Researchers have long been intrigued by the connection between depression and risky decision-making, and have sought to unravel whether people suffering from major depressive disorder (MDD) exhibit different patterns of risk-taking behavior than their healthy counterparts. A team from Southwest University in Chongqing, China, led by Tao Wang and collaborators Yujie Yuan, Ying He, Jiayi Zhu, Beitong Lin, Qiao Yin, and Peiru Peng, under the direction of Associate Professor Jianmin Zeng, conducted a meta-analysis to shed light on this complex relationship. Their findings, published in the Journal of Affective Disorders Reports, provide valuable insights into how depression influences decision-making processes.
Depression, particularly major depressive disorder (MDD), is known to significantly impair cognitive functions, including decision-making. It is characterized by episodes of low mood, activity aversion, and other symptoms that affect a person's daily functioning. Given the societal burden of depression, understanding its impact on risk behavior is crucial to developing effective clinical interventions.
In their meta-analysis, the researchers examined numerous studies that used well-established decision-making tasks to assess risk-taking behavior in people with MDD. These tasks included the Iowa Gambling Task (IGT), the Balloon Analogue Risk Task (BART), the Cambridge Gambling Task (CGT), and the Game of Dice Task (GDT). By aggregating data from these studies, the team aimed to provide a comprehensive overview of how MDD affects risky decision-making.
The analysis revealed some intriguing findings. In the Iowa Gambling Task, individuals with MDD were found to select more disadvantageous decks compared to healthy controls (HC), indicating a higher risk propensity, supported by a medium effect size. In contrast, in the Balloon Analogue Risk Task, individuals with MDD pumped the balloon fewer times, suggesting that MDD patients may be more risk averse. The possible reason for this phenomenon may be attributed to structural differences between IGT and BART. The specific reasons warrant future research.
Interestingly, no significant differences were observed between MDD patients and healthy controls on the Cambridge Gambling Test and the Dice Test. These results imply that the impact of MDD on risk-taking behavior might be task-specific, influenced by the nature of the decision-making process involved in each task.
The meta-analysis also explored the role of demographic factors, such as age and gender, in modulating the relationship between MDD and risky decision making. Subgroup analysis revealed significant differences in effect sizes (the MDD-HC contrast) across various age groups within the Iowa Gambling Task and the Balloon Analogue Risk Task. Younger individuals exhibited larger effect sizes, whereas older participants did the opposite. These age-related differences underscore the importance of considering demographic factors when studying the cognitive effects of depression.
Dr. Zeng highlighted the practical implications of these findings. “Understanding the nuances in which depression affects decision-making can inform targeted interventions to help patients manage their illness more effectively,” he said. By identifying specific patterns of risk behaviors associated with MDD, clinicians can tailor their therapeutic approaches to better address the cognitive deficits linked to depression.
In conclusion, the meta-analysis by Dr. Zeng and colleagues provides a detailed examination of the intricate relationship between depression and risky decision-making. It highlights the variability in risk-taking behavior among individuals with MDD, depending on the nature of the decision-making task and demographic factors. These insights pave the way for more nuanced and effective clinical interventions aimed at mitigating the cognitive impairments associated with depression.
Journal reference
Wang, T., Zeng, J., Yuan, Y., He, Y., Zhu, J., Lin, B., Yin, Q., & Peng, P. (2024). Exploring the complex relationship between depression and risky decision making: A meta-analysis. Journal of Affective Disorders Reports. DOI: https://doi.org/10.1016/j.jadr.2024.100771
About the authors
Zeng Jianmin is an associate professor at the School of Psychology at Southwestern University. He mainly studies economic and social decision making from the perspectives of cognition, neuroscience, and genetics. He has published numerous articles in international journals, including prestigious journals such as Psychology and Marketing, Journal of neurology, Brain communications, Judgment and decision making. Among other academic contributions, He and his team have discovered several new decision phenomena, such as the final step effect, the interval anchoring effect, and the donor-recipient discrepancy in decisions between probabilistic and regular donations.
Wang Tao Wang is a graduate student at the School of Psychology, Southwest University. His research interests mainly focus on decision-making behaviors, especially the distinctive decision-making processes of people with mental illness. Wang is particularly interested in the neural mechanisms underlying decision-making and is committed to using methods such as meta-analysis to resolve existing contradictions in the field.
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