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Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders among school-age children [], with a prevalence of 7.6% []. Meanwhile, according to Diagnostic and Statistical Manual of Mental Disorders Text Revision Fourth Edition [], the prevalence of ADHD in school-age children is 3% to 7% []. The 3 main categories of ADHD symptoms are inattention, hyperactivity, and impulsivity, which usually manifest in the school-age period []. These symptoms have detrimental impacts on the quality of life and functioning, including self-esteem, academic performance, social functioning, and relationship building []. ADHD is usually associated with long-term disability []. The types of treatments vary in different stages of life []. Behavioral parenting training and medication are the common approaches used to improve the behaviors and self-control of school-age children with ADHD []. ADHD medications are associated with an increased risk of headache, anxiety, and sleep disturbances [,]. Behavioral therapies are generally limited by time and space []. Therefore, feasible nonpharmacological approaches are recommended as alternatives to regulate the behaviors, executive functions, and well-being of children with ADHD.
In the last 10 years, human-computer interaction has widely been recognized in psychiatric and mental health research [,]. Digital technologies, neurofeedback systems, and virtual reality for health support, care, and treatment have increasingly been adopted, thus successfully gaining psychological health advantage [,]. ADHD is one of the common psychiatric disorders for which technology-based treatments are often used as therapeutic tools [,]. The application and effectiveness of technology-based interventions have been evaluated in ADHD treatment [,,]. The advantages of technology-based treatment include improved executive functions and increased physiological and mental well-being [,]. However, inconsistent results have been reported regarding the efficiency of technology-based intervention in school-age children with ADHD. Regarding ADHD behaviors, Dovis et al [], Egeland et al [], Steiner et al [], and van der Oord et al [] found that computer-based training improved the inattention and hyperactivity in children with ADHD. However, some studies did not find significant results between technological treatment and ADHD behaviors [-]. Regarding executive functions, technology-based treatments improved inhibition [], working memory [,], flexibility [,], emotional control [], initiation [], planning and organization [], organizing materials [], monitoring [], and metacognition [,]. However, several studies determined that technology-based interventions have no effect on executive functions [,,]. Regarding disruptive behavior disorder, Dovis et al [], Lim et al [], Steiner et al [], and van der Oord et al [] reported that computer-assisted training and neurofeedback training regulated oppositional defiant disorder and conduct disorder, whereas Bikic et al [] and Breider et al [] found no significant effect. Some studies have discovered that technology-based interventions can significantly improve visual attention [,,], yet numerous studies indicated no significant effects [,,,,]. These contradictory results make it difficult to examine the effectiveness of technology-based interventions in school-age children with ADHD.
Previous reviews illustrated the effectiveness of different types of technologies on children with ADHD [-]. Cibrian et al [] and Powell et al [] summarized this topic through a narrative description. Although Powell et al [] adopted a meta-analysis to synthesize previous studies, their research focused on the use of virtual reality among children and adolescents with ADHD.
ObjectiveThese existing studies based on nonrandomized, cross-sectional, and observational designs have added to the knowledge base and identified the potential implications of technology in enhancing the ability and functions of children. In addition, more randomized controlled trials (RCTs) have been conducted in the recent decade, as a growing number of researchers have shown interest in the use of technology-based interventions to improve the capability and well-being of children with ADHD. A meta-analysis of RCTs can provide strong and robust evidence regarding the effectiveness of technology-based interventions in improving children with ADHD. Therefore, a systematic review and meta-analysis of the existing evidence of RCTs are needed to explicate the advantages of technology to school-age children with ADHD.
This review focused on RCTs using technologies to regulate the ability and alleviate the well-being of children with ADHD. This review was registered in the PROSPERO International Prospective Register of Systematic Reviews (registration number CRD42023446924). The studies included in this review were searched from electronic databases, including PubMed, MEDLINE, ScienceDirect, Web of Science, CINAHL (via EBSCO), PsycINFO (via OVID), and Scopus, in April 2022. The keywords used in the search engines were as follows:
Population: “children with ADHD” or “school-age children with ADHD” or “students with ADHD”Intervention: “technology” or “computer” or “robots” or “virtual reality” or “VR” or “augmented reality” or “AR” or “web-based” or “serious games”Outcomes: “inattentive” or “hyperactive-impulsive” or “hyperactivity” or “impulsivity” or “executive functions” or “executive functioning” or “inhibition” or “working memory” or “emotional control” or “flexibility” or “attention” or “initiation” or “planning” or “organization” or “time management” or “metacognition” or “quality of life” or “performance”shows the full search strategy.
Eligibility CriteriaThe titles and abstracts of the selected papers were screened to identify relevant papers for this review. The analysis was performed using Population, Intervention, Control, and Outcomes framework (1) population: patients who were diagnosed with ADHD and aged between 6 and 12 years; (2) intervention: using technology (ie, the method of applying scientific knowledge for practical purposes) without restriction of technology type or frequency of intervention; (3) comparison: technology-based interventions for managing ADHD versus no interventions, interventions with placebo effect, and treatment as usual or waitlist control; and (4) outcome: behaviors, cognitive functions, and whole well-being evaluation results for patients with ADHD. Studies were selected using the following inclusion criteria: (1) articles published in English and (2) RCTs. Exclusion criteria included (1) teenagers, adults, and older adults; (2) comorbidity with autism spectrum disorder, psychosis, and affective or anxiety disorder; (3) consumption of toxic substances; (4) diagnosed with learning disorder; (5) non–peer reviewed studies; and (6) qualitative studies, reviews, cross-sectional studies, case studies, observational studies, study protocols, pre-post studies without a control group, or conference abstracts without full text. Furthermore, the references of the included papers were manually checked for eligibility. After removing duplicate articles, the studies were independently screened by 2 reviewers (KPW and BZ). The selected full-text articles were retrieved and reviewed by 4 reviewers (KPW, JQ, YJX, and BZ).
Quality AssessmentThe risk of bias in each study were independently evaluated by 3 reviewers (KPW, JQ, and BZ) using the Cochrane Collaboration tool for assessing the risk of bias []. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria were adopted for conducting this review []. demonstrates the PRISMA checklist. The criteria of the tool included (1) random sequence generation, (2) allocation concealment, (3) blinding of participants and personnel, (4) blinding of outcome assessment, (5) incomplete outcome data, (6) selective reporting, and (7) other bias. In addition, judgment has 3 levels, including “low risk of bias,” “high risk of bias,” and “unclear risk of bias.” The conflicting results were settled by 4 reviewers (KPW, JQ, YJX, and BZ) through discussion.
Data ExtractionThe information of the selected studies was extracted and coded into different categories, including study characteristics (first author’s name, publication year, country, and setting), characteristics of participants (sample size, sex, and age), intervention and control condition (type of technology used, frequency, length, and duration), outcome measurement (rating scale, test, and questionnaire), and result (mean and SD).
Data SynthesisData processing and analysis were conducted using the Review Manager Software RevMan (version 5.4), Cochrane Collaboration. The standardized mean difference (SMD) with a 95% CI was used to compute the effect size of the continuous outcomes of the interventions. The mean value of the baseline and posttest with SDs and the number of participants in the intervention groups and control groups were selected for the effect size calculation (ie, effect size of group differences). If reported, we selected the results estimated by the analysis of covariance, which treats individual baseline scores as covariates to correct for regression to baseline imbalanced means []. If the analysis of covariance had not been reported, change from baseline with SDs and posttest with SDs were selected. Multiple effect sizes were included in the same study, which contradicted the assumption that the effect sizes are independent of each other in the conventional meta-analytic procedures because the effect sizes in one study may be more correlated than those in other studies []. The results would become biased if this dependency was not considered. Hence, effect sizes assessed by the same measures were clustered to estimate the association between technology-based interventions and the conditions of school-age children with ADHD. The random effects model was applied in the meta-analysis, given the methodological diversity across the studies. Heterogeneity was measured using the I2 value (P<.10; I2>50%), and the higher the value of I2, the higher the level of heterogeneity. Subgroup analysis of parent-rated, teacher-rated, computer-rated, and self-rated results was performed, where applicable. To test moderating effects, 5 study-level characteristics, including the number of sessions, sample size, setting, game elements, and types of control group, were selected to calculate the meta-regression for each moderator.
A total of 2404 articles were retrieved from electronic databases. After removing duplicates, the titles and abstracts of 1568 articles were screened. In total, 1347 articles were excluded, and the remaining 221 articles were selected for full-text screening. At this stage, we excluded reviews (n=65), experimental studies (n=31), cross-sectional studies (n=21), longitudinal studies (n=25), qualitative studies (n=24), case studies (n=19), mixed methods studies (n=8), study protocols (n=4), RCT registrations (n=3), and non-English publications (n=2). Finally, 19 RCTs that met the inclusion and exclusion criteria were identified. A flowchart of the study selection process is shown in .
Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart of the study selection process. RCT: randomized controlled trial. Risk of BiasA low risk of random sequence generation was recorded from 8 trials (ie, the use of a computer random number generator and web-based system). Seven studies reported a low risk of allocation concealment. Meanwhile, 18 studies had a low risk of blinding participants and personnel. Although some studies had no complete blinding of participants and personnel [-,,,,,], the reviewers determined that the outcomes were not likely to be affected by a lack of blinding. Six studies were judged to have a low risk of blinding the outcome assessment. Seven studies indicated no blinding of assessors, and 6 studies did not clearly indicate the blinding of assessors. All studies were judged to have a low risk of incomplete outcome data because the attrition rate of all studies was <20%. All studies were judged to have a low risk of selective reporting, as nearly all studies had the protocol and all studies reported the primary and secondary outcomes. Ten studies described the way to manage missing data (ie, intention-to-treat analysis) [,-,,,,,]. The risk of bias assessment is shown in and [,-, ,,,,].
Figure 2. Risk of bias summary. 
Figure 3. Risk of bias graph. Study CharacteristicsFourteen studies used a 2-arm trials design [-,-,-], and the remaining 5 studies had a 3-arm trial design [,,,,]. These studies were conducted in 11 countries: Canada [], Denmark [], France [], Germany [,], Iran [], the Netherlands [,,], Norway [], Singapore [], Spain [,], Switzerland [], and the United States [,,,,].
Participants CharacteristicsA total of 1843 school-age children were included in this review, all of whom were diagnosed with ADHD. The number of participants included in each trial ranged from 10 to 246. Most studies were conducted in participants’ homes, and a small number of studies were conducted in schools, classrooms, and clinics. Detailed information is presented in .
Table 1. Participants’ characteristics of the selected studies (n=19).StudyCountrySettingSample size, nSex (female/male), n/nAge (years), mean (range)aAzami et al []IranParticipants’ home340/347-12Benzing and Schmidt []SwitzerlandParticipants’ home5110/4110.43 (8-12)Bigorra et al []SpainParticipants’ home6636/248.9Bikic et al []DenmarkParticipants’ home7011/599.96Bioulac et al []FranceNo mention5110/418.9Breider et al []NetherlandsParticipants’ home216/157.76Corkum et al []CanadaClassroom-based587/518.83 (6-12)Dovis et al []NetherlandsHome-based training8918/7110.50Egeland et al []NorwaySchool6718/4910.4Fried et al []The United StatesParticipants’ home33388/2459.13Gevensleben et al []GermanyNo mention9417/779.21Kofler et al []The United StatesOffice and participants’ home5412/4210.41Kollins et al []The United StatesParticipants’ home348100/2489.65Lim et al []SingaporeClinic17225/1478.6Meyer et al []The United StatesHome4012/2810.15Moreno-García et al []SpainHome and school5713/448.84Steiner et al []The United StatesClassroom10434/708.56van der Oord et al []NetherlandsHome407/339.75Wangler et al []GermanyNo mention9417/779.64aIf studies did not provide mean values and/or ranges for participant ages, this information was not shown in the table.
Technology-Based Intervention and Control ConditionDifferent types of technologies were adopted in the intervention group among the included studies, including computer-assisted training programs, neurofeedback training, and virtual reality. For the control groups, 6 studies used treatment or medication as the usual approach. The participants in the control groups of 3 included studies did not receive any training. Two studies used stimulants, 7 studies used placebo cognitive training, and 1 study used a digital game. Detailed information is presented in .
Table 2. Characteristics of intervention of the selected studies (n=19).StudyInterventionControlType of interventionOutcome measurementAzami et al []Computer-assisted cognitive rehabilitationPsychostimulantsIndividual: 20 sessions in 3 mo, 90 min/sessionContinuous Performance Test, Tower-of-London, Forward/Backward Digit Span From WISC-Ra, Raven Progressive Matrices, and web-based version of Span Board Task Progressive MatricesBenzing and Schmidt []Exergame trainingNot receiving trainingIndividual: 8 wk, 3 times a week for at least 30 minConners‐3 Rating Scales and German Motor TestBigorra et al []Computerized working memory trainingNonadaptive work memory trainingIndividual: 5 wk, 5 sessions per week, 30-45 min/session Backward Digit Span, Letter-number Sequencing of WISC-IVb, Backward Spatial Span of WMS-IIIc, Lowa Gambling Task, Happé Strange Stories, and Folk Psychology TestBikic et al [] Cognitive computer games of the ACTIVATE programTreatment as usualIndividual: 6 times a week, 8 wkCambridge Neuropsychological Test Automated Battery, Motor Screening Task, Attention Switching Task, Rapid Visual Information Processing, Intraextra Dimensional Set Shift, Reaction Time, ADHDd Rating Scale, and Behavior Rating Inventory of Executive FunctionBioulac et al []Virtual classroom cognitive remediation programPsychotherapy placebo trainingIndividual: twice a week for 6 wk, 12 sessions, 30 min/sessionADHD Rating Scale and Continuous Performance Test Task AssessmentBreider et al []Web-based program and supportive therapist contactFace-to-face parent trainingParents: 17 sessions, 45-60 min/sessionChild Behavior ChecklistCorkum et al []Web-based learning and blackboard learningTreatment as usualTeachers: 6 training sessionsConners-3 Parent and Teacher Rating Scales and Impairment Rating ScaleDovis et al []Braingame Brian trainingPlacebo-mode working memory trainingIndividual: 25 training sessions in 5 wk, 35-50 min per sessionDisruptive Behavior Disorder Rating Scale, Behavior Rating Inventory of Executive Function, Sensitivity to Punishment and Sensitivity to Reward Questionnaire for Children, Pediatric Quality of Life Inventory, and Home Situations QuestionnaireEgeland et al []Cogmed RoboMemo programTreatment as usualIndividual: daily basis for 5-7 wk, 30-45 minColor Word Test, Trail Making Test, Conners Continuous Performance Test-II, Key Math, Logometrica, Benton Visual Retention Test, Children’s Auditory Verbal Learning Test-2, ADHD Rating Scale, Strengths and Difficulties Questionnaire, and Behavior Rating Inventory of Executive FunctionFried et al []Text messagingTreatment as usualIndividual: 45 dAdherence to stimulantsGevensleben et al []Neurofeedback trainingAttention skills trainingIndividual: 6 mo, 25-30 min/sessionADHD Rating Scale, German Rating Scale for Oppositional Defiant/Conduct Disorders, Strength and Difficulties Questionnaire, Home Situations Questionnaire, and Homework Problem ChecklistKofler et al []Central executive trainingInhibitory control trainingGroup: 10 wk, 1 h/wk; individual: 10 wk, 2-3 d/wk, 15 min/dBehavior Assessment System for Children, ADHD Rating Scale, and Phonological and Visuospatial ReorderingKollins et al []AKL-T01 (a digital therapeutic)Digital gameIndividual: 5 d/wk for 4 wk, 25 min/dADHD Rating Scale, Test of Variables of Attention, and Attention Performance IndexLim et al []Brain computer interface-based attention training programNot receiving trainingIndividual: 3 sessions/wk in the first 8 wk and 4 sessions/wk in the next 12 wkADHD Rating Scale Inattention Score and Child Behavior ChecklistMeyer et al []Computerized trainingMedication as usualIndividual: at least 5 d a week for 4 wk, 15 min/dSwanson, Nolan, and Pelham-IV Questionnaire and Conners Parent Rating Scale and Conners Teacher Rating ScaleMoreno-García et al []Neurofeedback trainingPharmacologyIndividual: 40 sessionsADHD Rating Scale and Integrated Visual and Auditory Continuous Performance TestSteiner et al []Computer attention training using neurofeedback or cognitive trainingNot receiving trainingIndividual: 40 sessions over 5 mo, 3 times/wk, 45 min/timeConners 3–Parent Assessment Report, Behavior Rating Inventory of Executive Function, and Behavioral Observation of Students in Schoolsvan der Oord et al []Executive functioning trainingTreatment as usualIndividual: 25 sessions over 5 wk, 40 min/sessionBehavior Rating Inventory of Executive Functioning and Disruptive Behavior Disorder Rating ScaleWangler et al []Neurofeedback trainingComputerized attention skills trainingIndividual: 3-4 wk, 25-30 min/sessionAttention Network Test and ADHD Rating ScaleaWISC-R: Wechsler Intelligence Scale for Children—Revised.
bWISC-IV: Backward Digit Span of the Wechsler Intelligence Scale for Children-IV.
cWMS-III: Wechsler Memory Scale–III.
dADHD: attention-deficit/hyperactivity disorder.
Intervention Duration and LengthThe intervention duration of 3 studies was 4 weeks. Meanwhile, the intervention duration of 9 studies was 5 to 8 weeks. One study had an intervention duration of 12 weeks, 2 studies had an intervention duration of 5 months, and 1 study had an intervention duration of 6 months. For the length of intervention, 1 trial was conducted for 15 minutes per session, 10 studies varied from 25 to 45 minutes per session, 2 studies varied from 45 to 60 minutes per session, and 1 study was conducted for 90 minutes per session.
Meta-Analysis Results of the Technology-Based InterventionADHD BehaviorsADHD behaviors included in this study were inattention and hyperactivity or impulsivity. Moderate heterogeneity was observed among the studies examining ADHD behaviors (I2=26.4%). shows the pooled results of ADHD behavior. Corkum et al [] evaluated the overall ADHD behaviors of participants, whereas the other 10 studies classified the results of the ADHD behaviors into inattention and hyperactivity or impulsivity. Corkum et al [] reported the Conners 3 Parent Rating Scale (Conners 3-P) and Conners 3 Teacher Rating Scale (Conners 3-T) scores. The SMD of ADHD behaviors measured with parent-rated evaluation was −0.21 (95% CI −0.73 to 0.31), and the teacher-rated evaluation of ADHD behaviors was −0.46 (95% CI −0.98 to 0.06). However, no significant effect was observed for ADHD behavior.
A total of 12 studies reported inattention, which was measured using the ADHD Rating Scale (ADHD-RS), Disruptive Behavior Disorder Rating Scale (DBDRS), Conners 3-P, and Conners 3-T. Parent-rated inattention measured by ADHD-RS (K=7), Conners 3-P (K=4), and DBDRS (K=2) had no statistically significant effect. Teacher-rated inattention measured by ADHD-RS (K=6), Conners 3-T (K=1), and DBDRS (K=2) had no significant effect. Computer-rated inattention measured by ADHD-RS (K=2; SMD −0.35, 95% CI −0.68 to −0.01) had a small and statistically significant effect (P<.04).
Ten studies explored the effectiveness of technology-based interventions on hyperactivity or impulsivity. Three different scales were used: ADHD-RS, DBDRS, and Conners 3-P and Conners 3-T. No significant effect was found in parent-rated hyperactivity or impulsivity measured by ADHD-RS (K=7), Conners 3-P (K=4), and DBDRS (K=2) and teacher-rated hyperactivity or impulsivity measured by ADHD-RS (K=4), Conners 3-T (K=1), and DBDRS (K=2).
The results of moderator analysis demonstrated that the sample size, setting, game elements, and type of control group moderated the effect size (). A sample size of ≤50 (K=10; SMD −0.25, 95% CI −0.47 to −0.03; P<.03), nonhome setting (ie, clinic or school; K=12; SMD −0.24, 95% CI −0.37 to −0.11; P<.001), game elements excluded (K=40; SMD −0.15, 95% CI −0.23 to −0.07; P<.001), and control groups with no treatment (K=28; SMD −0.22, 95% CI −0.32 to −0.13; P<.001) and nonequivalent treatment had a significant moderating effect on the effect size.
Table 3. Meta-analyses results of technology-based interventions for school-age children with attention-deficit/hyperactivity disorder.VariablesNumber of effect sizesStandardized mean differenceSE95% CIz scoreP valueParent-rated inattentionaADHD-RS: ADHD Rating Scale.
bConners 3-P: Conners 3 Parent Rating Scale.
cDBDRS: Disruptive Behavior Disorder Rating Scale.
dConners 3-T: Conners 3 Teacher Rating Scale.
eBRIEF: Behavior Rating Inventory of Executive Function.
fBASC: Behavior Assessment System for Children.
gWISC-IV: Backward Digit Span of the Wechsler Intelligence Scale for Children-IV.
hBOSS: Behavioral Observation of Students in Schools.
iCBC: Child Behavior Checklist.
jFBB-SSV: Fremdbeurteilungsbogen für Störungen des Sozialverhaltens.
kANT: Attention Network Test.
lAST: Attention Switching Task.
mBVRT: Benton Visual Retention Test.
nCPT: Continuous Performance Test.
oIED: Intraextra Dimensional Set Shift.
pIVA/CPT: Integrated Visual and Auditory Continuous Performance Test.
qRTI: Reaction Time.
rRVIP: Rapid Visual Information Processing.
sCAVLT-2: Children’s Auditory Verbal Learning Test-2.
tSPSRQ-C: Sensitivity to Punishment and Sensitivity to Reward Questionnaire for Children.
uPedsQL: Pediatric Quality of Life Inventory.
vLOGOS: Logometrica.
Table 4. Results of moderators between technology-based intervention for school-age children with attention-deficit/hyperactivity disorder (ADHD).
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