Empowering People Against Dark Patterns – Information, Recommendations, and “Counter-Nudging”

Abstract: The present study contributes to research on deceptive designs by applying the theory of planned behavior (TPB) to intention to detect and oppose dark patterns, aiming to understand whether this intention is explained by the main TPB factors – attitudes, social norm, and perceived behavioral control – and evaluating the relative importance of these predictors as well. We also assessed the role of participants’ digital competence, intended as an element of actual control in the TPB’s framework. In addition, through an experimental survey ( N = 200), we tested how different types of intervention strategies – label-based counter-nudging and explicit recommendations – influence participants’ intention and their actual ability to recognize dark patterns. Results show that TPB constructs are significantly associated with intention, and subjective norm emerged as the strongest predictor. The label-based strategy positively influenced participants’ behavior in the experimental task, but not their self-reported intention. Explicit recommendations did not significantly affect either behavior or intention.

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Publication Details

Journal
Zeitschrift für Psychologie
Published
2026-10-06
DOI
https://doi.org/10.1027/2151-2604/a000632
Primary Topic
Innovative Human-Technology Interaction
Type
article
Field-Weighted Citation Impact
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article

Empowering People Against Dark Patterns – Information, Recommendations, and “Counter-Nudging”

Carmela Altamura, Francesco La Barbera
Zeitschrift für Psychologie
Innovative Human-Technology Interaction
article

Empowering People Against Dark Patterns – Information, Recommendations, and “Counter-Nudging”

Carmela Altamura, Francesco La Barbera
article en

Abstract

Abstract: The present study contributes to research on deceptive designs by applying the theory of planned behavior (TPB) to intention to detect and oppose dark patterns, aiming to understand whether this intention is explained by the main TPB factors – attitudes, social norm, and perceived behavioral control – and evaluating the relative importance of these predictors as well. We also assessed the role of participants’ digital competence, intended as an element of actual control in the TPB’s framework. In addition, through an experimental survey ( N = 200), we tested how different types of intervention strategies – label-based counter-nudging and explicit recommendations – influence participants’ intention and their actual ability to recognize dark patterns. Results show that TPB constructs are significantly associated with intention, and subjective norm emerged as the strongest predictor. The label-based strategy positively influenced participants’ behavior in the experimental task, but not their self-reported intention. Explicit recommendations did not significantly affect either behavior or intention.

Zeitschrift für Psychologie
University of Naples Federico II (IT)
Openalex Percentile: Top 8%
Innovative Human-Technology Interaction
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