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  • Author or Editor: T. Cameron Wild x
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Background and aims

The aims of this study were (a) to describe the prevalence of single versus multiple addiction problems in a large representative sample and (b) to identify distinct subgroups of people experiencing substance-related and behavioral addiction problems.

Methods

A random sample of 6,000 respondents from Alberta, Canada, completed survey items assessing self-attributed problems experienced in the past year with four substances (alcohol, tobacco, marijuana, and cocaine) and six behaviors (gambling, eating, shopping, sex, video gaming, and work). Hierarchical cluster analyses were used to classify patterns of co-occurring addiction problems on an analytic subsample of 2,728 respondents (1,696 women and 1032 men; M age = 45.1 years, SD age = 13.5 years) who reported problems with one or more of the addictive behaviors in the previous year.

Results

In the total sample, 49.2% of the respondents reported zero, 29.8% reported one, 13.1% reported two, and 7.9% reported three or more addiction problems in the previous year. Cluster-analytic results suggested a 7-group solution. Members of most clusters were characterized by multiple addiction problems; the average number of past year addictive behaviors in cluster members ranged between 1 (Cluster II: excessive eating only) and 2.5 (Cluster VII: excessive video game playing with the frequent co-occurrence of smoking, excessive eating and work).

Discussion and conclusions

Our findings replicate previous results indicating that about half of the adult population struggles with at least one excessive behavior in a given year; however, our analyses revealed a higher number of co-occurring addiction clusters than typically found in previous studies.

Open access

Abstract

Background and aims

The Brief Screener for Substance and Behavioral Addictions (SSBAs) was developed to assess a common addiction construct across four substances (alcohol, tobacco, cannabis, and cocaine), and six behaviors (gambling, shopping, videogaming, eating, sexual activity, and working) using a lay epidemiology perspective. This paper extends our previous work by examining the predictive utility of the SSBA to identify self-attributed addiction problems.

Method

Participants (N = 6,000) were recruited in Canada using quota sampling methods. Receiver Operating Characteristics (ROCs) analyses were conducted, and thresholds established for each target behavior's subscale to predict self-attributed problems with these substances and behaviors. For each substance and behavior, regression models compared overall classification accuracy and model fit when lay epidemiologic indicators assessed using the SSBA were compared with validated screening measures to predict selfattributed problems.

Results

ROC analyses indicted moderate to high diagnostic accuracy (Area under the curves (AUCs) 0.73–0.94) across SSBA subscales. Thresholds for identifying self-attributed problems were 3 for six of the subscales (alcohol, tobacco, cannabis, cocaine, shopping, and gaming), and 2 for the remaining four behaviors (gambling, eating, sexual activity, and working). Compared to other instruments assessing addiction problems, models using the SSBA provided equivalent or better model fit, and overall had higher classification accuracy in the prediction of self-attributed problems.

Discussion and conclusions

The SSBA is a viable screening tool for problematic engagement across ten potentially addictive behaviors. Where longer screening tools are not appropriate, the SSBA may be used to identify individuals who would benefit from further assessment.

Open access