Dynamics between Impulsiveness, Self-esteem and Alcohol Consumption: Sociodemographic Perspectives in Emerging Adults of the city of Cuenca-Ecuador 2024-2026

Research on impulsivity, self-esteem and alcohol consumption is crucial in urban environments like Cuenca, where various sociodemographic dynamics coexist. The objective of the study is to determine the interrelationships between these variables in emerging adults, highlighting the influence of sociodemographic factors. The study will adopt an observational, cross-sectional and descriptive-correlational design, using a quantitative approach to measure the variables of interest. Multivariate analyses, such as linear and logistic regression, will be implemented to explore how multiple factors, including sociodemographic factors, affect these interrelationships in a sample of emerging adults in Cuenca. The target population is made up of approximately 103,409 emerging adults (19 to 29 years old) according to data from the National Institute of Statistics and Censuses of Ecuador (INEC, 2022). A sample size of 597 people has been calculated, based on a confidence level of 95% and a margin of error of 4%. Several instruments will be used for data collection: a sociodemographic form (Ad Hoc) and psychological scales, including the Barratt Impulsivity Scale (BIS-11) (Patton et al., 1995), the Rosenberg Self-Esteem Scale (Rosenberg, 1965) and the Alcohol Use Disorders Identification Test (AUDIT; Saunders, 1993). It is anticipated that a significant percentage of emerging adults in Cuenca report varying levels of impulsivity, self-esteem, and alcohol consumption, with variations influenced by sociodemographic factors such as age, gender, educational level, and socioeconomic context. Based on previous research, it is expected that greater impulsivity will be related to greater alcohol consumption, and that self-esteem will act as a moderator in these relationships. The analysis of sociodemographic factors will allow the identification of risk and resilience patterns that will be essential for the design of specific interventions. This will help better understand how these variables interact in different groups, informing appropriate prevention and support strategies.

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