Decentralized study settings have been proven to increase efficiency and diversity in clinical trials and research studies. However, one of the biggest challenges of decentralized settings is high dropout rates and low adherence to the study protocol. Gamification has shown to be a promising tool to increase motivation and engagement in different settings, but very few tools exist implementing personalization, which is crucial to address the needs of diverse user contexts. In this paper, we present our vision of using gamification to improve adherence and retention in digital, decentralized research studies and clinical trials. We aim to design, implement and evaluate a modular, AI-based gamification engine designed to personalize motivational strategies based on user profiles and context. Its modular, test-agnostic design approach enables the integration across platforms and study types, offering the potential of a reusable infrastructure for adherence support in digital health research.

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Adaptive, Personalized Gamification to Improve Adherence and Retention in Decentralized Study Settings

  • Janna Herrmann,
  • Marc Schubhan,
  • Maximilian Altmeyer

摘要

Decentralized study settings have been proven to increase efficiency and diversity in clinical trials and research studies. However, one of the biggest challenges of decentralized settings is high dropout rates and low adherence to the study protocol. Gamification has shown to be a promising tool to increase motivation and engagement in different settings, but very few tools exist implementing personalization, which is crucial to address the needs of diverse user contexts. In this paper, we present our vision of using gamification to improve adherence and retention in digital, decentralized research studies and clinical trials. We aim to design, implement and evaluate a modular, AI-based gamification engine designed to personalize motivational strategies based on user profiles and context. Its modular, test-agnostic design approach enables the integration across platforms and study types, offering the potential of a reusable infrastructure for adherence support in digital health research.