| Literature DB >> 26029121 |
Jessica Weafer1, Jessica De Arcangelis1, Harriet de Wit1.
Abstract
INTRODUCTION: Mounting evidence from both animal and human studies suggests that females are more vulnerable to drug and alcohol abuse than males. Some of this increased risk may be related to behavioral traits, such as impulsivity. Here, we examined sex differences in two forms of behavioral impulsivity (inhibitory control and impulsive choice) in young men and women, in relation to their level of alcohol consumption and alcohol-related problems (at-risk or non-risk).Entities:
Keywords: AUDIT; alcohol; behavioral impulsivity; delay discounting; go/no-go; impulsive choice; inhibitory control
Year: 2015 PMID: 26029121 PMCID: PMC4429551 DOI: 10.3389/fpsyt.2015.00072
Source DB: PubMed Journal: Front Psychiatry ISSN: 1664-0640 Impact factor: 4.157
Figure 1Schematic of a go (top) and no-go (bottom) trial on the go/no-go task.
Figure 2Schematic of a trial on the delay discounting task.
Demographics and drug use characteristics of participants.
| At-risk drinkers | Non-risk drinkers | |||||
|---|---|---|---|---|---|---|
| Men ( | Women ( | Total ( | Men ( | Women ( | Total ( | |
| Age (mean, SD) | 23.3 (3.5) | 22.0 (2.8) | 22.6 (3.2) | 23.3 (3.3) | 22.9 (3.1) | 23.0 (3.2) |
| Education in years (mean, SD) | 15.3 (2.3) | 14.9 (1.9) | 15.1 (2.1) | 15.4 (2.3) | 15.5 (2.0) | 15.5 (2.1) |
| Race (number, %) | ||||||
| Caucasian | 80 (89%) | 79 (95%) | 159 (92%) | 187 (91%) | 329 (90%) | 516 (91%) |
| African-American | 2 (2%) | 2 (1%) | 11 (5%) | 14 (4%) | 25 (4%) | |
| Asian | 7 (8%) | 7 (4%) | 5 (2%) | 15 (4%) | 20 (4%) | |
| Other | 1 (1%) | 4 (5%) | 5 (3%) | 3 (2%) | 6 (2%) | 9 (1%) |
| IQ (mean, SD) | 119.0 (10.5) | 120.3 (10.3) | 119.6 (10.4) | 119.5 (9.4) | 118.7 (9.2) | 119.0 (9.3) |
| Alcohol use measures | ||||||
| AUDIT (mean, SD) | 10.5 (2.5) | 10.2 (2.4) | 10.3 (2.4) | 4.5 (1.7) | 4.1 (1.9) | 4.2 (1.8) |
| TLFB | ||||||
| Drinking days/month | 13.0 (6.5) | 11.0 (5.8) | 12.2 (6.2) | 8.2 (6.0) | 7.4 (5.4) | 7.7 (5.6) |
| Binges/month | 4.5 (3.5) | 4.4 (3.6) | 4.5 (3.5) | 1.2 (1.7) | 1.3 (1.8) | 1.3 (1.7) |
| Cigarettes/day (mean/SD) | 1.1 (2.6) | 0.6 (1.3) | 0.9 (2.1) | 0.6 (1.8) | 0.5 (2.2) | 0.5 (2.1) |
| Marijuana (number, %) | ||||||
| None | 31 (34%) | 34 (41%) | 65 (37%) | 125 (61%) | 245 (67%) | 370 (65%) |
| Monthly | 37 (41%) | 37 (45%) | 74 (43%) | 52 (25%) | 94 (26%) | 146 (26%) |
| Weekly | 17 (19%) | 10 (12%) | 27 (16%) | 22 (11%) | 24 (6.5%) | 46 (8%) |
| Daily | 5 (6%) | 2 (2%) | 7 (4%) | 7 (3%) | 1 (0.5%) | 8 (1%) |
.
Figure 3Mean inhibitory failures on the go/no-go task for men and women in the non-risk (AUDIT scores below 8) and at-risk (AUDIT scores of 8 or above) drinker groups. In the non-risk group, men (n = 190) and women (n = 335) did not differ. In the at-risk group, women (n = 75) committed significantly more inhibitory failures than men (n = 79), p = 0.01. Capped vertical lines represent standard error of the mean (SEM).
Figure 4Mean area under the curve on the delay discounting task for men and women in the non-risk (AUDIT scores below 8) and at-risk (AUDIT scores of 8 or above) drinker groups. No sex differences were observed in either group. Capped vertical lines represent standard error of the mean (SEM).