- Email: [email protected]
Demographic effects on the Trail Making Test in a drug abuse treatment sample
Archives of Clinical Neuropsychology 18 (2003) 49–56
Demographic effects on the Trail Making Test in a drug abuse treatment sample夽 Arthur MacNeill Horton∗ , Charles Roberts Center for Substance Abuse Treatment, Substance Abuse and Mental Health Services Administration, Suite 840, Rockwall II Building, 5600 Fishers Lane, Rockville, MD 20857, USA Accepted 10 September 2001
Abstract Appreciation of the importance of screening for cognitive impairment among substance abusing populations has increased in recent years. In this article, demographic effects on the Trail Making Test (TMT), a test often used for screening for cognitive impairment, are examined in a sample of patients in drug abuse treatment programs. A sample of 5619 males and 2902 females was drawn from electronic files of data from the Drug Abuse Treatment Outcome Study (DATOS). The DATOS was a naturalistic cohort study that collected data from 1991 to 1993 in 96 programs in 11 cities in the US. Data were analyzed to determine the effects of demographic variables on the two parts of the TMT in this large sample of patients. Consistent with previous research, demographic variables such as age, gender, education level, and ethnicity were statistically significantly related to both TMT Parts A and B. More importantly, however, the percentage of variance accounted for was quite small. These results suggest that, while clearly present, demographic effects on the TMT are weak. Published by Elsevier Science Ltd on behalf of National Academy of Neuropsychology. Keywords: Drug abuse; Drug abuse treatment; Trail Making Test
1. Introduction Appreciation of the importance of screening for cognitive impairment among substance abusing populations has increased in recent years (Horton, 1993). A considerable body of 夽
The opinions expressed herein are the views of the authors and do not necessarily reflect the official position of the Center for Substance Abuse Treatment or any other part of the Department of Health and Human Services. ∗ Corresponding author. E-mail address: [email protected] (A.M. Horton). 0887-6177/02/$ – see front matter © 2002 National Academy of Neuropsychology. PII: S 0 8 8 7 - 6 1 7 7 ( 0 1 ) 0 0 1 8 3 - 4
50
A.M. Horton, C. Roberts / Archives of Clinical Neuropsychology 18 (2003) 49–56
literature suggests that there are cognitive impairments that result from abuse of certain drugs. These data are most clear for inhalant/solvent abuse, use of marijuana and cocaine, and alcohol abuse (Horton, 1996; Miller, 1985; Root & Rowbotham, 1988; Rowley, Lowenstein, Rowbotham, & Simon, 1989; Schwartz & Cohen, 1984; Strickland et al., 1993; Wojak & Flamm, 1987). Given these findings, the question arises on how substance abuse treatment programs determine which patients are cognitively impaired to the point that they may not benefit from standard treatment programs. Obviously, screening for cognitive impairment is necessary in drug abuse treatment programs. One very economical measure often used for neuropsychological screening is the Trail Making Test (TMT) (Horton, 1979; Mezzich & Moses, 1980; Reitan, 1955). The TMT is a brief, portable, and inexpensive neuropsychological test that has been used to assess cognitive dysfunctions for over half a century (Armitage, 1946; Reitan, 1958). It is considered to be one of the best measures of brain damage (Horton & Wedding, 1984; Mezzich & Moses, 1980; Norton, 1978; Reitan & Wolfson, 1992). In addition, it is one of the most frequently administered individual neuropsychological tests and is a standard component of the Halstead–Reitan Neuropsychological Battery as well as most flexible neuropsychological screening batteries (Butler, Retzlaff, & Van der Ploeg, 1991). The TMT has also been widely used to assess substance abusers (McCaffrey, Krahula, Heimberg, Keller, & Purcell 1988; Mezzich & Moses, 1980; Miller, 1985). However, an issue that has arisen in using neuropsychological screening tests is that of appropriate demographic corrections (Heaton, Grant, & Matthews, 1991). As noted by others, there has been significant variability in normative data on the TMT (Soukup, Ingram, Grady, & Schiess, 1998). It has been suggested that demographic factors such as age, gender, education level, and ethnicity may have affected tests scores and perhaps caused some to fall into the cognitively impaired range inappropriately (Adams, Boake, & Crain, 1982; Amante, VanHouten, Grieve, Bader, & Margules, 1977; Campbell et al., 1996; Davies, 1968; Goul & Brown, 1970; Kennedy, 1981; Knuckle & Campbell, 1984; Lex, 1991; Piazza, 1980). In substance abuse treatment populations, this possible skewing of test scores could serve to suggest organic deficits in an already stigmatized group (Horton, 1996; McCaffrey et al., 1988; Miller, 1985). Clearly, research is needed to investigate the effects of these demographic factors on the TMT in a drug abuse treatment population. In this article, demographic effects on the TMT are examined in a sample of patients enrolled in drug abuse treatment programs.
2. Method 2.1. Subjects A sample of 5619 males and 2902 females was drawn from electronic files of data from the Drug Abuse Treatment Outcome Study (DATOS). The DATOS was a naturalistic, prospective cohort study of adults enrolled in drug abuse treatment programs that was sponsored by the National Institute on Drug Abuse (NIDA) of the National Institutes of Health (NIH) (Fletcher, Tims, & Brown, 1997; Horton, 1993). The DATOS collected data from 1991 to 1993 in 96 programs in 11 cities in the US. The DATOS intake cohort consisted of 10,010 subjects
A.M. Horton, C. Roberts / Archives of Clinical Neuropsychology 18 (2003) 49–56
51
interviewed at admission to drug abuse treatment in 96 treatment programs (Flynn, Craddock, Hubbard, Anderson, & Etheridge, 1997). Patients participated in a two-part interview procedure. The first interview, usually done within 1 week of admission, addressed demographic characteristics and substance abuse, legal and employment histories. The second interview was approximately 1 week after the first interview and contained the major assessment modules concerning psychological status, psychiatric symptoms, and the TMT. The length of time since admission before the TMT was administered was intended to reduce acute effects of substances of abuse (Simpson, Joe, Fletcher, Hubbard, & Anglin, 1999). As the purpose of the DATOS was to evaluate the effectiveness of drug abuse treatment in typical and stable community-based drug abuse treatment programs, there may be a bias in the data collection skewed toward larger and more stable programs (Etheridge, Hubbard, Anderson, Craddock, & Flynn, 1997). Therefore, the DATOS data is most representative of subjects in the more established treatment programs in medium to large metropolitan areas in the US. The specific cities from which drug abuse treatment subjects were drawn were: Chicago, Houston, Miami, Minneapolis, Newark, New Orleans, New York, Phoenix, Pittsburgh, Portland, and San Jose. The cities producing the largest numbers of subjects were Pittsburgh, New York, New Orleans, Chicago, and Miami. Of the entire sample, 66% of the subjects were male, 47% were African Americans, and 13% were Hispanic Americans. The average age of the sample was 32.6 years (Fletcher et al., 1997). It might be noted that the current study includes by far the largest sample of clinical patients ever administered the TMT (Soukup et al., 1998). In the DATOS, due to time and expense considerations, formal psychiatric diagnostic instruments were not used. Rather, the clinical assessment focused on marker variables such as depression, suicide, and need for medication (Horton, 1993) to assess the psychiatric status of the patients. Of the patients utilized in this study, the majority had suffered from depression as 63% had felt very depressed for at least 2 weeks during their life. Similarly, 20% had attempted suicide at least once. On the other hand, only 11% had required regular medication for emotional problems. (Frequency tables are available from the second author, Charles Roberts, PhD.) All in all, the sample does seem to have significant psychiatric problems as might be expected from patients entering a substance abuse treatment program. 2.2. Instrumentation As has already been mentioned, the TMT is a brief, portable, and inexpensive neuropsychological test that is frequently used as a screening measure in a wide variety of clinical and treatment settings (Horton, 1979). Like all good organic impairment screening tasks, the TMT taps a wide range of neuropsychological skills including letter and number recognition, visual scanning, cognitive flexibility, processing speed, working memory, motor skill and sequencing ability (Horton, 1979). The TMT is particularly appropriate for screening clinical subjects for cognitive impairment as it typically takes less than 5 min to administer, is in the public domain, and can be administered by a trained paraprofessional (Reitan & Wolfson, 1992). Although the TMT is in the public domain, it was declared obsolete by the Adjutant General’s Office of the War Department and permission was given to Ralph M. Reitan, PhD to distribute the test
52
A.M. Horton, C. Roberts / Archives of Clinical Neuropsychology 18 (2003) 49–56
for clinical use to clinicians motivated by Reitan’s research findings with the TMT (personal communication from Ralph M. Reitan, PhD). In 1990, the TMT was adopted by a panel of assessment experts formed in connection with the DATOS as a measure of cognitive impairment on the recommendation of the first author of this article, a member of the DATOS assessment expert panel (Horton, 1993). The TMT consists of two parts labeled Trails A and Trails B. Trails A consists of 25 consecutive numbered circles that the patient connects by drawing a line through each element in the series. Trails B is a more complex task in which a series of numbers (1–13) and letters (A–L) are presented on the page enclosed within circles. The patient is required to work through the entire set alternately connecting numbers and letters (i.e., 1–A–2–B–3–C. . . L–13) until the 25th circle is reached. The patient is required to connect the circles with a pencil line as rapidly as possible. The final score for both parts is the number of seconds required to complete the task. In the course of this exercise, errors are pointed out by the examiner and the subject is redirected to the last correct circle while timing continues. Errors, therefore, count by increasing performance time (Reitan & Wolfson, 1992).
Table 1 Means and standard deviations for the TMT by demographic variables A
B
n
Mean
Standard deviation
Mean
Standard deviation
Sex Male Female
5521 2848
32.4 31.4
12.1 11.4
73.5 71.1
22.8 22.1
Age 18–20 21–25 26–30 31–35 36–44 Over 44
270 1194 2023 2199 2182 501
30.0 29.2 31.0 31.9 33.9 37.2
10.6 10.8 11.0 11.7 12.5 13.5
67.3 68.1 70.4 73.2 75.8 80.5
21.2 22.1 21.0 23.3 23.0 22.1
Ethnicity African American/Black Caucasian/White Hispanic Other
3911 3226 1024 208
34.1 29.3 33.1 32.2
12.3 10.6 12.3 12.4
77.5 66.2 75.3 71.1
23.6 20.2 21.2 21.8
Education Grade school/less High school High school degree Some college Junior college/associate degree College degree Advanced degree
340 2643 3215 1443 352 314 62
37.3 33.8 31.6 29.8 30.0 30.1 31.0
12.4 12.6 11.5 10.9 10.3 10.9 11.8
87.3 76.9 71.5 67.7 66.1 66.1 65.5
25.1 23.1 21.9 20.9 19.9 19.8 20.8
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2.3. Procedure This study involved secondary analysis of data collected as part of the DATOS from 1991 to 1993. The DATOS used standard test administration procedures for data collection (Horton, 1993). The DATOS data have been placed in electronic files on the Internet in public archives at the Substance Abuse and Mental Health Data Archive (SAMHDA) located at http://www.icpsr.umich.edu/SAMHDA. The available data set consisted of files with information on 8755 subjects, identified as intake2. Files were downloaded from ftp://ftp.icpsr.umich. edu/pub/FastTrack/. The data files were downloaded and cleaned. An examination of the tails of TMT A and B scores revealed approximately 1% of outliers in each tail. To facilitate data integrity, outliers and cases with missing demographics or TMT times were excluded from analyses leaving 8521 cases available. For this study, secondary analyses were conducted on the data files. Analysis of variance statistical procedures (SAS Institute, 1989) were used to calculate the percentage of variances accounted for by selected demographic variables such as age, gender, education level, and ethnicity. Separate analyses were run for both Parts A and B of the TMT. As earlier noted, it has been suggested that demographic factors such as age, gender, education level, and ethnicity may skew tests scores into the impaired range inappropriately. Table 1 presents means and standard deviations of the TMT by demographic variables.
3. Results and discussion Data were analyzed to determine the effects of demographic variables on scores for both parts of the TMT in this large sample of patients. Consistent with previous research (Adams et al., 1982; Bernard, 1989; Davies, 1968; Goul & Brown, 1970; Heaton et al., 1991; Kennedy, 1981), demographic variables such as age, gender, education level, and ethnicity were statistically significantly related to both TMT Parts A and B. More important, however, the percentage of variances accounted for (A = 0.09, B = 0.12) was quite small (Cohen, 1988). The large sample of subjects, of course, produces a very stringent test of the effects of demographic factors. Table 2 presents the results of the analysis of variance of the TMT with demographic variables as the sources of variation. Table 2 Analysis of variance for the TMT A
B
Source
df
F value
Pr > F
F value
Pr > F
Sex Age Ethnicity Education Residual R2
1 5 3 6 8353
12.15 56.15 75.16 37.84
.0005 <.0001 <.0001 <.0001
27.03 49.16 121.52 69.04
<.0001 <.0001 <.0001 <.0001
.086
119
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A.M. Horton, C. Roberts / Archives of Clinical Neuropsychology 18 (2003) 49–56
These results suggest that, while clearly present, demographic effects on the TMT are weak. This finding is of special significance given the fact that the current sample is by far the largest sample of clinical subjects with TMT scores (Heaton et al., 1991; Soukup et al., 1998). At the same time, some limitations might be noted. Quite clearly, these findings are specific to a particular form of psychopathology, i.e., drug abuse (Horton, 1996). It may be that different sorts of disorders may have different relationships with demographic variables and could have different effects on neuropsychological tests. Also, the population used for this study, as might be expected in a drug abuse treatment sample, was quite young. It may be that the variable of age would require the full range of ages to be represented for the variable to be properly expressed. Earlier efforts to find age effects on the TMT that failed (Boll & Reitan, 1973) used a similar age range to this sample and cases where the age effects were pronounced included much older subjects (Davies, 1968). Very clearly, the current sample is limited and certainly is not the best group in which to evaluate age effects. Nonetheless, given the purpose of this study to examine demographic effects for a drug abuse sample, the study sample population is appropriate for that purpose. Similarly, it is quite likely that normal subjects show substantial education effects on TMT performances but in persons with definite evidence of brain damage such effects are likely very limited. Reitan and Wolfson (1999) have shown such limitations on brain-sensitive neuropsychological measures in groups of both adults and children with structural brain damage as well as children with learning disabilities. It appears that in conditions that have a direct effect on results of sensitive neuropsychological tests, the condition itself, and its severity, tends to determine the test scores and the influence of attribute variables, such as age and education, is reduced (Reitan & Wolfson, 1999). In summary, at least with youthful drug abusers enrolled in treatment, the TMT appears to be affected relatively slightly by demographic factors. Implications of this study are that the TMT scores appear quite robust and may not need extensive demographic correction for use with a drug abuse treatment population. This finding will clearly serve to promote the value of the TMT in substance abuse settings. Much data support the value of the TMT as a screening device (McCaffrey et al., 1988; Norton, 1978).
References Adams, R., Boake, C., & Crain, C. (1982). Bias in a neuropsychological test classification related to education, age, and ethnicity. Journal of Consulting and Clinical Psychology, 50, 143–145. Amante, D., VanHouten, V., Grieve, J., Bader, C., & Margules, P. (1977). Neuropsychological deficit, ethnicity, and socioeconomic status. Journal of Consulting and Clinical Psychology, 45(4), 524–535. Armitage, S. (1946). Analysis of certain psychological tests used for the evaluation of brain damage. Psychological Monographs, 60(1), 1–277 (Whole no. 277). Bernard, L. C. (1989). Halstead–Reitan Neuropsychological Test performance of Black, Hispanic, and White young adult males from poor academic backgrounds. Archives of Clinical Neuropsychology, 4, 267–274. Boll, T. J., & Reitan, R. M. (1973). Effect of age on performance of the Trail Making Test. Perceptual and Motor Skills, 36, 619–694. Butler, M., Retzlaff, H. P., & Van der Ploeg, R. (1991). Neuropsychological test usage. Professional Psychology: Theory, Research and Practice, 22, 510–512.
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Campbell, A. L., Rorie, K. D., Dennis, G., Wood, D., Combs, S., Hearn, L., Davis, H., & Brown, A. (1996). Neuropsychological assessment of African Americans: Conceptual and methodological considerations. In R. Jones (Eds.), Handbook of tests and measurements for Black populations. Berkeley: Cobb and Henry. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum. Davies, A. D. M. (1968). The influence of age on the Trail Making Test performance. Journal of Consulting Psychology, 24, 96–98. Etheridge, R. M., Hubbard, R. L., Anderson, J., Craddock, S. G., & Flynn, P. M. (1997). Treatment structure and program services in the Drug Abuse Treatment Outcome Study. Psychology of Addictive Behaviors, 11, 244–260. Fletcher, B. W., Tims, F. M., & Brown, B. S. (1997). Drug Abuse Treatment Outcome Study (DATOS): Treatment evaluation research in the United States. Psychology of Addictive Behaviors, 11, 216–229. Flynn, P. M., Craddock, S. G., Hubbard, R. L., Anderson, J., & Etheridge, R. M. (1997). Methodological overview and research design for the Drug Abuse Treatment Outcome Study (DATOS). Psychology of Addictive Behaviors, 11, 230–243. Goul, W. R., & Brown, M. (1970). Effects of age and intelligence on Trail Making Test performance and validity. Perceptual and Motor Skills, 30, 319–326. Heaton, R., Grant, I., & Matthews, C. (1991). Comprehensive norms for an expanded Halstead–Reitan battery. Odessa, FL: Psychological Assessment Resources. Horton, A. M., Jr. (1979). Some suggestions regarding the clinical interpretation of the Trail Making Test. Clinical Neuropsychology, 1, 20–23. Horton, A. M., Jr. (1993). Future directions in the development of addiction assessment instruments. In B. J. Rounsaville, F. M. Tims, A. M. Horton Jr., & B. J. Sowder (Eds.), Diagnostic source book on drug abuse research and treatment (pp. 87–92). Rockville, MD: U.S. Department of Health and Human Services. Horton, A. M., Jr. (1996). Neuropsychology of drug abuse. In R. J. Sbordone & C. J. Long (Eds.), Ecological validity of neuropsychological testing (pp. 357–368). Delray Beach, FL: GR Press/St. Lucie Press. Horton, A. M., Jr., & Wedding, D. (1984). Clinical and behavioral neuropsychology. New York: Praeger. Kennedy, K. J. (1981). Age effects on Trail Making Test performance. Perceptual and Motor Skills, 52, 671–675. Knuckle, E., & Campbell, A. (1984). Suitability of neuropsychological test norms with Black adolescents. Paper presented at the International Neuropsychological Society Meeting, Houston, TX. Lex, B. W. (1991). Some gender differences in alcohol and polysubstance abusers. Health Psychology, 10(2), 121–132. McCaffrey, R. J., Krahula, M. M., Heimberg, R. G., Keller, K. E., & Purcell, M. J. (1988). A comparison of the Trail Making Test, Symbol Digit Modalities Test and the Hooper Visual Organization Test in an inpatient substance abuse population. Archives of Clinical Neuropsychology, 3, 181–187. Mezzich, J. E., & Moses, J. A. (1980). Efficient screening for brain-dysfunction. Biological Psychiatry, 15, 333–337. Miller, L. (1985). Neuropsychological assessment of substance abusers: Review and recommendations. Journal of Substance Abuse Treatment, 2, 5–17. Norton, J. C. (1978). The Trail Making Test and Bender background interference procedure as screening devices. Journal of Clinical Psychology, 34, 916–922. Piazza, D. M. (1980). The influence of sex and handedness in the hemispheric specialization of verbal and nonverbal tasks. Neuropsychologia, 18, 163–175. Reitan, R. M. (1955). The relation of the Trail Making Test to organic brain damage. Journal of Consulting Psychology, 19, 393–394. Reitan, R. M. (1958). Validity of the Trail Making Test as an indicator of organic brain damage. Perceptual and Motor Skills, 8, 271–276. Reitan, R. M., & Wolfson, D. (1992). The Halstead–Reitan Neuropsychological Test Battery: Theory and clinical interpretation (2nd ed.). Tucson, AZ: Neuropsychology Press. Reitan, R. M., & Wolfson, D. (1999). The influence of age and education on neuropsychological performances of persons with mild traumatic brain injuries. In M. J. Raymond, T. L. Bennett, L. C. Hartlage, & C. L. Cullum (Eds.), Mild traumatic brain injury: A clinician’s guide (pp. 49–76). Austin: Pro-ed.
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Root, R. K., & Rowbotham, M. (1988). Neurologic aspects of cocaine abuse. Western Journal of Medicine, 149, 442–448. Rowley, H. A., Lowenstein, D. H., Rowbotham, M. C., & Simon, R. P. (1989). Thalamomesencephalic strokes after cocaine abuse. Neurology, 39, 428–430. SAS Institute. (1989). SAS/STAT users’s guide, version 6 (4th ed.). Cary, NC: SAS Institute. Schwartz, K. A., & Cohen, J. A. (1984). Subarachnoid hemorrhage precipitated by cocaine snorting. Archives of Neurology, 41, 705. Simpson, D. D., Joe, G. W., Fletcher, B. W., Hubbard, R. L., & Anglin, D. (1999). A national evaluation of treatment outcomes for cocaine dependence. Archives of General Psychiatry, 56, 507–514. Soukup, V. M., Ingram, F., Grady, J. J., & Schiess, M. C. (1998). Trail Making Test: Issues in normative data selection. Applied Neuropsychology, 5(2), 65–73. Strickland, T. L., Mena, I., Villanueva-Meyer, J., Miller, B. L., Cummings, J., Mehringer, C. M., Satz, P., & Myers, H. (1993). Cerebral perfusion and neuropsychological consequences of chronic cocaine use. Journal of Neuropsychiatry and Clinical Neuroscience, 5, 419–427. Wojak, J. C., & Flamm, E. S. (1987). Intracranial hemorrhage and cocaine abuse. Stroke, 18, 712–715.
Demographic effects on the Trail Making Test in a drug abuse treatment sample夽 Arthur MacNeill Horton∗ , Charles Roberts Center for Substance Abuse Treatment, Substance Abuse and Mental Health Services Administration, Suite 840, Rockwall II Building, 5600 Fishers Lane, Rockville, MD 20857, USA Accepted 10 September 2001
Abstract Appreciation of the importance of screening for cognitive impairment among substance abusing populations has increased in recent years. In this article, demographic effects on the Trail Making Test (TMT), a test often used for screening for cognitive impairment, are examined in a sample of patients in drug abuse treatment programs. A sample of 5619 males and 2902 females was drawn from electronic files of data from the Drug Abuse Treatment Outcome Study (DATOS). The DATOS was a naturalistic cohort study that collected data from 1991 to 1993 in 96 programs in 11 cities in the US. Data were analyzed to determine the effects of demographic variables on the two parts of the TMT in this large sample of patients. Consistent with previous research, demographic variables such as age, gender, education level, and ethnicity were statistically significantly related to both TMT Parts A and B. More importantly, however, the percentage of variance accounted for was quite small. These results suggest that, while clearly present, demographic effects on the TMT are weak. Published by Elsevier Science Ltd on behalf of National Academy of Neuropsychology. Keywords: Drug abuse; Drug abuse treatment; Trail Making Test
1. Introduction Appreciation of the importance of screening for cognitive impairment among substance abusing populations has increased in recent years (Horton, 1993). A considerable body of 夽
The opinions expressed herein are the views of the authors and do not necessarily reflect the official position of the Center for Substance Abuse Treatment or any other part of the Department of Health and Human Services. ∗ Corresponding author. E-mail address: [email protected] (A.M. Horton). 0887-6177/02/$ – see front matter © 2002 National Academy of Neuropsychology. PII: S 0 8 8 7 - 6 1 7 7 ( 0 1 ) 0 0 1 8 3 - 4
50
A.M. Horton, C. Roberts / Archives of Clinical Neuropsychology 18 (2003) 49–56
literature suggests that there are cognitive impairments that result from abuse of certain drugs. These data are most clear for inhalant/solvent abuse, use of marijuana and cocaine, and alcohol abuse (Horton, 1996; Miller, 1985; Root & Rowbotham, 1988; Rowley, Lowenstein, Rowbotham, & Simon, 1989; Schwartz & Cohen, 1984; Strickland et al., 1993; Wojak & Flamm, 1987). Given these findings, the question arises on how substance abuse treatment programs determine which patients are cognitively impaired to the point that they may not benefit from standard treatment programs. Obviously, screening for cognitive impairment is necessary in drug abuse treatment programs. One very economical measure often used for neuropsychological screening is the Trail Making Test (TMT) (Horton, 1979; Mezzich & Moses, 1980; Reitan, 1955). The TMT is a brief, portable, and inexpensive neuropsychological test that has been used to assess cognitive dysfunctions for over half a century (Armitage, 1946; Reitan, 1958). It is considered to be one of the best measures of brain damage (Horton & Wedding, 1984; Mezzich & Moses, 1980; Norton, 1978; Reitan & Wolfson, 1992). In addition, it is one of the most frequently administered individual neuropsychological tests and is a standard component of the Halstead–Reitan Neuropsychological Battery as well as most flexible neuropsychological screening batteries (Butler, Retzlaff, & Van der Ploeg, 1991). The TMT has also been widely used to assess substance abusers (McCaffrey, Krahula, Heimberg, Keller, & Purcell 1988; Mezzich & Moses, 1980; Miller, 1985). However, an issue that has arisen in using neuropsychological screening tests is that of appropriate demographic corrections (Heaton, Grant, & Matthews, 1991). As noted by others, there has been significant variability in normative data on the TMT (Soukup, Ingram, Grady, & Schiess, 1998). It has been suggested that demographic factors such as age, gender, education level, and ethnicity may have affected tests scores and perhaps caused some to fall into the cognitively impaired range inappropriately (Adams, Boake, & Crain, 1982; Amante, VanHouten, Grieve, Bader, & Margules, 1977; Campbell et al., 1996; Davies, 1968; Goul & Brown, 1970; Kennedy, 1981; Knuckle & Campbell, 1984; Lex, 1991; Piazza, 1980). In substance abuse treatment populations, this possible skewing of test scores could serve to suggest organic deficits in an already stigmatized group (Horton, 1996; McCaffrey et al., 1988; Miller, 1985). Clearly, research is needed to investigate the effects of these demographic factors on the TMT in a drug abuse treatment population. In this article, demographic effects on the TMT are examined in a sample of patients enrolled in drug abuse treatment programs.
2. Method 2.1. Subjects A sample of 5619 males and 2902 females was drawn from electronic files of data from the Drug Abuse Treatment Outcome Study (DATOS). The DATOS was a naturalistic, prospective cohort study of adults enrolled in drug abuse treatment programs that was sponsored by the National Institute on Drug Abuse (NIDA) of the National Institutes of Health (NIH) (Fletcher, Tims, & Brown, 1997; Horton, 1993). The DATOS collected data from 1991 to 1993 in 96 programs in 11 cities in the US. The DATOS intake cohort consisted of 10,010 subjects
A.M. Horton, C. Roberts / Archives of Clinical Neuropsychology 18 (2003) 49–56
51
interviewed at admission to drug abuse treatment in 96 treatment programs (Flynn, Craddock, Hubbard, Anderson, & Etheridge, 1997). Patients participated in a two-part interview procedure. The first interview, usually done within 1 week of admission, addressed demographic characteristics and substance abuse, legal and employment histories. The second interview was approximately 1 week after the first interview and contained the major assessment modules concerning psychological status, psychiatric symptoms, and the TMT. The length of time since admission before the TMT was administered was intended to reduce acute effects of substances of abuse (Simpson, Joe, Fletcher, Hubbard, & Anglin, 1999). As the purpose of the DATOS was to evaluate the effectiveness of drug abuse treatment in typical and stable community-based drug abuse treatment programs, there may be a bias in the data collection skewed toward larger and more stable programs (Etheridge, Hubbard, Anderson, Craddock, & Flynn, 1997). Therefore, the DATOS data is most representative of subjects in the more established treatment programs in medium to large metropolitan areas in the US. The specific cities from which drug abuse treatment subjects were drawn were: Chicago, Houston, Miami, Minneapolis, Newark, New Orleans, New York, Phoenix, Pittsburgh, Portland, and San Jose. The cities producing the largest numbers of subjects were Pittsburgh, New York, New Orleans, Chicago, and Miami. Of the entire sample, 66% of the subjects were male, 47% were African Americans, and 13% were Hispanic Americans. The average age of the sample was 32.6 years (Fletcher et al., 1997). It might be noted that the current study includes by far the largest sample of clinical patients ever administered the TMT (Soukup et al., 1998). In the DATOS, due to time and expense considerations, formal psychiatric diagnostic instruments were not used. Rather, the clinical assessment focused on marker variables such as depression, suicide, and need for medication (Horton, 1993) to assess the psychiatric status of the patients. Of the patients utilized in this study, the majority had suffered from depression as 63% had felt very depressed for at least 2 weeks during their life. Similarly, 20% had attempted suicide at least once. On the other hand, only 11% had required regular medication for emotional problems. (Frequency tables are available from the second author, Charles Roberts, PhD.) All in all, the sample does seem to have significant psychiatric problems as might be expected from patients entering a substance abuse treatment program. 2.2. Instrumentation As has already been mentioned, the TMT is a brief, portable, and inexpensive neuropsychological test that is frequently used as a screening measure in a wide variety of clinical and treatment settings (Horton, 1979). Like all good organic impairment screening tasks, the TMT taps a wide range of neuropsychological skills including letter and number recognition, visual scanning, cognitive flexibility, processing speed, working memory, motor skill and sequencing ability (Horton, 1979). The TMT is particularly appropriate for screening clinical subjects for cognitive impairment as it typically takes less than 5 min to administer, is in the public domain, and can be administered by a trained paraprofessional (Reitan & Wolfson, 1992). Although the TMT is in the public domain, it was declared obsolete by the Adjutant General’s Office of the War Department and permission was given to Ralph M. Reitan, PhD to distribute the test
52
A.M. Horton, C. Roberts / Archives of Clinical Neuropsychology 18 (2003) 49–56
for clinical use to clinicians motivated by Reitan’s research findings with the TMT (personal communication from Ralph M. Reitan, PhD). In 1990, the TMT was adopted by a panel of assessment experts formed in connection with the DATOS as a measure of cognitive impairment on the recommendation of the first author of this article, a member of the DATOS assessment expert panel (Horton, 1993). The TMT consists of two parts labeled Trails A and Trails B. Trails A consists of 25 consecutive numbered circles that the patient connects by drawing a line through each element in the series. Trails B is a more complex task in which a series of numbers (1–13) and letters (A–L) are presented on the page enclosed within circles. The patient is required to work through the entire set alternately connecting numbers and letters (i.e., 1–A–2–B–3–C. . . L–13) until the 25th circle is reached. The patient is required to connect the circles with a pencil line as rapidly as possible. The final score for both parts is the number of seconds required to complete the task. In the course of this exercise, errors are pointed out by the examiner and the subject is redirected to the last correct circle while timing continues. Errors, therefore, count by increasing performance time (Reitan & Wolfson, 1992).
Table 1 Means and standard deviations for the TMT by demographic variables A
B
n
Mean
Standard deviation
Mean
Standard deviation
Sex Male Female
5521 2848
32.4 31.4
12.1 11.4
73.5 71.1
22.8 22.1
Age 18–20 21–25 26–30 31–35 36–44 Over 44
270 1194 2023 2199 2182 501
30.0 29.2 31.0 31.9 33.9 37.2
10.6 10.8 11.0 11.7 12.5 13.5
67.3 68.1 70.4 73.2 75.8 80.5
21.2 22.1 21.0 23.3 23.0 22.1
Ethnicity African American/Black Caucasian/White Hispanic Other
3911 3226 1024 208
34.1 29.3 33.1 32.2
12.3 10.6 12.3 12.4
77.5 66.2 75.3 71.1
23.6 20.2 21.2 21.8
Education Grade school/less High school High school degree Some college Junior college/associate degree College degree Advanced degree
340 2643 3215 1443 352 314 62
37.3 33.8 31.6 29.8 30.0 30.1 31.0
12.4 12.6 11.5 10.9 10.3 10.9 11.8
87.3 76.9 71.5 67.7 66.1 66.1 65.5
25.1 23.1 21.9 20.9 19.9 19.8 20.8
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2.3. Procedure This study involved secondary analysis of data collected as part of the DATOS from 1991 to 1993. The DATOS used standard test administration procedures for data collection (Horton, 1993). The DATOS data have been placed in electronic files on the Internet in public archives at the Substance Abuse and Mental Health Data Archive (SAMHDA) located at http://www.icpsr.umich.edu/SAMHDA. The available data set consisted of files with information on 8755 subjects, identified as intake2. Files were downloaded from ftp://ftp.icpsr.umich. edu/pub/FastTrack/. The data files were downloaded and cleaned. An examination of the tails of TMT A and B scores revealed approximately 1% of outliers in each tail. To facilitate data integrity, outliers and cases with missing demographics or TMT times were excluded from analyses leaving 8521 cases available. For this study, secondary analyses were conducted on the data files. Analysis of variance statistical procedures (SAS Institute, 1989) were used to calculate the percentage of variances accounted for by selected demographic variables such as age, gender, education level, and ethnicity. Separate analyses were run for both Parts A and B of the TMT. As earlier noted, it has been suggested that demographic factors such as age, gender, education level, and ethnicity may skew tests scores into the impaired range inappropriately. Table 1 presents means and standard deviations of the TMT by demographic variables.
3. Results and discussion Data were analyzed to determine the effects of demographic variables on scores for both parts of the TMT in this large sample of patients. Consistent with previous research (Adams et al., 1982; Bernard, 1989; Davies, 1968; Goul & Brown, 1970; Heaton et al., 1991; Kennedy, 1981), demographic variables such as age, gender, education level, and ethnicity were statistically significantly related to both TMT Parts A and B. More important, however, the percentage of variances accounted for (A = 0.09, B = 0.12) was quite small (Cohen, 1988). The large sample of subjects, of course, produces a very stringent test of the effects of demographic factors. Table 2 presents the results of the analysis of variance of the TMT with demographic variables as the sources of variation. Table 2 Analysis of variance for the TMT A
B
Source
df
F value
Pr > F
F value
Pr > F
Sex Age Ethnicity Education Residual R2
1 5 3 6 8353
12.15 56.15 75.16 37.84
.0005 <.0001 <.0001 <.0001
27.03 49.16 121.52 69.04
<.0001 <.0001 <.0001 <.0001
.086
119
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These results suggest that, while clearly present, demographic effects on the TMT are weak. This finding is of special significance given the fact that the current sample is by far the largest sample of clinical subjects with TMT scores (Heaton et al., 1991; Soukup et al., 1998). At the same time, some limitations might be noted. Quite clearly, these findings are specific to a particular form of psychopathology, i.e., drug abuse (Horton, 1996). It may be that different sorts of disorders may have different relationships with demographic variables and could have different effects on neuropsychological tests. Also, the population used for this study, as might be expected in a drug abuse treatment sample, was quite young. It may be that the variable of age would require the full range of ages to be represented for the variable to be properly expressed. Earlier efforts to find age effects on the TMT that failed (Boll & Reitan, 1973) used a similar age range to this sample and cases where the age effects were pronounced included much older subjects (Davies, 1968). Very clearly, the current sample is limited and certainly is not the best group in which to evaluate age effects. Nonetheless, given the purpose of this study to examine demographic effects for a drug abuse sample, the study sample population is appropriate for that purpose. Similarly, it is quite likely that normal subjects show substantial education effects on TMT performances but in persons with definite evidence of brain damage such effects are likely very limited. Reitan and Wolfson (1999) have shown such limitations on brain-sensitive neuropsychological measures in groups of both adults and children with structural brain damage as well as children with learning disabilities. It appears that in conditions that have a direct effect on results of sensitive neuropsychological tests, the condition itself, and its severity, tends to determine the test scores and the influence of attribute variables, such as age and education, is reduced (Reitan & Wolfson, 1999). In summary, at least with youthful drug abusers enrolled in treatment, the TMT appears to be affected relatively slightly by demographic factors. Implications of this study are that the TMT scores appear quite robust and may not need extensive demographic correction for use with a drug abuse treatment population. This finding will clearly serve to promote the value of the TMT in substance abuse settings. Much data support the value of the TMT as a screening device (McCaffrey et al., 1988; Norton, 1978).
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