FAS and Animal Naming

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Normative data stratified by three levels of age (16–59, 60–79, and 80–95 years) and three levels of education (0–8, 9–12, and 13–21 years) are presented for ...
Archives of Clinical Neuropsychology, Vol. 14, No. 2, pp. 167–177, 1999 Copyright © 1999 National Academy of Neuropsychology Printed in the USA. All rights reserved. 0887-6177/99 $–see front matter

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Normative Data Stratified by Age and Education for Two Measures of Verbal Fluency: FAS and Animal Naming Tom N. Tombaugh Carleton University

Jean Kozak Sisters of Charity Health Services

Laura Rees Carleton University

Normative data stratified by three levels of age (16–59, 60–79, and 80–95 years) and three levels of education (0–8, 9–12, and 13–21 years) are presented for phonemic verbal fluency (FAS) and categorical verbal fluency (Animal Naming). The normative sample, aged 16 to 95 years, consisted of 1,300 cognitively intact individuals who resided in the community. Years of education ranged from 0 to 21. The total number of words in 1 minute for each of the letters F, A, and S was correlated r 5 .52 with the number of animal names generated in 1 minute. Regression analyses showed that FAS was more sensitive to the effects of education (18.6% of the variance) than age (11.0% of the variance). The opposite relationship occurred for Animal Naming, where age accounted for 23.4% of the variance and education accounted only for 13.6%. Gender accounted for less than 1% of variance for FAS and Animal Naming. The clinical utility of these norms is discussed. © 1999 National Academy of Neuropsychology. Published by Elsevier Science Ltd

Phonemic and semantic verbal fluency, as measured by an individual’s ability to generate words beginning with a specific letter (e.g., FAS and CFL) and semantic category (e.g., animals), have played a prominent role in neuropsychological research. Verbal fluency has been demonstrated to be sensitive to lesions in the frontal lobe, temporal lobe, and caudate nucleus (Benton, 1968; Butters, Granholm, Salmon, Grant, & Wolfe, 1987; Miceli, Caltagirone, Gainotti, Masullo, & Silveri, 1981; Milner, 1964; Perret, 1974; Ramier & Hecaen, 1970); Alzheimer’s disease (Appell, Kertesz, & Fisman, 1982; Bayles &

Address correspondence to: Tom N. Tombaugh, Department of Psychology, Carleton University, Ottawa Ontario, Canada K1S 5B6.



T. N. Tombaugh, J. Kozak, and L. Rees

Tomoeda, 1983; Butters et al., 1987; Chertkow & Bub, 1990; Cummings, Benson, Hill, & Read, 1985; Hodges, Salmon, & Butters, 1992; Martin & Fedio, 1983; Ober, Dronkers, Koss, Delis, & Friedland, 1986; Pachana, Boone, Miller, Cummings, & Berman, 1996; Rosen, 1980); Huntington’s disease (Butters, Sax, Montgomery, & Tarlow, 1978; Butters et al., 1987); amnesia (Butters et al., 1987; Weingartner, Grafman, Boutelle, Kaye, & Martin, 1983), and traumatic brain injury (Raskin & Rearick, 1996). Current time-limited, verbal fluency tests can be traced to the Thurstone’s Word Fluency Test, which formed part of the Primary Mental Abilities Test (Thurstone, 1938; Thurstone & Thurstone, 1949). This test required individuals to write words beginning with a specific letter over a relatively long period of time (e.g., 5 minutes to write all possible words that began with the letter S). Benton and colleagues are generally credited with developing a verbal counterpart for Thurstone’s procedure (Bechtoldt, Benton, & Fogel, 1962; Benton, 1968; Fogel, 1962). The letters FAS were used in these experiments with 1 minute of responding allowed for each letter. The first attempt to develop norms for letter fluency was by Borkowski, Benton, and Spreen (1967). All letters of the alphabet except X and Z were normed using 1-minute test intervals with 66 maternity patients. The letters were divided into three difficulty levels: hard (Q, J, V, Y, K, U); moderate (I, O, N, E, G, L, R); and easy (H, D, M, W, A, B F, P, T, C, S). Eventually, this lead to the verbal fluency test used in the Multilingual Aphasia Examination (MAE; Benton & Hamsher, 1976; Benton, Hamsher, & Sivan, 1994). Two parallel sets of letter triads (CFL and PRW) were used rather than FAS. However, according to Ruff, Light, Parker, and Levin (1996), the name of the test was changed to Controlled Oral Word Association Test (COWA or COWAT) to avoid confusing the phrase “word fluency” with the “fluent/nonfluent” dimension of aphasia. The letters FAS have continued to be used as a measure of verbal fluency in the Neurosensory Center Comprehensive Examination for Aphasia (NCCEA; Benton, 1967; Spreen & Benton, 1969, 1977). The other popular procedure for assessing verbal fluency is semantic fluency, where individuals are asked to generate names from a specified category (e.g., animals, fruits, cities). For example, the Western Aphasia Battery (WAB; Kertesz, 1982) and Boston Diagnostic Aphasia Examination (BDAE; Goodglass & Kaplan, 1983) uses Animal Naming as its word fluency test, the Mattis Dementia Rating Scale (Mattis, 1988) uses the Supermarket Test, where the person names items found in a supermarket, and the Set Test (Issacs & Kennie, 1973) uses color, animals, towns, and fruits. A review of the literature shows that the category of “animals” is most frequently employed. Recently, comparison of performance on phonemic and semantic measures of verbal fluency has been used to investigate language deficits in Alzheimer’s patients, with mixed results (for reviews see Hart, 1988; Lezak, 1995; Zec, 1993). In spite of the widespread use and clinical utility of verbal fluency tests, few norms are available across the entire adult age range. Those that are available are for the COWAT. This is largely because two recent studies have produced a reasonably comprehensive set of norms (Ivnik, Malec, & Smith, 1996; Ruff et al., 1996). Unfortunately, a similar state of affairs does not exist for FAS. The original normative data for FAS in NCCEA were from a rural sample that was poorly educated with lower levels of intelligence (Spreen & Strauss, 1991). The normative data produced subsequently suffer from restricted age samples or limited number of individuals (Bolla, Lindgren, Bonaccorsy, & Bleecker, 1990; Cauthen, 1978; Geiser & Vanderploeg, 1993; Kozora & Cullum, 1995; Read, 1987; Yeudall, Fromm, Reddon, & Stefanyk, 1986). Norms for animal naming with an adequate range for age and education are lacking also. Consequently, the purpose of the present study is to provide age (16–95 years) and education (0–21 years) appropriate normative data for FAS and Animal Naming.

Verbal Fluency


METHOD Participants and Materials The normative sample consisted of 1,300 individuals who participated in two different experiments. The first experiment investigated the effects of aging on the acquisition and retention of visual and verbal information with 895 community-dwelling volunteers (Hubley, 1995; McIntyre, 1996). Participants were recruited through booths at shopping centers, social organizations, places of employment, psychology classes, and by wordof-mouth. They did not receive any financial remuneration for participating. A selfreported history of medical and psychiatric problems, including a list of all currently prescribed medications, was obtained from each participant. Any person with a known history of neurological disease, psychiatric illness, head injury, or stroke was excluded. All participants were living independently in the community, and ranged in age from 16 to 85 years (M 5 52.3, SD 5 18.1). The average education level varied from 4 to 21 years (M 5 12.9, SD 5 2.6). The male to female ratio was 397 to 498. All persons scored higher than 23 on the Mini-Mental State Examination (MMSE; Folstein, Folstein, & McHugh, 1975) and lower than 12 on the Geriatric Depression Scale (GDS; Brink et al., 1982). English was the first language for all individuals. Scores from the Vocabulary subtest of the Wechsler Adult Intelligence Test-Revised (WAIS-R; Wechsler, 1981) were available for a subset of 364 participants. The remaining 405 participants represent a subset of individuals drawn from the Canadian Study of Health and Aging (CSHA) (Canadian Study of Health and Aging Working Group, 1994). All participants received a consensus diagnosis of “no cognitive impairment” regardless of 3MS scores (n 5 283 for 3MS .77; n 5 122 for 3MS ,78) by physicians and clinical neuropsychologists on the basis of history, clinical and neurological examination, and an extensive battery of neuropsychological tests (see Tuokko, Kristjannson, & Miller, 1995; Tuokko & Woodward, 1996 for additional details about neuropsychological protocol and results). Ages ranged from 65 to 95 years (M 5 79.2, SD 5 6.5). Number of years of education varied from 0 to 21 years (M 5 10.5, SD 5 3.8). The male to female ratio was 162 to 243. All persons stated that English was their first language.

Procedure The total number of words generated in 1 minute for the letters F, A, and S (phonemic fluency) was obtained from all 1,300 participants. The number of words generated for each individual letter was available only from the 895 participants from the first experiment. The instructions were identical to those used by Spreen and Benton (1977) and described in detail by Spreen and Strauss (1991). Participants were instructed that proper nouns and multiple words using the same stem with a different suffix (e.g., friend, friends, friendly) were not acceptable. The ages for the FAS sample ranged from 16 to 95 years (M 5 60.7, SD 5 19.9). Years of education ranged from 0 to 21 (M 5 12.1, SD 5 3.2). The male to female ratio was 559 to 741. The number of animal names generated in 1 minute (semantic fluency) was obtained from a subset of 735 individuals (331 from the first study and 404 from the second study). Instructions followed those of Rosen (1980) and required individuals to say “the names of as many animals that they could think of” in a 1-minute period. The ages for the Animal Naming sample ranged from 16 to 95 years (M 5 67.0, SD 5 19.8). Years of education ranged from 0 to 21 (M 5 11.4, SD 5 3.4). The male to female ratio was 310 to 425.


T. N. Tombaugh, J. Kozak, and L. Rees TABLE 1 Means (M) and Standard Deviations (SD) for Number of Words Generated to the letters F, A, and S for Education, Age, and Gender FAS Category

Education (years) 0–8 9–12 13–16 17–21 Age (years) 16–19 20–29 30–39 40–49 50–59 60–69 70–79 80–89 90–95 Gender Male Female Total




163 664 392 81

24.9 36.7 42.6 43.9

(10.7) (12.2) (11.6) (12.3)

19 106 132 121 144 220 334 200 24

39.3 41.2 43.1 43.5 42.1 38.5 34.8 28.9 28.2

(12.0) (09.2) (11.4) (12.2) (11.1) (13.7) (12.8) (11.7) (11.0)

559 741 1300

37.0 37.8 37.5

(13.0) (13.1) (13.1)

RESULTS Phonemic Fluency (FAS) For descriptive purposes, years of education was divided into four groups, and ages were divided into nine age ranges. Table 1 shows the mean number of words generated for each of these two variables as well as for gender. Inspection of Table 1 shows that FAS scores tended to increase with increasing education, with the least amount of change occurring between the last two categories (13–16 years and 17–21 years). FAS scores decreased with advancing age with the least amount of change occurring from ages 16 to 59 years. Females generated slightly more words than males. Simultaneous regression analyses further explored the effects of these three variables. Education accounted for 18.6% of the variance, while age accounted for only 11.0% Gender was not significant and therefore did not enter the equation. Comparable values were obtained from a subset of individuals who were administered both verbal fluency tests. Education accounted for 21.7% and age accounted for 11.8%. Vocabulary scores (WAIS-R) correlated r 5 .25 (p , .001) with overall FAS scores. On the basis of these analyses and visual inspection of the data, it was decided to stratify the norms on the basis of age (16–59, 60–79, and 80–95 years) and years of education (0–8, 9–12, and 13–21). Normative data for total FAS scores are provided in Table 2. Table 2 shows that within each age level FAS scores increase with increased education. When education is used as the major variable of interest, FAS scores decrease within any given educational category as age increased. An analysis of variance (ANOVA) appropriate for a 3 (education) 3 3 (age) factorial design showed that both age and education were statistically significant with a small but statistically significant interaction, Age: F(2, 1291) 5 50.6, p , .001; Education: F(2, 1291) 5 87.2, p , .001; Age 3 Education: F(4, 1291) 5 2.6, p , .05.

48 45 42 39 36 35 34 30 27 38.5 (12.0)

56 50 47 43 40 38 35 32 28 40.5 (10.7)

9–12 (n 5 268)

61 55 51 49 45 42 38 35 30 44.7 (11.2)

13–21 (n 5 242)

39 36 31 27 25 22 20 17 13 25.3 (11.1)

0–8 (n 5 76)

54 47 43 39 35 32 28 24 21 35.6 (12.5)

9–12 (n 5 292)

Education (Years)

Education (Years)

Note. M 5 mean; SD 5 standard deviation.

Percentile Score 90 80 70 60 50 40 30 20 10 M (SD)

0–8 (n 5 12)

Age 60–79 Years

Age 16–59 Years

59 53 49 45 41 38 36 34 27 42.0 (12.1)

13–21 (n 5 185)

33 29 26 24 22 21 19 17 13 22.4 (8.2)

0–8 (n 5 75)

42 38 34 31 29 27 24 22 18 29.8 (11.4)

9–12 (n 5 102)

Education (Years)

Age 80–95 Years

TABLE 2 Norms for FAS Stratified for Age (16–59, 60–79, and 80–95 Years) and Years of Education (0–8, 9–12, and 13–21)

56 47 43 39 36 33 30 28 23 37.0 (11.2)

13–21 (n 5 46)

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T. N. Tombaugh, J. Kozak, and L. Rees

Two measures of reliability were obtained. The first measure assessed the degree of internal consistency that existed among the three letters. A coefficient alpha (Cronbach alpha) was computed using the total number of words generated for each letter as individual items (Letter F: M 5 14.4, SD 5 4.5; Letter A: M 5 11.9, SD 5 4.4; Letter S: M 5 15.0, SD 5 4.7). The coefficient alpha of r 5 .83 was sufficiently high to insure high item homogeneity even though t-tests showed the number of words was significantly different (a 5 .001) among the three letters (F vs. A: t(1,893) 5 19.0; F vs. S: t(1,893) 5 5.2; A vs. S: t(1,893) 5 23.0). The second measure of reliability was obtained from 38 older participants who had taken the FAS on two occasions separated by 5.6 years (SD 5 .76). The mean ages at the first and second administration were 65.6 years (SD 5 9.7) and 71.2 years (SD 5 9.9), respectively. The small decrease in scores that occurred for the second administration (38.7 vs. 36.3) was not statistically significant (t 5 1.97, p . .05). A correlational analysis showed the test-retest reliability was within acceptable limits (r 5 .74, p , .001). Semantic Fluency (Animal Naming) Table 3 shows the number of animal names generated in 1 minute for each of four levels of education, nine age ranges, and gender. Inspection of the table shows that the number of animals named increased as years of education increased. The greatest increase occurred between 0 to 8 and 9 to 12 years, and between 9 to 12 and 13 to 16 years. The opposite trend occurred for age, where the number of animals named remains relatively constant until age 60, when it began to decrease with advancing age. Males generated more animals names than females. When the effects of age, education, and gender on animal naming were analyzed by regression analayses, age accounted for 23.4% of variance, education for 13.6%, and gender for less than 1%. It should be noted that all

TABLE 3 Means (M) and Standard Deviations (SD) Numbers of Animals Named in 1 Minute for Education, Age, and Gender Animal Naming Category

Education (years) 0–8 9–12 13–16 17–21 Age (years) 16–19 20–29 30–39 40–49 50–59 60–69 70–79 80–89 90–95 Gender Male Female Total




140 377 173 44

13.9 16.7 19.0 19.5

(3.9) (4.6) (5.2) (5.2)

19 41 43 45 43 92 228 200 24

21.5 19.9 21.5 20.7 20.1 17.6 16.1 14.3 13.0

(4.4) (5.0) (5.5) (4.2) (4.9) (4.7) (4.0) (3.9) (3.8)

310 425 735

17.4 16.5 16.9

(5.1) (5.0) (5.0)

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these individuals also had been administered the FAS. Vocabulary scores (WAIS-R) correlated r 5 .17 (p , .001) with total number of animals named. Table 4 presents normative data stratified using the same three levels of education and age as employed previously with FAS scores. As with FAS, number of animals named within a specific age level progressively increased with increasing amounts of education, and scores within any given educational level progressively decreased with increasing age. An ANOVA appropriate for a 3 (education) 3 3 (age) factorial design showed that both age and education were statistically significant, Age: F(2, 726) 5 88.1, p , .001; Education: F(2, 726) 5 28.1, p , .001; Age 3 Education: F(4, 726) 5 .65, p . .05). Finally, a correlational analysis showed that number of animals named correlated r 5 .52 (p , .01) with FAS scores. Correlations of the number of animals named with individual letters were as follows: Letter F 5 .31, Letter A 5 .36, and Letter S 5 .39.

DISCUSSION The results from the present study provide norms for two verbal fluency tests that have enjoyed widespread experimental and clinical usage but have not been adequately normed. Previous norms for FAS and animal naming have used a restricted age or educational range (Bolla et al., 1990; Geiser & Vanderploeg, 1993; Read, 1987; Selnes et al., 1991; Spreen & Benton, 1977; Yeudall et al., 1986). By recruiting individuals having a wide range of ages (16–95 years) and years of education (0–21), the present set of norms represent a substantial improvement over those previously available. Evidence from a variety of sources shows that verbal fluency measures are sensitive to the effect of years of education and age, but are relatively insensitive to gender (Bolla et al., 1990; Borod, Goodglass, & Kaplan, 1980; Geiser & Vanderploeg, 1993; Hamsher & Benton, 1978; Ivnik et al., 1996; Ruff et al., 1996; Sarno, Bounaguro, & Levita, 1985). The present study confirms and extends these findings by showing that measures of phonemic and semantic verbal fluency are differentially sensitive to age and education. Regression analyses performed on scores from individuals who had completed both verbal fluency tests demonstrated that for FAS education accounted for more variance than

TABLE 4 Norms for Animal Stratified for Age (16–59, 60–79, and 80–95 Years) and Years of Education (0–8, 9–12, and 13–21) Age 16–59 Years

Age 60–79 Years

Age 80–95 Years

Education (Years)

Education (Years)

Education (Years)

0–8 9–12 13–21 0–8 9–12 13–21 0–8 9–12 13–21 (n 5 4) (n 5 109) (n 5 78) (n 5 61) (n 5 165) (n 5 94) (n 5 75) (n 5 103) (n 5 46)

Percentile Score 90 75 50 25 10 M (SD)

26 23 20 17 15 19.8 (4.2)

30 25 23 18 16 21.9 (5.4)

Note. M 5 mean; SD 5 standard deviation.

20 17 14 12 11 14.4 (3.4)

22 19 17 14 12 16.4 (4.3)

25 22 19 16 13 18.2 (4.2)

18 16 13 11 9 13.1 (3.8)

19 17 14 12 11 13.9 (3.4)

24 20 16 14 12 16.3 (4.3)


T. N. Tombaugh, J. Kozak, and L. Rees

age (education 5 21.7% vs. age 5 11.8%) while for Animal Naming the opposite relationship existed (education 5 13.6% vs. age 5 23.4%). In both analyses, gender was found to account for less than 1% of the variance. Consequently, the current set of norms were stratified over age (16–59, 60–79, and 80–95 years) and years of education (0–8, 9–12, and 13–21) and percentile equivalents were determined. The results from our sample may differ from other normative data based exclusively on the CSHA sample, but contained only participants with 3MS scores greater than 77 (e.g., Tuokko & Woodward, 1996). We felt that using only the final consensus diagnosis would produce a more representative sample than combining it with a criterion 3MS score. This decision was based on two factors. First, the final consensus diagnosis was based on an extensive series of clinical, neurologic, and neuropsychologic tests. Consequently, we felt that using scores from a brief mental status examination was unwarranted and unnecessary. Second, results from prior research (Tombaugh, McDowell, Kristjansson, & Hubley, 1996) demonstrated that scores on the 3MS are sensitive to the effects of age and education, and using a 3MS criterion score might restrict the representativeness of our sample. Subsequent data analyses on the CSHA sample confirmed this suspicion. Participants scoring below a 3MS score of 78 were significantly (F 1,403), p , .01) older (81.8 vs. 79.8 years), had fewer years of education (8.7 vs. 11.9) and scored lower on FAS (23.8 vs. 33.4) and Animal Naming (11.5 vs. 12.9). The major clinical utility of these norms is that they will increase the ability of neuropsychologists to determine more precisely the degree to which verbal fluency is impaired in patients of varying ages and educational level. Moreover, the provision of norms for both phonemic and semantic fluency offers the additional advantage of allowing the neuropsychologist to determine if one type of verbal fluency is affected more than the other. Such a determination has been shown to be useful in making differential diagnoses. For example, Steenhuis and Ostbye (1995) reported that phonemic fluency had greater clinical utility in identifying cognitive loss in nondemented individuals and the generation of animal names contributed more to the diagnosis of dementia. Consistent with this are reports that semantic fluency declines more in Alzheimer’s patients than does letter fluency (Crossley, D’Arcy, & Rawson, 1997; Kozora & Cullum, 1995), and the inclusion of an animal naming test significantly increases the sensitivity of the MMSE to identify Alzheimer’s disease (Tombaugh et al., 1996). Finally, Zec (1993), in his review of the literature on Alzheimer’s disease (AD), concluded that semantic fluency “may be considerably more useful than phonemic word fluency in the differential diagnosis of patients with AD at all stages of dementia from normal elderly persons” (p. 43). Two major factors should be kept in mind when using the current norms. First, the norms are applicable only when the letters F, A, and S or the category of animals are used. A large degree of variety exists among the number of names generated to different letters of the alphabet. For example, in the present study, significant differences were found in number of words generated with the letters F, A, and S. This is consistent with Thorndike-Lorge’s frequency count (Thorndike & Lorge, 1944); with the data contained in the original report by Borkowski et al. (1967); and with results from other research using cognitively intact and cognitively impaired persons (Hart, Smith, & Swash, 1988; Yeudall et al., 1986). Similarly, different types of semantic categories yield different number of exemplars (Hart, Smith, & Swash, 1988; Hodges et al., 1992; Monsch et al., 1992). The lack of comparability in number of exemplars between different types of fluency tasks provides ample evidence that the present norms should be used exclusively with the letters F, A, and S and the semantic category of animals. Ruff et al. (1996), in their normative article on Benton’s Controlled Oral Word Association Test, expressed a similar caution that “despite the fact that the FAS and COWA (e.g., CFL or PRW) are

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two versions of the same procedures, the raw scores on the two versions are not comparable” (p. 337). Second, the current norms are only applicable when the person is fluent in English. The current norms should not be used when the exemplars to the same letters or animals category were generated in a different language. This is clearly illustrated by Steenhuis and Ostbye (1995), who reported a significant difference in verbal fluency between French and English for FAS (English 5 22.7, French 5 15.01) and Animal Naming (English 5 12.3, French 5 10.9) in an older population that contained individuals diagnosed as demented, cognitively impaired, and cognitively intact.

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