word acentuación de prueba de iq versión española

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Is adaptation of the Word Accentuation Test of PremorbidIntelligence necessary for use among older,Spanish-speaking immigrants in the United States?

ROBERT W. SCHRAUF,1 SANDRA WEINTRAUB,2 and ELLEN NAVARRO21Department of Linguistics and Applied Language Studies, The Pennsylvania State University, University Park, Pennsylvania2Department of Cognitive Neurology, Northwestern University, Chicago, Illinois

(Received September 15, 2005; Final Revision December 15, 2005; Accepted December 15, 2005)

Abstract

Adaptations of the National Adult Reading Test (NART) for assessing premorbid intelligence in languages otherthan English requires (a) generating word-items that are rare and do not follow grapheme-to-phoneme mappingscommon in that language, and ( b) subsequent validation against a cognitive battery normed on the population ofinterest. Such tests exist for Italy, France, Spain, and Argentina, all normed against national versions of the WechslerAdult Intelligence Scale. Given the varieties of Spanish spoken in the United States, the adaptation of the SpanishWord Accentuation Test (WAT) requires re-validating the original word list, plus possible new items, against acognitive battery that has been normed on Spanish-speakers from many countries. This study reports the generationof 55 additional words and revalidation in a sample of 80 older, Spanish-dominant immigrants. The BateraWoodcock-Muoz Revisada (BWM-R), normed on Spanish speakers from six countries and five U.S. states, wasused to establish criterion validity. The original WAT word list accounted for 77% of the variance in the BWM-Rand 58% of the variance in Ravens Colored Progressive Matrices, suggesting that the unmodified list possessesadequate predictive validity as an indicator of intelligence. Regression equations are provided for estimatingBWM-R and Ravens scores from WAT scores. (JINS, 2006, 12, 391399.)

Keywords: Neuropsychological test, Educational measurement, Multilingualism, Alzheimers disease, Dementia,Hispanic Americans

INTRODUCTION

Validation of the Word Accentuation Test

of Premorbid Intelligence (WAT) among

Older, Spanish-Speaking Immigrants

in the United States

The identification of dementia in older individuals requiresthat some standard of prior cognitive ability level be avail-able for comparison with screening or neuropsychologicaltest measures. One method that has been used to estimatepremorbid intelligence is the use of reading tests. Thismethod is based on three assumptions: (1) scores on tests of

reading ability and general intelligence are highly corre-lated among normals (Nelson & McKenna, 1975); (2) theability to pronounce words, without necessarily being ableto define them, is preserved in early stages of dementia(Christensen et al., 1991; Cummings et al., 1986; OCarroll,1995; Patterson et al., 1994; Storandt et al., 1995); and (3)familiarity with low-frequency words is an indicator of prior

education or higher levels of crystallized intelligence (Spreen& Strauss, 1991). This is the logic behind the National AdultReading Test ( NART; Nelson, 1982) and its various adap-tations (e.g., Blair & Spreen, 1989; Grober & Sliwinski,1991; Nelson, 1982) in which an individual reads aloud alist of rarely encountered English words. Scores on thesetests are then used in regression equations predicting scoreson the WechslerAdult Intelligence Scales (WAIS; for review,see Crawford, 1992).

The adaptation of tests similar to the NART in languagesother than English presents particular challenges. In gen-

Correspondence and reprint requests to: Robert W. Schrauf, Depart-ment of Linguistics and Applied Language Studies, 305 Sparks Building,Pennsylvania State University, University Park, PA 16802. E-mail:[email protected]

Journal of the International Ne uropsychological Society (2006), 12, 391399.Copyright 2006 INS. Published by Cambridge University Press. Printed in the USA.DOI: 10.10170S1355617706060462

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eral, on any NART-like test, word items are selected thatmeet two requirements. First, they must be sufficiently rarein the corpus so that the ability to read them reflects moreadvanced reading knowledge. Second, they must not followthe usual grapheme-to-phoneme mapping rules in the lan-guage. This ensures that individuals can only pronounce thewords because they have prior familiarity with them andnot by applying pronunciation rules. This is how Englishwords were chosen for the various British versions of theNART (Crawford, 1990, 1992; Nelson, 1982; Nelson &OConnell, 1978) and the versions adapted for Canada andthe United States (Blair & Spreen, 1989; Grober & Sliwin-ski, 1991, Schwartz & Saffran, 1987). The same proceduremust be followed in languages other than English. That is,the NART cannot be translated, but new word lists must beconfected for each language, again targeting words that areboth rare and that do not follow common grapheme-to-phoneme mappings in that language. Thus, for example,reading tests have been developed in Italian (Test di Intel-ligenza Breve or TIB; Colombo et al., 2000), in French

(the fNART by Bovet on a French-speaking Swiss sample;see Mackinnon & Mulligan, 2005), and in Spanish forSpain (Del Ser et al., 1997) and Argentina (Burin et al.,2000).

A second issue in developing NART-like reading tests inother languages is choosing an appropriate IQ battery againstwhich to establish the criterion validity of the instrument.The English versions were validated against the WAIS. Inthe case of languages other than English, either a properlyadapted version of the WAIS or a similarly normed cogni-tive battery must be used. For certain languages, versionsof the WAIS have been adapted, both linguistically andculturally, and re-standardized on the population of the rel-

evant language group. Thus for instance, versions of theFrench WAIS (Wechsler, 1989, 2000) were normed onFrench speakers in France, the ItalianWAIS (Wechsler, 1974,1997) was normed in Italy, and the Spanish WAIS wasnormed on Spanish speakers in Spain (Wechsler, 1958[1982], 1997) and in Argentina (Wechsler, 1984). Whereno version of the WAIS has been adapted and normed,another standardized instrument must be used.

Both of these issues shape the parameters for adaptingthe existing Spanish versions of theNART for Spanish speak-ers in the United States, where according to Census 2000there are almost 8 million Spanish-speakers who speakEnglish either not at all or not well. First, the words

used as test items must be appropriate for speakers of manySpanishes because the Spanish-speaking population ofthe United States has its origins in both Spain and LatinAmerica. Second, the target list must be validated against acognitive battery that was itself standardized on speakers ofSpanish from Spain, Latin America, and the United States.

The first Spanish version of the NART, the Word Accen-tuation Test (WAT), was developed in Spain by Del Ser andcolleagues (1997). Because Spanish has highly regular rulesof pronunciation, rare accented words were selected as testitems and then shorn of their accents (Table 1). That is,

Spanish represents phonemes in an almost straightfor-ward letter-to-sound mapping (Signorini, 1997; p. 323).Nevertheless, there are exceptions to this rule, and theseare words whose lexical stress requires explicit markingby means of accent. Thus, to pronounce written words aSpanish speaker must possess both knowledge of the rulesplus word-specific knowledge. It is this latter that is testedin the WAT. In the Del Ser et al. study (1997), perfor-mance by 81 cognitively healthy elders on a 30-item wordlist correlated significantly with Vocabulary (r 5 .842)

and Picture Completion (r5 .722) subtests of the Spanish(Spain) version of the WAIS (Wechsler, 1982). Internalvalidity (r5 .91), testretest reliability after 30 days ( r5.97), and inter-rater reliability (r5 .93) were all high. In across-validation with 40 controls and 20 patients withNINCDS-ADRDA diagnoses of dementia, matched on sex,age, and education, no statistical difference in WAT scoreswas obtained between groups, indicating that the WAT isresistant to mental deterioration.

An adaptation of theWAT for BuenosAires (the WAT-BA)was subsequently developed by Burin and colleagues (2000).

Table 1. List of 30 words in the WAT (Del Ser et al., 1997) andtheir correctly accented forms

Accented form WAT Item

ABOGACA ABOGACIAACM ACMEACLITO ACOLITOACULL ACULLAALBEDRO ALBEDRIOALEGORA ALEGORIAALEL ALELIMBAR AMBARANMALO ANOMALOAPTRIDA APATRIDABALAD BALADIBLGARO BULGAROCAN CAONCLIBE CELIBECNCAVO CONCAVOCPULA CUPULADESCORTS DESCORTESDIMETRO DIAMETRODSCOLO DISCOLOGRIS GRISUHSAR HUSARMANCH MANCHUMOAR MOAREPFANO PIFANOPOLGAMO POLIGAMOPGIL PUGILRAB RABISLICE SILICETCTIL TACTILVOLTIL VOLATIL

Note. WAT5Word Accentuation Test.

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A new word list, sensitive to Argentine Spanish, wasconfected and validated against the Argentine version ofthe WAIS (Wechsler, 1984). The WAT-BA accounted for85% of the variance on the Vocabulary subtest in a sampleof 74 cognitively healthy older adults.

The research reported here follows the logic of both theDel Ser et al. (1997) and Burin et al. (2000) studies and hasthree aims: (1) to test the feasibility of the original WATword list and add new items, if necessary; (2) to validatethe WAT on a sample of older, cognitively healthy LatinAmerican immigrants; and (3) to develop regression equa-tions predicting intelligence scores from WAT scores.

As noted above, one particular difficulty in this regard isthat Spanish versions of the WAIS have been normed inonly a few Spanish-speaking countries, and no existing ver-sion attempts to take into account variations in the Spanishspoken by immigrants to the United States. Thus, for thisresearch, the WAT was validated against the BateraWoodcock-Muoz (BWM-R; Woodcock & Muoz-Sandoval, 1996a). The BWM-R is the Spanish version of

the Woodcock-Johnson Psychoeducational BatteryRevised(WJ-R; Woodcock & Johnson, 1989, 1990) which wasnormed on 6,359 English-speakers, and subsequentlyre-calibrated on 2,000 Spanish-speakers in six countriesand five U.S. states.

Adaptation of the BWM-R took place as follows. Normson the BWM-R were equated with the WJ-R on the basisof item response theory (for a description of this process,see Woodcock & Muoz-Sandoval, 1993). That is, wheresubtest items had identical and nonverbal content (e.g., VisualMatching, Calculation), norms were used from the WJ-R.Where subtests used verbal prompts and required verbalresponses, items were translated from English into Spanish

by native Spanish speakers from various countries who fol-lowed an iterative process of crosschecking until consensuswas reached. Importantly, new items in Spanish were gen-erated and integrated into the item difficulty rankings of theexisting English items.

All of these items (those translated from English plusthe new Spanish items) were then re-calibrated on a Spanish-speaking sample of 2000 individuals from Mexico, PuertoRico, Costa Rica, Spain, Argentina, Peru, and Arizona,California, Florida, New York, and Texas. Items thatshowed some regional bias were then eliminated so thatregional varieties of Spanish would not affect participantperformance.

As with the English Woodcock-Johnson, the BWM-Rcomprises two batteries: cognitive and achievement. Theachievement battery measures formal academic achieve-ment: reading and writing skills, quantitative skills, sci-ence, social studies, and humanities (Woodcock & Muoz-Sandoval, 1996b). The cognitive battery (Woodcock &Muoz-Sandoval, 1996a) is based on the Horn-Catell theoryof intelligence (g) and measures the following domains ofgeneral intelligence by means of seven standard and sevensupplemental subtests: fluid reasoning (Gf), comprehen-sive knowledge (Gc), visual processing (Gv), auditory pro-

cessing (Ga), processing speed (Gs), long-term retrieval(Glr), and short-term retrieval (Gsm). Standard scores aregenerated with M5100 (SD515). In a sample of 17-year-olds, the English Woodcock-Johnson PsychoeducationalBatteryCognitive tests correlated significantly with theWAIS-R Full-Scale IQ ( r5 .64; Woodcock & Mather, 1989,Table 7.9). However, because no Spanish version of theWAIS normed is available in the United States, it is notpossible to establish a similar correlation for Spanish.

Thus, the major strength of the BWM-R for the purposesof this research is that it is the most comprehensive, prop-erly validated and normed intelligence test available for usewith Spanish-speaking immigrants, across the variety ofSpanishes of Latin America and the United States. (For areview of the strengths and weaknesses of the BWM-R foruse with older adults, see Schrauf & Navarro, 2005).

Two separate studies were conducted with the WAT. Inthe first, the WAT and additional test items were tested forfeasibility and identification of the most predictive items.On the basis of the results of that study, the original WAT

was validated against the BWM-R and the Ravens ColoredMatrices.

METHODS

Feasibility Study of The Word Accentuation

Test and Additional Test Items

The goals of the feasibility study were to ensure that cog-nitively healthy Spanish speakers could read out loud theprinted versions of the unaccented words (without neces-

sarily pronouncing them correctly), that words would begenerally unfamiliar but normally distributed across thegroup, and that the test administrator could discriminatecorrect from incorrect pronunciation.

Materials and procedures

To test for the advisability of modifying the original WATword list, 55 new words were generated and added to the 30items of the original WAT.As noted above, words in NART-like tests must not follow rule-governed grapheme-to-phoneme mappings in the language in question. Hence,Spanish words were chosen that were both rare in the cor-

pus and accented. Two Spanish linguists confected a list of100 rare, polysyllabic, accented words in Spanish, with par-ticular attention to Latin American usage. Of these, 55 wordswith a frequency below 3602,000,000 (Alameda & Cuetos,1995) were selected and combined with the30 original wordsof the Del Ser et al. (1997) version of the WAT for a finallist of 85 words. Participants in the feasibility study wereasked to read each word out loud and to rate its pronuncia-bility (Pronouncing this word is: 1 5 very difficult, 5 5very easy) and to rate their familiarity with the word (I haveencountered this word: 15 never, 55 constantly).

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Participants

Twenty (20) older, healthy, community-dwelling Spanish-speaking immigrants from Puerto Rico, Mexico, Cuba, ElSalvador, Honduras, and Guatemala participated in the fea-sibility study. The participants in both this study as well asthe validation study reported next were recruited from news-paper advertisements and senior centers.All signed informed

consent forms were approved by the Institutional ReviewBoard of Northwestern University, and the study was con-ducted in accord with the Helsinki Declaration.

RESULTS

Pronunciability indicated simply that participants could readthe word (whether correctly pronounced or not). The meanpronunciability score across the list was 3.93 (SD 5 .28)where a score of 4 was easy to pronounce. Familiarityindicated a subjective sense of having encountered the wordbefore. Mean familiarity across the list was 2.48 (SD 5.62), where 2 indicated rarely and 3 indicated some-

times. Kolmogorov-Smirnov tests showed a normal distri-bution for bothratings. These results indicate that participantscould read the words out loud but generally found themunfamiliar.

Validation of the Word Accentuation Test

Participants

The desired sample size was determined by a power analy-sis using r2 values between the WAT and intelligence bat-teries in the Spanish samples in Spain (Del Ser et al., 1997)and in Argentina (Burin et al., 2000). This analysis sug-

gested that 80 individuals would provide more than suffi-cient power. Thus, the combined 85 word list was validatedon a sample of 80 older, community-dwelling, Spanish-speaking immigrants (41 female).

Participants had a mean age of 69.44 (SD 5 5.24) andhad immigrated to the United States between the ages of 13and 80 (M 5 38.91, SD 5 17.71) from Colombia (9%),Cuba (5%), Dominican Republic (3%), Ecuador (3%), ElSalvador (1%), Guatemala (5%), Mexico (51%), Peru (6%),Puerto Rico (16%), and Uruguay (1%). These proportionsroughly mirror the distribution of Hispanics by country oforigin in the U.S. Census 2000 (Summary File 4): Mexican(59%), Central and South American (9%), Puerto Rican

(10%), and Cuban (3.5%). All participants were asked tolist all of the languages they knew, rank them by relativedominance, and report age-at-first-exposure. All 80 partici-pants indicated that Spanish was their dominant languageand provided self-reports of proficiency on 7-point scales(1 5 none, 7 5 like a native speaker) for understandingSpanish (M 5 6.89, SD 5 0.36), speaking Spanish (M 56.83, SD 5 0.50), reading Spanish ( M5 6.40, SD5 0.88),and writing Spanish ( M5 6.15, SD5 1.17). . Seventy-fourparticipants indicated that English was their second lan-guage, with six participants listing English as a third lan-

guage (after Kekchi, Quechua, Tarasco, and Lithuanian).They rated their abilities in English as more or less andfunctional across all four modalities: understanding (M53.27, SD51.64), speaking (M5 3.07, SD5 1.46), reading(M 5 3.21, SD51.73), and writing (M5 2.66, SD51.65).

Inclusion criteria required that all formal education becompleted in the (Hispanic) country of origin, and meanyears of education was 8.54 (SD 5 4.20). All participantswere screened for dementia by means of the Mini-MentalState Examination (MMSE; Folstein & McHugh, 1975),adapted for Spanish-speaking individuals (Sano et al., 1997).A SpanishEnglish bilingual researcher ( E.N.) with 6 yearsexperience in dementia-related projects administered theMMSE in Spanish, and only participants scoring 25 or higherwere admitted to the study (M 5 27.83, SD 5 1.40). Allparticipants denied any previous mental illness, psychiatrictreatment, alcoholism, or head injury. All were screened forvision using the MIS Pocket Vision Guide, and those withvision problems wore corrective lenses during testing.

Participants completed the following instruments:

Word Accentuation Test(WAT; Del Ser et al., 1997) PlusAdditional Items. As described above, the 30-item WATwas supplemented with an additional 55 new items. Wordswere printed, without accent marks, on a black and whitepage in 16-point type. Participants were asked to read eachword aloud without attending to whether they knew whatthe word meant or not. The total score is the number ofwords read correctly.

Ravens Colored Progressive Matrices (RCPM; Ravenet al., 2000). Sets A and Ab were administered to each par-ticipant. The RCPM is a test of nonverbal intelligence andcomes in several versions. The colored progressive matri-ces were chosen because they are more suitable than the

other forms for individuals with lower levels of formaleducation.

Folstein Mini-Mental Examination (MMSE; Folsteinet al., 1975). Participants completed a Spanish translation(Sano et al., 1997) in which the serial-sevens item wasreplaced by spelling the word mundo (world) back-ward (Marshall et al., 1997) and no ifs, ands, or buts wasreplaced by ms vale tarde que nunca (better late thannever; Mulgrew et al., 1999).

Batera Woodcock-MuozPruebas de Habilidad Cogni-

tiva Revisada (BWM-R; Woodcock & Muoz-Sandoval,1996a; for reviews, see Kaufman, 1990; Lezak, 1995). Par-ticipants completed seven standard and seven supplemental

subtests of the BWM-R, which combine in pairs to measurevarious subcomponents of intelligence. Because the intentin assessing premorbid intelligence is to assess crystallizedversus fluid intelligence, Comprehensive Knowledge waschosen as the most appropriate measure against which tovalidate the WAT. Comprehensive Knowledge in theBWM-R is a composite score resulting from two subtests:Picture Vocabulary and Oral Vocabulary. Picture Vocabu-lary measures the ability to name familiar and unfamiliarpictured objects. Oral Vocabulary measures knowledge ofthe meaning of words by requiring testees to generate syn-



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onyms and antonyms of words. The choice of Comprehen-sive Knowledge is consistent with the prior validations ofthe WAT developed in Spain (using Vocabulary and PictureCompletion Subtests of the WAIS; Del Ser et al., 1997) andin Argentina (using the Vocabulary subtest of the WAIS;Burin et al., 2000).

All of the instruments were administered in Spanish by abilingual research assistant. Participant performance on theWord Accentuation Test, Ravens Matrices, and subtests ofthe Batera Woodcock-Muoz was audiotaped, scored bythe bilingual research assistant, and reviewed in confer-ence. (A detailed account of these procedures are found inSchrauf & Navarro, 2005.)

RESULTS

Item analyses were conducted for the combined 85-itemlist. Items were accepted into the final list if their itemtotaltetrachoric correlation was greater than .40 and they corre-lated significantly (p , .01) with both the Comprehensive

Knowledge subscale of the BWM-R and Ravens Matrices.This created a final new list of 31 items, 12 of which wereshared with the original WAT list. These 31 items accountedfor 73% of the Comprehensive Knowledge subscale vari-ance (r2 5 .73, adjusted r2 5 .56, S.E. 5 5.95, p , .001)and 58% of the Ravens Matrices variance (r25 .58, adjustedr2 5 .30, S.E.5 3.30, p , .01). On the other hand, the 30items of the original WAT accounted for 77% of the Com-prehensive Knowledge subscale variance ( r25 .77, adjustedr2 5 .64, S.E. 5 5.40, p , .001) and 58% of the RavensMatrices variance (r25 .58, adjusted r25 .32, S.E.5 3.27,p , .01).

Construct and convergent validity were established by

means of Pearson correlations between the original WATword list of 30 words, the revised WAT word list of 31words constructed for this research, Ravens Matrices, andthe subtests of the BWM-R (Table 2). First, all other sub-components of intelligence correlated significantly with themeasure of crystallized intelligence (Comprehensive Knowl-edge). Second, the WAT and the revised WAT word listcorrelated highly with Comprehensive Knowledge, whichin turn is based on Picture Vocabulary (confrontation nam-ing) and Oral Vocabulary (synonyms and antonyms) sub-tests of the BWM-R. Third, the WAT and revised listcorrelated equivalently with the BWM-R; therefore, a newor revised list is not necessary. All subsequent analyses

concern only the original WAT.No significant gender effects were found. A comparison

of WAT scores of men and women showed no significantdifference between the groups (t(78)5 1.12). Age was notsignificantly correlated with WAT scores (2.13), perhapsreflecting that the WAT score is an indicator of crystallizedintelligence, which typically (in the aggregate) is fairlystable through the eighth decade of life (Park, 2000). Con-sistent with this, the correlation between age and Compre-hensive Knowledge (2.04) was not significant either.Education and scores on the WAT were not significantly

correlated (.20). This finding may reflect the restricted edu-cation range in the sample (M 5 8.54, SD 5 4.20).

Bilingual status did not affect performance on any of themeasures. As indicated above, 74 of 80 participants indi-cated that English was their second language, and the remain-ing 6 listed English as their third language. Hence, to testfor the effects of bilingualism on the intelligence measures(Comprehensive Knowledge, Ravens Matrices, and theWAT), we created low and high English proficiency groups.Because the median of self-reported ability to speak English

(median 5 3) was also the mode (21), we chose not toperform a median split by ability to speak English, but ratherby age-at-first exposure (median5 20). This strategy effec-tively created a higher proficiency group whose meanself-reported ability to speak English was 3.49 (SD51.55)anda lower proficiency group whose mean was 2.68 (SD51.27). Subsequent t tests comparing these groups on Com-prehensive Knowledge (t(78) 5 1.25), Ravens Matrices(t(78)51.17), and the WAT (t5.59) showed no significantdifferences between proficiency groups. Finally, an analy-sis of the effect of country-of-origin on the WAT suggestslittle influence, although only Mexico and Puerto Rico pro-vide enough numbers in this sample (41 and 14, respec-

tively) to test for these effects. A ttest shows no significantdifferences between these two countries on WAT perfor-mance (t(52) 5 .31).

As an additional indication of validity, a hierarchicalregression was performed entering BWM-R Comprehen-sive Knowledge scores, years of education, and age as pre-dictors of WAT scores (Table 3; adjusted r25 .64, F(2,77)571.37, p , .001). Comprehensive Knowledge was a strongpredictor of WAT scores ~b 5 .78, p , .001), whereas ageemerged as a weak predictor WAT scores ~ b 52.17, p ,.001), accounting for only an additional 3% of the variance

Table 2. Correlations of the WAT with the BWM-R,Ravens Colored Matrices, and Years of Education

WATTrialWAT

Comprehensiveknowledge

BWM-RComprehensive Knowledge .79 .79Long-Term Retrieval .52 .49 .61

Short-Term Retrieval .43 .44 .54Processing Speed .46 .44 .57 Auditory Processing .37 .36 .42Visual Processing .44 .45 .60Fluid Reasoning .38 .40 .58

Ravens .53 .57 .62Years of Education .20 .21 .48Age 2.13 2.11 2.04

Note. Significant correlations are indicated in bold and italicized. TrialWAT refers to the revised list of 31 words selected by performing itemanalyses on a combined list of the 30 words of the original WAT plus 55new words (explanation given in text).WAT 5 Word Accentuation Test; BWM-R 5 Batera Woodcock-MuozRevisada.



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in the WAT scores. Education did not enter as a significantpredictor. This finding provides additional evidence thatrelying on years of education alone as an indicator of pre-morbid intelligence can be problematic (Manly et al., 2003).

Linear regression equations were constructed to predictboth BWM-R Comprehensive Knowledge scores and scoreson Ravens Matrices as follows:

BWM-R Full Cognitive (predicted)5 1.109 WAT1 72.461

Raven (predicted)5 20.805 WAT1 .328

It is important to note that regression equations based onreading tests typically show regression-to-the-mean effects.That is, deviations between predicted and observed scoresare greatest for individuals with below-average and above-average scores (Basso et al., 2000; Graves et al., 1999;Griffin et al., 2002; Veiel & Koopman, 2001). To test forthese effects, the standardized Comprehensive Knowledge

scores (M5 100, SD5 15) were used to classify individu-als into three ability groups: below average (89 and below),average (90109), and above average (110 and over). Table 4(first row) shows the number of subjects, means, standarddeviations, and ranges for the Comprehensive Knowledgeand WAT scores for each group. Agreement between theWAT predicted scores and the BWM-R scores was obtainedin 67 of 80 cases (84%). Within groups, cases were cor-rectly classified as follows: below average, 21 of 27 (77%);average, 46 of 51 (90%); and above average, 0 of 2 (0%).

DISCUSSION

The Alzheimers Association estimates that the prevalenceof dementia among U.S. Hispanics could increase sixfoldby the year 2050 (Alzheimers Association, 2004). Giventhat many Hispanics have limited English proficiency, neuro-cognitive assessment must rely increasingly on instrumentscarefully adapted and normed for a Spanish-speaking pop-ulation (Artioli I Fortuny et al., 2005). As discussed above,the existing Spanish versions of the WAT (Del Ser et al.,1997; Burin et al., 2000) are based on versions of the WAISnormed in Spain and Argentina. However, Spanish speak-ers in the United States come from many different Spanish-

speaking countries and0or have lived in Spanish speakingregions of the United States for many generations. Hence,an appropriate revalidation of the WAT for use in the UnitedStates should rely for criterion validity on a cognitive bat-

tery whose norming sample reflects this diversity. For thesereasons, we chose the Batera Woodcock-Muoz-Revisada(BWM-R), which was normed in six Spanish-speaking coun-tries and five U.S. states where Spanish is more commonlyspoken.

In adapting the WAT to the U.S. context, we took thefurther step of having Spanish phonologists generate anadditional 55 rare, accented words to combine with the 30words of the original WAT. This was done to provide alter-natives to the original list in case any of those words (selectedfor Spain) provided insufficient discriminatory power for aWAT adapted for Spanish-speakers in the United States.However, analyses indicated that these additional items did

not improve the correlations of the original list with sub-tests of theWoodcock-Muoz or Ravens Matrices, and were,therefore, unnecessary. Thus, the original list of 30 wordsaccounts for 77% of the variance in Comprehensive Knowl-edge scores from the Batera Woodcock-Muoz and 58% ofthe variance on Ravens Colored Progressive Matrices.Regression equations are provided that predict both scoresfrom performance on the WAT.

These results are comparable, perhaps superior, to simi-lar results among English speakers for tests of premorbidintelligence predicting scores on the WAIS. Griffin et al.

Table 3. Hierarchical regression of BWM-R comprehensiveknowledge scores and age as predictors of WAT scores

Variables B b value r value Dr

BWM-R Comp. Knowledge .55 .78 .79 .62*Age 2.20 2.17 .81 .03**Education .10 .06 n.s. n.s.

Note. BWM-R5Batera Woodcock-MuozRevisada; WAT5WordAccen-tuation Test; n.s. 5 not significant.*p , .001; **p , .01.

Table 4. Number and percentages of cases correctly classifiedby instruments predicting intelligence scores on cognitivebatteriesa

Belowaverage Average

Aboveaverage

WAT (Spanish)No. correct classifications 21027 46051 002

% correct classifications 77% 90% 0%Barona (English)b

No. correct classifications 8025 18028 5011% correct classifications 32% 64% 45%

NAART (English)c


OPIE (English)d


WRAT (English)e


Note. WAT5Word Accentuation Test; NAART5NorthAmerican NationalAdult Reading Test; OPIE 5Oklahoma Premorbid Intelligence Estimate;WRAT5Wide Range Achievement Test.aClassification data for English instruments from Griffin et al. (2002).bBarona et al. (1984).cBlair and Spreen (1989).dScott et al. (1997).eWilkinson (1993).



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(2002) examined correct classifications of 64 cases usingthe Barona demographic equations (Barona et al., 1984),the North American National Adult Reading Test (NAART;Blair & Spreen, 1989), the Oklahoma Premorbid Intelli-gence Estimate (OPIE; Scott et al., 1997), and Wide RangeAchievement Test (WRAT; Wilkinson, 1993). Table 4 com-pares these classifications with those made using the WATto predict scores on the BWM-R. In sum, the WAT is sim-ilar to other reading tests in successfully predicting scoresin average ranges on cognitive batteries but tends to under-estimate higher than average scores and over-estimate lowerthan average scores (Johnstone et al., 1996). The WATappears weaker at predicting above average scores, althougha sample with more numerous, highly educated participantswould be necessary to confirm this result.

That the available methods for assessing premoribid intel-ligence generally show regression-to-the-mean effects isproblematic for clinical practice and poses additional chal-lenges for psychometric research. Obviously, clinicians mustinterpret the results in the context of other available data,

both from other instruments used in neuropsychologicalassessment as well as patient background and history. Forthe existing English instruments, other steps have been pro-posed. For instance, based on the data shown in Table 4,Griffin et al. (2002) have suggested that different instru-ments show better predictive ability for different ranges ofintelligence. Specifically, the OPIE which combines demo-graphic equations predicting WAIS scores with current per-formance on certain WAIS subtests, may be a more preciseindicator of premorbid intelligence for individuals in theabove average range. The WRAT-3, a reading test, is moreprecise for individuals in the below average range, whereasall three (OPIE, WRAT-3, and NAART) work well for indi-

viduals in the average range. Again, this advice is limited topatients who can be tested in English, but it suggests futureavenues for instrument development in Spanish. For instance,demographic equations (similar to the English versions pre-dicting scores on the WAIS; e.g., Barona et al., 1984) couldbe formulated based on information from the BWM-R stan-dardization sample and then combined with BWM-R sub-test performance to create an OPIE-like instrument. Anotherpossible response to regression-to-the-mean effects has beenmade by Veiel and Koopman (2001) who propose statisticalcorrections for regression equations predicting WAIS scores(Barona et al., 1984; Blair & Spreen, 1989; Krull et al.,1995). Whether or not these equations are effective with

WAT scores validated on the BWM-R is a topic of futureinvestigation.

While a principal virtue of this study is that it takes advan-tage of the cultural and linguistic diversity available in theBWM-R standardization sample, a limitation of the study isthe smaller numbers of individuals in our validation samplefrom South and CentralAmerican countries other than Mex-ico and Puerto Rico. Although no significant differenceswere found on WAT performance by Puerto Ricans andMexicans, additional data are necessary to test this relationfor the other countries-of-origin in the sample.

Finally, in work with clinical populations, we are initiat-ing a cross-validation of the WAT on Spanish-speaking con-trols and cognitively impaired individuals. As with thevalidation of the WAT in Spain (Del Ser et al., 1997), weexpect to see significant differences between controls andearly to mid-stage dementia patients in performance on cog-nitive measures (e.g., BWM-R Picture Vocabulary andRavens Matrices) but no differences on the WAT.

In summary, this study demonstrates the logic and prac-tice of adapting a NART-like reading test for the assess-ment of premorbid intelligence to the Spanish context ofthe United States. Specifically, the study demonstrates theconcurrent validity of the existing Spanish Word Accen-tuation Test (WAT; Del Ser et al., 1997) against theBatera Woodcock-Muoz-Revisada (Woodcock & Muoz-Sandoval, 1996a). For clinicians working with Spanish-speaking populations in the United States, the WAT providesan indicator of premorbid intelligence as part of more com-prehensive neuropsychological assessment and patienthistory.

ACKNOWLEDGMENTS

This research was supported by grants from the AlzheimersAsso-ciation (NIRG 02-3674) and, in part, from the National Instituteon Aging ( NIA P30 AG13854) to the Cognitive NeurologyAlz-heimers Disease Center of Northwestern University.

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