We gratefully acknowledge the support provided by the Programa de la Agencia Espa&#241;ola de Cooperaci&#243;n con Iberoam&#233;rica (AECI), enabling the adaptation of the technological tool Sicole-R-Primaria to the Spanish language variant of different countries within the Ibero-American space through the projects Evaluaci&#243;n de procesos cognitivos en la lectura mediante ayuda asistida a trav&#233;s de ordenador en poblaci&#243;n escolar de educaci&#243;n primaria (Assessment of Cognitive Processes in Reading through Computer-Assisted Aid in Primary School Student Population) in Guatemala (ref.: A/3877/05), Ecuador (ref.: C/030692/10), M&#233;xico (ref.: A/013941/07), and Chile (ref.: A/7548/07). Additionally, we would like to express our sincere gratitude to the Inter-American Development Bank (IDB) for their financial support toward the Ministry of Education (MEDUCA) of Panam&#225;, with the Organization of Ibero-American States for Education, Science and Culture (OEI) acting as an intermediary. This funding has enabled the adaptation of the Sicole-R for use on both computers and tablets. We are also grateful for the support provided within the framework of Program PN-L1143; 4357/OC-PN, particularly the Technical Support for Facilitator Training and Review of Educational Resources. Additionally, we extend our appreciation for the External Products and Services Contract (PEC), which is aimed at offering specialized training to facilitate the detection, identification, and early intervention of Panamanian students who may be at risk of experiencing difficulties in reading, writing, and mathematics. For all the projects mentioned above, the first author served as the principal investigator.

Computerized Dyslexia Assessment for Spanish-Speaking Children Using SICOLE-R

<ol>
	<li>World Federation of Neurology. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Report of research group on Dyslexia and world illiteracy. , (1968).</li><li>Diamanti, V., Goulandris, N., Campbell, R., Protopapas, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dyslexia+profiles+across+orthographies+differing+in+transparency:+An+evaluation+of+theoretical+predictions+contrasting+English+and+Greek.">Dyslexia profiles across orthographies differing in transparency: An evaluation of theoretical predictions contrasting English and Greek.</a> Sci Stud Reading. 22 (1), 55-69 (2018).</li><li>Shaywitz, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Overcoming dyslexia: A new and complete science-based program for reading problems at any level. , (2003).</li><li>Heikki Lyytinen, H., Ronimus, H., Alanko, A., Poikkeus, N. M., Taanila, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Early+identification+of+dyslexia+and+the+use+of+computer+game-based+practice+to+support+reading+acquisition.">Early identification of dyslexia and the use of computer game-based practice to support reading acquisition.</a> Nordic Psychol. 59 (2), 109-126 (2007).</li><li>Tobia, V., Marzocchi, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cognitive+profiles+of+Italian+children+with+developmental+dyslexia.">Cognitive profiles of Italian children with developmental dyslexia.</a> Reading Res Quart. 49 (4), 437-452 (2014).</li><li>Rauschenberger, M., Baeza-Yates, R., Rello, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+universal+screening+tool+for+dyslexia+by+a+web-game+and+machine+learning.">A universal screening tool for dyslexia by a web-game and machine learning.</a> Front Comput Sci. 3, 628634 (2022).</li><li>Ekhsan, H. M., Ahmad, S. Z., Halim, S. A., Hamid, J. N., Mansor, N. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+implementation+of+interactive+multimedia+in+early+screening+of+dyslexia.">The implementation of interactive multimedia in early screening of dyslexia.</a> Int Conf Innov Mgmt Tech Res. , 566-569 (2012).</li><li>Jim&#233;nez, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dyslexia+in+Spanish.">Dyslexia in Spanish.</a> Prevalence and cognitive, cultural, family and biological indicators. , (2012).</li><li>Hatcher, J., Snowling, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+phonological+representations+hypothesis+of+dyslexia:+From+theory+to+practice.">The phonological representations hypothesis of dyslexia: From theory to practice.</a> Dyslexia and Literacy, Theory and Practice. , (2002).</li><li>Goswami, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+temporal+sampling+framework+for+developmental+dyslexia.">A temporal sampling framework for developmental dyslexia.</a> Trends Cogn Sci. 15 (1), 3-10 (2011).</li><li>Stein, J. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+magnocellular+theory+of+developmental+dyslexia.">The magnocellular theory of developmental dyslexia.</a> Dyslexia. 7 (1), 12-36 (2001).</li><li>Nicolson, R. I., Fawcett, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+Dyslexia:+The+delayed+neural+commitment+framework.">Development of Dyslexia: The delayed neural commitment framework.</a> Front Behav Neurosci. 21 (13), 112 (2001).</li><li>Pennington, B. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Individual+prediction+of+dyslexia+by+single+versus+multiple+deficit+models.">Individual prediction of dyslexia by single versus multiple deficit models.</a> J Abnorm Psychol. 121 (1), 212-224 (2012).</li><li>Ring, J., Black, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+multiple+deficit+model+of+dyslexia:+what+does+it+mean+for+identification+and+intervention.">The multiple deficit model of dyslexia: what does it mean for identification and intervention.</a> Ann Dyslexia. 68 (2), 104-125 (2018).</li><li>Soriano-Ferrer, M., Nievas-Cazorla, F., S&#225;nchez-L&#243;pez, P., F&#233;lix-Mateo, V., Gonz&#225;lez-Torre, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reading-related+cognitive+deficits+in+Spanish+developmental+Dyslexia.">Reading-related cognitive deficits in Spanish developmental Dyslexia.</a> Procedia - Social Behav Sci. 132, 3-9 (2014).</li><li>Zygouris, N. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+implementation+of+a+web+application+for+screening+children+with+Dyslexia.">The implementation of a web application for screening children with Dyslexia.</a> , (2016).</li><li>Snowling, M. J., Hulme, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The Science of Reading: A Handbook. , (2021).</li><li>Politi-Georgousi, S., Drigas, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mobile+applications,+an+emerging+powerful+tool+for+Dyslexia+screening+and+intervention:+A+systematic+literature+review.">Mobile applications, an emerging powerful tool for Dyslexia screening and intervention: A systematic literature review.</a> Int J Interact Mobile Technol. 14 (18), 4-17 (2020).</li><li>Fawcett, A. J., Nicolson, R. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Dyslexia+early+screening+test.">The Dyslexia early screening test.</a> Irish J Psychol. 16 (3), 248-259 (1995).</li><li>Zygouris, N. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The implementation of a web application for screening children with dyslexia Interactive Collaborative Learning. , (2017).</li><li>Hautala, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+reading+difficulties+by+a+digital+game-based+assessment+technology.">Identification of reading difficulties by a digital game-based assessment technology.</a> J Edu Comput Res. 58 (5), 1003-1028 (2020).</li><li>Ahmad, N., Rehman, M. B., El Hassan, H. M., Ahmad, I., Rashid, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+efficient+machine+learning-based+feature+optimization+model+for+the+detection+of+dyslexia.">An efficient machine learning-based feature optimization model for the detection of dyslexia.</a> Comput Intell Neurosci. 9, 8491753 (2022).</li><li>Rello, L., Baeza-Yates, R., Ali, A., Bigham, J. P., Serra, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Predicting+risk+of+dyslexia+with+an+online+gamified+test.">Predicting risk of dyslexia with an online gamified test.</a> PLoS One. 15 (12), e0241687 (2020).</li><li>D&#281;bska, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+cognitive+basis+of+dyslexia+in+school-aged+children:+A+multiple+case+study+in+a+transparent+orthography.">The cognitive basis of dyslexia in school-aged children: A multiple case study in a transparent orthography.</a> Dev Sci. 25 (2), e13173 (2022).</li><li>Jim&#233;nez, J. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discriminant+validity+of+the+Sicole-R-Primaria+Multimedia+Battery+for+the+evaluation+of+cognitive+processes+associated+with+dyslexia.">Discriminant validity of the Sicole-R-Primaria Multimedia Battery for the evaluation of cognitive processes associated with dyslexia.</a> Revista de Investigaci&#243;n Educativa. 27 (1), 49-71 (2009).</li><li>Guzm&#225;n, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessment+of+naming+speed+in+reading+learning+difficulties.">Assessment of naming speed in reading learning difficulties.</a> Psicothema. 16 (3), 442-447 (2004).</li><li>Jim&#233;nez, J. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Is+the+deficit+in+phonological+awareness+better+explained+in+terms+of+task+differences+or+effects+of+syllable+structure.">Is the deficit in phonological awareness better explained in terms of task differences or effects of syllable structure.</a> Appl Psycholinguist. 26 (2), 267-283 (2005).</li><li>Ortiz, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Locus+and+nature+of+perceptual+phonological+deficit+in+Spanish+children+with+reading+disabilities.">Locus and nature of perceptual phonological deficit in Spanish children with reading disabilities.</a> J Learn Disabil. 40 (1), 80-92 (2007).</li><li>Ortiz, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+speech+perception+in+children+with+dyslexia.">Development of speech perception in children with dyslexia.</a> Psicothema. 20 (4), 678-683 (2008).</li><li>Jim&#233;nez, J. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Double-deficit+hypothesis+in+Spanish+developmental+dyslexia.">The Double-deficit hypothesis in Spanish developmental dyslexia.</a> Topics Lang Disorders. 28 (1), 46-60 (2008).</li><li>Jim&#233;nez, J. E., Garc&#237;a de la Cadena, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Learning+disabilities+in+Guatemala+and+Spain:+A+cross-national+study+of+the+prevalence+and+cognitive+processes+associated+with+reading+and+spelling+disabilities.">Learning disabilities in Guatemala and Spain: A cross-national study of the prevalence and cognitive processes associated with reading and spelling disabilities.</a> Learning Disabilities Res Pract. 22, 161-169 (2007).</li><li>Jim&#233;nez, J. E., de la Cadena, C. G., Siegel, L. S., O'Shanahan, I., Garc&#237;a, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gender+ratio+and+cognitive+profiles+in+dyslexia:+a+cross-national+study.">Gender ratio and cognitive profiles in dyslexia: a cross-national study.</a> Read Writ. 24, 729-747 (2011).</li><li>Rodrigo, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessment+of+orthographic+processing+in+Spanish+children+with+dyslexia:+the+role+of+lexical+and+sublexical+units.">Assessment of orthographic processing in Spanish children with dyslexia: the role of lexical and sublexical units.</a> Revista Electr&#243;nica de Investigaci&#243;n Psicoeducativa y Psicopedag&#243;gica. 2 (2), 105-126 (2004).</li><li>Jim&#233;nez, J. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+syntactic-semantic+processing+in+developmental+dyslexia.">Evaluation of syntactic-semantic processing in developmental dyslexia.</a> Elect J Res Edu Psychol. 2 (2), 127-142 (2004).</li><li>Jim&#233;nez, J. E., Rodr&#237;guez, C., Ram&#237;rez, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spanish+developmental+dyslexia:+prevalence,+cognitive+profile,+and+home+literacy+experiences.">Spanish developmental dyslexia: prevalence, cognitive profile, and home literacy experiences.</a> J Exp Child Psychol. 103 (2), 167-185 (2009).</li><li>Cuetos, F., Rodr&#237;guez, B., Ruano, R., Arribas, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> PROLEC-R. Primary Reading Processes Assessment Battery - Revised. , (2005).</li><li>Guzm&#225;n, R., Jim&#233;nez, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Normative+study+on+psycholinguistic+parameters+in+children+aged+6+to+8+years:+Subjective+familiarity.">Normative study on psycholinguistic parameters in children aged 6 to 8 years: Subjective familiarity.</a> Cognitiva. 2, 153-191 (2001).</li><li>Cohen, P., Cohen, J., Aiken, L., West, S. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+problem+of+units+and+the+circumstance+for+POMP.">The problem of units and the circumstance for POMP.</a> Multivariate Behav Res. 34, 315-346 (1999).</li><li>R Core Team. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=R:+A+Language+and+Environment+for+Statistical+Computing_.">R: A Language and Environment for Statistical Computing_.</a> R Foundation for Statistical Computing. , (2023).</li><li>Rosseel, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=lavaan:+An+R+package+for+structural+equation+modeling.">lavaan: An R package for structural equation modeling.</a> J Stat Software. 48 (2), 1-36 (2012).</li><li>Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., Rosseel, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> semTools: Useful tools for structural equation modeling. , (2022).</li><li>Wickham, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> ggplot2: Elegant graphics for data analysis. , (2016).</li><li>Byrne, B. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Structural equation modeling with AMOS: Basic concepts, applications, and programming. , (2016).</li><li>Vandenberg, R. J., Lance, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+review+and+synthesis+of+the+measurement+invariance+literature:+Suggestions,+practices,+and+recommendations+for+organizational+research.">A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research.</a> Org Res Methods. 3 (1), 4-70 (2000).</li><li>Hirschfeld, G., von Brachel, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple-Group+confirmatory+factor+analysis+in+R+-+A+tutorial+in+measurement+invariance+with+continuous+and+ordinal+indicators.">Multiple-Group confirmatory factor analysis in R - A tutorial in measurement invariance with continuous and ordinal indicators.</a> Pract Assess Res Eval. 19 (7), 1-12 (2014).</li><li>Sachs, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=plotROC:+A+Tool+for+Plotting+ROC+Curves.">plotROC: A Tool for Plotting ROC Curves.</a> J Stat Softw. 79, 2 (2017).</li><li>Jing, W., Yu, E. L. X., Motevalli, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comparison+between+cognitive+assessment+and+neurobiology+technology+assessment+of+dyslexia:+A+literature+review.">A comparison between cognitive assessment and neurobiology technology assessment of dyslexia: A literature review.</a> Int J Acad Res Busi Soc Sci. 13 (4), 976-986 (2023).</li></ol>

The authors listed above certify that there are no financial interests or other conflicts of interest regarding the present study.

In this study, confirmatory factor analysis (CFA) was employed to evaluate the factor structure of the Sicole-R battery, comprising one second-order factor and six latent variables representing different modules. The results indicated good model fit, convergent validity, and reliability, confirming the efficacy of the battery in assessing a comprehensive set of cognitive and reading skills that are critical for individuals with dyslexia. Importantly, the consistent performance of the digital tool across diverse demographic groups within Spain, Mexico, Guatemala, and Chile suggests its potential utility in educational and clinical settings across various Spanish-speaking regions.
This study contributes to literature by demonstrating how multimedia batteries can be used to effectively identify specific cognitive deficits associated with dyslexia. The battery&#39;s ability to pinpoint specific areas of difficulty, such as phonological awareness, speech perception, naming speed, orthographical processing, syntactic processing, and reading comprehension, enables tailored interventions to address individual student needs effectively. Moreover, the demonstrated consistency of the battery across genders underscores its utility in promoting equitable assessment practices, thereby supporting inclusive education initiatives aimed at providing equal opportunities for all students.
Although previous tools with similar characteristics were designed for use in the English language, such as the Dyslexia Early Screening Test (DEST) proposed by Fawcett and Nicolson17, which assesses multiple domains, this study demonstrated the applicability and effectiveness of the multimedia battery in a different linguistic context. Throughout the analysis, several critical steps were undertaken within the protocol to ensure the accuracy and validity of the results. These steps included data preprocessing, model specification, and parameter estimation, aligning with studies such as Hautala et al.19 that have demonstrated the reliability of computer-based tools in identifying students with reading difficulties. Additionally, other studies, such as those by Protopapas et al.20 and Pennington et al.12, have explored the implementation of computer-based screening tools for dyslexia identification, underscoring the importance of harnessing technology to enhance assessment strategies. Furthermore, the current study aligns with recent advancements in dyslexia research and psychometric assessment, emphasizing the relevance of the battery in contemporary contexts. Studies conducted by Jim&#233;nez et al.23 and Guzm&#225;n et al.24 have highlighted the critical need for robust assessment tools tailored to diverse linguistic backgrounds, underscoring Sicole-R&#39;s efficacy in filling this gap within Spanish-speaking populations. Moreover, the integration of digital technologies in dyslexia assessment, as discussed by Rauschenberg et al.6, reinforces the methodological rigor demonstrated in this study&#39;s approach to factor analysis and validation.
Despite the methodological rigor employed in this study, it is important to acknowledge certain limitations inherent in the analysis. One limitation concerns the generalizability of the findings, as the sample consisted of a specific demographic group, potentially limiting the applicability of the results to broader populations. Additionally, while efforts were made to ensure measurement invariance across genders, other demographic factors, such as age or socioeconomic status, were not explicitly accounted for in the analysis, which may have influenced the results.
Future research directions&#160;could explore its adaptation to different&#160;Spanish dialects and its integration into broader&#160;educational frameworks to enhance&#160;identification strategies. Moving forward, future research should aim to address the limitations identified in this study, such as exploring the utility of the multimedia battery in diverse populations and investigating its longitudinal validity and predictive validity in predicting long-term educational outcomes. Additionally, a promising future line of research has been highlighted in a recent review by Jin et al.47, suggesting the incorporation of neurobiological technology. They conducted a comprehensive review of scientific databases, selecting studies published between 2018 and 2023. Their findings suggest that neurobiological technology assessment is emerging as a promising trend in advancing the diagnosis of dyslexia.
In conclusion, the findings of&#160;this study highlight the multimedia battery as&#160;a&#160;valuable tool for educators, ultimately facilitating more effective support and improved outcomes for students with dyslexia. By incorporating these contemporary insights, the findings contribute to the evolving discourse on dyslexia assessment, offering practitioners and researchers updated perspectives on effective diagnostic strategy frameworks. To our knowledge, this study is among the first to validate a comprehensive multimedia battery tailored specifically for Spanish-speaking populations, filling a critical gap in the current diagnostic tools available for dyslexia.

Dyslexia is a neurodevelopmental disorder characterized by difficulties in accurate and/or fluent word recognition and poor spelling and decoding abilities and is characterized by unexpected and persistent difficulty in acquiring efficient reading skills despite conventional instruction, adequate intelligence, and sociocultural opportunity1. This neurobiological disorder often manifests as challenges in reading, spelling, and writing, primarily due to phonological deficits2,3. &#8220;The importance of early&#160;identification of dyslexia cannot be overstated,&#160;as it allows for timely intervention and support4,5. When a student does not progress beyond&#160;Tier-3 in a response-to-intervention model, it&#160;becomes essential to conduct a&#160;more&#160;comprehensive assessment of both domain-general and domain-specific abilities associated&#160;with dyslexia, as highlighted by the scientific&#160;literature. The development of the technique&#160;presented here is grounded in the necessity of&#160;conducting thorough evaluations to ensure that&#160;appropriate interventions and support are&#160;provided.&#160;Moreover, previous studies&#160;underscore the utility of technology-based&#160;screening tools, such as web applications and&#160;computer games, in facilitating effective&#160;screening processes6,7. These studies collectively highlight the multifaceted nature of dyslexia, emphasizing the need for comprehensive assessment and intervention strategies to address the diverse cognitive profiles of individuals with dyslexia. Despite the prevalence of dyslexia among school-aged children, most available diagnostic tools lack a framework that comprehensively assesses both domain-general and domain-specific skills. Moreover, there are minimal computerized options, particularly for Spanish-speaking populations. This multimedia battery addresses these gaps by leveraging technology to facilitate a detailed assessment of cognitive skills linked to dyslexia.
Theoretical perspectives and cognitive deficits in Dyslexia 
Various theoretical models, including phonological, rapid auditory processing, visual, magnocellular, and cerebellar theories, aim to explain the causes of dyslexia and inform interventions (see for a review)8. The phonological theory attributes dyslexia to difficulties in processing language sounds9, while the rapid auditory processing theory links dyslexia to deficits in perceiving rapidly changing sounds10. Visual theory highlights the visual aspects of reading difficulties, and magnocellular theory points to impairments in visual and auditory processing pathways11. The cerebellar theory suggests that dyslexia arises from cerebellar impairments affecting motor control and cognitive functions12. Nicolson and Fawcett&#39;s Delayed Neural Commitment (DNC) framework posits that slower skill acquisition and delayed neural network development are central to dyslexia. Recent models, such as the multiple deficit model, propose that dyslexia is a complex disorder influenced by genetic, cognitive, and environmental factors13,14,15. For instance, Ring and Black14 support the multiple deficit model, showing that both phonological and cognitive processing deficits contribute to the heterogeneity of dyslexia. Soriano-Ferrer et al.15 conducted a study with Spanish-speaking children with developmental dyslexia (DD) and found significant impairments in naming speed, verbal working memory, and phonological awareness (PA). Similarly, Zygouris et al.16 and Rauschenberger et al.6 underscore the importance of cognitive screening tools in identifying these deficits, with dyslexic individuals consistently scoring lower than typically achieving peers.
Examining technological approaches in Dyslexia screening: Insights from research studies 
Research on dyslexia screening has evolved with three main approaches: early detection strategies, multifaceted screening methods combining various assessments, and integrating technology for enhanced efficiency17. Politi-Georgousi&#39;s18&#160;recent&#160;systematic review highlights a shift toward&#160;more applications for intervening in dyslexia&#160;symptoms rather than screening processes,&#160;aligning with technology integration to improve&#160;reading skills in dyslexic students. Various tools exist, such as the Dyslexia Early Screening Test (DEST) by Fawcett and Nicolson, which assesses speed, phonological skills, motor skills, cerebellar function, and knowledge19. &#8220;Computer-based tools have&#160;advanced, including a web application assessing&#160;reading and cognitive skills in Greek children20 and tools by Hautala et al.21 and Rauschenberg et al.6&#160;that use gaming and machine learning for&#160;early identification of dyslexia. Ahmad et al. integrated gaming with neural networks, achieving 95% accuracy in detection22. Studies across different orthographies underscore the importance of phonological awareness and rapid automatized naming in dyslexia identification23,24.
Insights into Dyslexia among Spanish-speaking children 
The study of dyslexia in Spanish-speaking children has been significantly advanced through the use of Sicole-R technology. Jim&#233;nez et al. demonstrated its effectiveness in assessing dyslexia across age groups, particularly in distinguishing between dyslexic and typically achieving readers based on phonological and syntactic processing during early elementary years25. Guzm&#225;n et al. investigated naming speed deficits in dyslexic children with phonological challenges, highlighting interactions between dyslexia and naming speed measured through tasks such as letter-RAN and number-RAN26. Further studies by Jim&#233;nez et al. explored phonological awareness deficits across different syllable structures27, while Ortiz et al. investigated speech perception deficits among Spanish children with dyslexia, revealing impairments in speech perception development regardless of phonetic contrast or linguistic unit28,29. Jim&#233;nez et al. investigated the double-deficit hypothesis of dyslexia30, followed by analyses of cognitive processes and gender-related disparities in dyslexia prevalence31,32. Rodrigo et al. explored lexical access among Spanish dyslexic children33, and Jim&#233;nez et al. scrutinized syntactic processing deficits34. Finally, Jim&#233;nez et al. studied phonological and orthographical processes in dyslexic subtypes, highlighting differences in orthographic route efficiency35. These studies collectively enhance our understanding of the cognitive and linguistic challenges of dyslexia in Spanish-speaking populations.
The conducted studies share several common characteristics in terms of the age and background of the participating children. The children included in these studies ranged in age from 7 to 14 years. Most studies focused on primary school children aged between 7 and 12 years, except those that included children up to 14 years old, providing a sample that spans from early school years to preadolescence31,32. The participating children were primarily from the Canary Islands in Spain. Additionally, some studies included samples from other regions of Spain and Guatemala31,32. Participants were recruited from both public and private schools whose backgrounds included urban and suburban areas. The socioeconomic levels represented in these studies range from low-middle to working and middle class.
Together, these inquiries significantly advance our understanding of dyslexia&#39;s complexities, contributing to the field of dyslexia research. Adapted for use across multiple Ibero-American countries, including Spain, Guatemala, Chile, and Mexico, the tool facilitates the assessment of diagnostic accuracy and precision in a diverse Spanish-speaking sample for this study.
This study aimed to delineate a protocol for diagnosing Spanish-speaking children with reading difficulties using a specialized multimedia battery. The primary goal is to provide a comprehensive assessment tool that evaluates both domain-general and domain-specific skills associated with dyslexia.
Experimental setup overview 
The&#160;SICOLE-R was programmed in the Java 2 Platform Standard Edition (J2SE). The HSQL database engine is used as a database. The software includes 6 main modules to be evaluated: 1) perceptual processing, which includes the tasks of voicing, placing, and manner of articulation; 2) phonological processing, which includes phoneme isolation, phoneme deletion, phoneme segmentation, and phoneme blending tasks; 3) naming speed, which includes the tasks of naming speed in numbers, letters, colors and pictures; 4) orthographic processing, which includes tasks of morphological comprehension of lexemes and suffixes and homophone comprehension; 5) syntactic processing, including gender, number, function words, and grammatical structure tasks; and 6) semantic processing, which influences reading comprehension tasks through informative and narrative text. Instructions for each task, accompanied by one or two trials (depending on the task) and a demonstration, are delivered by a pedagogical agent prior to the initiation of the testing phase. The application protocol for each task is illustrated here.
Prior to administering the multimedia battery to the study sample, adaptations were made to the Spanish language modality for each country (i.e., Mexico, Guatemala, Ecuador, and Chile), including adjustments to vocabulary, images, and other relevant content. The administration conditions were the same across all Latin American countries. The administration environment had to be quiet within the school and free from noise, distractions, and interruptions. The duration of the multimedia battery administration ranged from 3-4 sessions of 30 min each, depending on the student&#39;s ability and age. Due to its database compatibility with most spreadsheet and statistical data processing systems, the evaluator can analyze the results of each child and each task. Concerning the data collection, two distinct task types were employed: 1) tasks where the examiner records students&#39; oral performance, noting successes and errors using an external mouse, and 2) tasks requiring students to independently select options by clicking on them.

<table><tbody><tr><td>Sicole-R</td><td>Universidad de La Laguna</td><td>TF-263- 07</td><td></td></tr></tbody></table>

advancing dyslexia assessment in children through computerized testing

The acquisition of reading skills is an intricate process that demands the cultivation of various domain-general and domain-specific abilities. Consequently, it is unsurprising that many children grapple with maintaining proficiency at the grade level, particularly when confronted with challenges spanning multiple abilities across both domains, as observed in individuals with reading difficulties. Strikingly, despite reading difficulties being among the most prevalent neurodevelopmental disorders affecting school-aged children, the majority of available diagnostic tools lack a comprehensive framework for assessing the full spectrum of cognitive skills linked to dyslexia, with minimal computerized options. Notably, there are currently limited tools with these features available for Spanish-speaking children. The aim of this study was to delineate the protocol for diagnosing Spanish-speaking children with reading difficulties using the Sicole-R multimedia battery. This tool for elementary grades focuses on evaluating cognitive skills that are associated with dyslexia as prescribed by the scientific literature. Specifically, it concentrates on assessing a range of cognitive abilities that studies have demonstrated to be linked to dyslexia. This focus is based on the observation that individuals with dyslexia typically exhibit deficits in several of the cognitive areas evaluated by this digital tool. The robust internal consistency and multidimensional internal structure of the battery were demonstrated. This multimedia battery has proven to be a fitting tool for diagnosing children with reading difficulties in primary education, offering a comprehensive cognitive profile that is valuable not only for diagnostic purposes but also for tailoring individualized instructional plans.

Sample study 
The sample included 881 participants from Spain (N = 325), Mexico (N = 169), Guatemala (N = 227), and Chile (N = 160), all of whom were native Spanish speakers. The sample was divided into two groups: 451 in the reading disability (RD) group and 430 in the normally achieving readers (NAR) group. Children with special educational needs-those requiring support and specific educational attention due to sensory impairments, neurological issues, or other conditions-were excluded because these factors are typically used as exclusionary criteria for learning disabilities or severe behavioral disorders, either temporarily or for the duration of their schooling. Participants in the RD group were selected based on criteria such as an IQ equal to or greater than 80, a word reading time measurement percentile above the 75th percentile, a pseudoword reading time measurement percentile above the 75th percentile, or a pseudoword reading accuracy measurement percentile below the 25th percentile. Similarly, the NAR group was selected based on comparable criteria, with the addition of a PROLEC36 comprehension task percentile above the 25th percentile. All percentiles were determined according to participants&#39; grade levels. The classification of participants into these groups relied on tasks of word reading and pseudoword reading, each comprising separate blocks. In both blocks, participants were instructed to read aloud the presented verbal stimuli as quickly as possible. The word reading block included 32 stimuli, while the pseudoword reading block contained 48 stimuli. The familiarity of the words was controlled using criteria outlined by Guzman and Jim&#233;nez37. Measures of hits, errors, and latency times were recorded, with latency times measured from the appearance of each item to the start of the student&#39;s vocal response. The word reading block demonstrated high internal consistency (&#945; = .89), while the pseudoword reading block exhibited even greater internal consistency (&#945; = .91). The distribution of students with RD and NAR across different grade levels was as follows: In the second grade, there were 30 NAR and 27 RD students. Transitioning to the third grade, 100 NARs were observed alongside 88 RD students. The fourth grade included 100 NAR and 116 RD students. In the fifth grade, there were 100 NAR and 116 RD students, while in the sixth grade, there were 100 NAR and 104 RD students. To assess age differences in the total sample and within each grade level, one-way ANOVA tests were conducted. The results revealed no significant differences, with all p-values exceeding 0.05. Similarly, the distribution of the gender variable was examined using the chi-square test, with all p values also exceeding 0.05.
Descriptive statistics 
Table 1 presents the descriptive statistics (mean and standard deviation) for age and the assessment measures. The data are categorized by gender, distinguishing between normally achieving readers and those with reading disabilities across various countries. The results showed positive and statistically significant correlations among a large number of assessment measures (see Table 2). The table displays correlations among the measures, spanning from weak to strong. Correlations less than 0.3 are considered weak, while those greater than 0.5 are categorized as strong. Specific correlation values are provided alongside their respective strength classifications. For example, weak correlations (r &#60; 0.3) included those of blending-segmentation (r = 0.354) and deletion-homophone comprehension (r = 0.270). Moderate correlations (0.3 &#8804; r &#60; 0.5) were observed between the grammatical structure-number (r = 0.463) and the functional words-grammatical structure (r = 0.512). Strong correlations (r &#8805; 0.5) are evident for number-gender (r = 0.642) and picture RAN-Color RAN (r = 0.442).
Table 1: Descriptive statistics of the measures. This table provides the mean, standard deviation, and other descriptive statistics for the various measures included in the digital tool. AGE: Age; NAR: Normally Achieving Readers; RD: Reading disability ; SEG: Segmentation; BLN: Blending; ISO: Phoneme isolation; DEL: Phoneme deletion; HOM: Homophone comprehension; R&#38;S: Root &#38; Suffixes; GEN: Gender; NUM: Number; FW: Functional words; GRS: Grammatical Structure; EXT: Expositive Text ; NAT: Narrative Text ; VOC: Voicing of articulation; MOA: Manner of articulation; POA= Place of articulation; DIG: Digit RAN; LET: Letter Ran; COL: Color RAN; PIC: Picture RAN <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67031/Table_1_RE.xlsx" target="_blank">Please click here to download this Table.</a>
Table 2: Correlation coefficients of the measures. This table shows the correlation coefficients between different measures of the digital tool, indicating the strength and direction of the relationships between these measures. SEG: Segmentation; BLN: Blending; ISO: Phoneme isolation; DEL: Phoneme deletion; HOM: Homophone comprehension; R&#38;S: Root &#38; Suffixes; GEN: Gender; NUM: Number; GRS: Grammatical Structure; FW: Functional Words; EXT: Expositive Text ; NAT: Narrative Text ; VOC: Voicing of articulation; MOA: Manner of articulation; POA= Place of articulation; DIG: Digit RAN; LET: Letter Ran; COL: Color RAN; PIC: Picture RAN. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67031/Table 2_RE.xlsx" target="_blank">Please click here to download this Table.</a>
Confirmatory factor analysis 
CFA was conducted to assess the proposed factor structure of the multimedia battery. The model includes one second-order factor and six latent variables, each representing distinct modules of the multimedia battery. These constructs include&#160;phonological awareness (including&#160;phonemic segmentation, isolation, blending,&#160;and deletion tasks), morpho-orthographic&#160;module (involving root and suffixes&#160;and&#160;homophone comprehension tasks), syntax (comprising gender, number, grammatical structure, and functional word tasks), speech perception (involving voicing, manner of articulation, and place of articulation tasks), reading comprehension (encompassing expositive text and narrative text comprehension tasks), and rapid automated naming (letters, colors, digits, and pictures tasks from the RAN task). To ensure consistency across all tasks in the multimedia battery (ranging from 0 to 1), we used the proportion of maximum scaling (POMS) estimation. POMS scores were computed for the time-based tasks (roots and suffixes)38.
Statistical analyses and graphical presentations were performed using R version 4.3.139, employing the lavaan40, semTools41, and ggplot242 packages. Model fit was assessed using various goodness-of-fit indices. Although the chi-square goodness of fit was significant, &#967;2(df) = 632.01, p &#60; .001, which suggests a discrepancy between the hypothesized model and the observed data, it is important to note that the chi-square test is sensitive to sample size43. Therefore, additional fit indices were considered.
The comparative fit index (CFI) yielded a value of .961, exceeding the commonly accepted threshold of .95 and indicating a good fit to the data. The root mean square error of approximation (RMSEA) was .038, indicating a close fit of the model to the data. The standardized root mean square residual (SRMR) was .034, which was below the recommended value of .05, suggesting an ideal fit. Factor loadings for the items ranged from .36 to .81, indicating significant loadings on their respective factors. The total average variance extracted (AVE) exceeded .50, suggesting adequate convergent validity, and the total composite reliability (CR) was above .80, indicating good internal consistency reliability.
In conclusion, the results of the CFA supported the proposed factor structure, demonstrating good model fit, convergent validity, and reliability. Please refer to the graphical representation of the model in Figure 1.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/67031/67031fig01.jpg" /> 
Figure 1: Confirmatory factor analysis. This figure illustrates the results of the confirmatory factor analysis performed on the digital tool, highlighting the factor loadings and the relationships between different cognitive processing measures. Abbreviations: SIC= Sicole-R; PA= Phonological awareness; SEG= Segmentation; BLN= Blending; ISO= Isolation; DEL= Deletion; MO= Morphological processing; HOM= Homophone comprehension; R&#38;S= Root and suffixes; SYN= Syntactic processing; GEN= Gender; NUM= Number; GRS= Grammatical structure; FW= Functional words; RC= Reading comprehension; EXT= Expositive text; NAT= Narrative text; SP= Speech perception; VOC= Voicing of articulation; MOA= Manner of articulation; POA= Place of articulation; RAN= Rapid Automatized Naming; NUM= Number RAN; LET= Letter RAN; COL= Color RAN; PIC= Picture RAN. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67031/67031fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Measurement invariance&#160;analyses were used to test whether&#160;the factor structure of the multimedia&#160;battery&#160;was stable across genders. Testing for measurement invariance consists of a series of model comparisons that define increasingly stringent equality constraints44. We carried out the statistical analyses and followed the same fit model criteria of the previous CFA. We successively constrained parameters representing the configural, metric (loadings), scalar (intercepts), and strict (residuals) structures45. A poor fit in any of these models suggests that the aspect being constrained does not operate consistently for the different groups. The degree of invariance was determined jointly when &#967;2D was &#62;0.05 and &#916;CFI was &#60;0.01. A summary of the results of the indices of the models and the differences between them are shown in Table 3.
Table 3: Invariance model fit indices. This table presents the fit indices for testing the&#160;gender invariance of the model, assessing how well the digital tool maintains consistency in its structure and measurement properties across male and female groups. These indices ensure the tool&#39;s reliability and validity by confirming its ability to measure cognitive processes consistently across diverse gender groups. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67031/Table 3_RE.xlsx" target="_blank">Please click here to download this Table.</a>
The configural model, which constrained only the relative configuration of variables in the model to be the same in both groups, had an adequate fit to the data: &#967;2(292) = 745.970, p&#60;.001, CFI = .964, SRMR = 0.034, RMSEA = .036, 90% CI (.033, .038). The metric invariance model constrained the configuration of variables and all factor loadings to be constant across groups. The fit indices were comparable to those of the configural model: &#967;2(310) = 768.56, p&#60;.001, CFI = .963, SRMR = .037, RMSEA = .036, 90% CI (.033, .038). The invariance of the factor loadings was supported by the nonsignificant difference tests that assessed model similarity: &#967;2D (18) = 26.30, p =.09; &#916;CFI = .001. In the scalar invariance model, the configuration, factor loadings, and indicator means/intercepts were constrained to be the same for each group. The fit indices were less than ideal: &#967;2(322) = 787,50, p&#60;.001, CFI = .963, SRMS = .038, RMSEA = .035 (90% CI = .032, .038). The difference tests that evaluated model similarity suggested that there was factorial invariance: &#967;2D(12)=13.00, p = .369; &#916;CFI = .001. Finally, in the strict invariance model, the configuration, factor loadings, indicator means/intercepts, and residuals were constrained to be the same for each group. The fit indices were less than ideal: &#967;2(341) =798.20, p&#60;.001, CFI = .961, SRMS = .039, RMSEA = .0035 (90% CI = .032, .038). Strict invariance was supported by the nonsignificant difference tests that assessed model similarity: &#967;2D(11) = 25.81, p&#60;.001; &#916;CFI =.002
Diagnostic accuracy 
To evaluate the accuracy and discriminative capacity of the multimedia battery, receiver operating characteristic (ROC) analyses were conducted. ROC analysis aids in determining the optimal threshold (cutoff value) for a continuous-scale assessment test, balancing sensitivity (ability to correctly identify true positives) and specificity (ability to correctly identify true negatives). Additionally, ROC analysis was used to assess the ability of the test to discriminate between the RD and NAR groups. To carry out the analysis, Z scores were calculated per grade for each task of the multimedia battery. The omnibus score consisted of the sum of the zeta scores. Statistical analyses and graphical presentations were carried out using R version 4.3.141. The pROC46 and ggplot242 packages were used. In terms of diagnostic accuracy, the multimedia battery exhibited an area under the curve (AUC) of 9439.8 [95% CI: 93.31%-96.24% (DeLong)] and a sensitivity of 91.0 (Figure 2). The ROC curves by grade showed the following indices: 2&#176; grade, AUC= 96.195% [CI: 91.54%-100% (DeLong)], Se= .96, Sp=.90; 3&#176; grade, AUC= 95.3, [95% CI: 92.43%-98.18% (DeLong)], Se=75.70, Sp= 72.34; 4&#176; grade, AUC=93.4 [95% CI: 90.2%-96.66% (DeLong)], Se=.92, Sp=.84; 5&#176; grade, AUC=95.9 [95% CI: 93.11%-98.75% (DeLong)], Se=.90, Sp=.95; 6&#176; grade, AUC=94.4 [95% CI: 91.11%-97.69% (DeLong)], Se=.92, Sp=.91.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/67031/67031fig02.jpg" /> 
Figure 2: Curve ROC analysis. This figure presents the ROC curve analysis, which shows the diagnostic accuracy of the digital tool by plotting the true positive rate against the false positive rate at various threshold settings. The units for the x-axis of the ROC curve are specificity, and the units for the y-axis are sensitivity. Abbreviations: ROC= receiver operating characteristic curve; AUC= area under the curve. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67031/67031fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

The Multimedia Battery for Assessment of General-Domain and Specific-Domain Skills in Reading is a reliable and valid multimedia battery designed to assess cognitive and basic reading skills. It enables the generation of a comprehensive cognitive and reading performance profile, which is particularly beneficial for children with dyslexia.

Advancing Dyslexia Assessment in Children Through Computerized Testing

The acquisition of reading skills is an intricate process that demands the cultivation of various domain-general and domain-specific abilities. ...

advancing-dyslexia-assessment-in-children-through-computerized-testing

Nanyang Technological University

Research

JoVE Journal

Behavior

668 Views.  Universidad de La Laguna. The Multimedia Battery for Assessment of General-Domain and Specific-Domain Skills in Reading is a reliable and valid multimedia battery designed to assess cognitive and basic reading skills. It enables the generation of a comprehensive cognitive and reading performance profile, which is particularly beneficial for children with dyslexia.

Video: Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale

There has been a long-standing interest in the assessment of the neurobehavioral integrity of the newborn infant. The NICU Network Neurobehavioral Scale (NNNS) was developed as an assessment for the at-risk infant. These are infants who are at increased risk for poor developmental outcome because of insults during prenatal development, such as substance exposure or prematurity or factors such as poverty, poor nutrition or lack of prenatal care that can have adverse effects on the intrauterine environment and affect the developing fetus. The NNNS assesses the full range of infant neurobehavioral performance including neurological integrity, behavioral functioning, and signs of stress/abstinence. The NNNS is a noninvasive neonatal assessment tool with demonstrated validity as a predictor, not only of medical outcomes such as cerebral palsy diagnosis, neurological abnormalities, and diseases with risks to the brain, but also of developmental outcomes such as mental and motor functioning, behavior problems, school readiness, and IQ. The NNNS can identify infants at high risk for abnormal developmental outcome and is an important clinical tool that enables medical researchers and health practitioners to identify these infants and develop intervention programs to optimize the development of these infants as early as possible. The video shows the NNNS procedures, shows examples of normal and abnormal performance and the various clinical populations in which the exam can be used.

The NICU Network Neurobehavioral Scale (NNNS) was developed as an assessment for the at-risk infant. The purpose of this article is to describe the NNNS, provide video examples of the NNNS procedures and discuss the ways in which the exam has been used.

There has been a long-standing interest in the assessment of the neurobehavioral integrity of the newborn infant.  The NICU Network Neurobehavioral Scale ...

Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology to quantitatively assess children&#39;s cortical processing of light touch, speech sounds and the multisensory processing of the 2 stimuli, without requiring active subject participation or causing children discomfort. To accomplish this we developed a dual channel, time and strength calibrated air puff stimulator that allows both tactile stimulation and sham control. We combined this with the use of event-related potential methodology to allow for high temporal resolution of signals from the primary and secondary somatosensory cortices as well as higher order processing. This methodology also allowed us to measure a multisensory response to auditory-tactile stimulation.

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology to quantitatively assess infants and children&#39;s cortical processing of light touch, speech sounds, and the multisensory processing of the 2 stimuli, without requiring active subject participation or causing discomfort in vulnerable patients.

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology ...

Cortical Source Analysis of High-Density EEG Recordings in Children

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.&#160;
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how&#160;EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.&#160;

In recent years, there has been increasing interest in estimating the cortical sources of scalp measured electrical activity for cognitive neuroscience experiments. This article describes how high density EEG is acquired and how recordings are processed for cortical source estimation in children from the age of 2 years at the London Baby Lab.

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and ...

Measuring Attentional Biases for Threat in Children and Adults

Investigators have long been interested in the human propensity for the rapid detection of threatening stimuli. However, until recently, research in this domain has focused almost exclusively on adult participants, completely ignoring the topic of threat detection over the course of development. One of the biggest reasons for the lack of developmental work in this area is likely the absence of a reliable paradigm that can measure perceptual biases for threat in children. To address this issue, we recently designed a modified visual search paradigm similar to the standard adult paradigm that is appropriate for studying threat detection in preschool-aged participants. Here we describe this new procedure. In the general paradigm, we present participants with matrices of color photographs, and ask them to find and touch a target on the screen. Latency to touch the target is recorded. Using a touch-screen monitor makes the procedure simple and easy, allowing us to collect data in participants ranging from 3 years of age to adults. Thus far, the paradigm has consistently shown that both adults and children detect threatening stimuli (e.g., snakes, spiders, angry/fearful faces) more quickly than neutral stimuli (e.g., flowers, mushrooms, happy/neutral faces). Altogether, this procedure provides an important new tool for researchers interested in studying the development of attentional biases for threat.

Here we describe a touch-screen visual search paradigm that can be used to study threat detection across the lifespan. The paradigm has already been used in various studies demonstrating that both children and adults detect threatening stimuli like snakes, spiders, and angry faces faster than non-threatening stimuli.

Investigators have long been interested in the human propensity for the rapid detection of threatening stimuli. However, until recently, research in this ...

Computerized Adaptive Testing System of Functional Assessment of Stroke

The computerized adaptive testing system of the functional assessment of stroke (CAT-FAS) can simultaneously assess four functions (motor functions of the upper and lower extremities, postural control, and basic activities of daily living) with sufficient reliability and administrative efficiency. CAT, a modern measurement method, aims to provide a reliable estimate of the examinee's level of function rapidly. CAT administers only a few items whose item difficulties match an examinee's level of function and, thus, the administered items of CAT can provide sufficient information to reliably estimate the examinee's level of function in a short time. The CAT-FAS was developed through four steps: (1) determining the item bank, (2) determining the stopping rules, (3) validating the CAT-FAS, and (4) establishing a platform of online administration. The results of this study indicate that the CAT-FAS has sufficient administrative efficiency (average number of items = 8.5) and reliability (group-level Rasch reliability: 0.88 - 0.93; individual-level Rasch reliability: &#8805;70% of patients had Rasch reliability score &#8805;0.90) to simultaneously assess four functions in patients with stroke. In addition, because the CAT-FAS is a computer-based test, the CAT-FAS has three additional advantages: the automatic calculation of scores, the immediate storage of data, and the easy exporting of data. These advantages of the CAT-FAS will be beneficial to data management for clinicians and researchers.

Here, we present a protocol to develop the computerized adaptive testing system of the functional assessment of stroke (CAT-FAS). The CAT-FAS can simultaneously assess four functions (two motor functions [upper and lower extremities], postural control, and basic activities of daily living) with sufficient reliability and administrative efficiency.

The computerized adaptive testing system of the functional assessment of stroke (CAT-FAS) can simultaneously assess four functions (motor functions of the ...

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

The purpose of this study was to describe a Spanish protocol that includes reading, writing, and math Curriculum-Based Measures (CBMs) aimed at early detection of students at risk of presenting learning disabilities (LD). Early identification of LD is a critical component of the Response to Intervention (RtI) model. In early grades, the screening of foundational skills mentioned above can provide a data-based guideline for identifying students requiring a more intensive response-based intervention before starting elementary school. We designed different CBMs based on indicators of basic early reading, writing, and math skills [Indicadores de Progreso de Aprendizaje en Lectura, Escritura y Matem&#225;ticas, IPAL, IPAE, and IPAM respectively]&#160;that aim to fulfill the twofold objective of universal screening and evaluation of the Spanish students&#8217; progress. For reading, IPAL includes alphabetic principle, phonological awareness, concepts about print, and riddles in kindergarten. In first and second grades, IPAL includes alphabetic principle, nonsense words fluency, maze sentences, and oral reading fluency. In addition, it includes phonemic segmentation for first grade and prosody for second grade. For writing, IPAE includes copying letters, writing allographs, dictated letters, dictated words with arbitrary spelling, dictated words with rule-based spelling, dictated nonsense words, dictated sentences, writing sentences, and writing a story for first-third grades. Finally, for math, IPAM includes number comparison, missing number, number identification, quantity array, and counting aloud for kindergarten, and number comparison, multi-digit computation, missing number, single-digit computation, and place value for first-third grades.

This work presents a protocol to administrate Spanish Curriculum-Based Measures for the early detection of reading, math, and writing difficulties. These tools could help practitioners and applied researchers working in the context of the Response to Intervention model.

The purpose of this study was to describe a Spanish protocol that includes reading, writing, and math Curriculum-Based Measures (CBMs) aimed at early ...

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Learning disabilities (LDs) encompass disorders of those who have difficulty learning and using academic skills, exhibiting performance below expectations for their chronological age in the areas of reading, writing, and/or mathematics. Each of the disorders making up the LDs involve different deficits; however, some commonalities can be found within that heterogeneity, such in terms of learning self-regulation and metacognition. Unlike in early ages and later educational levels, there are hardly any evidence-based evaluation protocols for adults with LDs. LDs influence academic performance but also have serious consequences in professional, social, and family contexts. In response to this, the current work proposes a multimodal evaluation protocol focused on metacognitive, self-regulation of learning, and emotional processes, which make up the basis of the difficulties in adults with LDs. The assessment is carried out through analysis of the on-line learning process using a variety methods, techniques, and sensors (e.g., eye tracking, facial expressions of emotion, physiological responses, concurrent verbalizations, log files, screen recordings of human-machine interactions) and off-line methods (e.g., questionnaires, interviews, and self-report measures). This theoretically-driven and empirically-based guideline aims to provide an accurate assessment of LDs in adulthood in order to design effective prevention and intervention proposals.

The current work proposes a multimodal evaluation protocol focused on metacognitive, self-regulation of learning, and emotional processes, which make up the basis of the difficulties in adults with LDs.

Learning disabilities (LDs) encompass disorders of those who have difficulty learning and using academic skills, exhibiting performance below expectations ...

Assessing Dyslexia at Six Year of Age

In recent years, there has been an increase in the prevalence of dyslexia at early ages in different countries and regions. This increase has serious consequences within school and family settings, due to the poor academic performance that characterizes people with dyslexia and the socio-emotional problems they sometimes display. One of the most frequent problems in the identification of the dyslexia is the lack of a common diagnostic protocol that encompasses specific criteria for the assessment of any child. The Learning Disabilities and Development Disorders research group at the University of Malaga has developed a protocol for the early detection of dyslexia. The protocol is based on the diagnostic and response to intervention models. Consequently, it takes into account diagnostic criteria agreed upon by some associations and committees of experts, as well as certain specific cognitive and language determinants that characterize people who present with dyslexia following adequate instruction, according to recent research. The action protocol is developed over several stages, and we propose the use of structured interviews with parents and teachers alongside standardized tests for the evaluation of intelligence, reading and writing, as well as the risk factors that determine the appearance of the problem. This action protocol provides a model for the detection of dyslexia, which seeks to distinguish it from other comorbid problems and identify its characteristics and determinants, in order to offer effective intervention and/or prevention from an early age.

This research sets out a proposed protocol for the identification of dyslexia. The protocol is based on diagnostic and response to intervention models. The proposal involves using structured interviews and standardized tests for the assessment of reading and writing performance and determinant factors.

In recent years, there has been an increase in the prevalence of dyslexia at early ages in different countries and regions. This increase has serious ...

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)

Learning mathematics is a complex process that requires the development of multiple domain-general and domain-specific skills. It is therefore not unexpected that many children struggle to stay at grade level, and this becomes especially difficult when several abilities from both domains are impaired, as in the case of mathematical learning disabilities (MLD). Surprisingly, although MLD is one of the most common neurodevelopmental disorders affecting schoolchildren, most of the diagnostic instruments available do not include assessment of domain-general and domain-specific skills. Furthermore, very few are computerized. To the best of our knowledge, there is no tool with these features for Spanish-speaking children. The purpose of this study was to describe the protocol for the diagnosis of Spanish MLD children using the BM-PROMA multimedia battery. BM-PROMA facilitates the evaluation of both skill domains, and the 12&#160;tasks included for this purpose are empirically evidence-based. The strong internal consistency of BM-PROMA and its multidimensional internal structure are demonstrated. BM-PROMA proves to be an appropriate tool for diagnosing children with MLD during primary education. It provides a broad cognitive profile for the child, which will be relevant not only for diagnosis but also for individualized instructional planning.

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

BM-PROMA is a valid and reliable multimedia diagnostic tool that can provide a complete cognitive profile of children with mathematical learning disabilities.

Learning mathematics is a complex process that requires the development of multiple domain-general and domain-specific skills. It is therefore not ...

A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing

Kindergarten writing involves acquiring fundamental skills, such as letter formation, phonemic awareness, and the gradual use of written language to express ideas. In this context, tablet-based curriculum assessments present new opportunities for teaching and evaluating these early writing abilities. To the best of our knowledge, there is currently no tool with these features available for Spanish-speaking children. Therefore, the primary objective of this study was to present a tablet-based protocol for screening at-risk young writers. This tablet-based protocol is specifically designed for kindergarten-level education and serves as a curriculum-based assessment tool that focuses on evaluating early writing skills in young learners. This user-friendly application incorporates interactive tasks and exercises, including assessments of phonological awareness, name writing, alphabet letter copying fluency, and oral narrative skills. These comprehensive evaluations cover various aspects of writing. This application is meticulously aligned with kindergarten curriculum objectives, ensuring that assessments adhere to educational standards. By providing educators with a digital platform to assess and enhance students' writing skills, this tool empowers them to make data-driven decisions for effective instruction during the early stages of writing development. Moreover, it functions as a curriculum-based measurement (CBM), offers valuable support for identifying potential writing challenges in young learners and continuously monitoring their progress. This feature enables early intervention and tailored instruction to optimize writing skill development.

This protocol presents the step-by-step method for using a writing-based, valid, and reliable application designed for kindergarten-level education. It operates as a curriculum-based assessment tool, specifically focusing on evaluating early writing skills in young learners.

Kindergarten writing involves acquiring fundamental skills, such as letter formation, phonemic awareness, and the gradual use of written language to ...