Neuropsychology

Test Administration

Early approaches to neuropsychological evaluation tended to use a fixed battery approach requiring that the same tests are administered to every patient in a standardized manner. One example of a fixed battery is the Halstead–Reitan battery ( Box 44.1 ), for which comprehensive norms have been published by Heaton and colleagues ( ). While this approach had the benefit of providing comprehensive assessment of cognitive functioning, the length of the battery (up to 8 hours), which was not tolerated by all patients, was not always necessary to address the referral question, and is often incompatible with the limited reimbursement schedules in managed care. For these reasons, the flexible battery (or hypothesis-driven battery) is more commonly used today.

The flexible battery approach allows neuropsychologists to develop a test battery based on the referral question, patient’s history, and clinical interview. In the flexible battery approach, a brief set of basic tests is initially administered, and additional tests of more specific abilities are used to conduct in-depth follow-up assessments based on each patient’s needs. For an example of this, see the Iowa-Benton method as illustrated in Fig. 44.1 ( ). Considerations when selecting tests include age, primary language, level of education, ethnicity/cultural factors, reading level, expected level of global cognitive impairment (to avoid ceiling or floor effects in testing), and physical disabilities ( ). Although this approach is more tailored to the individual needs of the patient (and is therefore briefer), it can be less comprehensive than the fixed-battery approach. Most neuropsychologists’ approaches fall somewhere between the use of a set battery and a completely individualized examination.

Test Interpretation

The interpretation of cognitive test results is central to the role of the neuropsychologist and differentiates neuropsychology from all other disciplines. Accurate interpretation of neuropsychological test results depends on a comprehensive understanding of the neuroanatomical correlates of cognition, neurological disease processes, and psychometric testing principles. One cannot simply administer a test, look at the score, and declare that the score indicates intact/impaired cognitive functioning. Test interpretation requires an understanding of test validity and reliability, sensitivity and specificity, likelihood ratios, and score distributions to avoid over- or underdiagnosing cognitive deficits. Substantial intraindividual differences exist in cognitive abilities, and a small number of poor test performances within a larger battery of tests is common among the general population. Cognitive test performances are also impacted by extra-neurological factors such as the number of tests administered, where cut scores are placed, the probability of certain test scores occurring, and the demographic characteristics of the patient ( ). Proper test interpretation requires that all of these variables are considered and that conclusions are based on recognizable patterns of test results rather than the interpretation of test scores in isolation.

Neuropsychological test interpretation is also dependent on an understanding of the scientific and theoretical concepts that underlie cognitive tests. No cognitive test measures a single isolated aspect of cognitive functioning. Most neuropsychological tests engage multiple cognitive abilities simultaneously. To illustrate, verbal memory tests (e.g., word list memory tasks) assess memory functioning, but they are also dependent on the patient’s attention, processing speed, and executive functioning. Therefore, an impaired score on a verbal memory task does not necessarily indicate a primary memory impairment. It is the neuropsychologist’s task to determine which cognitive deficits are actually causing impaired test performances by analyzing the patient’s overall pattern of results across the test battery and by comparing the neuropsychological profile to known patterns of disease. If a score on a verbal memory test does reflect a primary memory deficit, then the neuropsychologist determines whether the impairment is due to a deficit in encoding, storage, or retrieval, since the type of memory impairment may be indicative of different disease processes or lesion locations. Neuropsychologists use a similar method of analysis when assessing performances in other cognitive domains.

Test interpretation also requires the integration of neuropsychological test scores with findings from the clinical interview, the patient’s history, the neurological examination, neurophysiology and neuroimaging data, and relevant literature. Raw test scores must be compared to an appropriate reference standard. Several reference standards are used in interpreting neuropsychological test scores, including the use of normative data, cut scores, and comparisons with an individual’s own prior testing results.

Inferences about individual patients’ neuropsychological test scores are often derived by comparing test scores to normative data that are typically collected by test developers as a standardization sample. Normative data are useful for accounting for variables that are likely to influence test performance (e.g., demographic factors) so that accurate and appropriate conclusions are drawn. Confounding variables are accounted for by stratifying test scores according to sex, age, and level of education. An individual’s raw score is compared with the distribution of scores from his or her peer group to determine where it falls within the range of expected performances. Fig. 44.2 and Table 44.2 show a normal distribution and interpretive guidelines for use in neuropsychological interpretation. The usefulness of normative data depends strongly on the size and representativeness of the standardization sample. Clinical interpretation can also be greatly affected by the goodness-of-fit between the individual patient and the standardization sample. Furthermore, it is important to use the most recent norms available, because cohort effects may lead to differences between current patients and those from whom data were collected years ago. When appropriate norms are not available, there is a danger of over- or underdiagnosis of cognitive impairment.

Another approach to test interpretation is the use of cut scores. Tests that rely on cut scores often measure performances with low base rates or deficits very few healthy people demonstrate. Some tests are straightforward in their capability to measure abilities that are largely intact in normal subjects but impaired in disordered patients. For example, most people are able to bisect a line without difficulty, but patients with left-sided visuospatial neglect typically identify the midpoint of the line to be to the right of center. Cut scores are useful with brief tests of cognitive screening, such as the Mini-Mental State Examination (MMSE). It is critical to remain current with normative standards, however, as even these very brief screening tests vary greatly with persons varying in education and ethnicity. See Table 44.3 for MMSE cutoff scores for detection of Alzheimer disease varying by ethnicity ( ). One recent study of over 10,450 Medicare recipients suggested that claims data and cognitive performances were poorly matched, with less than half being identified by both measures, suggesting that healthcare providers underestimated dementia diagnoses in Black and Hispanic populations, compared with Whites ( ).

The comparison of current performance with past test scores is another important component of test interpretation, especially if cognitive decline is suspected. Rarely, however, do individuals have previous test data available for these comparisons. When no previous test scores are available, evidence of the patient’s premorbid intellectual functioning is estimated. Several techniques are available for estimating premorbid intellect, including regression equations that utilize demographic variables as predictors of IQ (e.g., the Barona formula; ), word reading tests that are correlated with IQ (e.g., the North American Adult Reading Test; or the Word Reading Test from the Wide Range Achievement Test; ), and “hold” subtests from intelligence measures that are frequently used as proxies for premorbid functioning (e.g., see , for review). Most contemporary neuropsychologists use a combination of these strategies, either formally (e.g., Oklahoma Premorbid Intelligence Estimate-3, ; Test of Premorbid Functioning, ) or informally.

Ultimately, feedback about the results of the neuropsychological evaluation, along with diagnostic impressions and treatment recommendations, is communicated to the referring physician and the patient. Some form of written report is typical in neuropsychological evaluations, and these tend to vary in length and level of detail (e.g., <1–15 pages). A common structure for a neuropsychological report includes sections summarizing the patient interview, collateral interview, medications, medical history, social background, behavioral observations, neuropsychological battery, neuropsychological test results and interpretation, final diagnostic impressions, and treatment recommendations.

Mini–Mental State Examination

One of the most widely used mental status examinations is the MMSE ( ), a 30-point standardized screening tool for assessing orientation, attention, short-term recall, naming, repetition, simple verbal and written commands, writing, and construction ( Fig. 44.3 ). The MMSE has been used in a variety of settings (e.g., community, institutions, general hospitals, specialty clinics), with many different neurological and psychiatric conditions (e.g., dementia, stroke, depression), across age ranges, and with different cultural and ethnic subgroups. Demographic variables such as age and education have been shown to systematically influence MMSE scores, so normative data or cut scores should account for these variables. One example of appropriate norms comes from the Epidemiologic Catchment Area study ( ); these are presented in Table 44.4 . Whereas many intact individuals achieve total scores near 30, a cut score of 23 on the MMSE has been shown to have adequate sensitivity and specificity (86% and 91%, respectively) for detecting dementia in community samples ( ). However, when working with highly educated patients (i.e., ≥16 years of formal education) a cut score of 27 is recommended ( ).

Despite its widespread use, the MMSE has some drawbacks. First, it only assesses a limited number of cognitive functions. Second, a potential threat to the test’s internal validity is the nonstandard administration of some of the items. Examples of these frequent adaptations of the MMSE include the use of nonorthogonal (i.e., semantically related) word stimuli for registration and recall, nonstandard scoring of serial 7’s, and nonstandard inclusion of spelling world backward. Another drawback of the MMSE is that it has “ceiling effects” that can miss cognitive impairments in high-functioning individuals. The MMSE also has difficulty differentiating individuals with mild cognitive impairment (MCI) from controls and those with dementia ( ). Finally, because this test relies on a single total score, partial administration of the measure (e.g., due to sensory impairments of the patient) provides no information about cognitive status. This same limitation is true for the Montreal Cognitive Assessment (MoCA). The MMSE is now copyrighted and is available for purchase.

Modified Mini-Mental State Examination

Some of the criticisms of the MMSE led to the development of the Modified Mini-Mental State Examination (3MS) ( ), a 14-item extension of the MMSE that assesses orientation (self, time, place), attention (simple and complex), memory (recall and recognition), language (naming, verbal fluency, repetition, following commands, writing), construction, and executive functioning (similarities). It remains relatively brief to administer (10 minutes), and age- and education-corrected normative data are available ( ). Regression-based prediction formulas for the 3MS allow for more accurate assessments of change across time ( ). The broader scoring range (0–100) has been shown to be more sensitive than that of the MMSE in identifying dementia ( ) and other cognitive disorders ( ) in large community samples. A cut score for cognitive impairment is typically 77 ( ), and a change of 5 points over the course of 5–10 years indicates the presence of clinically meaningful decline ( ).