• Users Online: 9
  • Print this page
  • Email this page

 
Table of Contents
ORIGINAL ARTICLE
Year : 2021  |  Volume : 35  |  Issue : 3  |  Page : 124-131

Cognitive function and alcohol use disorder: Path analysis for a cross-sectional study in Taiwan


1 Department of Occupational Therapy, Kaohsiung Municipal Kai-Syuan Psychiatric Hospital; Department of Occupational Therapy, Shu-Zen Junior College of Medicine and Management, Kaohsiung, Taiwan
2 Department of Nursing, Kaohsiung Municipal Kai-Syuan Psychiatric Hospital; Department of Nursing, Fooyin University, Kaohsiung, Taiwan
3 Department of Addiction Science, Kaohsiung Municipal Kai-Syuan Psychiatric Hospital; Department of Sports, Health and Leisure and Graduate Institute of Sports, Health and Leisure, Cheng Shiu University, Kaohsiung, Taiwan
4 Department of Occupational Therapy, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
5 Department of Superintendent, Kaohsiung Municipal Kai-Syuan Psychiatric Hospital, Kaohsiung, Taiwan
6 Department of Child and Adolescent Psychiatry, Kaohsiung Municipal Kai-Syuan Psychiatric Hospital; Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

Date of Submission08-Jan-2021
Date of Decision13-Feb-2021
Date of Acceptance17-Feb-2021
Date of Web Publication24-Sep-2021

Correspondence Address:
Frank Huang-Chih Chou
No. 130, Kaisyuan Second Road, Lingya District, Kaohsiung 802211
Taiwan
Kuan- Ying Hsieh
130, Kaisyuan Second Road, Lingya District, Kaohsiung 802211
Taiwan
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/TPSY.TPSY_25_21

Rights and Permissions
  Abstract 


Objective: Alcohol has cognitive impacts on patients with alcohol use disorder (AUD). In this study, we intended to study cognitive impairments in patients with AUD and their potential interrelationships. Methods: We enrolled 60 patients with AUD or alcohol intoxication in Taiwan. The severity of alcohol use was assessed using a copy for severity of alcohol dependence questionnaire (SADQ). Cognitive function was evaluated using Stroop color and word test, continuous performance test-identical pairs, trail making test, visual alternating and divided attention subscales of computerized everyday attention test, visual elevator subscale of test of everyday attention, Benton judgment of line orientation test, spatial perception subscale of visual object perception test, visual motor organization subscale of Loewenstein occupational therapy, thinking operations subscale of Loewenstein occupational therapy cognitive assessment, digit symbol coding subscale of Wechsler adult intelligence scale-third edition, as well as symbol digit modalities test. Moreover, we used a structural equation modeling (SEM) to link age, duration of alcohol use, SADQ, and cognitive impairments. Results: Patients with AUD had significantly impairments of “attention” (p < 0.01), “visual motor coordination” (p < 0.001), and “executive function” (p < 0.01). SEM analysis showed that the higher level of attention, visual motor coordination, and executive functional impairments were significantly linked with old age (p < 0.01), long duration of alcohol use (p < 0.01), and higher score of SADQ (p < 0.01). Furthermore, we found that the three cognitive impairments were positively associated with each other. Conclusion: Old age, long duration of alcohol use, and severe alcohol use were the predictors of cognitive impairments and early detection. The early screening of predictive factors and timely interventions should be considered to improve cognitive function in patients with AUD.

Keywords: alcohol dependence, attention, executive function, visual motor coordination


How to cite this article:
Cheng CH, Huang LL, Kao WT, Su CY, Chou FH, Hsieh KY. Cognitive function and alcohol use disorder: Path analysis for a cross-sectional study in Taiwan. Taiwan J Psychiatry 2021;35:124-31

How to cite this URL:
Cheng CH, Huang LL, Kao WT, Su CY, Chou FH, Hsieh KY. Cognitive function and alcohol use disorder: Path analysis for a cross-sectional study in Taiwan. Taiwan J Psychiatry [serial online] 2021 [cited 2021 Dec 6];35:124-31. Available from: http://www.e-tjp.org/text.asp?2021/35/3/124/326575




  Introduction Top


Almost 40% of the world's population has consumed alcohol in the past 12 months [1]. The lifetime prevalence of alcohol use disorder (AUD) is 11.1% in patients of a primary care setting in Taiwan [2]. The prevalence of AUD is higher in men than in women (3.2% vs. 0.2%), respectively [3]. Almost 78% of alcohol-dependent people have remarkable brain changes have been found in postmortem autopsy [4],[5]. Therefore, alcohol use and related problems are important.

Acute alcohol use affects perceptual and motor functions, including increased reaction times as well as decreased motor or cognitive functions, and attention [6],[7],[8],[9],[10],[11],[12]. Chronic excessive alcohol use is associated with shrinkage in white and gray matter, ventricular enlargement, widening of the sulci, and neuronal loss in the cerebellum [13],[14],[15],[16],[17],[18], leading to functional loss. The neuropsychological deficits seen in patients with alcohol use are associated with several neurological circuits, including frontocerebellar circuit, limbic system, network of addiction, and motivation [19]. The variation in clinical presentation and level of brain damage seen in alcohol-dependent individuals are influenced not only by alcohol itself but also by other factors, including injury and trauma, polysubstance use, poor nutritional status, as well as repeated periods of withdrawal and intoxication [19]. The Diagnostic and Statistical Manual of Mental Disorders, the Fifth Edition (DSM-5) now recognizes that cognitive deficits with chronic excessive alcohol use are alcohol-induced neurocognitive disorders [20]. But the prevalence and distribution of cognitive impairment as well as its association with severity or duration of alcohol use have rarely been studied and reported in Taiwan.

Alcohol-related cognitive impairments have been reported in previous studies, including attention [21],[22],[23],[24] visual motor coordination [25],[26], and executive function [27],[28]. In previous research, identified risk factors include gender [2],[3],[29], and age [30]. But few numbers of cognitive measures have been used to examine the interrelationship between cognitive impairments in those studies. Therefore, we need a comprehensive evaluation of known risk factors of cognitive impairments in alcohol users.

We hypothesized that the cognitive impairments could be related to sociodemographic factors, duration of alcohol use, and severity of alcohol use. Carrying out a cross-sectional study and using a path analysis, we intended to study the cognitive impairments among AUD patients and to explore the potential interrelationships among attention, visual motor coordination, and executive function.


  Methods Top


Study participants

Participants were recruited in the Kaohsiung Municipal Kai-Syuan Psychiatric Hospital (KSPH) inpatient, outpatient, and home-visit service in Taiwan. Participants were recruited from May 17, 2016, to January 14, 2017.

The inclusion criteria were individuals with (a) being aged between 45 and 65 years, (b) being diagnosed by psychiatrists with AUD or alcohol intoxication according to the criteria of the DSM-5 [20], (c) being abstinent for at least preceding two weeks, (d) having moderate or severe AUD with a score 16 or more on the copy of Chinese version of the severity of alcohol dependence questionnaire (SADQ) [31], (e) understanding the objective of the study, and (f) being able to follow the instructions from research assistants. Informed consent was obtained before participants started to fill in the copy of questionnaire.

The exclusion criteria were individuals with (a) psychiatric comorbidities, (b) a history of neurological disease, (c) having severe visual or hearing impairment, and (d) currently experiencing withdrawal symptoms.

The study was approved by the institutional review board (IRB) of KSPH (IRB protocol number = KSPH-2015-32 and date of approval = May 17, 2016), with the stipulation of obtaining informed consent from all study participants.

Measures

Severity of alcohol dependence questionnaire

The severity of alcohol dependence questionnaire (SADQ) is a 20-item copy of self-administered questionnaire, consisting of five sections to assess the severity of alcohol-related problems in the preceding month [32]. Each section of SADQ has four items – including physical withdrawal signs, affective withdrawal signs, withdrawal relief drinking and alcohol consumption, as well as reinstatement of withdrawal symptoms following abstinence in sequence. Each item is assessed on a four-point scale, with a score ranging from 0 to 3. A previous study has been validated that individuals with scores of 31 or higher, 16–30, and 16 or lower being victims with severe, moderate, or mild AUD, respectively [31].

The Stroop color and word test

The Stroop color and word test (SCWT) is a neuropsychological test extensively used to assess the ability to inhibit cognitive interference, which occurs when the processing of a stimulus feature affects the simultaneous processing of another attribute of the same stimulus [33]. Subjects are required to name color-word (CW) condition, and CWs are printed in an inconsistent color ink (for instance, the word “red” is printed in green ink). The score is the number of correct responses completed in 45 seconds. The SCWT is widely used to measure cognitive functions such as attention, processing speed, cognitive flexibility [34], and working memory [35].

Continuous performance test-identical pairs

Continuous performance test-identical pairs (CPT-IPs) are a family of neuropsychological measures originally developed to assess sustained attention and vigilance following traumatic brain injury [36]. The CPT-IPs require subjects to respond when the same stimulus appears twice in a row (an “identical pair”) so that subjects need to decode each stimulus carefully and keep it in working memory until it can be compared with the one immediately following [37]. The CPT-IP is to measure vigilance and sustained attention as well as working memory [38],[39],[40].

Trail making test-B

The trail making test part B (TMT-B) entails the ability to switch and divide attention between two conceptually distinct tasks that are done simultaneously [41]. In the Chinese version, participants are requested to connect the circles that include both numbers (1-12) and Chinese zodiac animals (from rats to boars) in the ascending order. Performance was expressed in the time taken to complete the trial. TMT-B is considered also to be a test of cognitive flexibility [41].

Visual elevator subscale of test of everyday attention

The visual elevator subtest of test of everyday attention (TEA-VE) subtest is to assess working memory, including sustained volitional attention contribution [42]. Participants count up and down aloud as they follow a series of pictures, indicating the direction of elevator travel, and report at which floor the lift has finished. The number of correct responses was recorded.

Benton judgment of line orientation test

The Benton judgment of line orientation test (BJOT) is a neuropsychological examination to assess visual spatial ability [43]. BJOT materials consist of 35 stimuli in a spiral-bound booklet. The stimuli appear in the upper part of the booklet with the same multiple-choice response card in the lower part. The response choice consists of an array of 11 lines, numbered consecutively, and drawn at 18° intervals from the point of origin. The BJOT has good validity and reliability [44].

Spatial perception subscale of visual object perception test

The space perception (SP) subscale of the visual object and space perception (VOSP-SP) comprises four subtests – spatial scanning, positions in space, spatial discrimination, and complex spatial relationships [45]. These subtest scores are summed up for a total score.

Visual motor coordination organization subscale of Loewenstein occupational therapy

The visual motor coordination organization subscale of the Lowenstein occupational therapy cognitive battery (LOTCA-VM) is used to probe the ability to visual motor coordination organization [46]. The test comprises seven items scored 1–4 points, with higher scores, suggesting greater capability for visual motor coordination organization.

Thinking operations subscale of Loewenstein occupational therapy cognitive assessment

The thinking operations (TO) subscale of the Lowenstein occupational therapy cognitive battery (LOTCA-TO) is used to probe the ability to categorize, sequence, and apply basic logic to solve problems [46]. The test consists of seven items scored 1–4 or 1–5 points, with higher scores, suggesting greater capability for concept function.

Digit symbol coding subscale of Wechsler adult intelligence scale-third edition

Digit symbol coding subscale of Wechsler adult intelligence scale-third edition (WAIS-III-DS) is a neuropsychological test to measure information processing speed, including serial processing, visual motor coordination, and associative learning [47]. It consists of digit-symbol pairs followed by a list of digits. Under each digit, the subject should write down the corresponding symbol as fast as possible. The number of correct symbols within the allowed time (120 s) is measured.

Symbol digit modalities test

The symbol digit modalities test (SDMT) is developed to assess key neurocognitive functions that underlie many substitution tasks, including attention, visual scanning, and motor speed [48]. The SDMT requires individuals to identify nine different symbols corresponding to the numbers 1 through 9 and to practice writing the correct number under the corresponding symbol. Then, they manually fill the blank space under each symbol with the corresponding number. A second oral administration is needed. The study participant was given a blank copy of the test and asked to state the correct number for each corresponding symbol in 90 s. Written and oral score were calculated with totaling the number of correct answers for each section.

Statistical analysis

To sort out interrelations among large numbers of psychological measures, we categorized them into three factors – including attention, visual motor coordination, and executive function – with confirmatory factor analysis (CFA), a maximum likelihood estimation required to ensure model statistics to obtain factor structure. Loading scores were used to weight the chosen cognitive measures within each CFA component to generate factor score, and the variables with loading scores greater than 0.50 were designated as the major contributors of the components.

In this study, we used Pearson's correlation to analyze the mutual relationships between gender, age, duration of alcohol use, SADQ, and cognitive factors using CFA. Moreover, this study used a structural equation modeling (SEM) to find causal relationship and the strength of the relationships between cognition and AUD.

SEM is better than traditional methods (e.g., multivariate regression) in analyzing complex causal relationships among variables [49]. The maximum likelihood estimation of model parameters is used to conduct SEM. Usually, the standardized root mean square residual (SRMR) should fall below 0.08 [50]; root mean square error of approximation (RMSEA) should fall below 0.08 [51],[52]. Comparative fit index (CFI) and non-normed fit index (NFI) above 0.9 [52] indicate a good fit, as well as a standard Chi-square (chi-square/df) smaller than 2 [50] or smaller than 5 [53]. A test for validity of the internal standardized tools was also carried out in this study.

All statistical analyses were done using Statistical Package for the Social Science software version 20.0 software (SPSS Inc., Chicago, Illinois, USA) and Amos 20.0 software (International Business Machine Corp., Armonk, New York, USA). Variables were shown as mean ± standard deviation. We also did group comparisons between females and males using t-tests for continuous variables. The difference between groups were considered significant if p-values were smaller than 0.05.


  Results Top


Totally, 60 individuals, 21 females and 39 males, participated in this study [Table 1]. The female and the male subjects were comparable without significant differences in age, duration of alcohol use, SADQ, and all psychological measures.
Table 1: Comparison of demographics and cognitive functions between females and males in patients with alcohol use disorder

Click here to view


[Table 2] shows three cognitive factors studied by CFA in which loading values for all variables were presented. The cognitive factors were, respectively, named according to the selected variables. Factor 1 primarily consisting of SCWT, CPT-IP, TMT-B, and TEA-VE was therefore labeled “attention.” Factor 2 containing BJOT, VOSP-SP, and LOTCA-VM, all in the same direction, was labeled “visual motor coordination.” The main components of factor 3 were LOTCA-TO, WAIS-III-DS, and SDMT and were named “executive function.” CFA fit index is within acceptable range: CFI = 0.627, IFI = 0.634, and NFI = 0.587. Except SRMR = 0.475, RMSEA = 0.278, standard Chi-square = 5.563 (Chi-square = 244.759, df = 44, p < 0.001). Otherwise, each factor's factor load was as follows: Factor 1 factor load = 0.71–0.86, factor 2 factor load = 0.65–0.92, factor 3 factor load = 0.90–0.95. Overall, current model shows that data were in an acceptable fit. Internal consistency of three factors measures with a Cronbach's α value of 0.68, 0.70, and 0.88, respectively.
Table 2: Cronbach's α and factor loading sores of the cognitive tests

Click here to view


[Table 3] shows correlation coefficients among gender, age, duration of alcohol use, and SADQ and the three cognitive factors. Gender did not have significant correlations to any cognitive factors. Age had a significantly negative correlation with “attention” (r = −0.472, p < 0.01), “visual motor coordination” (r = −0.522, p < 0.001), and “executive function” (r = −0.397, p < 0.01). Duration of alcohol use revealed a significantly negative correlation to “attention” (r = −0.734, p < 0.001), “visual motor coordination” (r = −0.718, p < 0.001), and “executive function” (r = −0.717, p < 0.001). SADQ was also significantly and negatively correlated with “attention” (r = −0.901, p < 0.001), “visual motor coordination” (r = −0.905, p < 0.001), and “executive function” (r = −0.905, p < 0.001).
Table 3: Correlation between attention, visual motor coordination, executive function, gender, age, duration of alcohol use, and severity of alcohol dependence questionnaire

Click here to view


[Figure 1] shows the results of the path analysis of age, duration of alcohol use, SADQ, and the three cognitive factors. The aforementioned correlation between age, duration of alcohol use, and three cognitive factors remained similar and significant in the SEM. In addition, the score of SADQ was significantly associated with duration of alcohol use (β = 0.61, p < 0.001). “Attention” (β = −0.74, p < 0.001), “visual motor coordination” (β = −0.76, p < 0.001), and “executive function” (β = −0.76, p < 0.001) were both significantly and inversely associated with the score of SADQ. “Attention” was significantly associated with “visual motor coordination” (β = 1.78, p < 0.05), and both of them were significantly associated with “executive function” (β = 0.87, p < 0.001 vs. β = 1.28, p < 0.05, respectively). The goodness-of-fit indices of SEM for the hypothesized model are within acceptable range: IFI = 0.952 and CFI = 0.951. Except NFI = 0.870, SRMR = 0.091, RMSEA = 0.093, standard Chi-square = 1.510 (Chi-square = 102.658, df = 68, p < 0.01).
Figure 1: A model for demonstrating the path analysis demographic characteristics, cognitive factors, and SADQ. * p < 0.05; ** p < 0.01; *** p < 0.001. SADQ, severity of alcohol dependence questionnaire.

Click here to view



  Discussion Top


Gender difference in the rate of alcohol dependence has been reported in previous surveys in Taiwan [2],[3],[29]. The alcohol dependence in general population is in the range of 9%–19% for males and 2%–14% for females, defined by the score of CAGE ≥ 2 [54],[55],[56],[57]. The effects of alcohol are more pronounced in females than in males [58],[59],[60],[61]. The causes of differences have been reported as differences in body fat [62], alcohol dehydrogenase [63], or drinking habits. But we failed to show difference between genders and cognitive impairments in our study [Table 1].

The cognitive function including attention, visual motor coordination, and executive function is complexed. As shown in [Table 2], we used several cognitive tests to examine. We also used confirmatory factor analyses and Cronbach's alpha to examine the internal consistency in those tests. All tests for internal consistency[Table 2] were acceptable.

We found that older patients with alcohol disorder showed significantly lower level of attention (p < 0.01), visual motor coordination (p < 0.01), and executive function (p < 0.01) than those in youngers in our study [Table 3]. Aging is associated with widespread reduction on both gray and white matter, including anterior thalamic radiations, cerebellum, connective structures of Papez's circuit, and the fornix and the cingulum [64]. Older patients with alcohol use are vulnerable to greater cognitive changes and show less recovery of function once they cease drinking, even controlling drinking history [30]. Considering the vulnerability of the aging brain to alcohol-related damage, clinicians should be aware of the importance of assessment and treatment of alcohol use in the elderly.

In our study [Table 3], we found that attention impairment was significantly affected by old age (p < 0.01), long duration of alcohol use (p < 0.001), and severe alcohol use (p < 0.001). Previous studies revealed that attention is affected strongly by alcohol consumption [21],[22],[23],[24]. Previous neurophysiological studies demonstrated that attention can boost neural signals related to target processing, whereas it inhibits responses unrelated to the attended target [65],[66],[67]. Therefore, considering alcohol-related attention problem, clinicians need to consider current blood level, age, and duration of alcohol drinking.

Our study demonstrated that alcohol-related visual motor coordination impairments were significantly related to long duration (p < 0.001) and significantly more severe use (p < 0.001) [Table 3]. Visual functions affected by alcohol intake have been reported as depth perception [68],[69], contrast sensitivity [68],[70],[71], visual short-term memory [69], and visual temporal processing. In a study examining the effects of two doses of alcohol on functional magnetic resonance imaging activation during a visual perception task [25], the investigators found that alcohol has both global and local effects upon the neural correlates of the motor-free visual perception test–revised task, some of which are dose dependent. Alcohol causes a dose-dependent decrease in activation amplitude over the visual perception network [25]. Increased dose-dependent activation has been observed in insula, dorsolateral prefrontal cortex (DLPFC), and precentral regions, whereas decreased dose-dependent activation is observed in the anterior and posterior cingulate, precuneus, and middle frontal areas. Frontal eye fields, DLPFC, and supplementary motor area became more diffusely activated at the higher dose of alcohol.Another study examined the blood alcohol concentrations (BACs) and motor performance, and the result showed that impairment was positively correlated with BAC while the information-processing performance was sparing [26]. Therefore, visual motor coordination is an important issue in alcohol-related harms.

In our study [Table 3], we found that executive function was affected by old age (p < 0.01), long duration of alcohol use (p < 0.001), and severe alcohol use (p < 0.001). The frontocerebellar circuit, includes the frontal cortex and the cerebellum, is particularly susceptible to alcohol-related damage [19]. Shrinkage of the pons and thalamus associated with loss of volume of the cerebellum and cortex further supports the theory that alcohol causes disruption of the frontocerebellar circuit [72],[73]. The frontocerebellar circuit is responsible for executive functions, such as reasoning, judgment, flexibility, inhibition, and planning [74]. Executive functions have been found to be impaired in alcohol-dependent people, particularly in inhibition, flexibility, deduction of rules, organization, and planning [27],[28]. Executive function, a higher level of cognitive function, is impaired by short-term and long-term use of alcohol.

The path analysis suggests that different types of cognitive impairment, as attention, visual motor coordination, and executive function, were correlated with each other significantly in AUD (Figure 1). Visual perception requires the connection of attention and the programming for motor activity. A conceptual model of attention and visual motor coordination has been proposed in a previous study [75]. Attention, like a unique “saliency map” that encodes for stimulus, is tightly interplayed with eye movements. The efficacy of programming speed is related to visual information [76] and the integrity of cortical structures [77],[78],[79],[80]. Visual-spatial skills and executive performance have been suggested to have a similar basis in information processing [81]. Drunk driving, a serious problem around the world, is related to acute alcohol impact. Our study revealed alcohol-related chronic cognitive impairment. Driving is a complex task that implicates attention, visual motor, and executive abilities. Moreover, driving involves executive functions that supervise all movements and decisions taken by the driver by initiation, planning, hypothesis generation, and decision-making [82]. Therefore, drunk driving can interfere with current serum alcohol level and chronic alcohol use.

Study limitations

The readers are warned against over-interpret the study results because our study has six study limitations:

  • The participants in this study were patient on a psychiatric hospital. A single-center study may limit the generalizability and applicability to other populations.
  • We recruiting patients with AUD or alcohol intoxication in our study, and the heterogeneity may cause type I error of the study.
  • The significant correlation between age and psychological tests may be cofounded by the natural aging course.
  • Medical comorbidity and education level were not assessed, which may also confound the cognitive function.
  • We did not evaluate thiamine level and memory problems which are related to Wernicke–Korsakoff syndrome [83], a well-known syndrome related to chronic alcohol use.
  • The cross-sectional research design is limited our ability to draw conclusions regarding the causal relationship among predictors and cognitive function.


Summary

In this cross-sectional study, we investigated the predictors of cognitive impairments among alcohol users include old age, long duration of alcohol use, as well as severe alcohol-related problems. Attention, visual motor coordination, and executive function impairments were positively associated with each other in alcohol users. The early screening of predictive factors, cognitive impairment, and timely interventions will be beneficial for patients with alcohol use disorders.


  Acknowledgments Top


Chwen-Yng Su helped do data analysis. Frank Huang-Chih Chou and Kuan-Ying Hsieh contributed equally. Wei-Tsung Kao, a member of executive editorial board of the Taiwanese Journal of Psychiatry, had no rôle in the peer review process or decision to publish this editorial.


  Financial Support and Sponsorship Top


This study received no external funding


  Conflicts of Interest Top


Wei-Tsung Kao is a member on the executive editorial board at the Taiwanese Journal of Psychiatry. He had no rôle in the peer review process of or decision to publish this review. The other authors declare no potential conflicts of interest in publishing this report.



 
  References Top

1.
World Health Organization: Global Status Report on Alcohol and Health. Geneva, Switzerland: World Health Organization, 2018.  Back to cited text no. 1
    
2.
Kuo C: Prevalence of alcoholism in a primary care setting. Taiwan J Psychiatry 2005; 19: 137-47.  Back to cited text no. 2
    
3.
Helzer JE, Canino GJ, Yeh EK, et al.: Alcoholism – North America and Asia: a comparison of population surveys with the Diagnostic Interview Schedule. Arch Gen Psychiatry 1990; 47: 313-9.  Back to cited text no. 3
    
4.
Harper C: The neuropathology of alcohol-specific brain damage, or does alcohol damage the brain? J Neuropath Exp Neur 1998; 57: 101-10.  Back to cited text no. 4
    
5.
Goldstein G, Shelly C: Neuropsychological investigation of brain lesion localization in alcoholism. In: Begleiter H, (ed).: Biological Effects of Alcohol. Boston: Springer, 1980: 731-43.  Back to cited text no. 5
    
6.
Abroms BD, Fillmore MT: Alcohol-induced impairment of inhibitory mechanisms involved in visual search. Exp Clin Psychopharmacol 2004; 12: 243.  Back to cited text no. 6
    
7.
Abroms BD, Gottlob LR, Fillmore MT: Alcohol effects on inhibitory control of attention: distinguishing between intentional and automatic mechanisms. Psychopharmacology (Berlin) 2006; 188: 324-34.  Back to cited text no. 7
    
8.
Field M, Wiers RW, Christiansen P, et al.: Acute alcohol effects on inhibitory control and implicit cognition: implications for loss of control over drinking. Alcohol Clin Exp Res 2010; 34: 1346-52.  Back to cited text no. 8
    
9.
Ivanec D, Švagelj A, Rebić V: The impact of different levels of blood alcohol concentration on psychomotor tasks. Suvrem Psihol 2009; 12: 81-97.  Back to cited text no. 9
    
10.
Koelega H: Alcohol and vigilance performance: a review. Psychopharmacology (Berlin) 1995; 118: 233-49.  Back to cited text no. 10
    
11.
Patel M, Modig F, Magnusson M, et al.: Alcohol intoxication at 0.06 and 0.10% blood alcohol concentration changes segmental body movement coordination. Exp Brain Res 2010; 202: 431-43.  Back to cited text no. 11
    
12.
Saults JS, Cowan N, Sher KJ, et al.: Differential effects of alcohol on working memory: distinguishing multiple processes. Exp Clin Psychopharmacol 2007; 15: 576.  Back to cited text no. 12
    
13.
Pfefferbaum A, Sullivan EV, Mathalon DH, et al.: Frontal lobe volume loss observed with magnetic resonance imaging in older chronic alcoholics. Alcohol Clin Exp Res 1997; 21: 521-9.  Back to cited text no. 13
    
14.
Dirksen CL, Howard JA, Cronin-Golomb A, et al.: Patterns of prefrontal dysfunction in alcoholics with and without Korsakoff's syndrome, patients with Parkinson's disease, and patients with rupture and repair of the anterior communicating artery. Neuropsychiatr Dis Treat 2006; 2: 327.  Back to cited text no. 14
    
15.
Harper C, Matsumoto I: Ethanol and brain damage. Curr Opin Pharmacol 2005; 5: 73-8.  Back to cited text no. 15
    
16.
Sullivan EV, Deshmukh A, Desmond JE, et al.: Cerebellar volume decline in normal aging, alcoholism, and Korsakoff's Syndrome: relation to ataxia. Cogn Neuropsychol 2000; 14: 341.  Back to cited text no. 16
    
17.
Cullen K, Halliday GM, Caine D, et al.: The nucleus basalis (Ch4) in the alcoholic Wernicke-Korsakoff syndrome: reduced cell number in both amnesic and non-amnesic patients. J Neurol Neurosurg Psychiatry 1997; 63: 315-20.  Back to cited text no. 17
    
18.
Pfefferbaum A, Lim KO, Desmond JE, et al.: Thinning of the corpus callosum in older alcoholic men: a magnetic resonance imaging study. Alcohol Clin Exp Res 1996; 20: 752-7.  Back to cited text no. 18
    
19.
Hayes V, Demirkol A, Ridley N, et al.: Alcohol-related cognitive impairment: current trends and future perspectives. Neurodegener Dis Manag 2016; 6: 509-23.  Back to cited text no. 19
    
20.
American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Washington, DC, USA: American Psychiatric Association, 2013.  Back to cited text no. 20
    
21.
do Canto-Pereira LH, David IP, Machado-Pinheiro W, et al.: Effects of acute alcohol intoxication on visuospatial attention. Hum Exp Toxicol 2007; 26: 311-9.  Back to cited text no. 21
    
22.
Roehrs T, Beare D, Zorick F, et al.: Sleepiness and ethanol effects on simulated driving. Alcohol Clin Exp Res 1994; 18: 154-8.  Back to cited text no. 22
    
23.
Rohrbaugh J, Stapleton JM, Parasuraman R, et al.: Alcohol intoxication in humans: effects on vigilance performance. Alcohol Alcohol Suppl 1987; 1: 97-102.  Back to cited text no. 23
    
24.
Schulte T, Müller-Oehring EM, Strasburger H, et al.: Acute effects of alcohol on divided and covert attention in men. Psychopharmacology 2001; 154: 61-9.  Back to cited text no. 24
    
25.
Calhoun VD, Altschul D, McGinty V, et al.: Alcohol intoxication effects on visual perception: an fMRI study. Hum Brain Mapp 2004; 21: 15-26.  Back to cited text no. 25
    
26.
Fogarty JN, Vogel-Sprott M: Cognitive processes and motor skills differ in sensitivity to alcohol impairment. J Stud Alcohol 2002; 63: 404-11.  Back to cited text no. 26
    
27.
Pitel AL, Beaunieux H, Witkowski T, et al.: Genuine episodic memory deficits and executive dysfunctions in alcoholic subjects early in abstinence. Alcohol Clin Exp Res 2007; 31: 1169-78.  Back to cited text no. 27
    
28.
Oscar-Berman M, Marinković K: Alcohol: effects on neurobehavioral functions and the brain. Neuropsychol Rev 2007; 17: 239-57.  Back to cited text no. 28
    
29.
Cheng AT, ChenWJ: Alcoholism among four aboriginal groups in Taiwan: high prevalences and their implications. Alcohol Clin Exp Res 1995; 19: 81-91.  Back to cited text no. 29
    
30.
Bates ME, Bowden SC, Barry D: Neurocognitive impairment associated with alcohol use disorders: implications for treatment. Exp Clin Psychopharmacol 2002; 10: 193.  Back to cited text no. 30
    
31.
Cheng WJ, Huang MC, Huang PS, et al.: The Chinese version of the severity of alcohol dependence questionnaire: reliability and factor structure. Taiwan J Psychiatry 2009; 23: 159-66.  Back to cited text no. 31
    
32.
Meehan JP, Webb MG, Unwin AR: The severity of alcohol dependence questionnaire (SADQ) in a sample of Irish problem drinkers. Br J Addict 1985; 80: 57-63.  Back to cited text no. 32
    
33.
Stroop JR: Studies of interference in serial verbal reactions. J Exp Psychol 1935; 18: 643-62.  Back to cited text no. 33
    
34.
Jensen AR, Rohwer WD Jr: The stroop color-word test: a review. Acta Psychol 1966; 25: 36-93.  Back to cited text no. 34
    
35.
Kane MJ, Engle RW: Working-memory capacity and the control of attention: the contributions of goal neglect, response competition, and task set to stroop interference. J Exp Psychol Gen 2003; 132: 47-70.  Back to cited text no. 35
    
36.
Rosvold HE, Mirsky AF, Sarason I, et al.: A continuous performance test of brain damage. J Consult Psychol 1956; 20: 343.  Back to cited text no. 36
    
37.
Cornblatt BA, Risch NJ, Faris G, et al.: The continuous performance test, identical pairs version (CPT-IP): I. new findings about sustained attention in normal families. Psychiatry Res 1988; 26: 223-38.  Back to cited text no. 37
    
38.
Nuechterlein KH: Signal detection in vigilance tasks and behavioral attributes among offspring of schizophrenic mothers and among hyperactive children. J Abnorm Psychol 1983; 92: 4.  Back to cited text no. 38
    
39.
Nuechterlein KH, Dawson ME: Information processing and attentional functioning in the developmental course of schizophrenic disorders. Schizophr Bull 1984; 10: 160-203.  Back to cited text no. 39
    
40.
Cornblatt BA, Erlenmeyer-Kimling L: Global attentional deviance as a marker of risk for schizophrenia: specificity and predictive validity. J Abnorm Psychol 1985; 94: 470.  Back to cited text no. 40
    
41.
Reed JC, Reed HB: The Halstead-Reitan neuropsychological battery. In: Goldstein G, Incagnoli TM, (eds).: Contemporary Approaches to Neuropsychological Assessment. Critical Issues in Neuropsychology. Boston, USA: Springer, 1997.  Back to cited text no. 41
    
42.
Robertson IH, Ward T, Ridgeway V, et al.: The structure of normal human attention: the test of everyday attention. J Int Neuropsychol Soc 1996;2:525-34.  Back to cited text no. 42
    
43.
Benton AL, Varney NR, Hamsher KD: Visuospatial judgment: a clinical test. Arch Neurol 1978; 35: 364-7.  Back to cited text no. 43
    
44.
Riccio CA, Hynd GW: Validity of Benton's judgement of line orientation test. J Psychoeduc Assess 1992; 10: 210-8.  Back to cited text no. 44
    
45.
Warrington EK, James M: The Visual Object and Space Perception Battery. London, UK: Pearson, 1991.  Back to cited text no. 45
    
46.
Katz N, Hartman-Maeir A, Ring H, et al.: Relationships of cognitive performance and daily function of clients following right hemisphere stroke: predictive and ecological validity of the LOTCA battery. Occup Ther J Res 2000; 20: 3-17.  Back to cited text no. 46
    
47.
Ryan JJ, Lopez SJ: Wechsler adult intelligence scale-III. In: Dorfman WI, Hersen M, (eds).: Understanding Psychological Assessment. Perspectives on Individual Differences. Boston, Massadusets, USA: Springer, 2001.  Back to cited text no. 47
    
48.
Smith A: Symbol Digit Modalities Test (SDMT): Manual (Revised). Los Angeles: Western Psychological Services, 1982.  Back to cited text no. 48
    
49.
Nusair K, Hua N: Comparative assessment of structural equation modeling and multiple regression research methodologies: e-commerce context. Tour Manag 2010; 31: 314-24.  Back to cited text no. 49
    
50.
Tabachnick BG, Fidell LS: Using Multivariate Statistics. 5th ed. New York, USA: Allyn and Bacon, 2007.  Back to cited text no. 50
    
51.
MacCallum RC, Browne MW, Sugawara HM: Power analysis and determination of sample size for covariance structure modeling. Psychol Methods 1996; 1: 130-49.  Back to cited text no. 51
    
52.
Bentler PM, Bonett DG: Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull 1980; 88: 588-606.  Back to cited text no. 52
    
53.
Wheaton B, Muthén B, Alwin DF, et al.: Assessing reliability and stability in panel models. Sociol Methodol 1977; 8: 84-136.  Back to cited text no. 53
    
54.
Head J, Stansfeld SA, Siegrist J: The psychosocial work environment and alcohol dependence: a prospective study. Occup Environ Med 2004; 61: 219-24.  Back to cited text no. 54
    
55.
Larsen A, Bøggild H, Mortensen JT, et al.: Mental health in the workforce: an occupational psychiatric study. Int J Soc Psychiatry 2010; 56: 578-92.  Back to cited text no. 55
    
56.
Etter JF, Gmel G: Paradoxical changes in alcohol consumption and CAGE ratings between 1996 and 2006 in the general population of Geneva. Alcohol Alcohol 2011; 46: 128-32.  Back to cited text no. 56
    
57.
Batty GD, Bhaskar A, Emslie C, et al.: Association of life course socioeconomic disadvantage with future problem drinking and heavy drinking: gender differentials in the west of Scotland. Int J Public Health 2012; 57: 119-26.  Back to cited text no. 57
    
58.
Avant LL: Alcohol impairs visual presence/absence detection more for females than for males. Percept Psychophys 1990; 48: 285-90.  Back to cited text no. 58
    
59.
Dougherty DM, Bjork JM, Bennett RH: Effects of alcohol on rotary pursuit performance: a gender comparison. Psychol Rec 1998; 48: 393-405.  Back to cited text no. 59
    
60.
Hoppenbrouwers SS, Hofman D, Schutter DJ: Alcohol breaks down interhemispheric inhibition in females but not in males. Psychopharmacology (Berlin) 2010; 208: 469-74.  Back to cited text no. 60
    
61.
Miller MA, Weafer J, Fillmore MT: Gender differences in alcohol impairment of simulated driving performance and driving-related skills. Alcohol Alcohol 2009; 44: 586-93.  Back to cited text no. 61
    
62.
Addolorato G, Capristo E, Caputo F, et al.: Nutritional status and body fluid distribution in chronic alcoholics compared with controls. Alcohol Clin Exp Res 1999; 23: 1232-7.  Back to cited text no. 62
    
63.
Baraona E, Abittan CS, Dohmen K, et al.: Gender differences in pharmacokinetics of alcohol. Alcohol Clin Exp Res 2001; 25: 502-7.  Back to cited text no. 63
    
64.
Giorgio A, Santelli L, Tomassini V, et al.: Age-related changes in grey and white matter structure throughout adulthood. Neuroimage 2010; 51: 943-51.  Back to cited text no. 64
    
65.
Martinez-Trujillo JC, Treue S: Feature-based attention increases the selectivity of population responses in primate visual cortex. Curr Biol 2004; 14: 744-51.  Back to cited text no. 65
    
66.
Maunsell JH, Treue S: Feature-based attention in visual cortex. Trends Neurosci 2006; 29: 317-22.  Back to cited text no. 66
    
67.
Treue S, Trujillo JC: Feature-based attention influences motion processing gain in macaque visual cortex. Nature 1999; 399: 575-9.  Back to cited text no. 67
    
68.
Watten RG, Lie I: Visual functions and acute ingestion of alcohol. Ophthalmic Physiol Opt 1996; 16: 460-6.  Back to cited text no. 68
    
69.
Wegner AJ, Fahle M: Alcohol and visual performance. Prog Neuropsychopharmacol Biol Psychiatry 1999; 23: 465-82.  Back to cited text no. 69
    
70.
Nicholson ME, Andre JT, Tyrrell RA, et al.: Effects of moderate dose alcohol on visual contrast sensitivity for stationary and moving targets. J Stud Alcohol 1995; 56: 261-6.  Back to cited text no. 70
    
71.
Pearson P, Timney B: Effects of moderate blood alcohol concentrations on spatial and temporal contrast sensitivity. J Stud Alcohol 1998; 59: 163-73.  Back to cited text no. 71
    
72.
Pfefferbaum A, Sullivan EV: Disruption of brain white matter microstructure by excessive intracellular and extracellular fluid in alcoholism: evidence from diffusion tensor imaging. Neuropsychopharmacology 2005; 30: 423-32.  Back to cited text no. 72
    
73.
Sullivan EV: Compromised pontocerebellar and cerebellothalamocortical systems: speculations on their contributions to cognitive and motor impairment in nonamnesic alcoholism. Alcohol Clin Exp Res 2003; 27: 1409-19.  Back to cited text no. 73
    
74.
Shallice T, Burgess P: The domain of supervisory processes and the temporal organization of behaviour. In: Roberts AC, Robbins TW, Weiskrantz L, (eds).: The Prefrontal Cortex: Executive and Cognitive Functions. London: Oxford University Press, 1998: 22-35.  Back to cited text no. 74
    
75.
Itti L, Koch C: Computational modelling of visual attention. Nat Rev Neurosci 2001; 2: 194-203.  Back to cited text no. 75
    
76.
Milner AD, Goodale MA: Two visual systems re-viewed. Neuropsychologia 2008; 46: 774-85.  Back to cited text no. 76
    
77.
Huberle E, Driver J, Karnath HO: Retinal versus physical stimulus size as determinants of visual perception in simultanagnosia. Neuropsychologia 2010; 48: 1677-82.  Back to cited text no. 77
    
78.
Qiu J, Li H, Liu Q, et al.: Brain mechanisms underlying visual perception and visual mental imagery of Chinese pseudo-characters: an event-related potential study. Brain Res 2007; 1184: 202-9.  Back to cited text no. 78
    
79.
Khayat PS, Pooresmaeili A, Roelfsema PR: Time course of attentional modulation in the frontal eye field during curve tracing. J Neurophysiol 2009; 101: 1813-22.  Back to cited text no. 79
    
80.
Wardak C, Denève S, Hamed SB: Focused visual attention distorts distance perception away from the attentional locus. Neuropsychologia 2011; 49: 535-45.  Back to cited text no. 80
    
81.
Blasi FD, Elia F, Buono S, et al.: Relationships between visual-motor and cognitive abilities in intellectual disabilities. Percept Mot Skills 2007; 104: 763-72.  Back to cited text no. 81
    
82.
Daigneault G, Joly P, Frigon JY: Executive functions in the evaluation of accident risk of older drivers. J Clin Exp Neuropsychol 2002; 24: 221-38.  Back to cited text no. 82
    
83.
Victor M, Adams RD, Collins GH: The Wernicke-Korsakoff syndrome. A clinical and pathological study of 245 patients, 82 with post-mortem examinations. Contemp Neurol Ser 1971; 7: 1-206.  Back to cited text no. 83
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

Top
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
   Abstract
  Introduction
  Methods
  Results
  Discussion
  Acknowledgments
   Financial Suppor...
   Conflicts of Int...
   References
   Article Figures
   Article Tables

 Article Access Statistics
    Viewed543    
    Printed12    
    Emailed0    
    PDF Downloaded62    
    Comments [Add]    

Recommend this journal