ArticleAppetite2026
Longitudinal analysis of decision-making deficits in binge-eating disorders using drift diffusion modeling.
Article in Appetite, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Individuals with binge-type eating disorders (binge-EDs) repeatedly engage in binge eating despite negative consequences, suggesting altered decision-making. However, the specific cognitive mechanisms underlying these alterations remain poorly understood. In this longitudinal study, we applied the drift diffusion model (DDM) - a computational approach that isolates core decision-making components - to examine how these components relate to binge-eating frequency over time. Ninety-five adults with binge-EDs (69% binge-eating disorder; 15% bulimia nervosa) completed a probabilistic reward task at baseline and 3-month follow-up, with binge-eating frequency assessed concurrently and at 6-month follow-up. Results indicated that slower evidence accumulation (lower drift rate) consistently predicted greater binge-eating frequency both cross-sectionally (baseline p < .001; 3-month p = .018) and prospectively (6-month p < .001), highlighting impaired integration of decision-relevant information as a possible mechanism maintaining binge eating. A lower decision threshold, indicating less cautious decision-making, was cross-sectionally associated with greater binge-eating frequency (baseline p < .001) but did not predict symptoms over time (p-values >.552). In contrast, reward sensitivity (start bias) showed no significant relationship with binge-eating frequency (p-values >.357), possibly reflecting methodological limitations. These findings tentatively support the hypothesis that specific deficits in core decision-making processes contribute to binge-eating persistence, suggesting novel intervention targets. Additionally, our study demonstrates the utility of the DDM as a computational framework for unifying and interpreting diverse behavioral data within the binge-ED literature.
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