Validation of SATURN, a free, electronic, self-administered cognitive screening test

The RODI mHealth app Insight: Machine-Learning-Driven Identification of Digital Indicators for Neurodegenerative Disorder Detection

Neurocognitive Disorders (NCDs) pose a significant global health concern, and early detection is crucial for optimizing therapeutic outcomes. In parallel, mobile health apps (mHealth apps) have emerged as a promising avenue for assisting individuals with cognitive deficits. Under this perspective, we pioneered the development of the RODI mHealth app, a unique method for detecting aligned with the criteria for NCDs using a series of brief tasks. Utilizing the RODI app, we conducted a study from July to October 2022 involving 182 individuals with NCDs and healthy participants. The study aimed to assess performance differences between healthy older adults and NCD patients, identify significant performance disparities during the initial administration of the RODI app, and determine critical features for outcome prediction. Subsequently, the results underwent machine learning processes to unveil underlying patterns associated with NCDs. We prioritize the tasks within RODI based on their alignment with the criteria for NCDs, thus acting as key digital indicators for the disorder. We achieve this by employing an ensemble strategy that leverages the feature importance mechanism from three contemporary classification algorithms. Our analysis revealed that tasks related to visual working memory were the most significant in distinguishing between healthy individuals and those with an NCD. On the other hand, processes involving mental calculations, executive working memory, and recall were less influential in the detection process. Our study serves as a blueprint for future mHealth apps, offering a guide for enhancing the detection of digital indicators for disorders and related conditions.

Newly self-administered two-step tool for screening cognitive function in an ageing Chinese population: an exploratory cross-sectional study

Background

Early screening of cognitive function is critical to dementia treatment and care. However, traditional tests require face-to-face administration and are often limited by implementation costs and biases.

Aims

This study aimed to assess whether the Thoven Cognitive Self-Assessment (TCSA), a novel, innovative two-step touchscreen-based cognition assessment tool, could identify early cognitive impairment due to dementia in older adults.

Methods

The TCSA was administered to 61 healthy controls (HCs), 46 participants with mild cognitive impairment (MCI) and 44 participants diagnosed with dementia recruited from Shanghai. Two outcome measures were generated from the TCSA test: the TCSA_{primary task} score and the TCSA_{secondary task} score.

Results

The total average scores in the control group for the TCSA_{primary task} and TCSA_{secondary task} were significantly higher than those in the MCI and dementia groups (TCSA_{primary task}: HCs vs MCI group vs dementia group, 8.58±1.76 vs 5.40±2.67 vs 2.74±2.11, F=75.40, p<0.001; TCSA_{secondary task}: HCs vs MCI group vs dementia group, 23.02±3.31 vs 17.95±4.93 vs 11.93±5.50, F=76.46, p<0.001). Moreover, receiver operating characteristic analysis showed that a score below 7.5 for the TCSA_{primary task} and a score below 22.5 for the TCSA_{secondary task} were indicators of MCI.

Conclusions

The TCSA appears to be efficacious for the detection of cognitive impairment in older adults. It demonstrates the potential for large-scale cognition screening in community service settings.

Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample

Monitoring of cognitive abilities in large-scale survey research is receiving increasing attention. Conventional cognitive testing, however, is often impractical on a population level highlighting the need for alternative means of cognitive assessment. We evaluated whether response times (RTs) to online survey items could be useful to infer cognitive abilities. We analyzed >5 million survey item RTs from >6000 individuals administered over 6.5 years in an internet panel together with cognitive tests (numerical reasoning, verbal reasoning, task switching/inhibitory control). We derived measures of mean RT and intraindividual RT variability from a multilevel location-scale model as well as an expanded version that separated intraindividual RT variability into systematic RT adjustments (variation of RTs with item time intensities) and residual intraindividual RT variability (residual error in RTs). RT measures from the location-scale model showed weak associations with cognitive test scores. However, RT measures from the expanded model explained 22−26% of the variance in cognitive scores and had prospective associations with cognitive assessments over lag-periods of at least 6.5 years (mean RTs), 4.5 years (systematic RT adjustments) and 1 year (residual RT variability). Our findings suggest that RTs in online surveys may be useful for gaining information about cognitive abilities in large-scale survey research.

Digital Cognitive Biomarker for Mild Cognitive Impairments and Dementia: A Systematic Review

The dementia population is increasing as the world’s population is growing older. The current systematic review aims to identify digital cognitive biomarkers from computerized tests for detecting dementia and its risk state of mild cognitive impairment (MCI), and to evaluate the diagnostic performance of digital cognitive biomarkers. A literature search was performed in three databases, and supplemented by a Google search for names of previously identified computerized tests. Computerized tests were categorized into five types, including memory tests, test batteries, other single/multiple cognitive tests, handwriting/drawing tests, and daily living tasks and serious games. Results showed that 78 studies were eligible. Around 90% of the included studies were rated as high quality based on the Newcastle–Ottawa Scale (NOS). Most of the digital cognitive biomarkers achieved comparable or even better diagnostic performance than traditional paper-and-pencil tests. Moderate to large group differences were consistently observed in cognitive outcomes related to memory and executive functions, as well as some novel outcomes measured by handwriting/drawing tests, daily living tasks, and serious games. These outcomes have the potential to be sensitive digital cognitive biomarkers for MCI and dementia. Therefore, digital cognitive biomarkers can be a sensitive and promising clinical tool for detecting MCI and dementia.

Self-administered Web-Based Tests of Executive Functioning and Perceptual Speed: Measurement Development Study With a Large Probability-Based Survey Panel

BACKGROUND

Cognitive testing in large population surveys is frequently used to describe cognitive aging and determine the incidence rates, risk factors, and long-term trajectories of the development of cognitive impairment. As these surveys are increasingly administered on internet-based platforms, web-based and self-administered cognitive testing calls for close investigation.

OBJECTIVE

Web-based, self-administered versions of 2 age-sensitive cognitive tests, the Stop and Go Switching Task for executive functioning and the Figure Identification test for perceptual speed, were developed and administered to adult participants in the Understanding America Study. We examined differences in cognitive test scores across internet device types and the extent to which the scores were associated with self-reported distractions in everyday environments in which the participants took the tests. In addition, national norms were provided for the US population.

METHODS

Data were collected from a probability-based internet panel representative of the US adult population-the Understanding America Study. Participants with access to both a keyboard- and mouse-based device and a touch screen-based device were asked to complete the cognitive tests twice in a randomized order across device types, whereas participants with access to only 1 type of device were asked to complete the tests twice on the same device. At the end of each test, the participants answered questions about interruptions and potential distractions that occurred during the test.

RESULTS

Of the 7410 (Stop and Go) and 7216 (Figure Identification) participants who completed the device ownership survey, 6129 (82.71% for Stop and Go) and 6717 (93.08% for Figure Identification) participants completed the first session and correctly responded to at least 70% of the trials. On average, the standardized differences across device types were small, with the absolute value of Cohen d ranging from 0.05 (for the switch score in Stop and Go and the Figure Identification score) to 0.13 (for the nonswitch score in Stop and Go). Poorer cognitive performance was moderately associated with older age (the absolute value of r ranged from 0.32 to 0.61), and this relationship was comparable across device types (the absolute value of Cohen q ranged from 0.01 to 0.17). Approximately 12.72% (779/6123 for Stop and Go) and 12.32% (828/6721 for Figure Identification) of participants were interrupted during the test. Interruptions predicted poorer cognitive performance (P<.01 for all scores). Specific distractions (eg, watching television and listening to music) were inconsistently related to cognitive performance. National norms, calculated as weighted average scores using sampling weights, suggested poorer cognitive performance as age increased.

CONCLUSIONS

Cognitive scores assessed by self-administered web-based tests were sensitive to age differences in cognitive performance and were comparable across the keyboard- and touch screen-based internet devices. Distraction in everyday environments, especially when interrupted during the test, may result in a nontrivial bias in cognitive testing.

The practice of teleneurology in the Philippines during the COVID-19 pandemic

Background and objectives

The practice of teleneurology provided an accessible and safe method of consultation during the COVID-19 pandemic. We aimed to describe the practice of teleneurology among Filipino neurologists and determine the factors affecting its adoption using the unified theory of acceptance and use of technology (UTAUT) model and its constructs, namely performance expectancy, effort expectancy, social influence, and facilitating conditions.

Methods

This was a cross-sectional survey conducted online last October 2020 involving adult and pediatric neurologists in the Philippines. The internal consistency of the questionnaire adapted from UTAUT model was determined using Cronbach’s alpha. We performed logistic regression analysis to determine which constructs of the UTAUT model were significant factors on the intent to practice teleneurology.

Results

The study yielded a 28.8% response rate. Among the respondents (n₁ = 147), 95.2% (n₂ = 140) practiced teleneurology during the pandemic, and 77.6% (n₁ = 147) planned to continue it after the pandemic. Teleneurology was mostly done on an outpatient basis on social media platforms via videoconferencing due to easier access for both end-users. The UTAUT model explained 80.9% (95% CI 0.76, 0.86a) of the total variation. Performance expectancy and facilitating conditions affect the intent to use teleneurology.

Conclusions

Due to the limited resources and knowledge of its practice, infrastructural support and benefit awareness campaigns would be beneficial to increase its adoption, especially in developing countries.