May 2012  << Back  

  Can't open the PDF? Click here for help.



Recovery of cognitive functioning in patients with co-occurring bipolar disorder and alcohol dependence during early remission from an acute mood episode

Boaz Levy, PhD

Mental Health Counseling, Department of Counseling and School Psychology, University of Massachusetts, Boston, MA, USA, Department of Psychiatry, Harvard Medical School/McLean Hospital, Belmont, MA, USA

Emily Manove, JD

Psychology Department, University of Massachusetts, Boston, MA, USA

Roger D. Weiss, MD

Department of Psychiatry, Harvard Medical School/McLean Hospital, Belmont, MA, USA

OBJECTIVE: This study aimed to examine cognitive recovery in patients with co-occurring bipolar disorder (BD) and alcohol dependence (AD) during remission from an acute mood disturbance.

METHOD: Fifty-five adult inpatients with bipolar I disorder (BD I) completed a neuropsychological battery, mood measures, and substance abuse measures upon discharge from the hospital and at a 3-month follow-up. Analyses provided group comparisons on these measures between patients who presented with co-occurring AD (n = 21) in the year prior to hospital admission and patients without a substance use disorder (SUD; n = 34).

RESULTS: Multivariate analyses of variance detected group differences on measures of visual memory, verbal memory, and executive functioning, using previous number of psychiatric admissions and age of onset of BD as covariates. These differences occurred both at discharge and follow-up. Between discharge and follow-up, the group without SUD exhibited more substantial gains than the group of dually diagnosed patients on free recall of verbal and visual materials and on a measure of cognitive flexibility.

CONCLUSIONS: Patients with co-occurring BD and AD may suffer from more severe cognitive dysfunction and less favorable recovery of cognitive deficits than patients without SUD over the course of remission from a mood episode.

KEYWORDS: bipolar disorder, cognitive impairment, alcohol dependence, dually diagnosed patients, inpatients



The co-occurrence of bipolar disorder (BD) and substance use disorders (SUD) represents a serious public health problem.1-4 Among all psychiatric disorders, BD has a particularly high prevalence of SUD in general5 and alcohol abuse (AA) and dependence (AD) in particular.6 SUD may pose a major obstacle to the treatment of BD,7-11 as it typically predicts unfavorable rates of remission,7,12-16 a more severe course of illness,2,17-19 and limited response to treatment.20-22 In addition, it may exacerbate psychosocial disability,8,20-23 increase the cost of care,1,4,8 and reduce the quality of life of patients.20

Several recent studies have advanced the hypothesis that cognitive impairment may contribute to illness severity and disability in dually diagnosed BD patients.24-26 BD is associated with cognitive dysfunction that often persists into periods of euthymia.27 Similarly, patients with AD suffer from significant cognitive impairment, even after extended periods of abstinence.28-34 Moreover, in both BD and AD, deficits in executive functioning are particularly predictive of poor prognosis and psychosocial disability.35-43 It is therefore possible that people who suffer from both conditions may be at greater risk for developing debilitating cognitive impairment and a more severe course of illness.24-26

Three of the studies that examined cognitive functioning in dually diagnosed bipolar I disorder (BD I) patients recruited individuals in remitted states. The first study26 reported additional decrements in executive functions in euthymic BD patients with a history of AD compared with BD patients without SUD. A more recent study25 found poorer inhibitory control among euthymic BD patients with a history of a wide range of alcohol use disorders relative to patients without such a history. A third study43 detected no association between cognitive functioning in BD and a history of AA. These studies explored trait-related cognitive deficits in BD/AD, and their focus on euthymic patients aimed to avoid the confounding effects of mood symptoms on cognitive functioning.

Although the causes of cognitive deficits are more difficult to establish in a non-euthymic state, understanding the degree of impairment in symptomatic patients is critically important for practical considerations related to treatment and post-hospital rehabilitation. For this reason, our group conducted a fourth study24 with patients during early remission from a severe episode of mood disturbance. This study reported more severe memory and executive deficits in patients with co-occurring AD than similar patients without SUD at the time of discharge from the hospital. Collectively, these studies are consistent with the hypothesis that cognitive deficits associated with comorbid BD and AD converge to form more severe impairment in dually diagnosed patients.

The current study aimed to examine the recovery of cognitive functions of dually diagnosed BD/AD patients during remission from acute mood disturbance. Dually diagnosed patients may be particularly vulnerable to the effects of cognitive deficits during this sensitive time. The temporal proximity to the peak of both mood disturbance and substance use, coupled with the use and titration of potentially sedating medications over the course of hospitalization, may lead to compromised cognitive states. Negotiating the demanding transition from the minimally-stressful environment of the inpatient unit to less supervised settings after discharge may be highly challenging for patients while at a cognitive ebb. Understanding the cognitive state of dually diagnosed patients when they leave the hospital, as well as the extent of cognitive recovery that occurs after discharge, may therefore be important for developing effective discharge plans and for follow-up care.

The first part of this study was designed to replicate with an independent sample the previous assessment of cognitive functioning that we conducted with dually diagnosed patients before discharge from inpatient care.24 The second part extended this investigation in a longitudinal design, with a follow-up assessment of cognitive functioning 3 months after hospital discharge. Our hypothesis was that dually diagnosed patients would show poorer performance than BD patients without AD at the time of discharge from the hospital. The study further aimed to examine potential group differences in recovery of cognitive functioning at follow-up.



A total of 82 inpatients age 18 to 59 with BD I completed the initial assessment before discharge from McLean Hospital in Belmont, MA. Fifty-five participants completed the second assessment at the 3-month follow-up. Among the 27 participants who did not complete the study (11 with co-occurring AD), 15 were readmitted to the hospital for mood disturbance (3 with co-occurring AD), 7 reported admission to a SUD treatment unit, and 5 maintained an outpatient status (1 with co-occurring AD). A comparison of clinical and cognitive variables between participants who were re-hospitalized and those who completed the current study is summarized in a previous report.44 This prior analysis indicated a more severe mood episode leading to the initial hospitalization as well as greater cognitive deficits among patients who were readmitted to the hospital within 3 months of discharge. Among participants who discontinued the study, comparisons between patients with and without AD revealed no group differences in education, sex, age, mood symptoms at discharge, or in the number or type of medications prescribed for BD. There were no group differences in attrition rate.

Among participants who completed the study, 21 met diagnostic criteria for AD in the past year. In this group, 13 participants reported past abuse or dependence on other drugs. Four of the 13 reported marijuana use, 2 reported cocaine use, and 2 reported opioid use during the month prior to hospital admission. All participants in the study were admitted for an acute mood disturbance, and none required detoxification upon admission to the hospital. From the 55 participants who completed the study, 34 did not report a history of SUD and served as a control group for dually diagnosed patients. In the entire sample, 9 patients were admitted with depression, 12 in a mixed state, and 34 in a manic state. The sample consisted of 30 men and 25 women. Forty-six identified themselves as white, and 9 identified an affiliation with an ethnic minority group. Thirty were single, 14 married, and 11 divorced.

Inclusion/exclusion criteria

All participants in the study were adults who met DSM-IV diagnostic criteria for BD I. At enrollment, all participants were hospitalized. Assignment to the dually diagnosed group required a diagnosis of AD during the 12 months prior to admission. None of the other participants met diagnostic criteria for SUD in the past year. To control for the impact of mood symptoms on test performance, inclusion criteria required a Beck Depression Inventory, Second Edition (BDI-II)45 score <15, a Beck Hopelessness Scale (BHS)46 score <10, and a Young Mania Rating Scale (YMRS)47 score <15. Based on structured interviews and review of medical records, patients with a clear history of neurological illness or injury were excluded from participation.

Diagnosis and procedure

After signing written informed consent, which had been reviewed and approved by the institutional review board of McLean Hospital, participants underwent initial assessment to determine eligibility. This included review of records and verbal communication with the attending psychiatrist. Participants were approached for a diagnostic interview only after the information collected by the research team converged to indicate at least 1 current or past manic episode that could not be attributed to substance use and provided no evidence for psychosis in the absence of mania. An independent confirmation of diagnostic status was attained through a Structured Clinical Interview for DSM-IV48 by a trained clinician. Once the treatment team indicated that a patient was sufficiently stable and approaching discharge, the patient was scheduled for neuropsychological testing 24 to 48 hours prior to discharge.

On the day of testing, the examiner administered the mood and substance use measures, followed by the neuropsychological battery. The session typically ranged from 2.5 to 3.5 hours. After discharge, the treatment team remained in telephone contact with participants on a monthly basis. After approximately 3 months (88 to 102 days), participants returned for a follow-up evaluation, at which time all of the measures were re-administered. Before testing, participants gave urine for a drug screen and had a breath alcohol test. These procedures detected no recent use of alcohol, stimulants, or opioids in any of the participants. Three of the participants tested positive for marijuana but reported no use in the 5 days prior to testing.


Mood measures. To assess residual mood symptoms at the time of testing, participants completed the BDI-II,45 a 21-item self-report instrument that measures the severity of depressive symptoms as listed in the DSM-IV. Participants also filled out the BHS,46 which measures negative attitudes about the future. The BHS consists of 20 1-point aggregated items and offers a true/false response format. The severity of manic symptoms was assessed with the YMRS.47 This 11-item scale with a 0 to 4 or 0 to 8 scoring system is used extensively in clinical and research settings. Ratings were based on patients’ self-reports, clinician observation, and verbal reports of the treatment team. The assessment period covered the 48 hours prior to testing at discharge and 2 weeks prior to follow-up.

Substance use measures. Participants completed the drug and alcohol section of the Addiction Severity Index – 5th edition (ASI-5)49 in the format of a semi-structured interview. This measure provides an assessment of both recent (past 30 days) and lifetime use of alcohol and a variety of other drugs (heroin, methadone, other opioids, barbiturates, other sedatives and tranquilizers, cocaine, amphetamines, cannabis, hallucinogens, and inhalants). To measure actual alcohol consumption and drug use 30 days prior to admission, we used the Timeline Followback method, using a calendar and key date anchors.50,51 This method has been shown to have good psychometric properties with a variety of alcohol-using populations and cross-culturally.52,53 Alcohol measures included the number of standard alcoholic drinks consumed in past 30 days, and the number of days in which alcohol was consumed over the same period. Participants also completed the Alcohol Use Disorder Identification Test (AUDIT),54 a 10-item questionnaire (score range: 0 to 40) assessing potential problems that often result from excessive drinking (eg, blackouts, accidents) occurring during the year prior to the assessment.

The neuropsychological battery. The neuropsychological assessment covered 5 domains of cognitive functioning—IQ, attention and working memory, verbal memory, processing of complex visual material and visual memory, and executive functioning—employing a battery with well-documented norms and satisfactory estimates of reliability and validity.

IQ. Participants completed the Wechsler Abbreviated Scale of Intelligence,55 Vocabulary and Block Design subtests. Vocabulary (a measure of verbal intelligence) requires participants to provide definitions to words, and Block Design (a measure of nonverbal intelligence) requires the manipulation of colored blocks to copy designs that progress in gradual complexity.

ATTENTION AND WORKING MEMORY. To assess auditory attention and working memory, the battery included the Digit Span subtest from the Wechsler Adult Intelligence Scale – Third Edition.56 On this test, participants are asked to repeat a string of digits forward and then backwards. Visual scanning was assessed with the Letter and Symbol Cancellation Task,57 where participants are required to circle target symbols or letters scattered amid distracters, using a pencil in maximum speed. Participants also completed the Trail Making Test, Parts A and B.58,59 On this test, participants are required to connect consecutive numbers on a page (Trail A) and alternate between ascending sequences of letter and numbers (Trail B) with maximum speed.

VERBAL MEMORY. The acquisition of auditory verbal information was assessed with a list learning task (ie, California Verbal Learning Test II – Short Form [CVLT-II])60 and memory of passages (Logical Memory from Wechsler Memory Scale-III).61 The CVLT-II measures the number of words immediately recalled from the list of 9 words across 4 trials, and after a short and long (20-minute) delay. Logical Memory measures the number of details participants recall from 2 short stories with short and long (20-minute) delays.

PROCESSING OF COMPLEX VISUAL MATERIAL AND VISUAL MEMORY was assessed with the Rey Complex Figure test.62 In this test, participants are required to copy a complex visual design and then reproduce it from memory after short and long delays.

EXECUTIVE FUNCTIONING. Inhibitory control was assessed with the Stroop Color-Word Interference Test.63 The test requires participants to inhibit the automatic urge to read the name of a color-word and instead name the color of the ink in which the word is printed. The score is determined by speed and accuracy of execution. Phonemic and categorical fluency was assessed with the Controlled Oral Word Association Test - FAS letters format and Animal Naming Task.64 In 3 separate trials, the test requires participants to retrieve as many words as they can that begin with F, A, and S in 60 seconds. In a later trial, participants are asked to name as many animals as they can in 60 seconds. The battery also included the Wisconsin Card Sorting Test – 64 Card Version,65 a test of nonverbal concept formation, cognitive flexibility, and ability to benefit from feedback. Participants are asked to match a target card to 1 of 4 alternatives. After each match, participants receive correct/incorrect feedback and need to figure out the underlying principle that governs that matching rule (eg, color, number, and shape of items that appear on the cards). After 10 consecutive correct matches, the rule shifts without announcement and participants need to adjust their strategy accordingly.

Statistical analysis

Analyses of group differences in demographic and clinical data applied the Pearson χ2 and t tests for categorical and continuous variables, respectively.

Cognitive data were analyzed with the Multivariate Analysis of Variance (MANOVA), General Linear Model in the Statistical Package for the Social Sciences (SPSS 18 statistical software from IBM). This procedure was applied separately to the 5 different cognitive domains and repeated across times of measurement (discharge and follow-up). Experimentwise Type I error for multiple comparisons was controlled with Rom’s66 procedure. To compare the magnitude of change between groups over the recovery period, we applied the MANOVA procedure to change variables, which represent the difference in scale scores for each cognitive measure across measurements. All MANOVA and post-hoc analyses of between-subjects effects for individual measures applied previous number of hospitalizations and age of onset as covariates. Scores for cognitive measures included Standard Scores, based on normative data (mean = 50, SD = 10; California Verbal Learning Test - II immediate and delayed recall and recognition scores had a mean of 0 and SD of 1; Digit Span scores had a mean of 10 and SD of 3). In all tests, lower values represented poorer performance.


Demographic and clinical variables

Group comparisons of demographic and clinical variables appear in TABLE 1. As the table indicates, comparisons of demographic variables detected no group differences in age and education. Analysis further failed to detect differences in sex (the sample included 24 women) and marital status. With respect to clinical variables, the group with AD reported almost twice as many previous psychiatric hospitalizations (P < .03) and a trend toward a younger age of onset for BD (P < .06) than the group without SUD. A significant difference (P < .01) emerged in reported formal disability status between the dually diagnosed group (19 out of 21 persons) and the group without SUD (22 out of 34 persons). No significant group differences emerged in mood measures at either discharge or follow-up. However, statistically significant improvement in all mood measures was noted within groups between discharge and follow-up.


Means, standard deviations, and group comparisons of demographic variables, clinical variables, mood measures, and alcohol abuse measures

Measures Bipolar patients with AD (n = 21) Bipolar patients without SUD (n = 34) Between groups Within groups (paired sample)
Demographic Mean SD Mean SD t P t P
Education, y 15.1 1.61 14.4 2.38 0.9 0.37    
Age, y 40.7 11.3 36.4 12.2 1.3 0.19    
Onset 23.4 7.7 28.1 9.8 –1.8 0.06    
Admissions 8.1 7.4 4.3 5.2 2.2 0.03a    
YMRS (DIS) 6.5 3.6 6.1 3.7 0.4 0.68 5.4 0.001b
YMRS (FU) 4.7 2.1 4.0 1.7 1.4 0.15    
BDI – II (DIS) 7.9 2.7 8.0 3.2 –0.05 0.95 11.6 0.001b
BDI – II (FU) 6.4 2.0 6.1 2.5 0.42 0.67    
BHS (DIS) 4.7 3.6 3.8 3.4 0.89 0.37 6.6 0.001b
BHS (FU) 3.2 2.2 2.9 2.9 0.39 0.70    
AUDIT (DIS) 30.3 4.4 4.5 2.9 26.1 0.001b    
Quantity (DIS) 44.8 57.9 5.9 5.4 3.9 0.001b 2.9 0.006b
Quantity (FU) 23.0 44.4 6.0 4.3 2.2 0.03a    
Frequency (DIS) 3.6 4.1 3.4 2.7 0.2 0.83 4.2 0.001b
Frequency (FU) 1.4 2.3 2.7 2.3 –0.7 0.51    
aP < .05.
bP < .001.
Admissions: previous number of psychiatric admissions; Onset: age of first psychiatric admission for mood disturbance; Quantity: number of standard drinks consumed in past 30 days; Frequency: number of days in past 30 days in which the participant consumed alcohol.
AD: alcohol dependence; AUDIT: Alcohol Use Disorders Identification Test; BDI: Beck Depression Inventory; BHS: Beck Hopelessness Scale; DIS: time of discharge; FU: 3 months after discharge; SD: standard deviation; SUD: substance use disorder; YMRS: Young Mania Rating Scale.

Analysis did not control for dose and medication type in the sample, although no group differences emerged in the number of psychotropic medications taken on the day of testing. This analysis compared the groups with and without AD on hospital discharge with respective frequencies of lithium (62% vs 66%) benzodiazepines (27% vs 23%), neuroleptics (80% vs 83%), and anticonvulsants (47% vs 45%). Four patients in the AD group were prescribed naltrexone. Insignificant changes in overall percentages of medication classes were noted from discharge to follow-up.

Alcohol measures

Analyses of alcohol measures indicated highly significant group differences in AUDIT scores for the 12-month period prior to admission. In keeping with the overall design of the study, the range of scores for the group with AD was consistent with a diagnosis of AD in past year, and the scores of the group without SUD ranged between abstinence and light social drinking (see TABLE 1). Quantity (number of standard alcoholic drinks) and frequency (number of days in which alcohol was consumed) of alcohol use 30 days prior to hospital admission were significantly higher in the group with AD. On the ASI-5, all participants in the AD group reported being engaged in active treatment for a SUD during the 3 months preceding hospitalization. Seven participants reported abstinence during the month prior to admission, and none reported daily drinking. Eleven in the AD group reported averaging >10 drinks per drinking occasion. Group comparison of quantity and frequency of alcohol use 30 days prior to follow-up revealed no statistically significant differences, although drinking patterns were varied. In the AD group, 11 participants reported abstinence, whereas 10 reported a pattern of drinking ≥8 drinks per drinking occasion on few days (mostly 1 or 2 days) of the month. The group without SUD reported light social drinking ranging from 0 to 14 drinks per month, and a maximum of 5 drinks in 1 occasion. Drinking quantity and frequency decreased significantly in the AD group between the month before admission and follow-up.

Cognitive measures

Attention and working memory. The MANOVA procedure revealed no group differences on measures of attention and working memory upon discharge (Wilks Λ, F(5,47) = 1.32; P < .26), and at follow-up (Wilks Λ, F(6,46) = 1.18; P < .33). This analysis suggests that the groups did not differ in speed and accuracy of visual scanning, speed of basic numerical sequencing, and auditory span. However, these measures improved in the entire sample between discharge and follow-up (F = 3.1; P < .04).

Visual memory. The MANOVA procedure detected significant differences in visual memory, as measured by the Rey-Osterrieth Complex Figure Test, at discharge [Wilks Λ; F(4,48) = 4.12; P < .006, partial eta squared (PES) = 0.25], follow-up (Wilks Λ, F(4,48) = 5.35; P < .001; PES = 0.3), and degree of change during recovery (Wilks Λ, F(4,48) = 3.7; P < .01). As TABLE 2 indicates, post-hoc analysis of between-subjects effects for individual measures revealed significant group differences on all parts of the test, both at discharge and follow-up, at which time the extent of gains in the free delayed recall of the figure was significantly greater in the group without SUD.


Group comparison of scaled scores of visual memory measures (Rey-Osterrieth Complex Figure Test)

Test of between-subjects effects Means and standard deviations of measures
with AD
without SUD
Measure Time SS MS F PES Mean SD Mean SD
Rey Copy DIS 144.5 48.2 3.2a 0.16 28.9 4.5 31.9 3.4
FU 160.5 53.5 3.6a 0.18 30.1 5.1 33.1 2.8
DIF 2.3 0.78 0.5 0.03 1.1 1.2 1.2 1.3
Rey Immediate Recall DIS 915.7 305.2 3.4a 0.17 32.8 8.1 39.2 10.4
FU 918.9 306.3 3.8a 0.18 34.3 8.7 41.3 9.3
DIF 16.2 5.4 1.8 0.10 1.5 1.7 2.0 1.8
Rey Delayed Recall DIS 1160.1 386.1 4.0b 0.19 26.8 7.4 34.8 11.1
FU 1519.1 506.6 5.0c 0.23 28.2 8.8 38.1 10.6
DIF 51.5 17.2 3.9b 0.12 1.4 2.1 3.3 2.0
Rey Recognition DIS 861.0 287.0 2.4 (.07) 0.13 36.1 10.6 43.5 10.8
FU 966.6 322.2 3.0a 0.15 37.3 10.1 45.5 10.1
DIF 17.2 5.7 1.7 0.09 1.2 1.5 2.0 1.9
aP < .05.
bP < .01.
cP < .001.
Time: time of measurement (DIS: time of discharge; FU: 3 months after discharge; DIF: difference in scores between follow-up and discharge); PES: partial eta squared: SS: sum of square; MS: mean sum of square.
AD: alcohol dependence; SD: standard deviation; SUD: substance use disorder.

Verbal memory. The MANOVA procedure detected significant differences in verbal memory at discharge (Wilks Λ, F(6,46) = 2.48; P < .05; PES = 0.24 ) and larger differences at follow-up (Wilks Λ, F(6,46) = 8.0; P < .001; PES = 0.51). The degree of change from discharge to follow-up was also different between the groups (Wilks Λ, F(6,46) = 3.0; P < .05; PES = 0.28). As TABLE 3 indicates, post-hoc analysis of between-subjects effects for individual measures revealed superior performance for the group without SUD on most parts of the list learning task, but no significant group differences emerged for story memory. This pattern was consistent between discharge and follow-up. More substantial gains during recovery were noted for the group without SUD on delayed free recall of the stories, delayed free recall of the list learning task, and recognition of the word list.


Group comparison of scaled scores of verbal memory measures

Test of between-subjects effects Means and standard deviations of measures
with AD
without SUD
Measure Time SS MS F PES Mean SD Mean SD
Logical memory immediate recall DIS 21.9 7.3 0.07 0.004 43.0 8.5 43.4 10.5
FU 25.9 8.6 0.08 0.005 44.5 9.3 44.2 10.6
DIF 7.5 2.5 1.0 0.05 1.5 1.9 0.8 1.2
Logical memory delayed recall DIS 72.7 24.2 0.23 0.01 42.2 9.0 43.7 10.7
FU 361.2 120.4 1.24 0.06 43.0 8.0 47.6 10.6
DIF 136.2 45.4 3.3a 0.16 0.7 3.0 3.9 4.0
CVLT acquisition DIS 958.8 319.6 3.2a 0.16 36.0 10.4 43.5 9.7
FU 1000.5 333.5 4.5c 0.21 38.8 7.4 46.5 9.3
DIF 18.8 6.2 0.4 0.02 2.8 5.6 3.0 2.3
CVLT immediate recall DIS 16.1 5.3 3.3a 0.16 –1.3 0.9 –0.4 1.4
FU 14.4 4.8 4.0b 0.19 –0.9 0.8 –0.02 1.2
DIF 1.0 0.3 2.2 1.12 0.3 0.3 0.4 0.5
CVLT delayed recall DIS 11.7 3.9 4.6c 0.21 –1.5 0.9 –0.7 0.8
FU 16.9 5.6 8.5c 0.33 –1.1 0.8 0.0 0.8
DIF 1.4 0.5 3.6b 0.17 0.4 0.4 0.7 0.3
CVLT recognition DIS 15.0 5.0 3.4 0.17 –1.5 1.3 –0.6 1.1
FU 16.2 5.4 5.6c 0.25 –1.2 1.0 –0.08 0.9
DIF 0.8 0.3 0.9 0.05 0.4 0.4 0.6 0.6
aP < .05.
bP < .01
cP < .001.
Time: time of measurement (DIS: time of discharge; FU: 3 months after discharge; DIF: difference in scores between follow up and discharge), SS: sum of square; MS: mean sum of square; F: Wilks λ, F(6,46); PES: partial eta squared.
AD: alcohol dependence; CVLT: California Verbal Learning Test II – Short Form; SD: standard deviation; SUD: substance use disorder

Executive functioning. Analysis indicated significant differences in measures of executive functioning. The MANOVA procedure was highly significant at discharge (Wilks Λ, F(6,48) = 5.1; P < .0001; PES = 0.41) and follow-up (Wilks Λ, F(6,48) = 6.9; P < .0001; PES = 0.47). The degree of change over the course of recovery was approaching significance (Wilks Λ, F(6,48) = 2.1; P < .07; PES = 0.21). As TABLE 4 indicates, poorer performance was noted for the group with AD on semantic/phonemic fluency, Stroop test, and overall number of errors on the WCST, both at discharge and follow-up. More substantial recovery was noted for the group without SUD on the Trail Making Test, Part B, which measures cognitive flexibility and ability to shift cognitive set.


Group comparison of scaled scores of executive measures

Test of between-subjects effects Means and standard deviations of measures
with AD
Bipolar without SUD
Measure Time SS MS F PES Mean SD Mean SD
Trails B DIS 1145.4 381.8 2.4 0.12 31.4 11.4 40.7 12.6
FU 1691.6 563.8 4.4c 0.20 32.7 10.6 44.1 12.2
DIF 72.3 24.1 3.1a 0.16 1.3 1.8 3.4 3.1
COWAT-FAS DIS 599.0 199.6 2.9a 0.14 40.6 7.6 47.3 8.3
FU 525.1 175.0 3.0a 0.15 43.7 7.4 50.0 7.4
DIF 12.1 4.0 0.45 0.02 3.1 3.4 2.6 2.6
DIS 1923.0 641.0 4.5b 0.21 45.8 11.4 55.4 12.7
FU 1739.7 579.9 4.9c 0.22 46.0 10.6 56.2 11.2
DIF 73.3 24.4 2.1 0.10 0.14 2.9 0.8 3.8
Stroop Interference DIS 888.7 296.2 3.6b 0.17 41.1 6.3 49.3 10.0
FU 902.0 300.6 4.3c 0.20 43.3 6.2 51.5 9.1
DIF 1.39 0.46 0.51 0.003 2.1 2.1 2.2 2.9
WCST Non-Perseverative Errors DIS 1015.6 338.5 4.2b 0.19 34.7 8.8 42.1 9.2
FU 1410.6 470.2 8.9c 0.34 37.8 6.8 47.5 7.7
DIF 104.3 34.7 2.2 0.11 3.1 3.2 5.4 4.3
WCST Perseverative Errors DIS 247.8 82.6 1.3 0.07 42.1 7.0 41.4 8.4
FU 277.8 92.6 1.6 0.08 43.6 6.5 45.3 8.3
DIF 101.2 33.7 1.5 0.08 1.4 2.5 3.9 5.5
aP < .05.
bP < .01.
cP < .001.
Time: time of measurement (DIS: time of discharge; FU: 3 months after discharge; DIF: difference in scores between follow up and discharge), SS: sum of square; MS: mean sum of square; F: Wilks λ, F(6,46); PES: partial eta squared.
AD: alcohol dependence; COWAT: Controlled Oral Word Association Test; Stroop Interference: Stroop Color-Word Interference Test; SUD: substance use disorder; Trails B: Trail Making Test, Part B; WCST: Wisconsin Card Sorting Test.

IQ. Analysis applying the Univariate General Linear Model revealed no group differences on a test of vocabulary [F = 0.8; mean sum of square (MS) = 79.2; P < .48]. However, poorer performance was found for the group with AD on Block Design (F = 4.1; MS = 378.2; P < .01), which is a timed pressured task that measures visuospatial reasoning and abstract nonverbal problem solving. The difference in group means was approximately 10 scale points (54 vs 44; population mean = 50), which is the equivalent of 1 standard deviation in the normative sample.


The current study examined the cognitive functioning of patients with co-occurring BD and AD over the course of early remission from an acute mood disturbance. Consistent with previous findings,24 analysis at the time of discharge from inpatient care indicated that dually diagnosed patients performed more poorly on measures of memory (both verbal and nonverbal) and executive functioning than patients without a history of SUD. At 3-month follow-up, similar discrepancies emerged between the groups. Although cognitive recovery during remission was noted in both groups, the group without SUD exhibited more significant gains than the dually diagnosed group on delayed free recall of the word list, stories, and complex figure. More significant gains for the group without SUD were also noted on the Trail Making Test, Part B, which assesses complex attention and cognitive flexibility. These results remained significant after controlling for group differences in clinical variables relating to illness severity. Thus, in this sample, dually diagnosed patients exhibited more compromised cognitive functioning and, to a certain extent, more limited cognitive recovery than patients without SUD during mood remission. The data, however, do not elucidate causes for the observed group differences on cognitive measures.

This study reported more extensive cognitive deficits in dually diagnosed patients than others that focused on cognitive functioning during strictly-defined periods of euthymia and abstinence26 or a wider range of alcohol use disorders.25 Whereas those studies found deficits primarily in executive functioning, this study also found impairment in learning and memory. The larger scope of cognitive impairment detected in this study is consistent with findings indicating more pronounced cognitive deficits in patients with AD than in patients with milder alcohol use disorders.67-70 Current findings also agree with studies showing greater cognitive deficits in early phases of remission from prolonged intoxication in AD71,72 or mood disturbance in BD.73,74 In this respect, this study reaffirms the previously established connection between cognitive functioning and clinical state and more specifically examines cognitive functioning in dually diagnosed patients in a particular clinical state that is under-researched: non-euthymic BD patients in partial recovery from AD.

Whereas previous research with dually diagnosed patients excluded symptomatic participants because of methodologic considerations, this study focused on these patients for clinical concerns. Specifically, it examined the cognitive challenges of a distinct group of patients during a critical time in their illness. The results suggest that dually diagnosed patients who suffer an acute mood disturbance during early or partial remission from AD may suffer more significant cognitive impairment than asymptomatic patients or BD patients without SUD in the same affective state. These findings may be important for clinical care.

Psychiatric care of dually diagnosed patients may benefit from future research that explores the clinical effects of cognitive impairment during recovery from acute mood episodes. Specifically, debilitating cognitive impairment may compound the destabilizing shift between the symptomatic phases of BD and AD. For example, early remission from AD typically is accompanied by mood instability.75-77 With co-occurring BD, increasing mood symptoms and stress can lead to an acute mood episode that requires hospitalization.78-82 When patients enter the hospital with depression or mania, they are stabilized with psychiatric medications. On discharge, they face the challenge of transitioning from the protective environment of the inpatient unit to a less supervised setting73,83 at a neurocognitive low point. In this state, the task of negotiating the demands of everyday life can be overwhelming,80-82 as indicated by the robust links among cognitive impairment, prognosis, and psychosocial disability in both BD84-88 and AD.89 Suboptimal postdischarge support may therefore lead to a vicious cycle of stress, relapse to either disorder, greater psychosocial disability, and further compromise of quality of life.

Several limitations of the study deserve mention. The sample size was fairly small and may limit conclusions in the absence of larger independent replications. Results may not generalize to minority groups, which were not represented in this sample in a way that allowed for informative analysis of differences in cognitive functioning related to ethnicity and culture. In addition, the current sample was too small to control for the effects of medication, with the exception of number of medications taken on days of testing. Because the cognitive measures were repeated across discharge and follow-up, some of the observed gains may have resulted from practice effects and may not reflect brain changes related to affective recovery. Finally, significant attrition between discharge and follow-up, mostly the result of relapse and readmission, rendered a selective sample of those who managed to maintain their outpatient status. As noted in our previous report,44 further investigation into the differences between patients who relapsed and those who recovered may help to illuminate the connections between cognitive functioning at discharge and post-hospital adjustment in BD patients both with and without AD or other SUD.

Finally, this study does not illuminate the causes for the observed difference between the groups. The study did not determine baseline differences between the groups before hospitalization or during euthymia. The symptomatic recovery of patients with AD may have been less favorable during the interval between discharge and follow-up. It is also possible that patients with AD have slower recovery and therefore may continue to improve beyond the 3-month follow-up period. Differences in treatment, stress and social support may also play a role in accounting for the cognitive disparities between the groups.


This study provides further evidence that the co-occurrence of BD and AD is associated with increased impairment of cognitive functioning. The results suggest that, over the course of remission from an acute mood disturbance, dually diagnosed patients in partial remission from AD exhibit more severe deficits and poorer recovery of memory and executive functioning than BD patients without SUD. The unique set of circumstances, complex clinical picture, and level of disability of dually diagnosed patients may require additional measures for their care. Careful neurocognitive evaluation before hospital discharge may inform discharge planning in a manner that increases supports for the early phases of rehabilitation and recovery. Understanding the extent of cognitive impairment at discharge, and the expected degree of functional recovery over the course of early remission, may help to decrease relapse, disability, cost, and suffering.

DISCLOSURE: The authors report no financial relationship with any company whose products are mentioned in this article or with manufacturers of competing products.

FUNDING SOURCE: This study was supported by a Kaplen Fellowship on Depression Award from the Department of Psychiatry, Harvard Medical School; a Young Investigator Award from the National Alliance for Research on Schizophrenia and Depression; and the National Institute on Drug Abuse (grants R01 DA15968 and K24 DA022288).

ACKNOWLEDGEMENTS: The authors are grateful for the technical assistance of the treatment teams on AB2 unit at McLean Hospital. In particular, we are thankful for the invaluable clinical support of Matt Bernstein, MD, Liz Liebson, MD, Katherine Healey, MSW, Amy Carlson, MSW, Amy Burch, MSW, and Kevin Aubrey, MSW.


  1. Albanese MJ, Pies R. The bipolar patient with comorbid substance use disorder: recognition and management. CNS Drugs. 2004;18:585–596.
  2. Salloum IM, Thase ME. Impact of substance abuse on the course and treatment of bipolar disorder. Bipolar Disord. 2000;2(3 pt 2):269–280.
  3. Oquendo MA, Currier D, Liu SM, et al. Increased risk for suicidal behavior in comorbid bipolar disorder and alcohol use disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). J Clin Psychiatry. 2010;71:902–909.
  4. Strakowski SM, DelBello MP, Fleck DE, et al. The impact of substance abuse on the course of bipolar disorder. Biol Psychiatry. 2000;48:477–485.
  5. Regier DA, Farmer ME, Rae DS, et al. Comorbidity of mental disorders with alcohol and other drug abuse. Results from the Epidemiologic Catchment Area (ECA) Study. JAMA. 1990;264:2511–2518.
  6. Kessler RC, Crum RM, Warner LA, et al. Lifetime co-occurrence of DSM-III-R alcohol abuse and dependence with other psychiatric disorders in the National Comorbidity Survey. Arch Gen Psychiatry. 1997; 54:313–321.
  7. Vornik LA, Brown ES. Management of comorbid bipolar disorder and substance abuse. J Clin Psychiatry. 2006;67(suppl 7):24–30.
  8. Jaworski F, Dubertret C, Adès J, et al. Presence of co-morbid substance use disorder in bipolar patients worsens their social functioning to the level observed in patients with schizophrenia. Psychiatry Res. 2011; 185:129–134.
  9. Tohen M, Greenfield SF, Weiss RD, et al. The effect of comorbid substance use disorders on the course of bipolar disorder: a review. Harv Rev Psychiatry. 1998;6:133–141.
  10. Cerullo MA, Strakowski SM. The prevalence and significance of substance use disorders in bipolar type I and II disorder. Subst Abuse Treat Prev Policy. 2007;2:29.
  11. Ostacher MJ, Perlis RH, Nierenberg AA, et al. Impact of substance use disorders on recovery from episodes of depression in bipolar disorder patients: prospective data from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Am J Psychiatry. 2010;167:289–297.
  12. Manwani SG, Szilagyi KA, Zablotsky B, et al. Adherence to pharmacotherapy in bipolar disorder patients with and without co-occurring substance use disorders. J Clin Psychiatry. 2007;68:1172–1176.
  13. Sajatovic M, Ignacio RV, West JA, et al. Predictors of nonadherence among individuals with bipolar disorder receiving treatment in a community mental health clinic. Compr Psychiatry. 2009;50:100–107.
  14. Salloum IM, Cornelius JR, Mezzich JE, et al. Impact of concurrent alcohol misuse on symptom presentation of acute mania at initial evaluation. Bipolar Disord. 2002;4:418–421.
  15. Goldberg JF, Garno JL, Leon AC, et al. A history of substance abuse complicates remission from acute mania in bipolar disorder. J Clin Psychiatry. 1999;60:733–740.
  16. Swann AC. The strong relationship between bipolar and substance-use disorder. Ann N Y Acad Sci. 2010;1187:276–293.
  17. Hoblyn JC, Balt SL, Woodard SA, et al. Substance use disorders as risk factors for psychiatric hospitalization in bipolar disorder. Psychiatr Serv. 2009;60:50–55.
  18. Gaudiano BA, Uebelacker LA, Miller IW. Impact of remitted substance use disorders on the future course of bipolar I disorder: findings from a clinical trial. Psychiatry Res. 2008;160:63–71.
  19. Cassidy F, Ahearn EP, Carroll BJ. Substance abuse in bipolar disorder. Bipolar Disord. 2001;3:181–188.
  20. Mazza M, Mandelli L, Di Nicola M, et al. Clinical features, response to treatment and functional outcome of bipolar disorder patients with and without co-occurring substance use disorder: 1-year follow-up. J Affect Disord. 2009;115(1-2):27–35.
  21. Singh J, Mattoo SK, Sharan P, et al. Quality of life and its correlates in patients with dual diagnosis of bipolar affective disorder and substance dependence. Bipolar Disord. 2005;7:187–191.
  22. van Zaane J, van den Brink W, Draisma S, et al. The effect of moderate and excessive alcohol use on the course and outcome of patients with bipolar disorders: a prospective cohort study. J Clin Psychiatry. 2010;71:885–893.
  23. Lagerberg TV, Andreassen OA, Ringen PA, et al. Excessive substance use in bipolar disorder is associated with impaired functioning rather than clinical characteristics, a descriptive study. BMC Psychiatry. 2010;10:9.
  24. Levy B, Monzani BA, Stephansky MR, et al. Neurocognitive impairment in patients with co-occurring bipolar disorder and alcohol dependence upon discharge from inpatient care. Psychiatry Res. 2008;161:28–35.
  25. Sanchez-Moreno J, Martinez-Aran A, Colom F, et al. Neurocognitive dysfunctions in euthymic bipolar patients with and without prior history of alcohol use. J Clin Psychiatry. 2009;70:1120–1127.
  26. van Gorp WG, Altshuler L, Theberge DC, et al. Cognitive impairment in euthymic bipolar patients with and without prior alcohol dependence. A preliminary study. Arch Gen Psychiatry. 1998;55:41–46.
  27. Torres IJ, Boudreau VG, Yatham LN. Neuropsychological functioning in euthymic bipolar disorder: a meta-analysis. Acta Psychiatr Scand Suppl. 2007;(434):17–26.
  28. Cunha PJ, Nicastri S, de Andrade AG, et al. The frontal assessment battery (FAB) reveals neurocognitive dysfunction in substance-dependent individuals in distinct executive domains: Abstract reasoning, motor programming, and cognitive flexibility. Addict Behav. 2010;35:875–881.
  29. Munro CA, Saxton J, Butters MA. The neuropsychological consequences of abstinence among older alcoholics: a cross-sectional study. Alcohol Clin Exp Res. 2000;24:1510–1516.
  30. Fein G, Torres J, Price LJ, et al. Cognitive performance in long-term abstinent alcoholic individuals. Alcohol Clin Exp Res. 2006;30:1538–1544.
  31. Loeber S, Duka T, Welzel H, et al. Impairment of cognitive abilities and decision making after chronic use of alcohol: the impact of multiple detoxifications. Alcohol Alcohol. 2009;44:372–381.
  32. Rourke SB, Grant I. The interactive effects of age and length of abstinence on the recovery of neuropsychological functioning in chronic male alcoholics: a 2-year follow-up study. J Int Neuropsychol Soc. 1999;5:234–246.
  33. Manning V, Wanigaratne S, Best D, et al. Changes in neuropsychological functioning during alcohol detoxification. Eur Addict Res. 2008;14:226–233.
  34. Davies SJ, Pandit SA, Feeney A, et al. Is there cognitive impairment in clinically ‘healthy’ abstinent alcohol dependence? Alcohol Alcohol. 2005;40:498–503.
  35. Mur M, Portella MJ, Martínez-Arán A, et al. Persistent neuropsychological deficit in euthymic bipolar patients: executive function as a core deficit. J Clin Psychiatry. 2007;68:1078–1086.
  36. Gildengers AG, Butters MA, Chisholm D, et al. Cognitive functioning and instrumental activities of daily living in late-life bipolar disorder. Am J Geriatr Psychiatry. 2007;15:174–179.
  37. O’Shea R, Poz R, Michael A, et al. Ecologically valid cognitive tests and everyday functioning in euthymic bipolar disorder patients. J Affect Disord. 2010;125:336–340.
  38. O’Bryant SE, Falkowski J, Hobson V, et al. Executive functioning mediates the link between other neuropsychological domains and daily functioning: a Project FRONTIER study. Int Psychogeriatr. 2011;23:107–113.
  39. Burdick KE, Goldberg JF, Harrow M. Neurocognitive dysfunction and psychosocial outcome in patients with bipolar I disorder at 15-year follow-up. Acta Psychiatr Scand. 2010;122:499–506.
  40. Bonnín CM, Martínez-Arán A, Torrent C, et al. Clinical and neurocognitive predictors of functional outcome in bipolar euthymic patients: a long-term, follow-up study. J Affect Disord. 2010;121:156–160.
  41. Durazzo TC, Gazdzinski S, Yeh PH, et al. Combined neuroimaging, neurocognitive and psychiatric factors to predict alcohol consumption following treatment for alcohol dependence. Alcohol Alcohol. 2008;43:683–691.
  42. Adamson SJ, Sellman JD, Frampton CM. Patient predictors of alcohol treatment outcome: a systematic review. J Subst Abuse Treat. 2009;36:75–86.
  43. van der Werf-Eldering MJ, Burger H, Holthausen EA, et al. Cognitive functioning in patients with bipolar disorder: association with depressive symptoms and alcohol use. PLoS One. 2010;5:e13032.
  44. Levy B, Medina AM, Manove E, et al. The characteristics of a discrete mood episode, neuro-cognitive impairment and re-hospitalization in bipolar disorder. J Psychiatr Res. 2011;45:1048–1054.
  45. Dozois DJA, Dobson KS, Ahnberg JL. A psychometric evaluation of the Beck Depression Inventory–II. Psychol Assess. 1998;10:83–89.
  46. Beck AT, Weissman A, Lester D, et al. The measurement of pessimism: the hopelessness scale. J Consult Clin Psychol. 1974;42:861–865.
  47. Young RC, Biggs JT, Ziegler VE, et al. A rating scale for mania: reliability, validity and sensitivity. Br J Psychiatry. 1978;133:429–435.
  48. First MB, Spitzer RL, Gibbon M, et al. The Structured Clinical Interview for Axis I DSM-IV Disorders Patients Edition (SCID-I/P), Version 2. New York, NY: Biometric Research, New York State Psychiatric Institute; 1994.
  49. McLellan AT, Kushner H, Metzger D, et al. The Fifth Edition of the Addiction Severity Index. J Subst Abuse Treat. 1992;9:199–213.
  50. Sobell LC, Sobell MB. Timeline followback: a technique for assessing self-reported alcohol consumption. In: Litten RZ Allen J, eds. Measuring alcohol consumption: psychosocial and biological methods. Totowa, NJ: The Humana Press, Inc.; 1992:41–72.
  51. Sobell LC, Sobell MB. Alcohol consumption measures. In: Allen JP Columbus M, eds. Assessing alcohol problems: a guide for clinicians and researchers. Bethesda, MD; 1995:55–73.
  52. Annis HM, Sobell LC, Ayala-Velazquez H, et al. Drinking-related assessment instruments: cross-cultural studies. Subst Use Misuse. 1996;31:1525–1546.
  53. Sobell LC, Agrawal S, Annis H, et al. Cross-cultural evaluation of two drinking assessment instruments: alcohol timeline followback and inventory of drinking situations. Subst Use Misuse. 2001;36:313–331.
  54. Pal HR, Jena R, Yadav D. Validation of the Alcohol Use Disorders Identification Test (AUDIT) in urban community outreach and de-addiction center samples in north India. J Stud Alcohol. 2004;65:794–800.
  55. Wechsler D. Wechsler Abbreviated Scale of Intelligence. San Antonio TX: The Psychological Cooperation; 1999.
  56. Wechsler D. Wechsler Adult Intelligence Scale – Third Edition. San Antonio TX: The Psychological Cooperation; 1997.
  57. Spreen O, Strauss E. A compendium of neuropsychological tests: administration norms, and commentary. 2nd ed. New York, NY: Oxford University Press; 1998.
  58. Corrigan JD, Hinkeldey NS. Relationships between parts A and B of the Trail Making Test. J Clin Psychol. 1987;43:402–409.
  59. Gaudino EA, Geisler MW, Squires NK. Construct validity in the Trail Making Test: what makes Part B harder? J Clin Exp Neuropsychol. 1995;17:529–535.
  60. Delis D, Kramer J, Kaplan E, et al. California Verbal Learning Test – Second Edition (CVLT-II) Manual. San Antonio, TX: The Psychological Corporation; 1999.
  61. Wechsler D. Wechsler Memory Scale – Revised. San Antonio TX: The Psychological Corporation;. 1987.
  62. Meyers JE, Meyers KR. The Meyers scoring system for the Rey Complex figure test and the recognition trial: professional manual. Odessa FL: Psychological Assessment Resources, Inc.; 1995.
  63. Golden CJ. Stroop Color and Word Test: a manual for clinical and experimental uses. Wood Dale IL: Stoelting Company; 1978:1–32.
  64. Tombaugh TN, Kozak J, Rees L. Normative data stratified by age and education for two measures of verbal fluency: FAS and animal naming. Arch Clin Neuropsychol. 1999;14:167–177.
  65. Heaton RK, Chelune GJ, Talley JL, et al. Wisconsin Card Sorting Test: Computer Version 4 (WCST; CV4) Research Edition. San Antonio, TX: Psychological Assessment Resources, Inc.; 2003.
  66. Rom DM. A sequentially rejective test procedure based on a modified Bonferroni inequality. Biometrika. 1990;77:663–665.
  67. Eckardt MJ, Stapleton JM, Rawlings RR, et al. Neuropsychological functioning in detoxified alcoholics between 18 and 35 years of age. Am J Psychiatry. 1995;152:53–59.
  68. Sullivan EV, Fama R, Rosenbloom MJ, et al. A profile of neuropsychological deficits in alcoholic women. Neuropsychology. 2002;16:74–83.
  69. Sullivan EV, Rosenbloom MJ, Pfefferbaum A. Pattern of motor and cognitive deficits in detoxified alcoholic men. Alcohol Clin Exp Res. 2000;24:611–621.
  70. Keenan E, O’Donnell C, Sinanan K, et al. Severity of alcohol dependence and its relationship to neurological soft signs, neuropsychological impairment and family history. Acta Psychiatr Scand. 1997;95:272–276.
  71. Zinn S, Stein R, Swartzwelder HS. Executive functioning early in abstinence from alcohol. Alcohol Clin Exp Res. 2004;28:1338–1346.
  72. Pitel AL, Rivier J, Beaunieux H, et al. Changes in the episodic memory and executive functions of abstinent and relapsed alcoholics over a 6-month period. Alcohol Clin Exp Res. 2009;33:490–498.
  73. Levy B, Weiss RD. Neurocognitive impairment and psychosis in bipolar I disorder during early remission from an acute episode of mood disturbance. J Clin Psychiatry. 2010;71:201–206.
  74. Torres IJ, DeFreitas VG, DeFreitas CM, et al. Neurocognitive functioning in patients with bipolar I disorder recently recovered from a first manic episode. J Clin Psychiatry. 2010;71:1234–1242.
  75. Bowen R, Block G, Baetz M. Mood and attention variability in women with alcohol dependence: a preliminary investigation. Am J Addict. 2008;17:77–81.
  76. Bokström K, Balldin J, Långström G. Individual mood profiles in alcohol withdrawal. Alcohol Clin Exp Res. 1991;15:508–513.
  77. Kiefer F, Andersohn F, Jahn H, et al. Involvement of plasma atrial natriuretic peptide in protracted alcohol withdrawal. Acta Psychiatr Scand. 2002;105:65–70.
  78. Judd LL, Schettler PJ, Akiskal HS, et al. Residual symptom recovery from major affective episodes in bipolar disorders and rapid episode relapse/recurrence. Arch Gen Psychiatry. 2008;65:386–394.
  79. Hosang GM, Korszun A, Jones L, et al. Adverse life event reporting and worst illness episodes in unipolar and bipolar affective disorders: measuring environmental risk for genetic research. Psychol Med. 2010;40:1829–1837.
  80. Hosang GM, Uher R, Keers R, et al. Stressful life events and the brain-derived neurotrophic factor gene in bipolar disorder. J Affect Disord. 2010;125:345–349.
  81. Sylvia LG, Alloy LB, Hafner JA, et al. Life events and social rhythms in bipolar spectrum disorders: a prospective study. Behav Ther. 2009;40:131–141.
  82. Cohen AN, Hammen C, Henry RM, et al. Effects of stress and social support on recurrence in bipolar disorder. J Affect Disord. 2004;82:143–147.
  83. Levy B, Stephansky MR, Dobie KC, et al. The duration of inpatient admission predicts cognitive functioning at discharge in patients with bipolar disorder. Compr Psychiatry. 2009;50:322–326.
  84. Brissos S, Dias VV, Kapczinski F. Cognitive performance and quality of life in bipolar disorder. Can J Psychiatry. 2008;53:517–524.
  85. Dickerson F, Origoni A, Stallings C, et al. Occupational status and social adjustment six months after hospitalization early in the course of bipolar disorder: a prospective study. Bipolar Disord. 2010;12:10–20.
  86. Mur M, Portella MJ, Martinez-Aran A, et al. Influence of clinical and neuropsychological variables on the psychosocial and occupational outcome of remitted bipolar patients. Psychopathology. 2009; 42:148–156.
  87. Jaeger J, Berns S, Loftus S, et al. Neurocognitive test performance predicts functional recovery from acute exacerbation leading to hospitalization in bipolar disorder. Bipolar Disord. 2007;9:93–102.
  88. Martinez-Aran A, Vieta E, Torrent C, et al. Functional outcome in bipolar disorder: the role of clinical and cognitive factors. Bipolar Disord. 2007; 9:103–113.
  89. Zlotnick C, Agnew J. Neuropsychological function and psychosocial status of alcohol rehabilitation program residents. Addict Behav. 1997;22:183–194.

CORRESPONDENCE: Boaz Levy, PhD, University of Massachusetts, Boston, Department of Counseling and School Psychology, 100 Morrissey Blvd. Boston, MA 02125 USA E-MAIL: