This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: A study by the Universitat Rovira i Virgili (URV) has analyzed which factors are most associated with pornography use during adolescence. The results show that the most predictive variable is gender, followed by problematic internet use, cannabis and alcohol consumption, family conflict and engaging in certain risky sexual behaviors.
The research, published in the journal Computation, was based on the 2023 ESTUDES survey and used a sample of 33,543 adolescents. The aim was to determine which personal, family, digital and behavioral variables are most useful for predicting whether an adolescent reports having viewed or used pornography in the previous 30 days. "Our aim was not to single out individual adolescents, but to better understand which factors tend to be associated with this behavior," explains Jorge de Andrés-Sánchez, a researcher at the URV's Social and Business Research Laboratory and co-author of the article.
The study combines the conventional statistical technique of logistic regression, three machine learning models (XGBoost, LightGBM and CatBoost) and explainable artificial intelligence techniques. These tools are able to detect complex relationships between variables and reveal the weight that each variable carries in the predictions. The different models produced similar results.
The machine learning systems slightly improved some indicators, but the differences compared with logistic regression were small. The authors therefore note that more complex models should not automatically replace traditional statistical techniques. "Artificial intelligence helps us see that this behavior does not appear in isolation, but within a broader profile of digital, family and behavioral factors," the authors affirmed.
The sex of the individual is, by far, the variable that carries the most weight in the predictions, with boys being more likely to use pornography. Age is also associated with it, but has a lower predictive importance. After gender, the next most significant factor is problematic internet use, which includes behaviors such as having difficulty staying offline, sleeping less to be online, neglecting obligations or using the internet to escape from worries or negative emotions.
The researchers point out that problematic internet use does not equate to a clinical diagnosis of internet addiction. The next most predictive variables are cannabis and alcohol use and family conflict. Some risky sexual behaviors, such as having sex without a condom or having a sexual encounter that the teenager regrets the next day, are also slightly predictive.
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