Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-22T18:14:49.507Z Has data issue: false hasContentIssue false
  • English
  • Français

The brief cognitive assessment tool (BCAT): cross-validation in a community dwelling older adult sample

Published online by Cambridge University Press:  13 August 2014

Elizabeth E. MacDougall ,
William E. Mansbach ,
Kristen Clark  and
Ryan A. Mace
Elizabeth E. MacDougall*
Affiliation:
Hood College, 401 Rosemont Avenue, Frederick, Maryland, Frederick, Maryland, USA
William E. Mansbach
Affiliation:
Mansbach Health Tools, LLC, , Simpsonville, Maryland, Simpsonville, Maryland, USA
Kristen Clark
Affiliation:
Mansbach Health Tools, LLC, , Simpsonville, Maryland, Simpsonville, Maryland, USA
Ryan A. Mace
Affiliation:
Mansbach Health Tools, LLC, , Simpsonville, Maryland, Simpsonville, Maryland, USA
*
Correspondence should be addressed to: Elizabeth E. MacDougall, Hood College, 401 Rosemont Avenue, Frederick, Maryland 21701, Phone: 301-696-3892; Fax: 301-696-3863. Email: [email protected].
Get access

Abstract

Background:

Cognitive impairment is underrecognized and misdiagnosed among community-dwelling older adults. At present, there is no consensus about which cognitive screening tool represents the “gold standard.” However, one tool that shows promise is the Brief Cognitive Assessment Tool (BCAT), which was originally validated in an assisted living sample and contains a multi-level memory component (e.g. word lists and story recall items) and complex executive functions features (e.g. judgment, set-shifting, and problem-solving).

Methods:

The present study cross-validated the BCAT in a sample of 75 community-dwelling older adults. Participants completed a short battery of several individually administered cognitive tests, including the BCAT and the Montreal Cognitive Assessment (MoCA). Using a very conservative MoCA cut score of <26, the base rate of cognitive impairment in this sample was 35%.

Results:

Adequate internal consistency and strong evidence of construct validity were found. A receiver operating characteristic (ROC) curve was calculated from sensitivity and 1-specificity values for the classification of cognitively impaired versus cognitively unimpaired. The area under the ROC curve (AUC) for the BCAT was .90, p < 0.001, 95% CI [0.83, 0.97]. A BCAT cut-score of 45 (scores below 45 suggesting cognitive impairment) resulted in the best balance between sensitivity (0.81) and specificity (0.80).

Conclusions:

A BCAT cut-score can be used for identifying persons to be referred to appropriate healthcare professionals for more comprehensive cognitive assessment. In addition, guidelines are provided for clinicians to interpret separate BCAT memory and executive dysfunction component scores.

Keywords

psychometricsreliabilityvaliditycognitive impairmentscreeningolder adults
Type
Research Article
Information
International Psychogeriatrics , Volume 27 , Issue 2 , February 2015 , pp. 243 - 250
Copyright
Copyright © International Psychogeriatric Association 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alzheimer's Association. (2012). Alzheimer's Association Publishes New Recommendations for Primary Care Physicians on how to Assess Cognition During the Medicare Annual Wellness Visit. Retrieved December 7, 2013, from http://www.alz.org/documents_custom/pr_awv_recommendations.pdf Google Scholar
Boustani, M. et al. (2005). Implementing a screening and diagnosis program for dementia in primary care. Journal of General Internal Medicine, 20, 572–577. doi: 10.1080/13607863.2010.496445 Google Scholar
Bradford, A., Kunik, M. E., Schultz, P., Williams, S. P. and Singh, H. (2009). Missed and delayed diagnosis of dementia in primary care: prevalence and contributing factors. Alzheimer Disease and Associated Disorders, 23, 306–314. doi: 10.1097/WAD.0b013e3181a6bebc Google Scholar
Callahan, C. M., Hendrie, H. C. and Tierney, W. M. (1995). Documentation and evaluation of cognitive impairment in elderly primary care patients. Annals of Internal Medicine, 122, 422–429. doi: 10.7326/0003-4819-122-6-199503150-00004 Google Scholar
Cordell, C. B. et al. (2013). Alzheimer's Association recommendations for operationalizing the detection of cognitive impairment during the Medicare Annual Wellness Visit in a primary care setting. Alzheimer's and Dementia, 9, 141–150. doi: 10.1016/j.jalz.2012.09.011.Google Scholar
Corrada, M. M., Brookmeyer, R., Paganini-Hill, A., Berlau, D. and Kawas, C. H. (2010). Dementia incidence continues to increase with age in the oldest old: the 90+ study. Annals of Neurology, 67, 114–121. doi: 10.1002/ana.21915 Google Scholar
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198. doi:10.1016/0022-3956(75)90026-6 Google Scholar
Galvin, J. E. et al. (2005). The AD8: A brief informant interview to detect dementia. Neurology, 65, 559–564. doi: 10.1212/01.wnl.0000172958.95282.2a Google Scholar
Galvin, J. E., Roe, C. M., Coats, M. A. and Morris, J. C. (2007). Patient's rating of cognitive ability: using the AD8, a brief informant interview, as a self-rating tool to detect dementia. Archives of Neurology, 64, 725–730. doi:10.1001/archneur.64.5.725 Google Scholar
Galvin, J. E., Roe, C. M., Xiong, C. and Morris, J. C. (2006). Validity and reliability of the AD8 informant interview in dementia. Neurology, 67, 1942–1948. doi: 10.1212/01.wnl.0000247042.15547.eb Google Scholar
Hsieh, S., Schubert, S., Hoon, C., Mioshi, E. and Hodges, J. R. (2013). Validation of the Addenbrooke's Cognitive Examination III in frontotemporal dementia and Alzheimer's disease. Dementia and Geriatric Cognitive Disorders, 36, 242–250. doi: 10.1159/000351671 Google Scholar
Lopez, M. N., Quan, N. M. and Carvajal, P. M. (2010). A psychometric study of the geriatric depression scale. European Journal of Psychological Assessment, 26, 55–60. doi:10.1027/1015–5759/a000008 Google Scholar
Luis, C. A., Keegan, A. P. and Mullan, M. (2009). Cross validation of the Montreal Cognitive Assessment in community dwelling older adults residing in the Southeastern US. International Journal of Geriatric Psychiatry, 24, 197–201. doi: 10.1002/gps.2101 Google Scholar
Mansbach, W. E., MacDougall, E. E. and Rosenzweig, A. S. (2012). The Brief Cognitive Assessment Tool (BCAT): A new test emphasizing contextual memory, executive functions, attentional capacity, and the prediction of instrumental activities of daily living. Journal of Clinical and Experimental Neuropsychology, 34, 183–194. doi:10.1080/13803395.2011.630649 Google Scholar
Nasreddine, Z. S. et al. (2005). The Montreal Cognitive Assessment (MoCA): a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53, 695–699. doi: 10.1111/j.1532-5415.2005.53221.x Google Scholar
Olazarán, J. et al. (2010). Nonpharmacological therapies in Alzheimer's disease: a systematic review of efficacy. Dementia and Geriatric Cognitive Disorders, 30, 161–178. doi: 10.1159/000316119 CrossRefGoogle ScholarPubMed
Petersen, R. C. et al. (2009). Mild cognitive impairment: ten years later. Archives of Neurology, 66, 1447–1455. doi: 10.1001/archneurol.2009.266 Google Scholar
Raykov, T. and Marcoulides, G. A. (2011). Introduction to Psychometric Theory. New York, NY: Taylor and Francis Group, LLC.CrossRefGoogle Scholar
Reuben, D. B. et al. (2010). Assessing care of vulnerable elders—Alzheimer's disease: a pilot study of a practice redesign intervention to improve the quality of dementia care. Journal of the American Geriatric Society, 58, 324–329. doi: 10.1111/j.1532-5415.2009.02678.x Google Scholar
Rossetti, H. C., Lacritz, L. H., Cullum, C. M. and Weiner, M. F. (2011). Normative data for the Montreal Cognitive Assessment (MoCA) in a population-based sample. Neurology, 77, 1272–1275. doi: 10.1212/WNL.0b013e318230208a Google Scholar
Simning, A., Conwell, Y. and van Wijngaarden, E. (2013). Cognitive impairment in public housing residents living in Western New York. Social Psychiatry and Psychiatric Epidemiology. Advance online publication.Google Scholar
Stern, R. A. and White, T. (2003). Neuropsychological Assessment Battery. Lutz, FL: Psychological Assessment Resources.Google Scholar
Stiles, P. G. and McGarrahan, J. F. (1998). The geriatric depression scale: a comprehensive review. Journal of Clinical Geropsychology, 4, 89–110.Google Scholar
US Preventive Services Task Force (USPSTF) (2003). Screening for dementia: recommendations and rationale. Annals of Internal Medicine, 138, 925–926. Retrieved from http://www.uspreventiveservicestaskforce.org/3rdusptf/dementia/dementrr/htm Google Scholar
Valcour, V. G., Masaki, K. H., Curb, J. D. and Blanchette, P. L. (2000). The detection of dementia in the primary care setting. Archives of Internal Medicine, 160, 2964–2968. doi:10.1001/archinte.160.19.2964 Google Scholar
Wancata, J., Alexandrowicz, R., Marquart, B., Weiss, M. and Friedrich, F. (2006). The criterion validity of the geriatric depression scale: a systematic review. Acta Psychiatrica Scandinavia, 114, 398–410. doi:10.1111/j.1600-0447.2006.00888.x CrossRefGoogle ScholarPubMed
White, T. and Stern, R.A. (2003). Neuropsychological Assessment Battery: Psychometric and technical manual. Lutz, FL: Psychological Assessment Resources.Google Scholar
Yesavage, J. A. et al. (1983). Development and validation of a geriatric depression screening scale: a preliminary report. Journal of Psychiatric Research, 17, 37–49.Google Scholar
Zahodne, L. B. et al. (2011). The case for testing memory with both stories and word lists prior to DBS surgery for Parkinson's disease. The Clinical Neuropsychologist, 25, 348–358. doi: 10.1080/13854046.2011.562869 CrossRefGoogle ScholarPubMed