The Role of Impulsivity in Major Depression: A Systematic Review

Fields, Sherecce; Schueler, Jordan; Arthur, Kianna; Harris, Bethany

doi:10.1007/s40473-021-00231-y

Cited by 10 publications

(6 citation statements)

References 63 publications

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“…Impulsiveness is an important risk factor for several mental disorders, including depression (1)(2)(3). The causal effect of impulsiveness on depression is confirmed by a longitudinal study (3).…”

Section: Introductionmentioning

confidence: 81%

“…The self-reported facets, such as "urgency" (14-16), "lack of perseverance" (16), "inattention, " "lack of planning, " and "inability in controlling temper or behavior" (17), are positively correlated with depression. In addition, the behavioral-measured impulsive decisionmaking and disinhibition of response are significantly different in depressive participants compared to the control groups (2). However, the above studies do not consider trait-level depression and its facets.…”

Section: Introductionmentioning

confidence: 94%

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Network Analysis of the Relationship Between Trait Depression and Impulsiveness Among Youth

Zhang

Xue

et al. 2022

Front. Psychiatry

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ObjectiveBoth impulsiveness and trait depression are the trait-level risk factors for depressive symptoms. However, the two traits overlap and do not affect depressive symptoms independently. This study takes impulsiveness and trait depression into a whole construct, aiming to find the complex associations among all facets and explore their relative importance in a trait network. It can help us find the key facets that need consideration in preventing depression.Materials and MethodsWe used the Barratt Impulsiveness Scale (BIS) and Trait Depression Scale (T-DEP) as measuring tools, conducted network analysis, and applied the Graphic Least Absolute Shrinkage and Selection Operator (GLASSO) algorithm to estimate the network structure and compute the linkage and centrality indexes. The accuracy and stability of the indexes were estimated through bootstrapping. All the computations were performed by R script and packages.ResultsWe found that “trait anhedonia” was connected with “non-planning” and “cognitive” impulsiveness, while “trait dysthymia” was connected with “motor” impulsiveness. “Cognitive” impulsiveness had a statistically significant higher expected influence than “motor” impulsiveness and had the trend to be dominant in the network. “Trait dysthymia” had a statistically significant higher bridge expected influence than “cognitive” impulsiveness and had the trend to be the key facet linking impulsiveness with trait depression. “Non-only children” had higher network global strength than “only children.” All indexes were accurate and stable.ConclusionThe present study confirms the complex associations among facets of trait depression and impulsiveness, finding that “cognitive” impulsiveness and “trait dysthymia” are the two key factors in the network. The results imply that different facets of impulsiveness should be considered respectively regarding anhedonia and dysthymia. “Cognitive” impulsiveness and “trait dysthymia” are critical to the prevention of depression.

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Section: Introductionmentioning

confidence: 81%

Section: Introductionmentioning

confidence: 94%

Network Analysis of the Relationship Between Trait Depression and Impulsiveness Among Youth

Zhang

Xue

et al. 2022

Front. Psychiatry

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“…Depressed mood has been linked to increased feelings of social isolation and alienation from others, but also to actual reduced social support (Joiner, 2002), which may increase the likelihood of aggressive reactions to perceived injustice, and thus, may increase willingness to harm others in creative ways. Similarly, depressed affect has been found to increase impulsivity and hostility, leading to reduced behavioral control and self‐regulation (e.g., Chabrol et al., 2010; Fields, Schueler, Arthur, & Harris, 2021), which may make individuals more reactive to unfair social situations, and at the same time, favor unconventional thinking “out of the box” (e.g., Acar & Sen, 2013; Perchtold‐Stefan et al., 2022a). This proposed pathway may be amplified for malevolent creativity, as depression and creative ideation are believed to share certain cognitive vulnerabilities, like reduced latent inhibition, which may allow for unusual experiences and thoughts, but also increase stress in response to an “unfiltered” environment (Young et al., 2013), potentially triggering harmful creative ideation.…”

Section: Discussionmentioning

confidence: 99%

Depressive Symptoms are Positively Linked to Malevolent Creativity: A Novel Perspective on the Maladaptive Nature of Revenge Ideation

Perchtold‐Stefan

Rominger

Fink

2023

Journal of Creative Behavior

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Depressed mood has attracted little attention in creativity research. By comparison, psychotherapeutic studies have repeatedly associated depressive symptomatology with increased revenge ideation. Combining creativity and retaliatory ideation, the present study examined whether self-reported subclinical depressive symptoms are linked to malevolent creativitycreativity used for the purpose of damaging othersin a psychometric test. In a sample of n = 259 participants, overall depressive symptoms were positively associated with malevolent creativity. Sensitivity analyses confirmed this link for motivational and interactional symptoms, but not cognitive symptoms of depression. As a gender-specific finding, malevolent creativity was positively linked to emotional symptoms of depression in women, but not men. Our findings hint at the possibility that mood impairments through depressive symptoms may facilitate malevolent creative ideation through increased impulsivity, reduced self-regulation, and protracted anger rumination. Following recommendations regarding more focused investigations into the vast research complex of psychopathology and creativity, this study emphasizes negative mood as a risk factor for the occurrence of harmful creative ideation, and thus, presents a novel perspective on the intricate link between internalizing and externalizing symptomatology.

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“…There has been consistent evidence showing that impulsivity is higher individuals with MDD and is positively associated with depressive symptoms 43 , but evidence for longitudinal relationship has been limited 44,45 . Our results indicate that higher impulsivity is associated with higher risk of multiple mental health conditions and could be a potential maker in targeted prevention programs.…”

Section: Predictors Of Future Mental Health Symptomsmentioning

confidence: 99%

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder

Desrivières,

Zhang,

Robinson

et al. 2024

Preprint

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This study uses machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder (MDD), and alcohol use disorder (AUD). Utilizing case-control samples (ages 18-25 years) and a longitudinal population-based sample (n=1,851), the models, incorporating diverse data domains, achieved high accuracy in classifying EDs, MDD, and AUD from healthy controls. The area under the receiver operating characteristic curves (AUC-ROC [95% CI]) reached 0.92 [0.86-0.97] for AN and 0.91 [0.85-0.96] for BN, without relying on body mass index as a predictor. The classification accuracies for MDD (0.91 [0.88-0.94]) and AUD (0.80 [0.74-0.85]) were also high. Each data domain emerged as accurate classifiers individually, with personality distinguishing AN, BN, and their controls with AUC-ROCs ranging from 0.77 to 0.89. The models demonstrated high transdiagnostic potential, as those trained for EDs were also accurate in classifying AUD and MDD from healthy controls, and vice versa (AUC-ROCs, 0.75-0.93). Shared predictors, such as neuroticism, hopelessness, and symptoms of attention-deficit/hyperactivity disorder, were identified as reliable classifiers. For risk prediction in the longitudinal population sample, the models exhibited moderate performance (AUC-ROCs, 0.64-0.71), highlighting the potential of combining multi-domain data for precise diagnostic and risk prediction applications in psychiatry.

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The Role of Impulsivity in Major Depression: A Systematic Review

Cited by 10 publications

References 63 publications

Network Analysis of the Relationship Between Trait Depression and Impulsiveness Among Youth

Network Analysis of the Relationship Between Trait Depression and Impulsiveness Among Youth

Depressive Symptoms are Positively Linked to Malevolent Creativity: A Novel Perspective on the Maladaptive Nature of Revenge Ideation

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder

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