Neurocognitive Measures of Self-blame and Risk Prediction Models of Recurrence in Major Depressive Disorder

Fennema

et al. 2022

Preprint

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Darwin stated that humans have a strong and involuntary tendency to perform certain actions when a specific state of mind is induced. Such "action tendencies" are key to understanding the maladaptive impact of self-blame-related feelings in depression. For example, feeling like "hiding" and "creating a distance from oneself" in a text-based task were previously associated with recurrence risk in remitted depression. Despite their functional importance, action tendencies have not been systematically investigated in current depression, which was the aim of this pre-registered study. To this end, we developed the first virtual reality (VR) assessment of blame-related action tendencies and compared current depression (n=98) with control participants (n=40). The immersive VR-task, pre-programmed on devices sent to participants' homes, used hypothetical social interactions, in which either participants (self-agency) or their friend (other-agency) were described to have acted inappropriately. Good concurrent validity was demonstrated for VR- versus the text-based task. As predicted, compared with controls, people with depression showed a maladaptive profile: Particularly in the other-agency condition, rather than feeling like verbally attacking their friend, they were prone to feeling like hiding, and punishing themselves. The depression group showed a more pronounced slowing of response times in the other- versus the self-agency condition, which may reflect a stronger ambivalence about externalising blame in depression. Interestingly, feeling like punishing oneself was associated with a history of self-harm but not suicide attempts. Current depression and self-harm history were thus linked with distinctive motivational signatures, paving the way for remote VR-based stratification and treatment.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Remote virtual reality assessment elucidates self-blame-related action tendencies in depression

Fennema

et al. 2022

Preprint

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“…In addition, a doubly Cross-Validated Elastic-net regularised generalised linear model of the gaussian family (dCVnet, Lawrence et al, 2021) was performed to examine the crossvalidated model performance when predicting the prognosis of depression as measured by depressive symptoms at final follow-up assessment. This method uses double crossvalidation and regularisation to guard against overfitting and cross-validation, allowing a more accurate estimate of model performance which is more likely to generalise to independent future samples.…”

Section: Discussionmentioning

confidence: 99%

Virtual reality-assessment of social interactions and prognosis in depression

Lawrence

et al. 2022

Preprint

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Importance: Stratification of depression for personalised treatment is urgently needed to improve poor outcomes. Excessive self-blame-related motivations such as self-punishing tendencies have been proposed to play a key role in the onset and maintenance of depression. Their prognostic role, however, remains elusive. Objective: Use Virtual Reality (VR) to determine whether maladaptive self-blame-related action tendencies are associated with a poor prognosis for depression when treated as usual in primary care (pre-registered: NCT04593537). Design: Remote prospective cohort study (6/2020-6/2021) with four months follow-up. Settings: Online recruitment from primary care and self-report. Participants: n=879 pre-screened, n=164 eligible, n=101 completed baseline (age:18-66 years, mean=32.05±12.32, n=89 female), n=98 the VR-task, and n=93 the follow-up. Main inclusion criteria: at least one antidepressant medication trial and Patient Health Questionnaire-9≥15 at screening; main exclusion criteria: screening above threshold on validated self-report instruments for bipolar or alcohol/substance use disorders. Exposure(s): All participants completed a VR assessment via headsets sent to their homes, as well as online questionnaires to measure their clinical characteristics. Main outcomes and Measures: Primary: Quick Inventory of Depressive Symptomatology self-reported-16 score after four months. Hypotheses in the study were formulated before the data collection and pre-registered. Results: Contrary to our specific prediction, neither feeling like hiding nor creating a distance from oneself was associated with prognosis of depression during the follow-up period in the pre-registered regression model. Using a data-driven principal components analysis of all pre-registered continuous measures, a factor most strongly loading on punishing oneself for other people's wrongdoings (β=.23, p=.01), a baseline symptom factor (β=.30, p=.006) and Maudsley Staging Method treatment-resistance scores (β=.28, p=.009) at baseline predicted higher depressive symptoms after four months. This relationship was confirmed by a significant interaction between feeling like punishing oneself for others' wrongdoings and time of monthly follow-up which was driven by higher depressive symptoms at last follow-up [F(1,84)=6.45, p=.01, partial Eta Squared=0.07] in the subgroup who had reported feeling like punishing themselves at baseline. Our pre-registered statistical learning model prospectively predicted a cross-validated 19% of variance in depressive symptoms. Conclusions and Relevance: Feeling like punishing oneself is a relevant prognostic factor and should therefore be assessed and tackled in personalised care pathways for difficult-to-treat depression.

“…Self-blaming emotions were hypothesized to be associated with action tendencies ( Haidt, 2003 ; Janoff-Bulman et al, 2009 ; Tangney et al, 2007 ) which describe a motivational and cognitive state in which there is an increased tendency to engage in certain goal-related behaviours ( Haidt, 2003 ), such as “feeling like hiding”. Determining whether these action tendencies play a role in the vulnerability to MDD is an essential step not only towards a better understanding of psychopathology, but also towards designing novel interventions and risk prediction markers ( Lawrence et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Maladaptive blame-related action tendencies are associated with vulnerability to major depressive disorder

Lawrence

Journal of Psychiatric Research

et al. 2022

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Biases towards self-blaming emotions, such as self-contempt/disgust, were previously associated with vulnerability to major depressive disorder (MDD). Self-blaming emotions are thought to prompt specific action tendencies (e.g. “feeling like hiding”), which are likely to be more important for psychosocial functioning than the emotions themselves. Systematic investigations, however, of these action tendencies in MDD are lacking. Here, we investigated the role of blame-related action tendencies for MDD vulnerability and their relationship with blame-related emotions. 76 participants with medication-free remitted MDD and 44 healthy control (HC) participants without a history of MDD completed the value-related moral sentiment task, which measured their blame-related emotions during hypothetical social interactions and a novel task to assess their blame-related action tendencies (feeling like hiding, apologising, creating a distance from oneself, attacking oneself, creating a distance from other, attacking other, no action). As predicted, the MDD group showed a maladaptive profile of action tendencies: a higher proneness to feeling like hiding and creating a distance from themselves compared with the HC group. In contrast, feeling like apologising was less common in the MDD than the HC group. Apologising for one's wrongdoing was associated with all self-blaming emotions including shame, guilt, self-contempt/disgust and self-indignation. Hiding was associated with both shame and guilt. Our study shows that MDD vulnerability was associated with specific maladaptive action tendencies which were independent of the type of emotion, thus unveiling novel cognitive markers and neurocognitive treatment targets.