Determination of Behavioural Addictions and Addiction Pattern Risk Models within the Framework of Sociodemographic Characteristics

Abstract

The concept of behavioral addiction has emerged as some behaviors are exhibited excessively and show similar characteristics to substance-related disorders. Studies indicate that behavioral addictions accompany each other and that various sociodemographic characteristics play a role in their emergence. In this study, gambling, internet gaming, shopping, and exercise behaviors, the pattern of co-occurrence of the symptoms indicating addiction, and which sociodemographic characteristics are affected by these behaviors were examined. A total of 1114 adults living in Turkey participated in the study. Two-step cluster analysis was used to identify addiction-prone classes for each addiction type and these were named as specific addiction clusters. In addition, three different general addiction groups were formed as a result of the two-step cluster analysis conducted with all items of the measurement tools assessing addictions. These were named as those who were prone to non-exercise addictions (gambling, gaming, and shopping), those who were prone to exercise addiction, and those who were not prone to addiction. As in many studies, the variation of addiction types according to gender and the differentiation of levels in terms of age groups were also observed in this study. Sociodemographic characteristics were analyzed in both specific and general addiction clusters. Logistic regression analyses were conducted to understand how various sociodemographic characteristics that differed according to the clusters explained the addiction groups together. Logistic regression analyses indicated that factors such as gender, age, education, employment status, marital status, smoking, and alcohol use may pose a risk for being in different addiction clusters.