AbstractBackground: The Addenbrooke's Cognitive Examination (ACE) is used to measure cognition across a range of domains in dementia. Identifying the order in which cognitive decline occurs across items, and whether this varies between dementia aetiologies could add more information to subdomain scores. Method: ACE-Revised data from 350 patients were split into three groups: Alzheimer's type (n = 131), predominantly frontal (n = 119) and other frontotemporal lobe degenerative disorders (n = 100). Results of factor analysis and Mokken scaling analysis were compared. Results: Principal component analysis revealed one factor for each group.
Confirmatory factor analysis found that the one-factor model fit two samples poorly. Mokken analyses revealed different item ordering in terms of difficulty for each group. Conclusion: The different patterns for each diagnostic group could aid in the separation of these different types of dementia.© 2015 S.
Karger AG, BaselIntroductionCognitive measures are commonly used to screen for dementia as well as assessing severity and monitoring disease progression. Often underlying these tests is the assumption that cognition deteriorates along a fixed course of decline on a single cognitive trait (i.e. Total test scores are considered meaningful in themselves) and that the impairment and severity can be measured when a patient is unable to respond correctly to certain cognitive challenges. Looking at total and subdomain scores may lead to important information being neglected. For example, two different individuals achieving the same score on a cognitive measure may have reached this score by missing different combinations of items. Using the summed score as a measure of cognition fails to take into account the information embedded in the specific pattern of scores. Items may differ in several ways.
Different items on a scale may be unequally related to the construct of cognitive impairment. Additionally, test items are likely to differ in terms of difficulty - how difficult an individual finds it to respond correctly to an item.The Addenbrooke's Cognitive Examination (ACE) was originally developed to provide a brief test that would be both sensitive to the initial symptoms of dementia and capable of discriminating different types of dementia including Alzheimer's disease (AD) and frontotemporal dementia (FTD). The ACE and the revised version (ACE-R) encompass tests of attention/orientation, memory, language, visuospatial abilities and executive function. They also incorporate the Mini-Mental State Examination , so this score may also be produced. The ACE is relatively quick to administer (approximately 15 min) and has good sensitivity and specificity for identifying dementia. While modifications to the ACE have been made to address the original scale's weaknesses, there have been no examinations of the item properties or ‘hierarchical' structure of either the original ACE or its successor the ACE-R using item response theory (IRT) methods.
A hierarchical scale in the context of IRT implies that all scale items are ordered relative to each other in terms of their level of difficulty (i.e. The ease with which an item is responded to) and that all are ordered along the latent trait being measured.
All references to hierarchical scales in this paper will refer to this IRT hierarchical ordering by difficulty.Factor analysis can be used to investigate the relationship between ACE-R items and the total score. While this method offers some insight into the dimensionality of the ACE-R, IRT can provide further insight into the item properties and how they function in relation to the other items within the scale. This item level analysis can be applied to determine the items for a hierarchy of item difficulty.The interpretation of the ACE-R and other cognitive measures would be greatly improved if the ordering of the difficulty of the cognitive tasks (items) was similar for patients at different stages of dementia. When the ordering of the items by mean scores is the same across different values of the latent construct, it can be said that items conform to a hierarchical scale with invariant item ordering (IIO). Fundamentally, IIO means that the items in a scale ‘have the same order with respect to difficulty or attractiveness for all respondents' , p.
Brief Neuropsychological Cognitive Examination Bnce
IIO is a very important property as once this has been established, the item ordering within the scale in question will be the same for the population of interest, along with any subgroup of the population. IIO can facilitate diagnosing dementia. For example, an IIO hierarchy detailing the expected trajectory of decline in AD may differ from an IIO hierarchy of decline in semantic dementia (SD). In this way, IIO hierarchies can be used to identify distinctive profiles of cognitive dysfunction which can serve as an adjunct to diagnosis. IIO can also facilitate the comparison of patients with respect to their degree of cognitive decline, for example a patient experiencing problems with one of the least difficult items in the hierarchy would be considered more severely impaired than a patient only experiencing a problem with one of the most difficult items in the hierarchy. IIO hierarchies can also be useful in the detection of unexpected score patterns and in characterising differences among subgroups and different forms of dementia.Mokken scaling analysis , based on IRT principles, is commonly applied to determine whether hierarchical scales meeting IIO criteria exist within data.
This method has been more frequently applied to dichotomous items within scales. However, examining polytomous scales (i.e. Scales with more than two response options, for example ‘strongly disagree', ‘disagree', ‘agree', ‘strongly agree' or an item with a score range of 0-3) for IIO has recently become possible ,.The aim of the present study is to determine whether the ACE-R has hierarchical properties with IIO and to compare these findings with factor analysis using structural equation modelling to determine whether a hierarchy of item difficulty can add to the information provided by the subdomain scores.
Methods ParticipantsA sample of 350 patients was sourced from the specialist multidisciplinary tertiary referral centre FRONTIER (the Frontotemporal Dementia Research Group) at Neuroscience Research Australia (NeuRA), Sydney. Patients meeting current clinical diagnostic criteria for behavioural variant FTD (bv-FTD) , AD , logopenic progressive aphasia (LPA) , motor neurone disease (MND) , progressive non-fluent aphasia (PNFA) or SD were recruited through FRONTIER.
Diagnosis was established by consensus among neurologist, neuropsychologist and occupational therapist, based on extensive clinical assessments, cognitive assessment and evidence of atrophy on structural MRI brain scans. All patients provided informed consent for the study, and dual consent was obtained from the carer in some cases. Patients underwent clinical, neuropsychological, behavioural and imaging assessment between 2007 and 2011.
Data from patients with complete itemised ACE-R data (n = 350) were included in the analysis.The sample was very diagnostically heterogeneous, and in an attempt to limit the effects of this heterogeneity, the sample was divided into three groups: AD type: AD and LPA (n = 131); predominantly frontal dementia: bv-FTD and FTD-MND (n = 119); other frontotemporal lobe degenerative disorders, other frontotemporal lobe degenerative disorders temporal: SD and PNFA (n = 100). MeasuresThe ACE-R comprises 26 items, is scored out of 100 and includes items assessing 5 cognitive domains: attention/orientation (18 points), memory (26 points), fluency (14 points), language (26 points) and visuospatial (16 points).
The total ACE-R score is created by the addition of all item scores across all domains.The mean for each ACE-R item score was divided by the maximum number of points available for that item to equate scores for comparison (i.e. Equal weighting of items even though items can contribute different weighted values to the summed total score), giving an item score with minimum 0 and maximum 1. For example, the mean score of 2.5 for ‘memory retrograde' for the predominantly frontal group was divided by 4 (the maximum number of points available on this item) to give a new ‘overall' mean score of 0.625.
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These equated mean item scores were used for the analyses.Although the rescoring of ‘naming (10 items)' potentially removes some important variation in response, this was minimised by collapsing the item responses at the bottom end of the range since the prevalence of responses in the lowest category is very low (n = 34, 9.7%). Factor AnalysesTo identify the underlying factor structure, an exploratory principal component analysis (PCA) was performed on the subdomain scores for each of the diagnostic groups using the IBM SPSS, version 19. Inspection of scree plots and the Kaiser criterion of eigenvalues 1 were used to decide on the number of components to extract.The final factor solution derived from the PCA was entered into AMOS and converted to a simple structure confirmatory factor analysis (CFA) model, in which one latent variable explained the covariance in the five subdomains. CFA was performed on the emergent factor structure to evaluate whether the PCA model fit the data well. The Comparative Fit Index (CFI) and the root mean square error of approximation (RMSEA) were used to estimate the model fit. The following rules of thumb with regard to model fit were used: CFI 0.95 indicates a good model fit; RMSEA 0.10 indicates a poor fit, 0.5 0.3 indicating a scale with IIO. Visual inspection of item pair plots was also used to assess IIO.
Brief Neuropsychological Cognitive Examination
Item rest-score regression plots were visually inspected to identify item overlap or ‘outlying' items: items located far away from the cluster of the other scale items. These items can cause artificially exaggerated IIO and can result in the misleading appearance of IIO. ResultsA total of 350 participants (232 male, 118 female) with a mean age of 65.38 (standard deviation = 8.5) years, diagnosed with dementia were included in the analysis (table ). The sample was diagnostically heterogeneous: bv-FTD (n = 96), AD (n = 88), SD (n = 61), LPA (n = 43), PNFA (n = 39) and FTD-MND (n = 23). ACE-R items grouped by domain, means and total scores PCA AnalysisVisual inspection of scree plots and Kaiser's criterion were used to extract factors with an eigenvalue 1. Both methods suggested a single-factor structure with the extraction of one component with an eigenvalue 1 for the AD type, predominantly frontal, and patients diagnosed with other frontotemporal lobe degenerative disorders, explaining 65, 68 and 61% of the variance in the groups, respectively.
The correlations between the extracted component and the ACE-R subdomains are similar across the three diagnostic groups, as shown in table. Correlations between ACE-R subdomains and the component extracted from PCA CFA AnalysisThis one-factor model derived from PCA was converted to a CFA model. CFA was performed to evaluate whether the PCA model fit the data well.
Whereas PCA examined all variance, the CFA model examined the shared variance. This model fit the data well in the predominantly frontal group (χ 2 = 6.754, d.f. = 5; CFI = 0.994; RMSEA = 0.054) but less successfully in the AD type groups (χ 2 = 18.405, d.f.
= 5; CFI = 0.957; RMSEA = 0.143) and other frontotemporal lobe degenerative disorders group (χ 2 = 40.327, d.f. = 5; CFI = 0.841; RMSEA = 0.269). Based on the CFI and RMSEA, the one-factor model fitted the AD type and other frontotemporal lobe degenerative disorders groups poorly. Mokken Scaling AnalysisAD TypeMokken's scalability coefficients were examined to assess the unidimensionality of the items. The H i values of 6 items were below the recommended threshold level (0.3) for retaining items. These items: 'draw overlapping pentagons', ‘draw a cube', ‘count dot arrays', ‘follow written instruction', ‘three-item recall', and ‘repetition-no ifs, ands or buts' were removed.
These low values suggest that the items have weak discriminatory power. There were no violations of monotonicity. Therefore, the remaining 20 items were deemed sufficiently homogenous to be unidimensional on the basis of the item scalability coefficients and H of 0.45.Assessment of IIO resulted in 32 violations, 16 of which were significant. Starting with the item with the greatest violation, items were removed iteratively until no further violations remained. This process prompted the removal of a further 6 items (‘identify fragmented letters', ‘verbal fluency-animals', ‘name and address learning', ‘semantic comprehension', ‘verbal fluency-letters', ‘repetition of single multi-syllabic words'). The removal of these items resulted in 14 out of the original 26 items being retained in a moderately strong hierarchical Mokken scale H = 0.44, standard error (SE) = 0.04 with IIO ( H T = 0.69). Inspection of item pair plots resulted in the exclusion of a further 3 items; ‘repetition-above, beyond and below' and ‘reading' were shown to intersect (fig.
) and ‘naming (10 items)' was identified as being located at some distance from the other items (fig. ) which could be driving the high H T value. The removal of these additional items left 11 items conforming to a moderate Mokken scale ( H = 0.43, SE = 0.04) and lowered the strength of IIO ( H T = 0.52). Example of item pair plot for ‘naming (10 items)' lying at some distance from a selection of remaining item pair plots.
A Item pair plots for ‘naming (10 items)' (solid line) and ‘write a sentence' (dashed line). B Item pair plots for ‘naming (10 items)' (solid line) and ‘reading' (dashed line). C Item pair plots for ‘naming (10 items)' (solid line) and ‘repetition-above, beyond and below' (dashed line).Discriminatory values of these items are presented in table in the order of decreasing item scalability coefficients. SEs of scalability coefficients are also provided. IIO hierarchies with items ordered from most to least difficult in each diagnostic groupPredominantly Frontal DementiaFour items were removed due to low H i values; ‘draw a cube', ‘repetition-no ifs, ands or buts', ‘repetition of single multi-syllabic words' and word reading'. There were no violations of monotonicity. The remaining 22 items were sufficiently homogenous to be considered unidimensional ( H = 0.52).There were 42 violations of IIO, 32 of which were significant.
This process resulted in the removal of 6 items (‘identify fragmented letters', ‘three-item registration', ‘syntactical comprehension', ‘verbal fluency-animals', ‘verbal fluency-letters', ‘name and address recall'). Following the removal of these items, 16 items were retained in a strong Mokken scale ( H = 0.52, SE = 0.05) with IIO ( H T = 0.82).Some intersection was observed from visual inspection of the item pair plots. This warranted the further exclusion of 4 items: ‘write a sentence', ‘draw intersecting pentagons', ‘repetition-above beyond and below' and ‘follow written instruction-close eyes' (fig. This left 12 items which conformed to a strong Mokken scale ( H = 0.54, SE = 0.05) with a lowered strength of IIO ( H T = 0.72; see table for item ordering by discrimination and table for item ordering by difficulty). Example of intersecting items from predominantly frontal dementia analysis.
A Item pair plots for ‘follow written instruction-close eyes' (solid line) and ‘write a sentence' (dashed line). B Item pair plots for ‘draw intersecting pentagons' (solid line) and ‘repetition above, beyond and below' (dashed line). C Item pair plots for ‘draw intersecting pentagons' (solid line) and ‘write a sentence' (dashed line). D Item pair plots for ‘repetition-above, beyond and below' (solid line) and ‘write a sentence' (dashed line).Other Frontotemporal Lobe Degenerative DisordersTen items were removed due to low H i values (‘follow written instruction', ‘repetition of single multi-syllabic words', ‘repetition-above, beyond and below', ‘repetition-no ifs, ands or buts', ‘naming (10 items)', ‘draw overlapping pentagons', ‘draw a cube', ‘count dot arrays', ‘syntactical comprehension', ‘semantic comprehension'). Again, there were no violations of monotonicity.
The remaining 16 items were sufficiently homogenous to be considered unidimensional ( H = 0.44).There were only two violations of IIO. This resulted in the exclusion of a further 2 items ‘identify fragmented letters', ‘naming (pencil and watch)'.
Following the removal of these items, 14 items were retained in a moderate Mokken scale ( H = 0.45, SE = 0.04) with IIO ( H T = 0.65). No further items were excluded following inspection of item plots.Items of this IIO subset are presented in the order of discrimination (table ) and difficulty (table ).
DiscussionThis study aimed to determine if hierarchies of ACE-R items meeting IIO criteria were present in three different samples consisting of different dementia diagnoses and to establish whether these hierarchies add anything to the subdomain scores and factor structure revealed by PCA. Mokken scaling analyses of the full 26 items of the scale for each of the three samples resulted in 11 items being retained in an IIO hierarchy in the AD type sample, 12 items in the predominantly frontal dementia sample and 14 items in the other frontotemporal lobe degenerative disorders sample.The results of PCA did not indicate a difference between groups, with all groups being dominated by a large single component with similar item loadings. However, CFA analyses indicate that the structure of the one-factor model did not fit two of the three groups: AD type and other frontotemporal lobe degenerative disorders.
The rickover effect ebook download. Combining results of exploratory and confirmatory factor analyses and Mokken scaling analyses suggests that the factor structure of the ACE-R domains and the item ordering by difficulty within domains differ between diagnostic groups. These domain and item level differences could be applied to further differentiate different types of dementia by their associated ACE-R performance profiles.In comparison with factor analysis, Mokken scaling has considerable theoretical and practical advantages.
Whereas factor analysis identifies groups of highly correlating items, Mokken scaling can illustrate the systematic order relationship between the items in a scale which improves construct validity. Additionally, factor loadings disregard how item performance may differ across levels of the latent trait. These advantages of Mokken scaling offer meaningful clinical implications.
Establishing a formal hierarchy of item difficulty within a scale adds to the possibilities of interpretation and application. Hierarchical scales are appealing for their ease of use and scoring. Responses to individual items, not just total scores, can provide an insight into a patient's level of ability based on the item's degree of difficulty. For example, across the three diagnostic groups, a patient responding correctly to the ‘memory retrograde' item is unlikely to have difficulty with any of the less difficult items. This insight enables quicker estimations of a patient's cognitive functioning and can facilitate adaptive testing, whereby only a selection of items, either from the more difficult or the less difficult range of the scale depending on the ability of the specific patient, is required for testing.
Tailoring tests to specific levels of ability can reduce testing time and stress and burden on patients.Mokken scaling of dementia screening instruments can be used to assess whether the cognitive abilities are lost - or retained - hierarchically. Establishing whether these hierarchies differ across diagnostic groups can be useful in differential diagnosis. Although the comparison between the hierarchies is hampered by the lack of common items between the hierarchies, there are several notable differences in the ordering of item difficulty among the common items between the groups. Published online: April 15, 2015Issue release date: January – AprilNumber of Print Pages: 15Number of Figures: 3Number of Tables: 5eISSN: (Online)For additional information:Open Access License / Drug Dosage / DisclaimerOpen Access License: This is an Open Access article licensed under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported license (CC BY-NC) , applicable to the online version of the article only. Distribution permitted for non-commercial purposes only.Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication.
However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.
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TONKONOGY, MD, PHDThis convenient test assesses the cognitive functions targeted in a typical neuropsychological exam. In less than 30 minutes, it gives you a general cognitive profile that can be used for screening, diagnosis, or follow-up. More efficient than a neuropsychological battery and more thorough than a screener, BNCE is an ideal way to evaluate the cognitive status of patients with psychiatric disorders or psychiatric manifestations of neurological diseases.
Measure Processing Skills Needed for Everyday FunctioningAppropriate for individuals 18 years of age and older, the BNCE assesses:. Working memory.
Gnosis. Praxis. Language. Orientation. Attention. Executive functionsIt is composed of 10 subtests, none requiring more than minimal reading skills. Five of these subtests measure the ability to process conventional, frequently used information, while the remaining five measure the ability to process novel or incomplete information.
The test focuses on processing skills needed for everyday functioning, and is sensitive to mild impairment often missed by other brief cognitive screeners. Find Out How the Patient Processes Novel Versus Conventional InformationThe BNCE gives you subtest scores, a total score indicating overall severity, and two aggregate scores for the simple and complex subtests—so that you can look at the patient’s ability to process conventional versus novel information.
Results can help you differentiate problems caused by subcortical lesions from those caused by cortical lesions and those caused by primary psychiatric disorders. The BNCE Manual is unique in that it provides extensive guidance in interpreting test results. Quickly Uncover Cognitive AbnormalitiesThe BNCE is an excellent way to start a process-oriented neuropsychological exam—it quickly reveals specific cognitive abnormalities that may warrant more detailed evaluation. And it can be used to monitor the course of both psychiatric and neurological disease.
It has been found especially useful in evaluating patients with sequelae of head injury, stroke, encephalitis, and primary degenerative disorders such as Alzheimer’s, Huntington’s, Parkinson’s, and Pick’s diseases, and those suffering from seizure disorders, schizophrenia, mood disorders, and alcohol and drug abuse.
It is common for clinicians to be uncertain as to whether a patient is demonstrating behaviors that suggest cognitive impairment. It is important to quickly assess which of these patients are actually demonstrating cognitive impairment that may be contributing to functional problem. Numerous cognitive measures have been developed in an attempt to quickly and efficiently examine one or several areas of cognitive abilities to determine if a more thorough evaluation is necessary.
Certain screening examinations are utilized by physicians before referring to neuropsychological testing. Often, skills such as orientation, attention, language abilities, memory.
.Neuropsychological tests are specifically designed tasks used to measure a psychological function known to be linked to a particular structure or pathway. Tests are used for into brain function and in a setting for the diagnosis of deficits. They usually involve the systematic administration of clearly defined procedures in a formal environment. Neuropsychological tests are typically administered to a single person working with an examiner in a quiet office environment, free from distractions. As such, it can be argued that neuropsychological tests at times offer an estimate of a person's peak level of cognitive performance.
Neuropsychological tests are a core component of the process of conducting, along with personal, interpersonal and contextual factors.Most neuropsychological tests in current use are based on traditional theory. In this model, a person's on a test is compared to a large general population sample, that should ideally be drawn from a comparable population to the person being examined. Normative studies frequently provide data stratified by age, level of education, and/or ethnicity, where such factors have been shown by research to affect performance on a particular test.
This allows for a person's performance to be compared to a suitable, and thus provide a fair assessment of their current cognitive function.According to Larry J. Seidman, the analysis of the wide range of neuropsychological tests can be broken down into four categories. First is an analysis of overall performance, or how well people do from test to test along with how they perform in comparison to the average score. Second is left-right comparisons: how well a person performs on specific tasks that deal with the left and right side of the body. Third is pathognomic signs, or specific test results that directly relate to a distinct disorder. Finally, the last category is differential patterns, which are strange test scores that are typical for specific diseases or types of damage. Contents.Categories Most forms of cognition actually involve multiple cognitive functions working in unison, however tests can be organised into broad categories based on the cognitive function which they predominantly assess.
Some tests appear under multiple headings as different versions and aspects of tests can be used to assess different functions.Intelligence testing in a research context is relatively more straightforward than in a clinical context. In research, intelligence is tested and results are generally as obtained, however in a clinical setting intelligence may be impaired so estimates are required for comparison with obtained results. Estimates can be determined through a number of methods, the most common include:comparison of test results to expected achievement levels based on prior education and occupation and the use of which are based on cognitive faculties which are generally good indicators of intelligence and thought to be more resistant to cognitive damage, e.g. Language.Memory is a very broad function which includes several distinct abilities, all of which can be selectively impaired and require individual testing.
There is disagreement as to the number of memory systems, depending on the psychological perspective taken. From a clinical perspective, a view of five distinct types of memory, is in most cases sufficient. Semantic memory and episodic memory (collectively called or explicit memory); procedural memory and priming or perceptual learning (collectively called or implicit memory) all four of which are long term memory systems; and working memory or short term memory.