Psychometric properties of Addenbrooke's Cognitive Examination III (ACE-III): An item response theory approach

Evidence of validity and reliability of the Colombian version of Addenbroke's Cognitive Examination Revised (ACE-R)

OBJECTIVE

The purpose of this study is to provide evidence that supports the validity and reliability of the Colombian version of the Addenbrooke's Cognitive Examination Revised (ACE-R) in comparison to the MMSE at assessing and finding patients with Mild Cognitive Impairment (MCI). Additionally, the study aims to determine the optimal cut-off scores based on the age of a population with a low education level.

METHOD

This study included 314 individuals (235 participants diagnosed with MCI and 79 cognitively healthy) who live in two different rural departments (states) in Colombia. The participants were recruited for this study through community clubs for the older adults. Most of the individuals were female (236), the average age was 65.95 years of age (SD= 7.8), and the average education level was of 3.78 years (SD = 1.79). It is important to note that the sample only included people with a maximum of 6 years of schooling.

RESULTS

A ROC analysis indicated that the ACE-R is more effective than the MMSE at evaluating and finding MCI individuals within the three groups. The cut-off points for the Under 60 years of age group was 83.50 (sensitivity 0.880% and specificity 0.632%); 61-69 years of age 80.50 (sensitivity 0.714% and specificity 0.677%); and Over 70 years of age was 79.50 (sensitivity 0.750% and specificity 0.659%). The internal consistency analysis with MacDonald's Ω determined reliability indicators ≥70 in the ACE-R, except for the age range of 61 to 69 years.

CONCLUSION

The Colombian version of the ACE-R demonstrates to be a valid and reliable global cognitive screening tool. It is effective at discerning MCI individuals from healthy within a group of participants with a low education level.

Illiterate Addenbrooke's Cognitive Examination-III in Three Indian Languages: An Adaptation and Validation Study

BACKGROUND

Literacy is an important factor that predicts cognitive performance. Existing cognitive screening tools are validated only in educated populations and are not appropriate for older adults with little or no education leading to poor performance on these tests and eventually leading to misdiagnosis. This challenge for clinicians necessitates a screening tool suitable for illiterate or low-literate older individuals.

OBJECTIVES

The objective was to adapt and validate Addenbrooke's Cognitive Examination-III (ACE-III) for screening general cognitive functions in illiterate and low-literate older populations in the Indian context in three languages.

METHOD

The Indian illiterate ACE-III was systematically adapted by modifying the original items of the Indian literate ACE-III to assess the cognitive functions of illiterates and low-literates with the consensus of an expert panel of professionals working in the area of dementia and related disorders. A total of 180 illiterate or low-literate participants (84 healthy-controls, 50 with dementia, and 46 with mild cognitive impairment [MCI]) were recruited from three different centers speaking Bengali, Hindi, and Kannada to validate the adapted version.

RESULTS

The optimal cut-off score for illiterate ACE-III to distinguish controls from dementia in all 3 languages was 75. The optimal cut-off scores in distinguishing between controls and MCI ranged from 79 to 82, with a sensitivity ranging from 93% to 99% and a specificity ranging from 72% to 99%.

CONCLUSION

The test is found to have good psychometric properties and is a reliable cognitive screening tool for identifying dementia and MCI in older adults with low educational backgrounds in the Indian context.

A robust harmonization approach for cognitive data from multiple aging and dementia cohorts

INTRODUCTION

Although many cognitive measures have been developed to assess cognitive decline due to Alzheimer's disease (AD), there is little consensus on optimal measures, leading to varied assessments across research cohorts and clinical trials making it difficult to pool cognitive measures across studies.

METHODS

We used a two-stage approach to harmonize cognitive data across cohorts and derive a cross-cohort score of cognitive impairment due to AD. First, we pool and harmonize cognitive data from international cohorts of varying size and ethnic diversity. Next, we derived cognitive composites that leverage maximal data from the harmonized dataset.

RESULTS

We show that our cognitive composites are robust across cohorts and achieve greater or comparable sensitivity to AD-related cognitive decline compared to the Mini-Mental State Examination and Preclinical Alzheimer Cognitive Composite. Finally, we used an independent cohort validating both our harmonization approach and composite measures.

DISCUSSION

Our easy to implement and readily available pipeline offers an approach for researchers to harmonize their cognitive data with large publicly available cohorts, providing a simple way to pool data for the development or validation of findings related to cognitive decline due to AD.

Validation of the test for finding word retrieval deficits (WoFi) in detecting Alzheimer's disease in a naturalistic clinical setting

BACKGROUND

Detecting impaired naming capacity contributes to the detection of mild (MildND) and major (MajorND) neurocognitive disorder due to Alzheimer's disease (AD). The Test for Finding Word retrieval deficits (WoFi) is a new, 50-item, auditory stimuli-based instrument.

OBJECTIVE

The study aimed to adapt WoFi to the Greek language, to develop a short version of WoFi (WoFi-brief), to compare the item frequency and the utility of both instruments with the naming subtest of the widely used Addenbrooke's cognitive examination III (ACEIIINaming) in detecting MildND and MajorND due to AD.

METHODS

This cross-sectional, validation study included 99 individuals without neurocognitive disorder, as well as 114 and 49 patients with MildND and MajorND due to AD, respectively. The analyses included categorical principal components analysis using Cramer's V, assessment of the frequency of test items based on corpora of television subtitles, comparison analyses, Kernel Fisher discriminant analysis models, proportional odds logistic regression (POLR) models and stratified repeated random subsampling used to recursive partitioning to training and validation set (70/30 ratio).

RESULTS

WoFi and WoFi-brief, which consists of 16 items, have comparable item frequency and utility and outperform ACEIIINaming. According to the results of the discriminant analysis, the misclassification error was 30.9%, 33.6% and 42.4% for WoFi, WoFi-brief and ACEIIINaming, respectively. In the validation regression model including WoFi the mean misclassification error was 33%, while in those including WoFi-brief and ACEIIINaming it was 31% and 34%, respectively.

CONCLUSIONS

WoFi and WoFi-brief are more effective in detecting MildND and MajorND due to AD than ACEIIINaming.

Application of machine learning techniques for dementia severity prediction from psychometric tests in the elderly population

Previous research has shown the benefits of early detection and treatment of dementia. This detection is usually performed manually by one or more clinicians based on reports and psychometric testing. Machine learning algorithms provide an alternative method of prediction that may contribute, with an automated process and insights, to the diagnosis and classification of the severity level of dementia. The aim of this study is to explore the use of neuropsychological data from a reduced version of the Addenbrooke's Cognitive Examination III (ACE-III) to predict absence or different levels of dementia severity using the Global Deterioration Scale (GDS) scores through the implementation of the kNN machine learning algorithm. A sample of 1164 elderly people over sixty years old were evaluated using a reduced version of the ACE-III and the GDS. The kNN classifier provided good accuracies using 15 items from the ACE-III and adequately differentiating people with absence and mild impairment, from those with more severe levels of impairment according to the GDS rating. Our results suggest that the kNN algorithm may be used to automate aspects of clinical cognitive impairment classification in the elderly population.

Naming ability assessment in neurocognitive disorders: a clinician's perspective

BACKGROUND

Detecting impaired naming capacity is valuable in diagnosing neurocognitive disorders (ND). A. clinical practice- oriented overview of naming tests validated in ND is not available yet. Here, features of naming tests with validated utility in ND which are open access or available for purchase are succinctly presented and compared.

METHODS

Searches were carried out across Pubmed, Medline and Google Scholar. Additional studies were identified by searching reference lists. Only peer-reviewed journal articles were eligible. A narrative- and tabullar synthesis was used to summarize different aspects of the naming assessment instruments used in patients with ND such as stimuli type, administration time, assessment parameters and accessibility. Based on computational word frequency calculations, the tests were compared in terms of the average frequency of their linguistic content.

RESULTS

Twelve naming tests, relying either on visual or auditory stimuli have been validated in ND. Their content and administration time vary between three and 60 items and one and 20 minutes, respectively. The average frequency of the words of each considered test was two or lower, pointing to low frequency of most items. In all but one test, scoring systems are exclusively based on correctly named items. Seven instruments are open access and four are available in more than one language.

CONCLUSIONS

Gaining insights into naming tests' characteristics may catalyze the wide incorporation of those with short administration time but high diagnostic accuracy into the diagnostic workup of ND at primary healthcare and of extensive, visual or auditory ones into the diagnostic endeavors of memory clinics, as well as of secondary and tertiary brain healthcare settings.

Progression of Cognitive Impairment to Alzheimer's Disease: Through the Lens of Salivary Extracellular Vesicles

The elusiveness encircling around the domain of cognition, its impairment, and the poor prognosis of Alzheimer’s disease has made early diagnosis a necessity. The noticeable symptoms in these conditions appear years later after the neuropathological changes occur in the brain. Exosomes, a small-sized extracellular vesicle facilitate intercellular communication of disease pathologies and their cargo can provide molecular information about its place of origin. The study titled “A novel approach to correlate the salivary exosomes and their protein cargo in the progression of cognitive impairment into Alzheimer’s disease” was an attempt toward understanding the role of salivary small-sized extracellular vesicular (EV’s) cargo in monitoring the progression. Outcomes of the study represent, that the salivary small-sized EV’s (ssEV’s) levels were higher in the cognitively impaired and Alzheimer’s diseased as well the differential expression of the protein in the cargo correlates well with the disease severity staging. Thus, it can help in the development of an early non-invasive screening method.

An Item Response Theory to Analyze the Psychological Impacts of Rail-Transport Delay

Questionnaire instruments have been used extensively by researchers in the literature review for evaluation of various aspects of public transportation. Important implications have been derived from those instruments to improve various aspects of the transport. However, it is important that instruments, which are designed to measure various stimuli, meet criteria of reliability to reflect a real impact of the stressors. Particularly, given the diverse range of commuter characteristics considered in this study, it is necessary to ensure that instruments are reliable and accurate. This can be achieved by finding the relationship between the item’s properties and the underlying unobserved trait, being measured. The item response theory (IRT) refers to measurement of an instrument’s reliability by examining the relationship between the unobserved trait and various observed items. In this study, to determine if our instrument suffers from any potentially associated problems, the IRT analysis was conducted. The analysis was employed based on the graded response model (GRM) due to the ordinal nature of the data. Various aspects of the instruments, such as discriminability and informativity of the items were tested. For instance, it was found while the classical test theory (CTT) confirm the reliability of the instrument, IRT highlight some concerns regarding the instrument. Also, the person fit assessment measure, for instance, highlights some concern regarding respondents answering some of the questions due to lack of interest, choosing answers randomly. Not many studies have examined instruments’ reliability in determining the psychological impacts of public transportation on commuters in the way that was performed here.