Players with schizophrenia show wide variability in cognitive abilities, from rapid problem-solving to difficulty with simple tutorials. Traditional static difficulty curves fail to accommodate such variability. Effective remediation games require algorithms that adapt difficulty and scaffolding in real time based on individual performance. Adaptive systems should advance users who master challenges and provide unobtrusive support for those who struggle. Poor balance can drive away both highly capable and challenged players. Game design must address technical complexity alongside high user-experience stakes. Assumptions about gaming literacy must be tested through diverse user research.
The biggest surprise was how dramatically cognitive abilities varied within our target population. 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.
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