PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Clin Neuropsychol. Author manuscript; available in PMC 2009 June 15.
Published in final edited form as:
PMCID: PMC2696226
NIHMSID: NIHMS107595

UNDERSTANDING THE NEUROPSYCHOLOGICAL PROFILE OF HIV+ PARTICIPANTS WITH LOW LITERACY: ROLE OF THE GENERAL ABILITY MEASURE FOR ADULTS (GAMA)

Abstract

The WRAT-3 Reading subtest (WRS) may be inappropriate in diseases having disproportionate impact on populations with educational disadvantages (i.e., HIV/AIDS). To understand how low literate individuals would perform on an IQ test requiring minimal education, the General Ability Measure for Adults (GAMA) was studied. HIV+ participants completed WRS, GAMA, and neuropsychological tests. Participants with low WRS (<80 SS) but higher GAMA (≥80 SS) had significantly better overall neuropsychological functioning than those with <80 SS on both tests. The GAMA may be a useful test when disparities in educational quality render reading-based measures of IQ a poor surrogate of premorbid function.

Keywords: Ethnicity, HIV, Literacy, Neuropsychological testing, Premorbid IQ, Quality of education

INTRODUCTION

Estimation of premorbid intellectual functioning is an essential part of interpreting neuropsychological performance following brain injury and disease. Oftentimes prior neuropsychological assessment is non-existent, which necessitates the use of premorbid indicators to determine the presence or degree of injury or disease-induced impairment. The neuropsychological research literature has studied various estimation methods including the “best performance” method, the use of actuarial or demographic regression formulas, and measuring cognitive functions assumed to be resistant to disease or injury. The latter method includes assessing reading ability to predict premorbid functioning.

Using reading level as a premorbid indicator is predicated on reading’s high correlation with IQ in the general population, its greater resistance to dementia than vocabulary tests, and its supposed reliance on previous knowledge rather than current cognitive functioning (Franzen, Burgess, & Smith-Seemiller, 1997; Nelson & McKenna, 1975). Several reading tasks have been studied including The National Adult Reading Test (NART) (Nelson & McKenna, 1975), The North American Adult Reading Test (NAART) (Spreen & Strauss, 1991), and versions of the Wide Range Achievement Test – Reading Recognition subtest (WRAT) (Jastak & Wilkinson, 1984). The WRAT Reading subtest unlike the NART (or NAART) includes regularly, as well as irregularly, spelled words. The WRAT Reading subtest is routinely used for assessing premorbid intelligence because it is well normed and easy to administer. It also provides a corresponding grade level for reading ability.

The National NeuroAIDS Tissue Consortium (NNTC) is a multi-site, longitudinal observational study of advanced HIV patients that utilizes a comprehensive neuropsychological battery and includes the WRAT-3 Reading subtest to estimate premorbid intelligence (Woods et al., 2004). Within this consortium, the Manhattan HIV Brain Bank (MHBB) site has a predominantly racial/ethnic minority cohort in which 41% of its participants have <an eighth-grade reading level and 56% have reading levels which are ≥2 years lower than their stated educational level (Ryan et al., 2005). Thus, it provides a laboratory in which the effects of neurologic disease on a low-literacy cohort can be examined. In the MHBB cohort we have observed individuals whose performance on the WRAT-3 Reading subtest is indicative of premorbid intellectual functioning in the mentally retarded range despite clinical presentations, as well as work and social histories, that are not suggestive of mental retardation (nor do these individuals report dyslexia, remedial reading, or any other condition that could account for a very low reading level). Thus, we suspect that a poor quality of education is responsible for very low reading levels in this cohort, and sought to assess intellectual functioning using a measure that would be less dependent on verbal abilities or education.

The MHBB is not the only group in which discrepancy in education and reading levels has been reported; it has been seen in research settings with other racial/ethnic minority cohorts (Manly, Jacobs, Touradji, Small, & Stern, 2002; O’Bryant, Schrimsher, & O’Jile., 2005; O’Bryant et al., 2007). These studies have led to a suggestion that reading ability should be used as a proxy for educational level (Manly et al., 2002). While reading ability is likely to be a better approximation of the number of years of education completed for racial/ethnic minorities, it may also have limitations in completely eradicating neuropsychological test biases, and addressing the issue of estimating premorbid intelligence.

Foremost among these limitations is the fact that reading ability has a variable relationship to intellectual functioning across racial/ethnic populations, and that there is over-representation of racial/ethnic minorities at the lowest levels of literacy (NCES, 2007). For racial/ethnic minorities, educational inequities (i.e., teacher training, school district spending on students, and student/teacher ratio, etc.) are confounded with reading ability. Given inequities in educational quality and funding, reading ability does not appear to have the same relationship to intellectual functioning in racial/ethnic minorities that has been reported in predominantly non-Hispanic White samples (Johnstone et al., 1996; Wiens, Bryan, & Crosson, 1993). Race/ethnicity has been found to be a significant predictor of the relationship between reading and IQ, and adds incrementally more variance to the model (beyond the WRAT Reading subtest) (Kareken, Gur, & Saykin, 1995). The incremental variance that race/ethnicity contributes to the relationship between reading and IQ likely reflects access to a quality education; a factor that can differ by race/ethnicity but is due to sociopolitical forces. Thus, while using educational level may be biased toward overestimating racial/ethnic minorities’ abilities, using reading level could potentially underestimate abilities for some, given inadequate teaching resources. Use of a test that is less dependent on education would be ideal in understanding expected neuropsychological functioning in individuals with low literacy.

The General Ability Measure for Adults (GAMA) assesses intellectual functioning using abstract designs, thereby limiting reliance on verbal comprehension (Naglieri & Bardos, 1997). It was specifically designed for individuals with limited educational experiences and/or verbal skills. Given these features of the GAMA, it may be an appropriate measure of intellectual functioning for a racially and ethnically diverse urban cohort who have likely experienced a poor quality of education.

The GAMA consists of four types of problems: matching, reasoning by analogy, sequencing, and mental construction. “Matching” requires the individual to choose which of six options is identical to the target stimulus in shape, color, and configuration. “Analogies” demands that the individual recognize the relationship between two figures and then determine which of six options mimics the same conceptual relationship to the target stimulus. In “Sequences” the color, shape, and location of the abstract design changes in a logical sequence. The individual must understand the pattern of change and choose the option that fits the pattern. “Construction” has the individual decide how several target shapes can be put together to produce one of the six options. Thus, the individual has to analyze and synthesize the spatial characteristics of the target shapes to mentally construct the correct design.

The psychometric properties of the GAMA reveal adequate internal consistency, as well as test–retest reliability. Validity studies revealed that individuals performed similarly on the GAMA as on other tests of intellectual functioning (Naglieri & Bardos, 1997). GAMA correlated .74 with WAIS-R PIQ, .65 with WAIS-R VIQ, and .75 with WAIS-R FSIQ. Notably, these correlations are higher than those of the WRAT-3 Reading subtest with the WAIS-R (despite similar racial/ethnic composition in the normative groups). The WRAT-3 manual reports that the reading subtest correlated .63 for WAIS-R VIQ, .31 for PIQ, and .53 for FSIQ (Wilkinson, 1993).

Both the WRAT-3 and the GAMA were standardized to match the 1990 US Census. The WRAT-3 standardization sample was comprised of 49.3% women and 50.7% men; the GAMA had 54.3% women and 45.7% men. The racial/ethnic composition of the GAMA and the WRAT-3 normative groups were similar. Racial/ethnicity breakdown was 71.7% White, 13.6% African American, 10.7% Hispanic, and 3.9% Other for the WRAT-3; and 76.3% White, 12.5% African American, 7.8% Hispanic, and 3.4% Other for the GAMA. Age groups for the WRAT-3 varied from age 5 to age 75 whereas the GAMA ranged from 18 to 96 years. While the WRAT-3 did not stratify by education level, the GAMA included five educational levels (less than 9 years education completed, 9–12 years completed without graduating, high school graduate or GED, some college including vocational programs and 2-year colleges, and a bachelor’s degree or more). The WRAT-3 test manual states that the standardization sample is representative of the US population with regard to SES whereas the GAMA makes no mention of SES characteristics of its normative sample.

Using a cross-sectional design, the present study examined the comparability of the GAMA and the WRAT-3 Reading subtest among a predominantly racial/ethnic minority cohort with advanced HIV disease. The study’s aim was to determine how the GAMA performed relative to the WRAT-3 Reading test at varying levels of literacy, and also to examine how the GAMA and the WRAT-3 Reading test related to neuropsychological domains at different levels of literacy. We hypothesized that participants with low literacy would perform better on the GAMA than on the WRAT-3 Reading subtest, and that the GAMA would more strongly correlate with neuropsychological functioning than the WRAT-3 among a cohort characterized by low literacy. Additionally, we hypothesized that participants with low literacy (WRAT-3 reading scores<80 SS), but GAMA scores within normal limits (>80 SS), would perform better on neuropsychological domains than individuals whose performance was low (<80 SS) on both tests.

METHOD

Research participants

The 95 study participants were derived from the Manhattan HIV Brain Bank (MHBB; R24MH59724), a longitudinal observational study that includes biannual neurologic, neuropsychologic, and psychiatric examinations of exclusively HIV participants. MHBB participation eligibility criteria include (1) advanced HIV disease or another disease without effective therapy,1 or (2) a CD4 count ≤50 cells/mm3 for at least a 3 month period of time, or (3) substantive risk for imminent mortality in the judgment of the participant’s primary physician. (For further inclusion criteria see Ryan et al., 2005.) Selection criterion for this study was having completed the GAMA in addition to the neuropsychological battery.

The MHBB participants all gave consent for post-mortem organ donation for research purposes. All participants were English speaking. Hispanic participants were mainly of Dominican and Puerto Rican descent and all were dominant English speakers. Participants were excluded from this study analysis if they reported dyslexia, remedial reading assistance, or were known to have another condition (i.e., CMV retinopathy, blindness) that confounded or prevented their reading. Data reported in this manuscript were obtained in compliance with the Mount Sinai School of Medicine IRB.

Procedure

Laboratory values

Current absolute CD4 count and HIV plasma RNA were obtained either through blood draw and laboratory analysis, or via clinical chart review. “Current” is defined as the closest laboratory measures to the neuropsychological test battery. All participants had a urine toxicology screen at the time of neuropsychological assessment.

Psychiatric interview

The Psychiatric Research Interview for Substance and Mental Disorders (PRISM) (Hasin et al., 1996) was administered to assess for substance use disorders.

Income

We used data from the 2000 U.S. Census Bureau report to obtain a proxy for income level, as self-reported income was not ascertained. Tables listing median household income per zip code by ethnicity were utilized (U.S. Census Bureau, 2000).

Reading level

The Reading Recognition subtest of the Wide Range Achievement Test -Version 3, WRAT-3 (Wilkinson, 1993) was administered to assess reading level. Participants were asked to pronounce words, and if they were unable to correctly pronounce 10 consecutive words, to name letters. Words are listed in order of decreasing familiarity and increasing phonological complexity. Grade-equivalent scores were derived by age-based normative values from the WRAT-3 manual. The WRAT-3 reading grades were quantified from pre-kindergarten through eighth grade. Beyond an eighth-grade reading level, participants were assigned a twelfth-grade reading level for “high school” and 13 years for “post high school” reading levels as we have done in our previous work (Ryan et al., 2005).

We operationalized ‘‘low literacy’’ as <80 SS (or < eighth-grade reading level) and divided the cohort on this basis.

General Ability Measure for Adults (GAMA)

The GAMA (Naglieri & Bardos, 1997) consists of four subtests that utilize abstract, colorful designs to assess matching to a sample, reasoning by analogy, mental construction, and recognizing a visual sequence. The GAMA is self-administered and has a multiple choice format; the time limit is 25 minutes. The four subtests are combined into an IQ score (M = 100, SD = 15).

Alphabet writing

Alphabet writing, a component of the HIV Dementia Scale (Power, Selnes, Grim, & McArthur, 1995), was used to study participants’ ability to write the letters of the alphabet without errors. Alphabet writing has been shown to be a predictor of reading (Bruck, Genesee, & Caravolas, 1997).

Neuropsychological battery

Participants were administered the NNTC neuropsychological test battery which assessed a broad range of cognitive abilities sensitive to HIV impairment (Woods et al., 2004). Specific tests included the Trailmaking Test – Parts A and B (TMT-A and TMT-B, respectively), Grooved Pegboard Test – Dominant and Nondominant Hands (GPDH and GPNH, respectively); Hopkins Verbal Learning Test (HVLT), Brief Visuospatial Memory Test-Revised (BVMT-R), WAIS-III Digit Symbol, WAIS-III Symbol Search, WAIS-III Letter Number Sequencing, Controlled Oral Word Association Test (FAS), Paced Auditory Serial Attention Test (PASAT), and the Wisconsin Card Sorting Test-64 card version (WCST-64). To investigate prevalence of impairment across domains, we assigned T-scores using the following published norms: Heaton et al. (1991) for GPDH, GPNH, TMT-A, and TMT-B; Gladsjo et al. (1999) for FAS; Benedict et al. (1998) for HVLT; Benedict (1997) for BVMT-R; Wechsler (1997) for the WAIS-III subtests; Diehr et al. (2003) for PASAT; and Kongs et al. (2000) for the WCST-64. The PASAT and FAS provide racial/ethnicity corrections for non-Hispanic Whites and African Americans (Diehr et al., 2003; Gladsjo et al., 1999). All of the tests except the BVMT-R and the WAIS-III tests corrected for education.

The individual tests were also grouped according to domains (Woods et al., 2004) as indicated in the Appendix. Domain scores were derived from the mean T-scores of the individual tests in that particular domain with the Global domain score derived from the mean of all the individual neuropsychological test T-scores.

RESULTS

Demographic and medical characteristics

A total of 95 participants (47% male) were studied. Of the participants, 44% were African American, 32% were non-Hispanic White, and 24% were Hispanic. Mean age was 49.4 years (SD = 7.7). A total of 78% had AIDS and the remainder had no documentation of a CD4 <200 cells/mm3 or an AIDS-defining illness (CDC, 1992). Median CD4 count was 315 cells/mm3 and median log plasma HIV RNA was 1.88 copies/mL. Absolute CD4 count was drawn a mean of 2.54 days (SD = 3.32) from the GAMA and NP battery (with 70% of the participants having labs drawn the same day). There were no significant differences in CD4 or plasma HIV RNA across the racial/ethnic groups. Participants mainly identified intravenous drug use (IDU) as their HIV risk factor (37.9%) with homosexual/bisexual risk the next highest category (30.5%). Comparison of mean education and reading levels revealed that African American and Hispanic participants had significantly lower education, F(2, 92) = 7.3, <.01, and reading grade levels, F(2, 92)=9.3, p<.001, than non-Hispanic Whites, but not compared to each other (see Table 1). Hispanic participants were significantly younger (M = 45.8 years, SD = 6.1) than the African Americans (M = 50.3 years, SD = 7.3) and the non-Hispanic Whites (M = 50.9 years, SD = 8.6) F(2, 92)=35.17, p<.05.

Table 1
Education level and reading grade

WRAT-3 Reading and GAMA

For the sample, the mean WRAT-3 Reading standard score was 88.5 (SD = 17.8), and the mean GAMA standard score was 90.0 (SD = 12.9). The GAMA and the WRAT-3 Reading subtest were significantly correlated (r = .50, p<.01). WRAT-3 Reading was more highly correlated with education (r =.72, p<.01) and income (r =.56, p<.01) than the GAMA (r =.26, p<.05; r =.40, p<.05, respectively). Fisher’s z transformation revealed that the WRAT-3 Reading correlation with education was significantly stronger (z diff=4.35, p<.001) than that of the GAMA and education. There was no significant difference in the correlation of the tests with income.

Comparison by reading levels (<eighth-grade reading vs ≥ eighth grade)

In our sample, a SS of <80 on the WRAT-3 Reading test was equivalent to < eighth-grade reading level. While 2% of the cohort had < eighth-grade education, 38% had < eighth-grade reading level as assessed by the WRAT-3 Reading subtest. Table 2 displays the sample’s medical and demographic information by reading level (< eighth-grade vs ≥ eighth grade). Among participants who had < eighth-grade reading level, their mean education level was 10.9 years (SD = 2.4) and their median household income per zip code was $21,810. Both African American and Hispanic participants were more likely than non-Hispanic Whites to have < eighth-grade reading level (χ2 = 11.6, df = 1, p<.01; χ2 = 6.09, df = 1, p<.05). Of the participants with < eighth-grade reading level, 53% were unable to write the alphabet without making an error (not including self-corrected errors).

Table 2
Demographic and medical status by reading level

Correlations between the WRAT-3 Reading subtest and the GAMA with specific neuropsychological domains varied by reading level (< eighth grade vs ≥ eighth grade) as depicted in Table 3. Among low-literate participants (< eighth-grade reading) the WRAT-3 Reading subtest was not significantly correlated with any of the neuropsychological domains. Reading had small to medium-sized correlations with motor, processing speed, working memory, learning, and global neuropsychological functioning among participants with ≥ eighth-grade reading. Both groups exhibited more robust correlations with the GAMA and the largest correlations were with the processing speed and global neuropsychological domains.

Table 3
Correlations of WRAT-3 Reading and General Ability Measure for Adults with neuropsychological domains by reading level

Comparison of reading levels and GAMA test performance

We divided the sample into quartiles based on WRAT-3 Reading SS. As shown in Table 4, participants scoring in the lowest quartile of WRAT-3 Reading scores had significantly less education, F(3, 91)=26.42, p=.000, and as expected, lower reading SS, F(3, 91)=283.4, p=.000, than the other groups. Notably, their GAMA scores were significantly higher than their WRAT-3 scores, t(23)=−6.40, p<.001. In contrast, participants in the highest quartile of WRAT-3 Reading scores had GAMA scores that were significantly lower than their WRAT-3 scores, t(21)=5.47, p<.001. In the highest and lowest WRAT-3 reading quartiles, there were no differences in HIV indices of CD4 and HIV RNA. Participants in the middle quartiles of reading function scored equivalently on the WRAT-3 and the GAMA.

Table 4
Participant characterization by WRAT-3 reading quartiles

In order to assure that better performance on the GAMA in the lowest WRAT-3 quartile was not solely an artifact, we also separated the group into quartiles based on GAMA performance. As shown in Table 5, both participants scoring in the lowest GAMA quartile as well as those scoring in the second GAMA quartile had significantly less education than participants in the third GAMA quartile, F(3, 91)=4.50, p<.01. Additionally participants in the lowest GAMA quartile had significantly lower reading SS, F(3, 91)=12.74, p=.000, than the other groups. In regards to WRAT-3 and GAMA performance, the first three quartiles showed equivalent performance on the two tests, but the participants in the highest GAMA quartile exhibited significantly better performance on the GAMA, t(20)=2.69, p<.05, relative to the WRAT-3 (Table 5). No differences in CD4 or HIV RNA were detected.

Table 5
Participant characterization by General Ability Measure for Adults quartiles

GAMA, reading level, and global neuropsychological test performance

The GAMA (r=.64, p<.0001) and the WRAT-3 Reading tests (r=.41, p<.0001) were each significantly correlated with global neuropsychological functioning; using Fisher’s z transformation, the GAMA correlation with global neuropsychological functioning was significantly stronger (z diff = 2.19, p < .05). Additionally, all of the GAMA subtests were significantly correlated with the neuropsychological domain scores (rs=.2–.60), with the exception of the GAMA construction subtest and the working memory domain.

Neuropsychological functioning by low reading levels and GAMA test performance

To understand whether a difference in neuropsychological test performance existed based on WRAT-3 and GAMA scores, we compared participants with both WRAT-3 reading levels and GAMA scores that were <80 SS (n=15) to participants with low (<80 SS) WRAT-3 reading levels but higher GAMA scores (≥80 SS) (n=19). The two groups did not significantly differ in age, HIV risk factor (i.e., IDU, sexual risk, or blood products), substance use disorders (either within the past 12 months or at any time in their lives), presence of an illicit urine toxicology screen, or HIV disease indices (CD4 and plasma HIV RNA).

As shown in Table 6, the participants with low WRAT and low GAMA scores performed worse on every neuropsychological domain and significantly lower on global neuropsychological functioning, t(32)=−2.56, p<.05, and processing speed, t(32)=−3.19, p<.01. There were also trends toward worse functioning in learning and executive functioning. The participants with ≥80 GAMA SS (but low WRAT-3 scores, <80 SS) exhibited normal T-score domain performance on processing speed, working memory, and fluency.

Table 6
Neuropsychological domain scores

DISCUSSION

The present study compared reading ability and a test of nonverbal intellectual functioning (that was less reliant on education) to assess their relationship to each other and to global and domain-specific neuropsychological function among a predominantly racial/ethnic cohort in which more than a third of participants had < eighth-grade reading level. Consistent with our hypotheses, the GAMA correlated more strongly with global neuropsychological functioning than reading ability. Participants with the lowest literacy (mean reading grade score = fourth grade) achieved GAMA scores that were significantly higher than their reading scores. Among those with < eighth-grade reading level, WRAT-3 reading scores were not significantly associated with neuropsychological domain scores whereas GAMA scores were, and across the sample the GAMA was found to be less confounded by education. While participants with low WRAT and low GAMA scores (both <80 SS) had uniformly impaired average T-scores on neuropsychological domains, those with low WRAT-3 ability (<80 SS) but GAMA scores within normal limits (>80 SS) performed significantly better on global neuropsychological functioning and processing speed.

The results demonstrate that the GAMA and the WRAT-3 Reading test function differently in low-literate participants. For instance, those who perform at the lowest level of literacy would be labeled as falling in the “mentally retarded” range of intellectual functioning (if using reading scores to estimate their IQ), whereas this same group performed in the “low average” range on the GAMA. Notably, their GAMA scores were only 1 standard deviation below participants with the highest level of literacy (mean WRAT-3 SS = 113; SD = 4) whereas their WRAT-3 scores were 3 standard deviations less. Higher GAMA compared to reading scores among low-literate participants is consistent with the report of stronger visuoperceptual skills relative to language- or reading-related abilities among both illiterate, indigenous adults unexposed to an educational system (Ostrosky-Solis, Ramirez, & Ardilla, 2004) and pre-literate, low-SES, African American kindergarteners (Noble, Norman, & Farah, 2005).

Our study findings also suggest that using reading scores to understand premorbid functioning could lead to inaccurate interpretations about the lack of disease-related effects because some low-literate individuals may exhibit a “floor effect.” As we demonstrated, separating patients with low WRAT scores (<80 SS) by GAMA scores (<80 SS versus ≥80 SS) revealed differences in performance on neuropsychological domains that were unrelated to HIV disease indices or other risk factors (age, means of HIV risk, or substance use disorders). Thus, the GAMA may help distinguish individuals who demonstrate solely low literacy from those with longstanding poor cognitive functioning across measures.

While the GAMA shows promise in understanding the abilities of low-literate individuals, current research has yet to determine the best way to assess cognitive functioning of racial/ethnic minorities that may have received a poor quality of education. Manly (2005) has noted that most neuropsychological tests do not tap the full potential of cognitive skills and strategies of racial/ethnic minorities, and our results support this observation. Although neuropsychological tests are vulnerable to sociodemographics (Byrd et al., 2006; Heaton et al., 1991; Heaton, Taylor, & Manly, 2001; Manly et al., 1998, 2004), most tests were designed for use with a non-Hispanic White population and have been normed primarily with this group (Manly, 2005). This is especially problematic in a disease like HIV, where racial/ethnic minorities are disproportionately affected.

It is imperative that clinicians be mindful of the higher likelihood that racial/ethnic minorities were raised in a low-SES environment, and understand that SES impacts reading. Low SES comprises not only low family income, but also lower maternal/caregiver education level, limited or poor-quality community resources in terms of schools, libraries, etc., and fewer and/or poor-quality home literacy materials and experiences (Brooks-Gunn, Duncan, Klebanov, & Sealand, 1993; Fazio, Naramore, & Connell, 1996; Hoffman & Llagas, 2003; Nettles & Perna, 1997). Given these factors, SES is highly predictive of the quantity and quality of children’s early reading experiences (Bradley, Corwyn, Pipes McAdo, & Garcia Coll, 2001; Raz & Bryant, 1990; Whitehurst, 1997). There are also qualitative differences in the early home literacy experiences of African Americans. African Americans are more likely to have rich oral storytelling experiences (Ball, 1992), but are less likely to engage in daily storybook reading (Federal Interagency Forum on Child and Family Statistics, 2003). Additionally, their first experiences with text may occur as environmental forms of print, such as trademarks, which can often have unconventional spellings (Craig & Washington, 2004). Thus, the circumstances that contribute to low literacy are multi-faceted, and yet these circumstances are not routinely inquired about in the clinical interview nor are they factored into interpreting the neuropsychological profile. Similarly, experiences such as early exposure to print versus oral storytelling among low-literate people are not considered.

In trying to understand the quality of education in our own cohort, we found and previously reported that 56% of our cohort has a reading level that is at least 2 years discrepant from their educational level, suggesting that a sizable portion of our cohort has received a poor quality of education. Disentangling the effect of poor educational quality from HIV-related effects on cognitive functioning is very challenging given the dearth of information about normative neuropsychological performance in low-literate individuals. Besides normative data, understanding cognitive reserve in low-literate people is also important.

Education (De Ronchi et al., 2002; Satz et al., 1993; Stern, Silva, Chaisson, & Evans, 1996;) and verbal IQ (Basso & Bornstein et al., 2000; Farinpour et al., 2003) have been found to be markers of cognitive reserve in HIV. However, these measures may not be reliable markers of cognitive reserve for HIV+ racial/ethnic minorities who have received a poor quality of education. For instance, among healthy racial/ethnic minority elders, literacy (not education) was the most sensitive predictor of verbal memory decline (Manly, Touradji, Tang, & Stern, 2003). Among low-literate individuals it is unclear what the best predictor of cognitive reserve is. The GAMA may be the best predictor of cognitive reserve for low-literate individuals, because performance on it is less dependent on education (Noble et al., 2005; Ostrosky-Solis et al., 2004) and it has “ecologic relevance” for this group as they have may have relied more on visuoperceptual ability than literacy to negotiate the world. Longitudinal studies of HIV-related neurocognitive impairment in low-literate individuals would help to increase understanding of the utility of literacy versus visuoperceptual processing as a marker of cognitive reserve.

Whether low literacy and low GAMA scores signify lower cognitive reserve and greater vulnerability to the effects of HIV or whether low scores on both tests denote poorer premorbid cognitive functioning remains to be determined. While there is some evidence of an HIV-related pattern of impairment in NP domain scores among the group who had <80 SS on both tests (i.e., significantly lower speed of processing and a trend toward lower learning and executive functioning), a longitudinal study following individuals pre and post seroconversion would determine the significance of both low WRAT and low GAMA scores.

A limitation of this study is the assumption that HIV does not affect the GAMA. Investigation of how the GAMA performs relative to neuropsychological tests in a seronegative control group of low-literate people is needed in order to judge its ultimate utility. Despite not knowing HIV’s effect on the GAMA, our finding that a subgroup of low-literate people had GAMA scores that were within normal limits was consistent with these participants’ present and historical functional levels. The GAMA was also more strongly correlated with global neuropsychological functioning than the WRAT-3 reading test. Taken together, the GAMA appears to provide valuable information for understanding individuals who may have had ineffective instruction, and it should be considered in a neuropsychological evaluation when reading scores are <80 SS. As this study demonstrates, identifying an accurate premorbid estimation method for individuals whose low literacy is secondary to a poor quality of education would be a significant contribution to neuropsychological research.

We also recommend further study of phonological awareness skills, the building blocks of reading. Phonological awareness skills in kindergarteners are a better predictor of reading in adolescence than kindergarten reading ability (MacDonald & Cornwall, 1995). Noble, Farah, and McCandliss (2006) suggest that phonological awareness interacts with SES in the development of reading ability. At lower phonological awareness levels, children from lower-SES environments had worse reading ability, suggesting that a higher-SES environment and its accompanying resources can facilitate reading. More than half of our participants with < eighth-grade reading level were unable to write the alphabet flawlessly, and likely have deficient phonological awareness skills. Thus, future study of the relationship between alphabet writing and phonological awareness in low-literate adults may help to provide more specific information about the nature of their literacy deficiencies such that they can be quantified more precisely.

Currently it is unclear what constitutes impairment among individuals with low literacy, as well as what constitutes a clinically meaningful decline in cognitive functioning. Being able to identify cognitive impairment and decline in low-literate individuals is particularly important in HIV given the disproportionate effect of the virus on racial/ethnic minorities who are vulnerable to receiving a poor quality of education. In fact, HIV may be one of the most challenging diseases in which to distinguish disease-related effects from poor education because, for some individuals, HIV can cause only subtle neuropsychological impairment or may not cause any impairment at all (given advances in combination antiretroviral treatment). Despite the backdrop of this challenge, we were able to distinguish low-literate individuals based on their GAMA performance and show differences in overall neuropsychological functioning. These findings highlight the need for further refinement of neuropsychological assessment techniques with low-literate individuals; work, in HIV populations, that will require a heretofore unprecedented understanding of the interplay of social/environmental factors and neurobiology.

ACKNOWLEDGMENTS

The authors thank the participants and staff of the Manhattan HIV Brain Bank. This work is supported by grant R24MH59724 (to SM) and the Clinical Research Center of the Mount Sinai School of Medicine (M01-RR-00071) from the National Institutes of Health.

APPENDIX

Neuropsychological domains

DomainTestsNorms
GlobalMean T-score of all NP TestsAs indicated below
MotorGrooved Pegboard, DHHeaton et al., 1991
Grooved Pegboard, NDH
Processing SpeedTrailmaking Test, AHeaton et al., 1991
WAIS-III Digit SymbolWechsler, 1997
WAIS-III Symbol Search
Working MemoryWAIS-III Letter Number SequencingWechsler, 1997
PASATDiehr et al., 2003
LearningBrief Visual Memory Test - Total RecallBenedict et al., 1997, 1998
Hopkins Verbal Learning Test - Total Recall
MemoryBrief Visual Memory Test - Delayed RecallBenedict, 1997, 1998;
Hopkins Verbal Learning Test - Delayed Recall
FluencyFASGladsjo et al., 1999
Executive FunctioningTrailmaking Test, BHeaton et al., 1991
WCST Perseverative ResponsesKongs et al., 2000

Footnotes

Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf

This article maybe used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden.

Publisher's Disclaimer: The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.

1Indicator conditions include progressive multifocal leucoencephalopathy; lymphoma (systemic or CNS); disseminated mycobacteriumavium-intercellulare; wasting (>30% of lean body mass); AIDS dementia complex; CMV end organ disease; viscera Kaposi’s sarcoma; congestive heart failure; or serum albumin <3.2 g/dl.

REFERENCES

  • Ball AF. Cultural preference and the expository writing of African-American adolescents. Written Communication. 1992;9:501–532.
  • Basso MR, Borstein RA. Estimated premorbid intelligence mediates neurobehavioral change in individuals infected with HIV across 12 months. Journal of Clinical and Experimental Neuropsychology. 2000;22:208–218. [PubMed]
  • Benedict RH. Brief visuospatial memory test-revised. Odessa, FL: Psychological Assessment Resources; 1997.
  • Benedict RH, Schretlen D, Groninger L, Brandt J. Hopkins verbal learning test – revised: Normative data and analysis of inter-form and test–retest reliability. The Clinical Neuropsychologist. 1998;12:43–55.
  • Bradley RH, Corwyn RF, Pipes McAdoo H, Garcia Coll C. The home environments of children in the United States Part I: Variations by age, ethnicity, and poverty status. Child Development. 2001;72:1844–1867. [PubMed]
  • Brooks-Gunn J, Duncan GJ, Klebanov PK, Sealand N. Do neighborhoods influence child and adolescent development? American Journal of Sociology. 1993;99:353–395.
  • Bruck M, Genesee F, Caravolas M. A cross-linguistic study of early literacy acquisition. In: Blachman B, editor. Foundations of reading acquisition and dyslexia: Implications for early interventions. Mahwah, NJ: Lawrence Erlbaum Associates Inc; 1997. pp. 145–162.
  • Byrd D, Miller S, Reilly J, Weber S, Wall T, Heaton R. Early environmental factors, ethnicity, and adult cognitive test performance. The Clinical Neuropsychologist. 2006;20:243–260. [PubMed]
  • CDC. 1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. Morbidity and Mortality Weekly Reports Recommdations and Reports. 1992. pp. 1–19. [PubMed]
  • Craig HK, Washington JA. Grade-related changes in the production of African American English. Journal of Speech, Language, and Hearing Research. 2004;47:450–463. [PubMed]
  • De Ronchi D, Faranca I, Berardi D, Scudellari P, Borderi M, Manfredi R, et al. Risk factors for cognitive impairment in HIV-1-infected persons with different risk behaviors. Archives of Neurology. 2002;59:812–818. [PubMed]
  • Diehr MC, Cherner M, Wolfson TJ, Miller SW, Grant I, Heaton RK, et al. The 50 and 100-item short forms of Paced Auditory Serial Addition Task (PASAT): Demographically corrected norms and comparisons with the full PASAT in normal and clinical samples. Journal of Clinical Experimental Neuropsychology. 2003;25:571–585. [PubMed]
  • Farinpour R, Miller EN, Satz P, Selnes OA, Cohen BA, Becker JT, et al. Psychosocial risk factors of HIV morbidity and mortality: Findings from the MACS. Journal of Clinical Experimental Neuropsychology. 2003;25:654–670. [PubMed]
  • Fazio BB, Naremore RC, Connell PJ. Tracking children from poverty at risk for specific language impairment: A 3-year longitudinal study. Journal of Speech and Hearing Research. 1996;39:661–624. [PubMed]
  • Federal Interagency Forum on Child, & Family Statistics. America’s children: Key national indicators of well being. Washington, DC: U.S. Government Printing Office; 2003.
  • Franzen MD, Burgess EJ, Smith-Seemiller L. Methods of estimating premorbid functioning. Archives of Clinical Neuropsychology. 1997;12:711–738. [PubMed]
  • Gladsjo JA, Schuman CC, Evans JD, Peavy GM, Miller SW, Heaton RK. Norms for letter and category fluency: Demographic corrections for age, education, and ethnicity. Assessment. 1999;6:147–178. [PubMed]
  • Hasin DS, Trautman KD, Miele GM, Samet S, Smith M, Endicott J. Psychiatric Research Interview for Substance and Mental Disorders (PRISM): Reliability for substance abusers. American Journal of Psychiatry. 1996;153(9):1195–1201. [PubMed]
  • Heaton R, Grant I, Matthews CG. Comprehensive norms for an Expanded Halstead-Reitan Battery: Demographic corrections, research findings, and clinical applications. Odessa, FL: Psychological Assessment Resources; 1991.
  • Heaton RK, Taylor M, Manly J. Demographic effects and demographically corrected norms with the WAIS-III and WMS-III. In: Tulsky D, Heaton RK, Chelune GJ, Ivnik I, Bornstein RA, Prifitera A, et al., editors. Clinical interpretations of the WAIS-III and WMS-III. San Diego, CA: Academic Press; 2001. pp. 181–210.
  • Hoffman K, Llagas C. Status and trends in the education of Blacks (NCES 2003-034) September. Washington, DC: U.S. Department of Education, National Center for Education Statistics; 2003.
  • Jastak S, Wilkinson G. The Wide Range Achievement Test: Manual of instructions. Wilmington, DE: Jastak Associates; 1984.
  • Kareken DA, Gur RC, Saykin AJ. Reading on the Wide Range Achievement Test – Revised and parental education as predictors of IQ: Comparison with the Barona Formula. Archives of Clinical Neuropsychology. 1995;10:147–157. [PubMed]
  • Kongs SK, Thompson LL, Iverson GL, Heaton RK. Wisconsin Card Sorting Test-64 Card Computerized Version. Odessa, FL: Psychological Assessment Resources; 2000.
  • Kutner M, Greenberg E, Jin Y, Boyle B, Hsu Y, Dunleavy E. U.S. Department of Education. Literacy in everyday life: Results from the 2003 National Assessment of Adult Literacy (NCES 2007-480) Washington, DC: National Center for Education Statistics; 2007.
  • MacDonald GW, Cornwall A. The relationship between phonological awareness and reading and spelling achievement eleven years later. Journal of Learning Disabilities. 1995;28:523–527. [PubMed]
  • Manly JJ. Advantages and disadvantages of separate norms for African Americans. The Clinical Neuropsychologist. 2005;19:270–275. [PubMed]
  • Manly JJ, Jacobs DM, Sano M, Bell K, Merchant CA, Small SA, et al. Cognitive test performance among nondemented elderly African Americans and Whites. Neurology. 1998;50:1238–1245. [PubMed]
  • Manly JJ, Jacobs DM, Touradji P, Small SA, Stern Y. Reading level attenuates differences in neuropsychological test performance between African American and White elders. Journal of the International Society. 2002;8:341–348. [PubMed]
  • Manly JJ, Touradji P, Tang M-X, Stern Y. Literacy and memory decline among ethnically diverse elders. Journal of Clinical and Experimental Neuropsychology. 2003;5:680–690. [PubMed]
  • Naglieri JA, Bardos AN. General Ability Measure for Adults. Minneapolis, MN: National Computer Systems; 1997.
  • Nettles MT, Perna LW. The African American education data book, Volume II: Preschool through high school education. Fairfax, VA: Frederick D. Patterson Research Institute; 1997.
  • Nelson HE, McKenna P. The use of current reading ability in the assessment of dementia. British Journal of Social and Clinical Psychology. 1975;14:259–267. [PubMed]
  • Noble KG, Farah MJ, McCandliss BD. Socioeconomic background modulates cognition–achievement relationships in reading. Cognitive Development. 2006;21:349–368. [PMC free article] [PubMed]
  • Noble KG, Norman MF, Farah MJ. Neurocognitive correlates of socioeconomic status in kindergarten children. Developmental Science. 2005;8:74–87. [PubMed]
  • O’Bryant SE, Schrimsher GW, O’Jile JR. Discrepancies between self-reported years of education and estimated reading level: Potential implications for neuropsychologists. Applied Neuropsychology. 2005;12:5–11. [PubMed]
  • O’Bryant SE, Lucas JA, Willis FB, Smith GE, Graff-Radford NR, Ivnik RJ. Discrepancies between self-reported years of education and estimated reading level among elderly community-dwelling African-Americans: Analysis of the MOAANS data. Archives of Clinical Neuropsychology. 2007;22:327–332. [PubMed]
  • Ostrosky-Solis F, Ramirez M, Ardilla A. Effects of culture and education on neuropsychological testing: A preliminary study with indigenous and nonindigenous population. Applied Neuropsychology. 2004;11:186–193. [PubMed]
  • Power C, Selnes OA, Grim JA, McArthur JC. HIV Dementia Scale: A rapid screening test. Journal of Acquired Immunodeficiency Syndromes and Human Retrovirology. 1995;8:273–278. [PubMed]
  • Raz IS, Bryant P. Social background, phonological awareness, and children’s reading. British Journal of Developmental Psychology. 1990;8:209–225.
  • Ryan EL, Baird R, Mindt Rivera M, Byrd D, Monzones J, Morgello S. the Manhattan HIV Brain Bank. Neuropsychological impairment in racial/ethnic minorities with HIV infection and low literacy levels: Effects of education and reading level in patient characterization. Journal of the International Neuropsychological Society. 2005;11:889–898. [PMC free article] [PubMed]
  • Satz P, Morgenstern H, Miller EN, Selnes OA, McArthur JC, Cohen BA, et al. Low education as a possible risk factor for cognitive abnormalities in HIV-1: Findings from the multicenter AIDS Cohort Study (MACS) Acquired Immune Deficiency Syndrome. 1993;6:503–511. [PubMed]
  • Spreen O, Strauss E. A compendium of neuropsychological tests: Administration, norms, and commentary. New York: Oxford University Press; 1991.
  • Stern RA, Silva G, Chaisson N, Evans L. Influence of cognitive reserve on neuropsychological functioning in asymptomatic human immunodeficiency virus-1 infection. Archives of Neurology. 1996;53:148–153. [PubMed]
  • U.S. Census Bureau (2000) Summary File 3 (SF 3) 2000. [Retrieved May 23, 2006]. from http://factfinder.census.gov.
  • Wechsler D. Wechsler Adult Intelligence Scale – Third Edition: Administration and Scoring Manual. San Antonio, TX: Harcourt Brace; 1997.
  • Whitehurst GL. Language processes in context: Language learning in children reared in poverty. In: Adamson LB, Romski MA, editors. Research on communication and language disorders: Contribution to theories of language development. Baltimore: Brookes; 1997.
  • Wiens AN, Bryan JE, Crossen JR. Estimating the WAIS-R FSIQ from the National Adult Reading Test-Revised in normal subjects. The Clinical Neuropsychologist. 1993;7:70–84.
  • Wilkinson G. Wide Range Achievement Test (3rd ed.) Administration manual. Wilmington, DE: Wide Range Inc.; 1993.
  • Woods SP, Rippeth JD, Frol AB, Levy JK, Ryan E, Soukup VM, et al. Interrater reliability of clinical ratings and neurocognitive diagnoses in HIV. Journal of Clinical and Experimental Neuropsychology. 2004;26:759–778. [PubMed]