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

Research Background and Issues

• What problems or challenges did the authors identify?

  • This study focuses on the widespread presence of "dark patterns" in social media—strategies that manipulate user behavior through interface design. Previous research indicates that many users struggle to recognize these patterns.
  • Specifically, the study investigates whether individuals with Attention Deficit Hyperactivity Disorder (ADHD) exhibit distinct abilities in identifying and avoiding dark patterns, as they may be more susceptible to interface designs that affect attention.

• Why is this issue important?

  • Dark patterns have been proven to negatively impact users' privacy, autonomy, and mental health, especially within the data-driven social media ecosystem.
  • Individuals with ADHD may face greater risks due to their attention allocation and executive function deficits, which could make them more vulnerable to manipulation.

• Research Motivation and Related Work

  • While prior studies have explored the negative effects of dark patterns, research targeting specific (especially vulnerable) populations remains scarce.
  • ADHD is a highly prevalent neurodevelopmental disorder, and existing studies have shown its significant impact on technology use behaviors (e.g., video game addiction). This study aims to address this research gap.

Solutions

• What methods or solutions did the authors propose?

  • The study designed a 2×2 factorial comparison experiment, dividing 135 participants into ADHD and non-ADHD groups to explore their abilities to identify and avoid dark patterns in social media.
  • A dynamic interactive simulated social media platform was developed to enable in-depth analysis of dark patterns, offering a more realistic environment compared to static screenshots used in previous studies.

• What are the innovative aspects of this solution?

  • The use of a simulated platform to present dark patterns in a multi-task format allows tracking of user responses to dark patterns in dynamic interactions.
  • The user interface was designed based on a mature dark pattern taxonomy, incorporating high, medium, and low-level strategies to advance understanding of the temporal effects of dark patterns.
  • A customizable open-source platform was provided for future research, supporting studies targeting specific user groups.

• What are the implementation steps and key technologies used?

  • Experimental tasks included creating accounts and commenting on content within the simulated platform, with UI designs adjusted to create versions with and without dark patterns.
  • A web application developed using Vue.js recorded user behavior data, including navigation paths and interactions.
  • Surveys measured users' perceptions of dark pattern characteristics (e.g., hidden information, misleading design) and cognitive load (NASA-TLX).

Research Outcomes

• What specific outcomes were achieved?

  • ADHD and non-ADHD groups exhibited similar performance in identifying dark patterns, but significant differences were found in their ability to avoid them:
    • ADHD individuals were more likely to disclose personal information but were more successful in avoiding paid account options.
    • Non-ADHD individuals were more susceptible to implicit strategies in dark patterns, such as pre-checked terms.

• What advantages does this solution have compared to existing ones?

  • The study extends dark pattern research from static screenshots to dynamic interactions, collecting real-time process data and improving ecological validity.
  • It is the first to explore how specific vulnerable groups (ADHD) interact with dark patterns, offering new perspectives for design research related to neurodiversity.

• What are the experimental or evaluation results?

  • Different task versions (dark pattern vs. non-dark pattern) significantly influenced participants' choices.
  • ADHD participants were more sensitive to reward-driven dark patterns (e.g., progress bars showing task completion rates).
  • NASA-TLX scores indicated that dark patterns increased overall cognitive load, but ADHD individuals reported lower effort and frustration levels.

• Limitations and Future Directions

  • Limitations:
    • ADHD diagnosis was self-reported and not medically verified, so results should be interpreted cautiously.
    • The study was conducted on a simulated platform rather than real social media, potentially limiting ecological validity of user behavior.
    • Differences in task conditions (e.g., mandatory steps in tasks) may lead to data incomparability.
  • Future Directions:
    • Investigate how other neurodiverse groups interact with dark patterns.
    • Develop validation scales to more reliably measure dark pattern recognition abilities.
    • Extend research to more real-world social media platforms and task scenarios.

By synthesizing this research, the study not only fills a gap in understanding how specific populations interact with dark patterns but also calls for stricter regulation and intervention regarding the ethical issues of incorporating dark patterns into design.