mHealth Technologies for Managing Problematic Pornography Use: Content Analysis

Abstract

Background: Several mobile apps are currently available that purportedly help with managing pornography addiction. However, the utility of these apps is unclear, given the lack of literature on the effectiveness of mobile health solutions for problematic pornography use. Little is also known about the content, structure, and features of these apps.

Objective: This study aims to characterize the purpose, content, and popularity of mobile apps that claim to manage pornography addiction.

Methods: The phrase "pornography addiction" was entered as a search term in the app stores of the two major mobile phone platforms (Android and iOS). App features were categorized according to a coding scheme that contained 16 categories. Apps were included in the analysis if they were described as helpful for reducing pornography use, and data were extracted from the store descriptions of the apps. Metrics such as number of user ratings, mean rating score, and number of installations were analyzed on a per-feature basis.

Results: In total, 170 apps from both app stores met the inclusion criteria. The five most common and popular features, both in terms of number of apps with each feature and minimum possible number of installations, were the ability to track the time since last relapse (apps with feature=72/170, 42.4%; minimum possible number of installations=6,388,000), tutorials and coaching (apps with feature=63/170, 37.1%; minimum possible number of installations=9,286,505), access to accountability partners or communities (apps with feature=51/170, 30%; minimum possible number of installations=5,544,500), content blocking or content monitoring (apps with feature=46/170, 27.1%; minimum possible number of installations=17,883,000), and a reward system for progress (apps with feature=34/170, 20%; minimum possible number of installations=4,425,300). Of these features, content-blocking apps had the highest minimum possible number of installations. Content blocking was also the most detected feature combination in a combinatorial analysis (with 28 apps having only this feature), but it also had the lowest mean consumer satisfaction rating (4.04) and second-lowest median rating (4.00) out of 5 stars. None of the apps reviewed contained references to literature that provided direct evidence for the app's efficacy or safety.

Conclusions: There are several apps with the potential to provide low- or zero-cost real-time interventions for people struggling to manage problematic pornography use. Popular app features include blockers of pornographic content, behavior monitoring, and tutorials that instruct users how to eliminate pornography use. However, there is currently no empirical evidence to support the effectiveness and safety of these apps. Further research is required to be able to provide recommendations about which apps (and app features) are safe for public consumption.

Keywords: CSBD; PPU; addiction; behavioral addiction; compulsive sexual behavior disorder; internet addiction; just-in-time adaptive intervention; mHealth; mobile health; mobile intervention; mobile phone; pornography; problematic pornography use; smartphone-based therapy.