1. Neuropsychological Performance in Patients with SUD with and without Mood Disorders
Irma Höijer, M.Sc., Doctoral Student
Doctoral Programme of Clinical Investigation
University of Turku
Tuula Ilonen, Ph.D.
University of Turku, Department of psychiatry
Eliisa Löyttyniemi, M.Sc.
Department of Biostatistics
Raimo Salokangas, Ph.D.
Turku University Hospital Psychiatry

2. Background And aims
Substance abuse as well as mood disorder has been consistently associated with neuropsychological impairment in many cognitive domains.
SUD may create a “double deficit” in cognitive functions in those with mood disorder and have an adverse impact on their course of illness and functional outcome.
The aim of the study was to examine the effects of mood and substance use disorders on specific neuropsychological measures in a sample of single and multidrug patients with and without mood disorders. 

3. . Method Participants 164 hospitalised patients, 88 with (SUD+MD) and
76 (SUD-MD) without mood disorders

4. Participants
Diagnoses were made according to the criteria of ICD-10 by experienced psychiatrists.
Substance use disorder (SUD) diagnoses also consisted of alcohol overuse or dependence.
No significant differences were cited between SUD-MD and SUD+MD groups in the use of intoxicating substances (see table 1).

5. Table 1. Substance used in patients.
SUD-MD
N=76
SUD+MD
N=88
Only one drug
39 (51%)
52 (59%)
Alcohol
29 (38%)
39 (44%)
Sedatives
3 (3%)
8 (9%)
Stimulants
Opioids
2 (1%)
Multidrug
37 (48%)
36 (40%)
Alcohol, sedatives
5 (7%)
20 (23%)
Alcohol, cannabis
1 (1 %)
0 (0%)
Alcohol, stimulants
1 (1%)
Alcohol, other psychoactives
12 (16%)
10 (11%)
Opioids, other psychoactives
9 (11%)
Other psychoactive substance-
related disorders
 10 (13%)
 5 (5%)

6. Diagnostic distribution of SUD+MD sample
Bipolar Disorder: severe with psychotic features (F32.3; 3%),
major depressive disorder, single episode, bipolar disorder (F31; 21%),
Major depressive disorder, single episode, mild (F32.0; 3%),
major depressive disorder, single episode, moderate (F32.1; 23%),
major depressive disorder, single episode, severe without psychotic features (F32.2.;11%),
major depressive disorder, single episodeunspecified (F32.9; 6%),
recurrent major depressive disorder, mild (F33.0; 2%),
recurrent major depressive disorder, moderate (F33.1; 6%),
recurrent major depressive disorder, severe without psychotic symptoms (F33.2; 3%)
recurrent major depressive disorder, in remission (F33.4; 3%),
Persistent mood (affective) disorders (F34.1; 3% ) and
Mixed anxiety and depressive disorder (F41.2; 13%).

7. Sosiodemographics SUD-MD N = 76 SUD+MD N = 88 Statistical analysis
SUD-MD
N = 76
SUD+MD
N = 88
Statistical
analysis
p value
Age (mean, SD)
37.8 (11.9)
39.1 (10.3)
t-test
.42
Sex
Male
Female
42 (43.3%)
34 (50.7%)
55 (56.7%)
33 (49.3%)
ChiSquare
.35
Level of Education
No Primary School
Primary School
Vocational Training
College-level Education
Higher Education
0 (0.0%)
35 (53.0%)
23 (43.4%)
10 (35.7%)
8 (47.1%)
31 (47.0%)
32 (56.6%)
18 (64.3%)
9 (52.9%)
.45
Marital status
Married
Stable Partner
Single
Separate/Divorced
12 (48.0%)
6 (50.0 %)
36 (55.4%)
22 (35.5%)
13 (52.0%)
6 (50.0%)
29 (44.6%)
40 (64.5%)
.16
Unemployed
47 (50.5%)
46 (49.5%)
.23
Military Service (only males)
Exemption
Completed
Unknown
17 (53.1%)
20 (35.7%)
2 (33.3%)
15 (46.9%)
36(64.3%)
4 (66.7%)
.26
Prison ruling
None
Parole
Prison
Pending Judgment
54 (50.0%)
8 (50.0%)
10 (47.6%)
4 (100.0%)
11 (52.4)
1 (100.0%)
.29

8. Clinical variables (1) SUD-MD N=76 SUD+MD N=88 Statistical analysis
SUD-MD
N=76
SUD+MD
N=88
Statistical analysis
p value
Onset of substance use age
16.2 (7.6)
16.3 (5.9)
T-test
0.97
Onset of regular substance use
21.2 (11.3)
23.5 (1.0)
0.17
Substance use duration (years)
16.1 (9.4)
15.7 (8.8)
0.78
Onset of multidrug use
18.6 (9.5)
24.2 (1.0)
0.01˟˟

9. Clinical variables (2) SUD-MD N=76 SUD+MD N=88 Statistical analysis
SUD-MD
N=76
SUD+MD
N=88
Statistical analysis
p value
Multidrug use in years
8.2 (8.0)
10.7 (7.1)
T-test
0.07
Onset of injection drug abuse
19.9 (5.3)
23.3 (6.6)
0.12
Duration of injection abuse
4.5 (6.0)
5.7 (3.7)
0.55
Treatment onset age
33.1 (12.3)
36.2 (10.3)
0.09

10. Clinical variables (3) SUD-MD N=76 SUD+MD N=88 Statistical analysis
SUD-MD
N=76
SUD+MD
N=88
Statistical analysis
p value
Depression score (MMPI)
79.2 (17.7)
91.5 (18.4)
T-test
0.001˟˟˟
Affection disorder data (only males)
Duration of disorder
4.4 (4.5)

11. Table 2.1 Neuropsychological measures
Cognitive Domain
Test
Score units
Premorbid IQ
Vocabulary (WAIS-R; Wechsler, 1975)
Standard Score
Attention
Digit Span Forward
Digit Span Backward
Total raw score, max 12
Speed of Processing
Digit Symbol (WAIS-R; Wechsler, 1975)
Simple reaction time (CogniSpeed; Revonsuo et al., 1993)
Time to complete (ms)
Perceptual Reasoning
Block Design (WAIS-R; Wechsler, 1975)
Raven Standard Matrices (Raven, 2004)

12. Table 2.2 Neuropsychological measures
Cognitive Domain
Test
Score units
Verbal Memory and Learning
Verbal subtests of the WMS-R (Wechsler, 1987)
Immediate Logical Memory
Delayed recall of Logical Memory
Immediate Associate Learning
Delayed recall of Associate Learning
Verbal Memory Index
Total raw score, max 50
Total raw score, max 24
Total raw score, max 8
Visual Memory and Learning
Visual subtests of (WMS-R (Wechsler, 1987)
Immediate Visual Learning
Delayed recall of Visual Learning
Immediate Visual Reproduction
Delayed recall of Visual Reproduction
Visual Memory Index
Total raw score, max 18
Total raw score, max 6
Total raw score, max 41
Delayed Memory
(WMS-R (Wechsler, 1987)
Delayed Memory Index

13. Table 2.3 Neuropsychological measures
Cognitive Domain
Test
Score units
Inhibitory Capacity
CogniSpeed version of the Stroop Color-Word Test (Stroop, 1935)
Neutral Condition, COL
Congruous Word Condition, CON
Incongruous Word Condition, IN2
Time to complete (ms), and number of errors
Executive Function
Total Stroop
(IN2-CON)
Stroop Interference
(IN2-COL)
Time to complete (ms)

14. CogniSpeed Color Reaction time-tasks
Neutral Condition
COL
nnnnnnnn
Right index finger push the reaction key red or blue as
soon as possible
Congruous
Word
Condition
CON
Red
Blue
Incongruous
IN2
Pay attention only the color,
Ignore the possible word and its meaning (semantic content)
STIN
nnnnnnnn nnnnnnnn
Red Blue
Same instructions than above
STIR
Red Blue

15. Results
Compared with normative, memory, learning and processing speed were impaired in both SUD+MD and SUD-MD groups.
Processing speed (p <0.01), perceptual reasoning (p<0.05) and susceptibility to interference (p=0.03) were more impaired in the SUD+MD group than in the SUD-MD group.
The SUD+MD and SUD-MD were most powerfully separated by the Digit Symbol and Block Design tests.
Cognitive interference in the SUD+MD group was significantly correlated with slowing the speed of processing.

16. The Digit Symbol of WAIS-R standard scores for the SUD-MD group and the SUD+MD group.
The significant differences within each diagnostic group are shown by an asterisk (P < .01).
The data shown are 95% Confidence Interval for median, Lower Bound and Upper Bound 9.0 for the SUD-MD group; Lower Bound 6.4 and Upper Bound 7.7 for the SUD+MD group.

17. Simple reaction time of CogniSpeed tasks reaction time (ms) for the SUD-MD group and SUD+MD group.
The significant differences within each diagnostic group are shown by asterisk (P < .01).
The Data shown are 95% Confidence Interval for median, Lower Bound and Upper Bound for SUD-MD Group; Lower Bound and Upper Bound for SUD+MD group.

18. The Block Design test of WAIS-R standard scores for the SUD-MD group and the SUD+MD group.
The significant differences within each diagnostic group are shown by asterisk (P < .01).
The Data shown are 95% Confidence Interval for median, Lower Bound and Upper Bound for SUD-MD Group; Lower Bound and Upper Bound for SUD+MD group.

19. Incongruous Word Condition of CogniSpeed tasks reaction time (ms) for the SUD-MD group and the SUD+MD group.
The significant differences within each diagnostic group are shown by asterisks (P < .01).
The Data shown are 95% Confidence Interval for median, Lower Bound and Upper Bound for the SUD Group; Lower Bound and Upper Bound836.8 for the SUD+MD group.

20. Conclusions
SUD+MD patients may suffer from more severe cognitive deficits than SUD-MD patients.
In this study processing speed was also measured by CogniSpeed tasks (simple reaction time, COL, IN2). Both groups -SUD-MD and SUD+MD - had deficits in processing speed compared to healthy controls, but mood disorders further enhanced slowing down.
Mental speed was partially modulated by age in CogniSpeed tasks. Elderly patients were slower, but their higher education level was a compensatory factor diminishing the impact of ageing.
The single substance used (mostly alcohol) was probably involved in test performance deterioration. The mean age of the SUD+MD patients was 38, but their processing speed was at the same level as normal 67 year olds have.

21. Conclusions
In the SUD+MD group of this study, Stroop interference significantly slowed down information processing, both in automatic and more conscious, effortful processing. The wrong or irrelevant word slowed ink-naming performance (e.g., the blue colored letters formed the word ‘red’) significantly independently of age, education level, multiple substance use and learning difficulties.
The role of Total Stroop is less researched in mood disorders and substance abuse disorders. The Total Stroop effect is a combined effect of facilitation and interference (Revonsuo, 1995).
In SUD+MD patients the increased Total Stroop was related significantly with the slowing of processing speed. It seems that patients could not use congruent and facilitative and relevant conditions (the right word ‘red’ in red ink) to speed performance.

22. Conclusions
As a quantitative measure of selective attention and executive function, Stroop tasks require future research in order to clarify what mechanisms are involved in Stroop effects in individuals with substance abuse and mood disorders.
It is possible that Stroop effects are cognitive markers of comorbidity and are worthy of inclusion in future studies. The tasks may have prognostic utility among drug-dependent patients (Carpenter et al., 2006).