Geriatric performance on the Neurobehavioral Cognitive Status Examination (Cognistat)

Archives of Clinical Neuropsychology 18 (2003) 463–471

Geriatric performance on the Neurobehavioral Cognitive Status Examination (Cognistat) What is normal? Caitlin Macaulay a,∗ , Matthew Battista b , Paul C. Lebby c , Jonathan Mueller d a

California School of Professional Psychology—Fresno, Fresno, CA, USA b VA Central California Healthcare System—Fresno, Fresno, CA, USA c Valley Children’s Hospital, Madera, CA, USA d San Francisco Clinical Neurosciences, San Francisco, CA, USA Accepted 24 January 2002

Abstract The Neurobehavioral Cognitive Status Examination (Cognistat) is a widely used cognitive screening measure that has been utilized in several clinical studies with a geriatric population. However, there has been relatively little normative research since its original publication. The objective of this study was to develop age-corrected norms for Cognistat. One hundred and fifty healthy participants aged 60–85 were recruited, all of whom spoke English fluently. Twenty-seven peoples met at least one exclusionary criterion and were therefore excluded. The participants were administered Cognistat along with measures of IQ, depression, alcohol usage, and activity level. Data were not normally distributed; therefore, analysis of these data was completed using descriptive statistics and the nonparametric bootstrapping technique. Study results provide age-corrected profiles that differ significantly from and extend the originally published norms. © 2002 National Academy of Neuropsychology. Published by Elsevier Science Ltd. All rights reserved. Keywords: Neurobehavioral Cognitive Status Examination; Cognistat; Geriatric; Cognitive norms

∗

Corresponding author. Present address: MCSC, 108 Riverway Place, Bedford, NH, USA. Tel.: +1-603-623-5608; fax: +1-603-623-5947. E-mail address: [email protected] (C. Macaulay). 0887-6177/02/$ – see front matter © 2002 National Academy of Neuropsychology. PII: S 0 8 8 7 - 6 1 7 7 ( 0 2 ) 0 0 1 4 1 - 5

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1. Introduction Cognitive screening measures are commonly utilized in geriatric assessment to provide a quick estimate of the patient’s mental functioning. Results are commonly used in conjunction with other data for the differential diagnosis of dementia and other cognitive disorders. Brief measures of cognitive function are also utilized to determine whether or not further neuropsychological assessment may be necessary. Given healthcare resource limitations, efficient and accurate detection of cognitive impairment in an elderly population requires a reliable appreciation of normal age-related changes in cognition. Accordingly, cognitive screening measures that are well constructed, easy to administer, and appropriately normed for this population are essential. The Neurobehavioral Cognitive Status Examination (Cognistat) is a screening instrument that provides a profile of cognitive performance by domain rather than by a global score of functioning. It was originally designed to detect the presence of organically-based cognitive impairment while minimizing false-negative diagnoses (Kiernan, Mueller, Langston, & Van Dyke, 1987). In order to maintain adequate sensitivity, Cognistat was based on an abilities model of brain function that emphasizes the independent assessment of five major cognitive domains: language, visuospatial functioning, memory, arithmetic, and verbal reasoning (Northern California Neurobehavioral Group, 1983, 1995, 2001). This scoring system, which independently calculates scores for each domain, was designed so that successful performance in several cognitive domains does not obscure deficits in others (Schwamm, Van Dyke, Kiernan, Merrin, & Mueller, 1987). Original standardization of Cognistat was completed with 60 healthy adults ages 20–66 (Kiernan et al., 1987). Numerous clinical studies have utilized Cognistat with the geriatric population (Drane & Osato, 1997; Fields, Fulop, Sachs, Strain, & Fillit, 1992; Fladby et al., 1999; Katz, HartmanMaeir, Weiss, & Armon, 1997; Osato, Yang, & La Rue, 1993; Wiederman & Morgan, 1995). In particular, standardization data were collected on 59 elderly individuals ages 70–92 (Harris, Van Aelstyn, Kurn, & Kiernan, 1990). Mean age of this geriatric sample was 77.6, and mean years of education was 13.7 years. Results from this geriatric sample supported extending the range of performance designated as normal for people over the age of 65 on the Construction, Memory, and Similarities subtests. However, these results were based on a relatively small sample size. Drane, Yuspeh, Huthwaite, Klingler, and Hendry (1998) developed normative data for Cognistat utilizing healthy older adults (ages 53–96). They found a statistically significant difference between the youngest age group’s (<70) performance on the Memory subtest as compared to the oldest age group (>80). They also computed a composite score of all the subtests and found a significantly lower composite score for the oldest age group as compared to the younger age groups (<70 and 70–79 years). All of the participants had performed within normal limits on the Mini Mental State Examination (MMSE; Folstein, Folstein, & McHugh, 1975). Therefore, they concluded that Cognistat is more sensitive to the effects of normal aging than the MMSE. Though possibly true, their study utilized broadly stratified age ranges, they did not administer the screen item, and they utilized a composite score. Drane and Osato (1997) attempted to validate Cognistat using healthy elderly and others diagnosed with dementia. Their results, which were based on 20 subjects, revealed that dementia participants differed significantly from the control group on five of the subtests: Orientation, Comprehension,

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Repetition, Construction, and Memory. Although they obtained 100% sensitivity, specificity was only 30%. Therefore, 70% (14 out of 20) of the control group was identified as impaired. Given inconsistencies in existing normative data, the purpose of this study was to establish age-corrected norms for the geriatric population (age 60–85).

2. Methods 2.1. Study sample Data from 150 participants were collected. Out of the original sample, 27 people met at least one exclusionary criterion and were therefore excluded from the data analysis. The exclusion criterion was a history of medical or psychiatric condition that might affect cognitive functioning (i.e., previous diagnosis of dementia, organic brain dysfunction, mental retardation, sleep disorder, psychotic disorder, seizure disorder, stroke, coma, and head injury with loss of consciousness greater than 5 min, as well as having a current diagnosis of depression or currently alcoholic, or previously treated with electroconvulsive therapy) or current use of psychotropic medication. Participants were volunteers aged 60–85, who were recruited from various organizations such as senior centers, elderly housing, low-income housing, retirement groups, and service organizations in California and Massachusetts. All participants spoke English fluently. Prior to recruitment, this study was reviewed and approved by the appropriate institutional review boards. Informed consent was obtained from all participants.

3. Instruments Demographic information such as age, gender, race, native language, and years of education, as well as neurologic, medical, and psychiatric history was obtained using a two-page questionnaire. Participants were screened for a history of alcoholism using a cutoff score of 6 on the Veteran Alcoholism Screening Test (VAST; Magruder-Habib, Harris, & Fraker, 1982). The Geriatric Depression Scale (GDS) was used to screen participants for depression (Yesavage et al., 1983). As suggested by Brink et al. (1982) and supported by Dunn and Sacco (1989), Olin, Schneider, Eaton, Zemansky, and Pollock (1992), and Yesavage et al. (1983), a cutoff score of 11 or greater was used to determine if the participant was experiencing significant depressive symptomatology. However, current depression was not an exclusionary criterion. The Self-Evaluation of Life Function (SELF) Scale devised by Linn and Linn (1984) was utilized to determine the degree of physical and social activity of the study participants. Although each participant was asked all 54 items, only those items that loaded on the Physical Disability and Social Satisfaction factors were analyzed. The North American Adult Reading Test (NAART) that was devised by Blair and Spreen (1989) was used to estimate each participant’s IQ. Blair and Spreen compared the NAART with the Wechsler Adult Intelligence Scale-Revised and found that the NAART was well correlated with Verbal IQ and Full Scale IQ (FSIQ).

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Table 1 Mean years of education and estimated FSIQ Age group

n

Education

Education range

FSIQ range

60–64 65–69 70–74 75–79 80–84

20 22 29 21 20

14.68 (3.36) 16.32 (2.23) 14.31 (2.50) 14.81 (2.99) 14.15 (2.21)

8–20 12–19 10–21 8–20 12–19

96.60–125.46 88.80–123.12 81.78–122.34 101.28–122.34 83.34–124.68

All values are expressed as mean (S.D.).

Cognistat was administered utilizing the standard screen and metric approach: each subtest has a screen item, which approximately 20% of the normal adult population fails (Kiernan et al., 1987). If a participant fails the screen item, he or she is asked the metric items, which are arranged in order of increasing difficulty. If a participant passes the screen item, that ability is recorded as intact and normal. Total points from each subtest provide independent scores which when plotted provide a profile of cognitive functioning.

4. Statistical analyses 4.1. Descriptive characteristics of the study population One hundred and twenty-three participants were included in the analysis for this study (data for 87 females and 36 males were analyzed) with the vast majority being Caucasian (n = 116). Each participant was administered the GDS with no participant scoring over the cutoff score that is typically used to support a diagnosis of depression. Table 1 presents the means for years of education and estimated FSIQ summarized by age. Overall mean years of education was 14.42. Overall mean estimated IQ was 112.43. Table 2 presents means and standard deviations for each subtest by age. Tables 3 and 4 present the normal range of performance for each age group, which was defined by the mean less one standard deviation, a method that was used to establish the original geriatric and nongeriatric norms (Harris et al., 1990; Kiernan et al., 1987). Due to ceiling effect, the mean plus one standard deviation was not calculated. Table 2 Means and standard deviations for performance on each subtest Age group

n

Atten

Comp

Rep

Nam

60–64 65–69 70–74 75–79 80–84

20 22 29 21 20

7.80 (0.62) 7.96 (0.21) 7.24 (1.57) 7.52 (1.21) 7.75 (0.91)

6.00 (0.00) 6.00 (0.00) 5.65 (0.90) 5.86 (0.48) 5.85 (0.67)

12.00 (0.00) 11.96 (0.21) 11.65 (0.90) 11.43 (1.43) 11.50 (1.10)

8.00 (0.00) 7.86 (0.64) 7.90 (0.90) 7.81 (0.87) 7.75 (0.44)

All values are expressed as mean (S.D.). Atten = Attention subtest; Comp = Comprehension subtest; Rep = Repetition subtest; Nam = Naming subtest.

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Table 3 Cognistat profile for the 65–74-year-old age groups Language

Reasoning

Loc

Ori

Atten

Comp

Rep

Nam

Const

Mem

Calc

Sim

Judg

Alrt

-12-

-(S)8-

-(S)6-

-12-

-(S)4-

-8- -(S)6-

-6- -(S)5-

-6-5-3-

-5-4-3-

-(S)-8-7-5-3-

-6- -(S)5-

-10-8-6-

-(S)-12-11-9-7-

-4-3-2-

-3-2-1-

-5-4-3-

-4-3-2-

-4-

-1-

-2-

-5-

-2-

-0-

-10-8-6-4-

-0-

-2-

-1-

Degree of impairment: regular type = normal range of performance (note: extension of performance on Memory); italic type = mild impairment; bold type = moderate impairment; and bold italic type = severe impairment. Loc = level of consciousness; Ori = Orientation subtest; Atten = Attention subtest; Comp = Comprehension subtest; Rep = Repetition subtest; Nam = Naming subtest; Const = Construction subtest; Mem = Memory subtest; Calc = Calculations subtest; Sim = Similarities subtest; Judg = Judgment subtest; Alrt = Alert. Table 4 Cognistat profile for the 75–84-year-old age groups Language

Reasoning

Loc

Ori

Atten

Comp

Rep

Nam

Const

Mem

Calc

Sim

Judg

Alrt

-12-

-(S)8-

-(S)6-

-12-

-(S)4-

-8- -(S)6-

-6- -(S)5-

-6-5-3-

-5-4-3-

-(S)-8-7-5-3-

-6- -(S)5-

-10-8-6-

-(S)-12-11-9-7-

-5-4-3-

-4-3-2-

-1-

-2-

-5-

-2-

-10-8-6-4-

-3-2-1-

-4-

-4-3-2-0-

-0-

-2-

-1-

Degree of impairment: regular type = normal range of performance (note: extension of performance on Memory); italic type = mild impairment; bold type = moderate impairment; and bold italic type = severe impairment. Loc = level of consciousness; Ori = Orientation subtest; Atten = Attention subtest; Comp = Comprehension subtest; Rep = Repetition subtest; Nam = Naming subtest; Const = Construction subtest; Mem = Memory subtest; Calc = Calculations subtest; Sim = Similarities subtest; Judg = Judgment subtest; Alrt = Alert.

5. Nonparametric and parametric statistics Cognistat was designed to focus on degree of disability, not to discriminate between average and superior performance. Normals typically obtain perfect scores on most subtests, resulting in a restricted range of performance for the normal population, including normal elderly individuals. Accordingly, parametric statistics were not appropriate as the data were not normally distributed. Therefore, bootstrapping, a nonparametric statistic that utilizes confidence intervals, was used to determine statistical significance. Bootstrapping draws many samples, with replacement (in this case 1000 replacements), from a population consisting of the data that were collected (D. C. Howell, personal communication, October 31, 1999). For computing these statistics, if a subject passed the screen, he or she was given the numerical score that is equivalent to that screen; if he or she did not pass the screen, the metric score was used.

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A mean was calculated for each sample, and the distribution of those means produced a 95% confidence limit. Using this technique, data were compared to the originally established norms for the nongeriatric population. Nonetheless, results from both nonparametric and parametric techniques produced data that were compared to the originally established norms for the geriatric population. Interestingly, comparison of the traditional parametric analyses (t tests) and those of the bootstrapping technique were equivalent for each comparison.

6. Results Using the bootstrapping technique, which derives confidence intervals, performance on the Memory subtest was significantly different (from the original established norms) for the 75–79- and 80–84-year-old age groups. However, the confidence intervals also showed a sizable decline in normal performance for the 65–69- and 70–74-year-old age groups. In cases, where there was a sizeable decline (more than one standard deviation) of normal range of performance, a one-step extension was supported. Therefore, extending the range of normal performance one-step on the Memory subtest for the 65–69- and 70–74-year-old age groups was supported (see Table 3). Further extension for range of normal performance for the 75–79and 80–84-year-old age groups is supported by bootstrapping and the resultant significant confidence intervals (see Table 4). Const

Mem

Calc

Sim

Judg

4.75 (1.12) 4.96 (0.79) 4.72 (1.13) 4.33 (1.50) 4.15 (1.23)

10.75 (2.15) 9.50 (2.43) 9.28 (2.78) 8.48 (2.99) 7.90 (2.83)

4.00 (0.00) 3.86 (0.64) 3.90 (0.41) 3.95 (0.22) 3.80 (0.70)

6.20 (0.62) 5.86 (0.64) 6.00 (1.44) 5.86 (0.65) 6.00 (0.97)

5.10 (0.31) 5.18 (0.39) 5.00 (0.65) 4.95 (0.50) 4.95 (0.76)

Using the bootstrapping technique, performance on the Construction subtest was significant for the 75–79- and 80–84-year-old age groups. This result supports extending the range of normal performance one step on the Construction subtest (see Table 3). The confidence intervals did not demonstrate any decline in normal range of performance for the 60–64-, 65–69-, or 70–74-year-old age groups; therefore, no extension of performance for these age groups. Using the bootstrapping technique in combination with descriptive statistics, neither descriptive decline nor statistical significance was found for performance on the Calculations, Naming, or Similarities subtests. Therefore, extending the range of performance designated as normal on these subtests for people in age groups from 60 to 84 was not statistically supported. The existing (Harris et al., 1990) criteria for mild, moderate, and severe impairment should be used for the 60–64-year age group. It was not hypothesized that there would be significant decline for performance on Orientation, Attention, Comprehension, Repetition, or Judgment subtests; therefore, the existing (Harris et al., 1990) criteria for mild, moderate, and severe impairment should be used for these subtests for all the age groups. For revised criteria for

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mild, moderate, and severe impairment, please see Tables 3 and 4 (emphases in these tables denote degree of impairment).

7. Discussion The purpose of this study was to establish age-corrected norms for Cognistat, a widely utilized measure of cognitive functioning. Study results reveal that age-associated changes for specific cognitive domains have a different trajectory than those originally described for Cognistat (Harris et al., 1990). Harris et al.’s (1990) data suggest that the normal range of functioning on the Construction, Memory, and Similarities subtests should be extended for people over the age of 65. The current study does not support extension of the normal range of functioning for Similarities in any age group (i.e., 60–85). However, the current study does support the extension of the normal range of functioning for performance on the Construction subtest for ages 75–79 and 80–84, but not for those in the 60–64-, 65–69-, and 70–74-year-old age groups. Study results also reveal a different pattern of change for memory functioning across age groups. Our data support an extension of the normal range of functioning on the Memory subtest for individuals in the 65–69- and 70–74-year-old age groups, and a further extension for those in the 75–79- and 80–84-year-old age groups. Scores that are “mildly impaired” for younger age groups are now considered “normal” using these extended norms. Several differences exist between Harris et al.’s (1990) data and our data. One difference being that the average years of education for our sample (14.42) was significantly greater than the original sample. Although education may partially explain the improved performance on the Similarities and Construction subtests, it further emphasizes the decline in performance on the Memory subtest. Although mean education for the 65–69-year-old age group was significantly greater than the other age groups, it did not have a significant impact on the age results; rather, it emphasizes the decline in memory performance. Other possible factors that may contribute to the differences between datasets may include differences in the sample’s intelligence and health status. However, it was not possible to compare either intelligence or health status of this sample with the original sample, as those characteristics were never described. Also, affects of medications that are commonly used by the elderly (i.e., vasodilators, diuretics, ACE inhibitors) were not analyzed, which is likely a limitation of this study. It should also be noted that affects of depression were not taken into consideration, largely because none of the participants were acknowledging significant symptoms of depression at the time of the examination. It can be argued that those taking antidepressant medication demonstrate less cognitive impairment than those depressed and not taking antidepressant medication. However, in order to clarify this question, further study including this as an investigation variable will be needed. In any case, these revised norms for Cognistat are particularly interesting for individuals aged 75 and older given that referral for memory concerns in the elderly population is common. Crum, Anthony, Bassett, and Folstein (1993) found that performance on the MMSE varied due to age; therefore, it is not surprising that relatively large reductions in task performance is still equated with normal age performance in an elderly population. Our data suggest that

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Cognistat also demonstrates these age corrections and we recommend that they be cautiously utilized in both clinical use and future research.

Acknowledgments The authors wish to thank David Howell, Ph.D. at the University of Vermont, who assisted with the statistical analyses for this project.

References Blair, J. R., & Spreen, O. (1989). Predicting pre-morbid IQ: A revision of the National Adult Reading Test. Clinical Neuropsychologist, 3, 129–136. Brink, T. L., Yesavage, J. A., Lum, O., Heersema, P., Adey, M., & Rose, T. L. (1982). Screening tests for geriatric depression. Clinical Gerontologist, 1(1), 37–43. Crum, R. M., Anthony, J. C., Bassett, S. S., & Folstein, M. F. (1993). Population-based norms for the Mini-Mental State Examination by age and educational level. Journal of the American Medical Association, 269, 2386–2391. Drane, D. L., & Osato, S. S. (1997). Using the Neurobehavioral Cognitive Status Examination as a screening measure for older adults. Archives of Clinical Neuropsychology, 12, 139–143. Drane, D. L., Yuspeh, R. L., Huthwaite, J. S., Klingler, L. K., & Hendry, K. M. (1998, November). Older adult norms for the Cognistat (NCSE). Poster session presented at the annual meeting of the National Academy of Neuropsychology, Washington, DC. Dunn, V. K., & Sacco, W. P. (1989). Psychometric evaluation of the Geriatric Depression Scale and the Zung Self-Rating Depression scale using an elderly community sample. Psychology and Aging, 4(1), 125–126. Fields, S. D., Fulop, G., Sachs, C. J., Strain, J., & Fillit, H. (1992). Usefulness of the Neurobehavioral Cognitive Status Examination in the hospitalized elderly. International Psychogeriatrics, 4(1), 93–102. Fladby, T., Schuster, M., Gronli, O., Sioholm, H., Loseth, S., & Sexton, H. (1999). Organic brain disease in psychogeriatric patients: Impact of symptoms and screening methods on the diagnostic process. Journal of Geriatric Psychiatry and Neurology, 12, 16–20. Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-Mental State: A practical method grading the cognitive state of patients for the clinician. Psychiatric Research, 12, 189–198. Harris, M. E., Van Aelstyn, C., Kurn, S. J., & Kiernan, R. J. (1990, November). Performance of normal elderly on the Neurobehavioral Cognitive Status Examination. Poster session presented at the annual meeting of the National Academy of Neuropsychology, Reno, NV. Katz, N., Hartman-Maeir, A., Weiss, P., & Armon, N. (1997). Comparison of cognitive status profiles of healthy elderly persons with dementia and neurosurgical patients using the Neurobehavioral Cognitive Status Examination. NeuroRehabilitation, 8, 179–186. Kiernan, R., Mueller, J., Langston, W., & Van Dyke, C. (1987). The Neurobehavioral Cognitive Status Examination: A brief but differentiated approach to cognitive assessment. Annals of Internal Medicine, 107, 481–485. Linn, M. W., & Linn, B. S. (1984). Self-Evaluation of Life Function (SELF) scale: A short, comprehensive, self-report of health for elderly adults. Journal of Gerontology, 39, 613–622. Magruder-Habib, K., Harris, K. E., & Fraker, G. G. (1982). Validation of the Veterans Alcoholism Screening Test. Journal of Studies on Alcohol, 43, 910–926. Northern California Neurobehavioral Group. (1983). Manual for the Neurobehavioral Cognitive Status Examination. Fairfax, CA: Author. Northern California Neurobehavioral Group. (1995). Manual for the Neurobehavioral Cognitive Status Examination. Fairfax, CA: Author. Northern California Neurobehavioral Group. (2001). Manual for the Neurobehavioral Cognitive Status Examination. Fairfax, CA: Author.

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Olin, J. T., Schneider, L. S., Eaton, E. M., Zemansky, M. F., & Pollock, V. E. (1992). The Geriatric Depression Scale and the Beck Depression Inventory as screening instruments in an older adult population. Psychological Assessment, 4, 190–192. Osato, S. S., Yang, J., & La Rue, A. (1993). The Neurobehavioral Cognitive Status Examination in an elderly psychiatric population. Neuropsychiatry, Neuropsychology, and Behavioral Neurology, 6, 98–102. Schwamm, L., Van Dyke, C., Kiernan, R. J., Merrin, E. L., & Mueller, J. (1987). The Neurobehavioral Cognitive Status Examination: Comparison with the Cognitive Capacity Screening Examination and the Mini-Mental State Examination in a neurosurgical population. Annals of Internal Medicine, 107, 486–491. Wiederman, M. W., & Morgan, C. D. (1995). Neurobehavioral Cognitive Status Examination (NCSE) with geriatric inpatients. Clinical Gerontologist, 15(4), 35–47. Yesavage, J. A., Brink, T. L., Rose, T. L., Lum, O., Huang, V., Adey, M., & Leirer, V. O. (1983). Development and validation of a geriatric depression screening scale: A preliminary report. Journal of Psychiatric Research, 17, 37–49.