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>
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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 border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<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

595 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 ...

Testing Sensory and Multisensory Function in Children with Autism Spectrum Disorder

In addition to impairments in social communication and the presence of restricted interests and repetitive behaviors, deficits in sensory processing are now recognized as a core symptom in autism spectrum disorder (ASD). Our ability to perceive and interact with the external world is rooted in sensory processing. For example, listening to a conversation entails processing the auditory cues coming from the speaker (speech content, prosody, syntax) as well as the associated visual information (facial expressions, gestures). Collectively, the &#8220;integration&#8221; of these multisensory (i.e., combined audiovisual) pieces of information results in better comprehension. Such multisensory integration has been shown to be strongly dependent upon the temporal relationship of the paired stimuli. Thus, stimuli that occur in close temporal proximity are highly likely to result in behavioral and perceptual benefits &#8211; gains believed to be reflective of the perceptual system&#39;s judgment of the likelihood that these two stimuli came from the same source. Changes in this temporal integration are expected to strongly alter perceptual processes, and are likely to diminish the ability to accurately perceive and interact with our world. Here, a battery of tasks designed to characterize various aspects of sensory and multisensory temporal processing in children with ASD is described. In addition to its utility in autism, this battery has great potential for characterizing changes in sensory function in other clinical populations, as well as being used to examine changes in these processes across the lifespan.

We describe how to implement a battery of behavioral tasks to examine the processing and integration of sensory stimuli in children with ASD. The goal is to characterize individual differences in temporal processing of simple auditory and visual stimuli and relate these to higher order perceptual skills like speech perception.

In addition to impairments in social communication and the presence of restricted interests and repetitive behaviors, deficits in sensory processing are ...

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device (ALDM) Test Systems

Fagot &#38; Paleressompoulle1 and Fagot &#38; Bonte2 have published an automated learning device (ALDM) for the study of cognitive abilities of monkeys maintained in semi-free ranging conditions. Data accumulated during the last five years have consistently demonstrated the efficiency of this protocol to investigate individual/physical cognition in monkeys, and have further shown that this procedure reduces stress level during animal testing3. This paper demonstrates that networks of ALDM can also be used to investigate different facets of social cognition and in-group expressed behaviors in monkeys, and describes three illustrative protocols developed for that purpose. The first study demonstrates how ethological assessments of social behavior and computerized assessments of cognitive performance could be integrated to investigate the effects of socially exhibited moods on the cognitive performance of individuals. The second study shows that batteries of ALDM running in parallel can provide unique information on the influence of the presence of others on task performance. Finally, the last study shows that networks of ALDM test units can also be used to study issues related to social transmission and cultural evolution. Combined together, these three studies demonstrate clearly that ALDM testing is a highly promising experimental tool for bridging the gap in the animal literature between research on individual cognition and research on social cognition.

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

Fagot &#38; Paleressompoulle1 have published an automated learning device (ALDM) aimed at testing individual cognitive abilities in semi-free ranging monkeys. The main goal of our protocol is to use a network of ALDM test units to study social cognition in non-human primates.

Fagot &#38; Paleressompoulle1 and Fagot &#38; Bonte2 have published an automated learning device (ALDM) for the study of cognitive abilities of monkeys ...

Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses

Collecting reliable behavioral data from toddlers and preschoolers is challenging. As a result, there are significant gaps in our understanding of human auditory development for these age groups. This paper describes an observer-based procedure for measuring hearing sensitivity with a two-interval, two-alternative forced-choice paradigm. Young children are trained to perform a play-based, motor response (e.g., putting a block in a bucket) whenever they hear a target signal. An experimenter observes the child&#39;s behavior and makes a judgment about whether the signal was presented during the first or second observation interval; the experimenter is blinded to the true signal interval, so this judgment is based solely on the child&#39;s behavior. These procedures were used to test 2 to 4 year-olds (n = 33) with no known hearing problems. The signal was a 1,000 Hz warble tone presented in quiet, and the signal level was adjusted to estimate a threshold corresponding to 71%-correct detection. A valid threshold was obtained for 82% of children. These results indicate that the two-interval procedure is both feasible and reliable for use with toddlers and preschoolers. The two-interval, observer-based procedure described in this paper is a powerful tool for evaluating hearing in young children because it guards against response bias on the part of the experimenter.

This paper describes a procedure for measuring hearing sensitivity in 2 to 4 year-old children. Children are trained to perform play-based responses when they hear a target signal. Thresholds are then estimated in a two-interval, two-alternative forced-choice paradigm, based on observations of the child&#39;s behaviors.

Collecting reliable behavioral data from toddlers and preschoolers is challenging. As a result, there are significant gaps in our understanding of human ...

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children &#8211; Working Memory (CABC-WM)

The Comprehensive Assessment Battery for Children - Working Memory (CABC-WM) is a computer-based battery designed to assess different components of working memory in young school-age children. Working memory deficits have been identified in children with language-based learning disabilities, including dyslexia1,2 and language impairment3,4, but it is not clear whether these children exhibit deficits in subcomponents of working memory, such as visuospatial or phonological working memory. The CABC-WM is administered on a desktop computer with a touchscreen interface and was specifically developed to be engaging and motivating for children. Although the long-term goal of the CABC-WM is to provide individualized working memory profiles in children, the present study focuses on the initial success and utility of the CABC-WM for measuring central executive, visuospatial, phonological loop, and binding constructs in children with typical development. Immediate next steps are to administer the CABC-WM to children with specific language impairment, dyslexia, and comorbid specific language impairment and dyslexia.

Working memory predicts a significant amount of variance for a variety of cognitive tasks, including speaking, reading, and writing. However, few tools are available to assess working memory in children. We present an innovative, computer-based battery that comprehensively assesses different components of working memory in school-age children.

The Comprehensive Assessment Battery for Children - Working Memory (CABC-WM) is a computer-based battery designed to assess different components of ...

Classical Short-Delay Eyeblink Conditioning in One-Year-Old Children

Classical eyeblink conditioning (EBC) refers to the learned association between a conditioned stimulus (an auditory tone) and an unconditioned stimulus (a puff of air to the cornea). Eyeblink conditioning is often used experimentally to detect abnormalities in cerebellar-dependent learning and memory that underlies this type of associative learning. While experiments in adults and older children are relatively simple to administer using commercial equipment, eyeblink conditioning in infants is more challenging due to their poor compliance, which makes correct positioning of the equipment difficult. To achieve conditioning in one-year-old infants, a custom-made or an adapted commercial system can be used to deliver the air puff to the infant's cornea. The main challenge lies in successfully detecting and classifying the behavioral responses. We report that automated blink detection methods are unreliable in this population, and that conditioning experiments should be analyzed using frame-by-frame analysis of supplementary video camera recordings. This method can be applied to study developmental changes in eyeblink conditioning and to examine whether this paradigm can detect children with neurological disorders.

This protocol describes an eyeblink conditioning paradigm appropriate for experiments with one-year-old infants. Commercial or custom-made equipment can be used to deliver the stimuli, and data collection and analysis should be performed on the video recordings.

Classical eyeblink conditioning (EBC) refers to the learned association between a conditioned stimulus (an auditory tone) and an unconditioned stimulus (a ...

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 ...