What is it about?
Many people with mental health problems recognize this experience: “I know it would be good for me, but I can’t get myself to do it.” This reduced drive to pursue rewarding activities is often described as amotivation and anhedonia. In this paper, we synthesized research on effort-based decision-making, lab tasks that measure how willing people are to exert effort for a potential reward, especially when rewards vary in size and likelihood. Across 68 studies (nearly 3,700 participants) spanning schizophrenia-spectrum disorders, bipolar disorder, major depressive disorder, and at-risk samples, we found that willingness to work for reward was most consistently reduced in schizophrenia-spectrum and bipolar disorders, smaller but significant in major depressive disorder, and not reliably reduced in at-risk samples. A key pattern was that effort often did not scale up when rewards were larger and more likely, even though that is usually the most beneficial choice. We also reviewed computational work suggesting these difficulties can reflect different mechanisms, such as increased effort sensitivity, reduced reward sensitivity, and cognitive constraints.
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Why is it important?
What’s unique and timely about this work is that it brings together a fast-growing, but methodologically diverse, literature on effort-based decision-making (EBDM) into a single transdiagnostic synthesis that is directly anchored in clinically relevant problems: amotivation and anhedonia. Rather than focusing on one disorder or one paradigm, we integrate evidence across schizophrenia-spectrum disorders, bipolar disorder, major depressive disorder, and at-risk samples, and we examine how key task and study features shape results. Clinically, this matters because similar “motivation” complaints can reflect different underlying pathways. By combining meta-analytic findings with a structured review of computational modeling, our paper moves beyond a one-size-fits-all account. It supports a more nuanced view in which reduced effort allocation may arise from higher effort costs, reduced reward sensitivity, and/or cognitive constraints, with some mechanisms appearing more prominent in particular disorders (e.g., unsystematic effort allocation and cognitive impairment in schizophrenia-spectrum disorders). The practical impact is that this work helps translate laboratory measures into more clinically actionable insights. Our findings can inform intervention development by clarifying which mechanisms may be most relevant to target in different populations. Morover, they can guide task selection and hypothesis testing, improving comparability and cumulative progress in future research.
Perspectives
Writing this paper was personally meaningful because it sits right at the intersection of what I hear clinically and what we try to capture in the lab: motivational problems despite knowing what is good for us and even having meaningful personal goals. What I value most about this work is that it offers insight into disorder-specific pathways to motivational difficulties, despite a shared phenomenology across diagnoses. In other words, similar clinical complaints may reflect different underlying mechanisms and that distinction matters if we want more precise assessment and better targeted interventions. On a personal note, it was a privilege to work with leading experts in the field. I learned a great deal from their expertise and from seeing just how much work on effort-based decision-making has emerged over the past decade.
Matthias Pillny
University of Hamburg
Read the Original
This page is a summary of: Effort-based decision making in psychopathology: A transdiagnostic multilevel meta-analysis and systematic review of behavioral patterns and mechanisms underlying amotivational psychopathology., Psychological Bulletin, March 2026, American Psychological Association (APA),
DOI: 10.1037/bul0000510.
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