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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Appl Neuropsychol. Author manuscript; available in PMC May 3, 2011.
Published in final edited form as:
PMCID: PMC3085831

FAS and CFL Forms of Verbal Fluency Differ in Difficulty: A Meta-analytic Study

Danielle Barry
University of Connecticut Health Center Farmington, CT, USA


The Controlled Oral Word Association (COWA) Test is a brief and sensitive measure of executive cognitive dysfunction. There are two commonly used forms of the test, one using the letters F, A, and S, and the other using C, F, and L. This study examines the relative difficulty of the two forms using a meta-analytic approach that includes multiple samples of normal individuals. The effects of age, education, gender composition, exclusion criteria, and age of study are also examined. Results indicate that the CFL form of the test is more difficult and that age, education, and the use of strict exclusion criteria influence performance. Performance is more variable for the FAS form, and age and age of study influence performance variability.

Keywords: Verbal Fluency, Controlled Oral Word Association Test, COWA, FAS, CFL


An oral Verbal Fluency Test was first developed by Arthur Benton over 40 years ago (Mitrushina, Boone, & D'Elia, 1998). It was included in the Multilingual Aphasia Examination (Benton & Hamsher, 1976) in a slightly different form and with a new name, the Controlled Oral Word Association (COWA) Test. This test, also known as the phonemic or letter fluency test, requires test takers to name as many words beginning with a single letter as they can in one minute. Standard administration provides three letters. The most commonly used form of the test today uses the letters F, A, and S (Spreen & Strauss, 1998), but the form included in the Multilingual Aphasia Examination (Benton & Hamsher, 1976) uses the letters C, F, and L or P, R, and W. Although the name COWA is most accurately applied to the CFL/PRW form of the test, it has been widely adopted to describe the FAS form as well. Other versions of the letter fluency test that use different letters or different numbers of letters are included in a variety of test batteries (Spreen & Strauss, 1998). For example, the Test of Verbal Conceptualization and Fluency (TVCF; Reynolds & Horton, 2006) includes a verbal fluency test employing the letters P, D, S, and T, and the Delis-Kaplan Executive Function Scale (D-KEFS; Delis, Kaplan, & Kramer, 2001) includes the FAS form and a version using B, H, and R. Although it was developed as a test of verbal ability, the COWA is also considered a test of executive functions, including cognitive organization, initiation, maintenance of effort, and the ability to conduct a non-routine search for words based on a specific first letter, rather than lexical definition (Andrewes, 2001; Devinsky & D'Esposito, 2004; Walsh & Darby, 1999). This interpretation is consistent with research showing poor performance in individuals with frontal lobe lesions (Ruff, Allen, Farrow, Niemann, & Wylie, 1994; Walsh & Darby, 1999) and sensitivity to cognitive dysfunction in disorders that affect executive functions (Henry & Beatty, 2006).

There is some evidence that different forms of the COWA have different levels of difficulty. Borkowski, Benton, and Spreen (1967) classified the letters C, F, P, A, and S as easy letters and the letters L and R as difficult letters based on the English vocabulary size for each letter. The FAS test thus includes only easy letters, whereas the CFL/PRW norms are based on fluency in response to two easy and one difficult letter (Bolla et al., 1990; Lacy et al., 1996; Ruff, Light, Parker, & Levin, 1996). Although comparison of norms for the FAS and CFL forms of the COWA suggest some differences in difficulty, these differences are difficult to interpret due to the use of different samples for each form (see Spreen & Strauss, 1998, for summary). Lacy et al. (1996) studied the equivalence of the two forms in a sample of 287 patients with various neuropsychological complaints. They administered the letters A, C, F, L, and S to each patient in various orders and then compared performance on CFL and FAS groupings. The two forms correlated highly in all patient groups, suggesting that interpretation of FAS using CFL norms would be accurate, at least in clinical samples (Lacy et al., 1996).

In addition to the form of test used, effects of demographic variables are important to consider when interpreting COWA results. Age effects have failed to emerge in many studies (Axelrod & Henry, 1992; Bolla et al., 1990; Ruff et al., 1996; Selnes et al., 1991), although some studies have shown modest age effects, with higher age predicting poorer performance (Libon et al., 1994). Higher education has been associated with better COWA performance in several studies (Ruff et al., 1996; Selnes et al., 1991; Tombaugh, Kozak, & Rees, 1999). Some studies find superior performance on the COWA in women compared to men (Bolla et al., 1990; Ruff et al., 1996), although other studies find no difference between men and women (Boone, 1999; Saykin et al., 1995; Tombaugh et al., 1999).

This study uses multiple regression analysis to examine the influence of form of administration (FAS or CFL) on COWA performance in a large sample comprising multiple published and unpublished studies of normal participants. It also examines the influence of age, education, and gender on mean performance. Influences on the variability of performance were also examined by analyzing the effect of independent variables on the standard deviation of the mean. The meta-analytic methodology employed allows for the examination of two other factors that could influence the applicability of normative samples: the strictness of the exclusion criteria, and the recency of data collection.


Data Collection

Data were collected from published journal articles, normative studies, and unpublished dissertations reporting data obtained from normal, English-speaking participants. Studies were identified through searches of three computerized databases, PsychInfo, Medline, and Web of Science, using the terms verbal fluency test, controlled oral word association, COWA, and word fluency as keywords. A manual search of issues of Neuropsychology, The Clinical Neuropsychologist, the Journal of Clinical and Experimental Neuropsychology, Archives of Clinical Neuropsychology, and the Journal of the International Neuropsychological Society between 1997 and March 2006 was also conducted. Additional studies were identified from the references in studies obtained by the first two methods. Once identified, publications examining normal participants and reporting mean scores for the tests and at least one of three demographic variables (age, education, or gender composition) were included. Studies that used non-standard test administration procedures or that failed to report the form of COWA used were excluded. Only studies conducted in the United States or Canada were used, because differences in educational systems in other English-speaking countries would interfere with analysis of education effects.


The following data were entered into an Excel spreadsheet for each study: mean test score, standard deviation of the mean, age, education, gender composition, year of study, exclusion criteria, and form of test (FAS, CFL) used. Test form and exclusion criteria were dummy coded for inclusion in the regression analysis. Studies using the FAS form of the COWA were coded 1, and those using the CFL form were coded 2. Studies that excluded participants based on at least three characteristics (history of neurological illness, history of significant head injury, history of psychiatric illness, history of significant medical illness, current substance use disorder), were coded 1, and those that did not employ at least three exclusion criteria were coded 0. The sample included 134 studies. Table 1 shows the demographic characteristics of the studies, and Table 2 shows characteristics of the sample included.

Table 1
Demographic Characteristics of the Sample
Table 2
Characteristics of Studies

Data Analysis

Mplus statistical software (Muthén & Muthén, 1998) was used for data analysis. A full information maximum likelihood (FIML) method was used to produce unbiased parameter estimates assuming that data are missing at random (Allison, 2001; Muthén & Muthén). Multiple regression analyses yielded regression equations for the sample means and standard deviations of each test. Following the initial analyses, regression weights of non-significant variables were set to zero, and the analyses rerun, in order to obtain model fit indices. Variables that approached but did not reach significance were not set to zero. Most independent variables were normally distributed. Education was negatively skewed, indicating a higher proportion of scores at the higher end of the distribution. Square root, log, and inverse transformations were conducted on the education variable, but these transformations did not alter the results of the analyses, so the original analyses with untransformed variables were retained in order to avoid difficulty interpreting the effects of substantive differences in independent variables. Effect sizes for each independent variable were obtained as the unique variance accounted for by that variable.


The regression equation for the mean fit the data well when non-significant variables were set to zero (χ2 = 0.831, df = 2, p= 0.6582, RMSEA = 0.00, 90% CI = 0.00 – 0.13, SRMR = 0.01, CFI = 1.00, TLI = 1.00). Gender and year of study were not significant in the preliminary analysis and were set to zero for the purpose of obtaining fit indices. Age and education were significantly associated with mean performance on the Verbal Fluency Test. Older age predicted worse performance, higher education predicted better performance, and the effect sizes for both variables were large. Exclusion criteria also had a significant effect on mean performance. More words were produced in studies with stricter exclusion criteria, with a medium effect size. Test form was also a significant predictor of mean performance, with worse mean performance in studies using the CFL form, but the effect size was small. The mean score for the FAS form of the test was 40.48 (6.08), and the mean score for the CFL form was 38.66 (5.55). The independent variables accounted for 47% of the variance in mean scores.

The regression equation for the standard deviation of the mean also fit the data well when non-significant variables were set to zero (χ2 = 2.489, df = 3, p = 0.4762, RMSEA = 0.00, 90% CI = 0.00 – 0.14, SRMR = 0.02, CFI = 1.00, TLI = 1.00). Age was associated with standard deviation; there was greater variability in older samples. Age of study also predicted variability of performance, with less variability in older studies. Form was a significant predictor of standard deviation as well, suggesting greater variability in samples employing the FAS form of the Verbal Fluency Test. The effect sizes for age of study and form were large. The independent variables accounted for 15% of the variance in the standard deviation of COWA performance.

Table 3 shows the unstandardized beta weights for each variable retained in the second analysis. Table 4 shows the effect sizes represented as percent of variance accounted for by each variable.

Table 3
Estimates for Demographic and Study Variables (Unstandardized Beta Weights)
Table 4
Variance in Means Accounted for by Independent Variables


The results of this study suggest that the CFL form of the COWA Test is more difficult than the FAS form and that there is greater variability in performance on the FAS form among normal individuals. Because the range of normal scores is narrower for CFL, interpretation of results from the two forms could be different for individuals whose scores lie at the extremes of the distribution where the effect of differences in standard deviations may be amplified. These results are inconsistent with findings from the study by Lacy et al. (1996) showing comparable performance on the two forms in clinical samples. One implication of these results is that performance on one form of the test cannot be accurately interpreted using norms based on the other form. Similarly, comparisons of raw scores on the two forms of the test, such as might be used in a pre- and post-intervention evaluation of cognitive ability, should be made cautiously, if at all.

Although previous studies have been inconsistent in their support of age as a variable influencing COWA performance, this study indicates that older adults will perform more poorly than younger adults and that their performance will be more variable. Verbal ability is generally considered a crystallized ability, one that does not decline with age or in response to subtle brain dysfunction, but verbal fluency, particularly phonemic fluency, requires executive ability, specifically the ability to initiate and maintain effort and organize information for retrieval, abilities that are sensitive to subtle cerebral dysfunction and aging (Bryan & Luszez, 2000; Burke & Barnes, 2006; Henry & Beatty, 2006; Mittenberg, Seidenberg, O'Leary, & DiGiulio, 1989; Plumet, Gil, & Gaonac'h, 2005). Education was a potent predictor of performance, consistent with prior research. Higher education predicted better performance. Previous research on the effect of gender on Verbal Fluency performance has been inconsistent. This study indicates that gender does not influence verbal fluency.

Overall, these results support the importance of using norms stratified by age and education, but not gender, when interpreting COWA performance and suggest caution in using the two forms of the test interchangeably.


This study was supported by the National Institute of Alcohol Abuse and Alcoholism Grants R01 AA11594, and K02 AA00325.

Appendix A

Studies included in the analysis.

% MaleStrict
Axelrod & Henry (1992)2041.19.955.315.450YesFAS
Basso et al. (2002)3144.09.1634.0914.919YesFAS
Basso et al. (1999)8247.6810.8231.914.56100YesFAS
Beatty et al. (1989)1339.511.665.414.4YesFAS
Berry et al. (1993)2141.610.733.214.195YesFAS
Bolla et al. (1990)3238126113100YesFAS
Bolla et al. (1999)2136.310.033.912.681YesFAS
Bondi et al. (2003)4339.0510.2966.7214.6756NoFAS
Boone et al. (1990)2543.566.5154.514.68YesFAS
Boone et al. (1995)11040.4511.1263.114.847YesFAS
Caccappolo-Van Vliet et al. (2003)15539.067.915.140NoCFL
Carone et al. (2005)3742.210.242.315.0***YesCFL
Cerhan et al. (2002)22134.0111.3176.113.741YesCFL
Cerhan et al. (1998)62234.812.647100NoFAS
Clark et al. (1997)9241.410.335.513.929NoFAS
Clark et al. (2001)3048.713.837.615.653NoCFL
Comilang (2003)12442.269.119.926YesCFL
Connor et al. (2000)1545.511.824.3100YesFAS
Crossley et al. (1997)13924.012.469.68.2NoFAS
Crowell et al. (2002)8033.5610.737.9512.98100NoFAS
DeLuca et al. (1998)2042.
Demakis (1999)2137.811.122.513.633NoCFL
Dinn & Harris (2000)1041.69.028.913.9100YesFAS
Dursun et al. (2002)4754163916.090NoFAS
Elmudesi (1995)928.226.7636.8914.0100NoCFL
Feinstein et al. (1998)1144.112.025.3YesFAS
Friedman et al. (1995)2444.2912.535.8YesFAS
Friend et al. (1999)4245.3112.9645.8314.3817YesCFL
Garrett (2004)2540.715.276.512.444YesFAS
Goldstein et al. (2001)1432.37.765.313.464YesFAS
Gopal (1996)1047.79.7440.314.390YesFAS
Gourovitch et al. (1996)2442.3633.0414.0422YesFAS
Hall (1995)2041.18.0932.4514.330YesFAS
Heaton et al. (1995)11145.8210.0433.114.7100YesFAS
Hildebrand (1996)3134.849.323.2545NoCFL
Hodges et al. (1990)1440.173.113.350YesFAS
Johnson et al. (2006)9526.7311.2272.3412.3419NoCFL
Johnson et al. (2001)3839.588.8840.817.2963NoFAS
Johnson (2000)14542.2814.2578.741643YesFAS
Johnstone et al. (1995)2037.829.4212.3580NoFAS
Kozora & Cullum (1995)4141.2312.1054.514.351YesFAS
Kozora et al. (1999)3146.313.469.913.351YesFAS
Kramer et al. (2002)2741.014.072.8215.67YesFAS
Kremen et al. (2003)8340.541.113.6941YesFAS
Kuo (2001)5140.613.058.215.057YesFAS
Lafleche & Albert (1995)2051.9010.9976.214.745YesFAS
Lebowitz et al. (2001)3039.5711.0731.213.1657YesFAS
Libon et al. (1994)2349.516.069.713.435YesCFL
Lovejoy et al. (1999)2639.927.14411650YesCFL
Monsch et al. (1992)5341.212.571.213.632YesFAS
Munro et al. (2000)1745.1814.1466.9413.2753YesFAS
Myers & Rohling (2004)2949.910.238.613.4350YesFAS
Nebes et al. (2002)1239.712.873.517.2NoFAS
Norris et al. (1995)5436.910.173.116.7NoFAS
Nyberg et al. (1997)3942.519.7777.313.6NoFAS
Owens et al. (2002)1045.213.827.717.30NoFAS
Rapport et al. (2001)3244.010.833.214.859YesFAS
Riccio et al. (2005)3040.7311.6221.0914.3843.3NoFAS
Rippeth et al. (2004)6040.19.634.413.250NoFAS
Rockers et al. (1996)8839.89.62114.350NoFAS
Ross (2003)12538.17.920.131YesCFL
Ross et al. (2005)6038.887.7220.4322NoCFL
Rouleau et al. (2002)551.873.813.220YesFAS
Royall et al. (2005)54732.012.677.915.141.7NoCFL
Ruby (2000)1545.3311.4033.8717.60NoFAS
Ruff et al. (1986)12039.740.514.050YesCFL
Ryan et al. (1993)6742.6410.5035.313.831YesFAS
Salthouse et al. (1996)25937.349.981537NoFAS
Saxton et al. (2000)1541.111.270.813.253YesFAS
Selnes et al. (1991)30945.712.731.016.1100YesFAS
Simkins-Bullock et al. (1994)1943.589.6352.615.653YesFAS
Simon et al. (2000)6543.011.03112.840NoFAS
Spica (1995)2639.3112.5671.2713.1938NoCFL
Stowe (1996)1638.213.025.713.238YesFAS
Sumerall et al. (1997)473111.282.1914.3519YesCFL
Suter (1997)7538.8710.6723.5413.533YesFAS
Svetina et al. (1999)4543.99.83316.4NoCFL
Thomason (1997)3035.9712.1266.9213.8233NoFAS
Tombaugh et al. (1996)1238.512.037.57YesFAS
Tomer & Levin (1993)2639.211.85513.2YesFAS
Troyer et al. (1997)4141.8811.4522.314.437NoFAS
Troyer et al. (1998)3840.89.673.812.663YesFAS
Vasudev (2000)2245.7310.5565.3217.6873YesFAS
Westervelt (2000)1749.0616.051.0616.1824YesFAS
White et al. (1997)1550.37.237.714.5100NoFAS
Woods & Troster (2003)1837.1116.268.7614.1867YesFAS
Yuspeh (1994)3245.3710.1521.7113.03NoFAS
Zakzanis et al. (2000)3539.779.0443.912.631YesCFL
Zee et al. (1999)4536.613.163.113.624YesFAS


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