"During our user testing sessions, I watched one participant solve complex spatial puzzles in under ten seconds while expressing frustration that the game wasn't challenging them enough. Twenty minutes later, another participant struggled with what I considered the simplest tutorial level. Both users had the same diagnosis. Both were part of our target demographic. But their cognitive strengths and challenges were completely different."
"This taught me that traditional difficulty curves don't work for cognitive remediation games. You can't design three difficulty settings and call it accessible. Instead, you need systems that automatically adapt in real time based on user performance. If someone breezes through the first five levels, the algorithm should immediately jump them ahead. If someone struggles with basic interactions, the system needs to provide more scaffolding without making them feel patronized."
Extensive user testing with people diagnosed with schizophrenia revealed dramatic variability in cognitive abilities among individuals sharing the same diagnosis. Some participants solved complex spatial puzzles in seconds while others struggled with basic tutorial tasks. Conventional fixed difficulty settings and limited difficulty tiers failed to accommodate this variability. Effective cognitive remediation games require real-time adaptive systems that accelerate challenge for capable players and provide scaffolding for those who struggle, without causing frustration or patronization. Implementing reliable Auto Balance systems presents technical and UX challenges, and many players in the target population have prior gaming experience.
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