Comparison of children’s gaming scores to NEPSY-II scores: Validation of computer games as cognitive tools

Martinović, Dragana; Burgess, Gerald H.; Pomerleau, Chantal M.; Marin, Cristina

doi:10.1016/j.chb.2015.03.039

Cited by 20 publications

(6 citation statements)

References 31 publications

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“…Regarding mood, we would like to note that we measured it by observing positive mood signals such as smiling or laughing, children' verbal expressions of happiness, their weekly level of excitement or energy, their interest in the content being taught, etc. Table 5 includes a definition of all behavioral parameters used in this study, which have been also used in related research works (Boot, Kramer, Simons, Fabiani, & Gratton, 2008;Campigotto, McEwen, & Demmans Epp, 2013;Dobrowolski, Hanusz, Sobczyk, Skorko, & Wiatrow, 2015; Fern andez-L opez, Rodríguez-F ortiz, Rodríguez-Almendros, & Martínez-Segura, 2013; Helms & Sawtelle, 2007;Karal, Kokoç, & Ayyildiz, 2010;Martinovic, Burgess, Pomerleau, & Marin, 2015;Nouchi et al, 2013). Perceptual and cognitive observations, i.e., attention, memory, reasoning, easiness to handle the program, and intuition were included because engagement with music plays a major role in developing perceptual processing systems that facilitate the encoding and identification of speech sounds and patterns (Azizinezhad, Hashemi, & Darvishi, 2013), thus being used in other works from the related literature as mentioned above.…”

Section: Data Collectionmentioning

confidence: 99%

On the use of a multimedia platform for music education with handicapped children: A case study

Cano

Sánchez-Iborra

2015

Computers & Education

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Section: Data Collectionmentioning

confidence: 99%

On the use of a multimedia platform for music education with handicapped children: A case study

Cano

Sánchez-Iborra

2015

Computers & Education

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“…Additionally, children from the age of 2 years on have been shown to interact meaningfully with touch-screen tablets, understand rules of playing digital games and provide appropriate responses through gestures such as taps and drags, providing a unique opportunity to use gamified neuropsychological tasks for directly assessing children's developmental abilities (Semmelmann et al, 2016). The emerging literature demonstrates that computerized neuropsychological assessments are reliable and valid (Martinovic et al, 2015), and the introduction of "gamification" increases participant engagement and ecological validity (Lumsden et al, 2016;Pitchford and Outhwaite, 2016). The advantages of data in digital format, beyond improvements in efficiency and accuracy, can be further complemented by the use of advanced analytics such as machine learning, which has the potential to predict outcomes using a data-driven approach (Anzulewicz et al, 2016;Bosl et al, 2018), and continually update algorithms to iteratively improve the accuracy of these predictions as more relevant data become available.…”

Section: Introductionmentioning

confidence: 99%

Proof of Concept of a Gamified DEvelopmental Assessment on an E-Platform (DEEP) Tool to Measure Cognitive Development in Rural Indian Preschool Children

et al. 2020

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Over 250 million children in developing countries are at risk of not achieving their developmental potential, and unlikely to receive timely interventions because existing developmental assessments that help identify children who are faltering are prohibitive for use in low resource contexts. To bridge this "detection gap," we developed a tablet-based, gamified cognitive assessment tool named DEvelopmental assessment on an E-Platform (DEEP), which is feasible for delivery by non-specialists in rural Indian households and acceptable to all end-users. Here we provide proof-of-concept of using a supervised machine learning (ML) approach benchmarked to the Bayley's Scale of Infant and Toddler Development, 3rd Edition (BSID-III) cognitive scale, to predict a child's cognitive development using metrics derived from gameplay on DEEP. Two-hundred children aged 34-40 months recruited from rural Haryana, India were concurrently assessed using DEEP and BSID-III. Seventy percent of the sample was used for training the ML algorithms using a 10-fold cross validation approach and ensemble modeling, while 30% was assigned to the "test" dataset to evaluate the algorithm's accuracy on novel data. Of the 522 features that computationally described children's performance on DEEP, 31 features which together represented all nine games of DEEP were selected in the final model. The predicted DEEP scores were in good agreement (ICC [2,1] > 0.6) and positively correlated (Pearson's r = 0.67) with BSID-cognitive scores, and model performance metrics were highly comparable between the training and test datasets. Importantly, the mean absolute prediction error was less than three points (<10% error) on a possible range of 31 points on the BSID-cognitive scale in both the training and test datasets. Leveraging the power of ML which allows iterative improvements as more diverse data become available for training, DEEP, pending further validation, holds promise to serve as an acceptable and feasible cognitive assessment tool to bridge the detection gap and support optimum child development.

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“…Also, video games involve complex cognitive skills that better reflect everyday cognitive function than simple cognitive tasks (Boot et al, 2013). To date, several studies demonstrated associations between video game performance measures and performance on specific cognitive tests, suggesting that video games measure relevant cognitive abilities (Baniqued et al, 2013;Oei and Patterson, 2013;Martinovic et al, 2015) and are feasible to assess cognitive function in older adults (Thompson et al, 2012;Tong et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Development and Evaluation of Maze-Like Puzzle Games to Assess Cognitive and Motor Function in Aging and Neurodegenerative Diseases

Nef

Chesham

Schütz

et al. 2020

Front. Aging Neurosci.

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There is currently a need for engaging, user-friendly, and repeatable tasks for assessment of cognitive and motor function in aging and neurodegenerative diseases. This study evaluated the feasibility of a maze-like Numberlink puzzle game in assessing differences in game-based measures of cognition and motor function due to age and neurodegenerative diseases. Fifty-five participants, including young (18-31 years, n = 18), older (64-79 years, n = 14), and oldest adults (86-98 years, n = 14), and patients with Parkinson's (59-76 years, n = 4) and Huntington's disease (HD; 35-66 years, n = 5) played different difficulty levels of the Numberlink puzzle game and completed usability questionnaires and tests for psychomotor, attentional, visuospatial, and constructional and executive function. Analyses of Numberlink game-based cognitive (solving time and errors) and motor [mean velocity and movement direction changes (MDC)] performance metrics revealed statistically significant differences between age groups and between patients with HD and older adults. However, patients with Parkinson's disease (PD) did not differ from older adults. Correlational analyses showed significant associations between game-based performance and movement metrics and performance on neuropsychological tests for psychomotor, attentional, visuospatial, and constructional and executive function. Furthermore, varying characteristics of the Numberlink puzzle game succeeded in creating graded difficulty levels. Findings from this study support recent suggestions that data from a maze-like puzzle game provide potential "digital biomarkers" to assess changes in psychomotor, visuoconstructional, and executive function related to aging and neurodegeneration. In particular, game-based movement measures from the maze-like puzzle Numberlink games are promising as a tool to monitor the progression of motor impairment in neurodegenerative diseases. Further studies are needed to more comprehensively establish the cognitive validity and test-retest reliability of using Numberlink puzzles as a valid cognitive assessment tool.

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Comparison of children’s gaming scores to NEPSY-II scores: Validation of computer games as cognitive tools

Cited by 20 publications

References 31 publications

On the use of a multimedia platform for music education with handicapped children: A case study

On the use of a multimedia platform for music education with handicapped children: A case study

Proof of Concept of a Gamified DEvelopmental Assessment on an E-Platform (DEEP) Tool to Measure Cognitive Development in Rural Indian Preschool Children

Development and Evaluation of Maze-Like Puzzle Games to Assess Cognitive and Motor Function in Aging and Neurodegenerative Diseases

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