Gamification of cognitive bias modification for interpretations in anxiety increases training engagement and enjoyment

Abstract

Background and objectives: Interpretation bias plays a crucial role in anxiety. To test the causal role and potential clinical benefits, training procedures were developed to experimentally change interpretation bias. However, these procedures are monotonous and plain, which could negatively affect motivation and adherence. The aim of this study was to make the interpretation training more engaging and enjoyable, without compromising its effectiveness, through gamification. Methods: The training was gamified by including extrinsically and intrinsically motivating elements such as points, scores, time-pressure, fun and adaptive elements (training at an individually challenging level). A 2 (Type: Gamified vs. Standard) x 2 (Training Valence: Positive vs. Placebo) between-subjects design was used with random allocation of 79 above-average anxious individuals. Post-training, we assessed the liking and recommendation of the training task, interpretation bias (Recognition task and the Scrambled Sentence Task) and anxiety. Results: Participants experienced the gamified training tasks as more engaging and enjoyable than the standard tasks, although it was not recommend more to fellow-students. Both positive training conditions (gamified and standard) were successful in eliciting a positive interpretation bias when assessed with the Recognition task, while only the standard positive training impacted on interpretations when assessed with the Scrambled Sentence Task. No differential effects were observed on anxiety. Limitations: The study involved only a single-session training and participants were selected for high trait (and not social) anxiety. Conclusions: The gamified training was evaluated more positively by the participants, while maintaining the effectiveness of eliciting positive interpretations when assessed with the Recognition task. This suggests that gamification might be a promising new approach.