Exploring Task Design and Heuristics Interaction Through a Knowledge‐Free Option Generation Task. - Chen, Yanlin; Ang, Yuen‐Siang; Cusin, Cristina; Fava, Maurizio; Pizzagalli, Diego A. (Scandinavian Journal of Psychology, 2025)
Past research on option generation, the mental process of creating possible courses of action for goal‐directed behaviors, focused extensively on the outcomes of the process, specifically, the quantity and quality of options generated. Accordingly, various effects were introduced to describe and categorize observed trends in option properties, yet these studies utilize differing task designs. This paper focuses on the "quantity‐breeds‐quality", "less‐is‐more", and the concomitant "Take The First" (TTF) heuristics. We conducted a secondary analysis of data from a culture‐free, education‐independent, and quantitative option generation task and compared the results to those predicted by the heuristics to discuss how study characteristics are well‐aligned with the heuristics they investigate. To bolster ecological validity and reflect a more diverse range of cognitive experiences beyond the neurotypical population, 44 healthy individuals and 54 patients with Major Depressive Disorder were asked to generate as many different paths as they could between two fixed points on a touchscreen computer in 1.5 min, and the generated options were quantified based on three metrics of interest: fluency, uniqueness, and diversity. For both groups, the mean uniqueness, maximum uniqueness, and diversity of an individual's paths were negatively correlated with an increase in fluency, in line with the less‐is‐more effect yet conflicting with the results predicted by the quantity‐breeds‐quality effect. In addition, normalized path uniqueness decreased with the path index, contrary to the results predicted by the TTF heuristic. The results were analyzed with reference to the three heuristics, to discuss possible task characteristics that cause a particular heuristic to apply, and demonstrate the fundamental differences between real‐life decision‐making scenarios and knowledge‐independent tasks.