Decision Making assessed by the Iowa Gambling Task and Major Depressive Disorder A systematic review

Siqueira, Adriano Felipe Perez; Flaks, Mariana K.; Biella, Marina Maria; Mauer, Sivan; Borges, Marcus Kiiti; Aprahamian, Ivan

doi:10.1590/1980-57642018dn12-030005

Cited by 15 publications

(12 citation statements)

References 22 publications

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“…First, only sex, age, and pain duration were collected in the demographic data, but no other measures of education or psychological status, such as anxiety and depression, were considered apart from pain severity and pain interference. It is known that experiencing chronic pain puts a person at increased risk of developing anxiety and depression disorders, and these 2 factors have been documented to have a significant influence on decision-making [ 49 , 50 ]. We did not consider the impact of medications on decision-making either (ie, we did have the participants’ medication information but did not exclude participants who were receiving medical treatments).…”

Section: Discussionmentioning

confidence: 99%

Differences in Learning and Persistency Characterizing Behavior in Chronic Pain for the Iowa Gambling Task: Web-Based Laboratory-in-the-Field Study

Zhang¹,

Vashisht²,

Nethra³

et al. 2022

J Med Internet Res

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Background Chronic pain is a significant worldwide health problem. It has been reported that people with chronic pain experience decision-making impairments, but these findings have been based on conventional laboratory experiments to date. In such experiments, researchers have extensive control of conditions and can more precisely eliminate potential confounds. In contrast, there is much less known regarding how chronic pain affects decision-making captured via laboratory-in-the-field experiments. Although such settings can introduce more experimental uncertainty, collecting data in more ecologically valid contexts can better characterize the real-world impact of chronic pain. Objective We aim to quantify decision-making differences between individuals with chronic pain and healthy controls in a laboratory-in-the-field environment by taking advantage of internet technologies and social media. Methods A cross-sectional design with independent groups was used. A convenience sample of 45 participants was recruited through social media: 20 (44%) participants who self-reported living with chronic pain, and 25 (56%) people with no pain or who were living with pain for <6 months acting as controls. All participants completed a self-report questionnaire assessing their pain experiences and a neuropsychological task measuring their decision-making (ie, the Iowa Gambling Task) in their web browser at a time and location of their choice without supervision. Results Standard behavioral analysis revealed no differences in learning strategies between the 2 groups, although qualitative differences could be observed in the learning curves. However, computational modeling revealed that individuals with chronic pain were quicker to update their behavior than healthy controls, which reflected their increased learning rate (95% highest–posterior-density interval [HDI] 0.66-0.99) when fitted to the Values-Plus-Perseverance model. This result was further validated and extended on the Outcome-Representation Learning model as higher differences (95% HDI 0.16-0.47) between the reward and punishment learning rates were observed when fitted to this model, indicating that individuals with chronic pain were more sensitive to rewards. It was also found that they were less persistent in their choices during the Iowa Gambling Task compared with controls, a fact reflected by their decreased outcome perseverance (95% HDI −4.38 to −0.21) when fitted using the Outcome-Representation Learning model. Moreover, correlation analysis revealed that the estimated parameters had predictive value for the self-reported pain experiences, suggesting that the altered cognitive parameters could be potential candidates for inclusion in chronic pain assessments. Conclusions We found that individuals with chronic pain were more driven by rewards and less consistent when making decisions in our laboratory-in-the-field experiment. In this case study, it was demonstrated that, compared with standard statistical summaries of behavioral performance, computational approaches offered superior ability to resolve, understand, and explain the differences in decision-making behavior in the context of chronic pain outside the laboratory.

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Section: Discussionmentioning

confidence: 99%

Differences in Learning and Persistency Characterizing Behavior in Chronic Pain for the Iowa Gambling Task: Web-Based Laboratory-in-the-Field Study

Zhang¹,

Vashisht²,

Nethra³

et al. 2022

J Med Internet Res

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“…These profiles are associated with an increased risk of adverse outcomes, such as cessation of treatment, alcohol abuse, stress, worsening of quality of life, depression and anxiety. A systematic review was conducted to evaluate the performance of adults with major depressive disorder on the Iowa Gambling Task (IGT) (Siqueira et al, 2018). Five studies were included: 3 reported significant differences in DM performance between depressed and non-depressed individuals.…”

Section: Discussionmentioning

confidence: 99%

Decision-making profile in older adults: the influence of cognitive impairment, premorbid intelligence and depressive symptoms

Biella

Siqueira

Borges

et al. 2019

Int. Psychogeriatr.

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ABSTRACTObjective:Decision-making (DM) is a component of executive functioning. DM is essential to make proper decisions regarding important life and health issues. DM can be impaired in cognitive disorders among older adults, but current literature is scarce. The aim of this study was to evaluate the DM profile in participants with and without cognitive impairment.Design:Cross-sectional analysis of a cohort study on cognitive aging.Participants:143 older adults.Setting:University-based memory clinic.Methods:Patients comprised three groups after inclusion and exclusion criteria: healthy controls (n=29), mild cognitive impairment (n=81) and dementia (n=33). Participants were evaluated using an extensive neuropsychological protocol. DM profile was evaluated by the Melbourne Decision Making Questionnaire. Multinomial logistic regression was used to evaluate associations between age, sex, educational level, estimated intelligence quotient (IQ), cognitive disorders, depressive or anxiety symptoms, and the DM profiles.Results:The most prevalent DM profile was the vigilant type, having a prevalence of 64.3%. The vigilant profile also predominated in all three groups. The multinomial logistic regression showed that the avoidance profile (i.e. buck-passing) was associated with a greater presence of dementia (p=0.046) and depressive symptoms (p=0.024), but with less anxious symptoms (p=0.047). The procrastination profile was also associated with depressive symptoms (p=0.048). Finally, the hypervigilant profile was associated with a lower pre-morbid IQ (p=0.007).Conclusion:Older adults with cognitive impairment tended to make more unfavorable choices and have a more dysfunctional DM profile compared to healthy elders.

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“…Abnormal delayed discounting has been identified in patients with attentiondeficit/hyperactivity disorder (ADHD), addictive disorders, major depressive disorder (MDD), and other conditions (Amlung et al, 2019;Amlung, Vedelago, Acker, Balodis, & MacKillop, 2017; de Castro Paiva, de Souza Costa, Malloy-Diniz, Marques de Miranda, & Jardim de Paula, 2019). Substance abuse disorders (SUDs) and MDD have been associated with anhedonia and increased risky decision-making, as measured by the Iowa Gambling Task (IGT) (de Siqueira et al, 2018;Kovács, Richman, Janka, Maraz, & Andó, 2017;Rizvi, Lambert, & Kennedy, 2018). Additionally, increased impulsive decision-making is found in children with ADHD, though results have been mixed for adults with ADHD (Groen, Gaastra, Lewis-Evans, & Tucha, 2013).…”

Section: Introductionmentioning

confidence: 99%

Reward Dysfunction in General and Specific Psychopathology in Children and Adults

Saxena

Hartman

Blatt

et al. 2021

Preprint

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Background: Reward dysfunction has been implicated in many psychiatric disorders such as attention-deficit/hyperactivity disorders, depression, and substance use disorders. However, psychiatric comorbidities are common, and the specificity of reward dysfunction to individual psychopathologies is unknown. The objective of this study was to evaluate the association between reward functioning and specific or general psychopathologies. Methods: 1044 adults and their 1215 children (ages 6-12) completed various measures of the Positive Valence System domain from the Research Domain Criteria (RDoC), which included the Delayed and Probability Discounting Tasks, Energy Expenditure for Reward Task, and Iowa Gambling Task. Children also completed the Experienced Pleasure Scale for children, while adults completed the Temporal Experience of Pleasure Scale and the Behavioral Activation System tasks. Psychopathology was assessed using the Child Behavior Checklist (CBCL) for children and the Adult Self Report (ASR) for parents. Results: One general factor identified via principal factors factor analysis explained the majority of variance in psychopathology in both groups. Reward measures in both adults and children were significantly associated with general psychopathology as well as most specific psychopathologies. Some associations between reward and psychopathology did not hold following removal of general psychopathology; nonetheless, certain reward constructs were uniquely associated with specific disorder problems but not general psychopathology. Conclusion: Disorder problem specific associations with reward functioning can be identified after removal of comorbidity. General propensity toward psychopathology is significantly but not uniquely correlated with reward dysfunction. Altogether, this may have broader implications for future study of the role of reward in disease pathogenesis.

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Decision Making assessed by the Iowa Gambling Task and Major Depressive Disorder A systematic review

Cited by 15 publications

References 22 publications

Differences in Learning and Persistency Characterizing Behavior in Chronic Pain for the Iowa Gambling Task: Web-Based Laboratory-in-the-Field Study

Differences in Learning and Persistency Characterizing Behavior in Chronic Pain for the Iowa Gambling Task: Web-Based Laboratory-in-the-Field Study

Decision-making profile in older adults: the influence of cognitive impairment, premorbid intelligence and depressive symptoms

Reward Dysfunction in General and Specific Psychopathology in Children and Adults

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