Cognitive dysfunction in compulsive checkers: Further explorations

Recent evidence suggests a relationship between certain memory deficits and compulsive-checking behavior. The present study explores this relationship in the context of several additional memory capacities not yet investigated. Using the Maudsley Obsessional-Compulsive Inventory and the Everyday Checking Behavior Scale four groups of Ss were identified: (1) frequent checkers, (2) occasional checkers, (3) infrequent checkers and (4) noncheckers. Consistent with previous research, a memory-for-actions task indicated a deficit among compulsive checkers. Furthermore, checking status was found to be negatively related to memory functioning as measured by the Wechsler Memory Scale (WMS) and the Cognitive Failures Questionnaire (CFQ). This memory deficit was most pronounced on the Logical Memory subtest of the WMS. Checkers appear to have difficulty recalling details of meaningfully linked sequences, either presented in narrative form or engaged in personally. Although the reasons for these checking-related deficits are not clear, a complete understanding of checking phenomena will involve an appreciation of the role played by memory deficits.     

Cognitive deficits in compulsive checkers: An exploratory study

Compulsive-checking behavior can be conceptualized as resulting, in part, from a memory failure. In order to determine if memory difficulties are associated with compulsive checking, the performance of college-student checkers were compared with the performance of non-checkers on a number of cognitive tasks hypothesized to be relevant to understanding checking behavior. Using the Checking and Cleaning subscales of the Maudsley Obsessional-Compulsive Inventory, four groups of subjects were identified: (1) Cleaning Checkers (N = 13); (2) Noncleaning Checkers (N = 13); (3) Cleaning Noncheckers (N = 13); and (4) Noncleaning Noncheckers (N = 15). It was hypothesized that the cognitive deficits studied would characterize individuals with cheeking compulsions, but not persons with non-checking compulsions (i.e. Cleaning Noncheckers) or normal controls (i.e. Noncleaning Noncheckers). Compulsive checkers were found to have a poorer memory for prior actions than non-checkers and were also found to underestimate their ability at distinguishing memories of real and imagined events, a process referred to as reality monitoring. Both of these deficits were specific to compulsive checkers and can be viewed as contributing to the likelihood that an individual will engage in checking behavior. If an individual has difficulty in recalling whether an intended action has been executed, they may be inclined to engage in checking behavior to insure the intended action is carried out. Similarly, a tendency to underestimate reality-monitoring ability could result in increased checking behavior as the individual attempts to reduce his/her uncertainty over whether a previous behavior actually occurred or merely was thought to occur. It is concluded that the study of cognitive deficits in compulsive checking is a potentially fruitful avenue for further inquiry.     

Conjoint developmental trajectories of young adult alcohol and tobacco use

Developmental and etiological advances have set the stage for considering trajectories of problem behavior across the life course, but little work thus far addresses co-occurring problem behavior trajectories. Although recent work characterizes drinking and smoking trajectories, none has explored the course of concurrent drinking and smoking. Using panel data from the Monitoring the Future Project (N=32,087), the authors applied growth mixture modeling to 4 waves of heavy drinking and smoking in a young-adult sample. The authors extracted a single latent group membership factor from heavy drinking and smoking. Associations between trajectory classes and risk factors were relatively unique to the substance being predicted. The association of smoking with alcohol expectancies and delinquency appeared to exist by virtue of smoking's comorbidity with drinking.     

Borderline personality features predict alcohol use problems

This study assessed the relation between BPD features and problems associated with alcohol use 2 years later in young adults. Approximately 5,000 nonclinical young adults were screened for BPD features, and two cohorts of participants completed the laboratory phase of the study at Time 1 (total N = 421) and then again 2 years later at Time 2 (total N = 356). Measures included self-report and interview-based assessments of personality disorders, psychopathology in biological parents, Axis I psychopathology, and alcohol use problems. BPD features were found to significantly predict alcohol use problems 2 years later after controlling for parents' substance use disorders, Axis I psycho-pathology (including alcohol abuse/dependence), and non-BPD personality disorders. In addition, the BPD subscale that assesses impulsivity was found to be significantly associated with alcohol use problems once all predictors were entered into the model.     

Do college students drink more than their non-college-attending peers? Evidence from a population-based longitudinal female twin study

The association of college attendance with alcohol use and alcohol use disorders was examined in a population-based young adult female twin sample identified from a systematic search of birth records. College-attending women consumed a larger overall volume of alcohol than did their non-college-attending peers, but they were not more likely to be diagnosed with an alcohol use disorder. Significant associations between college attendance and alcohol involvement were probed using 3 different complementary research designs: multivariate cross-sectional analyses, longitudinal analyses of the precollege and college years, and cotwin-control analyses of twin pairs discordant for attending college. Although demographic and lifestyle characteristics accounted for most or all of the association between college attendance and alcohol involvement, there was 1 aspect of drinking behavior, occasionally consuming large quantities of alcohol, that remained significantly associated with college attendance even after controlling for these characteristics or for genetic and family background factors. These results are consistent with the conclusion that some aspect of the college experience may be an important environmental risk factor for this pattern of drinking among young adults.     

Deconstructing the age-prevalence curve of alcohol dependence: why "maturing out" is only a small piece of the puzzle

Epidemiological studies have consistently demonstrated that heavy alcohol use and alcohol dependence (AD) tend to increase in adolescence and emerging adulthood and then show a large decline in the late 20s, a phenomenon called maturing out. This decline has been explained as an effect of "role incompatibility" in which involvement in new roles and activities interferes with a heavy drinking lifestyle. However, maturing out has been conceived mostly as a decrease in offset, with little attention paid to reductions in new onset or recurrence across decades of life. Moreover, although role incompatibility processes have been studied with young samples, little is known about the effect of life transitions (e.g., marriage, parenthood, changes in employment status) on AD later in life and whether similar effects are observed. Using longitudinal data from the National Epidemiologic Survey on Alcohol and Related Conditions, a nationally representative epidemiologic survey, we examined the patterns of stability and change in AD across the life span and the differential effect of life transitions on AD across different age strata. Results showed that persistence of AD tended to increase with age, although not dramatically, and that onset and recurrence tended to decrease with age. Moreover, the effects of life transitions on the course of AD varied across the life span and were different for men and women. These results indicate that life transitions differentially affect the patterns of stability and change in younger versus older people, have a different impact for men and women, and highlight the need to consider the unique aspects of each stage of adult development on the course of AD.