difficulties in developmental coordination disorder:

Symbolic and nonsymbolic number processing. Research in Developmental

Disabilities, 43–44, 167–178.

164

Harrowell, I., Hollén, L., Lingam, R., & Emond, A. (2017). Mental health outcomes of

developmental coordination disorder in late adolescence. Developmental

Medicine and Child Neurology, 59(9), 973–979.

Heath, N.L., Toste, J.R., & Missiuna, C. (2005). An exploration of the relationship

between motor impairment and emotional/behavioural difficulties amongst

children suspected of having DCD. Israeli Journal of Occupational Therapy, 14,

153–170.

Hedges, L., & Olkin, I. (1985). Statistical models for meta-analysis. Orlando, FL:

Academic Press.

Hill, E.L., & Brown, D. (2013). Mood impairments in adults previously diagnosed with

developmental coordination disorder. Journal of Mental Health, 22(4), 334–340.

Hill, E.L., Brown, D., & Sorgardt, K.S. (2011). A preliminary investigation of quality of

life satisfaction reports in emerging adults with and without Developmental

Coordination Disorder. Journal of Adult Development, 18(3), 130–134.

King-Dowling, S., Missiuna, C., Rodriguez, M.C., Greenway, M., & Cairney, J. (2015).

Co-occurring motor, language and emotional–behavioral problems in children 3–

6 years of age. Human Movement Science, 39, 101–108.

Kirby, A., & Sugden, D.A. (2007). Children with developmental coordination disorders.

Journal of the Royal Society of Medicine, 100(4), 182–186.

Kirby, A., Sugden, D., Beveridge, S., Edwards, L., & Edwards, R. (2008). Dyslexia and

developmental co-ordination disorder in further and higher education—

similarities and differences. Does the ‘Label’ influence the support given?

Dyslexia, 14(3), 197–213.

165

Kirby, A., Williams, N., Thomas, M., & Hill, E.L. (2013). Self-reported mood, general

health, wellbeing and employment status in adults with suspected DCD.

Research in Developmental Disabilities, 34(4), 1357–1364.

Kovacs, M., & Devlin, B. (1998). Internalizing disorders in childhood. The Journal of

Child Psychology and Psychiatry, 39(1), 47–63.

Lantrip, C., Isquith, P.K., Koven, N.S., Welsh, K., & Roth, R.M. (2016). Executive

function and emotion regulation strategy use in adolescents. Applied

Neuropsychology: Child, 5(1), 50–55.

Letkiewicz, A.M., Miller, G.A., Crocker, L.D., Warren, S.L., Infantolino, Z.P.,

Mimnaugh, K.J., & Heller, W. (2014). Executive function deficits in daily life

prospectively predict increases in depressive symptoms. Cognitive Therapy and

Research, 38(6), 612–620.

Li, Y.C., Kwan, M.Y., Clark, H.J., Hay, J., Faught, B.E., & Cairney, J. (2018). A test of

the environmental stress hypothesis in children with and without developmental

coordination disorder. Psychology of Sport and Exercise, 37, 244-250.

Lingam, R., Jongmans, M.J., Ellis, M., Hunt, L.P., Golding, J., & Emond, A. (2012).

Mental health difficulties in children with developmental coordination disorder.

Pediatrics, 129(4), e882–e891.

Mancini, V.O., Rigoli, D., Cairney, J., Roberts, L.D., & Piek, J.P. (2016). The elaborated

environmental stress hypothesis as a framework for understanding the

association between motor skills and internalizing problems: A mini-review.

Developmental Psychology, 7, 239.

166

Martin, N.C., Piek, J.P., & Hay, D. (2006). DCD and ADHD: A genetic study of their

shared aetiology. Human Movement Science, 25(1), 110–124.

Missiuna, C. (1994). Motor skill acquisition in children with Developmental

Coordination Disorder. Adapted Physical Activity Quarterly, 11(2), 214–235.

Missiuna, C., Pollock, N.A., Levac, D.E., Campbell, W.N., Whalen, S.D.S., Bennett,

S.M., Hecimovich C.A., Gaines, B.R., Cairney, J., & Russell, D.J. (2012).

Partnering for Change: An innovative school-based occupational therapy service

delivery model for children with developmental coordination disorder. Canadian

Journal of Occupational Therapy, 79(1), 41–50.

Missiuna, C., Cairney, J., Pollock, N., Campbell, W., Russell, D. J., Macdonald, K.,

Schmidt, L., Heath, N., Veldhuizen, S., & Cousins, M. (2014). Psychological

distress in children with developmental coordination disorder and attention-

deficit hyperactivity disorder. Research in Developmental Disabilities, 35(5),

1198–1207.

Missiuna, C., & Campbell, W. N. (2014). Psychological aspects of developmental

coordination disorder: Can we establish causality? Current Developmental

Disorders Reports, 1(2), 125–131.

Missiuna, C., Moll, S., King, S., King, G., & Law, M. (2007). A trajectory of troubles:

Parents’ impressions of the impact of developmental coordination disorder.

Physical & Occupational Therapy in Pediatrics, 27(1), 81–101.

Miyahara, M., & Piek, J. (2006). Self-esteem of children and adolescents with physical

disabilities: Quantitative evidence from meta-analysis. Journal of Developmental

and Physical Disabilities, 18(3), 219–234.

167

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The Prisma Group. (2009).

Preferred reporting items for systematic reviews and meta-analyses: The

PRISMA Statement. PLOS Medicine, 6(7), e1000097.

Norman, G., Sloan, J., & Wyrwich, K. (2003). Interpretation of changes in health-related

quality of life: the remarkable universality of half a standard deviation. Medical

Care, 41(5), 582–592.

Pearsall-Jones, J. G., Piek, J. P., Rigoli, D., Martin, N. C., & Levy, F. (2011). Motor

disorder and anxious and depressive symptomatology: A monozygotic co-twin

control approach. Research in Developmental Disabilities, 32(4), 1245–1252.

Piek, J. P., Bradbury, G. S., Elsley, S. C., & Tate, L. (2008). Motor coordination and

social–emotional behaviour in preschool‐aged children. International Journal of

Disability, Development and Education, 55(2), 143–151.

Piek, J.P., Rigoli, D., Pearsall-Jones, J.G., Martin, N.C., Hay, D.A., Bennett, K.S., &

Levy, F. (2007). Depressive symptomatology in child and adolescent twins with

attention-deficit hyperactivity disorder and/or developmental coordination

disorder. Twin Research and Human Genetics, 10(04), 587–596.

Pieters, S., De Block, K., Scheiris, J., Eyssen, M., Desoete, A., Deboutte, D., …

Roeyers, H. (2012). How common are motor problems in children with a

developmental disorder: rule or exception? Child: Care, Health and

Development, 38(1), 139–145.

Pinquart, M., & Shen, Y. (2011a). Anxiety in children and adolescents with chronic

physical illnesses: A meta‐analysis. Acta Paediatrica, 100(8), 1069–1076.

168

Pinquart, M., & Shen, Y. (2011b). Depressive symptoms in children and adolescents

with chronic physical illness: An updated meta-analysis. Journal of Pediatric

Psychology, 36(4), 375–384.

Poole, K.L., Schmidt, L.A., Missiuna, C., Saigal, S., Boyle, M.H., & Van Lieshout, R.J.

(2016). Childhood motor coordination and adult psychopathology in extremely

low birth weight survivors. Journal of Affective Disorders, 190, 294–299.

Poulsen, A.A., Ziviani, J.M., & Cuskelly, M. (2006). General self-concept and life

satisfaction for boys with differing levels of physical coordination: The role of

goal orientations and leisure participation. Human Movement Science, 25(6),

839–860.

Poulsen, A.A., Ziviani, J.M., Cuskelly, M., & Smith, R. (2007). Boys with

developmental coordination disorder: Loneliness and team sports participation.

American Journal of Occupational Therapy, 61(4), 451–462.

Pratt, M.L., & Hill, E.L. (2011). Anxiety profiles in children with and without

developmental coordination disorder. Research in Developmental Disabilities,

32(4), 1253–1259.

Rasmussen, P., & Gillberg, C. (2000). Natural outcome of ADHD with developmental

coordination disorder at age 22 years: A controlled, longitudinal, community-

based study. Journal of the American Academy of Child & Adolescent

Psychiatry, 39(11), 1424–1431.

Raz-Silbiger, S., Lifshitz, N., Katz, N., Steinhart, S., Cermak, S.A., & Weintraub, N.

(2015). Relationship between motor skills, participation in leisure activities and

169

quality of life of children with Developmental Coordination Disorder: Temporal

aspects. Research in Developmental Disabilities, 38, 171–180.

Rigoli, D., Kane, R.T., Mancini, V., Thornton, A., Licari, M., Hands, B., McIntyre, F.,

& Piek, J. (2017). The relationship between motor proficiency and mental health

outcomes in young adults: A test of the Environmental Stress Hypothesis.

Human Movement Science, 53, 16–23.

Rigoli, D., Piek, J.P., & Kane, R. (2012). Motor coordination and psychosocial

correlates in a normative adolescent sample. Pediatrics, 129(4), e892–e900.

Rivard, L.M., Missiuna, C., Hanna, S., & Wishart, L. (2011). Understanding teachers’

perceptions of the motor difficulties of children with developmental coordination

disorder (DCD). British Journal of Educational Psychology, 77(3), 633–648.

Rosenthal, R. (1979). The file drawer problem and tolerance for null results.

Psychological Bulletin, 86(3), 638.

Sanderson, S., Tatt, I.D., & Higgins, J.P. (2007). Tools for assessing quality and

susceptibility to bias in observational studies in epidemiology: A systematic

review and annotated bibliography. International Journal of Epidemiology,

36(3), 666–676.

Schoemaker, M.M., & Kalverboer, A.F. (1994). Social and affective problems of

children who are clumsy: How early do they begin? Adapted Physical Activity

Quarterly, 11(2), 130–140.

Sigurdsson E, van Os J, Fombonne E, Sigurdsson, E., Van Os, J., & Fombonne, E.

(2002). Are impaired childhood motor skills a risk factor for adolescent anxiety?

170

Results from the 1958 U.K. birth cohort and the National Child Development

Study. American Journal of Psychiatry, 159(6), 1044–1046.

Skinner, R.A., & Piek, J.P. (2001). Psychosocial implications of poor motor

coordination in children and adolescents. Human Movement Science, 20(1–2),

73–94.

Stephenson, E.A., & Chesson, R.A. (2008). ‘Always the guiding hand’: Parents’

accounts of the long-term implications of developmental co-ordination disorder

for their children and families. Child: Care, Health and Development, 34(3),

335–343.

Stroup, D.F., Berlin, J.A., Morton, S.C., Olkin, I., Williamson, G.D., Rennie, D., Moher,

D., Becker, B.J., Sipe, T.A., Thacker, S.B. (2000). Meta-analysis of

observational studies in epidemiology: a proposal for reporting. Meta-analysis Of

Observational Studies in Epidemiology (MOOSE) group. JAMA, 283(15), 2008–

2012.

Trautmann, S., Rehm, J., & Wittchen, H.U. (2016). The economic costs of mental

disorders. EMBO Reports, 17(9), 1245–1249.

Tseng, M.H., Howe, T.H., Chuang, I.C., & Hsieh, C.L. (2007). Cooccurrence of

problems in activity level, attention, psychosocial adjustment, reading and

writing in children with developmental coordination disorder. International

Journal of Rehabilitation Research, 30(4), 327–332.

Twenge, J.M., & Nolen-Hoeksema, S. (2002). Age, gender, race, socioeconomic status,

and birth cohort differences on the children’s depression inventory: A meta-

analysis. Journal of Abnormal Psychology, 111(4), 578–588.

171

van den Heuvel, M., Jansen, D.E.M.C., Reijneveld, S.A., Flapper, B.C.T., & Smits-

Engelsman, B.C.M. (2016). Identification of emotional and behavioral problems

by teachers in children with developmental coordination disorder in the school

community. Research in Developmental Disabilities, 51–52, 40–48.

Voils, C.I., Crandell, J.L., Chang, Y., Leeman, J., & Sandelowski, M. (2011).

Combining adjusted and unadjusted findings in mixed research synthesis.

Journal of Evaluation in Clinical Practice, 17(3), 429–434.

Wagner, M. (2017). Considerations on the assessment of developmental coordination

disorder and the elaboration of related contextual pathways. Developmental

Medicine & Child Neurology, 59(9), 891–892.

Wagner, M., Jekauc, D., Worth, A., & Woll, A. (2016). Elaboration of the

environmental stress hypothesis-results from a population-based 6-year follow-

up. Frontiers in Psychology, 7, 1904.

Wagner, M., Bös, K., Jascenoka, J., Jekauc, D., & Petermann, F. (2012). Peer problems

mediate the relationship between developmental coordination disorder and

behavioral problems in school-aged children. Research in Developmental

Disabilities, 33(6), 2072–2079.

Watson, L., & Knott, F. (2006). Self-esteem and coping in children with developmental

coordination disorder. British Journal of Occupational Therapy, 69(10), 450–

456.

Wells, G.A., Shea, B., O’connell, D., Peterson, J., Welch, V., Losos, M., & Tugwell, P.

(2011). The Newcastle-Ottawa Scale (NOS) for assessing the quality of

172

nonrandomised studies in meta-analyses. Retrieved May 10, 2018, from

http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp.

Wilson, A., Piek, J.P., & Kane, R. (2013). The mediating role of social skills in the

relationship between motor ability and internalizing symptoms in pre-primary

children. Infant and Child Development, 22(2), 151–164.

Wilson, B.N., Neil, K., Kamps, P.H., & Babcock, S. (2013). Awareness and knowledge

of developmental co-ordination disorder among physicians, teachers and parents.

Child: Care, Health and Development, 39(2), 296–300.

Wilson, P.H., Ruddock, S., Smits-Engelsman, B., Polatajko, H., & Blank, R. (2013).

Understanding performance deficits in developmental coordination disorder: A

meta-analysis of recent research. Developmental Medicine and Child Neurology,

55(3), 217–228.

Zwicker, J.G., Harris, S.R., & Klassen, A.F. (2013). Quality of life domains affected in

children with developmental coordination disorder: A systematic review. Child:

Care, Health and Development, 39(4), 562–580.

173

Appendix: Guidelines for authors

[Appendix removed for E-Thesis submission]

174

Part 3: Summary of Clinical Experience

Adult placement

Service: Community Mental Health Team

Dates: October 2015 – September 2016

Experience: Conducting psychological assessments and interventions with adults

presenting with a range of mental health difficulties. I predominantly worked within a

Cognitive-Behavioural Therapy (CBT) model. This included CBT for depression,

generalised anxiety disorder, social anxiety, obsessive compulsive disorder, health

anxiety and panic disorder. I gained experience applying third-wave CBT models (e.g.

Acceptance and Commitment Therapy) in one-to-one sessions and facilitating a

Dialectical Behaviour Therapy (DBT) group for people diagnosed with borderline

personality disorder. I gained some experience administering neuropsychological tests. I

also conducted a service evaluation of a multidisciplinary referrals meeting.

Child and adolescent placement

Service: Tier 2 Child and Adolescent Mental Health Team

Dates: October 2016 – March 2017

Experience: Working within a Choice and Partnership Approach to conduct

psychological assessments and intervention with young people presenting with mild-

moderate mental health difficulties and their families. I predominantly worked within

the CBT model with some experience applying systemic models. Presenting concerns

included depression, anxiety and behavioural difficulties. I gained experience working

175

with young people with Attention Deficit Hyperactivity Disorder and Autism Spectrum

Conditions. I facilitated a CBT group for anxiety. I administered neuropsychological

tests. I had the opportunity to conduct consultation work for local schools and provided a

teaching session to health professionals on Developmental Coordination Disorder.

Older people placement

Service: Memory Assessment Service

Dates: April 2017 – September 2017

Experience: Conducting detailed cognitive assessments and formulations with adults

presenting with possible dementia. I gained experience administering and scoring a

range of neuropsychological tests and working within a neurocognitive model to assist

with diagnosis. I delivered brief interventions with people adjusting to a recent diagnosis

of dementia and their carers. This included one-to-one, family, and group sessions

focused on psychoeducation, CBT, systemic therapy, neurorehabilitation, and cognitive

stimulation therapy. Presenting diagnoses included Alzheimer’s disease, vascular

dementia, frontotemporal dementia, Lewy-bodies dementia, Parkinson’s disease,

progressive supranuclear palsy, and mild cognitive impairment. I also delivered a

training session to the multidisciplinary team on delivering a diagnosis of dementia.

People with Learning Disabilities placement

Service: Community Team for People with Learning Disabilities

Dates: October 2017 – March 2018

176

Experience: Adapting psychological models and interventions for adults with a learning

disability. This included working within an integrated framework, informed by CBT,

systemic, neurocognitive, and behavioural models. Presenting concerns included low

mood, anxiety, anger, and behaviours that challenge. I gained experience conducting

functional assessments and developing Positive Behaviour Support plans to help clients

and their carers manage challenging behaviours. I gained experience with consultation

and joint working with other professionals. I also conducted relaxation groups within an

inpatient service. I had the opportunity to supervise assistant psychologists.

Specialist placement: Neuropsychology

Service: Epilepsy neuropsychology outpatients / inpatient acute traumatic brain injury

Dates: April 2018 – September 2018

Experience: Conducting neuropsychological assessment with people with a diagnosis of

epilepsy. This included individuals concerned by cognitive difficulties or as part of a

presurgical screening assessment. I gained experience working within the

neurocognitive model and writing detailed neuropsychological reports. I also worked in

an inpatient acute neurorehabilitation service for people with a traumatic brain injury. I

gained experience with neuropsychological assessment; delivering brain injury

education groups; working with families; conducting mood assessments and

intervention; delivering insight-raising interventions; and introducing cognitive

rehabilitation strategies. I obtained experience working closely with other healthcare

professionals, taking on a leadership role within the team, and supervising assistant

psychologists.

177

Part 4: Table of Assessments Completed During Training

Year I Assessments

ASSESSMENT TITLE

WAIS WAIS Interpretation (online assessment)

Practice Report of

Clinical Activity

A cognitive-behavioural assessment and initial

formulation of a female in late adolescence experiencing

anxiety, low mood, and non-epileptic seizures

Audio Recording of

Clinical Activity with

Critical Appraisal

Audio recording and critical appraisal of a Cognitive

Behaviour Therapy session with a male with depression

and social anxiety

Report of Clinical

Activity N=1

A cognitive-behavioural assessment and intervention for

a man in his twenties experiencing depression and social

anxiety

Major Research Project

Literature Survey

Mental health in Developmental Coordination Disorder:

Literature Survey

Major Research Project

Proposal

Executive function and internalizing problems in

children with and without Developmental Coordination

Disorder

Service-Related Project Clinicians’ views on a weekly meeting dedicated to

discussing new referrals in a Community Mental Health

& Recovery Service

Year II Assessments

ASSESSMENT TITLE

Report of Clinical

Activity/Report of

Clinical Activity –

Formal Assessment

A neuropsychological assessment of a male in his mid-

teens, presenting with academic and behavioural

difficulties at school

PPLD Process Account A reflective process account of a trainee’s experiences of

a Personal and Professional Development group during

the first two years of training

Year III Assessments

ASSESSMENT TITLE

Presentation of Clinical

Activity

A post-diagnostic intervention for a woman in her 70’s

recently diagnosed with vascular dementia: A cognitive-

behavioural and systemic approach

178

Major Research Project

Literature Review

Internalising symptoms in Developmental Coordination

Disorder: A systematic review and meta-analysis

Major Research Project

Empirical Paper

Internalising symptoms and executive function

difficulties in adolescents with and without

Developmental Coordination Disorder

Report of Clinical

Activity/Report of

Clinical Activity –

Formal Assessment

An assessment and intervention with a man with learning

disabilities and a cavernous haemangioma presenting

with challenging behaviour: A positive behavioural

support approach

Final Reflective

Account

On becoming a clinical psychologist: A retrospective,

developmental, reflective account of the experience of

training