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. Author manuscript; available in PMC: 2008 Jul 7.
Published in final edited form as: Neuropsychology. 2006 Nov;20(6):716–726. doi: 10.1037/0894-4105.20.6.716

Neuropsychological Functioning in Posttraumatic Stress Disorder and Alcohol Abuse

Kristin W Samuelson 1, Thomas J Metzler 2, Johannes Rothlind 3, Gerard Choucroun 4, Thomas C Neylan 5, Maryanne Lenoci 6, Clare Henn-Haase 7, Michael W Weiner 8, Charles R Marmar 8
PMCID: PMC2443729  NIHMSID: NIHMS48312  PMID: 17100516

Abstract

Studies have shown differences in neuropsychological functioning between groups with posttraumatic stress disorder (PTSD) and control participants. Because individuals with PTSD often have a history of comorbid alcohol abuse, the extent to which an alcohol confound is responsible for these differences remains a concern. The current study compares neuropsychological testing scores in 4 groups of veterans with and without PTSD (PTSD+] and PTSD–, respectively) and with and without a history of alcohol abuse (ETOH+ and ETOH–, respectively): n for PTSD+/ETOH+ = 30, n for PTSD+/ETOH– = 37, n for PTSD–/ETOH+= 30, and n for PTSD–/ETOH– = 31. Results showed that PTSD, when alcohol, educational level, vocabulary, and depression are controlled for, was associated with decreased verbal memory, attention, and processing speed performance. Alcohol abuse history was associated with decreased visual memory performance. By controlling for alcohol and depression, the authors can more conclusively demonstrate that verbal memory and attention differences are associated with PTSD.

Keywords: PTSD, veterans, memory, attention, alcohol abuse

Interest in neuropsychological functioning in posttraumatic stress disorder (PTSD) arose in response to patients’ complaints of problems with memory, attention, and concentration. A number of studies have identified decreased performance in verbal memory and learning in participants with PTSD relative to control participants (Elzinga & Bremner, 2002; Gil, Calev, Greenberg, Kugelmass, & Lerer, 1990; Golier & Yehuda, 2002; Horner & Hamner, 2002; Koenen et al., 2001; Uddo, Vasterling, Brailey, & Sutker, 1993; Yehuda et al., 1995). Other studies have documented differences between groups with and without PTSD in the areas of working memory and attention (Brandes et al., 2002; Gilbertson, Gurvits, Lasko, Orr, & Pitman, 2001; Vasterling, Brailey, Constans, & Sutker, 1998; Vasterling et al., 2002) and processing speed (Brandes et al., 2002). In addition, many but not all studies have reported decreases in hippocampal volume (Bremner et al., 1995, 1997; Gilbertson et al., 2002; Gurvits et al., 1996; Stein, Koverola, Hanna, Torchia, & McClarty, 1997; Villarreal et al., 2002) and hippocampal N-acetylaspartate (Freeman, Cardwell, Karson, & Komoroski, 1998; Schuff et al., 1997, 2001) as well as associations between hippocampal atrophy and poorer verbal memory in PTSD (Bremner et al., 1995). Although Brandes et al. (2002) and Uddo et al. (1993) found impaired visual memory performance in individuals with PTSD, the majority of studies have failed to find PTSD-related deficits in visual memory (Bremner et al., 1995; Stein, Kennedy, & Twamley, 2002; Vasterling et al., 1998, 2002; Zalewski, Thompson, & Gottesman, 1994).

Findings of neuropsychological deficits in PTSD are not consistent, however, and several studies have not shown differences between samples with and without PTSD in memory performance (Crowell, Kieffer, Siders, & Vanderploeg, 2002; Neylan et al., 2004; Stein, Hanna, Vaerum, & Koverola, 1999; Stein et al., 2002; Zalewski et al., 1994) or attention (Golier et al., 1997; Yehuda et al., 1995). Such inconsistencies in findings may be attributed in part to sample limitations inherent in populations diagnosed with PTSD. Most neuropsychological studies of PTSD involve veterans with chronic PTSD who frequently exhibit comorbid psychiatric diagnoses. In particular, high lifetime rates of alcohol abuse frequently accompany PTSD, thereby confounding the attribution of neuropsychological deficits specifically to PTSD. In their review, Keane and Kaloupek (1997) found lifetime alcohol abuse and dependence rates varying from 24% to 84% in individuals with PTSD. Because alcoholism itself may impact neuropsychological functioning, we cannot be sure that neuropsychological deficits seen in patients with PTSD are in fact due to PTSD without adequately controlling for comorbid alcohol abuse and dependence.

Research studies on neuropsychological deficits in alcoholics tend to show more severe deficits in visual–spatial functions than in verbal functions (e.g., Butters, Cermak, Montgomery, & Adinofli, 1977; Donat, 1986; Fabian, Parsons, & Sheldon, 1994; Leber, Jenkins, & Parsons, 1981; Ryan & Butters, 1980), leading many alcohol researchers to suggest that the right hemisphere might be more vulnerable to the effects of alcohol abuse than the left hemisphere of the brain (see Ellis & Oscar-Berman, 1989, for review). Although the majority of studies show deficits in chronic or recently detoxified alcoholics, some studies have found neuropsychological problems to persist after the acute withdrawal period. Cross-sectional studies of recovering alcoholics who have been abstinent for several years have shown impairment particularly in visual–spatial tasks (Brandt, Butters, Ryan, & Bayog, 1983; Fama, Pfefferbaum, & Sullivan, 2004). A review of longitudinal studies (Parsons, 1996) showed that although neuropsychological performance improves over time in abstinent alcoholics, recovering alcoholics still show significant differences from control groups at retesting for several years. These studies illustrate the continued debate surrounding the long-term effects of alcoholism on neuropsychological functioning.

In their large study of neurocognition in veterans with and without PTSD, Barrett, Green, Morris, Giles, and Croft (1996) examined the impact of comorbid psychiatric disorders. Veterans with PTSD alone did not show lower scores on measures of neuropsychological functioning compared with normal control participants. However, veterans with both PTSD and a concurrent diagnosis of depression, anxiety, or substance abuse performed significantly less well. These results suggested that a diagnosis of PTSD alone may not be strongly associated with neuropsychological impairment.

Researchers of some studies have attempted to address the comorbidity issue by matching participants with PTSD and control participants on alcohol abuse history (Bremner et al., 1993, 1995; Jenkins, Langlais, Delis, & Cohen, 1998) or by statistically controlling for lifetime history of alcohol use (Gilbertson et al., 2001), and they have continued to find PTSD-related neuropsychological deficits. Other studies have excluded participants with recent alcohol abuse histories altogether (Neylan et al., 2004; Stein et al., 2002). Although it is necessary to ensure that the effects of alcohol are controlled for, it is also important to study participants with PTSD and recent alcohol abuse histories, otherwise findings will not be representative of the larger population of veterans with PTSD. This concern is underscored by initial clinical impressions of high levels of alcohol abuse in returning Afghanistan and Iraq veterans with PTSD. By comparing four groups of individuals with and without PTSD and alcohol abuse history, it is possible to experimentally determine the independent contribution of PTSD to neuropsychological functioning, the independent contribution of alcohol abuse history, and the interactive effects of both conditions. Including participants with PTSD with and without a history of recent alcohol abuse offers an opportunity to better understand the factors that may contribute to lower neuropsychological performance in PTSD, and it may yield results that are generalizable to a real world clinical population of combat veterans with PTSD.

Comorbid depression diagnoses present an additional challenge in PTSD research. The review by Keane and Kaloupek (1997) reported rates of depression among individuals with PTSD to range from 28% to 84%. The effects of depressed mood on neuropsychological functioning have been well documented (Snyder & Nussbaum, 1998). The high rate of comorbidity and overlap of symptoms between these two disorders makes it extremely difficult to exclude individuals with current depression from PTSD studies. However, it is important to address the presence of comorbid depression and include measures of depression as covariates in PTSD studies.

The previously documented attention difficulties in PTSD (Uddo et al., 1993; Vasterling et al., 1998, 2002) also complicate the interpretation of lower scores on memory measures in this disorder. One possible explanation for memory difficulties in PTSD is that explicit memory performance may be impacted by impaired attention resources during processing. Siegel (1995) and others have theorized that the heightened emotional reactivity in those with PTSD disrupts attentional resources. Because attention and concentration difficulties are symptoms of PTSD, and attentional deficits have been documented in veterans with PTSD, it is possible that observed differences in memory actually reflect impaired attention. Impaired attention prevents sufficient registration of information, which in turn prevents consolidation and retrieval of memory. Gilbertson et al. (2001) found that after controlling for attentional differences, most neuropsychological tasks (executive functioning, perceptual motor speed, visual–spatial skills) were not altered in PTSD, with the exception of explicit memory functioning, as measured by the Wechsler Memory Scale—Third Edition (WMS–III; Wechsler, 1997b).

In the present study, we attempted to control for several potentially confounding factors that often complicate interpretations of PTSD neurocognitive studies. By using a 2 × 2 factorial design, examining groups with and without diagnoses of PTSD and with and without histories of alcohol abuse, we examined the independent and interactive effects of PTSD and alcohol. We defined history of alcohol abuse as a diagnosis of abuse or dependence within the last 5 years, on the basis of previous research suggesting neuropsychological deficits in alcoholics for several years postsobriety but not 5 or more years postsobriety (see Parsons, 1996, for a review). In addition, we statistically controlled for depression, vocabulary, and education level. To control for the role of attention, we then analyzed differences in neuropsychological performance after covarying for a measure of attention. Our primary hypothesis was that PTSD is associated with decreased performance in domains of verbal learning and memory, and working memory, attention, and processing speed when the effects of alcohol, education, vocabulary, and depression symptoms are controlled for. We also hypothesized that alcohol abuse history would be associated with decreased performance in visual memory and visual–spatial domains. We did not predict a PTSD × Alcohol interaction effect on any measure.

Method

Participants

Two hundred and forty-four male and female veterans, ranging in age from 22 to 60 years, were recruited from the San Francisco Veteran's Affairs Medical Center and from the community by using advertisements in the media for a study on magnetic resonance imaging and neuropsychological functioning in veterans. None of the participants were inpatients at the time of the study. An initial screening interview was performed, and written informed consent was obtained after participants were provided with a complete description of the study. The study protocol and consent form was approved by the Committee on Human Research at the University of California, San Francisco. Eleven participants with a history of head trauma, prolonged loss of consciousness (> 10 min), neurological disorder, or systemic illness affecting central nervous system function (including all neurologic disorders and diabetes) were excluded. Twenty-eight participants who were diagnosed during the screening interview with past or current alcohol abuse and dependence, lifetime history of psychotic disorder or bipolar disorder, and drug abuse or dependence within the previous 6 months were also excluded. In addition, 54 veterans were excluded because they did not meet appropriate PTSD criteria for the study, 15 veterans dropped out of the study after the initial interview, and 8 veterans were excluded because of positive toxicology screens.

The final sample consisted of 128 veterans in four groups. Groups were divided into participants with and without PTSD (PTSD+ and PTSD–, respectively) and with and without a history of alcohol abuse or dependence in the past 5 years (ETOH+ and ETOH–, respectively; ETOH = ethanol, or alcohol). Thirty veterans were identified as PTSD+/ETOH+, 37 veterans were identified as PTSD+/ETOH–, 30 veterans were identified as PTSD–/ETOH+, and 31 veterans were identified as PTSD–/ETOH–.

Demographic characteristics (age, gender, ethnicity, and education), trauma histories, and clinical and background variables [Clinician Administered PTSD Scale (CAPS, Blake et al., 1995); Lifetime Drinking History (LDH, Skinner & Sheu, 1982); Wechsler Adult Intelligence Scale—Third Edition (WAIS–III), Vocabulary (Wechsler, 1997a); and Symptom Checklist-90-R (SCL-90-R, Derogatis, 1994) Depression scale] are summarized in Table 1. The groups did not differ by age or gender, but the groups that were ETOH+ had fewer years of education than the other groups. As expected, groups that were PTSD+ had higher CAPS scores than groups that were PTSD–, but CAPS score differences between groups PTSD+ with and without alcohol abuse were not significant. The groups differed substantially by lifetime drinking, with both groups PTSD+ and ETOH+ having significantly higher scores. The groups differed significantly by current drinking totals in the past 3 months, with groups ETOH+ having significantly higher scores than groups ETOH–. Post hoc analyses revealed that the group identified as PTSD+/ETOH+ did not differ from the group identified as PTSD–/ETOH+ on number of drinks in the past 3 months. Groups that were PTSD+ had significantly higher SCL-90-R Depression subscale scores, as well as lower WAIS–III Vocabulary scores, than groups that were PTSD–. The participants were ethnically diverse although predominantly White (73%). The groups were comparable in ethnic composition. English was the dominant language for all participants.

Table 1.

Demographic, Clinical, and Background Variables

PTSD+/ETOH+ (n = 30)
 PTSD+/ETOH− (n = 37)
 PTSD−/ETOH+ (n = 30)
 PTSD−/ETOH− (n = 31)
Variable M SD % M SD % M SD % M SD % F or χ2 p Significant contrasts
Age 48.57 7.7 47.89 9.4 43.60 12.0 46.42 9.6 None
    Main effect for PTSD F(3, 124) = 3.46 .065
    Main effect for ETOH F(3, 124) = 0.384 .537
    Interactive effect F(3, 124) = 1.02 .315
Education 13.50 1.6 14.89 2.4 14.17 1.7 15.39 2.0
    Main effect for PTSD F(3, 124) = 2.69 .104
    Main effect for ETOH F(3, 124) = 13.58 .000 ETOH+ < ETOH−
    Interactive effect F(3, 124) = 0.059 .809
Gender χ2(3, N = 128) = 0.09 .880 None
    Men 93 84 96 84
    Women 7 16 4 16
Ethnicity None
    Asian 3 3 0 3
    Black 21 22 10 26
    Hispanic 3 6 10 0
    White 73 68 80 71
CAPS total score 65.16 16.93 65.13 19.66 3.07 4.81 0.87 2.08
    Main effect for PTSD F(3, 124) = 704.32 .000 PTSD+ > PTSD−
    Main effect for ETOH F(3, 124) = 0.207 .650
    Interactive effect F(3, 124) = 0.218 .641
SCL-90-Depression subscale 1.77 0.72 1.85 0.96 0.70 0.47 0.46 0.72
    Main effect for PTSD F(3, 124) = 85.14 .000 PTSD+ > PTSD−
    Main effect for ETOH F(3, 124) = 0.346 .557
    Interactive effect F(3, 124) = 1.40 .240
WAIS-III Vocabulary 46.40 10.63 50.08 9.58 51.47 7.54 53.87 8.17
    Main effect for PTSD F(3, 124) = 7.55 .007 PTSD+ < PTSD−
    Main effect for ETOH F(3, 124) = 3.56 .061
    Interactive effect F(3, 124) = 0.157 .693
LDH total drinks 83,745 86,234 21,657 38,050 45,950 41,442 15,289 44,925
    Main effect for PTSD F(3, 123) = 5.03 .027 PTSD+ > PTSD−
    Main effect for ETOH F(3, 123) = 22.17 .000 ETOH+ > ETOH−
    Interactive effect F(3, 123) = 2.55 .113
LDH 3-month drink total 90.02 209.75 26.23 54.12 166.41 240.48 53.71 105.09
    Main effect for PTSD F(1, 122) = 3.08 .082
    Main effect for ETOH F(1, 122) = 8.90 .003 ETOH+ > ETOH−
    Interactive effect F(1, 122) = 0.683 .410
Other diagnoses
    MDD 27 43 3 6 χ2(3, N = 128) = 4.55 .033 PTSD+ > PTSD−
    Anxiety disorders 40 30 10 3 χ2(3, N = 128) = 3.90 .048 PTSD+ > PTSD−
    Past drug abuse or dependence 53 32 50 6 χ2(3, N = 128) = 18.57 .000 PTSD+ > PTSD−, ETOH+ > ETOH−
Current psychiatric medication use Traumatic event 56 30 43 26 χ2(3, N = 128) = 7.80 .050 PTSD+ > PTSD−
    Vietnam combat 63 57 10 10
    Gulf War combat 3 14 0 0
    Military-related 24 21 17 16
    Nonmilitary 13 8 46 33
    None 0 0 17 42
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Note. All scores are raw scores. Military-related traumas include accidents or physical or sexual assaults. Nonmilitary traumas include child abuse and accidents. PTSD+ = current diagnosis of posttraumatic stress disorder (PTSD); PTSD− = no history of diagnosis of PTSD; ETOH = ethonol, or alcohol; ETOH+ = diagnosis of alcohol abuse or dependence in the past 5 years; ETOH− = no diagnosis of alcohol abuse or dependence in the past 5 years; CAPS = Clinician Administered PTSD Scale; SCL-90-R = Symptom Checklist—90-R; WAIS—III = Wechsler Adult Intelligence Scale—Third Edition; LDH = Lifetime Drinking History; MDD = major depressive disorder.

Information about comorbid mood and anxiety disorder diagnoses and past drug abuse or dependence diagnoses are also included in Table 1. There were significant differences between groups that were PTSD+ and PTSD– in rates of major depressive disorder and anxiety disorders (including obsessive–compulsive disorder, panic disorder, generalized anxiety disorder, or social phobia). Mood and anxiety disorders are so common among individuals with PTSD that they are often conceptualized as part of the PTSD psychopathology (Sutker, Uddo-Crane, & Allain, 1991). Thus, participants were not excluded from the study on the basis of these comorbidities. Psychiatric medication use is also summarized in Table 1. Participants with PTSD had significantly higher rates of psychiatric medication (primarily antidepressant) use. Only eight participants out of the entire sample were taking benzodiazepines, evenly distributed among the four groups, χ2(3, N = 128) = 1.11, p = .78.

Measures

Structured diagnostic interviews

Participants were interviewed by a clinical psychologist with extensive PTSD experience in using the Structured Clinical Interview for DSM–IV Diagnosis (First, Spitzer, Williams, & Gibbon, 1996) and in using the CAPS, and they were classified into groups. A second rater listened to 20% of the taped CAPS interviews, and interrater reliability was obtained. The intraclass correlation coefficient for the two raters was .984. The Structured Clinical Interview for DSM–IV Diagnosis was used to diagnose comorbid psychiatric disorders.

Veterans with past but not current PTSD, or current subsyndromal PTSD, were not included in the study. Veterans with a history of alcohol abuse or dependence in the past 5 years were included in groups that were ETOH+, whereas veterans with no history of alcohol abuse or dependence anytime in the past 5 years were included in groups that were ETOH–. In the group identified as PTSD+/ETOH+, 25 of the 30 participants had alcohol dependence diagnoses and 5 had alcohol abuse diagnoses. In the group identified as PTSD–/ETOH+, 24 of the 30 participants had alcohol dependence diagnoses, compared with 6 with abuse diagnoses.

SCL-90-R

Participants completed the SCL-90-R, a 90-item self-report clinical rating scale of psychiatric symptomatology. Of interest in the current study was the Depression subscale score, which consists of 13 items of depressive symptomatology such as feelings of hopelessness, worthlessness, and suicidality.

Lifetime drinking history

We obtained lifetime alcohol use histories on all of the participants by using the LDH.

Neuropsychological variables

All participants were administered a battery of neuropsychological tests that assessed three domains of cognitive functioning: verbal memory; visual memory and visual–spatial skills; and attention, working memory, and processing speed.

Verbal memory

To assess verbal memory and learning, we used three variables from the California Verbal Learning Test (CVLT; Delis, Free-land, Kramer, & Kaplan, 1988). The CVLT measures both recall and recognition of word lists over a number of trials. The Trial 1 score provides a measure of initial acquisition of verbally presented material, whereas the Total Trials 1−5 score provides a measure of verbal learning. The Long-Delay Free Recall score reflects the test takers’ ability to retain the word list over a period of 20 min, and is a measure of delayed verbal memory. Participants also completed the Logical Memory I and II subtests of the WMS–III. For Logical Memory I, the participant listens to two stories read by the examiner and immediately after hearing each story, is asked to retell it from memory. Thirty min later, the participant is asked to retell the stories, which constitutes the Logical Memory II score. The Percent Retention score is a measure of how much of the stories the participant remembered relative to his or her immediate recall. Low scores on the Logical Memory subtests suggest weaknesses in learning of or memory for orally presented narratives, whereas low scores on Percent Retention suggest difficulties with retaining auditory narratives after a delay.

Visual memory and visual–spatial skills

To assess short and long-term visual memory, we used the Visual Immediate Index and Visual Delayed Index scores of the WMS–III. These indices are composed of the Faces and Family Pictures subtests, immediate and delayed recall. In the Faces subtest, the participant is asked to remember photographs of faces and then is shown a series of faces and must identify whether the face was one he or she was asked to remember. For the Family Pictures subtest, the participant is shown scenes with family members and asked to remember aspects of the scene. Whereas Faces is a test of recognition, Family Pictures is a test of recall, but low scores on both indicate memory deficits with visually presented material. For Faces II and Family Pictures II, which make up the Visual Delayed Index, participants are asked to identify or recall the faces or family pictures 30 min later. Visual–spatial skill was assessed by using the Block Design subtest of the WAIS–III, which requires the participant to replicate pictures of geometric patterns with two-color blocks.

Working memory, attention, and processing speed

Working memory and attention were assessed by using the Letter Number Sequencing, Spatial Span, and Digit Span subtests of the WMS–III. For the Letter Number Sequencing subtest, a measure of auditory working memory, the participant is read a series of numbers and letters and is asked to repeat them, saying the numbers first in ascending order and then the letters in alphabetical order. In the Spatial Span subtest, the examiner taps cubes on a board in a specified sequence, and the participant must tap the blocks in the same sequence. The Digit Span subtest consists of Digit Span Forward, in which the participant is asked to repeat back a series of digits in the same sequence as the examiner presented, and Digit Span Backward, in which the examinee must repeat back the digits but in reverse order. Digit Span Forward is a measure of focused attention, whereas Digit Span Backward demands more effort from working memory, requiring the participant to manipulate information stored in the short-term memory (Wechsler, 1997b). To assess processing speed, we administered the Digit Symbol subtest of the WAIS–III. The examiner is presented with a key of numbers corresponding with symbols and is required to use the key to copy the symbols under the numbers. The task measures psychomotor speed and set shifting.

Intellectual functioning

Participants were administered several subtests of the WAIS–III, and the Vocabulary subtest score was used as an estimate of intellectual functioning. The Vocabulary subtest is often used as a “hold” test from which estimates of premorbid functioning are derived in brain-injured populations (Lezak, 1995).

A clinical psychologist administered the neuropsychological battery.The neuropsychological tests were administered in the same order for all participants. The first 11 participants did not receive some tests (Digit Symbol, Logical Memory I and II, Letter Number Sequencing) that were added to the battery after their completion. Testing took approximately 2 hours including a midsession 15-min break. Participants were instructed to abstain from using alcoholic beverages and were breathalyzed before neuropsychological testing. Participants also had urinalysis for drug toxicology on the day of neuropsychological assessment. Data from 2 participants who had positive toxicology screens were excluded from the analysis.

Data Analysis

We conducted individual analyses of covariance (ANCOVAs) on measures from three domains of neuropsychological functioning—verbal memory; visual–spatial and visual memory; and attention, working memory, and processing speed. In each analysis, we covaried for background or clinical variables in which there were differences between groups, such as education, vocabulary performance, and depression. Post hoc analyses of group effects were made for each analysis, adjusting for multiple comparisons by using a modification of Bonferroni's method for correlated multiple outcomes, grouping together these domain variables (Sankoh, Huque, & Dubey, 1997). Our four-group model accounts for alcohol abuse history in the past 5 years but may not adequately account for current alcohol use. Therefore, we next conducted analyses on variables previously seen to be significantly different between groups that were PTSD+ and PTSD–, covarying for level of current alcohol use determined by total drinks in the past 3 months on the LDH. We also conducted ANCOVAs on all neuropsychological measures, comparing participants with lifetime histories of drug dependence or abuse with participants without drug dependence or abuse. If any differences were detected, we then entered drug history as a covariate to determine if any previously significant differences seen between groups that were PTSD+ and PTSD– remained after controlling for drug history. Finally, to control for attention in secondary analyses, we conducted individual ANCOVAs on variables with significant differences in the initially specified ANCOVAs, using the Digits Forward score as a covariate.

Results

Primary Analyses

Verbal memory

We conducted individual ANCOVAs on six measures of verbal memory—CVLT total score, Trial 1 score, and Long-Delay Free Recall score, and the WMS–III Logical Memory I, Logical Memory II, and Logical Memory Percent Retention scores. We controlled for education, Vocabulary, and depression. Because depression and PTSD share several symptoms, we constructed a residualized variable of the SCL-90-R Depression sub-scale that partials out shared variance with the CAPS, and we entered this residualized variable into the model as a covariate. Post hoc analyses of group effects adjusting for multiple comparisons were then conducted with a modification of Bonferroni's method for correlated multiple outcomes. Results are shown in Table 2. There was a main effect for PTSD on both CVLT total score and Trial 1 score, and we did not find a main effect for alcohol or an interaction effect. There were no significant differences at the Bonferroni-adjusted alpha level between groups on the three Logical Memory measures, although there was a trend for lower Logical Memory Percent Retention in groups that were PTSD+.

Table 2.

Verbal Memory Performance

PTSD+/ETOH+ (n = 30)
 PTSD+/ETOH− (n = 37)
 PTSD−/ETOH+ (n = 30)
 PTSD−/ETOH− (n = 31)
Test M SD M SD M SD M SD F p Significant contrasts (Bonferroni alpha = .019)
CVLT Trials 1−5 44.50 11.29 46.49 10.20 52.30 9.90 52.26 9.36
    Main effect for PTSD F(3, 121) = 7.863 .006 PTSD+ < PTSD−
    Main effect for ETOH F(3, 121) = 0.089 .766
    Interactive effect F(3, 121) = 0.349 .556
CVLT Trial 1 5.93 1.89 5.84 1.89 7.00 1.68 7.55 1.82
    Main effect for PTSD F(3, 121) = 12.91 .000 PTSD+ < PTSD−
    Main effect for ETOH F(3, 121) = 0.219 .641
    Interactive effect F(3, 121) = 1.14 .288
CVLT Long-Delay Free Recall 9.70 3.34 10.92 2.63 11.37 2.71 11.10 2.84 None
    Main effect for PTSD F(3, 121) = 0.710 .401
    Main effect for ETOH F(3, 121) = 0.058 .810
    Interactive effect F(3, 121) = 2.36 .127
WMS—III Logical Memory I Recall 46.58 9.40 45.34 10.20 49.37 9.20 49.68 8.00 None
    Main effect for PTSD F(3, 112) = 0.416 .520
    Main effect for ETOH F(3, 112) = 1.65 .201
    Interactive effect F(3, 112) = 0.232 .631
WMS—III Logical Memory II Recall 30.38 6.96 27.91 7.73 32.07 6.40 32.81 5.77 None
    Main effect for PTSD F(3, 112) = 1.397 .240
    Main effect for ETOH F(3, 112) = 4.743 .032
    Interactive effect F(3, 112) = 1.988 .161
WMS—III Logical Memory % Retention 89.04 7.10 85.16 10.30 91.33 8.40 91.35 6.50 None
    Main effect for PTSD F(3, 112) = 4.954 .028
    Main effect for ETOH F(3, 112) = 3.462 .065
    Interactive effect F(3, 112) = 1.509 .222
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Note. All scores are raw scores. All analysis of covariance covaried for education, WAIS—III Vocabulary raw score, and SCL-90-R Depression residualized score. PTSD+ = current diagnosis of posttraumatic stress disorder (PTSD); PTSD− = no history of diagnosis of PTSD; ETOH = ethanol, or alcohol; ETOH+ = diagnosis of alcohol abuse or dependence in the past 5 years; ETOH− = no diagnosis of alcohol abuse or dependence in the past 5 years; CVLT = California Verbal Learning Test; WMS—III = Wechsler Memory Scale—Third Edition; WAIS—III = Wechsler Adult Intelligence Scale—Third Edition.

Working memory, attention, and processing speed

We conducted three separate ANCOVAs for measures of working memory (WMS–III Letter Number Sequencing and Spatial Span), attention (WAIS–III Digit Span), and processing speed (WAIS–III Digit Symbol). Results are shown in Table 3. We again adjusted for multiple comparisons of these variables with Bonferroni's method. After covarying for education, Vocabulary, and the residualized SCL-90-R Depression score, there was a main effect for PTSD on Letter Number Sequencing, Digit Span, and Digit Symbol. There were no main effects for alcohol or interaction effects on any of these measures.

Table 3.

Working Memory, Attention, and Processing Speed Performance

PTSD+/ETOH+ (n = 30)
 PTSD+/ETOH− (n = 37)
 PTSD−/ETOH+ (n = 30)
 PTSD−/ETOH− (n = 31)
Test M SD M SD M SD M SD F p Significant contrasts (Bonferroni alpha = .025)
WMS—III Spatial Span 15.17 3.22 15.19 3.50 16.10 3.32 15.90 3.02
    Main effect for PTSD F(3, 120) = 3.125 .574 None
    Main effect for ETOH F(3, 120) = 7.978 .370
    Interactive effect F(3, 120) = 0.029 .865
WMS—III Letter Number Sequencing 10.00 1.96 9.84 2.47 11.93 2.45 11.58 2.19
    Main effect for PTSD F(3, 112) = 12.481 .001 PTSD+ < PTSD−
    Main effect for ETOH F(3, 112) = 1.010 .317
    Interactive effect F(3, 112) = 0.140 .709
WMS—III Digit Span 16.27 3.92 15.30 4.21 18.70 3.85 19.52 4.46
    Main effect for PTSD F(3, 121) = 12.90 .000 PTSD+ < PTSD−
    Main effect for ETOH F(3, 121) = 1.06 .306
    Interactive effect F(3, 121) = 2.04 .156
WAIS—III Digit Symbol 62.04 13.33 60.17 16.63 71.17 12.54 72.27 15.38
    Main effect for PTSD F(3, 109) = 11.726 .001 PTSD+ < PTSD−
    Main effect for ETOH F(3, 109) = 0.225 .636
    Interactive effect F(3, 109) = 0.155 .695
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Note. All scores are raw scores. All analyses of covariance covaried for education, WAIS—III vocabulary raw score, and SCL-90-R Depression residualized score. PTSD+ = current diagnosis of posttraumatic stress disorder (PTSD); PTSD− = no history of diagnosis of PTSD; ETOH = ethanol, or alcohol; ETOH+ = diagnosis of alcohol abuse or dependence in the past 5 years; ETOH− = no diagnosis of alcohol abuse or dependence in the past 5 years; WMS—III = Wechsler Memory Scale—Third Edition; WAIS—III = Wechsler Adult Intelligence Scale—Third Edition.

Visual memory

We conducted three ANCOVAs for measures of visual–spatial reasoning (Block Design) and visual memory (WMS–III Visual Immediate Memory Index and WMS–III Visual Delayed Memory Index). Results are shown in Table 4. Adjusted multiple comparison alphas were again used for these analyses. After covarying for education, Vocabulary, and the residualized SCL-90-R Depression score, we did not find either main effects for PTSD and alcohol or an interaction effect for Block Design. There was a main effect for alcohol on the WMS–III Visual Immediate Index. There were no main effects for PTSD on any measures, and there were no interaction effects.

Table 4.

Visual—Spatial and Visual Memory Performance

PTSD+/ETOH+ (n = 30)
 PTSD+/ETOH− (n = 37)
 PTSD−/ETOH+ (n = 30)
 PTSD−/ETOH− (n = 31)
Test M SD M SD M SD M SD F p Significant contrasts (Bonferroni alpha = .028)
WMS—III Visual
    Immediate Index 17.33 4.80 20.59 3.70 18.73 4.10 20.55 14.90
    Main effect for PTSD F(3, 121) = 0.005 .946
    Main effect for ETOH F(3, 121) = 6.411 .013 ETOH+ < ETOH−
    Interactive effect F(3, 121) = 0.576 .449
WMS—III Visual
    Delayed Index 18.10 4.70 20.59 4.30 18.50 3.90 20.77 4.70 None
    Main effect for PTSD F(3, 121) = 1.031 .312
    Main effect for ETOH F(3, 121) = 4.218 .042
    Interactive effect F(3, 121) = 0.001 .979
WAIS—III Block Design 38.73 11.52 38.11 11.22 41.33 12.08 41.61 12.08
    Main effect for PTSD F(3, 121) = 0.304 .583 None
    Main effect for ETOH F(3, 121) = 0.476 .492
    Interactive effect F(3, 121) = 0.059 .808
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Note. All scores are raw scores. All analyses of covariance covaried for education, WAIS—III vocabulary raw score, and SCL-90-R Depression residualized score. PTSD+ = current diagnosis of posttraumatic stress disorder (PTSD); PTSD− = no history of diagnosis of PTSD; ETOH = ethanol, or alcohol; ETOH+ = diagnosis of alcohol abuse or dependence in the past 5 years; ETOH− = no diagnosis of alcohol abuse or dependence in the past 5 years; WMS—III = Wechsler Memory Scale—Third Edition; WAIS—III = Wechsler Adult Intelligence Scale—Third Edition.

Secondary Analyses

Having found lower scores in groups that were PTSD+ compared with groups that were PTSD– on measures of verbal memory, attention, and processing speed, we then conducted univariate analyses covarying for current alcohol use by using a measure of total number of drinks in the past 3 months obtained from the LDH. After covarying for current level of alcohol use, in addition to education, Vocabulary, and SCL-90-R Depression residualized score, the main effects for PTSD persisted on all measures: the CVLT Total Score, F(1, 120) = 7.10, p = .009; Digits Forward, F(1, 118) = 14.66, p = .000; and Digit Symbol, F(1, 108) = 11.33, p = .001.

Given the findings of differences in short-term visual memory performance between groups that were ETOH+ and ETOH–, we conducted bivariate correlations of WMS–III Visual Immediate Index and current alcohol use amount by group. None of the correlations were significant, suggesting that frequency of recent alcohol use is not related to visual memory impairment.

We also conducted ANCOVAs to determine if participants with lifetime drug abuse or dependence diagnoses performed differently on the neuropsychological tests. After covarying for education, Vocabulary, and SCL-90-R Depression residualized score, there was a significant difference between groups on Digit Symbol performance, F(1, 108) = 5.90, p = .017, with the drug history group (M = 61.62, SD = 13.25) showing decreased performance compared with the group without lifetime substance abuse diagnoses (M = 69.36, SD = 15.89). We then conducted ANCOVAs, entering drug history as an additional covariate, comparing groups that were PTSD+ and PTSD– on the Digit Symbol measure, and there remained a significant difference between groups, F(1, 109) = 8.91, p = .003.

Univariate analyses were next conducted to determine if the verbal memory, working memory, and processing speed differences seen in the groups that were PTSD+ were a function of attentional problems. After covarying for attention by using the Digits Forward score on the Digit Span subtest—in addition to covarying for education, SCL-90-R Depression residualized score, and Vocabulary—we still found a significant difference on CVLT total score, F(1, 120) = 4.96, p = .028; CVLT Trial 1, F(1, 120) = 8.30, p = .005; Letter Number Sequencing, F(1, 112) = 16.23, p = .030; and Digit Symbol, F(1, 110) = 8.67, p = .004.

Discussion

The results confirmed our hypotheses that PTSD would be associated with decreased performance on measures of verbal learning, working memory, attention, and processing speed. Alcohol abuse history was associated with decreased performance on a measure of immediate visual memory. There were no interaction effects of PTSD and alcohol. After covarying for several potential confounds—including education, an estimate of intellectual functioning, depression, current level of alcohol use, and drug history—differences between individuals with and without PTSD remained significant. Given these results, we can more conclusively determine that lower scores on tests of verbal learning, working memory, attention, and processing speed among the participants who were PTSD+ in this sample are not due to the confounding effects of alcohol or depression.

Our findings suggest that memory deficits are not global but restricted to specific tasks. On memory measures, veterans with PTSD showed deficiencies relative to veterans without PTSD in the initial registration and learning of word lists but not on retention. Although we found differences on CVLT performance, we did not see differences between participants who were PTSD+ or PTSD– on paragraph recall, suggesting that verbal memory may be more compromised when the task does not involve a narrative context. In the group with PTSD, working memory was impaired when the task involved auditory material (i.e., Digit Span, Letter Number Sequencing) but not visual material (Spatial Span). Similarly, participants with PTSD did not exhibit deficits on immediate or delayed visual memory. Consistent with previous research (Vasterling et al., 1998, 2002; Yehuda et al., 1995), these findings of weaknesses in tasks involving attention, working memory, and new learning are suggestive of frontal-limbic abnormalities.

These results also add to the alcoholism literature, suggesting effects of alcohol abuse history on short-term visual memory performance. Because visual memory but not verbal memory was compromised in our participants with significant alcohol abuse histories, our findings offer partial support for the “right hemisphere hypothesis” of alcoholism, suggesting that the right hemisphere may be particularly vulnerable to the effects of alcoholism. These results are consistent with other studies showing impaired visual memory in recently detoxified alcoholics (Donat, 1986; Leber et al., 1981). However, in our sample there was not a relationship between frequency of recent alcohol use and visual memory performance, suggesting that impairments seen are due to a longer term history of alcohol abuse or dependence or to genetic or early developmental risk factors for alcohol abuse. These findings highlight the continued need for alcohol abuse researchers to examine visual–spatial and visual memory performance in alcoholics well past the acute withdrawal period. They also suggest the need for familial studies of gene markers and neurocognitive testing to determine if visual–spatial and visual memory deficits are heritable risk factors for alcohol abuse.

Because the groups that were PTSD+ had significantly lower scores on a measure of attention, it was possible that observed differences in verbal memory actually reflected impaired attention. After covarying for the effects of passive auditory attention, the differences on CVLT measures, Letter Number Sequencing, and Digit Symbol remained significant. These results suggest that difficulties in both verbal learning and memory as well as set shifting and mental flexibility are not merely an artifact of reduced passive auditory attention. However, it may also be that the measure of attention used in this study is not sufficiently sensitive to detect alterations in attention that might account for effects on memory. Future studies might continue to study this hypothesis, using a measure of attention such as the Continuous Performance Test (Conners, 1994).

Several limitations should be noted when interpreting the results of this study. First, it is difficult to adequately identify individuals with significant alcohol abuse histories. By using the categorical DSM–IV diagnosis to identify our participants with a history of alcohol abuse, we may be including individuals in our groups with ETOH– who are binge drinkers yet do not meet the diagnostic criteria of abuse or dependence. In addition, many of our participants with a history of alcohol abuse were presently in remission, with some having been sober for nearly 5 years. As alcohol effects have been most consistently identified in current or newly abstinent drinkers (e.g., Beatty, Tivis, Stott, Nixon, & Parsons, 2000; Grant, 1987), it is certainly possible that the variation in recency of alcohol abuse or dependence limited our ability to detect a significant effect for alcohol. We attempted to account for this limitation by covarying for current alcohol use in secondary analyses of measures that detected differences in individuals who are PTSD+ and PTSD–; all differences previously seen remained significant. However, our study had limited power to detect effects of recent drinking given the small number of recent drinkers. It is important to note that post hoc analyses revealed the group PTSD+/ETOH+ did not differ from the group PTSD–/ETOH+ on number of drinks in the past 3 months, underscoring our success in controlling for recent heavy alcohol use, arguably the most important PTSD/alcohol confound in neurocognitive testing.

Ideally, neuropsychological studies comparing group differences should match participants in each group on key demographic variables, such as age and education, which will likely have an impact on the dependent variable. When groups are not matched, as was the case in the current study with education level, a less satisfactory approach applies ANCOVA, with differences in demographic variables controlled for (Adams, Brown, & Grant, 1985). It can be particularly difficult to match participants in PTSD and alcoholism research on education level, but researchers should continue to strive to do so.

In addition, our neuropsychological battery did not include systematic measures of executive function. Past studies have included measures of executive functioning (e.g., Stein et al., 2002), and future researchers might continue to test these skills by using a design similar to ours. Finally, it is possible that exposure to toxins such as Agent Orange may worsen veterans’ neuropsychological functioning, a possibility not explored in the present study. Future studies might explore in more detail the deployment and toxic exposure histories of enlisted military personnel. Recognizing these limitations, the present findings add to the literature documenting neuropsychological differences in individuals with and without PTSD. Verbal and working memory difficulties were more prominent than visual impairments in veterans with PTSD.

Most important to note is that these differences cannot be accounted for by alcohol abuse history, depression, or attentional disturbances.

Acknowledgments

This study was supported by the Sierra Pacific (VISN 21) Mental Illness Research, Education, and Clinical Center (MIRECC).

Contributor Information

Kristin W. Samuelson, San Francisco Veteran's Affairs Medical Center and California School of Professional Psychology at Alliant International University

Thomas J. Metzler, San Francisco Veteran's Affairs Medical Center and University of California, San Francisco

Johannes Rothlind, San Francisco Veteran's Affairs Medical Center.

Gerard Choucroun, San Francisco Veteran's Affairs Medical Center.

Thomas C. Neylan, San Francisco Veteran's Affairs Medical Center and University of California, San Francisco

Maryanne Lenoci, San Francisco Veteran's Affairs Medical Center.

Clare Henn-Haase, San Francisco Veteran's Affairs Medical Center and University of California, San Francisco.

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