{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T20:20:58Z","timestamp":1787948458766,"version":"build-2784847793"},"reference-count":42,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Serious Games"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Attention-deficit\/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children, characterized by inattention, hyperactivity, and impulsivity that significantly disrupt daily functioning. Comprehensive ADHD assessment requires multimethod and multi-informant evaluation, and objective attention measures can complement this process. Serious game\u2013based assessments may further support this process by combining structured task mechanics and dynamic audiovisual guidance in a child-oriented digital environment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to develop and validate Attention Robots, a serious game designed for assessing behavioral attention indicators in children and adolescents. The goal was to examine whether its outputs corresponded with indicators from the widely used D2-R Test of Attention as preliminary evidence of convergent validity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this preliminary cross-sectional convergent validation study, 58 participants (34 male and 24 female individuals) aged 6-18 years, recruited through clinical referral and community sources, completed Attention Robots followed by the D2-R test. The original group variable, assigned by the project psychologists, identified 19 participants in the experimental group and 39 participants in the control group. Attention Robots presents timed rows of robot stimuli and asks participants to identify and select predefined target robots. Spearman and Pearson correlations compared working speed, omissions, commissions, concentration, and precision across both instruments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Primary cross-test correlations were positive. Spearman correlations were observed for working speed (\u03c1=0.905, 95% CI 0.84-0.94; P&lt;.001), omissions (\u03c1=0.333, 95% CI 0.08-0.54; P=.01), commissions (\u03c1=0.496, 95% CI 0.27-0.67; P&lt;.001), concentration (\u03c1=0.926, 95% CI 0.88-0.96; P&lt;.001), and precision (\u03c1=0.607, 95% CI 0.41-0.75; P&lt;.001). Pearson correlations showed a similar pattern for working speed (r=0.911, 95% CI 0.85-0.95; P&lt;.001), omissions (r=0.278, 95% CI 0.02-0.50; P=.04), commissions (r=0.396, 95% CI 0.15-0.59; P=.002), concentration (r=0.922, 95% CI 0.87-0.95; P&lt;.001), and precision (r=0.574, 95% CI 0.37-0.72; P&lt;.001). These findings support preliminary convergent correspondence between corresponding behavioral indicators, but they do not establish interchangeability, discriminative validity, diagnostic use, or superior engagement or acceptability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Attention Robots provides preliminary evidence of convergent validity with the D2-R for behavioral attention indicators in children and adolescents. The innovative aspect of this study is the translation of D2-R\u2013based attentional demands into a child-oriented serious game environment with robot-based stimuli, dynamic audiovisual guidance, and structured behavioral data capture. Unlike previous digital or serious game approaches, this study empirically compares game-derived indicators with corresponding indicators from an established attention test rather than evaluating only task feasibility, engagement, or intervention effects. This work contributes to the field by providing a preliminary validation of a serious game format that may support the collection of objective attention-related data in children and adolescents. In applied contexts, Attention Robots could be further developed as a complementary tool within multimethod ADHD assessment, although larger studies are required to evaluate subgroup performance, agreement, diagnostic use, and user experience before clinical adoption.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/80441","type":"journal-article","created":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T20:05:09Z","timestamp":1787947509000},"page":"e80441","source":"Crossref","is-referenced-by-count":0,"title":["Serious Game\u2013Based Attention Assessment for Attention-Deficit\/Hyperactivity Disorder in Children and Adolescents: Preliminary Cross-Sectional Convergent Validation Study"],"prefix":"10.2196","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-5084-0468","authenticated-orcid":false,"given":"Alejandro","family":"Panagiotidis-Arrizabalaga","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8399-4666","authenticated-orcid":false,"given":"Ana","family":"Lavalle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0102-6918","authenticated-orcid":false,"given":"Miguel A","family":"Teruel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0118-8127","authenticated-orcid":false,"given":"Javier","family":"Sanchis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7522-5162","authenticated-orcid":false,"given":"Nicol\u00e1s","family":"Ruiz-Robledillo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6658-768X","authenticated-orcid":false,"given":"Borja","family":"Costa-L\u00f3pez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,8,28]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/s41380-018-0070-0"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sbae228"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2005.02.006"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1177\/13591045221128399"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.105525"},{"key":"ref6","year":"2013","journal-title":"Diagnostic and Statistical Manual of Mental Disorders: DSM-5"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1080\/16506073.2015.1073786"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11065-019-09407-6"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10802-018-0438-2"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.2196\/59124"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/mti9010008"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.entcom.2020.100341"},{"key":"ref13","author":"Teruel, MA","year":"2017","journal-title":"Natural and Artificial Computation for Biomedicine and Neuroscience"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1080\/09297049.2025.2468411"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"1466107","DOI":"10.3389\/fpsyt.2025.1466107","volume":"16","author":"Guigou, Y","year":"2025","journal-title":"Front Psychiatry"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1080\/13854046.2016.1144793"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.acn.2005.12.002"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/brainsci12070877"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2012.10.004"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2013.10.006"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.entcom.2021.100417"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1038\/nrdp.2015.20"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3390\/brainsci10100716"},{"key":"ref24","author":"Conners, CK","year":"2000","journal-title":"Conners' Continuous Performance Test II (CPT II v. 5)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1002\/ana.410240504"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1080\/21622965.2022.2112679"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2012.11.004"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2015.00328"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"93148","DOI":"10.1109\/ACCESS.2025.3567427","volume":"13","author":"Ul Ain, Q","year":"2025","journal-title":"IEEE Access"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/2017975"},{"key":"ref31","author":"Brickenkamp, R","year":"2022","journal-title":"D2-R. 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