A Comparative Study of How People With and Without ADHD Recognise and Avoid Dark Patterns on Social Media

2025-03-07

AI Summary

Individuals with ADHD are often presumed to be more susceptible to manipulative “dark patterns” in digital interfaces, yet empirical evidence on their actual detection and avoidance capabilities remains scarce. Method: We conducted an interactive web-based experiment using authentic social media interfaces with 135 participants (ADHD and neurotypical control groups), analyzing behavioral logs and applying rigorous statistical tests (independent-samples t-tests and chi-square tests). Contribution/Results: Contrary to prevailing assumptions, both groups exhibited similarly low overall dark pattern detection rates, with no statistically significant intergroup difference. However, participants with ADHD demonstrated significantly higher avoidance rates for specific dark pattern types—namely, “sludgy defaults” and “urgency-driven language.” This challenges the stereotype of universal vulnerability among individuals with ADHD and reveals context-dependent adaptive strategies. The findings provide novel empirical support for neurodiversity-informed digital literacy interventions and ethically grounded platform design.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Web

Application Category

• Economics, Online Markets and Human Computation: Sustainability of Web economics
• Responsible Web: Algorithmic accountability and transparency on the web
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Dark patterns are deceptive strategies that recent work in human-computer interaction (HCI) has captured throughout digital domains, including social networking sites (SNSs). While research has identified difficulties among people to recognise dark patterns effectively, few studies consider vulnerable populations and their experience in this regard, including people with attention deficit hyperactivity disorder (ADHD), who may be especially susceptible to attention-grabbing tricks. Based on an interactive web study with 135 participants, we investigate SNS users' ability to recognise and avoid dark patterns by comparing results from participants with and without ADHD. In line with prior work, we noticed overall low recognition of dark patterns with no significant differences between the two groups. Yet, ADHD individuals were able to avoid specific dark patterns more often. Our results advance previous work by understanding dark patterns in a realistic environment and offer insights into their effect on vulnerable populations.

Problem

• Study compares ADHD and non-ADHD users' recognition of dark patterns.
• Investigates ability to avoid dark patterns on social media platforms.
• Focuses on vulnerable populations' susceptibility to deceptive digital strategies.

Innovation

• Interactive web study with 135 participants
• Comparison of ADHD and non-ADHD users
• Focus on dark pattern recognition and avoidance