Hot or Not: Response Inhibition Reduces the Hedonic Value and Motivational Incentive of Sexual Stimuli

We argue that to best comprehend many data sets, plotting judiciously selected sample statistics with associated confidence intervals can usefully supplement, or even replace, standard hypothesis-testing procedures. We note that most social science statistics textbooks limit discussion of confidence intervals to their use in between-subject designs. Our central purpose in this article is to describe how to compute an analogous confidence interval that can be used in within-subject designs. This confidence interval rests on the reasoning that because between-subject variance typically plays no role in statistical analyses of within-subject designs, it can legitimately be ignored; hence, an appropriate confidence interval can be based on the standard within-subject error term-that is, on the variability due to the subject × condition interaction. Computation of such a confidence interval is simple and is embodied in Equation 2 on p. 482 of this article. This confidence interval has two useful properties. First, it is based on the same error term as is the corresponding analysis of variance, and hence leads to comparable conclusions. Second, it is related by a known factor (√2) to a confidence interval of the difference between sample means; accordingly, it can be used to infer the faith one can put in some pattern of sample means as a reflection of the underlying pattern of population means. These two properties correspond to analogous properties of the more widely used between-subject confidence interval.

A wealth of research from the past two decades shows that addictive behaviors are characterized by attentional biases for substance-related stimuli. We review the relevant evidence and present an integration of existing theoretical models to explain the development, causes, and consequences of addiction-related attentional biases. We suggest that through classical conditioning, substance-related stimuli elicit the expectancy of substance availability, and this expectancy causes both attentional bias for substance-related stimuli and subjective craving. Furthermore, attentional bias and craving have a mutual excitatory relationship such that increases in one lead to increases in the other, a process that is likely to result in substance self-administration. Cognitive avoidance strategies, impulsivity, and impaired inhibitory control appear to influence the strength of attentional biases and subjective craving. However, some measures of attentional bias, particularly the addiction Stroop, might reflect multiple underlying processes, so results need to be interpreted cautiously. We make several predictions that require testing in future research, and we discuss implications for the treatment of addictive behaviors.

Seventy male alcohol-dependent patients participated in a 12-week, double-blind, placebo-controlled trial of naltrexone hydrochloride (50 mg/d) as an adjunct to treatment following alcohol detoxification. Subjects taking naltrexone reported significantly less alcohol craving and days in which any alcohol was consumed. During the 12-week study, only 23% of the naltrexone-treated subjects met the criteria for a relapse, whereas 54.3% of the placebo-treated subjects relapsed. The primary effect of naltrexone was seen in patients who drank any alcohol while attending outpatient treatment. Nineteen (95%) of the 20 placebo-treated patients relapsed after they sampled alcohol, while only eight (50%) of 16 naltrexone-treated patients exposed to alcohol met relapse criteria. Naltrexone was not associated with mood changes or other psychiatric symptoms. Significant side effects (nausea) occurred in two naltrexone-treated subjects, and one naltrexone-treated subject complained of increased pain from arthritis. These results suggest that naltrexone may be a safe and effective adjunct to treatment in alcohol-dependent subjects, particularly in preventing alcohol relapse.