People are at least as good at optimizing reward rate under fixed-trial compared to fixed-time conditions.

Finding an optimal decision-making strategy requires a careful balance between the competing demands of accuracy and urgency.In experimental settings, researchers are typically interested in whether people can optimise this trade-off, typically operationalised as reward rate, with evidence accumulation models serving as the key framework to determine whether people are performing optimally. However, recent studies have suggested that inferences about optimality can be highly dependent on the task design, meaning that inferences about whether people can achieve optimality may not generalise across contexts.Here, we investigate one fundamental, though typically overlooked, design factor: whether participants spend a fixed amount of time on each block (fixed-time) or have a fixed number of trials in each block (fixed-trials), with researchers typically assuming that people are better able to optimize reward rate under fixed-time conditions. Across three experiments, our results consistently indicate that people are at least as good at optimising reward rate under fixed-trial conditions as fixed-time conditions, and potentially even better under fixed-trial conditions. Importantly, these findings both challenge the common assumption within reward rate optimality research regarding the superiority of fixed-time study designs, and further emphasise the importance of carefully considering study design factors when making inferences about optimality in decision-making.