The necessary, albeit belated, transition to computerized cognitive assessment

Asensio, David; Duñabeitia, Jon Andoni

doi:10.3389/fpsyg.2023.1160554

Cited by 5 publications

(2 citation statements)

References 48 publications

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“…Several of these challenges are overcome by supervised computerized assessments [ 10 ] (eg, the National Institutes of Health [NIH] Toolbox [ 11 ], NIH Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research [EXAMINER] [ 12 ], Cogstate [ 13 ], and CNS Vital Signs [ 14 ]). These batteries have strong normative data sets supporting their interpretation, brief testing durations, and automated scoring yet still require administrator training and oversight, device restrictions, or software installation that in some cases prevent widespread scalability, especially in vulnerable populations without access to researcher or clinician support.…”

Section: Introductionmentioning

confidence: 99%

The Real-World Usability, Feasibility, and Performance Distributions of Deploying a Digital Toolbox of Computerized Assessments to Remotely Evaluate Brain Health: Development and Usability Study

Attarha,

Mahncke,

Merzenich

2024

JMIR Form Res

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Background An ongoing global challenge is managing brain health and understanding how performance changes across the lifespan. Objective We developed and deployed a set of self-administrable, computerized assessments designed to measure key indexes of brain health across the visual and auditory sensory modalities. In this pilot study, we evaluated the usability, feasibility, and performance distributions of the assessments in a home-based, real-world setting without supervision. Methods Potential participants were untrained users who self-registered on an existing brain training app called BrainHQ. Participants were contacted via a recruitment email and registered remotely to complete a demographics questionnaire and 29 unique assessments on their personal devices. We examined participant engagement, descriptive and psychometric properties of the assessments, associations between performance and self-reported demographic variables, cognitive profiles, and factor loadings. Results Of the 365,782 potential participants contacted via a recruitment email, 414 (0.11%) registered, of whom 367 (88.6%) completed at least one assessment and 104 (25.1%) completed all 29 assessments. Registered participants were, on average, aged 63.6 (SD 14.8; range 13-107) years, mostly female (265/414, 64%), educated (329/414, 79.5% with a degree), and White (349/414, 84.3% White and 48/414, 11.6% people of color). A total of 72% (21/29) of the assessments showed no ceiling or floor effects or had easily modifiable score bounds to eliminate these effects. When correlating performance with self-reported demographic variables, 72% (21/29) of the assessments were sensitive to age, 72% (21/29) of the assessments were insensitive to gender, 93% (27/29) of the assessments were insensitive to race and ethnicity, and 93% (27/29) of the assessments were insensitive to education-based differences. Assessments were brief, with a mean duration of 3 (SD 1.0) minutes per task. The pattern of performance across the assessments revealed distinctive cognitive profiles and loaded onto 4 independent factors. Conclusions The assessments were both usable and feasible and warrant a full normative study. A digital toolbox of scalable and self-administrable assessments that can evaluate brain health at a glance (and longitudinally) may lead to novel future applications across clinical trials, diagnostics, and performance optimization.

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Section: Introductionmentioning

confidence: 99%

The Real-World Usability, Feasibility, and Performance Distributions of Deploying a Digital Toolbox of Computerized Assessments to Remotely Evaluate Brain Health: Development and Usability Study

Attarha,

Mahncke,

Merzenich

2024

JMIR Form Res

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“…Continuous monitoring of cognitive functions can be achieved through computerized assessments (see Asensio and Duñabeitia, 2023 ), which enable the collection of vast amounts of data from a single patient, overcoming the impracticalities related to having multiple face-to-face interviews. Allard et al (2014) suggest that measuring cognition over time on mobile devices effectively complements traditional testing.…”

Section: Introductionmentioning

confidence: 99%

Cognitive decline monitoring through a web-based application

Sánchez-Vincitore,

Cubilla-Bonnetier,

Marte-Santana

et al. 2023

Front. Aging Neurosci.

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Cognitive decline usually begins after individuals reach maturity, which is more evident in late adulthood. Rapid and constant cognitive screenings allow early detection of cognitive decline and motivate individuals to participate in prevention interventions. Due to accelerated technological advances, cognitive screening and training are now available to the layperson using electronic devices connected to the internet. Large datasets generated by these platforms provide a unique opportunity to explore cognitive development throughout life and across multiple naturalistic environments. However, such data collection mechanisms must be validated. This study aimed to determine whether the data gathered by commercial visuospatial and phonological working memory tests (CogniFit Inc., San Francisco, USA) confirm the well-established argument that age predicts cognitive decline. Data from 3,212 participants (2,238 females) who were 45 years old or older were analyzed. A linear regression analysis explored the relationship between age and working memory while controlling for gender, sleep quality, and physical activity (variables that are known to affect working memory). We found that age negatively predicts working memory. Furthermore, there was an interaction between age and gender for visuospatial working memory, indicating that although male participants significantly outperformed females, the relationship between age and working memory differs for females and males. Our results suggest that the computerized assessment of visuospatial and phonological working memory is sensible enough to predict cognitive functions in aging. Suggestions for improving the sensitivity of self-reports are discussed. Further studies must explore the nature of gender effects on cognitive aging.

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