A Meta-Analysis of the Experimental Evidence on the Near- andFar-Transfer Effects Among Children’s Executive Function Skills

Reka KassaiELTE Eötvös Loránd University and MTA-ELTE Lendület

Adaptation Research Group

Judit Futo and Zsolt DemetrovicsELTE Eötvös Loránd University

Zsofia K. TakacsELTE Eötvös Loránd University and MTA-ELTE Lendület Adaptation Research Group

In the present meta-analysis we examined the near- and far-transfer effects of training components ofchildren’s executive functions skills: working memory, inhibitory control, and cognitive flexibility. Wefound a significant near-transfer effect (g� � 0.44, k � 43, p � .001) showing that the interventions inthe primary studies were successful in training the targeted components. However, we found noconvincing evidence of far-transfer (g� � 0.11, k � 17, p � .11). That is, training a component did nothave a significant effect on the untrained components. By showing the absence of benefits that generalizebeyond the trained components, we question the practical relevance of training specific executivefunction skills in isolation. Furthermore, the present results might explain the absence of far-transfereffects of working memory training on academic skills (Melby-Lervag & Hulme, 2013; Sala & Gobet,2017).

Public Significance StatementThe present meta-analysis suggests that it is possible to foster executive functions in childhood byexplicitly training them. However, these programs have limited practical relevance as they onlypromote the component(s), (working memory, inhibitory control, and cognitive flexibility) that aretargeted in the training and do not have far-transfer effects to untrained component(s).

Keywords: executive functions, children, meta-analysis, intervention

Supplemental materials: http://dx.doi.org/10.1037/bul0000180.supp

Executive functions in childhood are crucial skills as they havean important role in social-emotional and cognitive development(Zelazo & Carlson, 2012). These fundamental cognitive skills inthe preschool age are strongly related to school readiness (Bier-man, Nix, Greenberg, Blair, & Domitrovich, 2008; Blair, 2002)and they are more predictive of later academic achievement thanIQ (Blair & Razza, 2007). In a previous meta-analysis on the

concurrent and predictive relations of executive function skills and(later) academic achievement in childhood (Jacob & Parkinson,2015) moderate associations were found both regarding math andreading skills. When children enter formal schooling, executivefunctions are also of high importance in the adjustment to thelearning environment and developing social relationships (Liew,2012). Children’s ability to focus their attention on the relevantobjects, inhibit distractors and impulsive responses, practice self-regulation and self-control by resisting the immediate gratificationof their momentary needs, and solve problems in a flexible andcreative manner are all necessary for academic success as well asfor thriving in social relationships (McClelland & Cameron, 2012).Thus, the importance of executive functions in childhood is clear.

Executive functions are a set of cognitive skills that is respon-sible for planning and organizing our deliberate and goal-directedbehavior (Lezak, 1982). These processes make us able to con-stantly monitor and flexibly adjust to the changes in the environ-ment, to solve new and complex problems, and practice self-control (Jurado & Rosselli, 2007). Behavior regulation via thesetop-down processes is discussed in several theoretical frameworks.While some approaches consider executive functions as a unitary

Reka Kassai, Doctoral School of Psychology, ELTE Eötvös LorándUniversity, and MTA-ELTE Lendület Adaptation Research Group; JuditFuto and Zsolt Demetrovics, Institute of Psychology, ELTE Eötvös LorándUniversity; Zsofia K. Takacs, Institute of Education, ELTE Eötvös LorándUniversity, and MTA-ELTE Lendület Adaptation Research Group.

This research was funded by the Hungarian National Research, Devel-opment and Innovation Office [grant PD121297], the ÚNKP-17-4 NewNational Excellence Program of the Ministry of Human Capacities [grantUNKP-17-4-I-ELTE-125], and the Hungarian Academy of Sciences in theframework of the Lendület II. program (project N: 2018-412).

Correspondence concerning this article should be addressed to Zsofia K.Takacs, Institute of Education, ELTE Eötvös Loránd University, 1075Budapest, Kazinczy u. 23–27, Hungary. E-mail: takacs.zsofia@ppk.elte.hu

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Psychological Bulletin© 2019 American Psychological Association 2019, Vol. 145, No. 2, 165–1880033-2909/19/$12.00 http://dx.doi.org/10.1037/bul0000180

165

construct, others highlight the distinction between different com-ponents of executive functioning while hypothesizing varying de-grees of unity among different numbers of components.

In Norman and Shallice’s (1986) model the supervisory atten-tional system is responsible for the deliberate regulation ofthoughts and behavior instead of giving schematic responses.Activation of this system makes us able to react in a more adaptivemanner when it is required by the circumstances, for example, innew or unexpected situations when habitual responses would notbe successful. In Baddeley and Hitch’s (1994) model of workingmemory the central executive has a similar role; this component isresponsible for the coordination and the regulation of the twosubsystems: the phonological loop and the visuospatial sketchpad.

Other models argue that executive function skills can be con-sidered to be a unitary construct with different numbers of sepa-rable components. In their seminal work, Miyake et al. (2000)examined the associations between the latent variables behinddifferent types of executive function measures designed to tapworking memory (updating), inhibition, and switching in adults.The factor analyses that provided the best fit resulted in threeclearly separable but moderately correlated factors: (a) updating(also labeled as working memory) that is used to keep informationin mind and to manipulate it; (b) inhibition that makes us able tocontrol our attention, emotions, and behavior by restraining auto-matic or prepotent responses; and (c) shifting (also labeled ascognitive flexibility) which makes us able to look at a problemfrom different points of views and to switch between differentrules and dimensions.

Lehto, Juujärvi, Kooistra, and Pulkkinen (2003) found evidencefor three factors within children’s executive function skills. How-ever, as stated above, there is no general consensus on the numberof components. Supporting this, in a sample of 11- to 12-year-oldchildren, St. Clair-Thompson and Gathercole (2006) found evi-dence for two factors: one for updating (working memory) and onefor inhibition. On the other hand, Wiebe, Espy, and Charak (2008)found that a unitary factor was just as good of a fit for 2- to6-year-old children’s results on working memory and inhibitiontasks as models with separate factors for working memory andinhibitory control. Diamond (2013) considers executive functionskills as a unitary construct with three separable components,however, she broadens this view with a developmental aspect: Sheposits that the executive function (EF) components of workingmemory and inhibitory control skills are mutually supportive ofeach other, and that cognitive flexibility is the latest to develop andbuilds on the other two components.

Although weak or at most moderate correlations among thecomponents are consistently found in the literature (Bull & Scerif,2001; Carlson, Moses, & Breton, 2002; Senn, Espy, & Kaufmann,2004; St. Clair-Thompson & Gathercole, 2006), in most studiesthose disappear after controlling for age and other control variableslike IQ (e.g., Hughes, 1998). It is important to note that studiesusing latent variables (Miyake et al., 2000) generally show stron-ger associations among different EF components. This discrepancybetween results based on single tests as opposed to latent variablesmight imply that measurement imperfections such as task impuritymight indeed play a major role in weakening the associationsfound among the components.

In sum, there is no consensus regarding whether the componentsof executive functions form a unitary construct in childhood.

Accordingly, it is highly questionable whether training one of thecomponents has an effect on the untrained executive function skillsof children. In fact, in literature reviews on the efficacy of differentinterventions aiming to foster children’s executive function skills,doubts have been expressed about the rationale of training specificcomponents in isolation. Diamond and Lee (2011) suggested thatCogmed, a software that trains working memory skills, does nothave significant effects on untrained executive function skills.Diamond and Ling (2016) concluded that while working memorytrainings are successful in training working memory skills, gainsdo not generalize to either inhibitory control or flexibility. Finally,Blair (2017) postulated that results are mixed regarding the far-transfer effects of computerized working memory trainings andactivities embedded in children’s everyday lives should be moreeffective in training executive function skills in general.

The most important aim of the present meta-analysis was to gaina deeper understanding of whether and to what extent the differentcomponents of executive functions are trainable and whether train-ing a specific executive function has an ameliorating effect onother main executive function components. This is of crucialimportance because in the long run the main aim of trainingexecutive functions skills is to improve children’s everyday func-tioning; for example, academic and social skills as well as emotionregulation. These complex skills are not supported by one soleexecutive function but generally rely on the interplay among mostof them (Blair & Razza, 2007).

Meta-analytic studies so far have shown that training workingmemory is possible (Melby-Lervag & Hulme, 2013; Melby-Lervåg, Redick, & Hulme, 2016; Sala & Gobet, 2017); however,it has limited far-transfer effects on the above mentioned complexsocial, emotional, and academic skill sets. Melby-Lervåg andHulme (2013) found no transfer effects of computerized workingmemory training on verbal and nonverbal ability, word decoding,or arithmetic. Further, Sala and Gobet (2017) found small far-transfer effects of working memory training on mathematics andliteracy/word decoding, and no transfer to fluid or crystallizedintelligence or science.

One possible explanation for the lack of far-transfer effect foundon these complex skills is that there might not even be a far-transfer effect among the executive function components them-selves (working memory, inhibition, cognitive flexibility) togetherwhich form the basis of the more complex social, academic, andemotional skills examined. In fact, previous meta-analyses(Melby-Lervag & Hulme, 2013; Sala & Gobet, 2017) have onlyconfirmed the existence of near-transfer effects of working mem-ory trainings (e.g., working memory training improving workingmemory), but could not show a far-transfer effect in children oninhibitory control (operationalized as Stroop-like tests in Melby-Lervag & Hulme, 2013, and as Stroop-tests, go/no-go tests, and thedichotic-listening task in Sala & Gobet, 2017), the only executivefunction component investigated in this respect to date. Althoughworking memory training in childhood have received considerableattention, data about training other EF components which are justas important for complex everyday skills as working memory havenot yet been synthetized to our knowledge.

Accordingly, our study aims to fill this gap in the literature byexamining the evidence regarding the near- and far-transfer effectsof training any and all of the main executive function componentsin childhood: working memory, inhibition, and cognitive flexibil-

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166 KASSAI, FUTO, DEMETROVICS, AND TAKACS

ity. Near-transfer effect was defined as effects on the same exec-utive function component(s) that were trained (excluding tasks thatwere practiced during the training), while far-transfer effect in thepresent study was considered as effects on executive functioncomponents that were untrained. By investigating these effects onall three main components of executive function skills in onemeta-analytic study including data of both typically and atypicallydeveloping children, this study provides a unique extension of ourexisting knowledge on the clinically relevant question of trainingexecutive functions and therefore potentially improves the every-day functioning of children.

Based on the literature the following hypotheses were tested:

Hypothesis 1: We expected significant near-transfer effectsbut small or no far-transfer effects of training components ofexecutive functions in childhood.

Hypothesis 2: Regarding the associations between the differ-ent pairs of components there is little evidence in the litera-ture. Melby-Lervåg and Hulme’s (2013) meta-analytic resultssuggest that working memory programs have a small butsignificant effect on inhibitory control measured by Stroop-like tasks. However, this effect was not significant in childsamples (although this was based on a very limited number ofstudies). Accordingly, we expected that training workingmemory might have an effect on inhibitory control. Regardingthe rest of the pairs of components, we had no priorexpectations.

The results of the present meta-analysis are highly relevant tothe clinical practice. A number of developmental psychopatholo-gies are characterized by executive dysfunctions, some of whichare directly linked to the behavioral symptoms. Many computer-based training programs aim to ameliorate the functioning of asingle executive function component; for example, working mem-ory trainings are frequently used with children living with atten-tion-deficit/hyperactivity disorder (ADHD; e.g., Lomas, 2001).However, it is still questionable whether the benefits observedtransfer to other skills such as inhibitory control or flexibility. Incase training a single component does not affect the others, morecomplex trainings that target different executive function compo-nents are probably more suitable in the clinical practice.

Method

Operational Definition

The aim of the present meta-analysis was to examine the near-and far-transfer effects among the following executive functionskills: working memory, inhibitory control, and cognitive flexibil-ity or shifting. Accordingly, we categorized the interventions andthe outcome measures of the primary studies based on the com-ponent(s) they targeted (see the online supplementary material).Most of the training programs utilized a game-like activity eitherin a computer (e.g., Alloway, Bibile, & Lau, 2013; Bennett,Holmes, & Buckley, 2013) or in a noncomputer setting (e.g.,Caviola, Mammarella, Cornoldi, & Lucangeli, 2009; Dowsett &Livesey, 2000) but all of them trained executive function skillsexplicitly by practicing tasks that require one or more executivefunction skills. When the intervention contained elements fostering

different components of executive functions, we considered themmulticomponent trainings (e.g., Goldin et al., 2014; Traverso,Viterbori, & Usai, 2015), while if the targeted skill was clearlyassociated with one core executive component, we defined it as asingle-component training (e.g., de Vries, Prins, Schmand, &Geurts, 2015; Volckaert & Noël, 2015).

In order to be able to assess near- and far-transfer effects we alsocategorized the outcome measures according to which componentit assessed. Instead of relying on the interpretation of the primarystudies’ authors of the tests, we categorized which component thetask loaded on according to the previous considerations in theliterature (Diamond, 2013; Friedman & Miyake, 2004; Garon,Bryson, & Smith, 2008; Miyake et al., 2000). For instance, back-ward digit, word, or spatial (e.g., Corsi block test) span tasks (e.g.,Chacko et al., 2014) were coded as measures of working memory.It is important to note that forward span tests were considered toreflect short-term memory (STM) because they require no manip-ulation of the information kept in mind (Alloway, Gathercole, &Pickering, 2006) and were thus excluded in the present study. Incase a measure including both forward and backward span taskwas reported in a study, it was still included as a measure ofworking memory (e.g., Dovis, Van der Oord, Wiers, & Prins,2015). Additionally, we decided to combine results over verbaland visuospatial working memory because we found very similarresults on the two kinds of working memory tasks (near-transfereffect on verbal working memory tasks: g� � 0.48, k � 20, SE �0.09, 95% CI [0.30, 0.66], p � .001; near-transfer effect onnonverbal working memory tasks: g� � 0.45, k � 22, SE � 0.07,95% CI [0.32, 0.61], p � .001; far-transfer effect on verbalworking memory tasks: g� � �0.04, k � 3, SE � 0.27, 95% CI[�0.56, 0.49], p � .89; far-transfer effect on nonverbal workingmemory tasks: g� � �0.30, k � 3, SE � 0.43, 95% CI [�1.13,0.54], p � .49). This is also in line with the evidence showing thatworking memory is a domain-general capacity (Alloway et al.,2006). It is important to note that the working memory interven-tions in the primary studies used both verbal and nonverbal tasksso we also could not differentiate trainings using verbal andnonverbal stimuli.

Tests that required children to inhibit either a prepotent/autom-atized reaction, a previously learnt response, or a distractor wereincluded as measures of inhibitory control: go/no-go (Dowsett &Livesey, 2000), flanker (e.g., Röthlisberger, Neuenschwander, Ci-meli, Michel, & Roebers, 2011), Stroop-like tests (e.g., Thorell,Lindqvist, Bergman Nutley, Bohlin, & Klingberg, 2009), andAX-CPT (e.g., Dörrenbächer, Müller, Tröger, & Kray, 2014) wereconsidered just like different tasks using the delay of gratificationparadigm like the toy wait test (e.g., Rueda, Checa, & Cómbita,2012) based on Diamond (2013). Similarly, the head-toes-shoulders-knees test was also considered a measure of inhibitorycontrol (Ponitz, McClelland, Matthews, & Morrison, 2009) be-cause children need to inhibit an automatized response—for in-stance, inhibit touching their head when the experimenter says soyet touching their toes instead. Although a second rule is intro-duced in the second phase of the test, it does not interfere with thefirst rule and does not require switching.

Tests that require children to switch between rules that refer tothe same stimuli such as the dimensional card sorting test (e.g.,Howard, Powell, Vasseleu, Johnstone, & Melhuish, 2016; Schmitt,2013) and tasks requiring flexible adjustment of strategies such as

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167TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

the trail making test part B (e.g., Dovis et al., 2015), the Tower ofLondon test (e.g., Goldin et al., 2014), or the Wisconsin cardsorting test (Lomas, 2001) were categorized as measures of cog-nitive flexibility.

Search Strategy

As the present study was a part of a more extensive meta-analytic project (Takacs & Kassai, 2018) in which we synthetizedall the available experimental results on the effectiveness of dif-ferent kinds of behavioral interventions that aimed to promoteexecutive functions (Diamond & Lee, 2011, e.g., physical exer-cise, art activity, executive function-specific curricula, martial arts,and mindfulness-based practice), we conducted a systematicsearch in the literature based on a detailed search string (seeAppendix A). Four databases (PsycINFO, Web of Science, Psy-cARTICLES, and ERIC) were scanned to identify all the availablejournal articles and unpublished studies like dissertations andconference papers that reported on the effects of an explicit train-ing of component(s) of executive functions with children. Afterexcluding duplicates, 7,287 studies remained. Two independentresearch assistants scanned all of them based on their title andabstract. As a secondary search, the references of the selectedstudies in addition to relevant review articles and meta-analyseswere checked to find all suitable results. Finally, as shown inAppendix B, we identified 38 studies with 47 contrasts that weresuitable for the present study.

Inclusion Criteria

The included studies had to meet the following criteria:

• Randomized controlled design was utilized (The random-ization was done either on an individual or on a group[e.g., classroom] basis).

• The results of the intervention group were compared witha passive or an active control group.

• The aim of the intervention was to explicitly train at leastone of the three core executive function components:working memory, inhibitory control, or cognitive flexibil-ity.

• The age of the sample was no more than 12 years at thebeginning of the study.

• The paper reported the results of at least one outcomemeasure that used a neurocognitive test of executive func-tions.

• The paper was written in English.

Exclusion Criteria

To begin, we excluded all the studies that utilized an implicitapproach for training. Accordingly, we did not include studies onphysical exercise (e.g., Fisher et al., 2011), art activity (e.g.,Schellenberg, 2004), executive function-specific curricula (e.g.,Bierman et al., 2008), mindfulness-based meditation (e.g., Flook,Goldberg, Pinger, & Davidson, 2015), or neuro/biofeedback train-ing (e.g., Beauregard & Lévesque, 2006), and those studies whereteachers or parents were trained instead of the children (Lewis-Morrarty, Dozier, Bernard, Terracciano, & Moore, 2012). Wecould not include correlational studies (e.g., Wiebe, Espy, &

Charak, 2008), as we wanted to draw conclusions about the causalrelationships between the components.

As outcome measures, we only included neurocognitive tests ofexecutive function conducted with the children. Accordingly, otherkinds of instruments were excluded: We did not include teacher-,parent-, or self-reported assessment of executive functions like theBehavior Rating Inventory of Executive Function (e.g., de Vries etal., 2015). Additionally, instead of reaction time (RT), we pre-ferred accuracy on these neurological tests (e.g., Röthlisberger,Neuenschwander, Cimeli, Michel, & Roebers, 2011) because ac-curacy or error rates are considered a more reliable measure ofexecutive functions in childhood (Diamond, Barnett, Thomas, &Munro, 2007). Finally, it is important to note that we did notinclude measures that were the same as the task the childrenpracticed during the intervention as we considered these as directmeasures of training efficacy and to reflect no near- or far-transfereffects. For instance, children practiced a go/no-go apparatus in thestudy of Dowsett and Livesey (2000) and were tested on the samemachine afterward. As these tasks were explicitly practiced duringthe intervention, we excluded them from the analyses in order notto overestimate near-transfer effects. Finally, results had to beexcluded in case we could not locate the full text in English (e.g.,Aghababaei, Malekpour, & Abedi, 2012) or if we did not havesufficient statistics to calculate an effect size even after contactingthe authors (e.g., St. Clair-Thompson & Holmes, 2008).

Coding

During the coding process, two research assistants coded everyarticle according to a predefined coding schema regarding thefollowing information: (a) bibliographic information (e.g., title,author(s), year of publication, and the country where the data wascollected); (b) sample characteristics (e.g., the number and themean age of the participants in the intervention and control groups,other characteristics of the sample such as IQ, SES, and clinicalstatus); (c) study design (e.g., passive or active control); (d) char-acteristics of the intervention (e.g., the executive function compo-nent(s) it targeted, whether the training was conducted individuallyor in groups, whether it was applied on a computer or not); (e) thekind of outcome measure (e.g., working memory, inhibitory con-trol, or flexibility) and whether it was a near-transfer measure (thecomponent targeted in the intervention was the same as tested bythe outcome measure) or far-transfer (the component targeted inthe intervention was different from what the outcome measuretested) measure. Interrater reliability (ranging from 78% to 100%agreement between two coders) was acceptable in all cases.

As shown in Table 1 and 2, from the studies that reported on theresults of more than one intervention or control conditions that metour inclusion criteria we included more contrasts. If there were twoor more suitable intervention conditions, all of them were includedas compared with the control group. The same strategy was usedwhen a study contained more control conditions like an active anda passive control. For instance, Kyttälä, Kanerva, and Kroesbergen(2015) tested the effects of a combined working memory and acounting training alone by comparing them to a passive controlcondition. In this case only the combined working memory andcounting training met our inclusion criteria, the counting trainingalone condition was considered an active control condition. There-fore, the results of the participants who received the working

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168 KASSAI, FUTO, DEMETROVICS, AND TAKACS

Tab

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wof

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Stud

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Incl

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33;

SD�

3.58

Typ

ical

lyde

velo

ping

Wor

king

mem

ory

and

inhi

bito

ryco

ntro

lan

dtr

aini

ng:

“Sho

rtex

ecut

ive

func

tion

trai

ning

prog

ram

”(n

�26

)

Act

ive

cont

rol

(n�

28)

Wor

king

mem

ory

(1m

easu

re):

1.B

ackw

ard

wor

dta

skIn

hibi

tory

cont

rol

(1m

easu

re):

1.Pe

gta

ppin

g

Cav

iola

2009

Ital

y,E

urop

e9

Typ

ical

lyde

velo

ping

Wor

king

mem

ory

trai

ning

:“M

etac

ogni

tive

visu

ospa

tial

wor

king

mem

ory

trai

ning

”(n

�22

)

Act

ive

cont

rol

(n�

24)

Wor

king

mem

ory

(2m

easu

res)

:1.

Bac

kwar

ddi

git

reca

ll2.

Cor

sibl

ock

test

Cha

cko

2014

New

Yor

k,N

orth

Am

eric

a7–

11D

iagn

osed

:A

DH

DW

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

44)

Act

ive

cont

rol

(n�

41)

Wor

king

mem

ory

(2m

easu

res)

:1.

Lis

teni

ngre

call

2.Sp

atia

lre

call

deV

ries

2015

Hol

land

,E

urop

e8–

12D

iagn

osed

:A

SDW

orki

ngm

emor

ytr

aini

ng:

“Bra

inga

me

Bri

an”

(n�

31)

Act

ive

cont

rol

(n�

29)

Wor

king

mem

ory

(1m

easu

re):

Con

tras

t1

1.N

-bac

kte

st

deV

ries

2015

Hol

land

,E

urop

e8–

12D

iagn

osed

:A

SDC

ogni

tive

flex

ibili

tytr

aini

ng:

“Bra

inga

me

Bri

an”

(n�

26)

Act

ive

cont

rol

(n�

29)

Cog

nitiv

efl

exib

ility

(2m

easu

re):

Con

tras

t2

1.N

umbe

r-gn

ome

switc

h2.

Gen

der-

emot

ion

switc

h(t

able

cont

inue

s)

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

169TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

Tab

le1

(con

tinu

ed)

Firs

tau

thor

Publ

icat

ion

year

Plac

eA

ge(i

nye

ars)

Clin

ical

stat

usof

the

sam

ple

Inte

rven

tion

cond

ition

Con

trol

cond

ition

Out

com

em

easu

re

Don

gen-

Boo

msm

a(D

isse

rtat

ion,

Cha

pter

VI)

2014

Hol

land

,E

urop

e5–

7D

iagn

osed

:A

DH

DW

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

26)

Act

ive

cont

rol

(n�

21)

Wor

king

mem

ory

(2m

easu

res)

:1.

Kno

xC

ubes

Lei

dse

Dia

gnos

tisch

eT

est

2.B

ackw

ard

digi

tsp

an

Dov

is20

15H

olla

nd,

Eur

ope

10D

iagn

osed

:A

DH

DW

orki

ngm

emor

y,in

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

“Bra

inga

me

Bri

an”

(Ful

lac

tive;

n�

31)

Act

ive

cont

rol

(n�

15)

Wor

king

mem

ory

(1m

easu

re):

Con

tras

t1

1.D

igit

Span

(WIS

C)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

1.T

rail

Mak

ing

Tes

t(s

witc

h-co

st)

Dov

is20

15H

olla

nd,

Eur

ope

10D

iagn

osed

:A

DH

DIn

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

“Bra

inga

me

Bri

an”

(Par

tially

activ

e;n

�31

)

Act

ive

cont

rol

(n�

30)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

Con

tras

t2

1.T

rail

Mak

ing

Tes

t(s

witc

h-co

st)

Dör

renb

äche

r20

14G

erm

any,

Eur

ope

8–11

Typ

ical

lyde

velo

ping

Cog

nitiv

efl

exib

ility

trai

ning

:“T

ask

switc

hing

trai

ning

”(h

igh

mot

ivat

ion;

n�

13)

Act

ive

cont

rol

(n�

14)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

Con

tras

t1

1.T

ask

switc

hing

task

Dör

renb

äche

r20

14G

erm

any,

Eur

ope

8–11

Typ

ical

lyde

velo

ping

Cog

nitiv

efl

exib

ility

:“T

ask

switc

hing

trai

ning

”(l

owm

otiv

atio

n;n

�14

)

Act

ive

cont

rol

(n�

14)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

Con

tras

t2

1.T

ask

switc

hing

task

Dun

ning

2013

Uni

ted

Kin

gdom

,E

urop

e7–

9L

owE

F:“L

oww

orki

ngm

emor

y”W

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

34)

Pass

ive

cont

rol

(n�

30)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

11.

Mix

ofba

ckw

ard

digi

tsp

anan

dlis

teni

ngre

call

2.M

ixof

Mr.

X,

Odd

one

out

Dun

ning

2013

Uni

ted

Kin

gdom

,E

urop

e7–

9L

owE

F:“L

oww

orki

ngm

emor

y”W

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

34)

Act

ive

cont

rol

(n�

30)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

21.

Mix

ofba

ckw

ard

digi

tsp

anan

dlis

teni

ngre

call

2.M

ixof

Mr.

X,

Odd

one

out

Esp

inet

2012

Can

ada,

Nor

thA

mer

ica

2–4

Typ

ical

lyde

velo

ping

Cog

nitiv

efl

exib

ility

trai

ning

:“R

efle

ctio

ntr

aini

ng”

(n�

15)

Act

ive

cont

rol

(n�

14)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

Exp

erim

ent

11.

Dim

ensi

onal

Cha

nge

Car

dSo

rtE

spin

etC

anad

a,N

orth

Am

eric

a2–

4T

ypic

ally

deve

lopi

ngC

ogni

tive

flex

ibili

tytr

aini

ng:

“Ref

lect

ion

trai

ning

”(n

�14

)

Act

ive

cont

rol

(n�

14)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

Exp

erim

ent

21.

Dim

ensi

onal

Cha

nge

Car

dSo

rtE

spin

etC

anad

a,N

orth

Am

eric

a2–

4T

ypic

ally

deve

lopi

ngC

ogni

tive

flex

ibili

tytr

aini

ng:

“Ref

lect

ion

trai

ning

”(n

�20

)

Act

ive

cont

rol

(n�

16)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

Exp

erim

ent

31.

Dim

ensi

onal

Cha

nge

Car

dSo

rtC

ontr

ast

1

Esp

inet

Can

ada,

Nor

thA

mer

ica

2–4

Typ

ical

lyde

velo

ping

Cog

nitiv

efl

exib

ility

trai

ning

:“R

efle

ctio

ntr

aini

ng”

(n�

20)

Act

ive

cont

rol

(n�

20)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

Exp

erim

ent

31.

Dim

ensi

onal

Cha

nge

Car

dSo

rtC

ontr

ast

2

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

170 KASSAI, FUTO, DEMETROVICS, AND TAKACS

Tab

le1

(con

tinu

ed)

Firs

tau

thor

Publ

icat

ion

year

Plac

eA

ge(i

nye

ars)

Clin

ical

stat

usof

the

sam

ple

Inte

rven

tion

cond

ition

Con

trol

cond

ition

Out

com

em

easu

re

Gol

din

2014

Arg

entin

a,So

uth

Am

eric

a6–

7T

ypic

ally

deve

lopi

ngW

orki

ngm

emor

y,in

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

“Mat

eM

arot

e”(n

�73

)

Act

ive

cont

rol

(n�

38)

Inhi

bito

ryco

ntro

l(2

mea

sure

s):

1.C

hild

Atte

ntio

nN

etw

ork

Tas

k—in

cong

ruen

t2.

Hea

rtan

dFl

ower

s—Fi

xin

cong

ruen

tC

ogni

tive

flex

ibili

ty(3

mea

sure

s):

1.H

eart

and

Flow

ers—

Mix

cong

ruen

t2.

Hea

rtan

dFl

ower

s—M

ixin

cong

ruen

t3.

Tow

erof

Lon

don

Hol

mes

2009

Uni

ted

Kin

gdom

,E

urop

e8–

11L

owE

F:“L

oww

orki

ngm

emor

y”W

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

22)

Act

ive

cont

rol

(n�

20)

Wor

king

mem

ory

(2m

easu

re):

1.M

ixof

Mr.

X,

Odd

one

out

2.C

ount

ing

reca

ll

Hov

ik20

13N

orw

ay,

Eur

ope

10–1

2D

iagn

osed

:A

DH

DW

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

33)

Pass

ive

cont

rol

(n�

34)

Wor

king

mem

ory

(2m

easu

res)

:1.

Lei

ter

Rfo

rwar

dan

dba

ckw

ard

2.M

ixof

lette

r–nu

mbe

rse

quen

cing

and

sent

ence

span

How

ard

2016

Aus

tral

ia4

Typ

ical

lyde

velo

ping

Wor

king

mem

ory,

inhi

bito

ryco

ntro

lan

dco

gniti

vefl

exib

ility

trai

ning

:“S

hare

dbo

okre

adin

gon

eon

one–

Qui

ncey

Quo

kka’

sQ

uest

”(n

�22

)

Act

ive

cont

rol

(n�

18)

Wor

king

mem

ory

(1m

easu

re):

Stud

y1,

Con

tras

t1

1.M

r.A

ntIn

hibi

tory

cont

rol

(1m

easu

re):

1.G

o/N

o-G

oC

ogni

tive

flex

ibili

ty(1

mea

sure

):1.

Dim

ensi

onal

Cha

nge

Car

dSo

rt

How

ard

2016

Aus

tral

ia4

Typ

ical

lyde

velo

ping

Wor

king

mem

ory,

inhi

bito

ryco

ntro

lan

dco

gniti

vefl

exib

ility

trai

ning

:“S

hare

dbo

okre

adin

gin

agr

oup–

Qui

ncey

Quo

kka’

sQ

uest

”(n

�25

)

Act

ive

cont

rol

(n�

18)

Wor

king

mem

ory

(1m

easu

re):

Stud

y1,

Con

tras

t2

1.M

r.A

ntIn

hibi

tory

cont

rol

(1m

easu

re):

1.G

o/N

o-G

oC

ogni

tive

flex

ibili

ty(1

mea

sure

):1.

Dim

ensi

onal

Cha

nge

Car

dSo

rt

How

ard

2016

Aus

tral

ia4

Typ

ical

lyde

velo

ping

Wor

king

mem

ory,

inhi

bito

ryco

ntro

lan

dco

gniti

vefl

exib

ility

trai

ning

:“S

hare

dbo

okre

adin

gon

e-on

-one

–Q

uinc

eyQ

uokk

a’s

Que

st”

(n�

19)

Act

ive

cont

rol

(n�

21)

Wor

king

mem

ory

(1m

easu

re):

Stud

y2

1.M

r.A

ntIn

hibi

tory

cont

rol

(1m

easu

re):

1.G

o/N

o-G

oC

ogni

tive

flex

ibili

ty(1

mea

sure

):1.

Dim

ensi

onal

Cha

nge

Car

dSo

rtH

owar

d20

16A

ustr

alia

4T

ypic

ally

deve

lopi

ngW

orki

ngm

emor

y,in

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

“Sha

red

book

read

ing

one-

on-o

ne–

Qui

ncey

Quo

kka’

sQ

uest

”(n

�19

)

Act

ive

cont

rol

(n�

15)

Wor

king

mem

ory

(1m

easu

re):

Stud

y3

1.M

r.A

ntIn

hibi

tory

cont

rol

(1m

easu

re):

1.G

o/N

o-G

oC

ogni

tive

flex

ibili

ty(1

mea

sure

):1.

Dim

ensi

onal

Cha

nge

Car

dSo

rt(t

able

cont

inue

s)

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

171TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

Tab

le1

(con

tinu

ed)

Firs

tau

thor

Publ

icat

ion

year

Plac

eA

ge(i

nye

ars)

Clin

ical

stat

usof

the

sam

ple

Inte

rven

tion

cond

ition

Con

trol

cond

ition

Out

com

em

easu

re

Klin

gber

g20

05Sw

eden

,E

urop

e7–

12D

iagn

osed

:A

DH

DW

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

20)

Act

ive

cont

rol

(n�

24)

Wor

king

mem

ory

(1m

easu

re):

1.Sp

anbo

ard

task

�K

loo

2003

Aus

tria

,E

urop

e2–

4T

ypic

ally

deve

lopi

ngC

ogni

tive

flex

ibili

tytr

aini

ng:

“Car

dSo

rtin

g”(n

�14

)A

ctiv

eco

ntro

l(n

�15

)C

ogni

tive

flex

ibili

ty(1

mea

sure

):1.

Dim

ensi

onal

Cha

nge

Car

dSo

rt

Kro

esbe

rgen

2014

Hol

land

,E

urop

e5

Typ

ical

lyde

velo

ping

Wor

king

mem

ory

trai

ning

:“D

omai

nge

nera

lw

orki

ngm

emor

ytr

aini

ng”

(n�

15)

Pass

ive

cont

rol

(n�

21)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

11.

Wor

dre

call

back

war

d2.

Odd

one

out

Kro

esbe

rgen

2014

Hol

land

,E

urop

e5

Typ

ical

lyde

velo

ping

Wor

king

mem

ory

trai

ning

:“D

omai

nsp

ecif

icw

orki

ngm

emor

ytr

aini

ng”

(n�

15)

Pass

ive

cont

rol

(n�

21)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

21.

Wor

dre

call

back

war

d2.

Odd

one

out

Kyt

tälä

2015

Finl

and,

Eur

ope

5.9

Typ

ical

lyde

velo

ping

Wor

king

mem

ory

trai

ning

:“W

orki

ngm

emor

yan

dco

untin

gtr

aini

ng”

(n�

23)

Act

ive

cont

rol

(n�

23)

Wor

king

mem

ory

(3m

easu

res)

:C

ontr

ast

11.

Bac

kwar

dw

ord

span

2.B

ackw

ard

digi

tsp

an3.

Odd

one

out

Kyt

tälä

2015

Finl

and,

Eur

ope

5.9

Typ

ical

lyde

velo

ping

Wor

king

mem

ory

trai

ning

:“W

orki

ngm

emor

yan

dco

untin

gtr

aini

ng”

(n�

23)

Pass

ive

cont

rol

(n�

17)

Wor

king

mem

ory

(3m

easu

res)

:C

ontr

ast

21.

Bac

kwar

dw

ord

span

2.B

ackw

ard

digi

tsp

an3.

Odd

one

out

Lom

as(D

isse

rtat

ion)

2001

Vir

gini

a,N

orth

Am

eric

a7–

9D

iagn

osed

:A

DH

DW

orki

ngm

emor

y,in

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

Pass

ive

cont

rol

(n�

15)

Inhi

bito

ryco

ntro

l(1

mea

sure

):1.

Con

tinuo

usPe

rfor

man

ceT

est—

com

mis

sion

erro

rs“L

ocuT

our

Mul

timed

iaC

ogni

tive

Reh

abili

tatio

n”(n

�16

)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

1.W

CST

—to

tal

corr

ect

Luo

2013

Chi

na,

Asi

a8–

11D

iagn

osed

:D

ysle

xia

Wor

king

mem

ory

and

inhi

bito

ryco

ntro

ltr

aini

ng:

“Wor

king

mem

ory

and

cent

ral

exec

utiv

eta

sks”

(n�

15)

Act

ive

cont

rol

(n�

15)

Wor

king

mem

ory

(2m

easu

res)

:1.

Wor

dsp

anta

skba

ckw

ard

2.D

igit

span

back

war

dIn

hibi

tory

cont

rol

(1m

easu

res)

:1.

Stro

op

Mar

kom

icha

li(D

isse

rtat

ion)

Stud

y1,

Con

tras

t1

2015

New

Ham

pshi

re,

Nor

thA

mer

ica

4–5

Typ

ical

lyde

velo

ping

Inhi

bito

ryco

ntro

ltr

aini

ng:

“Wai

ting

Gam

e”(n

�12

)A

ctiv

eco

ntro

l(n

�13

)In

hibi

tory

cont

rol

(1m

easu

re):

1.T

heT

eddi

esT

ask

Mar

kom

icha

li(D

isse

rtat

ion)

2015

New

Ham

pshi

re,

Nor

thA

mer

ica

4–5

Typ

ical

lyde

velo

ping

Inhi

bito

ryco

ntro

ltr

aini

ng:

“Wai

ting

Gam

e”(n

�12

)Pa

ssiv

eco

ntro

l(n

�13

)In

hibi

tory

cont

rol

(1m

easu

re):

1.T

heT

eddi

esT

ask

Stud

y1,

Con

tras

t2

Mar

kom

icha

li(D

isse

rtat

ion)

2015

New

Ham

pshi

re,

Nor

thA

mer

ica

4–6

Low

EF:

“Low

inhi

bitio

n”In

hibi

tory

cont

rol

trai

ning

:“W

aitin

gG

ame”

(n�

19)

Pass

ive

cont

rol

(n�

18)

Inhi

bito

ryco

ntro

l(2

mea

sure

s):

1.T

heT

eddi

esT

ask

2.B

eeD

elay

Tas

kSt

udy

2

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

172 KASSAI, FUTO, DEMETROVICS, AND TAKACS

Tab

le1

(con

tinu

ed)

Firs

tau

thor

Publ

icat

ion

year

Plac

eA

ge(i

nye

ars)

Clin

ical

stat

usof

the

sam

ple

Inte

rven

tion

cond

ition

Con

trol

cond

ition

Out

com

em

easu

re

Re

2007

Ital

y,E

urop

e5

Dia

gnos

ed:

AD

HD

Wor

king

mem

ory,

inhi

bito

ryco

ntro

lan

dco

gniti

vefl

exib

ility

trai

ning

:“W

orki

ngM

emor

yC

ontr

olT

rain

ing

Prog

ram

”(n

�5)

Pass

ive

cont

rol

(n�

5)W

orki

ngm

emor

y(1

mea

sure

):1.

Dua

lR

eque

stSe

lect

ive

Tas

kIn

hibi

tory

cont

rol

(1m

easu

re):

1.W

alk/

Don

’tW

alk

Re

2015

Ital

y,E

urop

e5

Low

EF:

“AD

HD

sym

ptom

s”W

orki

ngm

emor

y,in

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

“Wor

king

Mem

ory

Con

trol

Tra

inin

gPr

ogra

m”

(n�

13)

Act

ive

cont

rol

(n�

13)

Wor

king

mem

ory

(1m

easu

re):

Sam

ple

11.

Dua

lR

eque

stSe

lect

ive

Tas

kIn

hibi

tory

cont

rol

(1m

easu

re):

1.W

alk/

Don

’tW

alk

Re

2015

Ital

y,E

urop

e5

Typ

ical

lyde

velo

ping

Wor

king

mem

ory,

inhi

bito

ryco

ntro

lan

dco

gniti

vefl

exib

ility

trai

ning

:“W

orki

ngM

emor

yC

ontr

olT

rain

ing

Prog

ram

”(n

�13

)

Act

ive

cont

rol

(n�

13)

Wor

king

mem

ory

(1m

easu

re):

Sam

ple

21.

Dua

lR

eque

stSe

lect

ive

Tas

kIn

hibi

tory

cont

rol

(1m

easu

re):

1.W

alk/

Don

’tW

alk

Röt

hlis

berg

er20

11Sw

iss,

Eur

ope

5T

ypic

ally

deve

lopi

ngW

orki

ngm

emor

y,in

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

“Sm

all

grou

pin

terv

entio

nde

velo

ped

topr

omot

eE

F”(n

�33

)

Pass

ive

cont

rol

(n�

38)

Wor

king

mem

ory

(1m

easu

re):

Sam

ple

11.

Com

plex

Span

Tas

kIn

hibi

tory

cont

rol

(1m

easu

re):

1.Si

mpl

eFl

anke

rT

ask

Cog

nitiv

efl

exib

ility

(1m

easu

re):

1.M

ixed

Flan

ker

Tas

k

Röt

hlis

berg

er20

11Sw

iss,

Eur

ope

6T

ypic

ally

deve

lopi

ngW

orki

ngm

emor

y,in

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

“Sm

all

grou

pin

terv

entio

nde

velo

ped

topr

omot

eE

F”(n

�30

)

Pass

ive

cont

rol

(n�

34)

Wor

king

mem

ory

(1m

easu

re):

Sam

ple

21.

Com

plex

Span

Tas

kIn

hibi

tory

cont

rol

(1m

easu

re):

1.Si

mpl

eFl

anke

rT

ask

Cog

nitiv

efl

exib

ility

(1m

easu

re):

1.M

ixed

Flan

ker

Tas

k

Rue

da20

12Sp

ain,

Eur

ope

5T

ypic

ally

deve

lopi

ngIn

hibi

tory

cont

rol

trai

ning

:“C

ompu

teri

zed

trai

ning

ofat

tent

ion”

(n�

19)

Act

ive

cont

rol

(n�

18)

Inhi

bito

ryco

ntro

l(4

mea

sure

s):

1.D

elay

ofG

ratif

icat

ion–

Self

2.D

elay

ofG

ratif

icat

ion–

Oth

er3.

Chi

ldG

ambl

ing

Tas

k4.

Chi

ldA

NT

—om

issi

oner

ror

Schm

itt20

13O

rego

n,N

orth

Am

eric

a3–

5T

ypic

ally

deve

lopi

ngIn

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

“Sel

f-re

gula

tion

inte

rven

tion”

(n�

126)

Pass

ive

cont

rol

(n�

150)

Inhi

bito

ryco

ntro

l(1

mea

sure

):(D

isse

rtat

ion)

1.H

ead-

Toe

s-K

nees

-Sho

ulde

rsT

ask

Cog

nitiv

efl

exib

ility

(1m

easu

re):

1.D

CC

SSt

.C

lair

-Tho

mps

on20

08U

nite

dK

ingd

om,

Eur

ope

6–7

Typ

ical

deve

lopi

ngW

orki

ngm

emor

ytr

aini

ng:

“Mem

ory

Boo

ster

”(n

�22

)

Pass

ive

cont

rol

(n�

22)

Wor

king

mem

ory

(2m

easu

res)

:St

udy

11.

Lis

teni

ngre

call

task

2.C

ount

ing

reca

llta

sk

St.

Cla

ir-T

hom

pson

2008

Uni

ted

Kin

gdom

,E

urop

e6–

7T

ypic

ally

deve

lopi

ngW

orki

ngm

emor

ytr

aini

ng:

“Mem

ory

Boo

ster

”(n

�18

)

Pass

ive

cont

rol

(n�

18)

Wor

king

mem

ory

(2m

easu

res)

:St

udy

21.

Lis

teni

ngre

call

task

2.B

ackw

ard

digi

tre

call

St.

Cla

ir-T

hom

pson

2010

Uni

ted

Kin

gdom

,E

urop

e5–

8T

ypic

ally

deve

lopi

ngW

orki

ngm

emor

ytr

aini

ng:

“Mem

ory

Boo

ster

”(n

�11

7)

Act

ive

cont

rol

(n�

137)

Wor

king

mem

ory

(1m

easu

re):

1.L

iste

ning

reca

ll

(tab

leco

ntin

ues)

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

173TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

Tab

le1

(con

tinu

ed)

Firs

tau

thor

Publ

icat

ion

year

Plac

eA

ge(i

nye

ars)

Clin

ical

stat

usof

the

sam

ple

Inte

rven

tion

cond

ition

Con

trol

cond

ition

Out

com

em

easu

re

Tho

rell

2009

Swed

en,

Eur

ope

4–5

Typ

ical

deve

lopi

ngW

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

17)

Act

ive

cont

rol

(n�

14)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

11.

Span

Boa

rdT

ask

(WA

IS-R

-N

I)2.

Wor

dSp

anT

ask

Tho

rell

2009

Swed

en,

Eur

ope

4–5

Typ

ical

lyde

velo

ping

Wor

king

mem

ory

trai

ning

:“C

ogm

edW

orki

ngM

emor

yT

rain

ing:

Rob

oMem

o”(n

�17

)

Pass

ive

cont

rol

(n�

16)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

21.

Span

Boa

rdT

ask

(WA

IS-R

-N

I)2.

Wor

dSp

anT

ask

Tho

rell

2009

Swed

en,

Eur

ope

4–5

Typ

ical

lyde

velo

ping

Inhi

bito

ryco

ntro

ltr

aini

ng:

“Cog

med

Inhi

bitio

nT

rain

ing:

Rob

oMem

o”(n

�18

)

Act

ive

cont

rol

(n�

14)

Inhi

bito

ryco

ntro

l(2

mea

sure

s):

Con

tras

t3

1.D

ay-N

ight

Stro

opT

ask—

erro

r2.

Go/

No-

Go

Tas

k—co

mm

issi

oner

ror

Tho

rell

2009

Swed

en,

Eur

ope

4–5

Typ

ical

lyde

velo

ping

Inhi

bito

ryco

ntro

ltr

aini

ng:

“Cog

med

Inhi

bitio

nT

rain

ing:

Rob

oMem

o”(n

�18

)

Pass

ive

cont

rol

(n�

16)

Inhi

bito

ryco

ntro

l(2

mea

sure

s):

Con

tras

t4

1.D

ay-N

ight

Stro

opT

ask—

erro

r2.

Go/

No-

Go

Tas

k—co

mm

issi

oner

ror

Tom

iney

2011

Ore

gon,

Nor

thA

mer

ica

3–5

Typ

ical

lyde

velo

ping

Inhi

bito

ryco

ntro

lan

dco

gniti

vefl

exib

ility

trai

ning

:“C

ircl

eT

ime

Gam

es”

(n�

28)

Pass

ive

cont

rol

(n�

37)

Inhi

bito

ryco

ntro

l(1

mea

sure

):1.

Hea

d-T

oes-

Kne

es-S

houl

ders

Tas

k

Tra

vers

o20

15It

aly,

Eur

ope

5T

ypic

ally

deve

lopi

ngW

orki

ngm

emor

yan

din

hibi

tory

cont

rol

trai

ning

:“E

Fpr

omot

ing

smal

lgr

oup

prog

ram

–Chi

cco

and

Nan

a”(n

�32

)

Pass

ive

cont

rol

(n�

43)

Wor

king

mem

ory

(2m

easu

res)

:1.

Bac

kwar

dW

ord

Span

2.K

eep

Tra

ckIn

hibi

tory

cont

rol

(4m

easu

res)

:1.

Cir

cle

draw

ing

task

2.A

rrow

flan

ker

task

3.G

ift

wra

p4.

Del

ayta

sk

Vol

ckae

rt20

15B

elgi

um,

Eur

ope

4–5

Typ

ical

lyde

velo

ping

Inhi

bito

ryco

ntro

ltr

aini

ng:

“Inh

ibiti

ontr

aini

ng”

(n�

24)

Act

ive

cont

rol

(n�

23)

Inhi

bito

ryco

ntro

l(1

mea

sure

):1.

Mix

ofT

raff

iclig

hts,

Cat

-D

og-F

ish,

Mon

ster

Stro

op,

Hea

d-T

oes-

Kne

es-S

houl

ders

(Inh

ibiti

onfa

ctor

)

Won

g20

14C

hina

,A

sia

6–12

Low

EF:

“Low

wor

king

mem

ory”

Wor

king

mem

ory

trai

ning

:“C

ompu

teri

zed

wor

king

mem

ory

trai

ning

”(n

�26

)

Pass

ive

cont

rol

(n�

25)

Wor

king

mem

ory

(1m

easu

re):

1.Sp

anB

oard

task

Not

e.A

DH

D�

atte

ntio

n-de

fici

t/hyp

erac

tivity

diso

rder

;ASD

�au

tism

spec

trum

diso

rder

;EF

�ex

ecut

ive

func

tion.

The

stud

ym

arke

dby

�w

asex

clud

edfr

omth

ean

alys

esbe

caus

eit

had

anou

tlyin

gef

fect

size

.

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

174 KASSAI, FUTO, DEMETROVICS, AND TAKACS

Tab

le2

Ove

rvie

wof

the

Stud

ies

Incl

uded

inth

eSe

cond

Met

a-A

naly

sis

Reg

ardi

ngF

ar-T

rans

fer

Eff

ects

Firs

tau

thor

Publ

icat

ion

year

Plac

eA

ge(i

nye

ars)

Clin

ical

stat

usof

the

sam

ple

Inte

rven

tion

cond

ition

Con

trol

cond

ition

Out

com

em

easu

re

Big

orra

2016

Spai

n,E

urop

e7–

12D

iagn

osed

:A

DH

DW

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g”(n

�31

)

Act

ive

cont

rol

(n�

30)

Inhi

bito

ryco

ntro

l(1

mea

sure

):1.

CPT

II(c

omm

issi

oner

rors

)C

ogni

tive

flex

ibili

ty(3

mea

sure

s):

1.T

ower

ofL

ondo

n2.

WC

ST(p

erse

vera

tive

erro

rs)

3.T

rail

mak

ing

test

B

Bla

key

2015

Eng

land

,E

urop

eM

�4.

33;

SD�

3.58

Typ

ical

lyde

velo

ping

Wor

king

mem

ory

and

inhi

bito

ryco

ntro

lan

dtr

aini

ng:

“Sho

rtex

ecut

ive

func

tion

trai

ning

prog

ram

”(n

�26

)

Act

ive

cont

rol

(n�

28)

Cog

nitiv

efl

exib

ility

(2m

easu

res)

:1.

FIST

2.SW

IFT

mix

edsw

itch

Cha

cko

2014

New

Yor

k,N

orth

Am

eric

a7–

11D

iagn

osed

:A

DH

DW

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g”(n

�44

)

Act

ive

cont

rol

(n�

41)

Inhi

bito

ryco

ntro

l(1

mea

sure

):1.

CPT

(com

mis

sion

erro

rs)

deV

ries

2015

Hol

land

,E

urop

e8–

12D

iagn

osed

:A

SDW

orki

ngm

emor

ytr

aini

ng:

“Bra

inga

me

Bri

an”

(n�

31)

Act

ive

cont

rol

(n�

29)

Inhi

bito

ryco

ntro

l(1

mea

sure

):C

ontr

ast

11.

Stop

task

(com

mis

sion

erro

r)C

ogni

tive

flex

ibili

ty(2

mea

sure

):1.

Num

ber-

gnom

esw

itch

2.G

ende

r-em

otio

nsw

itch

deV

ries

2015

Hol

land

,E

urop

e8–

12D

iagn

osed

:A

SDC

ogni

tive

flex

ibili

tytr

aini

ng:

“Bra

inga

me

Bri

an”

(n�

31)

Act

ive

cont

rol

(n�

29)

Wor

king

mem

ory

(1m

easu

re):

Con

tras

t2

1.N

-bac

kte

stIn

hibi

tory

cont

rol

(1m

easu

re):

1.St

opta

sk(c

omm

issi

oner

ror)

Don

gen-

Boo

msm

a20

14H

olla

nd,

Eur

ope

5–7

Dia

gnos

ed:

AD

HD

Wor

king

mem

ory

trai

ning

:“C

ogm

edW

orki

ngM

emor

yT

rain

ing:

Rob

oMem

o”(n

�24

)

Act

ive

cont

rol

(n�

21)

Inhi

bito

ryco

ntro

l(3

mea

sure

s):

(Dis

sert

atio

n,C

hapt

erV

I.)

1.D

ay/N

ight

Stro

op2.

Shap

esc

hool

cont

rol

red

3.Sh

ape

scho

olco

ntro

lye

llow

Cog

nitiv

efl

exib

ility

(2m

easu

res)

:1.

Shap

esc

hool

switc

hre

d2.

Shap

esw

itch

yello

w

Dov

is20

15H

olla

nd,

Eur

ope

10D

iagn

osed

:A

DH

DIn

hibi

tory

cont

rol

and

cogn

itive

flex

ibili

tytr

aini

ng:

“Bra

inga

me

Bri

an”

(Par

tially

activ

e;n

�28

)

Act

ive

cont

rol

(n�

30)

Wor

king

mem

ory

(1m

easu

re):

Con

tras

t2

1.D

igit

Span

(WIS

C)

Dow

sett

2000

Aus

tral

ia3

Low

EF:

“Low

inhi

bitio

n”C

ogni

tive

flex

ibili

tytr

aini

ng:

Prac

ticin

gE

Fpr

omot

ing

task

s(n

�7)

Pass

ive

cont

rol

(n�

5)In

hibi

tory

cont

rol

(1m

easu

re):

Con

tras

t1

1.G

o/N

o-go

disc

rim

inat

ion

appa

ratu

s

Dow

sett

2000

Aus

tral

ia4–

5L

owE

F:“L

owin

hibi

tion”

Cog

nitiv

efl

exib

ility

trai

ning

:Pr

actic

ing

EF

prom

otin

gta

sks

(n�

8)

Pass

ive

cont

rol

(n�

4)In

hibi

tory

cont

rol

(1m

easu

re):

Con

tras

t2

1.G

o/N

o-go

disc

rim

inat

ion

appa

ratu

s(t

able

cont

inue

s)

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

175TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

Tab

le2

(con

tinu

ed)

Firs

tau

thor

Publ

icat

ion

year

Plac

eA

ge(i

nye

ars)

Clin

ical

stat

usof

the

sam

ple

Inte

rven

tion

cond

ition

Con

trol

cond

ition

Out

com

em

easu

re

Dör

renb

äche

r20

14G

erm

any,

Eur

ope

8–11

Typ

ical

lyde

velo

ping

Cog

nitiv

efl

exib

ility

trai

ning

:“T

ask

switc

hing

trai

ning

(hig

hm

otiv

atio

n”(n

�13

)

Act

ive

cont

rol

(n�

14)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

11.

Bac

kwar

ddi

git

span

2.C

ount

ing

span

Inhi

bito

ryco

ntro

l(3

mea

sure

s):

1.C

PTA

Y2.

CPT

BX

3.St

roop

test

Dör

renb

äche

r20

14G

erm

any,

Eur

ope

8–11

Typ

ical

lyde

velo

ping

Cog

nitiv

efl

exib

ility

trai

ning

:“T

ask

switc

hing

trai

ning

(low

mot

ivat

ion”

(n�

13)

Act

ive

cont

rol

(n�

14)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

21.

Bac

kwar

ddi

git

span

2.C

ount

ing

span

Inhi

bito

ryco

ntro

l(3

mea

sure

s):

1.C

PTA

Y2.

CPT

BX

3.St

roop

test

Dun

ning

2013

Uni

ted

Kin

gdom

,E

urop

e7–

9L

owE

F:“L

oww

orki

ngm

emor

y”W

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

17)

Pass

ive

cont

rol

(n�

30)

Inhi

bito

ryco

ntro

l(1

mea

sure

):C

ontr

ast

11.

CPT

(com

mis

sion

erro

r)

Dun

ning

2013

Uni

ted

Kin

gdom

,E

urop

e7–

9L

owE

F:“L

oww

orki

ngm

emor

y”W

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

31)

Act

ive

cont

rol

(n�

29)

Inhi

bito

ryco

ntro

l(1

mea

sure

):C

ontr

ast

21.

CPT

(com

mis

sion

erro

r)

Ege

land

2013

Nor

way

,E

urop

e10

–12

Dia

gnos

ed:

AD

HD

Wor

king

mem

ory

trai

ning

:“C

ogm

edW

orki

ngM

emor

yT

rain

ing:

Rob

oMem

o”(n

�33

)

Pass

ive

cont

rol

(n�

34)

Inhi

bito

ryco

ntro

l:1.

Col

orw

ord

test

2.C

ontin

uous

Perf

orm

ance

Tes

t—H

yper

activ

ity-I

mpu

lsiv

ityC

ogni

tive

Flex

ibili

ty1.

Tra

ilm

akin

gte

st(T

ask

4—di

vide

dat

tent

ion)

Kar

bach

2009

Ger

man

y,E

urop

e8–

10T

ypic

ally

deve

lopi

ngC

ogni

tive

flex

ibili

tytr

aini

ng:

“Tas

k-sw

itchi

ngtr

aini

ng”

(n�

14)

Act

ive

cont

rol

(n�

14)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

11.

Mix

ofre

adin

gsp

anan

dco

untin

gsp

an2.

Mix

ofsy

mm

etry

span

and

navi

gatio

nsp

anIn

hibi

tory

cont

rol

(1m

easu

re):

1.M

ixof

colo

ran

dnu

mbe

rSt

roop

task

Kar

bach

2009

Ger

man

y,E

urop

e8–

10T

ypic

ally

deve

lopi

ngC

ogni

tive

flex

ibili

tytr

aini

ng:

“Tas

k-sw

itchi

ngtr

aini

ng�

verb

alse

lf-i

nstr

uctio

ns”

(n�

14)

Act

ive

cont

rol

(n�

14)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

21.

Mix

ofre

adin

gsp

anan

dco

untin

gsp

an2.

Mix

ofsy

mm

etry

span

and

navi

gatio

nsp

anIn

hibi

tory

cont

rol

(1m

easu

re):

1.M

ixof

colo

ran

dnu

mbe

rSt

roop

task

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

176 KASSAI, FUTO, DEMETROVICS, AND TAKACS

Tab

le2

(con

tinu

ed)

Firs

tau

thor

Publ

icat

ion

year

Plac

eA

ge(i

nye

ars)

Clin

ical

stat

usof

the

sam

ple

Inte

rven

tion

cond

ition

Con

trol

cond

ition

Out

com

em

easu

re

Kar

bach

2009

Ger

man

y,E

urop

e8–

10T

ypic

ally

deve

lopi

ngC

ogni

tive

flex

ibili

tytr

aini

ng:

“Sw

itch

trai

ning

�ve

rbal

inst

ruct

ions

�va

riab

letr

aini

ng”

(n�

14)

Act

ive

cont

rol

(n�

14)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

31.

Mix

ofre

adin

gsp

anan

dco

untin

gsp

an2.

Mix

ofsy

mm

etry

span

and

navi

gatio

nsp

anIn

hibi

tory

cont

rol

(1m

easu

re):

1.M

ixof

colo

ran

dnu

mbe

rSt

roop

task

Klin

gber

g20

05Sw

eden

,E

urop

e7–

12D

iagn

osed

:A

DH

DW

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

20)

Act

ive

cont

rol

(n�

24)

Inhi

bito

ryco

ntro

l(1

mea

sure

):1.

Stro

opte

st

Tho

rell

2009

Swed

en,

Eur

ope

4–5

Typ

ical

deve

lopi

ngW

orki

ngm

emor

ytr

aini

ng:

“Cog

med

Wor

king

Mem

ory

Tra

inin

g:R

oboM

emo”

(n�

17)

Act

ive

cont

rol

(n�

14)

Inhi

bito

ryco

ntro

l(2

mea

sure

s):

Con

tras

t1

1.D

ay-N

ight

Stro

opT

ask—

erro

r2.

Go/

No-

Go

Tas

k—co

mm

issi

oner

ror

Tho

rell

2009

Swed

en,

Eur

ope

4–5

Typ

ical

lyde

velo

ping

Wor

king

mem

ory

trai

ning

:“C

ogm

edW

orki

ngM

emor

yT

rain

ing:

Rob

oMem

o”(n

�17

)

Pass

ive

cont

rol

(n�

16)

Inhi

bito

ryco

ntro

l(2

mea

sure

s):

Con

tras

t2

1.D

ay-N

ight

Stro

opT

ask—

erro

r2.

Go/

No-

Go

Tas

k—co

mm

issi

oner

ror

Tho

rell

2009

Swed

en,

Eur

ope

4–5

Typ

ical

lyde

velo

ping

Inhi

bito

ryco

ntro

ltr

aini

ng:

“Cog

med

Inhi

bitio

nT

rain

ing:

Rob

oMem

o”(n

�18

)

Act

ive

cont

rol

(n�

14)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

31.

Span

Boa

rdT

ask

(WA

IS-R

-NI)

2.W

ord

Span

Tas

k

Tho

rell

2009

Swed

en,

Eur

ope

4–5

Typ

ical

lyde

velo

ping

Inhi

bito

ryco

ntro

ltr

aini

ng:

“Cog

med

Inhi

bitio

nT

rain

ing:

Rob

oMem

o”(n

�18

)

Pass

ive

cont

rol

(n�

15)

Wor

king

mem

ory

(2m

easu

res)

:C

ontr

ast

41.

Span

Boa

rdT

ask

(WA

IS-R

-NI)

2.W

ord

Span

Tas

k

Tra

vers

o20

15It

aly,

Eur

ope

5T

ypic

ally

deve

lopi

ngW

orki

ngm

emor

yan

din

hibi

tory

cont

rol

trai

ning

:“E

Fpr

omot

ing

smal

lgr

oup

prog

ram

–C

hicc

oan

dN

ana”

(n�

32)

Pass

ive

cont

rol

(n�

43)

Cog

nitiv

efl

exib

ility

(1m

easu

re):

1.G

o/N

o-G

o(s

hift

ing

phas

e)2.

Dot

sta

sk

Vol

ckae

rt20

15B

elgi

um,

Eur

ope

4–5

Typ

ical

lyde

velo

ping

Inhi

bito

ryco

ntro

ltr

aini

ng:

“Inh

ibiti

ontr

aini

ng”

(n�

24)

Act

ive

cont

rol

(n�

23)

Wor

king

mem

ory

(1m

easu

re):

1.M

ixof

Cat

egos

pan,

Wor

dsSp

an,

Blo

ckta

ppin

gte

st(W

orki

ngm

emor

yfa

ctor

)C

ogni

tive

flex

ibili

ty(1

mea

sure

):1.

Mix

ofT

raff

iclig

hts

Hea

d-T

oes-

Kne

es-S

houl

ders

Mon

ster

Stro

op(F

lexi

bilit

yfa

ctor

)

Won

g20

14C

hina

,A

sia

6–12

Low

EF:

“Low

wor

king

mem

ory”

Wor

king

mem

ory

trai

ning

:“C

ompu

teri

zed

wor

king

mem

ory

trai

ning

”(n

�26

)

Pass

ive

cont

rol

(n�

25)

Inhi

bito

ryco

ntro

l(1

mea

sure

):1.

Stro

opta

sk

Not

e.A

DH

D�

atte

ntio

n-de

fici

t/hyp

erac

tivity

diso

rder

;A

SD�

autis

msp

ectr

umdi

sord

er;

EF

�ex

ecut

ive

func

tion.

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

177TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

memory and counting training were contrasted to the results of theparticipants of the counting training (active control) and to thosewho did not participated in any intervention (passive control; for asimilar procedure see: Bakermans-Kranenburg, van IJzendoorn, &Juffer, 2003; Mol, Bus, de Jong, & Smeets, 2008; Takacs, Swart,& Bus, 2015).

Meta-Analytic Procedures

We used the software Comprehensive Meta-Analysis (CMA),Version 3.0 (Borenstein, Hedges, Higgins, & Rothstein, 2005) tocalculate the effect size for each contrast for the standardized meandifference between the intervention and the control conditions,which was the dependent variable in the present meta-analysis. Wechose the effect size of Hedges’ g over Cohen’s d because itcorrects for small sample sizes (Borenstein, Hedges, Higgins, &Rothstein, 2009). A positive effect size reflected the advantage ofthe intervention condition, while a negative effect suggested thatthe control condition outperformed the intervention group. Forcalculating the effect sizes, the raw means and standard deviationson the posttests in the intervention and the control groups wereused or other statistics regarding the difference between the twogroups on the posttest (e.g., t- or F-statistics). When more than oneappropriate outcome measure was reported in a study, we calcu-lated effect sizes for all of those. The software takes the average ofthe effect sizes found on all outcome measures per study beforetaking the average over all contrasts; thus, these measures are notconsidered independent. The results were scanned for outliers witha standardized residual exceeding �3.29 (Tabachnik & Fidell,2007).

We conducted two meta-analyses: one for the near-transfer andone for the far-transfer effect. Thus, we tested the effects oftraining an executive function component on that specific compo-nent in the first model, and the effects of training an executivefunction component on the untrained components. Because therewas a wide range of different samples, interventions, and outcomemeasures, we used the random-effects model to calculate theaverage effect sizes. The random-effects model allows for suchbetween-study variance (Borenstein et al., 2009). Under this modelthe average effect size is calculated after weighting the contrastsby the inverse of the sampling error. Thus, studies with largersamples weigh more into the average. We conducted retrospectivestatistical power calculations to assess whether we had sufficientpower for testing the average near- and far-transfer effects. Wefound that statistical power was above 80% in both cases, using thevariance estimates found in the analyses, to show a small effect of0.20 (Borenstein et al., 2009).

It is plausible that there is an effect whether, for instance,children practice on a computer during the intervention and havenoncomputerized tests as outcome measures. Thus, we calculatedthe near- and far-transfer effects when the medium of the inter-vention and the outcome measure was congruent (both applied onthe computer or both were noncomputer based) and when not.Results were very similar, therefore the effect of medium was notconsidered further.

Additionally, we inspected the average near- and far-transfereffects on each component separately. Further, the Q-statistics wasutilized to calculate the heterogeneity of the average effect sizes. Asignificant Q-value indicates a heterogeneous effect. Finally, we

selected the contrasts in which they only trained a single compo-nent and assessed the effect on the untrained components sepa-rately in order to conduct fine-grained analyses regarding thespecific relations among the components.

In order to assess the effects of differences between theprimary studies that might have an influence on the results suchas the clinical status and the age of the sample, the length of theintervention, whether the study utilized an active or a passivecontrol condition, the year of publication, or the continentthe study was conducted in, subgroup analyses were planned tobe conducted in order to compare the contrasts based on cate-gorical moderator variables (e.g., clinical status of the sample),while metaregression was planned in case of continuous vari-ables (e.g., publication year) in both meta-analyses. Moderatorvariables had to have at least four contrasts in each category to sufficefor testing statistical significance (Bakermans-Kranenburg et al.,2003). Moreover, power analyses for the moderator and metare-gression analyses were conducted (Hedges & Pigott, 2004). Thatis, because a nonsignificant effect could reflect the lack of statis-tical power instead of truly no effect (Hedges & Pigott, 2004). Infact, power estimates showed low power for all moderator vari-ables except for the mean age of the sample, the number ofintervention sessions, and the year of publication in case of thefar-transfer effect. Thus, we decided to report preliminary descrip-tive results instead of statistical testing when the analysis wasunderpowered: the average effects in the different categories with-out statistically contrasting them for subgroup analyses and regres-sion coefficients without the corresponding p value for metare-gression analyses.

Publication bias was inspected in both sets of studies becausestudies with significant results are more likely to be published.Thus, significant findings are more likely to be included in ameta-analysis and this tendency may lead to an overestimationof the average effect size (Rothstein, Sutton, & Borenstein,2006). Moreover, Rosenthal’s fail-safe n was calculated, whichis an estimate regarding how many missing studies with a nullfinding would be needed for the average effect size to turnnonsignificant. In case of a robust effect, this fail-safe numbershould exceed 5k � 10 where k is the number of contrastsincluded (Rosenthal, 1979).

Finally, we conducted an additional meta-analysis to be able todirectly compare the near- and far-transfer effects. We selected thestudies that reported on both near- and far-transfer measures andcalculated the standardized mean difference between the near- andfar-transfer effect sizes found in each study, which was the depen-dent variable in this final analysis. In case there were more thanone near- or far-transfer measures, we took the average effect. Apositive effect size in this analysis showed that the near-transfereffect was larger, while a negative effect suggested a larger far-transfer effect.

Results

Preliminary Analyses

Near-transfer effect. There was one outlying contrast in themodel that was excluded (Kloo & Perner, 2003). The extremelylarge effect size in that study might be due to the fact that theoutcome measure was very similar to the intervention task. In fact,

Thi

sdo

cum

ent

isco

pyri

ghte

dby

the

Am

eric

anPs

ycho

logi

cal

Ass

ocia

tion

oron

eof

itsal

lied

publ

ishe

rs.

Thi

sar

ticle

isin

tend

edso

lely

for

the

pers

onal

use

ofth

ein

divi

dual

user

and

isno

tto

bedi

ssem

inat

edbr

oadl

y.

178 KASSAI, FUTO, DEMETROVICS, AND TAKACS

the same paradigm was used but with different stimuli. Thus, theaverage effect of near-transfer was calculated based on the resultsof 35 studies including 43 contrasts with 2,402 children in totalbetween the ages of 2 and 11 years shown in Table 1. The studieswere published between 2001 and 2016. Thirty-nine contrasts werepeer-reviewed journal articles and four of the contrasts were foundin nonrefereed reports such as doctorate dissertations. The studieswere geographically dispersed: 27 contrasts were from Europe, 10from North America, three from Australia, two from Asia, and onefrom South America. From the 43 contrasts, 25 used a typicallydeveloping sample of children, while 18 sampled children witheither a clinical diagnosis or behavioral problems reported byparents or teachers. In 23 of the contrasts, the intervention wascompared with an active control condition. In 15 contrasts, apassive control group was used, while in five studies the results ofthe intervention group were compared with both kinds of controlgroups.

Twenty-seven of these contrasts used a single-componenttraining program: In 19 contrasts working memory skills, infive contrasts inhibitory control, and in five contrasts cognitiveflexibility were trained. Additionally, there were 16 contrastsutilizing a training in which more than one of the componentswere trained: Three contrasts included an intervention for work-ing memory and inhibition and in three contrasts they trainedinhibition and flexibility and in 11 contrasts all three compo-nents were targeted.

For assessing potential bias, we planned to conduct subgroupand metaregression analyses. We could not test the moderator ofthe continent the study was conducted in because not all categorieshad at least four contrasts (Europe: g� � 0.50, k � 27, SE � 0.08,95% CI [0.35, 0.66], p � .001; North America: g� � 0.30, k � 10,SE � 0.11, 95% CI [0.09, 0.51], p � .01; Asia: g� � 0.50, k � 2,SE � 0.22, 95% CI [0.07, 0.94], p � .02; South America: Hedges’g � 0.15, k � 1, SE � 0.20, 95% CI [�0.24, 0.54], p � .45;Australia: g� � 0.40, k � 3, SE � 0.19, 95% CI [0.04, 0.77], p �.03).

Studies with children who were diagnosed with a neurodevel-opmental disorder or showed behavioral problems had an effectsize of g� � 0.39, k � 18, SE � 0.08, 95% CI [0.22, 0.55], p �.001, while studies with typically developing samples showed asimilar result, g� � 0.47, k � 25, SE � 0.08, 95% CI [0.31, 0.63],p � .001. Studies using an active control group had an averageeffect size of g� � 0.38, k � 28, SE � 0.06, 95% CI [0.27, 0.49],p � .001, while contrasts utilizing a passive control group showeda standardized mean difference of g� � 0.45, k � 20, SE � 0.11,95% CI [0.24, 0.65], p � .001. The mean age of the sample(coefficient: �0.02, SE � 0.03, 95% CI [�0.08, 0.03]), the num-ber of intervention sessions (coefficient: �0.003, SE � 0.01, 95%CI [�0.02, 0.01]), and the year of publication (coefficient: �0.03,SE � 0.02, 95% CI [�0.07, 0.01]) had very small relationshipswith the effect size.

According to the visual examination of the funnel plot, therewas no asymmetry around the average effect size and therefore thepresent results did not seem to be affected by a possible publica-tion bias. Moreover, the fail-safe number was found to be 1,126,which suggests a robust effect in case of 43 contrasts.

Far-transfer. Far-transfer effect was assessed based on 16studies including 17 contrasts with the data of 810 children in totalbetween the ages of 3 to 12 years shown in Table 2. All the studies

were peer-reviewed journal articles, published between 2000 and2015. Again, the set of the studies was geographically diverse:Data for 13 contrasts was collected in Europe, two in Australia,one in North America, and one in Asia. From these contrasts, fivefocused on typically developing children, while 12 used either adiagnosed (ADHD, autism spectrum disorder [ASD]) sample orchildren whose parents or teachers reported behavioral problems.Twelve contrasts compared the training with an active controlcondition, seven with a passive control condition, while in twostudies the results of the intervention group were compared withboth kinds of control groups. In nine contrasts, the training focusedon working memory skills, in two contrasts on inhibitory skills, infive contrasts on cognitive flexibility, while only in three contraststhey trained more than one component (that is, working memoryand inhibition in two contrast, and inhibition and flexibility in onecontrast).

We could not test the effect of continent as a moderator becausethere were not enough contrasts in each category (Europe: g� �0.18, k � 13, SE � 0.08, 95% CI [0.02, 0.33], p � .02; Australia:g� � �0.28, k � 2, SE � 0.41, 95% CI [�1.08, 0.52], p � .49;North America: Hedges’ g � �0.02, k � 1, SE � 0.22, 95% CI[�0.44, 0.40], p � .93; Asia: Hedges’ g � �0.30, k � 1, SE �0.28, 95% CI [�0.85, 0.24], p � .28).

Studies that included clinical samples or children whoshowed behavioral problems had an effect size of g� � 0.08,k � 12, SE � 0.08, 95% CI [�0.08, 0.24], p � .31, whilestudies with typically developing samples showed an averageeffect size of g� � 0.20, k � 5, SE � 0.14, 95% CI [�0.07,0.47], p � .15. Studies using an active control group had anaverage effect size of g� � 0.13, k � 12, SE � 0.08, 95% CI[�0.03, 0.29], p � .11, while contrasts utilizing a passivecontrol group also showed an effect of g� � 0.06, k � 7, SE �0.13, 95% CI [�0.19, 0.30], p � .66.

However, due to sufficient estimated statistical power, we testedthe effects of the mean age, the number of intervention sessions,and the year of publication in metaregression analyses; neither ofthese variables had a significant effect on the effect size (mean ageof the sample: coefficient: 0.006, SE � 0.03, 95% CI [�0.06,0.07], p � .86; number of intervention sessions: coefficient:�0.001, SE � 0.01, 95% CI [�0.02, 0.02], p � .88; year ofpublication: coefficient: �0.01, SE � 0.02, 95% CI [�0.05, 0.03],p � .75).

Assessing the funnel plot, the studies were evenly distributedaround the average effect size suggesting no evidence of pub-lication bias. As the average effect was not significant, thefail-safe n estimate was meaningless. No outlying contrastswere found.

Near-Transfer Effect

To test our first hypotheses, we calculated the average effectsize in the first meta-analysis for the difference between theintervention and the control conditions on the executive func-tion component(s) that were trained in the intervention. Asshown in Table 3, a significant moderate overall effect (g� �0.44) was found, which was heterogeneous, Q (42) � 75.62,p � .001 (see Figure 1 for the forest plot). When inspecting theresults separately for the three components, near-transfer ef-fects were significant on each of them. There was a medium-

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179TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

sized near-transfer effect on working memory (g� � 0.50),while the effects were small on the other two components(inhibitory control: g� � 0.24, cognitive flexibility: g� �0.37).

As a second step, we tested whether single-component trainingshad a different near-transfer effect as compared with multicompo-nent interventions. This was done because it is plausible that anintervention that is more focused on training one skill is moreeffective than aiming an intervention to foster more skills at a time.Single-component working memory trainings and multicomponentinterventions including working memory training had similar near-transfer effects on working memory (single-component: g� �

0.54, k � 19, SE � 0.10, 95% CI [0.35, 0.72], p � .001;multicomponent: g� � 0.42, k � 12, SE � 0.11, 95% CI [0.20,0.63], p � .001). Similarly, single-component inhibition trainingshad similar near-transfer effects on inhibition as compared withmulticomponent interventions including inhibitory control training(single-component: g� � 0.18, k � 5, SE � 0.15, 95% CI [�0.11,0.47], p � .21; multicomponent: g� � 0.25, k � 15, SE � 0.07,95% CI [0.12, 0.39], p � .001). Finally, single-component flexi-bility trainings had a similar near-transfer effect on flexibilitymeasures as multicomponent interventions including flexibilitytraining (single-component: g� � 0.51, k � 5, SE � 0.25, 95% CI

Table 3Near- and Far-Transfer Effects on the Different Executive Function Components

Outcome measure Transfer effectNumber of contrasts

(k)Average effect size

(g�)Standard error

(SE)95% confidence

interval p

Overall Near-transfer 43 .44 .06 [.32, .55] �.001Far-transfer 17 .11 .07 [�.03, .25] .11

Working memory Near-transfer 31 .50 .07 [.35, .64] �.001Far-transfer 6 �.01 .15 [�.31, .29] .94

Inhibitory control Near-transfer 20 .24 .06 [.12, .36] �.001Far-transfer 13 .11 .09 [�.06, .28] .21

Cognitive flexibility Near-transfer 14 .37 .09 [.19, .54] �.001Far-transfer 7 .15 .10 [�.05, .34] .14

Study name Statistics for each study Sample size

Hedges's Standard Lower Upper g error Variance limit limit Z-Value p-Value Interv ention Control

Lomas (2001) -0,190 0,352 0,124 -0,879 0,500 -0,539 0,590 16 15Dörrenbacher (2014) -0,127 0,383 0,146 -0,878 0,623 -0,333 0,739 14 13Markomichali (2015) - Chapter 6 -0,056 0,324 0,105 -0,690 0,578 -0,172 0,863 19 18Markomichali (2015) - Chapter 5 -0,005 0,388 0,151 -0,766 0,756 -0,013 0,990 12 13de Vries (2015) 0,017 0,261 0,068 -0,494 0,529 0,067 0,947 29 29Alloway (2012) 0,141 0,269 0,072 -0,386 0,668 0,525 0,600 24 32Thorell (2009) 0,148 0,345 0,119 -0,528 0,823 0,428 0,669 18 15Goldin (2014) 0,151 0,199 0,040 -0,239 0,541 0,759 0,448 73 38Re (2015) A 0,166 0,469 0,220 -0,754 1,086 0,353 0,724 10 10Kyttala (2015) 0,175 0,305 0,093 -0,422 0,772 0,574 0,566 23 20Chacko (2014) 0,178 0,216 0,047 -0,245 0,602 0,826 0,409 44 41Bennett (2013) 0,218 0,421 0,177 -0,606 1,043 0,519 0,604 10 11Rõthlisberger (2001) B 0,233 0,249 0,062 -0,255 0,720 0,936 0,349 30 34Hovik (2013) 0,242 0,243 0,059 -0,234 0,717 0,996 0,319 33 34Schmitt (2013) 0,265 0,121 0,015 0,027 0,502 2,186 0,029 126 150Dovis (2015) 0,275 0,259 0,067 -0,234 0,783 1,059 0,289 30 30Tominey (2011) 0,279 0,249 0,062 -0,209 0,766 1,120 0,263 28 37Traverso (2015) 0,292 0,235 0,055 -0,168 0,753 1,244 0,214 32 43Rõthlisberger (2001) A 0,334 0,238 0,057 -0,132 0,800 1,405 0,160 33 38Howard (2016) A 0,339 0,311 0,097 -0,271 0,949 1,090 0,276 24 18Caviola (2009) 0,374 0,294 0,086 -0,201 0,949 1,274 0,203 22 24Rueda (2012) 0,397 0,326 0,106 -0,242 1,035 1,218 0,223 19 18Luo (2013) 0,406 0,361 0,130 -0,302 1,113 1,123 0,261 15 15Howard (2016) B 0,408 0,316 0,100 -0,211 1,028 1,292 0,196 19 21Volckaert (2015) 0,430 0,290 0,084 -0,139 0,999 1,481 0,139 24 23Dongen-Boomsma (2014) 0,434 0,302 0,091 -0,158 1,025 1,437 0,151 24 20Howard (2016) C 0,477 0,344 0,119 -0,198 1,152 1,385 0,166 19 15Re (2015) B 0,489 0,470 0,220 -0,431 1,409 1,042 0,298 10 10Wong (2014) 0,560 0,281 0,079 0,008 1,111 1,989 0,047 26 25Holmes (2009) 0,579 0,310 0,096 -0,029 1,187 1,868 0,062 22 20Bergman Nutly (2011) 0,607 0,282 0,080 0,053 1,160 2,148 0,032 26 25Blakey (2015) 0,609 0,275 0,076 0,071 1,148 2,217 0,027 26 28Bigorra (2015) 0,641 0,259 0,067 0,132 1,149 2,469 0,014 31 30St Clair-Thompson (2008) B 0,678 0,303 0,092 0,083 1,272 2,233 0,026 22 22Kroesbergen (2014) 0,682 0,341 0,117 0,012 1,351 1,996 0,046 15 21Dunning (2013) 0,757 0,257 0,066 0,252 1,261 2,941 0,003 34 30Espinet (2012) A 0,840 0,378 0,143 0,100 1,580 2,224 0,026 15 14Espinet (2012) B 0,858 0,384 0,148 0,104 1,611 2,231 0,026 14 14Klingberg (2005) 1,019 0,317 0,100 0,399 1,639 3,219 0,001 20 24Espinet (2012) C 1,079 0,342 0,117 0,408 1,750 3,152 0,002 20 18St Clair-Thompson (2010) 1,146 0,135 0,018 0,881 1,411 8,463 0,000 117 137St Clair-Thompson (2008) A 1,305 0,359 0,129 0,601 2,009 3,633 0,000 18 18Re (2007) 2,229 0,760 0,578 0,740 3,719 2,933 0,003 5 5

0,438 0,059 0,003 0,323 0,553 7,451 0,000

-1,00 -0,50 0,00 0,50 1,00

Fav ours control Fav ours interv ention

Near-transfer effect

Figure 1. Forest plot of the studies that assessed near-transfer effects.

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180 KASSAI, FUTO, DEMETROVICS, AND TAKACS

[0.02, 1.01], p � .04; multicomponent: g� � 0.31, k � 9, SE �0.08, 95% CI [0.16, 0.47], p � .001).

Far-Transfer Effect

Far-transfer effect was tested in the second meta-analysis bycomputing the average standardized difference between the inter-vention and the control groups on the executive function compo-nents that were not trained in the interventions. As shown in Table3 and Figure 2, the overall between-component far-transfer effectwas small and not significant. This effect was not heterogeneous,Q (16) � 15.39, p � .50. In the same vein, inspecting thefar-transfer effects on the components separately, there was nosignificant effect on any of the three components. In sum, com-ponents of executive function skills do not seem to be facilitatedunless directly trained.

The Effects of Single-Component Trainings

In order to further examine the specific relations between thethree components, we tested the far-transfer effects of single-component trainings on the other two untrained components. Afterexcluding the contrasts in the set of studies assessing far-transfereffects that targeted more than one component, there remained 22contrasts. As shown on Figure 3, there were no significant far-transfer effects among the components. However, it is important tonote that in most cases we had a very limited number of contraststo test the connections between the components and the issue ofstatistical power has to be considered. It might be interesting tonote that only one study (Volckaert & Noël, 2015) assessed theeffects of inhibitory control training on cognitive flexibility skillsand it showed a moderate effect, Hedges’ g � 0.55, SE � 0.29,95% CI [�0.02, 1.12], p � .06.

Comparing Near- and Far-Transfer Effects

Finally, in order to be able to statistically compare the near-and far-transfer effects, we conducted an additional meta-

analysis including only the 13 studies that reported on bothnear- and far-transfer measures (see Figure 4). We took theaverage near- and far-transfer effects found in each study andcalculated the effect size for the standardized mean differencebetween the two effects. There were 13 studies that could beincluded. The average effect was g� � 0.28 (SE � 0.09, 95%CI [0.11, 0.45], p � .001), which confirmed that on average thenear-transfer effect was significantly larger than the far-transfereffect.

Discussion

The present meta-analysis is a quantitative synthesis of theliterature on the near- and far-transfer effects among the three corecomponents of executive functioning: working memory, inhibitorycontrol, and cognitive flexibility in childhood. As a first step, weassessed whether training has a significant effect on tasks tappingon the same component but other than the ones explicitly trainedduring the intervention. Moreover, we tested if training a specificcomponent of executive functions has a significant transfer effecton any of the untrained components and whether this far-transfereffect is similar in size to the near-transfer effect observed in thecase of the trained component. Finally, we directly compared thenear- and far-transfer effects.

Overall, we found a significant, medium-sized near-transfereffect. However, no far-transfer effect appeared. More specifi-cally, there were significant near-transfer effects on all threecomponents: a moderate-sized effect on working memory andsmall-sized effects on inhibition and cognitive flexibility. Incontrast, no far-transfer effects were found on working mem-ory, inhibitory control, or flexibility. The finding that there wasa significant near-transfer effect excludes the possibility thatthe interventions in the primary studies were not effective intraining the components that they targeted. Instead, perfor-mance on the components that were trained did significantlyimprove, however, these gains did not transfer to the untrainedcomponents. No effects were found when we tested the specific

Study name Statistics for each study Sample size

Hedges's Standard Lower Upper g error Variance limit limit Z-Value p-Value Intervention Control

Dowsett (2000) A -0,487 0,567 0,321 -1,598 0,625 -0,858 0,391 7 5Thorell (2009) -0,384 0,356 0,127 -1,082 0,314 -1,079 0,281 18 15Wong (2014) -0,301 0,277 0,077 -0,845 0,243 -1,085 0,278 26 25Bigorra (2015) -0,085 0,255 0,065 -0,585 0,415 -0,333 0,739 31 30Dowsett (2000) B -0,057 0,592 0,350 -1,217 1,102 -0,097 0,923 8 4Chacko (2014) -0,020 0,215 0,046 -0,441 0,401 -0,092 0,926 44 41Dovis (2015) 0,000 0,259 0,067 -0,508 0,508 0,000 1,000 28 30de Vries (2015) 0,002 0,254 0,064 -0,495 0,499 0,009 0,993 33 29Karbach (2009) 0,056 0,370 0,137 -0,670 0,781 0,150 0,881 14 14Blakey (2015) 0,114 0,269 0,072 -0,412 0,641 0,426 0,670 26 28Dongen-Boomsma (2014) 0,161 0,310 0,096 -0,447 0,769 0,519 0,604 23 18Egeland (2013) 0,175 0,243 0,059 -0,301 0,651 0,722 0,471 33 34Dörrenbacher (2014) 0,204 0,384 0,148 -0,549 0,957 0,532 0,595 13 13Dunning (2013) 0,350 0,267 0,071 -0,174 0,873 1,309 0,191 31 26Traverso (2015) 0,376 0,234 0,055 -0,082 0,835 1,610 0,107 32 43Volckaert (2015) 0,395 0,290 0,084 -0,174 0,964 1,360 0,174 24 23Klingberg (2005) 0,840 0,311 0,096 0,232 1,449 2,706 0,007 20 24

0,112 0,070 0,005 -0,025 0,249 1,602 0,109

-1,00 -0,50 0,00 0,50 1,00

Favours control Favours intervention

Far-transfer effect

Figure 2. Forest plot of the studies that assessed far-transfer effects.

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181TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

far-transfer effects of single-component trainings either. In linewith the results of Melby-Lervåg and Hulme (2013) and Salaand Gobet (2017), who found no significant transfer effect ofworking memory trainings on inhibitory control in child sam-ples, we also revealed no transfer effect of working memorytrainings on inhibitory control. The only study where a single-component training had marginally significant far-transfer ef-fect was a preliminary result based on only one contrast (Vol-ckaert & Noël, 2015) revealing that training inhibition mighthave an ameliorating effect on cognitive flexibility. However, itis important to note that in this study the flexibility outcomemeasures used were based on typical inhibitory control tests(e.g., the traffic lights task, the head-toes-knees-shoulders task,a semantic Stroop-test [Monster Stroop]), at the end of whichthey added an extra block that required switching between thepreviously practiced rules. Thus, these measures might be

somewhat similar to the inhibitory control games that werepracticed during the intervention. In sum, the present resultsneither confirm nor disprove the conclusions of Diamond andLing (2016) who showed in a narrative literature review that theeffects of computerized working memory training do not trans-fer to self-control or flexibility.

The lack of far-transfer effect found in the present meta-analysiseven within the set of executive function skills makes it—thoughlogically not impossible—still highly unlikely that training uniqueexecutive functions could have measurable ameliorating transfereffect on more distantly related and complex constructs, such asacademic and social skills (Blair & Razza, 2007) that rely just asmuch on the trained executive function component as on the otheruntrained and largely unaffected components. The results of thepresent meta-analysis therefore provide a possible explanation forthe previously found absence of far-transfer effects of working

Figure 3. The specific training effects among the three executive function components in childhood. Contin-uous lines show significant effects, dotted lines signal nonsignificant effects, while the broken line suggests asignificant result that is based on only one study.

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182 KASSAI, FUTO, DEMETROVICS, AND TAKACS

memory trainings on academic skills (Melby-Lervag & Hulme,2013; Melby-Lervåg et al., 2016; Sala & Gobet, 2017).

The present meta-analysis shows that there are limited practicalbenefits—other than on the trained component—of training singleexecutive function components in childhood. Thus, it might bemore advisable, both in the educational and in the clinical practice,to use approaches that target multiple executive function compo-nents.

Most moderator analyses were underpowered in the presentmeta-analyses. Thus, those results should be interpreted with cau-tion. For instance, considering the wide age range of the samplesin the primary studies of the present meta-analysis (2–12 years),we intended to test the effect of children’s age. The patternsuggested a very weak relationship between age and the effectsizes. However, considering the lack of statistical power in case ofthe near-transfer effect, we cannot draw firm conclusions. Furtherstudies are needed to clarify the connection between age and thestrength of near- and far-transfer effects among executive functioncomponents.

Beyond the practical implications of the present meta-analysis, it might also raise issues on the construct of executivefunctioning in childhood on a theoretical level. The lack ofcausal evidence for significant relationships among the threecore components might contradict accounts of executive func-tions as a single construct (Wiebe et al., 2008) or a unitaryconstruct with dissociable components (Miyake et al., 2000).Instead the present results seem to support the notion thatworking memory, inhibitory control, and cognitive flexibilityare mutually independent constructs and suggest that the cor-relations among them (Bull & Scerif, 2001; Carlson et al., 2002;Hughes, 1998; Senn et al., 2004; St. Clair-Thompson & Gath-ercole, 2006; Wiebe et al., 2008) might simply reflect co-occurrences. For example, the three components might simplybe maturing in a parallel timeframe as a consequence of theircommon neural correlates. Alternatively, there might be a pos-sible third variable such as verbal or nonverbal IQ or socioeco-nomic status that results in observable correlations among thecomponents. Another possibility is that there might be a com-

mon component that the three executive skills share, whichmight not be sufficiently affected by training single compo-nents. This latter account could result in a lack of transfer effectobserved even in case a unitary executive function constructexisted.

Limitations

Several problems emerge with measuring executive func-tions. First, the issue of task impurity means that most executivetasks do not exclusively tap on the executive functions ofinterest, but also on other executive and nonexecutive processes(Miyake et al., 2000). An example for the first is the Wisconsincard sorting task, which is a widely used measure of cognitiveflexibility as it requires switching between rules. However, inorder to switch between the rules, inhibition skills are alsorequired to restrain acting according to the previously used,now inappropriate rule. Examples for the second are that scoreson a verbal fluency test can be biased by the participant’svocabulary skills, or performance on a Stroop test can beaffected by reading skills.

Second, we face the problem of (what could be called)“component impurity” meaning, that the correlation betweendifferent tasks that are believed or intended to measure the sameexecutive functions components tend to be low to moderate(see, e.g., Miyake et al., 2000). Therefore, in case of ourmeta-analytic study on interventions that aimed to analyze thetransfer effects of training executive functions, the effect sizesmight be weakened by the relatively low correlations betweenthe within-component tasks. This problem could have beenalleviated by using “latent variables” (proposed by Miyake etal., 2000), variables that have been created by statistically“extracting” the “overlap” among tasks intended to measure thesame EF component. However, in our case this could not bedone as primary studies reported on performance on singletests. Further, because all measurable tasks have only a partialoverlap with the hypothetical background construct that theyaim to measure, the effects of training task “A” only partially

Study name Statistics for each study

Hedges's Standard Lower Upper g error Variance limit limit Z-Value p-Value Total

Dörrenbacher (2014) -0,322 0,372 0,139 -1,052 0,408 -0,865 0,387 27Traverso (2015) -0,083 0,232 0,054 -0,538 0,372 -0,358 0,720 75de Vries (2015) 0,015 0,254 0,064 -0,482 0,513 0,060 0,953 58Volckaert (2015) 0,035 0,286 0,082 -0,525 0,594 0,121 0,904 47Klingberg (2005) 0,176 0,308 0,095 -0,428 0,779 0,570 0,568 44Chacko (2014) 0,196 0,213 0,046 -0,222 0,615 0,920 0,358 85Dongen-Boomsma (2014) 0,268 0,301 0,090 -0,322 0,857 0,890 0,373 44Dovis (2015) 0,271 0,256 0,066 -0,230 0,773 1,060 0,289 60Dunning (2013) 0,402 0,259 0,067 -0,105 0,910 1,553 0,120 64Blakey (2015) 0,488 0,268 0,072 -0,037 1,013 1,821 0,069 54Thorell (2009) 0,519 0,342 0,117 -0,151 1,190 1,517 0,129 33Bigorra (2015) 0,717 0,254 0,065 0,218 1,215 2,820 0,005 61Wong (2014) 0,848 0,275 0,076 0,308 1,387 3,081 0,002 51

0,279 0,086 0,007 0,110 0,448 3,234 0,001

-1,00 -0,50 0,00 0,50 1,00

Favours far-transfer Favours near-transfer

Figure 4. Forest plot of the studies in which we could directly compare the near- and far-transfer effects.

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183TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

transfers to the background construct, which only has a partialoverlap with task “B,” which further weakens the measurableeffect of training task “A” on the performance on task “B.”Finally, it is also problematic that different tests are used withdifferent age groups and it is questionable how comparablethose are.

Further, when analyzing the effects of training certain exec-utive function components, it would have been very useful tohave an intervention check, for example, to have data availableon the difference between the scores on a specific task at thebeginning and at the end of the training. The sizes of themeasured near- and far-transfer effects would have been moremeaningful if compared with this original measurement on the“effectiveness of training.”

As mentioned above, it was difficult to gather data on single-component trainings. Training multiple executive functions com-ponents at once might actually decrease the duration of the trainingof one specific executive function component, therefore potentiallylowering the effectiveness of the training on that specific compo-nent, which eventually can lead to an underestimation of thetransfer effects. Available data on the duration and intensity of thetraining of specific executive function components would havebeen useful.

In the same vein, although we could locate enough contrasts totest the near- and far-transfer effects of the trainings on a compo-nent, fine-grained analyses regarding the specific relationshipsamong the specific components lacked more studies for a robustsynthesis thus only allowing for preliminary results.

Conclusions

The results of the present meta-analysis provide an importantcontribution to our knowledge about training executive functionsin childhood. Our meta-analytic findings show that it is possible toimprove children’s executive functions. However, the findingsalso suggest that there is limited rationale for training a singlecomponent of executive functions in the clinical or educationalpractice, as these gains do not seem to transfer to untrainedcomponents. Thus, the practical relevance of training a singleexecutive function component, as it is the case for widespreadworking memory training programs like Cogmed, has very limitedpractical relevance when applied in the treatment of neuropsycho-logical disorders such as ADHD.

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Zelazo, P. D., & Carlson, S. M. (2012). Hot and cool executive function inchildhood and adolescence: Development and plasticity. Child Devel-opment Perspectives, 6, 354–360.

Appendix A

Search String

(Training OR intervention OR curricul� OR Mindful� OR medi-tat� OR sport� OR exercise OR physical activity OR aerobic� ORmartial OR yoga OR mindful� OR “tools of the mind” OR mon-tessori OR “Promoting Alternative Thinking Strategies” OR Cog-Meg OR “Head Start REDI” OR “Chicago School ReadinessProject”) AND (“cognitive control” OR “behavioral control” OR

“self-control” OR “effortful control” OR “self-regulat�” OR regu-lat� OR “executive functi�” OR attention OR “working memory”OR inhibit� OR planning OR “cognitive flexibility” OR “delayedgratification” OR monitoring) AND (child� OR student� OR tod-dler� OR preschooler� OR kindergartner�) AND (experiment� orquasi-experiment�)

(Appendices continue)

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187TRANSFER AMONG CHILDREN’S EXECUTIVE FUNCTIONS

Appendix B

Received November 27, 2017Revision received October 19, 2018

Accepted October 22, 2018 �

Full-text ar�cles excluded (n=52)

because the interven�on did not explicitly train an execu�ve func�on skill

Records iden�fied through database searching

Screening

Included

Eligibility

Iden�fica�on Addi�onal records found on the reference lists of included papers

and reviews

Records a�er duplicates removed (n=7284)

Records screened based on �tle and abstract

(n=7284)

Records excluded (n=7034)

Full-text ar�cles assessed for eligibility

(n=250)

Full-text ar�cles excluded (n = 160)

For the following reasons: not appropriate sample (n=31) not appropriate interven�on (n=23) only acute effects (n=19) no appropriate control condi�on or

not an experimental design (n=27) no appropriate outcome measure

(n=47) no sufficient sta�s�cs, even a�er

a�emp�ng to contact authors (n=13) Studies included in the

larger meta-analy�c project (n=90)

Studies included in the present meta-analysis

(n=38)

Figure B. PRISMA Flow Diagram. See the online article for the color version of this figure.

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188 KASSAI, FUTO, DEMETROVICS, AND TAKACS