双相障碍患者的风险决策偏好：来自三水平元分析的证据

doi:10.3724/SP.J.1041.2025.0100

摘要/Abstract

摘要：

本研究采用三水平元分析定量估计双相患者与健康个体的风险决策偏好差异, 并检验该差异是否受到样本特征和测量特征的调节。基于71篇文献和176个效应量的元分析发现, 双相患者比健康个体更偏好风险寻求(Hedges' g = 0.301), 且这一偏好在风险态度量表(Hedges' g = 0.624)、行为实验任务(Hedges' g = 0.252)和日常风险行为(Hedges' g = 0.312)中都稳定存在。同时, 该差异还受到年龄(β = 0.009)和心境阶段的调节, 其中不论心境阶段如何, 双相患者均比健康个体更偏好风险寻求(缓解期: Hedges' g = 0.245; <轻>躁狂期: Hedges' g = 0.604; 重性抑郁期: Hedges' g = 0.417)。此外, 在行为实验任务中, 该差异受到年龄(β = 0.012)和地区的调节。特别是欧洲(Hedges' g = 0.419)和南美洲(Hedges' g = 0.420)的患者, 以及在爱荷华赌博任务(Hedges' g = 0.396)和剑桥赌博任务(Hedges' g = 0.220)中的患者, 均比健康个体更偏好风险寻求; 而在日常态度和行为中, 该差异仅受到心境阶段的调节, <轻>躁狂期患者(Hedges' g = 0.747)比健康个体更偏好风险寻求。本研究首次通过多种风险决策偏好测量类型探讨双相障碍与风险决策的关系, 得出了较稳定的结果, 并提出未来研究应充分考虑心境阶段、任务类型等因素的影响, 深入挖掘双相障碍影响风险决策的心理机制, 为双相障碍的临床管理和心理教育提供参考。

关键词: 双相障碍, 风险决策, 元分析, 决策范式, 跨心境特异性

Abstract:

Bipolar disorder (BD), one of six major mental disorders in China, manifests as recurrent episodes of (hypo)mania and major depression. Recently, researchers have increasingly focused on the cognitive and behavioral characteristics of BD patients. Notably, increased risk-taking might emerge as a typical symptom of BD, supported by evidence from BD patients' daily behaviors, empirical research, and neuroimaging studies. However, contradictory findings have been reported, with some studies failing to find differences in risk preferences between BD patients and healthy controls (HCs) and a few studies even indicating increased risk aversion among BD patients. Consequently, whether and to what extent BD is associated with alterations in risk preference remain unclear. Thus, this study involved a three-level meta-analysis to examine the relationship between BD and risky decision-making, encompassing studies utilizing various measures of risky decision-making (i.e., risk attitude scales, behavioral tasks, and daily risk behaviors). Moreover, we aimed to uncover potential moderators, including sample and measurement characteristics, to better address inconsistent findings.
A systematic literature search was conducted with the Web of Science, PubMed, Scopus, PsycINFO, CNKI (China National Knowledge Infrastructure), and WFD (Wan Fang Data) databases up to April 15, 2024, to identify studies investigating risky decision-making in BD patients and HCs. We calculated the standard mean differences (Hedges' g) in risky decision-making between BD patients and HCs. We conducted a three-level random-effects meta-analysis, including heterogeneity analysis, moderation analyses for sample and measurement characteristics, and assessments of publication bias.
Across 176 effect sizes in 71 cross-sectional studies, BD patients exhibited greater risk-seeking than HCs (Hedges' g = 0.301), regardless of whether it was measured via risk attitude scales (Hedges' g = 0.624), behavioral tasks (Hedges' g = 0.252) or daily risk behaviors (Hedges' g = 0.312). Moreover, this difference was also moderated by age (β = 0.009) and mood phase, where BD patients in any mood phase preferred more risk-seeking than HCs (euthymic: Hedges' g = 0.245; (hypo)mania: Hedges' g = 0.604; major depression: Hedges' g = 0.417). For behavioral tasks, age (β = 0.012) and region were found to have significant moderating effects. Specifically, significant effect sizes were observed for samples originating from Europe (Hedges' g = 0.419) and South America (Hedges' g = 0.420). Moreover, effect sizes were significant in studies using the Iowa Gambling Task (IGT; Hedges' g = 0.396) and Cambridge Gambling Task (Hedges' g = 0.220), and effect sizes in IGT studies were larger than in those employing the Classic Risky Choice Tasks. Regarding. With respect to daily attitudes/behaviors, mood phase was identified as a significant moderator. Notably, effect sizes for (hypo)manic patients (Hedges' g = 0.747) were significantly larger than those for euthymic patients. Moreover, compared with HCs, BD patients exhibited increased risk-seeking across the health (Hedges' g = 0.308), financial (Hedges' g = 0.331), and overall attitude (Hedges' g = 0.733) domains.
This study comprehensively explored the relationship between BD and risky decision-making via various measures, revealing a consistent pattern of increased risk-seeking among BD patients. These findings suggest that increased risk-taking might be a noteworthy symptom of BD and propose potential utility for its application in clinical management and psychoeducation. Furthermore, future studies should consider factors such as mood phase and task type and try to uncover the underlying psychological mechanisms through which BD affects risky decision-making.

Key words: Bipolar disorder, risky decision-making, meta-analysis, decision task, cross-mood specificity

中图分类号:

陆嘉琦, 李雨斯, 何贵兵. (2025). 双相障碍患者的风险决策偏好：来自三水平元分析的证据. 心理学报, 57(1), 100-124.

LU Jiaqi, LI Yusi, HE Guibing. (2025). Risky decision-making in bipolar disorder: Evidence from a three-level meta-analysis. Acta Psychologica Sinica, 57(1), 100-124.

图/表 15

参考文献 171

	*标记为纳入元分析的文献
[1]	^* Adida, M., Clark, L., Pomietto, P., Kaladjian, A., Besnier, N., Azorin, J. M., Jeanningros, R., & Goodwin, G. M. (2008). Lack of insight may predict impaired decision making in manic patients. Bipolar Disorders, 10(7), 829-837. https://doi.org/10.1111/j.1399-5618.2008.00618.x doi: 10.1111/j.1399-5618.2008.00618.x URL pmid: 19032715
[2]	^* Adida, M., Jollant, F., Clark, L., Besnier, N., Guillaume, S., Kaladjian, A., ... Courtet, P. (2011). Trait-related decision-making impairment in the three phases of bipolar disorder. Biological Psychiatry, 70(4), 357-365. https://doi.org/10.1016/j.biopsych.2011.01.018 doi: 10.1016/j.biopsych.2011.01.018 URL pmid: 21429477
[3]	American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.) (5th ed.). Arlington, VA: American Psychiatric Publishing. https://doi.org/10.1176/appi.books.9780890425596
[4]	Amlung, M., Marsden, E., Holshausen, K., Morris, V., Patel, H., Vedelago, L., ... McCabe, R. E. (2019). Delay discounting as a transdiagnostic process in psychiatric disorders: A meta-analysis. JAMA Psychiatry, 76(11), 1176-1186. https://doi.org/10.1001/jamapsychiatry.2019.2102
[5]	^* Anderson, Z., Fairley, K., Villanueva, C. M., Carter, R. M., & Gruber, J. (2021). No group differences in traditional economics measures of loss aversion and framing effects in bipolar i disorder. Plos One, 16(11), e0258360. https://doi.org/10.1371/journal.pone.0258360
[6]	Arria, A. M., Caldeira, K. M., Allen, H. K., Bugbee, B. A., Vincent, K. B., & O'Grady, K. E. (2017). Prevalence and incidence of drug use among college students: An 8-year longitudinal analysis. The American Journal of Drug and Alcohol Abuse, 43(6), 711-718. https://doi.org/10.1080/00952990.2017.1310219
[7]	Arts, B., Jabben, N. E. J. G., Krabbendam, L., & van Os, J. (2011). A 2-year naturalistic study on cognitive functioning in bipolar disorder. Acta Psychiatrica Scandinavica, 123(3), 190-205. https://doi.org/10.1111/j.1600-0447.2010.01601.x doi: 10.1111/j.1600-0447.2010.01601.x URL pmid: 20846251
[8]	Assink, M., & Wibbelink, C. J. M. (2016). Fitting three-level meta-analytic models in R: A step-by-step tutorial. The Quantitative Methods for Psychology, 12(3), 154-174. https://doi.org/10.20982/tqmp.12.3.p154
[9]	^* Ayidaga, T., Ozel-Kizil, E.T., Çolak, B., & Akman-Ayidaga, E. (2022). Detailed analysis of risk-taking in association with impulsivity and aggression in euthymic patients with bipolar disorder type I. Journal of Cognitive Psychology, 34(7), 917-929. https://doi.org/10.1080/20445911.2022. 2098303
[10]	Azorin, J. M., Belzeaux, R., Kaladjian, A., Adida, M., Hantouche, E., Lancrenon, S., & Fakra, E. (2013). Risks associated with gender differences in bipolar I disorder. Journal of Affective Disorders, 151(3), 1033-1040. https://doi.org/10.1016/j.jad.2013.08.031
[11]	^* Bauer, I. E., Diniz, B. S., Meyer, T. D., Teixeira, A. L., Sanches, M., Spiker, D., Zunta-Soares, G., & Soares, J. C. (2018). Increased reward-oriented impulsivity in older bipolar patients: A preliminary study. Journal of Affective Disorders, 225, 585-592. https://doi.org/10.1016/j.jad.2017.08.067 doi: S0165-0327(17)30861-3 URL pmid: 28886499
[12]	^* Bauer, I. E., Meyer, T. D., Sanches, M., Spiker, D., Zunta-Soares, G., & Soares, J. C. (2017). Are self-rated and behavioural measures of impulsivity in bipolar disorder mainly related to comorbid substance use problems? Cognitive Neuropsychiatry, 22(4), 298-314. https://doi.org/10.1080/13546805.2017.1324951 doi: 10.1080/13546805.2017.1324951 URL pmid: 28490234
[13]	Benazzi, F. (2003). The role of gender in depressive mixed state. Psychopathology, 36(4), 213-217. https://doi.org/10.1159/000072792 URL pmid: 14504456
[14]	Birmaher, B. (2013). Bipolar disorder in children and adolescents. Child and Adolescent Mental Health, 18(3), 140-148. https://doi.org/10.1111/camh.12021 doi: 10.1111/camh.12021 URL pmid: 24273457
[15]	Blais, A. -R., & Weber, E. U. (2006). A Domain-Specific Risk-Taking (DOSPERT) scale for adult populations. Judgment and Decision Making, 1(1), 33-47. https://doi.org/10.1017/s1930297500000334
[16]	Blankenstein, N. E., Peper, J. S., Crone, E. A., & van Duijvenvoorde, A. C. K. (2017). Neural mechanisms underlying risk and ambiguity attitudes. Journal of Cognitive Neuroscience, 29(11), 1845-1859. https://doi.org/10.1162/jocn_a_01162 doi: 10.1162/jocn_a_01162 URL pmid: 28686139
[17]	^* Bodur, B., Doğanavşargil Baysal, G. Ö., & Erdoğan, A. (2023). Comparison of behavioral addictions between euthymic bipolar disorder patients and healthy volunteers. Neuropsychiatric Investigation, 6(1), 1-5. https://doi.org/10.5152/NeuropsychiatricInvest.2023.22028
[18]	Bolton, S., Warner, J., Harriss, E., Geddes, J., & Saunders, K. E. A. (2021). Bipolar disorder: Trimodal age-at-onset distribution. Bipolar Disorders, 23(4), 341-356. https://doi.org/10.1111/bdi.13016 doi: 10.1111/bdi.13016 URL pmid: 33030292
[19]	Bora, E., Yucel, M., & Pantelis, C. (2009). Cognitive endophenotypes of bipolar disorder: A meta-analysis of neuropsychological deficits in euthymic patients and their first-degree relatives. Journal of Affective Disorders, 113(1-2), 1-20. https://doi.org/10.1016/j.jad.2008.06.009 doi: 10.1016/j.jad.2008.06.009 URL pmid: 18684514
[20]	Braddock, K. H., Dillard, J. P., Voigt, D. C., Stephenson, M. T., Sopory, P., & Anderson, J. W. (2011). Impulsivity partially mediates the relationship between BIS/BAS and risky health behaviors. Journal of Personality, 79(4), 793-810. https://doi.org/10.1111/j.1467-6494.2011.00699.x doi: 10.1111/j.1467-6494.2011.00699.x URL pmid: 21682726
[21]	Bragazzi, N. L., Beamish, D., Kong, J. D., & Wu, J. (2021). Illicit drug use in Canada and implications for suicidal behaviors, and household food insecurity: Findings from a large, nationally representative survey. International Journal of Environmental Research and Public Health, 18(12), 6425. https://doi.org/10.3390/ijerph18126425
[22]	Brainerd, C. J., & Reyna, V. F. (1990). Gist is the grist: Fuzzy-trace theory and the new intuitionism. Developmental Review, 10(1), 3-47. https://doi.org/10.1016/0273-2297(90)90003-M
[23]	^* Brambilla, P., Perlini, C., Bellani, M., Tomelleri, L., Ferro, A., Cerruti, S., ... Frangou, S. (2013). Increased salience of gains versus decreased associative learning differentiate bipolar disorder from schizophrenia during incentive decision making. Psychological Medicine, 43(3), 571-580. https://doi.org/10.1017/S0033291712001304 doi: 10.1017/S0033291712001304 URL pmid: 22687364
[24]	Brener, N. D., Kann, L., Kinchen, S. A., Grunbaum, J. A., Whalen, L., Eaton, D., Hawkins, J., & Ross, J. G. (2004). Methodology of the youth risk behavior surveillance system. MMWR. Recommendations and reports: Morbidity and mortality weekly report. Recommendations and Reports, 53(RR-12), 1-13.
[25]	Buelow, M. T., & Blaine, A. L. (2015). The assessment of risky decision making: A factor analysis of performance on the Iowa Gambling Task, Balloon Analogue Risk Task, and Columbia Card Task. Psychological Assessment, 27(3), 777-785. https://doi.org/10.1037/a0038622 doi: 10.1037/a0038622 URL pmid: 25580611
[26]	Butler, S., Rosman, A., Seleski, S., Garcia, M., Lee, S., Barnes, J., & Schwartz, A. (2012). A medical risk attitude subscale for DOSPERT. Judgment and Decision Making, 7(2), 189-195. https://doi.org/10.1017/s1930297500003028
[27]	Byrnes, J. P., Miller, D. C., & Schafer, W. D. (1999). Gender differences in risk taking: A meta-analysis. Psychological Bulletin, 125(3), 367-383. https://doi.org/10.1037/0033-2909.125.3.367
[28]	Cai, H. D., Zhang, Q., Cai, Q., & Chen, Q. R. (2012). Iowa Game Task and cognitive neural mechanisms on decision-making. Advances in Psychological Science, 20(9), 1401-1410. https://doi.org/10.3724/SP.J.1042.2012.0140
	[蔡厚德, 张权, 蔡琦, 陈庆荣. (2012). 爱荷华博弈任务(IGT)与决策的认知神经机制. 心理科学进展, 20(9), 1401-1410. https://doi.org/10.3724/SP.J.1042.2012.0140] doi: 10.3724/SP.J.1042.2012.01401 URL
[29]	^* Caletti, E., Paoli, R. A., Fiorentini, A., Cigliobianco, M., Zugno, E., Serati, M., ... Altamura, A. C. (2013). Neuropsychology, social cognition and global functioning among bipolar, schizophrenic patients and healthy controls: Preliminary data. Frontiers in Human Neuroscience, 7, 661. https://doi.org/10.3389/fnhum.2013.00661 doi: 10.3389/fnhum.2013.00661 URL pmid: 24146642
[30]	Chan, E. Y., & Saqib, N. U. (2021). The moderating role of processing style in risk perceptions and risky decision making. Journal of Behavioral Decision Making, 34(2), 290-299. https://doi.org/10.1002/bdm.2210
[31]	Charness, G., & Gneezy, U. (2012). Strong evidence for gender differences in risk taking. Journal of Economic Behavior and Organization, 83(1), 50-58. https://doi.org/10.1016/j.jebo.2011.06.007
[32]	Chen, X. J., Ba, L., & Kwak, Y. (2020). Neurocognitive underpinnings of cross-cultural differences in risky decision making. Social Cognitive and Affective Neuroscience, 15(6), 671-680. https://doi.org/10.1093/scan/nsaa078
[33]	Cheung, M. W. L. (2014). Modeling dependent effect sizes with three-level meta-analyses: A structural equation modeling approach. Psychological Methods, 19(2), 211-229. https://doi.org/10.1037/a0032968 doi: 10.1037/a0032968 URL pmid: 23834422
[34]	^* Clark, L., Iversen, S. D., & Goodwin, G. M. (2001). A neuropsychological investigation of prefrontal cortex involvement in acute mania. American Journal of Psychiatry, 158(10), 1605-1611. https://doi.org/10.1176/appi.ajp.158.10.1605 URL pmid: 11578991
[35]	Collett, J. (2016). It's not all about that bas: Trait bipolar disorder vulnerability weakly correlated with trait bas and not predictive of risky decision-making [Unpublished doctoral dissertation]. Swinburne University of Technology.
[36]	Croson, R., & Gneezy, U. (2009). Gender differences in preferences. Journal of Economic Literature, 47(2), 448-474. https://doi.org/10.1257/jel.47.2.448
[37]	Cullen, B., Ward, J., Graham, N. A., Deary, I. J., Pell, J. P., Smith, D. J., & Evans, J. J. (2016). Prevalence and correlates of cognitive impairment in euthymic adults with bipolar disorder: A systematic review. Journal of Affective Disorders, 205, 165-181. https://doi.org/10.1016/j.jad.2016.06.063 doi: S0165-0327(16)30753-4 URL pmid: 27449549
[38]	da Silva, J., Gonçalves-Pereira, M., Xavier, M., & Mukaetova-Ladinska, E. B. (2013). Affective disorders and risk of developing dementia: Systematic review. The British Journal of Psychiatry, 202(3), 177-186. https://doi.org/10.1192/bjp.bp.111.101931
[39]	Defoe, I. N., Dubas, J. S., Figner, B., & van Aken, M. A. (2015). A meta-analysis on age differences in risky decision making: Adolescents versus children and adults. Psychological Bulletin, 141(1), 48-84. https://doi.org/10.1037/a0038088 doi: 10.1037/a0038088 URL pmid: 25365761
[40]	Dekkers, T. J., Popma, A., van Rentergem, J. A. A., Bexkens, A., & Huizenga, H. M. (2016). Risky decision making in Attention-Deficit/Hyperactivity Disorder: A meta-regression analysis. Clinical Psychology Review, 45, 1-16. https://doi.org/10.1016/j.cpr.2016.03.001 doi: 10.1016/j.cpr.2016.03.001 URL pmid: 26978323
[41]	^* de Moraes, P. H. P., Neves, F. S., Vasconcelos, A. G., Lima, I. M. M., Brancaglion, M., Sedyiama, C. Y., ... Malloy-Diniz, L. F. (2013). Relationship between neuropsychological and clinical aspects and suicide attempts in euthymic bipolar patients. Psicologia: Reflexao e Critica, 26(1), 160-167. https://doi.org/10.1590/S0102-79722013000100017
[42]	^* Dickerson, F., Schroeder, J., Katsafanas, E., Khushalani, S., Origoni, A. E., Savage, C., ... Yolken, R. H. (2018). Cigarette smoking by patients with serious mental illness, 1999-2016: An increasing disparity. Psychiatric Services, 69(2), 147-153. https://doi.org/10.1176/appi.ps.201700118 doi: 10.1176/appi.ps.201700118 URL pmid: 28945183
[43]	^* Dickerson, F., Stallings, C. R., Origoni, A. E., Vaughan, C., Khushalani, S., Schroeder, J., & Yolken, R. H. (2013). Cigarette smoking among persons with schizophrenia or bipolar disorder in routine clinical settings, 1999-2011. Psychiatric Services, 64(1), 44-50. https://doi.org/10.1176/appi.ps.201200143 doi: 10.1176/appi.ps.201200143 URL pmid: 23280457
[44]	^* Di Nicola, M., Tedeschi, D., Mazza, M., Martinotti, G., Harnic, D., Catalano, V., ... Janiri, L. (2010). Behavioural addictions in bipolar disorder patients: Role of impulsivity and personality dimensions. Journal of Affective Disorders, 125(1-3), 82-88. https://doi.org/10.1016/j.jad.2009.12.016 doi: 10.1016/j.jad.2009.12.016 URL pmid: 20083309
[45]	Diniz, B. S., Teixeira, A. L., Cao, F., Gildengers, A., Soares, J. C., Butters, M. A., & Reynolds III, C. F. (2017). History of bipolar disorder and the risk of dementia: A systematic review and meta-analysis. The American Journal of Geriatric Psychiatry, 25(4), 357-362. https://doi.org/10.1016/j.jagp.2016.11.014 doi: S1064-7481(16)30308-6 URL pmid: 28161155
[46]	Dir, A. L., Coskunpinar, A., & Cyders, M. A. (2014). A meta-analytic review of the relationship between adolescent risky sexual behavior and impulsivity across gender, age, and race. Clinical Psychology Review, 34(7), 551-562. https://doi.org/10.1016/j.cpr.2014.08.004 doi: 10.1016/j.cpr.2014.08.004 URL pmid: 25261740
[47]	Du, W., Green, L., & Myerson, J. (2002). Cross-cultural comparisons of discounting delayed and probabilistic rewards. Psychological Record, 52(4), 479-492. https://doi.org/10.1007/BF03395199
[48]	Duffy, A. (2009). The early course of bipolar disorder in youth at familial risk. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 18(3), 200-205. pmid: 19718420
[49]	Duval, S., & Tweedie, R. (2000). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56(2), 455-463. https://doi.org/10.1111/j.0006-341X.2000.00455.x doi: 10.1111/j.0006-341x.2000.00455.x URL pmid: 10877304
[50]	^* Edge, M. D., Johnson, S. L., Ng, T., & Carver, C. S. (2013). Iowa gambling task performance in euthymic bipolar I disorder: A meta-analysis and empirical study. Journal of Affective Disorders, 150(1), 115-122. https://doi.org/10.1016/j.jad.2012.11.027 doi: 10.1016/j.jad.2012.11.027 URL pmid: 23219060
[51]	^* Ernst, M., Dickstein, D. P., Munson, S., Eshel, N., Pradella, A., Jazbec, S., Pine, D. S., & Leibenluft, E. (2004). Reward-related processes in pediatric bipolar disorder: A pilot study. Journal of Affective Disorders, 82, S89-S101. https://doi.org/10.1016/j.jad.2004.05.022
[52]	Fernandes, A. C., & Garcia-Marques, T. (2020). A meta- analytical review of the familiarity temporal effect: Testing assumptions of the attentional and the fluency-attributional accounts. Psychological Bulletin, 146(3), 187-217. https://doi.org/10.1037/bul0000222
[53]	Fischhoff, B., & Broomell, S. B. (2020). Judgment and decision making. Annual Review of Psychology, 71(1), 331-355. https://doi.org/10.1146/annurev-psych-010419-050747
[54]	^* Fletcher, K., Parker, G. B., & Manicavasagar, V. (2013). Coping profiles in bipolar disorder. Comprehensive Psychiatry, 54(8), 1177-1184. https://doi.org/10.1016/j.comppsych.2013.05.011 doi: 10.1016/j.comppsych.2013.05.011 URL pmid: 23810079
[55]	^* Frangou, S., Kington, J., Raymont, V., & Shergill, S. S. (2008). Examining ventral and dorsal prefrontal function in bipolar disorder: A functional magnetic resonance imaging study. European Psychiatry, 23(4), 300-308. https://doi.org/10.1016/j.eurpsy.2007.05.002 URL pmid: 17656073
[56]	Frey, R., Pedroni, A., Mata, R., Rieskamp, J., & Hertwig, R. (2017). Risk preference shares the psychometric structure of major psychological traits. Science Advances, 3(10), e1701381. https://doi.org/10.1126/sciadv.1701381
[57]	Gao, S., Assink, M., Cipriani, A., & Lin, K. (2017). Associations between rejection sensitivity and mental health outcomes: A meta-analytic review. Clinical Psychology Review, 57, 59-74. https://doi.org/10.1016/j.cpr.2017.08.007 doi: S0272-7358(17)30122-8 URL pmid: 28841457
[58]	Gelfand, M. J., Raver, J. L., Nishii, L., Leslie, L. M., Lun, J., Lim, B. C., … Yamaguchi, S. (2011). Differences between tight and loose cultures: A 33-nation study. Science, 332(6033), 1100-1104. https://doi.org/10.1126/science.1197754 doi: 10.1126/science.1197754 URL pmid: 21617077
[59]	^* Goldberg, J. F., Wenze, S. J., Welker, T. M., Steer, R. A., & Beck, A. T. (2005). Content‐specificity of dysfunctional cognitions for patients with bipolar mania versus unipolar depression: A preliminary study. Bipolar Disorders, 7(1), 49-56. https://doi.org/10.1111/j.1399-5618.2004.00165.x URL pmid: 15654932
[60]	^* Gomide Vasconcelos, A., Sergeant, J., Corrêa, H., Mattos, P., & Malloy-Diniz, L. (2014). When self-report diverges from performance: The usage of BIS-11 along with neuropsychological tests. Psychiatry Research, 218(1-2), 236-243. https://doi.org/10.1016/j.psychres.2014.03.002 doi: 10.1016/j.psychres.2014.03.002 URL pmid: 24726025
[61]	^* Gu, Y. T., Zhou, C., Yang, J., Zhang, Q., Zhu, G. H., Sun, L., Ge, M. H., & Wang, Y. Y. (2020). A transdiagnostic comparison of affective decision‐making in patients with schizophrenia, major depressive disorder, or bipolar disorder. PsyCh Journal, 9(2), 199-209. https://doi.org/10.1002/pchj.351
[62]	^* Haatveit, B., Westlye, L. T., Vaskinn, A., Flaaten, C. B., Mohn, C., Bjella, T., ... Ueland, T. (2023). Intra- and inter-individual cognitive variability in schizophrenia and bipolar spectrum disorder: An investigation across multiple cognitive domains. Schizophrenia, 9(1), 89. https://doi.org/10.1038/s41537-023-00414-4 doi: 10.1038/s41537-023-00414-4 URL pmid: 38110366
[63]	^* Hariri, A. G., Karadag, F., Gokalp, P., & Essizoglu, A. (2011). Risky sexual behavior among patients in Turkey with bipolar disorder, schizophrenia, and heroin addiction. The Journal of Sexual Medicine, 8(8), 2284-2291. https://doi.org/10.1111/j.1743-6109.2011.02282.x doi: 10.1111/j.1743-6109.2011.02282.x URL pmid: 21492406
[64]	^* Hart, K. L., Brown, H. E., Roffman, J. L., & Perlis, R. H. (2019). Risk tolerance measured by probability discounting among individuals with primary mood and psychotic disorders. Neuropsychology, 33(3), 417-424. https://doi.org/10.1037/neu0000506 doi: 10.1037/neu0000506 URL pmid: 30688494
[65]	Hartshorne, J. K., & Germine, L. T. (2015). When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span. Psychological Science, 26(4), 433-443. https://doi.org/10.1177/0956797614567339 doi: 10.1177/0956797614567339 URL pmid: 25770099
[66]	Hershenberg, R., Satterthwaite, T. D., Daldal, A., Katchmar, N., Moore, T. M., Kable, J. W., & Wolf, D. H. (2016). Diminished effort on a progressive ratio task in both unipolar and bipolar depression. Journal of Affective Disorders, 196, 97-100. https://doi.org/10.1016/j.jad.2016.02.003 doi: 10.1016/j.jad.2016.02.003 URL pmid: 26919058
[67]	Hertwig, R., Barron, G., Weber, E. U., & Erev, I. (2004). Decisions from experience and the effect of rare events in risky choice. Psychological Science, 15(8), 534-539. https://doi.org/10.1111/j.0956-7976.2004.00715.x doi: 10.1111/j.0956-7976.2004.00715.x URL pmid: 15270998
[68]	^* Hıdıroğlu, C., Esen, Ö. D., Tunca, Z., Yalçìn, Ş. N. G., Lombardo, L., Glahn, D. C., & Özerdem, A. (2013). Can risk-taking be an endophenotype for bipolar disorder? A study on patients with bipolar disorder type I and their first-degree relatives. Journal of the International Neuropsychological Society, 19(4), 474-482. https://doi.org/10.1017/S1355617713000015
[69]	^* Holmes, M. K., Bearden, C. E., Barguil, M., Fonseca, M., Monkul, E. S., Nery, F. G., … Glahn, D. C. (2009). Conceptualizing impulsivity and risk taking in bipolar disorder: Importance of history of alcohol abuse. Bipolar Disorders, 11(1), 33-40. https://doi.org/10.1111/j.1399-5618.2008.00657.x doi: 10.1111/j.1399-5618.2008.00657.x URL pmid: 19133964
[70]	Hosker-Field, A. M., Molnar, D. S., & Book, A. S. (2016). Psychopathy and risk taking: Examining the role of risk perception. Personality and Individual Differences, 91, 123-132. https://doi.org/10.1016/j.paid.2015.11.059
[71]	Hox, J. J., Moerbeek, M., & van de Schoot, R. (2010). Multilevel analysis: Techniques and applications. Routledge.
[72]	Hsee, C., & Weber, E. U. (1999). Cross-national differences in risk preference and lay predictions. Journal of Behavioral Decision Making, 12(2), 165-179. https://doi.org/10.1002/(SICI)1099-0771(199906)12:2＜165::AID-BDM316＞3.0.CO;2-N
[73]	Huang, Y., Wang, Y., Wang, H., Liu, Z., Yu, X., Yan, J., … Wu, Y. (2019). Prevalence of mental disorders in China: A cross-sectional epidemiological study. The Lancet Psychiatry, 6(3), 211-224. https://doi.org/10.1016/S2215-0366(18)30511-X
[74]	^* Ibanez, A., Cetkovich, M., Petroni, A., Urquina, H., Baez, S., Gonzalez-Gadea, M. L., ... Manes, F. (2012). The neural basis of decision-making and reward processing in adults with euthymic bipolar disorder or attention-deficit/ hyperactivity disorder (ADHD). PloS One, 7(5), e37306. https://doi.org/10.1371/journal.pone.0037306
[75]	Isen, A. M., & Patrick, R. (1983). The effect of positive feelings on risk taking: When the chips are down. Organizational Behavior and Human Performance, 31(2), 194-202. https://doi.org/10.1016/0030-5073(83)90120-4
[76]	Ji, C. Y. (2007). Adolescent health risk behavior. Chinese Journal of School Health, 28(4), 289-291.
	[季成叶. (2007). 青少年健康危险行为. 中国学校卫生, 28(4), 289-291.]
[77]	^* Ji, S., Ma, H., Yao, M., Guo, M., Li, S., Chen, N., ... Hu, B. (2021). Aberrant temporal variability in brain regions during risk decision making in patients with bipolar I disorder: A dynamic effective connectivity study. Neuroscience, 469, 68-78. https://doi.org/10.1016/j.neuroscience.2021.06.024 doi: 10.1016/j.neuroscience.2021.06.024 URL pmid: 34153355
[78]	Jia, Z., Jin, Y., Zhang, L., Wang, Z., & Lu, Z. (2018). Prevalence of drug use among students in mainland China: A systematic review and meta-analysis for 2003-2013. Drug and Alcohol Dependence, 186, 201-206. https://doi.org/10.1016/j.drugalcdep.2017.12.047
[79]	^* Jogia, J., Dima, D., Kumari, V., & Frangou, S. (2012). Frontopolar cortical inefficiency may underpin reward and working memory dysfunction in bipolar disorder. The World Journal of Biological Psychiatry, 13(8), 605-615. https://doi.org/10.3109/15622975.2011.585662
[80]	John, A., Patel, U., Rusted, J., Richards, M., & Gaysina, D. (2019). Affective problems and decline in cognitive state in older adults: A systematic review and meta-analysis. Psychological Medicine, 49(3), 353-365. https://doi.org/10.1017/S0033291718001137 doi: 10.1017/S0033291718001137 URL pmid: 29792244
[81]	Johnson, E. J., & Tversky, A. (1983). Affect, generalization, and the perception of risk. Journal of Personality and Social Psychology, 45(1), 20-31. https://doi.org/10.1037/0022-3514.45.1.20
[82]	Josef, A. K., Richter, D., Samanez-Larkin, G. R., Wagner, G. G., Hertwig, R., & Mata, R. (2016). Stability and change in risk-taking propensity across the adult life span. Journal of Personality and Social Psychology, 111(3), 430-450. https://doi.org/10.1037/pspp0000090 doi: 10.1037/pspp0000090 URL pmid: 26820061
[83]	Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-292. https://doi.org/10.2307/1914185
[84]	Kandel, D. B., Adler, I., & Sudit, M. (1981). The epidemiology of adolescent drug use in France and Israel. American Journal of Public Health, 71(3), 256-265. https://doi.org/10.2105/ajph.71.3.256 URL pmid: 7468857
[85]	Kathawalla, U., & Syed, M. (2021). Discrimination, life stress, and mental health among Muslims: A preregistered systematic review and meta-analysis. Collabra: Psychology, 7(1), 28248. https://doi.org/10.1525/collabra.28248
[86]	Katz, B. A., Naftalovich, H., Matanky, K., & Yovel, I. (2021). The dual-system theory of bipolar spectrum disorders: A meta-analysis. Clinical Psychology Review, 83, 101945. https://doi.org/10.1016/j.cpr.2020.101945
[87]	Kepes, S., & Thomas, M. A. (2018). Assessing the robustness of meta-analytic results in information systems: Publication bias and outliers. European Journal of Information Systems, 27(1), 90-123. https://doi.org/10.1080/0960085X.2017.1390188
[88]	^* Kollmann, B., Scholz, V., Linke, J., Kirsch, P., & Wessa, M. (2017). Reward anticipation revisited- evidence from an fMRI study in euthymic bipolar I patients and healthy first-degree relatives. Journal of Affective Disorders, 219, 178-186. https://doi.org/10.1016/j.jad.2017.04.044 doi: S0165-0327(16)31671-8 URL pmid: 28558365
[89]	^* Kollmann, B., Yuen, K., Scholz, V., & Wessa, M. (2019). Cognitive variability in bipolar I disorder: A cluster- analytic approach informed by resting-state data. Neuropharmacology, 156, 107585. https://doi.org/10.1016/j.neuropharm.2019.03.028
[90]	Krantz, M., Goldstein, T., Rooks, B., Merranko, J., Liao, F., Gill, M. K., ... Birmaher, B. (2018). Sexual risk behavior among youth with bipolar disorder: Identifying demographic and clinical risk factors. Journal of the American Academy of Child and Adolescent Psychiatry, 57(2), 118-124. https://doi.org/10.1016/j.jaac.2017.11.015 doi: S0890-8567(17)31865-8 URL pmid: 29413144
[91]	^* Lamy, M. (2009). Neural correlates of impulsivity and risk taking in bipolar disorder [Unpublished doctoral dissertation]. University of Cincinnati.
[92]	Lapomarda, G., Pappaianni, E., Siugzdaite, R., Sanfey, A. G., Rumiati, R. I., & Grecucci, A. (2021). Out of control: An altered parieto-occipital-cerebellar network for impulsivity in bipolar disorder. Behavioural Brain Research, 406, 113228. https://doi.org/10.1016/j.bbr.2021.113228 doi: 10.1016/j.bbr.2021.113228 URL pmid: 33684426
[93]	Lasagna, C. A., Pleskac, T. J., Burton, C. Z., McInnis, M. G., Taylor, S. F., & Tso, I. F. (2022). Mathematical modeling of risk-taking in bipolar disorder: Evidence of reduced behavioral consistency, with altered loss aversion specific to those with history of substance use disorder. Computational Psychiatry, 6(1), 96-116. https://doi.org/10.5334/cpsy.61
[94]	^* Le, V., Kirsch, D. E., Tretyak, V., Weber, W., Strakowski, S. M., & Lippard, E. T. C. (2021). Recent perceived stress, amygdala reactivity to acute psychosocial stress, and alcohol and cannabis use in adolescents and young adults with bipolar disorder. Frontiers in Psychiatry, 12, 767309. https://doi.org/10.3389/fpsyt.2021.767309
[95]	Lejuez, C. W., Read, J. P., Kahler, C. W., Richards, J. B., Ramsey, S. E., Stuart, G. L., Strong, D. R., & Brown, R. A. (2002). Evaluation of a behavioral measure of risk taking: The Balloon Analogue Risk Task (BART). Journal of Experimental Psychology: Applied, 8(2), 75-84. https://doi.org/10.1037//1076-898x.8.2.75
[96]	^* Levy, B. (2013). Autonomic nervous system arousal and cognitive functioning in bipolar disorder. Bipolar Disorders, 15(1), 70-79. https://doi.org/10.1111/bdi.12028 doi: 10.1111/bdi.12028 URL pmid: 23237079
[97]	Lewandowski, K. E., Sperry, S. H., Malloy, M. C., & Forester, B. P. (2014). Age as a predictor of cognitive decline in bipolar disorder. The American Journal of Geriatric Psychiatry, 22(12), 1462-1468. https://doi.org/10.1016/j.jagp.2013.10.002 doi: 10.1016/j.jagp.2013.10.002 URL pmid: 24262287
[98]	^* Linke, J., King, A. V., Poupon, C., Hennerici, M. G., Gass, A., & Wessa, M. (2013). Impaired anatomical connectivity and related executive functions: Differentiating vulnerability and disease marker in bipolar disorder. Biological Psychiatry, 74(12), 908-916. https://doi.org/10.1016/j.biopsych.2013.04.010 doi: 10.1016/j.biopsych.2013.04.010 URL pmid: 23684382
[99]	^* Lippard, E. T. C., Kirsch, D. E., Kosted, R., Le, V., Almeida, J. R. C., Fromme, K., & Strakowski, S. M. (2023). Subjective response to alcohol in young adults with bipolar disorder and recent alcohol use: A within-subject randomized placebo-controlled alcohol administration study. Psychopharmacology, 240(4), 739-753. https://doi.org/10.1007/s00213-023-06315-9 doi: 10.1007/s00213-023-06315-9 URL pmid: 36695842
[100]	Lu, J., Zhao, X., Wei, X., & He, G. (2024). Risky decision- making in major depressive disorder: A three-level meta- analysis. International Journal of Clinical and Health Psychology, 24(1), 100417. https://doi.org/10.1016/j.ijchp.2023.100417
[101]	Lukacs, J. N., Sicilia, A. C., Jones, S., & Algorta, G. P. (2021). Interactions and implications of Fuzzy-trace theory for risk taking behaviors in bipolar disorder. Journal of Affective Disorders, 293, 305-313. https://doi.org/10.1016/j.jad.2021.06.035 doi: 10.1016/j.jad.2021.06.035 URL pmid: 34229283
[102]	Lüdecke, D. (2019). ESC: Effect size computation for meta analysis (Version 0.5.1). https://CRAN.R-project.org/package=esc.
[103]	^* Malloy-Diniz, L. F., Neves, F. S., Abrantes, S. S. C., Fuentes, D., & Corrêa, H. (2009). Suicide behavior and neuropsychological assessment of type I bipolar patients. Journal of Affective Disorders, 112(1-3), 231-236. https://doi.org/10.1016/j.jad.2008.03.019 doi: 10.1016/j.jad.2008.03.019 URL pmid: 18485487
[104]	^* Malloy-Diniz, L. F., Neves, F. S., de Moraes, P. H. P., De Marco, L. A., Romano-Silva, M. A., Krebs, M. O., & Corrêa, H. (2011). The 5-HTTLPR polymorphism, impulsivity and suicide behavior in euthymic bipolar patients. Journal of Affective Disorders, 133(1-2), 221-226. https://doi.org/10.1016/j.jad.2011.03.051 doi: 10.1016/j.jad.2011.03.051 URL pmid: 21550122
[105]	Mann-Wrobel, M. C., Carreno, J. T., & Dickinson, D. (2011). Meta-analysis of neuropsychological functioning in euthymic bipolar disorder: An update and investigation of moderator variables. Bipolar Disorders, 13(4), 334-342. https://doi.org/10.1111/j.1399-5618.2011.00935.x doi: 10.1111/j.1399-5618.2011.00935.x URL pmid: 21843273
[106]	^* Marengo, E., Martino, D. J., Igoa, A., Fassi, G., Scápola, M., Baamonde, M. U., & Strejilevich, S. A. (2015). Sexual risk behaviors among women with bipolar disorder. Psychiatry Research, 230(3), 835-838. https://doi.org/10.1016/j.psychres.2015.10.021 doi: 10.1016/j.psychres.2015.10.021 URL pmid: 26564549
[107]	^* Martin, K., Woo, J., Timmins, V., Collins, J., Islam, A., Newton, D., & Goldstein, B. I. (2016). Binge eating and emotional eating behaviors among adolescents and young adults with bipolar disorder. Journal of Affective Disorders, 195, 88-95. https://doi.org/10.1016/j.jad.2016.02.030 doi: 10.1016/j.jad.2016.02.030 URL pmid: 26890288
[108]	^* Martino, D. J., & Strejilevich, S. A. (2014). A comparison of decision making in patients with bipolar i disorder and schizophrenia. Schizophrenia Research, 156(1), 135-136. https://doi.org/10.1016/j.schres.2014.03.019 doi: 10.1016/j.schres.2014.03.019 URL pmid: 24735784
[109]	^* Martino, D. J., Strejilevich, S. A., Torralva, T., & Manes, F. (2011). Decision making in euthymic bipolar I and bipolar II disorders. Psychological Medicine, 41(6), 1319-1327. https://doi.org/10.1017/S0033291710001832 doi: 10.1017/S0033291710001832 URL pmid: 20860871
[110]	^* Martyn, F. M., McPhilemy, G., Nabulsi, L., Quirke, J., Hallahan, B., McDonald, C., & Cannon, D. M. (2023). Alcohol use is associated with affective and interoceptive network alterations in bipolar disorder. Brain and Behavior, 13(1), e2832. https://doi.org/10.1002/brb3.2832
[111]	^* Mason, L., O'Sullivan, N., Montaldi, D., Bentall, R. P., & El-Deredy, W. (2014). Decision-making and trait impulsivity in bipolar disorder are associated with reduced prefrontal regulation of striatal reward valuation. Brain, 137(8), 2346-2355. https://doi.org/10.1093/brain/awu152
[112]	Meertens, R. M., & Lion, R. (2008). Measuring an individual's tendency to take risks: The risk propensity scale. Journal of Applied Social Psychology, 38(6), 1506-1520. https://doi.org/10.1111/j.1559-1816.2008.00357.x
[113]	Mellers, B., Schwartz, A., & Ritov, I. (1999). Emotion-based choice. Journal of Experimental Psychology: General, 128(3), 332-345. https://doi.org/10.1037/0096-3445.128.3.332
[114]	Merikangas, K. R., Jin, R., He, J. P., Kessler, R. C., Lee, S., Sampson, N. A., ... Zarkov, Z. (2011). Prevalence and correlates of bipolar spectrum disorder in the world mental health survey initiative. Archives of General Psychiatry, 68(3), 241-251. https://doi.org/10.1001/archgenpsychiatry.2011.12 doi: 10.1001/archgenpsychiatry.2011.12 URL pmid: 21383262
[115]	Miklowitz, D. J., & Johnson, S. L. (2006). The psychopathology and treatment of bipolar disorder. Annual Review of Clinical Psychology, 2, 199-235. https://doi.org/10.1146/annurev.clinpsy.2.022305.095332 URL pmid: 17716069
[116]	Miller, J. N., & Black, D. W. (2020). Bipolar disorder and suicide: A review. Current Psychiatry Reports, 22(2), 6. https://doi.org/10.1007/s11920-020-1130-0 doi: 10.1007/s11920-020-1130-0 URL pmid: 31955273
[117]	^* Murphy, F. C., Rubinsztein, J. S., Michael, A., Rogers, R. D., Robbins, T. W., Paykel, E. S., & Sahakian, B. J. (2001). Decision-making cognition in mania and depression. Psychological Medicine, 31(4), 679-693. https://doi.org/ 10.1017/s0033291701003804 URL pmid: 11352370
[118]	^* Naiberg, M. R., Newton, D. F., Collins, J. E., Bowie, C. R., & Goldstein, B. I. (2016). Impulsivity is associated with blood pressure and waist circumference among adolescents with bipolar disorder. Journal of Psychiatric Research, 83, 230-239. https://doi.org/10.1016/j.jpsychires.2016.08.019 doi: S0022-3956(16)30282-5 URL pmid: 27665535
[119]	National Institutes of Health. (2014). Study quality assessment tools. Retrieved from: https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools
[120]	^* Obeid, S., Chok, A., Sacre, H., Haddad, C., Tahan, F., Ghanem, L., Azar, J., & Hallit, S. (2021). Are eating disorders associated with bipolar disorder type I? Results of a Lebanese case-control study. Perspectives in Psychiatric Care, 57(1), 326-334. https://doi.org/10.1111/ppc.12567
[121]	^* Ono, Y., Kikuchi, M., Hirosawa, T., Hino, S., Nagasawa, T., Hashimoto, T., Munesue, T., & Minabe, Y. (2015). Reduced prefrontal activation during performance of the Iowa Gambling Task in patients with bipolar disorder. Psychiatry Research: Neuroimaging, 233(1), 1-8. https://doi.org/10.1016/j.pscychresns.2015.04.003
[122]	Pålsson, E., Figueras, C., Johansson, A. G., Ekman, C. J., Hultman, B., Östlind, J., & Landén, M. (2013). Neurocognitive function in bipolar disorder: A comparison between bipolar I and II disorder and matched controls. BMC Psychiatry, 13(1), 1-9. https://doi.org/10.1186/1471-244X-13-165
[123]	Paluckaitė, U., & Žardeckaitė-Matulaitienė, K. (2017). Adolescents' perception of risky behaviour on the Internet. In Z. Bekirogullari, M. Y. Minas, & R. X. Thambusamy (Eds.), Health and Health Psychology - icH&Hpsy 2017, Vol 30. European Proceedings of Social and Behavioural Sciences (pp. 284-292). Future Academy. https://doi.org/10.15405/epsbs.2017.09.27
[124]	^* Pavlickova, H., Turnbull, O., & Bentall, R. P. (2014). Cognitive vulnerability to bipolar disorder in offspring of parents with bipolar disorder. British Journal of Clinical Psychology, 53(4), 386-401. https://doi.org/10.1111/bjc.12051 doi: 10.1111/bjc.12051 URL pmid: 24749716
[125]	Plana-Ripoll, O., Weye, N., Knudsen, A. K., Hakulinen, C., Madsen, K. B., Christensen, M. K., ... McGrath, J. J. (2023). The association between mental disorders and subsequent years of working life: A Danish population-based cohort study. The Lancet Psychiatry, 10(1), 30-39. https://doi.org/10.1016/S2215-0366(22)00376-5
[126]	Plans, L., Barrot, C., Nieto, E., Rios, J., Schulze, T. G., Papiol, S., ... Benabarre, A. (2019). Association between completed suicide and bipolar disorder: A systematic review of the literature. Journal of Affective Disorders, 242, 111-122. https://doi.org/10.1016/j.jad.2018.08.054 doi: S0165-0327(18)30514-7 URL pmid: 30173059
[127]	Pleskac, T. J. (2008). Decision making and learning while taking sequential risks. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34(1), 167-185. https://doi.org/10.1037/0278-7393.34.1.167
[128]	^* Powers, R. L., Russo, M., Mahon, K., Brand, J., Braga, R. J., Malhotra, A. K., & Burdick, K. E. (2013). Impulsivity in bipolar disorder: Relationships with neurocognitive dysfunction and substance use history. Bipolar Disorders, 15(8), 876-884. https://doi.org/10.1111/bdi.12124 doi: 10.1111/bdi.12124 URL pmid: 24028391
[129]	Prietzel, T. T. (2020). The effect of emotion on risky decision making in the context of prospect theory: A comprehensive literature review. Management Review Quarterly, 70, 313-353. https://doi.org/10.1007/s11301-019-00169-2
[130]	Rai, S., Mishra, B. R., Sarkar, S., Praharaj, S. K., Das, S., Maiti, R., Agrawal, N., & Nizami, S. H. (2018). Higher impulsivity and HIV-risk taking behaviour in males with alcohol dependence compared to bipolar mania: A pilot study. Community Mental Health Journal, 54(2), 218-223. https://doi.org/10.1007/s10597-017-0139-2 doi: 10.1007/s10597-017-0139-2 URL pmid: 28456858
[131]	Ramírez-Martín, A., Ramos-Martín, J., Mayoral-Cleries, F., Moreno-Küstner, B., & Guzman-Parra, J. (2020). Impulsivity, decision-making and risk-taking behaviour in bipolar disorder: A systematic review and meta-analysis. Psychological Medicine, 50(13), 2141-2153. https://doi.org/10.1017/S0033291720003086
[132]	^* Ramírez-Martín, A., Sirignano, L., Streit, F., Foo, J. C., Forstner, A. J., Frank, J., ... Guzmán-Parra, J. (2024). Impulsivity, decision-making, and risk behavior in bipolar disorder and major depression from bipolar multiplex families. Brain and Behavior, 14(2), e3337. https://doi.org/10.1002/brb3.3337
[133]	^* Reddy, L. F., Lee, J., Davis, M. C., Altshuler, L., Glahn, D. C., Miklowitz, D. J., & Green, M. F. (2014). Impulsivity and risk taking in bipolar disorder and schizophrenia. Neuropsychopharmacology, 39(2), 456-463. https://doi.org/10.1038/npp.2013.218 doi: 10.1038/npp.2013.218 URL pmid: 23963117
[134]	Reyna, V. F., Weldon, R. B., & McCormick, M. (2015). Educating intuition: Reducing risky decisions using Fuzzy- trace theory. Current Directions in Psychological Science, 24(5), 392-398. https://doi.org/10.1177/0963721415588081
[135]	^* Richard-Devantoy, S., Olié, E., Guillaume, S., & Courtet, P. (2016). Decision-making in unipolar or bipolar suicide attempters. Journal of Affective Disorders, 190, 128-136. https://doi.org/10.1016/j.jad.2015.10.001 doi: S0165-0327(15)30827-2 URL pmid: 26496018
[136]	Richards, J. B., Zhang, L., Mitchell, S. H., & de Wit, H. (1999). Delay or probability discounting in a model of impulsive behavior: Effect of alcohol. Journal of the Experimental Analysis of Behavior, 71(2), 121-143. https://doi.org/10.1901/jeab.1999.71-121 doi: 10.1901/jeab.1999.71-121 URL pmid: 10220927
[137]	Rivers, S. E., Reyna, V. F., & Mills, B. (2008). Risk taking under the influence: A Fuzzy-trace theory of emotion in adolescence. Developmental Review, 28(1), 107-144. https://doi.org/10.1016/j.dr.2007.11.002 doi: 10.1016/j.dr.2007.11.002 URL pmid: 19255597
[138]	Roberts, D. K., Alderson, R. M., Betancourt, J. L., & Bullard, C. C. (2021). Attention-deficit/hyperactivity disorder and risk-taking: A three-level meta-analytic review of behavioral, self-report, and virtual reality metrics. Clinical Psychology Review, 87, 102039. https://doi.org/10.1016/j.cpr.2021.102039
[139]	Rodgers, M. A., & Pustejovsky, J. E. (2020). Evaluating meta-analytic methods to detect selective reporting in the presence of dependent effect sizes. Psychological Methods, 26(2), 141-160. https://doi.org/10.1037/met0000300
[140]	^* Rubinsztein, J. S., Michael, A., Underwood, B. R., Tempest, M., & Sahakian, B. J. (2006). Impaired cognition and decision-making in bipolar depression but no 'affective bias' evident. Psychological Medicine, 36(5), 629-639. https://doi.org/10.1017/S0033291705006689 doi: 10.1017/S0033291705006689 URL pmid: 16420729
[141]	^* Salarvan, S., Sparding, T., Clements, C., Rydén, E., & Landén, M. (2019). Neuropsychological profiles of adult bipolar disorder patients with and without comorbid attention- deficit hyperactivity disorder. International Journal of Bipolar Disorders, 7(1), 1-8. https://doi.org/10.1186/s40345-019-0149-9
[142]	^* Saunders, K. E., Goodwin, G. M., & Rogers, R. D. (2016). Insensitivity to the magnitude of potential gains or losses when making risky choices: Women with borderline personality disorder compared with bipolar disorder and controls. Journal of Personality Disorders, 30(4), 530-544. https://doi.org/10.1521/pedi_2015_29_216 doi: 10.1521/pedi_2015_29_216 URL pmid: 26623536
[143]	^* Saxena, K., Simonetti, A., Verrico, C. D., Janiri, D., Nicola, M. D., Catinari, A., ... Soares, J. C. (2023). Neurocognitive correlates of cerebellar volumetric alterations in youth with pediatric bipolar spectrum disorders and bipolar offspring. Current Neuropharmacology, 21(6), 1367-1378. https://doi.org/10.2174/1570159X21666221014120332
[144]	Schaffer, A., Isometsä, E. T., Tondo, L., Moreno, D. H., Turecki, G., Reis, C., ... Yatham, L. N. (2015). International society for bipolar disorders task force on suicide: Meta-analyses and meta-regression of correlates of suicide attempts and suicide deaths in bipolar disorder. Bipolar Disorders, 17(1), 1-16. https://doi.org/10.1111/bdi.12271 doi: 10.1111/bdi.12271 URL pmid: 25329791
[145]	^* Scholz, V., Houenou, J., Kollmann, B., Duclap, D., Poupon, C., & Wessa, M. (2016). Dysfunctional decision-making related to white matter alterations in bipolar i disorder. Journal of Affective Disorders, 194, 72-79. https://doi.org/10.1016/j.jad.2015.12.019 doi: 10.1016/j.jad.2015.12.019 URL pmid: 26803778
[146]	Sicilia, A. C., Lukacs, J. N., Jones, S., & Perez Algorta, G. (2020). Decision-making and risk in bipolar disorder: A quantitative study using fuzzy trace theory. Psychology and Psychotherapy, 93(1), 105-121. https://doi.org/10.1111/papt.12215
[147]	^* Simonetti, A., Kurian, S., Saxena, J., Verrico, C. D., Soares, J. C., Sani, G., & Saxena, K. (2021). Cognitive correlates of impulsive aggression in youth with pediatric bipolar disorder and bipolar offspring. Journal of Affective Disorders, 287, 387-396. https://doi.org/10.1016/j.jad.2021.03.044 doi: 10.1016/j.jad.2021.03.044 URL pmid: 33838473
[148]	Sparding, T., Silander, K., Pålsson, E., Östlind, J., Sellgren, C., Ekman, C. J., ... Landén, M. (2015). Cognitive functioning in clinically stable patients with bipolar disorder I and II. PloS One, 10(1), e0115562. https://doi.org/10.1371/journal.pone.0115562
[149]	^* Taylor Tavares, J. V., Clark, L., Cannon, D. M., Erickson, K., Drevets, W. C., & Sahakian, B. J. (2007). Distinct profiles of neurocognitive function in unmedicated unipolar depression and bipolar II depression. Biological Psychiatry, 62(8), 917-924. https://doi.org/10.1016/j.biopsych.2007.05.034 doi: 10.1016/j.biopsych.2007.05.034 URL pmid: 17825802
[150]	^* Thomas, J., Knowles, R., Tai, S., & Bentall, R. P. (2007). Response styles to depressed mood in bipolar affective disorder. Journal of Affective Disorders, 100(1-3), 249-252. https://doi.org/10.1016/j.jad.2006.10.017 URL pmid: 17134763
[151]	Tinner, L., Caldwell, D., Hickman, M., MacArthur, G. J., Gottfredson, D., Lana Perez, A., ... Campbell, R. (2018). Examining subgroup effects by socioeconomic status of public health interventions targeting multiple risk behaviour in adolescence. BMC Public Health, 18(1), 1180. https://doi.org/10.1186/s12889-018-6042-0 doi: 10.1186/s12889-018-6042-0 URL pmid: 30326897
[152]	Torrent, C., Martinez-Arán, A., Daban, C., Amann, B., Balanzá-Martínez, V., del Mar Bonnín, C., ... Vieta, E. (2011). Effects of atypical antipsychotics on neurocognition in euthymic bipolar patients. Comprehensive Psychiatry, 52(6), 613-622. https://doi.org/10.1016/j.comppsych.2010.12.009 doi: 10.1016/j.comppsych.2010.12.009 URL pmid: 21295774
[153]	^* Urošević, S., Youngstrom, E. A., Collins, P., Jensen, J. B., & Luciana, M. (2016). Associations of age with reward delay discounting and response inhibition in adolescents with bipolar disorders. Journal of Affective Disorders, 190, 649-656. https://doi.org/10.1016/j.jad.2015.11.005 doi: S0165-0327(15)30771-0 URL pmid: 26590512
[154]	^* Vancampfort, D., Hagemann, N., Wyckaert, S., Rosenbaum, S., Stubbs, B., Firth, J., ... Sienaert, P. (2017). Higher cardio-respiratory fitness is associated with increased mental and physical quality of life in people with bipolar disorder: A controlled pilot study. Psychiatry Research, 256, 219-224. https://doi.org/10.1016/j.psychres.2017.06.066 doi: S0165-1781(17)30385-2 URL pmid: 28646785
[155]	^* Vancampfort, D., Sienaert, P., Wyckaert, S., De Hert, M., Stubbs, B., Soundy, A., De Smet, J., & Probst, M. (2015). Health-related physical fitness in patients with bipolar disorder vs. healthy controls: An exploratory study. Journal of Affective Disorders, 177, 22-27. https://doi.org/10.1016/j.jad.2014.12.058 doi: 10.1016/j.jad.2014.12.058 URL pmid: 25745831
[156]	^* van Enkhuizen, J., Henry, B. L., Minassian, A., Perry, W., Milienne-Petiot, M., Higa, K. K., Geyer, M. A., & Young, J. W. (2014). Reduced dopamine transporter functioning induces high-reward risk-preference consistent with bipolar disorder. Neuropsychopharmacology, 39(13), 3112-3122. https://doi.org/10.1038/npp.2014.170 doi: 10.1038/npp.2014.170 URL pmid: 25005251
[157]	Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1-48. https://doi.org/10.18637/jss.v036.i03
[158]	Wang, X. T., Zheng, R., Xuan, Y. H., Chen, J., & Li, S. (2016). Not all risks are created equal: A twin study and meta-analyses of risk taking across seven domains. Journal of Experimental Psychology: General, 145(11), 1548-1560. https://doi.org/10.1037/xge0000225
[159]	Wei, G. X., Kan, B., Wu, J., & Wang, K. (2018). Decision- making behavior in manic and euthymic bipolar disorder under uncertain risk conditions. Journal of Chifeng University (Natural Science Edition), 34(8), 97-101. https://doi.org/10.13398/j.cnki.issn1673-260x.2018.08.035
	[魏格欣, 阚博, 吴娟, 汪凯. (2018). 躁狂期和缓解期双相情感障碍患者在风险不明确情境下决策行为的研究与探讨. 赤峰学院学报(自然科学版), 34(8), 97-101. https://doi.org/10.13398/j.cnki.issn1673-260x.2018.08.035 ]
[160]	^* Williams, S. C., Davey-Rothwell, M. A., Tobin, K. E., & Latkin, C. (2017). People who inject drugs and have mood disorders—A brief assessment of health risk behaviors. Substance Use and Misuse, 52(9), 1181-1190. https://doi.org/10.1080/10826084.2017.1302954 doi: 10.1080/10826084.2017.1302954 URL pmid: 28574740
[161]	^* Wong, S. C. Y., Ng, M. C. M., Chan, J. K. N., Luk, M. S. K., Lui, S. S. Y., Chen, E. Y. H., & Chang, W. C. (2021). Altered risk-taking behavior in early-stage bipolar disorder with a history of psychosis. Frontiers in Psychiatry, 12. https://doi.org/10.3389/fpsyt.2021.763545
[162]	World Health Organization (WHO). (2022). Mental disorders. Retrieved Feb 12, 2023, from https://vizhub.healthdata.org/gbd-compare/
[163]	Xu, S. H., Fang, Z., & Rao, H. Y. (2013). Real or hypothetical monetary rewards modulates risk taking behavior. Acta Psychologica Sinica, 45(8), 874-886. https://doi.org/10.3724/SP.J.1041.2013.00874 doi: 10.3724/SP.J.1041.2013.00874 URL
	[徐四华, 方卓, 饶恒毅. (2013). 真实和虚拟金钱奖赏影响风险决策行为. 心理学报, 45(8), 874-886. https://doi.org/10.3724/SP.J.1041.2013.00874]
[164]	^* Yechiam, E., Hayden, E. P., Bodkins, M., O'Donnell, B. F., & Hetrick, W. P. (2008). Decision making in bipolar disorder: A cognitive modeling approach. Psychiatry Research, 161(2), 142-152. https://doi.org/10.1016/j.psychres.2007.07.001 doi: 10.1016/j.psychres.2007.07.001 URL pmid: 18848361
[165]	Yue, L. Z., Li, S., & Liang, Z. Y. (2018). New avenues for the development of domain-specific nature of risky decision making. Advances in Psychological Science, 26(5), 928-938. https://doi.org/10.3724/SP.J.1042.2018.00928
	[岳灵紫, 李纾, 梁竹苑. (2018). 风险决策中的领域特异性. 心理科学进展, 26(5), 928-938. https://doi.org/10.3724/ SP.J.1042.2018.00928 ] doi: 10.3724/SP.J.1042.2018.00928 URL
[166]	Zeng, B. E. (2019). The relationship between college students' suicide behavior and risk decision-making [Unpublished master's thesis]. Southern Medical University, Guangzhou.
	[曾宝尔. (2019). 大学生自杀行为与风险决策的关系研究 (硕士学位论文). 南方医科大学, 广州.]
[167]	Zhang, D. C., Highhouse, S., & Nye, C. D. (2019). Development and validation of the general risk propensity scale (GRiPS). Journal of Behavioral Decision Making, 32(2), 152-167. https://doi.org/10.1002/bdm.2102 doi: 10.1002/bdm.2102 URL
[168]	Zhu. C., G. (2020). Analysis of the investment risk preference of bipolar disorder-mania patients in remission and healthy first-degree relatives (siblings) [Unpublished master's thesis]. Anhui Medical University, China.
	[朱承刚. (2020). 缓解期双相躁狂患者及其健康一级亲属(同胞)投资风险偏好的研究 (硕士学位论文). 安徽医科大学.]
[169]	Zhu, Q., Liang, W. J., Zhang, G. C., Wu, X. H., & Guan, N. H. (2019). Social cognition and its impact on social functioning in patients with euthymic bipolar disorder. Guangdong Medical Journal, 40(18), 2671-2677. https://doi.org/10.13820/j.cnki.gdyx.20190901
	[朱麒, 梁文靖, 张桂灿, 吴秀华, 关念红. (2019). 缓解期双相障碍患者社会认知及对社会功能的影响. 广东医学, 40(18), 2671-2677. https://doi.org/10.13820/j.cnki.gdyx.20190901]
[170]	Bechara, A., Damasio, A. R., Damasio, H. & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50(1-3), 7-15. https://doi.org/10.1016/0010-0277(94)90018-3 doi: 10.1016/0010-0277(94)90018-3 URL pmid: 8039375
[171]	Rogers, R. D., Everitt, B. J., Baldacchino, A., Blackshaw, A. J., Swainson, R., Wynne, K., ... Robbins, T. W. (1999). Dissociable deficits in the decision-making cognition of chronic amphetamine abusers, opiate abusers, patients with focal damage to prefrontal cortex, and tryptophan-depleted normal volunteers: evidence for monoaminergic mechanisms. Neuropsychopharmacology, 20(4), 322-339. https://doi.org/10.1016/S0893-133X(98)00091-8 doi: 10.1016/S0893-133X(98)00091-8 URL pmid: 10088133

调节变量	No. of ESs	Q_E (df)	F (df1, df2)	Hedges' g/β	SE	95% CI	t	p
人口学变量
a. 年龄	157	-	-	-	-	-	-	-
截距	-	Q_E (155) = 547.46, p < 0.001	F (1, 155) = 5.20, p = 0.024	0.266	0.038	[0.190, 0.341]	6.96	< 0.001
年龄	-	Q_E (155) = 547.46, p < 0.001	F (1, 155) = 5.20, p = 0.024	0.009	0.004	[0.001, 0.017]	2.28	0.024
b. 性别比	147	-	-	-	-	-	-	-
截距	-	Q_E (145) = 534.21, p < 0.001	F (1, 145) = 0.00, p = 0.955	0.286	0.040	[0.207, 0.365]	7.18	< 0.001
性别比	-	Q_E (145) = 534.21, p < 0.001	F (1, 145) = 0.00, p = 0.955	-0.016	0.277	[-0.562, 0.531]	-0.06	0.955
c. 受教育程度	77	-	-	-	-	-	-	-
截距	-	Q_E (75) = 278.00, p < 0.001	F (1, 75) = 0.24, p = 0.628	0.265	0.069	[0.127, 0.402]	3.83	< 0.001
受教育年限	-	Q_E (75) = 278.00, p < 0.001	F (1, 75) = 0.24, p = 0.628	0.016	0.033	[-0.049, 0.081]	0.49	0.628
d. 地区	174	-	-	-	-	-	-	-
欧洲 EU	72	Q_E (170) = 632.91, p < 0.001	F (3, 170) = 1.45, p = 0.231	0.333	0.062	[0.211, 0.455]	5.39	< 0.001
北美洲 NA	56			0.189	0.068	[0.054, 0.325]	2.77	0.006
南美洲 SA	27			0.415	0.105	[0.207, 0.623]	3.94	< 0.001
亚洲 ASIA	19			0.220	0.128	[-0.032, 0.472]	1.72	0.087
EU vs. NA	-			-0.144	0.092	[-0.326, 0.039]	-1.56	0.121
EU vs. SA	-			0.082	0.122	[-0.159, 0.323]	0.12	0.503
EU vs. ASIA	-			-0.113	0.142	[-0.393, 0.167]	-0.80	0.425
NA vs. SA	-			0.226	0.126	[-0.023, 0.474]	1.80	0.074
NA vs. ASIA	-			0.030	0.145	[-0.256, 0.316]	0.21	0.836
SA vs. ASIA	-			-0.196	0.166	[-0.522, 0.131]	-1.18	0.239
疾病特征
a. 心境阶段	77	-	-	-	-	-	-	-
缓解期E	64	Q_E (74) = 170.48, p < 0.001	F (2, 74) = 3.52, p = 0.035	0.245	0.063	[0.120, 0.369]	3.91	< 0.001
<轻>躁狂期M	9			0.604	0.129	[0.347, 0.862]	4.68	< 0.001
抑郁期D	4			0.417	0.190	[0.038, 0.796]	2.19	0.032
E vs. M	-			0.360	0.137	[0.087, 0.632]	2.63	0.010
E vs. D	-			0.172	0.194	[-0.214, 0.558]	0.89	0.377
M vs. D	-			-0.187	0.212	[-0.609, 0.234]	-0.89	0.379
测量特征
a. 风险偏好测量类型	176	-	-	-	-	-	-	-
风险态度量表A	13	Q_E (173) = 640.51, p < 0.001	F (2, 173) = 2.71, p = 0.070	0.624	0.151	[0.325, 0.923]	4.12	< 0.001
日常风险行为B	75			0.312	0.067	[0.179, 0.445]	4.62	< 0.001
行为实验任务T	88			0.252	0.053	[0.148, 0.356]	4.78	< 0.001
A vs. B	-			-0.371	0.160	[-0.688, -0.055]	-2.31	0.022
A vs. T	-			-0.312	0.166	[-0.639, 0.015]	-1.88	0.062
B vs. T	-			-0.059	0.085	[-0.226, 0.108]	-0.70	0.484
b. 任务类型	88
IGT	41	Q_E (84) = 255.07, p < 0.001	F (3, 84) = 2.15, p = 0.100	0.396	0.084	[0.229, 0.563]	4.71	< 0.001
BART	10			0.159	0.151	[-0.107, 0.580]	1.37	0.294
CGT	26			0.220	0.109	[0.003, 0.438]	2.02	0.047
RC tasks	11			-0.025	0.158	[-0.340, 0.290]	-0.16	0.875
IGT vs. BART	-			-0.237	0.173	[-0.580, 0.107]	-1.37	00.174
IGT vs. CGT	-			-0.176	0.138	[-0.450, 0.098]	-1.27	0.206
IGT vs. RC tasks	-			-0.421	0.178	[-0.775, -0.067]	-2.37	0.020
BART vs. CGT	-			0.061	0.186	[-0.309, 0.431]	0.33	0.744
BART vs. RC tasks	-			-0.184	0.215	[-0.611, 0.242]	-0.86	0.393
CGT vs. RC tasks	-			-0.245	0.192	[-0.628, 0.137]	-1.28	0.206
c. 任务明确性	88
显性任务	37	Q_E (86) = 267.98, p < 0.001	F (1, 86) = 2.85, p = 0.095	0.145	0.092	[-0.038, 0.328]	1.57	0.120
隐性任务	51			0.343	0.075	[0.194, 0.493]	4.57	< 0.001
显性 vs. 隐性	-			0.199	0.118	[-0.035, 0.433]	1.69	0.095
d. 行为领域	85
健康	71	Q_E (82) = 321.66, p < 0.001	F (2, 82) = 2.88, p = 0.062	0.308	0.067	[0.176, 0.441]	4.64	< 0.001
经济	6			0.331	0.155	[0.022, 0.640]	2.13	0.036
总体态度	8			0.733	0.165	[0.404, 1.061]	4.44	< 0.001
健康 vs. 经济	-			0.023	0.153	[-0.282, 0.327]	0.15	0.883
健康 vs. 总体态度	-			0.424	0.177	[0.072, 0.776]	2.40	0.019
经济 vs. 总体态度	-			0.402	0.224	[-0.043, 0.847]	1.80	0.076

调节变量	No. of ESs	Q_E (df)	F (df1, df2)	Hedges' g/β	SE	95% CI	t	p
人口学变量
a. 年龄	157	-	-	-	-	-	-	-
截距	-	Q_E (155) = 547.46, p < 0.001	F (1, 155) = 5.20, p = 0.024	0.266	0.038	[0.190, 0.341]	6.96	< 0.001
年龄	-	Q_E (155) = 547.46, p < 0.001	F (1, 155) = 5.20, p = 0.024	0.009	0.004	[0.001, 0.017]	2.28	0.024
b. 性别比	147	-	-	-	-	-	-	-
截距	-	Q_E (145) = 534.21, p < 0.001	F (1, 145) = 0.00, p = 0.955	0.286	0.040	[0.207, 0.365]	7.18	< 0.001
性别比	-	Q_E (145) = 534.21, p < 0.001	F (1, 145) = 0.00, p = 0.955	-0.016	0.277	[-0.562, 0.531]	-0.06	0.955
c. 受教育程度	77	-	-	-	-	-	-	-
截距	-	Q_E (75) = 278.00, p < 0.001	F (1, 75) = 0.24, p = 0.628	0.265	0.069	[0.127, 0.402]	3.83	< 0.001
受教育年限	-	Q_E (75) = 278.00, p < 0.001	F (1, 75) = 0.24, p = 0.628	0.016	0.033	[-0.049, 0.081]	0.49	0.628
d. 地区	174	-	-	-	-	-	-	-
欧洲 EU	72	Q_E (170) = 632.91, p < 0.001	F (3, 170) = 1.45, p = 0.231	0.333	0.062	[0.211, 0.455]	5.39	< 0.001
北美洲 NA	56			0.189	0.068	[0.054, 0.325]	2.77	0.006
南美洲 SA	27			0.415	0.105	[0.207, 0.623]	3.94	< 0.001
亚洲 ASIA	19			0.220	0.128	[-0.032, 0.472]	1.72	0.087
EU vs. NA	-			-0.144	0.092	[-0.326, 0.039]	-1.56	0.121
EU vs. SA	-			0.082	0.122	[-0.159, 0.323]	0.12	0.503
EU vs. ASIA	-			-0.113	0.142	[-0.393, 0.167]	-0.80	0.425
NA vs. SA	-			0.226	0.126	[-0.023, 0.474]	1.80	0.074
NA vs. ASIA	-			0.030	0.145	[-0.256, 0.316]	0.21	0.836
SA vs. ASIA	-			-0.196	0.166	[-0.522, 0.131]	-1.18	0.239
疾病特征
a. 心境阶段	77	-	-	-	-	-	-	-
缓解期E	64	Q_E (74) = 170.48, p < 0.001	F (2, 74) = 3.52, p = 0.035	0.245	0.063	[0.120, 0.369]	3.91	< 0.001
<轻>躁狂期M	9			0.604	0.129	[0.347, 0.862]	4.68	< 0.001
抑郁期D	4			0.417	0.190	[0.038, 0.796]	2.19	0.032
E vs. M	-			0.360	0.137	[0.087, 0.632]	2.63	0.010
E vs. D	-			0.172	0.194	[-0.214, 0.558]	0.89	0.377
M vs. D	-			-0.187	0.212	[-0.609, 0.234]	-0.89	0.379
测量特征
a. 风险偏好测量类型	176	-	-	-	-	-	-	-
风险态度量表A	13	Q_E (173) = 640.51, p < 0.001	F (2, 173) = 2.71, p = 0.070	0.624	0.151	[0.325, 0.923]	4.12	< 0.001
日常风险行为B	75			0.312	0.067	[0.179, 0.445]	4.62	< 0.001
行为实验任务T	88			0.252	0.053	[0.148, 0.356]	4.78	< 0.001
A vs. B	-			-0.371	0.160	[-0.688, -0.055]	-2.31	0.022
A vs. T	-			-0.312	0.166	[-0.639, 0.015]	-1.88	0.062
B vs. T	-			-0.059	0.085	[-0.226, 0.108]	-0.70	0.484
b. 任务类型	88
IGT	41	Q_E (84) = 255.07, p < 0.001	F (3, 84) = 2.15, p = 0.100	0.396	0.084	[0.229, 0.563]	4.71	< 0.001
BART	10			0.159	0.151	[-0.107, 0.580]	1.37	0.294
CGT	26			0.220	0.109	[0.003, 0.438]	2.02	0.047
RC tasks	11			-0.025	0.158	[-0.340, 0.290]	-0.16	0.875
IGT vs. BART	-			-0.237	0.173	[-0.580, 0.107]	-1.37	00.174
IGT vs. CGT	-			-0.176	0.138	[-0.450, 0.098]	-1.27	0.206
IGT vs. RC tasks	-			-0.421	0.178	[-0.775, -0.067]	-2.37	0.020
BART vs. CGT	-			0.061	0.186	[-0.309, 0.431]	0.33	0.744
BART vs. RC tasks	-			-0.184	0.215	[-0.611, 0.242]	-0.86	0.393
CGT vs. RC tasks	-			-0.245	0.192	[-0.628, 0.137]	-1.28	0.206
c. 任务明确性	88
显性任务	37	Q_E (86) = 267.98, p < 0.001	F (1, 86) = 2.85, p = 0.095	0.145	0.092	[-0.038, 0.328]	1.57	0.120
隐性任务	51			0.343	0.075	[0.194, 0.493]	4.57	< 0.001
显性 vs. 隐性	-			0.199	0.118	[-0.035, 0.433]	1.69	0.095
d. 行为领域	85
健康	71	Q_E (82) = 321.66, p < 0.001	F (2, 82) = 2.88, p = 0.062	0.308	0.067	[0.176, 0.441]	4.64	< 0.001
经济	6			0.331	0.155	[0.022, 0.640]	2.13	0.036
总体态度	8			0.733	0.165	[0.404, 1.061]	4.44	< 0.001
健康 vs. 经济	-			0.023	0.153	[-0.282, 0.327]	0.15	0.883
健康 vs. 总体态度	-			0.424	0.177	[0.072, 0.776]	2.40	0.019
经济 vs. 总体态度	-			0.402	0.224	[-0.043, 0.847]	1.80	0.076

调节变量	β (SE)	95% CI	t	p
截距	0.199 (0.064)	[0.070, 0.328]	3.09	0.003
年龄	0.015 (0.009)	[−0.004, 0.033]	1.59	0.117
心境阶段：缓解期 (vs. <轻>躁狂期)	0.397 (0.142)	[0.112, 0.681]	2.78	0.007
心境阶段：缓解期 (vs.抑郁期)	0.149 (0.205)	[−0.261, 0.559]	0.73	0.469
Q_Etest	Q_E (65) = 150.83, p < 0.001
Omnibus test	F (3, 65) = 3.36, p = 0.024
Number of ESs	69

调节变量	β (SE)	95% CI	t	p
截距	0.199 (0.064)	[0.070, 0.328]	3.09	0.003
年龄	0.015 (0.009)	[−0.004, 0.033]	1.59	0.117
心境阶段：缓解期 (vs. <轻>躁狂期)	0.397 (0.142)	[0.112, 0.681]	2.78	0.007
心境阶段：缓解期 (vs.抑郁期)	0.149 (0.205)	[−0.261, 0.559]	0.73	0.469
Q_Etest	Q_E (65) = 150.83, p < 0.001
Omnibus test	F (3, 65) = 3.36, p = 0.024
Number of ESs	69

调节变量	No. of ESs	Q_E (df)	F (df1, df2)	Hedges' g/β	SE	95% CI	t	p
人口学变量
a. 年龄	76	-	-	-	-	-	-	-
截距	-	Q_E (74) = 192.16, p < 0.001	F (1, 74) = 6.38, p = 0.014	0.232	0.050	[0.132, 0.333]	4.63	< 0.001
年龄	-	Q_E (74) = 192.16, p < 0.001	F (1, 74) = 6.38, p = 0.014	0.012	0.005	[0.003, 0.022]	2.53	0.014
b. 性别比	69	-	-	-	-	-	-	-
截距	-	Q_E (67) = 197.69, p < 0.001	F (1, 67) = 0.20, p = 0.657	0.253	0.059	[0.135, 0.371]	4.28	< 0.001
性别比	-	Q_E (67) = 197.69, p < 0.001	F (1, 67) = 0.20, p = 0.657	-0.167	0.375	[-0.916, 0.581]	-0.45	0.657
c. 受教育年限	48	-	-	-	-	-	-	-
截距	-	Q_E (46) = 130.07, p < 0.001	F (1, 46) = 0.20, p = 0.661	0.246	0.091	[0.063, 0.428]	2.71	0.010
受教育年限	-	Q_E (46) = 130.07, p < 0.001	F (1, 46) = 0.20, p = 0.661	0.019	0.043	[-0.068, 0.106]	0.44	0.661
d. 地区	88	-	-	-	-	-	-	-
欧洲 EU	26	Q_E (84) = 247.44, p < 0.001	F (3, 84) = 3.21, p = 0.027	0.419	0.097	[0.227, 0.611]	4.34	< 0.001
北美洲 NA	31			0.042	0.095	[-0.147, 0.230]	0.44	0.660
南美洲 SA	23			0.420	0.128	[0.165, 0.676]	3.28	0.002
亚洲 ASIA	8			0.216	0.165	[-0.112, 0.545]	1.31	0.194
EU vs. NA	-			-0.377	0.135	[-0.646, -0.108]	-2.79	0.007
EU vs. SA	-			0.002	0.161	[-0.318, 0.321]	0.01	0.992
EU vs. ASIA	-			-0.203	0.191	[-0.583, 0.178]	-1.06	0.293
NA vs. SA	-			0.379	0.160	[0.061, 0.696]	2.37	0.020
NA vs. ASIA	-			0.174	0.190	[-0.204, 0.553]	0.92	0.363
SA vs. ASIA	-			-0.204	0.209	[-0.620, 0.212]	-0.98	0.332
疾病特征
a. 心境阶段	48	-	-	-	-	-	-	-
缓解期 E	38	Q_E (45) = 125.61, p < 0.001	F (2, 45) = 1.37, p = 0.265	0.291	0.078	[0.134, 0.449]	3.72	< 0.001
<轻>躁狂期 M	7			0.553	0.155	[0.240, 0.865]	3.56	< 0.001
抑郁期 D	3			0.479	0.230	[0.015, 0.943]	2.08	0.043
E vs. M	-			0.261	0.165	[-0.071, 0.593]	1.58	0.120
E vs. D	-			0.188	0.235	[-0.286, 0.661]	0.80	0.430
M vs. D	-			-0.074	0.285	[-0.592, 0.445]	-0.29	0.777