Identifying Deceptive Patterns Across Three Age Groups: A Heuristic-Based Cognitive Walkthrough Study of Mobile Apps

2026-07-05

AI Summary

This study addresses the pervasive presence of deceptive design patterns in mobile applications targeting distinct age groups, which can inadvertently prompt unintended user behaviors. It presents the first systematic comparison of such patterns across adolescents, adults, and older adults within 30 apps spanning six categories, employing a qualitative analysis that integrates heuristic evaluation and cognitive walkthroughs. The findings reveal that 93% of the examined apps employ nagging-type dark patterns, with entertainment apps exhibiting particularly high prevalence. Crucially, entertainment applications designed for older adults deploy stealth strategies significantly more often than those targeting other age groups, uncovering a novel age-directed characteristic of deceptive design. These results provide empirical evidence to inform age-appropriate digital governance and regulatory interventions.

Abstract

Deceptive patterns are tactics used to manipulate users into performing unintended actions. Today, many of these deceptive patterns are implemented in mobile apps targeting diverse age groups. In this paper, we employ a heuristic-based cognitive walkthrough to explore how deceptive patterns are tailored to three age groups, specifically teens (12-17), adults (18-49), and older adults (50+), across different app categories. By analyzing 30 apps spanning 6 categories, we found that 93% of these apps use the nagging pattern. Furthermore, our findings reveal that entertainment apps contain significantly more deceptive patterns than other app categories, such as music/books. Our data also shows that entertainment apps for older adults use sneaking patterns more frequently than entertainment apps for teens or adults. These findings call for the development of more ethical, age-specific design guidelines to protect users from targeted digital manipulation attempts.

Problem

• deceptive patterns
• age groups
• mobile apps
• digital manipulation
• user protection

Innovation

• deceptive patterns
• heuristic-based cognitive walkthrough
• age-specific design
• mobile apps
• digital manipulation