Artificial intelligence to better understand problematic pornography consumption

More than 70 scientists around the world pooled their research data to identify more than 700 potential predictors, using a machine learning method.

“This was the first time we had collected all the existing data on problematic pornography use,” said Professor Peta Botti, from the Department of Psychology at the University of Montreal. We couldn't analyze so much data without AI and machine learning. No human being can do that.”

Seventeen strong predictors emerged from the group, but five stood out more than the rest: frequency of use; Emotional avoidance as well as stress reduction as motivations for consumption; Moral ambivalence regarding consumption; And sexual shame.

It goes without saying that not everyone who frequently consumes pornography suffers from problematic use. Distress has been described when there is excessive consumption, but especially in the case of an inability to control one's behavior.

Pornography use becomes a problem when an individual cannot stop using it, despite difficult emotional states and even if it greatly interferes with their daily life. This excessive consumption can lead to relational, financial, and even legal problems.

“When we look at the data, we see that there are two main categories of predictive factors,” Professor Botti explained. For example, and this is not surprising, people who consume the most pornography or who consume it for the longest time are at greatest risk for developing problematic use. But there are also predictive factors related to negative emotions and the way people manage these emotions.

Specifically, she added, data shows that people who use pornography to cope with negative emotions or to manage stress also have higher levels of problematic pornography use. People with symptoms of anxiety or depression, or those who feel lonely, will also be more at risk.

“So it appears that negative emotions and the way people deal with negative emotional stress may be an important factor in problematic pornography use,” Botti said.

Desiring to find preventative solutions to the harmful consequences of this disorder, the researcher and her colleagues became interested in variables that could help predict problems with pornography consumption.

Botti said this study contributes additional knowledge about pornography consumption in general, and risk factors for problematic use in particular.

This new empirical knowledge can contribute to the development of more targeted, relevant and effective prevention and intervention programs.

For example, the study showed that gender comes in only 14th on the list of predictive factors, even though pornography consumption is primarily associated with men in the popular imagination.

“It appears that gender is not as important as we thought in the past,” Professor Botti said. Studies have mainly focused on men, but we now see that we should also pay attention to women or individuals of different genders.

Problematic pornography consumption is the most common manifestation of compulsive sexual behavior disorder, a condition characterized by uncontrollable sexual urges and behaviors, as well as clinically significant distress.