"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."
Designing cognitive remediation games for people with schizophrenia requires adaptive, real-time difficulty scaling because cognitive abilities vary widely within the target population. Traditional difficulty curves and a few preset difficulty levels are insufficient for accessibility. Effective systems must automatically adjust based on performance, advancing fast players and providing scaffolding for those who struggle without being patronized. Automatic balancing poses significant technical challenges and carries high user-experience stakes. Failure to adapt can drive away both highly capable and less capable users for opposite reasons. Many players may also be experienced gamers, so designs must account for prior gaming skill alongside cognitive needs.
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