"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."
Cognitive abilities among people with schizophrenia vary widely, with some solving complex spatial puzzles quickly while others struggle with simple tutorials. Static difficulty curves and a few preset difficulty levels fail to accommodate this diversity. Games must implement adaptive systems that adjust difficulty in real time based on performance, accelerating progression for fast learners and offering scaffolding to those who struggle without causing embarrassment. Implementing robust auto-balance is technically challenging and requires careful UX design, because poor balancing can cause churn among both highly capable and low-capability users. Many players in this demographic are experienced gamers, influencing design expectations.
Read at Medium
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