Age and Sex Effects on Super G Performance Are Consistent Across Internet Devices

The Super G motor-cognitive game serves as a robust, scalable biomarker for detecting early signs of dementia by measuring motor skill acquisition. By evaluating performance metrics across both computer and mobile platforms, the research confirms that the game maintains consistent diagnostic validity regardless of the hardware used. While device type introduces a measurable performance offset of approximately 121 milliseconds, this variance is independent of user demographics, allowing for reliable cross-platform data integration once statistical adjustments are applied.

The study demonstrates that the established relationships between performance and participant age or sex remain stable across different digital environments. Although the specific interface influences initial baseline scores and the velocity of skill acquisition, these factors do not distort the underlying cognitive and motor patterns that the game is designed to measure. Consequently, the findings validate the use of Super G as a versatile assessment tool capable of producing consistent results across diverse populations.

Spanning foundational research in visuospatial processing and motor-skill learning, the analysis confirms that demographic variables consistently interact with game performance in predictable ways. By isolating the impact of hardware from the influence of age and gender, the research establishes a framework for deploying serious games in clinical settings. These insights ensure that digital health assessments can be administered on a wide range of consumer devices without compromising the integrity or sensitivity of the diagnostic data collected.