Hostname: page-component-745bb68f8f-d8cs5 Total loading time: 0 Render date: 2025-02-06T10:14:00.097Z Has data issue: false hasContentIssue false

Do pathological gambling and obsessive-compulsive disorder overlap? a neurocognitive perspective

Published online by Cambridge University Press:  02 July 2012

Ji-Won Hur
Affiliation:
Department of Brain and Cognitive Sciences, Seoul National University, Seoul, Korea Clinical Cognitive Neuroscience Center, Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Korea
Na young Shin
Affiliation:
Clinical Cognitive Neuroscience Center, Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Korea
Sung Nyun Kim
Affiliation:
Clinical Cognitive Neuroscience Center, Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Korea Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
Joon Hwan Jang
Affiliation:
Clinical Cognitive Neuroscience Center, Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Korea Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
Jung-Seok Choi
Affiliation:
Department of Psychiatry, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea
Young-Chul Shin
Affiliation:
Department of Psychiatry, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
Jun Soo Kwon*
Affiliation:
Department of Brain and Cognitive Sciences, Seoul National University, Seoul, Korea Clinical Cognitive Neuroscience Center, Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Korea Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
*
*Address for correspondence: Jun Soo Kwon, MD, PhD, Department of Psychiatry, Seoul National University College of Medicine, 101 Daehak-no, Chongno-gu, Seoul, Korea. (Email kwonjs@snu.ac.kr)
Rights & Permissions [Opens in a new window]

Abstract

Objective

Pathological gambling (PG) is a severe and persistent pattern of problem gambling that has been aligned with obsessive-compulsive disorder (OCD). However, no study has compared the neurocognitive profiles of individuals with PG and OCD.

Methods

We compared neurocognitive functioning, including executive function, verbal learning and memory, and visual–spatial organization and memory among 16 pathological gamblers, 31 drug-naïve OCD subjects, and 52 healthy controls.

Results

The only neurocognitive marker common to both groups was increased fragmentation errors on the Rey–Osterrieth Complex Figure Test (ROCF). The PG subjects showed increased nonperseverative error on the Wisconsin Card Sorting Test and organization difficulties in the ROCF, whereas the OCD subjects revealed longer response times on the Stroop test and retention difficulties on the immediate recall scale of the ROCF.

Conclusions

A more careful approach is required in considering whether PG is a part of the OCD spectrum, as little evidence of neurocognitive overlap between PG and OCD has been reported.

Type
Original Research
Copyright
Copyright © Cambridge University Press 2012

FOCUS POINTS

  • Pathological gambling (PG) and obsessive-compulsive disorder (OCD) have been considered related because of the peculiar intrusive ideas and the compulsive behaviors associated with specific themes, which are socially and occupationally dysfunctional to the individual. However, some argue against such a relationship.

  • The only neurocognitive deficit common to both PG and OCD groups is increased fragmentation error on the Rey–Osterrieth Complex Figure test. No neurocognitive function is decreased in either clinical group, including in the areas of executive function, verbal and visual memory, and visual organization, except for the fragmentation error.

  • Caution should be exercised in concluding that PG is a part of the OCD spectrum because neurocognitive evidence demonstrating the overlap between PG and OCD is currently insufficient.

Introduction

Pathological gambling (PG) is defined as a severe form of problem gambling that negatively affects interpersonal, occupational, and financial functioning.Reference Potenza, Kosten and Rounsaville1 Pathological gamblers show persistent and recurrent maladaptive gambling behavior, such as loss of control over gambling despite its adverse consequences. Therefore, PG is considered a problem related to impulse control in the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV)2 and the International Classification of Disorders, 10th Revision (ICD-10).Reference Potenza3

Some previous studies have suggested a similarity between PG and obsessive-compulsive disorder (OCD) because, like OCD, PG includes intrusive thoughts focusing on specific themes and repetitive behavior that generates distress.Reference Riggs and Foa4 Unlike clinicians, who have used PG to describe severe problem gambling, Gamblers Anonymous (GA) members have more often used the term “compulsive gambling.”Reference Raylu and Oei5, Reference Lesieur6 Although GA members misuse the term “compulsive” as it is defined by medical terminology, their intuition seems to be correct, considering the link between features of PG and OCD.Reference Lesieur6 Black and MoyerReference Black and Moyer7 found that the most common personality disorder in PG patients was OCD. Hollander and WongReference Hollander and Wong8 also suggested that PG can be viewed as an impulsive subtype of the obsessive-compulsive (OC) spectrum. Many researchers have studied PG patients’ obsessive preoccupation with gambling and have examined the relationship between the PG and the OC spectrum by focusing on clinical features and behavioral patterns.Reference Durdle, Gorey and Stewart9Reference Kim and Grant11 Whether the two disorders are related is still under debate.Reference Kim and Grant11Reference Blanco, Moreyra, Nunes, Saiz-Ruiz and Ibanez13

Given that the link between the PG and the OCD spectrum is unclear, neurocognitive studies could be a strategic alternative to identify the similarities and differences between these clinical groups. Indeed, many studies have identified the unique neurocognitive profiles of various disorders.Reference Rhinewine, Lencz and Thaden14, Reference Ferrier and Thompson15 However, no study has compared neurocognitive functions in PG and OCD patients. Furthermore, because contradictory evidence has been reported with respect to neurocognitive functions, such as executive function or attention, even among studies on PG,Reference Rugle and Melamed16Reference Brand, Kalbe and Labudda18 it is also necessary to identify the neurocognitive functions that are linked with emotional regulation and social, cognitive, and behavioral performance.Reference Greenberg, Kusché and Riggs19 Further, two studies have used the same neurocognitive test and yet shown different behavioral data. For example, one research group reported differences between PG patients and controls on the Wisconsin Card Sorting Test (WCST),Reference Marazziti, Catena Dell'Osso and Conversano20, Reference Heaton, Chelune, Talley, Kay and Curtiss21 whereas another failed to find differences compared to healthy controls.Reference Cavedini, Riboldi, Keller, D'Annucci and Bellodi22

In the present study, we investigated the neurocognitive profiles of PG and OCD groups. If the two disorders belong to the same psychopathological spectrum, the neurocognitive profile should show common patterns. We hypothesized that differing profiles between the two clinical groups would provide evidence for differentiating between PG and OCD.

Methods

Participants

Sixteen male outpatients who met the DSM-IV criteria for PG2 and achieved a score of ≥5 on the South Oaks Gambling Screen (SOGS; mean ± SD, 15.79 ± 1.53)Reference Lesieur and Blume23 were recruited from a psychiatric clinic in one university hospital in Seoul, Korea. We also recruited OCD patients who were drug naïve; this measure was taken to exclude the effects of drugs on neuropsychological performance,Reference Mataix-Cols, Alonso, Pifarré, Menchón and Vallejo24 because the PG patients had never been medicated. Thirty-six patients with OCD were screened from the OCD clinic at Seoul National University Hospital. Of these, 31 (23 males and 8 females) signed consent forms, underwent a Structured Clinical Interview for DSM-IV (SCID), and met the inclusion criteria. Diagnoses and comorbidity were established by experienced psychiatrists using the SCID-Axis I.

Fifty-two healthy controls over 19 years of age (HC; 36 males, 16 females) were recruited through Internet advertisements. HC subjects were also administered the nonpatient form of the SCID (SCID-NP) for Axis I or Axis II disorders. The groups were well matched for age, education, and intelligence. Table 1 provides demographic data. Exclusion criteria for all groups were (i) head injury, medical and neurological disorders, and alcohol or drug abuse; (ii) IQ <80; or (iii) age <19 years. The participants were paid $50 each for their time. Written informed consent was obtained from all participants after they had been completely informed of the study protocols. This study was conducted in accordance with the guidelines provided by the Institutional Review Board at Seoul National University Hospital.

Table 1 Demographic and clinical characteristics of pathological gambling, obsessive-compulsive disorder, and healthy control groups

PG, subject with pathological gambling; OCD, subject with obsessive-compulsive disorder; HC, healthy controls.

BDI, Beck Depression Inventory; BAI; Beck Anxiety Inventory; PG-YBOCS, Yale–Brown Obsessive Compulsive Scale adapted for Pathological Gambling; YBOCS, Yale–Brown Obsessive Compulsive Scale.

NA, not applicable.

aMANOVA analysis for BDI and BAI.

Clinical assessments

The Yale–Brown Obsessive-Compulsive Scale adapted for Pathological Gambling (PG-YBOCS), which was developed to measure the severity of PG symptoms,Reference Pallanti, DeCaria, Grant, Urpe and Hollander25, Reference Spitzer, Gibbon and Williams26 and the Yale–Brown Obsessive-Compulsive Scale (YBOCS)Reference Goodman, Price and Rasmussen27 were used to assess symptoms in the PG and OCD groups, respectively. The severity of depression and anxiety was assessed with the Beck Depression Inventory (BDI)Reference Beck and Steer28 and the Beck Anxiety Inventory (BAI)Reference Beck, Epstein, Brown and Steer29 because the both clinical groups might suffer mental health problems.

Neuropsychological assessments

First, the Vocabulary, Arithmetic, Block Design, and Picture Arrangement subtests of the Korean version of the Wechsler Adult Intelligence Scale (K-WAIS) were administered to provide an IQ estimate.Reference Kim and Lee30 Then, a neurocognitive test battery was administered to assess three main cognitive functions: executive function, verbal learning and memory, and visual organization and memory.

To evaluate executive function, we used the (i) Trail-Making Tests (TMTs),Reference Reitan31 (ii) Controlled Oral Word Association Test (COWA),Reference Benton32 (iii) Category Fluency Test (supermarket and animal),Reference Mattis33, Reference Kertesz34 (iv) Stroop task,Reference Trenerry, Crosson, DeBoe and Leber35 and (v) manual version of the Wisconsin Card Sorting Test (WCST).Reference Heaton, Chelune, Talley, Kay and Curtiss21 These tests require various cognitive functions such as controlled attention, set-shifting ability, abstract concepts, and problem solving.Reference Lezak36

We also administered the Korean version of the California Verbal Learning Test (K-CVLT)Reference Kang and Kim37, Reference Delis, Kramer, Kaplan and Ober38 to assess verbal learning and memory. This test yields recall for 16 target nouns, recall for 16 intervening nouns, immediate and delayed recall of 16 nouns learned verbally, and word recognition.

The Rey–Osterrieth Complex Figure Test (ROCF)Reference Shin, Park, Park, Seol and Kwon39 was used to test for visual organization and memory, together with the Boston Qualitative Scoring System (BQSS).Reference Stern, Singer and Duke40 The BQSS includes measures of copying and immediate and delayed recall, as well as a series of subscales such as planning (the order in which the elements are drawn), fragmentation (whether the elements are drawn as entities or as pieces), and organization (sum of planning and fragmentation scores).

The above neuropsychological tests took 1.5 hours to complete, and they were administered during a single day.

Statistical analysis

One-way analysis of variance (ANOVA) or χ2 tests were performed on demographic and clinical variables. Multivariate analysis of variance (MANOVA) with Bonferroni's post hoc tests were conducted on the neuropsychological variables due to the possibility of correlations among the variables. The relationship between the performance on the neuropsychological tests and clinical symptoms among the PG and OCD subjects was explored by Spearman rank correlation and Pearson's correlation, respectively. In the statistical analyses, P < .05 was considered significant.

Results

Demographic data

The mean age of the PG subjects was 28.31 ± 3.79 years, and the mean duration of illness since the onset of symptoms was 2.19 years (SD = 1.24). The mean age of the OCD patients was 26.90 ± 6.47 years, and the mean duration of illness since the onset of symptoms was 8.51 years (SD = 7.24). The mean age of the HCs was 25.13 ± 5.0 years. We found no differences among the PG, OCD, and HC groups in age (F[2,96] = 2.55, P = .084), education (F[2,96] = 1.95, P = .148), and IQ (F[2,96] = 0.23, P = .797); a difference in sex distribution was found (χ2[2] = 6.37, P = .041) (Table 1).

Clinical assessments

The mean score on the PG-YBOCS was 16.13 ± 7.03 in PG subjects. The mean score on the YBOCS was 23.40 ± 6.52 in OCD subjects. The MANOVA for BDI and BAI revealed significant group differences (Wilks’ λ = .62; F[2,93] = 12.33; P < .001; for three HCs, clinical evaluation was not available). The OCD subjects were found to be more depressed and more anxious compared with the HC group (both P < .001), whereas the PGs showed only greater depression compared with the HC subjects (P < .001) (Table 1).

Neurocognitive assessments

MANOVA showed significant group differences in some assessments of executive function (Wilks’ λ = .62; F[2,96] = 1.92; P = .017; WCST nonperseverative errors, P = .031 Stroop inference index, P = .004). The Bonferroni's post hoc test revealed that PG subjects demonstrated more nonperseverative error on the WCST than HCs did (P = .026), whereas OCD patients had poorer performance on the Stroop inference index (measured as the time for the color–word condition minus that for the word condition) compared with that in the HC group (P = .005) (Table 2, Figure 1).

Table 2 Mean scores and standard deviation of neurocognitive test in pathological gambling, obsessive-compulsive disorder, and healthy control groups

PG, subject with pathological gambling; OCD, subject with obsessive-compulsive disorder; HC, healthy controls.

TMT, Trail Making Test; COWAT, Controlled Oral Word Association Test; WCST, Wisconsin Card Sorting Test; PSV, Perseverative; WCST category, WCST category completed; CVLT, California Verbal Learning Test; IR, Immediate recall; DR, Delayed recall; ROCF, Rey–Osterrieth Complex Figure Test; RT, response time; BQSS, Boston Qualitative Scoring System for ROCF.

Figure 1 Z-scores of the differences between the OCD and PG group on neurocognitive performances. PG, subject with pathological gambling; OCD, subject with obsessive-compulsive disorder; HC, healthy controls. The z-scores were calculated based on the mean ± SD of the HC group. Plus/minus signs of some of variables were reversed to adjust the severity profile in the graph. Abbreviations as in Table 2. *OCD < HC, **PG < HC, ***OCD = PG < HC.

There was no significant group difference in any index of verbal learning and memory as assessed by CVLT (Wilks’ λ = .86; F[2,96] = 1.49; P = .146, Table 2). However, the BQSS scores on the ROCF suggested statistical differences among groups (Wilks’ λ = .76; F[2,96] = 1.90; P = .029; immediate retention P = .012; fragmentation P = .003; organization P = .006; Table 2). The Bonferroni's post hoc test revealed that the OCD subjects showed weaker retention in immediate recall and more fragmentation than did HCs (P = .011 and P = .041, respectively). With the same analyses, more fragmentation and less organization were found in the PG subjects compared with the HCs (P = .008 and P = .015, respectively).

Although group differences emerged in the response time on the TMT-B (P = .044) and in the BQSS delayed recall on the ROCF (P = .049), post hoc adjustments for multiple comparisons using Bonferroni's test resulted in no statistically significant differences.

There was a group difference in sex (P = .041); however, MANOVA for the OCD and HC groups and for all the subjects (N = 99) showed no evidence that neurocognitive functioning differed according to sex (all P > .05).

Discussion

We evaluated the neurocognitive functioning of PG and OCD subjects. The only common neurocognitive deficit shared by PG and OCD was the fragmentation error in the ROCF copying subtest. The PG subjects showed more nonperseverative errors on the WCST and less organization in construction on the ROCF compared with the HC group, whereas the OCD subjects performed worse on the Stroop inference test and in retention and immediate recall on the ROCF compared with the HC subjects. In short, the main findings showed differences in neurocognitive patterns between the PG and OCD groups, which could be evidence against the hypothesis that the two clinical entities represent positions on the same spectrum.

In the present study, the PG subjects committed more nonperseverative errors on the WCST. A previous review that analyzed 59 schizophrenia studies suggested that nonperseverative errors were a sign of impairment in set-shifting or inhibitory functions.Reference Li41 Another study also indicated that nonperseverative errors on the WCST had clinical implications for prefrontal impairment, as did perseverative response tendencies.Reference Barceló and Knight42 Thus nonperseverative errors appear to be related to inhibition, working memory, reasoning, strategy selection, monitoring, and task management,Reference Burgess and Shallice43Reference Smith and Jonides45 revealing ineffective cognitive processes among the PG group. These deficits in strategy selection, the irrational approach to a series of problems, and reduced monitoring and episodic memory might make the PG subjects persist in their damaging behavior.Reference Potenza, Kosten and Rounsaville1

Meanwhile, the OCD subjects showed similar levels of WCST performance to those of the HC subjects, which was consistent with previous studies reporting unimpaired WCST performance in OCD patients.Reference Kim, Park, Shin and Kwon46Reference Olley, Malhi and Sachdev49 The OCD group revealed inhibition deficits on the Stroop task in our study that correspond to findings in previous studies,Reference Rao, Reddy, Kumar, Kandavel and Chandrashekar50, Reference Bannon, Gonsalvez, Croft and Boyce51 but they did not show deficits in strategic reasoning, which were seen in the PG group.

We found that PG subjects showed more fragmentation and less organization compared with the HCs, whereas OCD subjects showed only increased fragmentation and retention impairment on the ROCF. In line with Seidman etal.'sReference Seidman, Stone, Jones, Harrison and Mirsky52 suggestion that the copying process is associated with visual memory performance, both poor organization and weak recall performance were shown together in the OCD group. Meanwhile, the PG subjects did not reveal any dysfunction in recall and recognition on the ROCF. Even though the PG subjects showed no deficit in the quantitative ROCF scores, they seemed not to use the organizational strategy or gestalt image to solve the problem when it was copied or recalled.Reference Shin, Park, Park, Seol and Kwon39 Although the PG subjects’ performance on the visual memory test seems to have been compensated for by their high average intelligence, their approach to the complex visual–spatial stimuli was poor compared with that of the HC subjects, and the deficits were broader than those in the OCD group.

Less efficient problem solving or organizational strategies have been also reported in patients with alcohol dependence, which is the most common substance-related disorder.Reference Sullivan, Mathalon, Ha, Zipursky and Pfefferbaum53 The poor organization of ROCF shown in the PG subjects was especially revealed in the patients with alcohol dependence.Reference Dawson and Grant54 The common trait between PG and alcohol dependence groups may be plausible, because the DSM-V work group has reclassified PG as a substance-related disorder that will be renamed “addiction and related disorders—substance use disorder.”55

We tried to investigate the relationship between clinical symptoms and impaired neurocognitive functions in the PG and OCD subjects. However, clinical measures including BDI, BAI, YBOCS, and PG-YBOCS did not show any significant relationship to cognitive measures (all P > .05). That is, the neurocognitive profile of each group was not related to the severity of clinical symptoms, but occurrence of critical symptoms itself could be a crucial factor for the neurocognitive pattern in each group.

One major limitation should be considered when interpreting our results. In Korea, the rate of PG among men is much higher than that in women (9:1); therefore, it was difficult to include female pathological gamblers.Reference Shin, Lim, Choi, Kim and Grant56 This selection bias may have limited generalization of the results, even though no gender effect on neurocognitive functions was found in the OCD and HC groups. Further research should assess both men and women with a large number of cases to confirm the present results.

Conclusion

To the best of our knowledge, this is the first comparison of neurocognitive profiles in PG and OCD groups. The only common deficit shared by the PG and the OCD groups was increased fragmentation on the ROCF. OCD was associated with deficits in inhibition and visual memory, whereas the deficits in the PG group were more concentrated in strategy selection, reasoning, and task management. Considering these differences, we should be cautious before assuming a link between the PG and the OCD spectrum. A challenge for future research is to further understand these disorders and to develop new interventions.

References

1.Potenza, MN, Kosten, TR, Rounsaville, BJ. Pathological gambling. JAMA. 2001; 286(2): 141144.CrossRefGoogle ScholarPubMed
2.American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 4th ed., text revision. Washington, DC: American Psychiatric Association; 2000.Google Scholar
3.Potenza, MN. The neurobiology of pathological gambling and drug addiction: an overview and new findings. Philos Trans R Soc Lond B, Biol Sci. 2008; 363(1507): 31813189.CrossRefGoogle ScholarPubMed
4.Riggs, DS, Foa, EB. Obsessive-compulsive disorder. In: Barlow DH, ed. Comprehensive Handbook of Personality and Psychopathology. New York: Guilford Press; 1993: 189239.Google Scholar
5.Raylu, N, Oei, TPS. Pathological gambling: A comprehensive review. Clin Psychol Rev. 2002; 22(7): 10091061.CrossRefGoogle ScholarPubMed
6.Lesieur, H. Compulsive gambling. Society. 1992; 29(4): 4350.CrossRefGoogle Scholar
7.Black, DW, Moyer, T. Clinical features and psychiatric comorbidity of subjects with pathological gambling behavior. Psychiatr Serv. 1998; 49(11): 14341439.CrossRefGoogle ScholarPubMed
8.Hollander, E, Wong, CM. Obsessive-compulsive spectrum disorders. J Clin Psychiatry. 1995; 56(suppl 4): 36.Google ScholarPubMed
9.Durdle, H, Gorey, KM, Stewart, SH. A meta-analysis examining the relations among pathological gambling, obsessive-compulsive disorder, and obsessive-compulsive traits. Psychol Rep. 2008; 103(2): 485498.CrossRefGoogle ScholarPubMed
10.Potenza, MN. Impulsivity and compulsivity in pathological gambling and obsessive-compulsive disorder. Rev Bras Psiquiatr. 2007; 29(2): 105106.CrossRefGoogle ScholarPubMed
11.Kim, SW, Grant, JE. Personality dimensions in pathological gambling disorder and obsessive-compulsive disorder. Psychiatry Res. 2001; 104(3): 205212.CrossRefGoogle ScholarPubMed
12.Black, DW, Goldstein, R, Noyes, R, Blum, N. Compulsive behaviors and obsessive-compulsive disorder (OCD): Lack of a relationship between OCD, eating disorders, and gambling. Compr Psychiatry. 1994; 35(2): 145148.CrossRefGoogle Scholar
13.Blanco, C, Moreyra, P, Nunes, EV, Saiz-Ruiz, J, Ibanez, A. Pathological gambling: addiction or compulsion? Semin Clin Neuropsychiatry. 2001; 6(3): 167176.Google ScholarPubMed
14.Rhinewine, JP, Lencz, T, Thaden, EP, etal. Neurocognitive profile in adolescents with early-onset schizophrenia: Clinical correlates. Biol Psychiatry. 2005; 58(9): 705712.CrossRefGoogle ScholarPubMed
15.Ferrier, IN, Thompson, JM. Cognitive impairment in bipolar affective disorder: implications for the bipolar diathesis. Br J Psychiatry. 2002; 180(4): 293295.CrossRefGoogle ScholarPubMed
16.Rugle, L, Melamed, L. Neuropsychological assessment of attention problems in pathological gamblers. J Nerv Ment Dis. 1993; 181(2): 107112.CrossRefGoogle ScholarPubMed
17.Regard, M, Knoch, D, Gütling, E, Landis, T. Brain damage and addictive behavior: a neuropsychological and electroencephalogram investigation with pathologic gamblers. Behav Cogn Neurosci Rev. 2003; 16(1): 4753.Google ScholarPubMed
18.Brand, M, Kalbe, E, Labudda, K, etal. Decision-making impairments in patients with pathological gambling. Psychiatry Res. 2005; 133(1): 9199.CrossRefGoogle ScholarPubMed
19.Greenberg, MT, Kusché, CA, Riggs, N. The PATHS curriculum: theory and research on neurocognitive development and school success. In: Zins JE, Weissberg RP, Wang MC, Walberg HJ, eds. Building Academic Success on Social and Emotional Learning. New York: Teachers College Press; 2004: 170.Google Scholar
20.Marazziti, D, Catena Dell'Osso, M, Conversano, C, etal. Executive function abnormalities in pathological gamblers. Clin Pract Epidemiol Ment Health. 2008; 4(1): 7.CrossRefGoogle ScholarPubMed
21.Heaton, RK, Chelune, GJ, Talley, JL, Kay, GG, Curtiss, G. Wisconsin Card Sorting Test Manual. Odessa, FL: Psychological Assessment Resources; 1993.Google Scholar
22.Cavedini, P, Riboldi, G, Keller, R, D'Annucci, A, Bellodi, L. Frontal lobe dysfunction in pathological gambling patients. Biol Psychiatry. 2002; 51(4): 334341.CrossRefGoogle ScholarPubMed
23.Lesieur, H, Blume, S. The South Oaks Gambling Screen (SOGS): a new instrument for the identification of pathological gamblers. Am J Psychiatry. 1987; 144(9): 11841188.Google ScholarPubMed
24.Mataix-Cols, D, Alonso, P, Pifarré, J, Menchón, JM, Vallejo, J. Neuropsychological performance in medicated vs. unmedicated patients with obsessive-compulsive disorder. Psychiatry Res. 2002; 109(3): 255264.CrossRefGoogle ScholarPubMed
25.Pallanti, S, DeCaria, C, Grant, JE, Urpe, M, Hollander, E. Reliability and validity of the Pathological Gambling Adaptation of the Yale-Brown Obsessive-Compulsive Scale (PG-YBOCS). J Gambl Stud. 2005; 21(4): 431443.CrossRefGoogle ScholarPubMed
26.Spitzer, R, Gibbon, M, Williams, J. Structured Clinical Interview for Axis I DSM-IV Disorders (SCID). Washington, DC: American Psychiatric Assocication; 1995.Google Scholar
27.Goodman, WK, Price, LH, Rasmussen, SA, etal. The Yale–Brown Obsessive Compulsive Scale: I. development, use, and reliability. Arch Gen Psychiatry. 1989; 46(11): 10061011.CrossRefGoogle ScholarPubMed
28.Beck, AT, Steer, RA. BDI, Beck Depression Inventory: Manual. Philadelphia: Center for Cognitive Therapy; 1978.Google Scholar
29.Beck, AT, Epstein, N, Brown, G, Steer, RA. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol. 1988; 56(6): 893897.CrossRefGoogle ScholarPubMed
30.Kim, Z-S, Lee, Y-S. Validity of short forms of the Korean-Wechsler Adult Intelligence Scale. Korean J Clin Psychol. 1995; 14: 111116.Google Scholar
31.Reitan, RM. Validity of the Trail Making Test as an indicator of organic brain damage. Percept Mot Skills. 1958; 8(3): 271276.CrossRefGoogle Scholar
32.Benton, A. Development of a multilingual aphasia battery: progress and problems. J Neurol Sci. 1969; 9(1): 3948.CrossRefGoogle ScholarPubMed
33.Mattis, S. Dementia Rating Scale. Odessa, FL: Psychological Assessment Resources; 1988.Google Scholar
34.Kertesz, A. Western Aphasia Battery Test Manual. San Antonio, TX: The Psychological Corporation; 1982.Google Scholar
35.Trenerry, MR, Crosson, B, DeBoe, J, Leber, WR. Stroop Neuropsychological Screening Test Manual. Odessa, FL: Psychological Assessment Resources; 1989.Google Scholar
36.Lezak, MD. Neuropsychological Assessment, 4th ed. New York: Oxford University Press; 2004.Google Scholar
37.Kang, YW, Kim, JK. Korean-California Verbal Learning Test (K-CVLT): a normative study. Korean J Clin Psychol. 1997; 16(2): 379396.Google Scholar
38.Delis, DC, Kramer, J, Kaplan, E, Ober, BA. California Verbal Learning Test. New York: Psychological Corporation; 1987.Google Scholar
39.Shin, MS, Park, SY, Park, SR, Seol, SH, Kwon, JS. Clinical and empirical applications of the Rey-Osterrieth complex figure test. Nat Protoc. 2006; 1(2): 892899.Google ScholarPubMed
40.Stern, RA, Singer, EA, Duke, LM, etal. The Boston Qualitative Scoring System for the Rey-Osterrieth Complex Figure: description and interrater reliability. Clin Neuropsychol. 1994; 8(3): 309322.CrossRefGoogle Scholar
41.Li, C-SR. Do schizophrenia patients make more perseverative than non-perseverative errors on the Wisconsin Card Sorting Test? A meta-analytic study. Psychiatry Res. 2004; 129(2): 179190.CrossRefGoogle ScholarPubMed
42.Barceló, F, Knight, RT. Both random and perseverative errors underlie WCST deficits in prefrontal patients. Neuropsychologia. 2002; 40(3): 349356.CrossRefGoogle ScholarPubMed
43.Burgess, PW, Shallice, T. Bizarre responses, rule detection and frontal lobe lesions. Cortex. 1996; 32(2): 241259.CrossRefGoogle ScholarPubMed
44.Gehring, WJ, Knight, RT. Lateral prefrontal damage affects processing selection but not attention switching. Cogn Brain Res. 2002; 13(2): 267279.CrossRefGoogle Scholar
45.Smith, EE, Jonides, J. Storage and executive processes in the frontal lobes. Science. 1999; 283(5408): 16571661.CrossRefGoogle ScholarPubMed
46.Kim, M-S, Park, S-J, Shin, MS, Kwon, JS. Neuropsychological profile in patients with obsessive-compulsive disorder over a period of 4-month treatment. J Psychiatr Res. 2002; 36(4): 257265.CrossRefGoogle Scholar
47.Chamberlain, SR, Blackwell, AD, Fineberg, NA, Robbins, TW, Sahakian, BJ. The neuropsychology of obsessive compulsive disorder: the importance of failures in cognitive and behavioural inhibition as candidate endophenotypic markers. Neurosci Biobehav Rev. 2005; 29(3): 399419.CrossRefGoogle ScholarPubMed
48.Abbruzzese, M, Ferri, S, Scarone, S. Wisconsin Card Sorting Test performance in obsessive-compulsive disorder: no evidence for involvement of dorsolateral prefrontal cortex. Psychiatry Res. 1995; 58(1): 3743.CrossRefGoogle ScholarPubMed
49.Olley, A, Malhi, G, Sachdev, P. Memory and executive functioning in obsessive-compulsive disorder: a selective review. J Affect Disord. 2007; 104(1–3): 1523.CrossRefGoogle ScholarPubMed
50.Rao, NP, Reddy, YCJ, Kumar, KJ, Kandavel, T, Chandrashekar, CR. Are neuropsychological deficits trait markers in OCD? Prog Neuropsychopharmacol Biol Psychiatry. 2008; 32(6): 15741579.CrossRefGoogle ScholarPubMed
51.Bannon, S, Gonsalvez, CJ, Croft, RJ, Boyce, PM. Response inhibition deficits in obsessive-compulsive disorder. Psychiatry Res. 2002; 110(2): 165174.CrossRefGoogle ScholarPubMed
52.Seidman, LJ, Stone, WS, Jones, R, Harrison, RH, Mirsky, AF. Comparative effects of schizophrenia and temporal lobe epilepsy on memory. J Int Neuropsychol Soc. 1998; 4(4): 342352.CrossRefGoogle ScholarPubMed
53.Sullivan, EV, Mathalon, DH, Ha, CN, Zipursky, RB, Pfefferbaum, A. The contribution of constructional accuracy and organizational strategy to nonverbal recall in schizophrenia and chronic alcoholism. Biol Psychiatry. 1992; 32(4): 312333.CrossRefGoogle ScholarPubMed
54.Dawson, LK, Grant, I. Alcoholics’ initial organizational and problem-solving skills predict learning and memory performance on the Rey–Osterrieth Complex Figure. J Int Neuropsychol Soc. 2000; 6(1): 1219.CrossRefGoogle ScholarPubMed
55. American Psychiatric Association. DSM-5 development: pathological gambling http://www.dsm5.org/ProposedRevisions/Pages/proposedrevision.aspx?rid=210#, 2010 (accessed 12 May 2012).Google Scholar
56.Shin, Y-C, Lim, S-W, Choi, S-W, Kim, S, Grant, J. Comparison of temperament and character between early- and late-onset Korean male pathological gamblers. J Gambl Stud. 2009; 25(4): 447453.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Demographic and clinical characteristics of pathological gambling, obsessive-compulsive disorder, and healthy control groups

Figure 1

Table 2 Mean scores and standard deviation of neurocognitive test in pathological gambling, obsessive-compulsive disorder, and healthy control groups

Figure 2

Figure 1 Z-scores of the differences between the OCD and PG group on neurocognitive performances. PG, subject with pathological gambling; OCD, subject with obsessive-compulsive disorder; HC, healthy controls. The z-scores were calculated based on the mean ± SD of the HC group. Plus/minus signs of some of variables were reversed to adjust the severity profile in the graph. Abbreviations as in Table 2. *OCD < HC, **PG < HC, ***OCD = PG < HC.