scholarly journals A-236 Concurrent Validity of the Paper-Match in a Diverse Population

2020 ◽  
Vol 35 (6) ◽  
pp. 1031-1031
Author(s):  
Veloz C ◽  
Weiss E ◽  
Ayers E ◽  
Possin K ◽  
Verghese J
Keyword(s):  
Primary Care ◽  
Cognitive Impairment ◽  
San Francisco ◽  
Health Assessment ◽  
Diverse Population ◽  
Neuropsychological Battery ◽  
Primary Care Population ◽  
Initial Description ◽  
Highly Correlated ◽  
The University

Abstract Introduction Symbol and digit substitution tasks are key instruments in the evaluation of attention, speed of processing, executive functioning, and cognitive dysfunction. The Match is an electronic (app-based) substitution task developed as part of the University of California San Francisco Brain Health Assessment that has been used to demonstrate cognitive impairment. We describe the paper-based oral symbol/number substitution task (Paper-Match), which was developed as part of the 5-Cog battery to assess for cognitive impairment including dementia and demonstrate it’s use in an urban, multi-ethnic, socioeconomically disadvantaged primary care population in Bronx NY. Method 109 participants, mean age 72.61 SD 6.42 and education 11.70 SD 3.82 years, 81% female, 48.6% Hispanic/Latino and 47.7% African American seen as part of 5-Cog. Participants (36.7% tested in Spanish) completed the Paper-Match (scored based on the number of correct matches in 90 seconds) and a comprehensive neuropsychological battery. Descriptive and correlational analysis were conducted. Results Mean Paper-Match score was 38.24 SD 11.83 items correct (range 4–51). Paper-Match performance was highly correlated with performance on the Symbol Digit Modalities Test (r = .819, p < .001) and moderately correlated with performance on the Montreal Cognitive Assessment (MOCA; r = .604, p < .001). Years of education and primary language impacted performances. Conclusion The results of this study provide the initial description and validation of the Paper-Match an oral symbol digit substitution task and its use in a diverse population of older primary care patients. Further research on the psychometric properties and construct validity of the Paper-Match are needed.

scholarly journals Accuracy of the Cognitive Assessment Battery in a Primary Care Population

2019 ◽  
Vol 9 (2) ◽  
pp. 294-301 ◽  
Author(s):  
Anna S. Kvitting ◽  
Maria M. Johansson ◽  
Jan Marcusson
Keyword(s):  
Primary Care ◽  
Logistic Regression ◽  
Cognitive Impairment ◽  
Cognitive Assessment ◽  
Characteristic Curve ◽  
Numerical Data ◽  
Assessment Tools ◽  
Binary Outcomes ◽  
Assessment Battery ◽  
Primary Care Population

Background: There are several cognitive assessment tools used in primary care, e.g., the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment. The Cognitive Assessment Battery (CAB) was introduced as a sensitive tool to detect cognitive decline in primary care. However, primary care validation is lacking. Therefore, we investigated the accuracy of the CAB in a primary care population. Objective: To investigate the accuracy of the CAB in a primary care population. Methods: Data from 46 individuals with cognitive impairment and 33 individuals who visited the primary care with somatic noncognitive symptoms were analyzed. They were investigated with the MMSE, the CAB, and a battery of neuropsychological tests; they also underwent consultation with a geriatric specialist. The accuracy of the CAB was assessed using c-statistics and the area under the receiver operating characteristic curve (AUC) was used to quantify the binary outcomes (“no cognitive impairment” or “cognitive impairment”). Results: The “cognitive impairment” group was significantly different from the unimpaired group for all the subtests of the CAB. When accuracy was based on binary significant reduction or not in one or several domains of the CAB, the AUC varied between 0.685 and 0.772. However, when a summation or logistic regression of several subcategories was performed, using the numerical values for each subcategory, the AUC was >0.9. For comparison, the AUC for the MMSE was 0.849. Conclusions: The accuracy of the CAB in a primary care population is poor to good when using binary cutoffs. Accuracy can be improved to high when using a summation or logistic regression of the numerical data of the subcategories. Considering CAB time, lack of adequate age norms, and a good accuracy for the MMSE, implementation of the CAB in primary care is not recommended at present based on the results of this study.

Stability of Diagnoses of Cognitive Impairment, Not Dementia in a Veterans Affairs Primary Care Population

2015 ◽  
Vol 63 (6) ◽  
pp. 1105-1111 ◽  
Author(s):  
Tracey Holsinger ◽  
Brenda L. Plassman ◽  
Karen M. Stechuchak ◽  
James R. Burke ◽  
Cynthia J. Coffman ◽  
...  
Keyword(s):  
Primary Care ◽  
Cognitive Impairment ◽  
Veterans Affairs ◽  
Primary Care Population

Shared Care Depression Collaborative Model: From Project Inception to Outcome Data

2008 ◽  
Vol 27 (2) ◽  
pp. 219-232 ◽  
Author(s):  
Whitney Sedgwick ◽  
Cheryl Washburn ◽  
Christie Newton ◽  
Patricia Mirwaldt
Keyword(s):  
Primary Care ◽  
Health Assessment ◽  
Pilot Project ◽  
Primary Care Providers ◽  
Outcome Data ◽  
Shared Care ◽  
Care Providers ◽  
University Of British Columbia ◽  
National College Health Assessment ◽  
The University

The University of British Columbia (UBC) has partnered with community primary care providers to implement a shared care pilot project for the management of depression. The National College Health Assessment survey conducted at UBC in 2004 identified a significant gap in the management of depression. This finding highlighted a need to better integrate existing resources and strengthen the capacity of primary care providers to effectively recognize, assess, and treat depression. This article outlines the development and evaluation of a shared care collaborative approach to the primary care of depression in the UBC campus community.

Estimation of premorbid intelligence and executive cognitive functions with lexical reading tasks

2020 ◽  
Author(s):  
Graham Pluck
Keyword(s):  
Cognitive Impairment ◽  
Lexical Decision ◽  
Cognitive Ability ◽  
Memory Span ◽  
Clinical Sample ◽  
Case Series ◽  
Stem Completion ◽  
Clinical Neuropsychology ◽  
Premorbid Intelligence ◽  
Highly Correlated

Introduction: Estimation of premorbid function is essential to accurate assessment of cognitive impairments in clinical neuropsychology and behavioral neurology, and has numerous research applications. However, current methods are rudimentary and imperfect. We explored how lexical tasks can be best used to accurately and precisely estimate intelligence and executive functions.Methods: We studied lexical word pronunciation, lexical decision, and stem-completion naming in the estimation of cognitive ability, in samples of healthy adults (n = 143), and patients with cognitive impairment due to neurological illness (n =15). Cognitive assessments included intelligence (WAIS-IV), episodic memory, and eight tests of executive functioning, including Theory of Mind.Results: When examined at the group level, single word pronunciation was particularly robust in the presence of cognitive impairment in patients with dementia. However, as a case series, patients showed idiosyncratic patterns of preservation of lexical skills including on tests of pronunciation, lexical decision and stem-completion naming. All of these tasks were highly correlated with IQ scores in a non-clinical sample, suggesting that they could be used as estimators of premorbid intelligence. Simulated impairments in non-clinical controls suggested that the median score from the three different tasks had the highest correlation with, and provided the most accurate and precise estimates of, intelligence, and was also the least sensitive to impairment. Finally, we show that these methods also predict executive functions, in particular, strong correlations were found for proverb interpretation, phonemic/semantic alternating verbal fluency, and working memory span performance. Conclusions: Several lexical tasks are potentially useful in predication of pre-illness cognitive ability in patients with neurological or psychiatric illness. However, due to the heterogeneity of impairments between patients, estimation of premorbid levels could be improved by the use of the median estimated values from multiple tests. This could potentially improve diagnostic accuracy and quantification of neuropsychological impairments.

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