There is a growing trend to accept, understand and cater to people with heterogenous mental health levels, as captured by the term “neurodiversity”. Population studies demonstrate growth in neurodiversity facets such as depression, anxiety, and attention deficit hyperactivity disorder (ADHD). Thus, samples of information systems (IS) users are likely neurodiverse. While studies started examining neurodiversity effects mostly in professional contexts, possible effects of IS users’ neurodiversity in leisure settings have been largely overlooked. Here, we suggest that we need to consider such possible effects more systematically. This is important because neurodiversity facets can manifest in changes in cognitive-emotional processing, social reactions, and decision making which can alter user responses to IS. Thus, ignoring the neurodiversity of users can affect the accuracy and generalizability of user behavior models; it can disadvantage large segments of users. To support these ideas, we first develop a theoretical model that explains how neurodiversity can affect the decision making of IS users. Next, we conduct three studies (n1=400, n2=381, and n3=280) that first replicate common IS models in leisure settings, and then theoretically and empirically integrate neurodiversity facets into these models. Results show that (a) typical IS user samples are neurodiverse, and (b) integrating neurodiversity facets into user behavior models can be informative, lead to greater inclusivity, and afford more nuanced theoretical and practical insights. Thus, we call for a more systematic inclusion of neurodiversity facets in behavioral IS research.