ABSTRACT
Background: As part of the process of creating an update of the clinical practice guidelines for developmental coordination disorder (DCD) (Blank, Smits-Engelsman, Polatajko, & Wilson, 2012), a systematic review of intervention studies, published since the last guidelines statement was conducted.
Aim: The aim of this study was to
1) systematically review the evidence published from January 2012 to February 2017 regarding the effectiveness of motor based interventions in individuals with DCD,
2) quantify treatment effects using a meta-analysis,
3) examine the available information on different aspects of delivery including use of group intervention, duration and frequency of therapy, and
4) identify gaps in the literature and make recommendations for future intervention research.
Method: An electronic search of 5 databases (PubMed, Embase, Pedro, Scopus and Cochrane) was conducted for studies that evaluated motor-based interventions to improve performance for individuals with DCD.
Results: Thirty studies covering 25 datasets were included, 19 of which provided outcomes on standardized measures of motor performance. The overall effect size (Cohen’s d) across intervention studies was large (1.06), but the range was wide: for 11 interventions, the observed effect was large (>0.80), in eight studies moderate (>0.50), and in five it was small or negligible (<0.50).
Positive benefits were evident for activity-oriented approaches, body function-oriented combined with activities, active video games, and small group programs. Conclusion: Results showed that activity-oriented and body function oriented interventions can have a positive effect on motor function and skills. However, given the varied methodological quality and the large confidence intervals of some studies, the results should be interpreted with caution.
1. Introduction
Developmental Coordination Disorder (DCD) is one of the most common movement disorders of childhood and a condition that most children do not out-grow (Cantell, Kooistra, Cermak, & Larkin, 2002; Hill, Brown, & Sorgardt, 2011; Kirby, Williams, Thomas, & Hill, 2013; Losse et al., 1991; Geuze & Borger, 1993; Cantell, Smyth, & Ahonen, 1994).
DCD is associated with a range of motor, cognitive, social and psychological issues that negatively affect everyday function (Hay, Hawes, & Faught, 2004; Venetsanou et al., 2011; Wilson,Ruddock,Smits Engelsman, Polatajko, & Blank, 2013; Wilson et al., 2017). These facts underscore the need for effective intervention to enhance motor skills and the ability to function in everyday life (Au et al., 2014). As part of the process of creating new clinical practice guideline for DCD (Blank, Smits-Engelsman, Polatajko, & Wilson, 2012), a prior systematic review of DCD intervention studies published between 1995 and 2011 was conducted.
In that review (Smits-Engelsman et al., 2013),we concluded that task oriented approaches were most beneficial on functional outcomes. We noted, however, that few randomized controlled trials (RCTs) were available. Other issues at that time were a need for stricter application of DSM (Diagnostic and Statistical Manual of Mental Disorders) criteria and consistency in the terms used to describe participants (Geuze, Schoemaker, & Smits-Engelsman, 2015).
Five years later, we present here an update as part of the 5-yearly revision required by Guidelines International Network of the clinical practice guideline for DCD. The main aim of this paper is to present the results of a systematic evaluation of new evidence on the effectiveness of interventions.
1.1. Description of the condition
By definition, children with DCD show characteristic difficulties in performing fine- and/or gross-motor skills to the level of their peers, and exhibit performance difficulties in the tasks of everyday living (American Psychiatric Association, 2013). In the language of the International classification of functioning, disability and health (ICF; WHO, 2001) DCD is manifest in the area of body function and structure (e.g., motor control processes, Blank et al., 2012), activity, and participation (Cairney & Veldhuizen, 2013).
A prevalence rate of around 5–6% for DCD is not trivial in school-aged children, with a somewhat higher incidence in boys than girls (Cairney, Hay, Faught, & Hawes, 2005; Lingam et al., 2010; Missiuna, Gaines, Soucie, & McLean, 2006; Venetsanou et al., 2011). Critically, nearly half of those diagnosed in early childhood continue to have difficulties into adolescence and early adulthood (Kirby et al., 2013). In addition, children with DCD frequently experience a range of comorbid problems including attentional issues (viz Attention Deficit Hyperactivity Disorder– ADHD), behavioral issues, language, and psychosocial problems including anxiety, depression and low self-esteem.
In general, the higher the severity of DCD and the more comorbid issues, the poorer the outcome (Peters, Barnett, & Henderson, 2001). Poor motor coordination also results in reduced physical activity participation and lower fitness outcomes in populations with DCD( Rivilis et al., 2011; Schott, Alof, Hultsch, & Meermann, 2007). Consequently, the risk of developing obesity and cardiovascular diseases is increased (Faught, Hay, Cairney,&Flouris,2005; Cantell & Crawford 2008). This cluster of developmental problems and the persistent nature of DCD show the importance of intervention that enhances activity and supports participation (Smits-Engelsman et al., 2013; Smits-Engelsman, Magalhaes, Oliveira, & Wilson, 2015; Wilson et al., 2013).
1.2. Description of the interventions
There have been numerous activity based approaches to intervention for DCD (Miyahara, Hillier, Pridham, & Nakagawa, 2017; Smits-Engelsman et al., 2013; Wilson et al., 2013), traditionally grouped into two broad areas: those that use activity to target the underlying performance problems, often referred to as process oriented approaches, and, those that use activity to address the performance itself, often referred to as task oriented approaches. In the review published in 2013, it was observed that task-oriented approaches were more efficient than process oriented, yielding better functional performance outcomes in less time for children with DCD (Smits-Engelsman et al., 2013).
Task oriented interventions are activity oriented but also clearly facilitate participation. Characteristics of task oriented intervention are:
1. Client-centred (meaningful for the client)
2. Goal oriented: Aiming at activities and participation as described in the ICF-Child and Youth (WHO, 2007).
3. Task and context specific
4. Involve active role of the client
5. Aimed at functionality not at normality
6. Aimed at active involvement of parent(s)/caretakers to enable transfer of learning to the everyday context.
In the earlier stages of DCD research, intervention approaches were almost exclusively process oriented or in ICF terms, focused on reducing impairment and improving body function and structure (Smits-Engelsman et al., 2013). These approaches were primarily medical or rehabilitative, and attempted either to prevent or ameliorate limitations in body function and structure by correcting or modifying them or by increasing capacity levels. Studies examining these approaches tended to report on changes at the level of body function and structure only.
However, more recently, studies of body function-oriented interventions have started to report on changes at the level of activity, and occasionally on participation. Similarly task oriented approaches, which tended to report only on changes at the level of activity and participation, have begun to broaden their scope by including outcomes related to body function and structure (Jelsma et al., 2014; Farhat et al., 2015).
A recent Cochrane review by Miyahara et al. (2017) was notable for targeting all available RCTs that evaluated task-oriented interventions specifically, regardless of publication date. Adhering to very strict inclusion criteria and fairly rigorous methodology, only 15 eligible studies were included (eight RCTs and seven quasi-RCTs), some dating back to 2000; of the total sample, only six were published after 2011. The main meta-analysis (involving six studies) showed a moderately positive effect on movement difficulties. The remaining nine studies were not combined for meta-analysis due to incomplete data or marked differences in the intervention per se.
The main issue with Miyahara’s review is that a large body of the evaluation literature (both RCT and Controlled Clinical Trials; CCTs) is not captured, especially the many studies published since 2011. If the concern is methodological quality, then rating all studies on their risk of bias can accommodate this. In any case, well-designed CCTs with high levels of evidence are important when evaluating new approaches to treatment. Large RCTs are not always possible or feasible, depending on the stage of research. Moreover, with a larger sample of studies, corroborating results from the same or very similar interventions can provide evidence of consistency, reducing the chance of spurious findings.
In short, an updated review of DCD intervention is needed to provide a comprehensive critique of the current body of work that provides direction for researchers and clinicians alike. To represent shifts in treatment approaches over recent years, we describe interventions reviewed here using the ICF terminology (WHO, 2007). Specifically, we describe interventions based on the level of the ICF that is the primary target of the intervention. This is a significant strength in methodology, allowing researchers and clinicians to interpret results within a broad and accessible conceptual framework. Interventions are identified as follows:
(i) body function and structure (BF) oriented, where the activity engaged in is designed to improve targeted body functions considered to underlie the reported functional motor problem;
(ii) activity oriented where the activity engaged in is designed to improve performance in that activity; and
(iii) participation oriented, where the activity engaged in is designed to improve participation in that activity in an everyday life situation.
In interventions identified as Activity- or Participation-oriented, the primary interest is to improve performance of particular activities or participation and the content of the intervention involves direct training of the skill concerned. Let us use the example. If stringing beads is used as an activity during intervention with the primary goal to improve eye hand coordination in a child with handwriting difficulties, it would be called BF oriented. In contrast, if in another child the goal of stringing beads were to improve the skill itself, it would be called an activity oriented intervention. If, to take it one step further, the goal were for the child to become better at stringing beads so he can make decorations with his friends it would be called activity and participation oriented.
1.3. Objectives
The core objective was to examine up to date evidence regarding motor-based intervention for individuals with DCD. More specifically, the review aimed to
(1) describe new evidence (between January 2012-February 2017) regarding the effectiveness of interventions focusing on motor skills or on tasks relevant for everyday life or for improving general fitness and motor proficiency for DCD,
(2) evaluate the level of evidence for each of these intervention approaches,
(3) examine the available information on different aspects of delivery including use of group intervention, duration and frequency of therapy, and suitability for key groups (e.g., children of different ages, socioeconomic status, and with co-occurring conditions);
(4) identify gaps in the literature and make recommendations for future intervention research.
2. Review methods
2.1. Search strategy for identification of studies
A systematic literature search of DCD-related studies was undertaken to identify eligible intervention studies for review. We identified studies from January 2012 up to February 2017 using electronic databases and the reference lists of retrieved studies.
If needed, we contacted authors for additional information. A primary search of the biomedical literature was performed using PubMed and Cochrane databases with appropriate headings and keywords related to intervention for individuals with DCD. We adapted the search strategy developed for PubMed for use in the other electronic databases (Embase, Pedro, and Scopus). The combinations of search terms are shown in Table S1.
2.1.1. Inclusion criteria
Initially, any study reporting new data on the motor outcomes of intervention for children or adults with DCD (or those labeled probable-DCD) was selected for review. This included: randomized clinical trials, controlled clinical trials, case-control studies, cohort studies, longitudinal studies, and single-case experimental design studies.
Studies were first read as abstracts only. From this initial pool, we selected any intervention study that aimed to improve motor functions, activities and/or participation outcomes. We included studies regardless of the type of intervention or delivery mode (one to one or group). All included studies were available as full-text articles. Review papers were handled separately and used for comparison purpose in the discussion.
2.1.2. Exclusion criteria
Studies published in languages other than English were excluded. We also excluded studies that reported only cognitive or physiological outcomes (e.g., motor control processes and brain-related activity such as event-related potentials—ERPs).
2.1.3. Types of outcome measure
The ICF was used as a framework for classifying outcomes addressing activity or skill improvement, which has been the primary focus of intervention research for many years. To enhance the quality of the systematic review, we focused on validated and reliable measures to improve the comparability of the effects between studies. The most common measures found to be used were the Movement Assessment Battery for Children Test first or second edition (MABC-1or−2), the Bruininks-Oseretsky Test of Motor Proficiency first or second edition (BOT-1or−2), or agility and functional fitness tasks (i.e., everyday tasks like running and jumping, stair climbing or cycling); we classified these as activity level measures.
We also found outcome measures that could be classified at the level of body function (e.g., postural sway, heart rate or maximum oxygen consumption) and participation (e.g., participation in daily living activities, sport and recreation). In these classifications, the outcome measures were more diverse (See also Table 2 for all outcome measures).
Abbreviations: 6-MWT: 6-min walk test; 10-MWT: 10-min walk test; ADHD: Attention deficit hyperactivity disorder; AVG: active video games; BOT(-2): Bruininks-Oseretsky Test of Motor Proficiency(-2); BV-COS: Battery for assessment of writing skills; CAPE: Children’s Assessment of Participation and Enjoyment; CCT: controlled clinical trial; ChAS: Children Activity Scale; CO-OP: Cognitive Orientation to (Daily) Occupational Performance; COPM: Canadian Occupational Performance Measure; CPET: Cardiopulmonary exercise test; CSAPPA: Children’s Self-Perceptions of Adequacy in and Predilection for Physical Activity Scale; CSHQ: Children’s Sleep Habits Questionnaire Chinese version; CSQ: Coordination Skills Questionnaire;
DCD: Developmental Coordination Disorder; DCD-Q: DCD-questionnaire; DSM-5: Diagnostic and Statistical Manual of Mental Disorders 5th edition; ERP: Event-related potential; FSM: Functional Strength Measure; GAS: Goal Attainment Scale; GSE: Global Self-Esteem; HHD: Hand-held dynamometer; HHP: Health Promotion Program; HPT: Handwriting Performance Test; HST: Handwriting Speed Test; HTP: Handwriting Task Program; MABC(-2): Movement Assessment Battery for Children(-2); MCT: motor control test for reactive balance control; MIT: motor imagery training; MPST: Muscle Power Sprint Test; NA: Not available; NAG: no-active video games; NCT: non-control trial;
NTT: Neuromotor Task Training; PAC: Preferences for Activities of Children; PACER: Progressive Aerobic Cardiovascular Endurance Running; PCERT: Pictorial Children’sEffort Rating Table; PE: physical education; PEGS: Perceived Efficacy and Goal Setting system; PMC: Perceived Motor Competence; PMT: Perceptual-motor therapy; PSDQ: Physical Self-Descriptive Questionnaire; RCT( CO): randomized-control trial (cross over); SCAS: Spence’s Child Anxiety Scale; SDQ: Strengths and Difficulties Questionnaire;
SISST: Sensory Input Systems Screening Test; SOT: Sensory Organization Test; SPC: self-perceived physical competence; SPPC: Self Perception Profile for Children; TBCT: trampoline balance circuit training; TD: typical development; TGMD-2: Test of Gross Motor Development-2nd Edition; PSDQ: Physical Self-Descriptive Questionnaire; QNST-2: Quick Neurological Screening Test 2; UST: Unilateral Stance Test; VMI: Visual-Motor Integration Test.GH.
2.2. Data extraction and assessment of study validity
2.2.1. Selection of studies
Two review authors (BSE and VQ) independently screened titles and abstracts for potential inclusion from the literature searches and coded them as either ‘retrieve' (eligible or potentially eligible/unclear) or ‘do not retrieve' (clearly not eligible). To avoid any conflict of interest due to authorship, we had two separate teams rate studies and extract data (SV/HP and BSE/VQ).
Each pair of reviewers independently screened each retrieved, eligible full-text publication (based on abstract) and recorded reasons for each “not retrieve” study. Any disagreement was resolved through discussion. Where a common dataset was reported in two or more separate papers, study information (like sample size) was pooled across papers. We recorded the selection process and summarized the information in a PRISMA flow diagram (Moher et al., 2009; See Fig. 1). The two pairs of review authors (BCM/VQ and SV/HP) independently extracted data from the included studies (number of participants, sex ratio, DSM criteria used, diagnostic tests and cut off used, means and SD on the outcomes).
2.2.2. Strength of evidence
The following three parameters were used to determine the strength of evidence for a given intervention approach:
(1) the quality of individual studies,
(2) quantity of studies, and
(3) consistency of outcomes across all reviewed studies.
(1) Study Quality. The quality of individual studies (or Level of Evidence—LOE) was assessed in two steps:
first, the integrity of design features, and
second, a rating of the risk of bias that may have contributed to an outcome. To rate the quality of the study design, we used a revised grading system for recommendations in evidence-based guidelines, which not only takes the design but also the risk of bias into account (See Table 1 adapted from Research System Agency for Health Care Policy; Harbour & Miller, 2001).
Since many of the studies in this review were clinical studies without randomization, we added the term, controlled clinical trial to the rating pro forma to denote non-randomized studies comparing two interventions, or comparing intervention and non-intervention groups of children with DCD. Each study was reviewed for risk of bias by at least two experts in the field (BSE, RB, VQ, HP, SV, PW) who independently rated and assigned a 1, 2 or 3 for design quality using the modifiers shown in Table 1 (adding + or − signs to the rating), which is further explained in Tables 3a and 3b.
Disagreements between raters were discussed and resolved through consensus involving a third rater. For randomized controlled trials, low overall risk of bias was determined when there was random sequence generation and blinded outcome assessment, and no other items had a high risk of bias. Since it was not possible to keep training personnel blind to the motor intervention, this aspect of design did not contribute to the risk scores. For the case-control studies and controlled clinical trials, we re-worded items 1–3 of Table 1 and rating scale (see Table 3b).
A potential selection bias in DCD research concerns whether or not children are referred for treatment by a professional clinician. This issue presents a possible confound when studies are compared (Geuze et al., 2015) and may hamper generalization of the results. For this reason, referral source was examined. In addition, we recorded how (non-DCD) children were assessed as being typically developing. Overall, studies that met 4 or fewer of the 7 criteria or had a serious flaw were rated as having high risk of bias.
(2) Study Quantity. The second parameter used to determine strength of the evidence was quantity, defined by the number of studies of a given type, and the number and type of participants included in those studies (See Tables 2 and 4).
(3) Consistency of Outcomes. The final parameter, consistency, was the extent to which findings are similar between different studies of the same type of intervention. We rated consistency as high when most studies (>50%) found similar or at least coherent results, and low when considerable variation existed between study findings.
2.3. Data extraction and management
The outcomes of interest for the selected studies are listed in Table 2. We used a customized Excel™ spreadsheet to record study characteristics and outcome data (Blank et al., 2012). Study characteristics were as follows: Population description: Number of participants, mean age, age range, gender, diagnostic criteria, motor test used, co-occurring diagnosis.
Methods: study design, total duration of study, frequency and duration per session.
Interventions: Intervention approach used, comparison intervention, or control. Each intervention was classified broadly as de scribed above in a Body Function-, Activity- and Participation-oriented approach.
Outcomes: Three aspects were noted: the times the outcome measures were administered (pre, post and follow up); the specific measures (classified according to the ICF categories), short description of the conclusions.
2.4. Effect size estimates Effect sizes (ES) are reported to aid comparisons of treatment efficacy across studies and between different approaches, and to inform power analyses in future work. Effect sizes were calculated to index the magnitude of pre-post differences for a given treatment group, independent of results for non-treatment DCD comparison groups. The index used was Cohen’s d, corrected for sample size (dc); means and pooled standard deviations (SD) for pre- and post-test scores were used when reported.
The magnitude of effects on norm-referenced tests were interpreted using the conventions of Cohen: small=0.2, medium=0.5, and large=0.8 (Cohen, 1988).
2.5. Study inclusion
Initially 1313 studies were identified from the computerized database search. After deleting duplicates and applying inclusion and exclusion criteria, 327 papers were retrieved (see Fig. 1). After reading the abstracts, 42 papers were selected for full review; of these, 30 reported an evaluation of some kind of motor-based intervention.
Characteristics of these 30 included studies are shown in Table 2. Eight additional studies (Bonney, Jelsma, Ferguson, & Smits-Engelsman, 2017a; Jarus et al., 2015; Jelsma, Ferguson, Smits Engelsman, & Geuze, 2015; Jelsma, Smits-Engelsman, Krijnen, & Geuze, 2016; Miles, Wood, Vine, Vickers, & Wilson, 2015; Snapp Childs, Mon-Williams, & Bingham, 2013; Wood et al., 2017; Zamani, Fatemi, & Soroushmoghadam, 2015) not included in these 30, were experimental studies of motor learning processes, and are grouped in Table S2 non-included studies, together with one pharmacological study (Bart, Daniel, Dan, & Bar-Haim, 2013).
There were six notable exclusions: One study of children with “low motor competence” (not DCD) failed to include motor outcomes (McIntyre, Chivers, Larkin, Rose, & Hands, 2015); a paper that analyzed data from a study that appeared in the earlier review, examining performance strategies used by the child (Hyland & Polatajko, 2012) and a paper using data from an earlier study to examine why an active video game (AVG) intervention was ineffective (Howie, Campbell, Abbott, & Straker, 2017). Both Bonney et al. (2017a) and Wood et al. (2017) compared different instruction methods (variable vs. repetitive AVG training, and quiet eye training vs. watching an expert model, respectively), informing what might be effective ways to instruct children with DCD.
Finally, Camden et al. (2016) investigated the impact of an evidence-based online module on perceived knowledge and skills of parents of children with DCD, and its behavioral/health outcomes. For the quantitative evaluation, 19 data sets reporting standardized motor outcomes were available.
3. Results
Results are presented in two main sections. First, we describe the general characteristics of the studies, including design. Second, we report results of the different approaches to intervention.
3.1. Study characteristics and design
Meeting inclusion criteria were 30 studies including a total of 807 participants with DCD (range 4–12 years of age) of which 509 received interventions and the rest received usual care or no intervention. No studies with adolescent or adult participants were found.
Of these 30 studies, five papers reported data on the same set of participants in another paper (Farhat et al., 2015; Farhat et al., 2016; Fong, Guo, Cheng et al., 2016; Fong, Guo, Liu et al., 2016; Fong, Chung, Chow, Ma, & Tsang, 2013; Fong, Tsang, & Ng, 2012; Howie et al., 2017; Straker et al., 2015; Larke, Campbell, Jensen, & Straker, 2015).
With data pooled across those studies, a final group of 25 datasets were examined. Descriptive characteristics of these 25 datasets (including participant characteristics, recruitment, DSM criteria and cut-off values for inclusion) are shown in Table 2. While DSM criteria were cited frequently (22/25), in many cases it was not mentioned whether participating children had a clinical referral for intervention.
3.1.1. Design
Most datasets (21/25) used a two-group comparison design between experimental intervention group and a no-intervention control or a second intervention group (7) (Au et al., 2014; Cacola, Romero, Ibana, & Chuang, 2016; Ferguson, Jelsma, Jelsma, & Smits-Engelsman, 2013; Fong, Guo, Liu et al., 2016; Noordstar, van der Net, Voerman, Helders, & Jongmans, 2017; Smits-Engelsman, Jelsma, & Ferguson, 2016; Wilson et al., 2016).
In most instances both groups were comprised of children with DCD (17 studies), and in some the control group comprised typically developing (TD) children (4). Six studies used a three-group comparison– where two groups were comprised of children with DCD and the third group was comprised of TD children.
Three studies used a pre-post design without control group (Ashkenazi, Weiss, Orian, & Laufer, 2013; Larke et al., 2015; Zwicker et al., 2015) and there were two case studies (Baldi, Nunzi, & Brina, 2015; Menz, Hatten, & Grant-Beuttler, 2013).
Ten data sets used an RCT and 11 a CCT design. The quality of these studies based on design and risk of bias is summarized in Tables 3a and 3b. Overall in three of the ten RCT’s there was still a significant risk that the found relationship was not causal as was the case for two of the 11 CCT’s. If we look at the experimental intervention (so not the control treatment) the ES of the RCT was higher (ES 1.31) than of the CCT (1.08).
In relation to the quantity of studies and consistency of outcomes across studies examined we found that 11/12 of the activity oriented 5/7 of the AVG and 5/5 of body function-oriented interventions led to significant effects on standardized motor tests. Of the studies with significant effects, Noordstar et al. (2017) and Wilson et al. (2017) showed confidence intervals that crossed the zero effect line.
3.1.2. Outcome measures
The Movement Assessment Battery for Children Test (MABC-1 or 2) was used most frequently, both for participant selection (20 of 25 datasets) and outcome evaluation (16 of 25). A version of the Bruininks-Oseretsky Test of Motor Proficiency 2nd Edition (BOT-2) was used in six studies (Au et al., 2014; Fong, Guo, Cheng et al., 2016; Hammond, Jones, Hill, Green, & Male, 2014; Menz et al., 2013; Kordi, Sohrabi, Saberi Kakhki, & Attarzadeh Hossini, 2016; Smits-Engelsman et al., 2017). Jelsma, Geuze, Mombarg, and Smits Engelsman (2014), Kordi et al., 2016 and Smits-Engelsman et al., 2017 used the MABC-2 for participant selection but also subtests of the BOT-2 for evaluation of the intervention.
One study used the Test of Gross Motor Development-2nd Edition (TGMD-2) as an outcome (Yu et al., 2016). Six papers (∼20%) did not measure or report intervention effects on a standardized motor test, but rather used experimental tests and questionnaires (Fong, Guo, Cheng et al., 2016; Fong, Guo, Liu et al., 2016; Fong et al., 2013; Fong et al., 2012; Giagazoglou, Sidiropoulou, Mitsiou, Arabatzi, & Kellis, 2015; Zwicker et al., 2015).
Baldi et al. (2015) reported outcomes on a standardized handwriting test. These seven studies were not included in the meta-analysis summarized in Table 4. Parent and/or teacher reports of activity outcomes were gathered in a small number of studies (7).
The Developmental Coordination Disorder Questionnaire (DCD-Q) was used in three studies and the Canadian Occupational Performance Measure (COPM) in the two Cognitive Orientation to Daily Occupational Performance (CO-OP) studies (Thornton et al., 2016; Zwicker et al., 2015).
Other questionnaires assessing parent perception of change in their child's participation were used in rare cases (see Tables 2 and 5). In four papers, postural sway was examined as an aspect of motor control, using the Sensory Organization Test (SOT) (Au et al., 2014; Fong, Guo, Cheng et al., 2016; Fong, Guo, Liu et al., 2016; Fong et al., 2013).
3.2. Results by intervention approach
The range of interventions and outcome measures reported in the included studies is displayed in Table 2. For the synthesis of results presented below, interventions were grouped in ICF terms according to the main orientation or target of intervention:
3.2.1. Body function oriented
Goal: improvement of body functions and prevention of significant deviation or loss of body function or structure, taking into account future health risks (WHO, 2001). Specific treatment modalities were:
(a) Strength training;
(b) Aerobic fitness training;
(c) Selective muscle activation (Biofeedback), and
(d) Visual training (Occulo-motor training).
3.2.2. Activity oriented
Goal: Improvement of the execution of a task or skill. This may involve removing the activity limitations that an individual may have in executing activities, taking into account the specific task and context.
Training considers the common circumstances and environment where the activity will be performed after the intervention. Specific treatment modalities were:
(a) Task oriented Intervention (Neuromotor Task Training; NTT/CO-OP);
(b) General Skill Training;
(c) Sport/Play related Skill Training;
(d) Virtual Reality Training (Active computer games, Exergames).
3.2.3. Participation oriented
Goal: Improvement in the child’s involvement in a real life situation. This will involve training in client-identified tasks of importance, removing any restrictions to participation, taking into account factors relating to the physical, social and cultural environment in which the child lives. To promote transfer of the intervention to real life situations, active involvement of the child, parents and/or teachers is needed.
3.2.4. Outcome measures
Table 2 shows what outcomes were assessed for each study. Two studies reported outcomes only on body functions level, 16 on body function and activity level (MABC-2 and BOT-2), and five on all 3 ICF levels (body function, activity and participation).
3.3. Treatment effects for the intervention approaches
The overall effect size on the standardized motor tests across intervention studies was large, dc=1.06. Of the five studies that compared two interventions on standardized tests, effect sizes were higher for the experimental (1.11) compared with the control interventions (0.63). For more detail see Tables 2 and 4.
3.3.1. Effects on standardized measures of movement skill
Of the 19 studies (and 24 interventions) that used the MABC or other standardized tests (BOT-2 and TGMD−2) as an outcome, the meaneffect size was high but variable across studies (M=1.06; range: 0.21–4.37). In 12 of the interventions, the observed effect was large (>0.80), in five studies moderate (>0.50), and in seven studies small or negligible (<0.50). Of the latter, two studies failed to show a significant effect between pre and post values of the standardized motor test (Ferguson et al., 2013; Thornton et al., 2016). When compared across the main intervention types, the mean ES was 1.81 for body-function oriented approaches (Range from 0.60–4.37) and 0.96 for activity oriented (Range from 0.21–2.77) (see Table 4).
3.3.2. Effects on validated questionnaires measuring motor function
Effect sizes against these standardized questionnaires are shown in Table 5, ranging from negligible to high, depending on the measure. The Thornton et al. (2016) study provides a good example of outcomes at different levels of the ICF: while children showed no improvement on the MABC, they wrote faster after intervention and parents (and the children) perceived changes in participation. Similarly, Zwicker et al. (2015) examined the effect of a small-group CO-OP intervention on a broad range of outcomes. Large effects were shown on the COPM performance and satisfaction (2.16 and 2.40) but no significant changes on the other questionnaires.
3.3.3. Intensity of the intervention
The mean duration of the intervention was 671min (median 540, range 120–2400min). Median frequency was 1.5 times per week (1–5), over 9 weeks (4–18) and 12 sessions (5–48). One half of the interventions were administered only once per week. To test the impact of treatment dose, we calculated correlations between effect size (ES) and the total duration of the intervention (mins).
A significant moderate correlation was found between ES on standardized tests and duration (rs=0.58, p=0.003). For one to one interventions alone, this relationship was not significant (rs = 0.39. p=0.34), while for other types of training (AVG/groups based) the relationship was moderate (rs=0.68, p=0.003).
The two Tsai studies (Tsai, Wang, & Tseng, 2012; Tsai et al., 2014) were clearly the most intensive (2400 and 1500min), followed by Farhat (Farhat et al., 2016; Farhat et al., 2015) and (Kordi et al., 2016) (both 1440min). The Hammond study (Hammond et al., 2014), Smits-Engelsman, Jelsma, Ferguson, and Geuze (2015) and Smits Engelsman et al. (2017) had shortest duration of training (120 and 200min, respectively).
3.3.4. Group intervention
Of the 25 datasets only eight studies involved in one to one interventions and 11 used a (small) group delivery mode. The remaining six studies used active exergaming as home-based intervention or in small groups as supervised play (see Table 2). While group-based intervention may be more cost effective, no study provided a formal cost-benefit analysis. Only one study (Cacola et al., 2016) examined the psychological experience and impact of working in groups, which is known to be of benefit in general development (Poulsen, Ziviani, Johnson, & Cuskelly, 2008). However, in addition to group size, other variables differed between comparison groups: the smaller group in the Cacola study was engaged in goal directed training, ad dressing goals chosen by the children, while the larger group was task oriented and involved different skills.
3.3.5. Virtual reality or active computer games
Playing AVGs was evaluated in seven studies of relatively small sample size (n=9 to 56); all studies with the exception of Smits Engelsman et al. (2017 were low in statistical power. In most cases, these AVG programs were implemented in a supervised school setting or as a supervised small-group intervention (4–6 students).
While six of these studies showed positive treatment effects (Ashkenazi et al., 2013; Ferguson et al., 2013; Hammond et al., 2014; Jelsma et al., 2014; Smits-Engelsman et al., 2017; Smits Engelsman, Jelsma et al., 2015) the effect sizes on standardized measures were mild to moderate at best (Mean ES=0.68, range 0.30–0.96); only those of Ashkenazi et al. (2013) (0.96), and Smits-Engelsman et al. (2016) were of larger magnitude (0.79 and 0.94). Ferguson et al. (2013) and Smits-Engelsman et al. (2016) examined also effects of AVG at the impairment level: ESs ranging between 0.46 and 1.67 on anaerobic fitness (Ferguson et al., 2013; Smits-Engelsman et al., 2016). Ashkenazi et al. (2013) used the DCD-Q (ES 0.81) and Hammond et al. (2014) the Client Satisfaction Questionnaire (CSQ) part quality and satisfaction for evaluation purposes with high effect sizes (ES 1.09 and 0.98).
Interestingly, although children reported perceived improvements in their physical skills and 13 out of the 21 children started participating in a new sport (Straker et al., 2015), the intervention did not improve their objectively measured physical activity and sedentary time (Howie, Campbell, & Straker, 2016). In a further analysis of these results the authors examined possible causes for the lack of improvement and concluded that children may not have exposed themselves to games that challenged and improved skill deficits, resulting in a motivation-outcome tradeoff (Howie et al., 2017).
Supervised use of AVGs has been recommended by Jelsma et al. (2015); the time children play games and the variety of choices should be monitored. There is some evidence that motor skills developed in the virtual reality environment transfer best to the real world when there is natural connection between the trained tasks and real world contexts (Bonney, Jelsma, Ferguson, & Smits-Engelsman 2017b; Smits-Engelsman et al., 2017). However, additional data is required to support this hypothesis and to determine the degree of specificity in learning.
3.3.6. Intervention effects on health related fitness outcomes
Fitness outcomes are salient to DCD because overweight and obesity are over represented in these children (Cairney et al., 2005; Hendrix, Prins, & Dekkers, 2014). Four studies reported improvement on tasks measuring physical fitness (e.g., 6min walk, sprinting). While targeting participation, a health promotion plan implemented in schools (Ferguson, Naidoo, & Smits-Engelsman, 2015) led to improved aerobic and anaerobic capacity and strength.
In Farhat et al. (2015) eight weeks of activity oriented training improved explosive power, cardiorespiratory fitness, aerobic endurance and motor coordination. Fong et al.’s (2013) Taekwondo program showed increased isokinetic knee muscle strength after 8 weeks of training. Running and agility also improved after 6 weeks of exergaming (Jelsma et al., 2014). The largest improvement on fitness measures was seen in the only study that was body-function oriented, which involved intensive endurance training (Tsai et al., 2014: 3×50-min sessions per week over 16 weeks).
Seven papers (Au et al., 2014; Farhat et al., 2016; Farhat et al., 2015; Ferguson et al., 2013; Ferguson et al., 2015; Fong et al., 2013; Smits-Engelsman et al., 2017), reported positive effects on strength, despite not targeting it specifically. Improvements were noted in isokinetic strength (Fong et al., 2013), functional strength (Ferguson et al., 2013; Ferguson et al., 2015; Smits-Engelsman et al., 2017) and BOT scores (Au et al., 2014). The largest increase in isometric leg muscle strength (ES 1.95) was seen in a program that specifically targeted strength, administered using two 60-min sessions per week over 12 weeks (Kordi et al., 2016).
Overall, a variety of motor interventions– whether Task oriented Training, General Skill Training, Sport/Play related Skill Training– led to moderate-to-strong improvements on fitness metrics, and associated changes in movement skill.
3.4. Intervention studies comparing two or more treatments
Six studies compared two or more different forms of intervention (Table 2). For five of these studies, we could calculate the effect size for the difference between treatments on standardized tests (Au et al., 2014; Cacola et al., 2016; Ferguson et al., 2013; Noordstar et al., 2017; Wilson et al., 2016); all involved primary-school aged children with comparable severity of motor impairment (aged 6–12 years with DCD<16th on the MABC) and relatively short duration training (5–10 weeks).
All studies (except the Wii group in Ferguson et al. (2013) reported positive effects for a range of activities- measured on standardized tests (MABC-2 or BOT-2); effect sizes were generally moderate to large (d=0.49–2.27). The RCT of Au et al. (2014) showed that activity oriented training and a core stability program yielded comparable (positive) effects on the BOT-2. Accordingly, the ES of the difference on the BOT-2 between groups was negligible, 0.122; Number to treat (NT)=14.55 showed the difference lacks clinical relevance.
However, the composite equilibrium score on the Sensory Organization Test (SOT) was significantly improved in the activity oriented group, only. The activity oriented program was broad-based, targeting functional tasks that involved body stability (e.g., standing) and body transport (e.g., walking, running, jumping, etc.), plus variations in task complexity/difficulty. In the CCT of Ferguson et al. (2013), NTT showed large improvements on the MABC-2 (ES −2.3, NT 1.11), while that for Wii training was small (ES −0.32, NT 5.58).
The effect size of the difference between the two groups was large 1.86 (NT 1.23), in favor of NTT. Differences in the magnitude of effects were most pronounced on manual dexterity and balance. Cacola et al. (2016) showed stronger effects for one activity oriented program (conducted in a single group of 11; ES=1.56, NT 1.37) compared with another activity oriented program (goal oriented approach; conducted in small groups), where skills were self selected (ES =1.24, NT 1.61).
The effect size of the difference between the two groups was moderate, 0.488 (NT 3.7). Of note, children reported higher anxiety and less enjoyment in the larger group intervention. The RCT by Wilson et al. (2016) was a replication and extension of an earlier study (Wilson, Thomas, & Maruff, 2002). This new study included a group of children with DCD, while the earlier study had children of below-average motor skill. Both studies compared Motor Imagery (MI) training, perceptual-motor training (PMT) and wait-list control. MI training consisted of: (i) video observation of skilled peers performing fundamental motor skills, (ii) mental reproduction of the observed movement from a 3rd person perspective, and (iii) internal simulation from a 1st-person perspective.
The PMT consisted of various perceptual-motor activities tailored to the needs of the individual child. Improvements on the MABC-1 were comparable between treatment groups (0.51, and 0.49 for MI and PMT, respectively NT 3.5), while no change was evident for the wait-list group (ES 0.15). The Noordstar study compared usual care with and without add-on perceived competence training using verbal feedback
(Noordstar et al., 2017). Both interventions yielded similar positive results for self-perception of motor ability and for movement skills and with moderate effect sizes (ES 0.54 and 0.53, NT 3.4).
It is clear that this difference between the interventions lacks clinical relevance. Importantly, this study is one of the few that re-evaluated the children and showed that after three months gains remained. The balance training program of Fong, Guo, Cheng et al. (2016) and Fong, Guo, Liu et al. (2016) targeted the impairment level, designed to enhance balance strategies in children with DCD.
The Functional Movement Training (FMT) group used biofeedback from EMG activation while performing MABC-1 balance items. A second treatment program involved individual strength/resistance training of the legs. Both programs improved equilibrium scores on the SOT, and on various aspects of leg strength and power. Improvement was maintained after 6 months in the FMT group. No comparisons were made between these groups on a standardized motor test, pre and post intervention.
4. Discussion
Children with DCD are generally referred to pediatric physical and occupational therapists, who use an array of therapeutic approaches to address the functional problems. Commonly used are body function oriented and activity oriented approaches.
Since the earlier recommendation for interventions for children with DCD (Blank et al., 2012), many new studies have been published in this field. Unlike other reviews, we have included here all motor-based intervention studies published between January 2012 and February 2017, independent of design (i.e., case-study to RCT); studies of varying rigor and complexity have been included.
Including different designs in our review (and thereby expanding the number of eligible studies) has the potential to introduce sources of error associated with uncontrolled variables. However, this is tempered by presenting ratings of the risk of bias (aka quality of the evidence) in both RCTs and CCTs. One major advantage of including a larger sample of studies is that corroborating results greatly reduce the chance of spurious findings. Because the effect sizes we report are independent of results for non-treatment (DCD) comparison groups, these estimates may be inflated. In addition, a range of factors may promote motor skill development, which are not controlled for in the evaluation of the studies (e.g., spontaneous development, extra attention, positive regard, or practice effects).
4.1. General trends
The review reports on 30 new intervention studies, addressing 25 datasets conducted between January 2012 and February 2017 (an average of five studies per year). These figures underline some of the challenges in conducting intervention studies, particularly large-N and RCTs. Nonetheless, the body of this work is instructive, and has revealed some compelling trends in the research over recent years. Overall, the design of the studies was moderate to good (see Tables 2, 3a and 3b) and data on several approaches increased (e.g. Sport/Play related Skill Training, Virtual Reality Training).
Of the three parameters used to determine the strength of evidence, we found that the quantity and quality was moderate to good (i.e., risk of bias was high in 5/21 studies). Consistency of outcomes across all reviewed studies was very good with 21/24 interventions showing significant improvement on standardized motor performance tests. There was a definite trend towards more activity oriented training that addressed specific skills needed for play and sports participation.
However, no comparison study tested whether interventions actually led to more participation in physical activity, sports or other forms of active play, nor tested effects on well-being. Also, no study tested whether intervention effects differed as a function of age, severity or co-occurring disorders. There have been some prominent changes in the type of training since 2011 with group-based intervention, other work using AVGs, and fitness-based programs adding to the treatment landscape.
Like earlier reviews, however, the most frequently reported type of intervention was activity oriented (12/24) (Table 4). Importantly, most studies show positive treatment effects, primarily on measures at the activity level of the ICF (esp. movement skill and activities requiring physical fitness) but also at impairment level (strength, cardiorespiratory function (CRF), body sway).
4.2. Activity oriented approaches are generally effective
Whereas the earlier clinical guidelines (Blank et al., 2012) reported a dominance of activity oriented approaches that were designed to promote movement skill, in recent years we see that improvement in body function has also been targeted, e.g., AVG to improve balance (Jelsma et al., 2015) and General Skill Training to improve strength or endurance (Farhat et al., 2015). Taken together, the review identified two forms of activity oriented interventions: task oriented approaches designed to address (specific) real world goals selected by the child (Cacola et al., 2016; Ferguson et al., 2013; Thornton et al., 2016; Zwicker et al., 2015) and generic activity oriented approaches designed to teach a set of general or sports/play related motor skills e.g. soccer: Tsai et al. (2012); Taekwando: Fong et al. (2012, 2013); health promotion: Ferguson et al. (2015).
Activity-oriented approaches (like NTT) that focus on task-specific skills showed consistent improvements not only on activity based outcomes but also on body function. This finding is corroborated by other, recent reviews. Lucas et al. (2016) reviewed nine RCT’s that evaluated interventions that aimed to improve gross-motor performance in children with neurodevelopmental disorders (Cerebral Palsy and DCD). They found that some interventions with a task oriented framework improved gross-motor outcomes; however, high quality intervention trials were not well represented.
Additionally, based on a systematic review and meta-analysis of 29 articles on physical therapy, Offor, Williamson, and Cacola (2016) concluded that task oriented approaches (NTT) and motor training programs from traditional and contemporary physiotherapy (PT) frameworks are beneficial for children with DCD. Inter ventions based on PT motor skills training and NTT are effective for gross-motor problems. NTT is also effective for fine-motor problems (Offor et al., 2016). The recent meta-analysis of 6 studies by Miyahara et al. (2017) reported that task-oriented inter ventions improved motor performance more compared to no intervention.
Finally, in a meta-analysis of nine RCTs in DCD, Preston et al. (2017) showed large ESs for ‘Neuromotor Task Training’, ‘Task oriented Motor Training’ and ‘Motor Imagery+Task Practice Training’. For the CO-OP approach (focusing mainly on cognitive strategies to facilitate skill acquisition), a controlled trial showed positive gains on the Goal Attainment Scale in the intervention compared to no intervention group (Thornton et al., 2016) and pre-post comparison on questionnaires measuring performance and satisfaction (COPM) (Zwicker et al., 2015); however, neither study showed change on standardized measures of movement skill.
In their narrative review on the effect of CO-OP, Anderson, Wilson, and Williams (2017) included six articles, no analysis of improvement on motor tests was reported. They concluded that the CO-OP approach, when administered in a group format, has the potential to benefit children with DCD in both physical and psycho-social domains. However, more controlled studies are needed that confirm the effectiveness of CO-OP on clinical tests of motor skill and physical participation (Anderson et al., 2017).
4.3. Active computer games as a useful adjunct
Use of AVGs has steadily grown as a popular form of entertainment and play, and are finding a place in movement rehabilitation across a range of conditions. The results of a recent review (Bonnechere, Jansen, Omelina, & Van Sint Jan, 2016) show that in most cases, the introduction of AVG training in physical rehabilitation offered similar results to conventional therapy. The evidence thus far shows a positive effect of AVGs on motivation and engagement in rehabilitation (Lohse, Shirzad, Verster, Hodges, & Van der Loos, 2013).
Although the use of AVGs for children with DCD is relatively new, efficacy has been tested in other health conditions (Cerebral Palsy, Stroke, Parkinson’s Disease). AVGs have numerous advantages, such as preventing monotony and boredom, increasing motivation, providing direct feedback, and allowing double-task training (Bonnechere et al., 2016). On the other hand there are some concerns with AVGs. Although AVGs aim to activate children by doing games in sport related tasks, they may increase time spent playing computer games in general, leading to less active outside play. AVG-based training in DCD shows promising effects, but the issue of transfer to everyday performance and participation is an unanswered question. It has recently been shown that AVGs lead to moderate improvement on balance tasks (Ashkenazi et al., 2013; Bonney et al., 2017a; Jelsma et al., 2015; Smits-Engelsman et al., 2017; Smits-Engelsman, Jelsma et al., 2015) in DCD, and that children also improved on more functional tasks like standing up from a chair and going up and down stairs (Bonney et al., 2017b; Smits-Engelsman et al., 2016).
Before we can make an evidence-based recommendation for the impact of AVGs on participation in sport and outside play, studies evaluating this aspect are needed. Importantly more insight is needed on mechanisms of transfer from the virtual to real world, and on the limits of such interventions. Taken together including AVGs as an adjunct to more mainstream intervention is worth considering.
Although mean effect size is moderate (ES 0.68), it was shown the children with DCD enjoy the games, which can improve engagement in the process of intervention and, therefore, may be a better alternative to more sedentary games. An important difference between AVGs and regular physical or occupational therapy is that children learn motor skills more implicitly during gaming since no formal instruction is provided. The relative efficacy of implicit and explicit approaches to learning is an area of future investigation. Finally, although supervision is needed, the hours that have to be put in by a professional are relatively few. Exergaming may be a convenient supplement to more tailored intervention. The relationship between improved AVG performance and engagement in physical activity (Participation) is in need of further investigation.
4.4. Body-function oriented training combined with activities
Body-function oriented therapies are now commonly combined with other forms of activity-based therapy. Most studies focusing on strength or visual training, for instance, were combined with some more functional tasks (e.g., Fong, Guo, Cheng et al. (2016) combined power training with Functional movement training; Coetzee & Pienaar (2013) combined reading with walking or jumping). Combined approaches such as these may have improved the level of transfer. The efficacy of body-function oriented approaches varies considerably and there remains a need to validate transfer to multiple ICF levels.
4.5. Intervention in small groups
Interpreting results for group-based intervention is not straightforward because differences in protocol exist other than group format vs. not. Overall, group-based intervention (ES 1.46) and individual-based training (ES 1.05) both produced large effects on motor performance. The strong effect for group-based intervention suggests that it may be a good option where the cost of treatment is an issue. Recommendations on the ideal group size cannot be determined based on the data but we know that groups of between 4 and 6 children have been used, are manageable, and effective with one therapist and optional assistant (Cacola et al., 2016; Farhat et al., 2015; Ferguson et al., 2013; Zwicker et al., 2015).
Indeed, small groups enable instructors to move easily between participants and to monitor both group dynamics and individual progress. It is possible that children with very poor motor skill may feel more anxious in a larger group as was found in one study (Cacola et al., 2016). These same children did, however, improve their ability to deal with peer problems, which is a very useful life skill. Results also showed that choosing your own goals and that playing together may reduce performance anxiety and encourage task engagement (Cacola et al., 2016; Zwicker et al., 2015). Moreover, playing games (both on the computer and real) in groups may improve adherence, both in the short- and longer-term (Ferguson et al., 2013; Jelsma et al., 2014). However, controlled studies that compare group-based and individual intervention on motor outcomes and psychological factors are needed.
4.6. Intervention to improve health-related physical fitness has a positive impact
To minimize the risk of long-term health problems associated with poor motor coordination (e.g., weight gain, physical inactivity, cardiovascular problems), promotion of an active lifestyle and training of skills needed in sports (e.g., agility, ball skills) is recommended. Studies provide consistent evidence that activity oriented training, like NTT and Sport/Play related Skill Training, and Virtual Reality Training involving exergames can all improve basic physical condition and functional strength needed in daily activities and can be integrated into intervention plans. However the real effects of these approaches on daily activity has not been examined.
4.7. Toward a standard framework for reporting trials
Interventions to improve motor performance in DCD have many components and vary in type, intensity, duration, and frequency. The Consolidated Standards of Reporting Trials (Consort, 2010) states that precise information should be given about the intervention but a number of studies in this review were hard to classify. In future, we strongly recommend that all authors use a comparable framework like the Template for Intervention Description and Replication (TIDieR) checklist (Hoffmann et al., 2014). This would facilitate replication studies and inter-study comparison, enabling reviewers to unpack often heterogeneous results.
4.8. Aspects of dose and scheduling: lack of comparative data
Our review also aimed to examine the available information on optimal duration and frequency of therapy, and treatment indications for different sub-groups (e.g., children of different ages, socioeconomic status, and with co-occurring conditions). However, research bearing on these questions was lacking. There is a large gap in knowledge of how the choice of therapy can be optimized for individuals with DCD and co-occurring disorders in terms of dosage, timing, scheduling, and content.
Although comorbidity is prominent in neurodevelopmental disorders (e.g Lingam, Golding, Jongmans, Hunt, Ellis, Emond, 2010), no study evaluated possible differences in effect or approach between groups of children with and without co-occurring disorders (e.g., DCD+/−ADHD). Co-occurring disorders may seriously impact outcomes and therefore deserve more attention in future research. Training protocols showed much variability in scheduling and dose across studies. While the average duration was relatively short at around 9 weeks, the length of intervention varied between 4 and 18. The studies that were in the longer range (10–16 weeks) and more frequent (2–3 per week) were group-based programs targeting specific sport skills or general fitness (Soccer, Trampoline, Endurance training, Power training) (Fong, Guo, Liu et al., 2016; Tsai et al., 2012; Tsai et al., 2014).
Scheduling and dose were broadly consistent with the goals of these programs. In particular, training fine-motor skills tends to be more time intensive than gross-motor. Although many of the programs of around 9h total duration show good training effects on manual dexterity, hand writing seems more resistant to change over these timeframes (Baldi et al., 2015). Studies that compare different treatment approaches, different modes of delivery and their applicability to subgroups are much needed in this area. Only the study of Ashkenazi et al. (2013) studied preschool children (aged 4–6 years) and no intervention studies of adolescents and adults were retrieved.
A final question for future research concerns how the duration of practice sessions and total duration of therapy interact with the practice schedule adopted. Results from the motor learning literature suggest that a random practice order enhances motor learning more when compared with blocked practice (Shea & Morgan, 1979). For DCD, no studies have yet examined the level of learning transfer, nor compared different modes of instruction.
For example, the addition of motor imagery and action observation (Adams, Lust, Wilson, & Steenbergen, 2014) might well complement other approaches to intervention. In one study, Yu et al. (2016) did test the effect of task oriented motor skill training using an error-reduced learning strategy, and Smits-Engelsman et al. (2016) and Bonney et al. (2017a), tested the effect of different AVG protocols. However, because group composition is not consistent across studies, the ability to draw strong inferences is reduced.
4.9. Quality of the studies and interpretation of the results
In short, our review confirms that children with the diagnosis of DCD should receive intervention. On valid and reliable norm referenced tests, the overall effect size across studies was large (d=1.06). However, there was considerable variation in the magnitude of effects. In 11 of the interventions, the ES was large (>0.80), in eight studies moderate (>0.50), and in five studies small or negligible (<0.50). Of the latter, two failed to show a significant effect between pre- and post-test values on a standardized test (Table 4). In general, for any given approach to intervention, the magnitude of effect sizes did not differ greatly between RCTs and CCTs. Although results indicate that there is evidence that activity-oriented and body function oriented interventions can have a positive effect on motor function and skills, mixed methodological quality and large confidence intervals of some studies suggests that results should be viewed with caution.
Our analysis shows that to best evaluate treatment effects, measures at both the activity and participation levels should be used, providing a broader representation of the impact of intervention (Table 2, 4 and 5). Because mechanisms of transfer remain unclear, it is recommended that activity-oriented approaches be used, which, by definition, are aligned to real world activities that are of significance to the child. In addition, body function oriented approaches should target function(s) that most clearly support the activities of significance (e.g., running agility for a field sport).
For all interventions there remains a dire need for (learning) retention studies and analysis of how effectively learned skills and capacities can transfer to the activities of daily living and participation in sport and recreation. The ability to measure subtle change in children's capacity in activities of daily living (ADL) is vital for researchers and clinicians.
New technologies (e.g., wearable sensors using accelerometers, bend sensors, Global Positioning System (GPS) tracking, exoskeletons, etc.) will improve our ability to track performance objectively over time and with greater precision. Lastly, to make the interpretation of results easier for readers, we encourage authors to report effect sizes and their associated confidence intervals. Clinical significance metrics like the minimal important difference (MID) values or smallest detectable difference (SDD) are also valuable for clinicians and researchers alike.
4.10. Limitations
By including both RCTs and CCTs in our review, additional error variance is introduced when calculating mean ESs. In particular, factors that may promote motor development in children are not controlled for; as such, alternative explanations for observed effects are possible (e.g., spontaneous development, extra positive attention or retest effects).
However, we have tempered our interpretation in a number of ways by:
(i) estimating the risk of bias in both RCTs and CCTs,
(ii) evaluating consistency of the results, and
(iii) reporting not only if the intervention led to a statistically significant change but also the effect size and its confidence interval. The review showed that in most cases the true effect lay within an acceptable range, but for some cases these values crossed the zero effect line warranting some caution in the interpretation.
4.11. Implications for practice and conclusion
This update on the evidence for DCD intervention shows that there is consistency for the positive effect of activity-based interventions on a range of outcome variables: 11 of the 12 interventions evaluated showed significant improvements between pre- and post-test on validated motor batteries. The general efficacy of activity oriented approaches, AVG and programs addressing body functions begs the question of the most cost effective approach.
Cost-benefit analyses are needed to inform how finite resources for intervention are best spent in the context of rising health care costs. New data supporting the immediate benefits on performance of relatively short duration intervention, AVGs, and small group programs now prompt more rigorous RCTs with follow up to show sustained change rather than short-term performance gains. The review reinforces the principle that training programs stay close to the tasks and circumstances needed in the child’s everyday life.
If the child is trained in tasks of everyday relevance, even relatively short periods of training can have a positive effect (around 9 weeks). Fine motor skills may take a little longer, but comparison studies between approaches for fine motor skills are absent. Future studies should also report on outcomes at the participation level as evidence of transfer from body function and activity level to the real world is sparse.
Moreover, long term effect or retention studies are needed since they are even more scant (Fong, 2016; Noordstar et al., 2017; Coetzee & Pienaar, 2013). Another important new finding was the large number of studies that reported on effectiveness when programs were conducted in a small group format. However, we do not have sufficient evidence to make informed decisions on who is most likely to benefit. Studies on the motivational or emotional aspects are lacking. The fact that no differences in the magnitude of treatment effects were found between small group and one to one therapy could have implications for intervention services.
Once children are deemed eligible for services in many countries, they are still placed on waitlists. Group intervention can improve access for many children and save resources, while one to one treatment tailored to the needs of the individual child is maintained. It has been shown in several studies that individual goals can still be addressed in small group programs (Ferguson et al., 2013; Zwicker et al., 2015). New training formats (like augmented feedback, for example), new delivery modes and training schedules could be piloted based on the available evidence and then evaluated in new RCT’s, which should include longer follow-up times.
Additionally time-series analysis might be used to monitor learning effects over the duration of training (Damiano, 2014). Specific comparison studies are needed to determine the optimal learning and teaching approaches for (subgroups of) children and adults with DCD to be able to make better evidence based recommendations for the broad spectrum of individuals with DCD. So far no study compared whether children referred to a clinic performed differently to those selected only for research. Until then conclusions about effectiveness should be interpreted with care. Whatever the intervention, the motor learning literature suggests that time on task (duration, repetition, intensity) and task salience are good predictors of progression in motor skill development (Kleim and Jones 2008).
As such it is important to leverage opportunities for practice and generalization of skills by enlisting the support of parents, teachers, and significant others. Both activity oriented interventions, and body-function oriented interventions that are combined with functional tasks are suggested. Training everyday activities by targeting the weakest link in the activity chain, and programs that support learning of complex motor skills in areas of (self-selected) interest are important, enhancing the child’s readiness and willingness to participate in life activities, improve fitness and prevent obesity.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Appendix A. Supplementary data
Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.ridd.2018.01. 002.
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