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Lu J, Zhao X, Wei X, He G. Risky decision-making in major depressive disorder: A three-level meta-analysis. Int J Clin Health Psychol 2024; 24:100417. [PMID: 38023370 PMCID: PMC10661582 DOI: 10.1016/j.ijchp.2023.100417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 10/03/2023] [Indexed: 12/01/2023] Open
Abstract
Background Individuals with major depressive disorder (MDD) are usually observed making inappropriate risky decisions. However, whether and to what extent MDD is associated with impairments in risky decision-making remains unclear. We performed a three-level meta-analysis to explore the relationship between risky decision-making and MDD. Method We searched the Web of Science, PubMed, Scopus, and PsycINFO databases up to February 7, 2023, and calculated Hedges' g to demonstrate the difference in risky decision-making between MDD patients and healthy controls (HCs). The moderating effect of sample and task characteristics were also revealed. Results Across 73 effect sizes in 39 cross-sectional studies, MDD patients exhibited greater risk-seeking than HCs (Hedges' g = 0.187, p = .030). Furthermore, age (p = .068), region (p = .005), and task type (p < .001) were found to have moderating effects. Specifically, patients preferred risk-seeking over HCs as age increased. European patients showed significantly increased risk-seeking compared to American and Asian patients. Patients in the Iowa Gambling Task (IGT) exhibited a notable rise in risk-seeking compared to other tasks, along with an increased risk aversion in the Balloon Analogue Risk Task (BART). The multiple-moderator analysis showed that only task type had significant effects, which may be explained by a tentative framework of "operationalization-mechanism-measure" specificity. Conclusions MDD patients generally exhibit higher risk-seeking than HCs. It implies that impaired risky decision-making might be a noteworthy symptom of depression, which should be placed more emphasis for clinical management and psycho-education.
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Affiliation(s)
- Jiaqi Lu
- Department of Psychology and Behavioral Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China
| | - Xu Zhao
- Department of Psychology and Behavioral Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China
| | - Xuxuan Wei
- Department of Psychology and Behavioral Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China
| | - Guibing He
- Department of Psychology and Behavioral Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China
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Compagne C, Mayer JT, Gabriel D, Comte A, Magnin E, Bennabi D, Tannou T. Adaptations of the balloon analog risk task for neuroimaging settings: a systematic review. Front Neurosci 2023; 17:1237734. [PMID: 37790591 PMCID: PMC10544912 DOI: 10.3389/fnins.2023.1237734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/16/2023] [Indexed: 10/05/2023] Open
Abstract
Introduction The Balloon Analog Risk Task (BART), a computerized behavioral paradigm, is one of the most common tools used to assess the risk-taking propensity of an individual. Since its initial behavioral version, the BART has been adapted to neuroimaging technique to explore brain networks of risk-taking behavior. However, while there are a variety of paradigms adapted to neuroimaging to date, no consensus has been reached on the best paradigm with the appropriate parameters to study the brain during risk-taking assessed by the BART. In this review of the literature, we aimed to identify the most appropriate BART parameters to adapt the initial paradigm to neuroimaging and increase the reliability of this tool. Methods A systematic review focused on the BART versions adapted to neuroimaging was performed in accordance with PRISMA guidelines. Results A total of 105 articles with 6,879 subjects identified from the PubMed database met the inclusion criteria. The BART was adapted in four neuroimaging techniques, mostly in functional magnetic resonance imaging or electroencephalography settings. Discussion First, to adapt the BART to neuroimaging, a delay was included between each trial, the total number of inflations was reduced between 12 and 30 pumps, and the number of trials was increased between 80 and 100 balloons, enabling us to respect the recording constraints of neuroimaging. Second, explicit feedback about the balloon burst limited the decisions under ambiguity associated with the first trials. Third, employing an outcome index that provides more informative measures than the standard average pump score, along with a model incorporating an exponential monotonic increase in explosion probability and a maximum explosion probability between 50 and 75%, can yield a reliable estimation of risk profile. Additionally, enhancing participant motivation can be achieved by increasing the reward in line with the risk level and implementing payment based on their performance in the BART. Although there is no universal adaptation of the BART to neuroimaging, and depending on the objectives of a study, an adjustment of parameters optimizes its evaluation and clinical utility in assessing risk-taking.
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Affiliation(s)
- Charline Compagne
- UR LINC, Université de Franche-Comté, Besançon, France
- CIC-1431 INSERM, Centre Hospitalier Universitaire, Besançon, France
| | - Juliana Teti Mayer
- UR LINC, Université de Franche-Comté, Besançon, France
- Centre Département de Psychiatrie de l’Adulte, Centre Hospitalier Universitaire, Besançon, France
| | - Damien Gabriel
- UR LINC, Université de Franche-Comté, Besançon, France
- CIC-1431 INSERM, Centre Hospitalier Universitaire, Besançon, France
- Plateforme de Neuroimagerie Fonctionnelle Neuraxess, Besançon, France
| | - Alexandre Comte
- UR LINC, Université de Franche-Comté, Besançon, France
- Centre Département de Psychiatrie de l’Adulte, Centre Hospitalier Universitaire, Besançon, France
| | - Eloi Magnin
- UR LINC, Université de Franche-Comté, Besançon, France
- CHU Département de Neurologie, Centre Hospitalier Universitaire, Besançon, France
| | - Djamila Bennabi
- UR LINC, Université de Franche-Comté, Besançon, France
- Centre Département de Psychiatrie de l’Adulte, Centre Hospitalier Universitaire, Besançon, France
- Centre Expert Dépression Résistante Fondamentale, Centre Hospitalier Universitaire, Besançon, France
| | - Thomas Tannou
- UR LINC, Université de Franche-Comté, Besançon, France
- Plateforme de Neuroimagerie Fonctionnelle Neuraxess, Besançon, France
- CIUSS Centre-Sud de l’Ile de Montréal, Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Montréal, QC, Canada
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Wang Y, Li X, Yan H, Zhang Q, Ou Y, Wu W, Shangguan W, Chen W, Yu Y, Liang J, Wu W, Liao H, Liu Z, Mai X, Xie G, Guo W. Multiple examinations indicated associations between abnormal regional homogeneity and cognitive dysfunction in major depressive disorder. Front Psychol 2023; 13:1090181. [PMID: 36778176 PMCID: PMC9909210 DOI: 10.3389/fpsyg.2022.1090181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 12/28/2022] [Indexed: 01/27/2023] Open
Abstract
Background This study aimed to investigate the relationships between regional neural activity and multiple related indicators in patients with major depressive disorder (MDD). Methods Forty-two patients and 42 healthy controls (HCs) were enrolled. Pearson/Spearman correlation analyses were applied to examine the associations between abnormal regional homogeneity (ReHo) and different indicators in the patients. Results Compared with HCs, patients with MDD had increased ReHo in the left inferior temporal gyrus (ITG) and decreased ReHo values in the left putamen, anterior cingulate cortex (ACC), and precentral gyrus. The ReHo of the left putamen was positively correlated with the PR interval, Repeatable Battery for the Assessment of Neuropsychological Status 4A, and Discriminant analysis (D), and negatively correlated with Ae (block) and Ae (total) in the patients. The ReHo value of the left ACC was positively correlated with the severity of depression, Stroop Color Word Test of C - 2B + 100 in reaction time, and negatively correlated with Ce (Missay) and Perseverative Responses in the patients. The ReHo of the left ITG was positively correlated with the Neuroticism scores and negatively correlated with the Lie scores in the patients. Conclusion These results suggested that the decreased ReHo of the salience network might be the underpinning of cognitive impairments in patients with MDD.
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Affiliation(s)
- Yun Wang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xiaoling Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Qinqin Zhang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Yangpan Ou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Weibin Wu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Webo Shangguan
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Wensheng Chen
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Yang Yu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Jiaquan Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Wanting Wu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Hairong Liao
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Zishan Liu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xiancong Mai
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China,*Correspondence: Guojun Xie, ✉
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China,Wenbin Guo, ✉
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Zheng S, Zeng W, Xin Q, Ye Y, Xue X, Li E, Liu T, Yan N, Chen W, Yin H. Can cognition help predict suicide risk in patients with major depressive disorder? A machine learning study. BMC Psychiatry 2022; 22:580. [PMID: 36050667 PMCID: PMC9434973 DOI: 10.1186/s12888-022-04223-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 08/23/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Previous studies suggest that deficits in cognition may increase the risk of suicide. Our study aims to develop a machine learning (ML) algorithm-based suicide risk prediction model using cognition in patients with major depressive disorder (MDD). METHODS Participants comprised 52 depressed suicide attempters (DSA) and 61 depressed non-suicide attempters (DNS), and 98 healthy controls (HC). All participants were required to complete a series of questionnaires, the Suicide Stroop Task (SST) and the Iowa Gambling Task (IGT). The performance in IGT was analyzed using repeated measures ANOVA. ML with extreme gradient boosting (XGBoost) classification algorithm and locally explanatory techniques assessed performance and relative importance of characteristics for predicting suicide attempts. Prediction performances were compared with the area under the curve (AUC), decision curve analysis (DCA), and net reclassification improvement (NRI). RESULTS DSA and DNS preferred to select the card from disadvantageous decks (decks "A" + "B") under risky situation (p = 0.023) and showed a significantly poorer learning effect during the IGT (F = 2.331, p = 0.019) compared with HC. Performance of XGBoost model based on demographic and clinical characteristics was compared with that of the model created after adding cognition data (AUC, 0.779 vs. 0.819, p > 0.05). The net benefit of model was improved and cognition resulted in continuous reclassification improvement with NRI of 5.3%. Several clinical dimensions were significant predictors in the XGBoost classification algorithm. LIMITATIONS A limited sample size and failure to include sufficient suicide risk factors in the predictive model. CONCLUSION This study demonstrate that cognitive deficits may serve as an important risk factor to predict suicide attempts in patients with MDD. Combined with other demographic characteristics and attributes drawn from clinical questionnaires, cognitive function can improve the predictive effectiveness of the ML model. Additionally, explanatory ML models can help clinicians detect specific risk factors for each suicide attempter within MDD patients. These findings may be helpful for clinicians to detect those at high risk of suicide attempts quickly and accurately, and help them make proactive treatment decisions.
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Affiliation(s)
- Shuqiong Zheng
- grid.416466.70000 0004 1757 959XDepartment of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China ,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
| | - Weixiong Zeng
- grid.416466.70000 0004 1757 959XDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Qianqian Xin
- grid.416466.70000 0004 1757 959XDepartment of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China ,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
| | - Youran Ye
- grid.416466.70000 0004 1757 959XDepartment of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China ,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
| | - Xiang Xue
- grid.416466.70000 0004 1757 959XDepartment of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China ,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
| | - Enze Li
- grid.416466.70000 0004 1757 959XDepartment of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China ,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
| | - Ting Liu
- grid.416466.70000 0004 1757 959XDepartment of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China ,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
| | - Na Yan
- grid.416466.70000 0004 1757 959XDepartment of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China ,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
| | - Weiguo Chen
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
| | - Honglei Yin
- Department of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China. .,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China.
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Kong X, Zhang P, Xiao F, Fang S, Ji X, Wang X, Lin P, Li H, Yao S, Wang X. State-independent and -dependent behavioral and neuroelectrophysiological characteristics during dynamic decision-making in patients with current and remitted depression. J Affect Disord 2022; 309:85-94. [PMID: 35472481 DOI: 10.1016/j.jad.2022.04.120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 04/14/2022] [Accepted: 04/19/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND It is unclear whether the altered decision-making (DM) observed in patients with major depressive disorder (MDD) is neurophysiological and whether it improves with remission of depressive symptoms. The aim of this study was to identify developmental patterns of DM behavior, related cognitive characteristics, and electrophysiological abnormalities in patients with MDD across clinical stages. METHODS A sample of 48 first-episode MDD patients (FD group), 41 remitted MDD patients (RD group), and 43 healthy controls (HCs) completed psychometric assessments and performed the balloon analogue risk task (BART) while event-related potentials (ERPs) were recorded. RESULTS The RD group had lower depressiveness, self-blame, rumination, and catastrophizing tendencies, and higher mental resilience scores than the FD group, but retained significant differences from HCs. MDD patients showed a more conservative DM strategy than HCs, with no significant difference between the FD and RD groups. Compared to the FD group, the RD group had a smaller FRN for negative feedback and a trend toward a smaller P3 for positive feedback. Compared with HCs, the RD group had a smaller P3 during the positive feedback phase. FRN amplitude correlated positively with depression level and negatively with mental resilience. LIMITATIONS Because a comparative cross-section design was employed, longitudinal studies are needed to make causal inferences. CONCLUSION MDD patients presented a stable risk-avoidance bias in actively depressed and remission periods, consistent with a state-independent impairment pattern. Significantly reduced FRN amplitudes during remission indicated a state-dependent impairment pattern, and FRN amplitudes correlated with depression level. An abnormal feedback P3 component may be a state-independent characteristic that may become more pronounced with MDD progression.
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Affiliation(s)
- Xinyuan Kong
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha 410011, China
| | - Panwen Zhang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; Shanghai Songjiang Jiuting Middle School, Shanghai, China
| | - Fan Xiao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha 410011, China
| | - Shulin Fang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha 410011, China
| | - Xinlei Ji
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha 410011, China
| | - Xiaosheng Wang
- Department of Human Anatomy and Neurobiology, Xiangya School of Medicine, Central South University, Changsha 410013, China
| | - Pan Lin
- Department of Psychology and Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, Hunan 410081, China
| | - Huanhuan Li
- Department of Psychology, Renmin University of China, Beijing 100872, China
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha 410011, China
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha 410011, China.
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