Objective:

To develop a gamified mobile decision support application for individuals with Type 1 Diabetes (T1D) and a companion application for caregivers.

Approach:

Key Findings:

• The Seq2Seq BiLSTM model outperformed other machine learning models in forecasting blood glucose trends.
• User acceptance of gamification features was noted among T1D participants.
• Caregivers identified a need for tools that provide safety monitoring while respecting patient autonomy.

Interpretation:

The Sugar Slay ecosystem integrates predictive modeling and gamification, aiming to enhance daily engagement and self-management in T1D care.

Limitations:

• The study's sample size for user experience and need-finding may limit generalizability.
• The effectiveness of the gamified approach in long-term management remains to be evaluated, and potential biases in participant selection should be considered.

Conclusion:

The Sugar Slay ecosystem represents a step towards a unified tool for T1D management, integrating support systems.

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