A psychometric evaluation of the NIH Toolbox fluid cognition tests adapted for Swahili and Dholuo languages in Kenyan children and adolescents

OBJECTIVE

Our objective was to evaluate the psychometric properties of the culturally adapted NIH Toolbox African Languages® when used in Swahili and Dholuo-speaking children in western Kenya.

METHOD

Swahili-speaking participants were recruited from Eldoret and Dholuo-speaking participants from Ajigo; all were <14 years of age and enrolled in primary school. Participants completed a demographics questionnaire and five fluid cognition tests of the NIH Toolbox® African Languages program, including Flanker, Dimensional Change Card Sort (DCCS), Picture Sequence Memory, Pattern Comparison, and List Sorting tests. Statistical analyses examined aspects of reliability, including internal consistency (in both languages) and test-retest reliability (in Dholuo only).

RESULTS

Participants included 479 children (n = 239, Swahili-speaking; n = 240, Dholuo-speaking). Generally, the tests had acceptable psychometric properties for research use within Swahili- and Dholuo-speaking populations (mean age = 10.5; SD = 2.3). Issues related to shape identification and accuracy over speed limited the utility of DCCS for many participants, with approximately 25% of children unable to match based on shape. These cultural differences affected outcomes of reliability testing among the Dholuo-speaking cohort, where accuracy improved across all five tests, including speed.

CONCLUSIONS

There is preliminary evidence that the NIH Toolbox ® African Languages potentially offers a valid assessment of development and performance using tests of fluid cognition in Swahili and Dholuo among research settings. With piloting underway across other diverse settings, future research should gather additional evidence on the clinical utility and acceptability of these tests, specifically through the establishment of norming data among Kenyan regions and evaluating these psychometric properties.

VR for Cognition and Memory

This chapter will provide a review of research into human cognition through the lens of VR-based paradigms for studying memory. Emphasis is placed on why VR increases the ecological validity of memory research and the implications of such enhancements.

Tracking the Progression and Influence of Beta-Amyloid Plaques Using Percolation Centrality and Collective Influence Algorithm: A Study Using PET Images

Background

The study of brain networks, particularly the spread of disease, is made easier thanks to the network theory. The aberrant accumulation of beta-amyloid plaques and tau protein tangles in Alzheimer's disease causes disruption in brain networks. The evaluation scores, such as the mini-mental state examination (MMSE) and neuropsychiatric inventory questionnaire, which provide a clinical diagnosis, are affected by this build-up.

Purpose

The percolation of beta-amyloid/tau tangles and their impact on cognitive tests are still unspecified.

Methods

Percolation centrality could be used to investigate beta-amyloid migration as a characteristic of positron emission tomography (PET)-image-based networks. The PET-image-based network was built utilizing a public database containing 551 scans published by the Alzheimer's Disease Neuroimaging Initiative. Each image in the Julich atlas has 121 zones of interest, which are network nodes. Furthermore, the influential nodes for each scan are computed using the collective influence algorithm.

Results

For five nodal metrics, analysis of variance (ANOVA; P < .05) reveals the region of interest (ROI) in gray matter (GM) Broca's area for Pittsburgh compound B (PiB) tracer type. The GM hippocampus area is significant for three nodal metrics in the case of florbetapir (AV45). Pairwise variance analysis of the clinical groups reveals five to twelve statistically significant ROIs for AV45 and PiB, respectively, that can distinguish between pairs of clinical situations. Based on multivariate linear regression, the MMSE is a trustworthy evaluation tool.

Conclusion

Percolation values suggest that around 50 of the memory, visual-spatial skills, and language ROIs are critical to the percolation of beta-amyloids within the brain network when compared to the other extensively used nodal metrics. The anatomical areas rank higher with the advancement of the disease, according to the collective influence algorithm.

Association between subfield volumes of the medial temporal lobe and cognitive assessments

Cognitive assessments and neuroimaging are routinely combined in clinical practice to diagnose dementia represented by Alzheimer's disease (AD). The Montreal Cognitive Assessment (MoCA) is reported to be more suitable than the Mini-Mental State Examination (MMSE) for screening mild cognitive impairment (MCI) and mild AD. On the other hand, attention to the subfield volumes of the medial temporal lobe has recently been considered important for the differential diagnosis and early detection of AD. The aim of this study was to uncover which specific hippocampal subfields and adjacent extrahippocampal structures contribute to deficits in cognitive assessment scores in patients with MCI and AD. We recruited from our institute 31 Japanese patients—14 with amnestic MCI and 17 with probable AD, with a clinical dementia rating (CDR) of 0.5 and 1, respectively—and 50 healthy elderly individuals with a CDR of 0. All participants underwent magnetic resonance imaging and cognitive assessments with the MMSE, Wechsler Memory Scale-Revised Logical Memory I and II, and Japanese version of the MoCA (MoCA-J). With adjustment for age and sex, we performed partial correlation analysis of the cognitive assessment scores with the subfield volumes of the medial temporal lobe measured by software-mediated automatic segmentation of hippocampal subfields using high-resolution T1-and T2-weighted images. Compared with normal controls, patients with MCI and AD showed subfield volume reductions in cornu ammonis (CA) 1, CA2, Brodmann area (BA) 35, BA36, the dentate gyrus (DG), the subiculum, and the entorhinal cortex (ERC). All participants showed high correlation coefficients (above 0.6) between cognitive assessment scores and subfield volumes in CA1, the DG, the subiculum, the ERC, and BA36. In patients with MCI and AD, the MoCA-J showed higher correlations than the MMSE with subfield volumes in CA1, the DG, the subiculum, and the ERC. These results suggest that the combination of the in vivo analysis of subfield morphometry of the medial temporal lobe with the MoCA-J paradigm provides important insights into whether changes within specific subfields are related to the cognitive profile in MCI and AD.