Self-blame in major depression: a randomised pilot trial comparing fMRI neurofeedback with self-guided psychological strategies.

BACKGROUND: Overgeneralised self-blame and worthlessness are key symptoms of major depressive disorder (MDD) and have previously been associated with self-blame-selective changes in connectivity between right superior anterior temporal lobe (rSATL) and subgenual frontal cortices. Another study showed that remitted MDD patients were able to modulate this neural signature using functional magnetic resonance imaging (fMRI) neurofeedback training, thereby increasing their self-esteem. The feasibility and potential of using this approach in symptomatic MDD were unknown. METHOD: This single-blind pre-registered randomised controlled pilot trial probed a novel self-guided psychological intervention with and without additional rSATL-posterior subgenual cortex (BA25) fMRI neurofeedback, targeting self-blaming emotions in people with insufficiently recovered MDD and early treatment-resistance (n = 43, n = 35 completers). Participants completed three weekly self-guided sessions to rebalance self-blaming biases. RESULTS: As predicted, neurofeedback led to a training-induced reduction in rSATL-BA25 connectivity for self-blame v. other-blame. Both interventions were safe and resulted in a 46% reduction on the Beck Depression Inventory-II, our primary outcome, with no group differences. Secondary analyses, however, revealed that patients without DSM-5-defined anxious distress showed a superior response to neurofeedback compared with the psychological intervention, and the opposite pattern in anxious MDD. As predicted, symptom remission was associated with increases in self-esteem and this correlated with the frequency with which participants employed the psychological strategies in daily life. CONCLUSIONS: These findings suggest that self-blame-rebalance neurofeedback may be superior over a solely psychological intervention in non-anxious MDD, although further confirmatory studies are needed. Simple self-guided strategies tackling self-blame were beneficial, but need to be compared against treatment-as-usual in further trials. https://doi.org/10.1186/ISRCTN10526888.

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

BACKGROUND: Overgeneralized self-blaming emotions, such as self-disgust, are core symptoms of major depressive disorder and prompt specific actions (i.e., action tendencies), which are more functionally relevant than the emotions themselves. We have recently shown, using a novel cognitive task, that when feeling self-blaming emotions, maladaptive action tendencies (feeling like hiding and feeling like creating a distance from oneself) and an overgeneralized perception of control are characteristic of major depressive disorder, even after remission of symptoms. Here, we probed the potential of this cognitive signature, and its combination with previously employed functional magnetic resonance imaging (fMRI) measures, to predict individual recurrence risk. For this purpose, we developed a user-friendly hybrid machine/statistical learning tool, which we make freely available. METHODS: A total of 52 medication-free patients with remitted major depressive disorder, who had completed the action tendencies task and our self-blame fMRI task at baseline, were followed up clinically over 14 months to determine recurrence. Prospective prediction models included baseline maladaptive self-blame-related action tendencies and anterior temporal fMRI connectivity patterns across a set of frontolimbic a priori regions of interest, as well as including established clinical and standard psychological predictors. Prediction models used elastic net regularized logistic regression with nested 10-fold cross-validation. RESULTS: Cross-validated discrimination was highly promising (area under the receiver-operating characteristic curve ≥ 0.86), and positive predictive values over 80% were achieved when including fMRI in multimodal models, but only up to 71% (area under the receiver-operating characteristic curve ≤ 0.74) when solely relying on cognitive and clinical measures. CONCLUSIONS: This study shows the high potential of multimodal signatures of self-blaming biases to predict recurrence risk at an individual level and calls for external validation in an independent sample.

Development and validation of the Maudsley Modified Patient Health Questionnaire (MM-PHQ-9).

BACKGROUND: The Patient Health Questionnaire-9 (PHQ-9) is a widely used measure of depression in primary care. It was, however, originally designed as a diagnostic screening tool, and not for measuring change in response to antidepressant treatment. Although the Quick Inventory of Depressive Symptomology (QIDS-SR-16) has been extensively validated for outcome measurement, it is poorly adopted in UK primary care, and, although free for clinicians, has licensing restrictions for healthcare organisation use. AIMS: We aimed to develop a modified version of the PHQ-9, the Maudsley Modified PHQ-9 (MM-PHQ-9), for tracking symptom changes in primary care. We tested the measure's validity, reliability and factor structure. METHOD: A sample of 121 participants was recruited across three studies, and comprised 78 participants with major depressive disorder and 43 controls. MM-PHQ-9 scores were compared with the QIDS-SR-16 and Clinical Global Impressions improvement scale, for concurrent validity. Internal consistency of the scale was assessed, and principal component analysis was conducted to determine the items' factor structure. RESULTS: The MM-PHQ-9 demonstrated good concurrent validity with the QIDS-SR-16, and excellent internal consistency. Sensitivity to change over a 14-week period was d = 0.41 compared with d = 0.61 on the QIDS-SR-16. Concurrent validity between the paper and mobile app versions of the MM-PHQ-9 was r = 0.67. CONCLUSIONS: These results indicate that the MM-PHQ-9 is a valid and reliable measure of depressive symptoms in paper and mobile app format, although further validation is required. The measure was sensitive to change, demonstrating suitability for use in routine outcome assessment.

What do we know about long-term treatment outcomes for severe depressive disorders?

In a recent issue of BJPsych Open, McPherson & Hengartner (see https://doi.org/10.1192/bjo.2019.65) reviewed 11 trials examining psychological and pharmacological treatment outcomes for chronic or treatment-resistant depression. They concluded that when assessed in the long term, antidepressants become less effective whereas psychological therapies become more effective. We argue that the evidence does not support this; indeed, most of the studies reviewed do not directly compare antidepressant with psychological therapy treatments and there is little consistency between them in terms of populations and interventions examined. The issue of long-term outcomes is key for optimising clinical guidelines and deserves more intensive research and scrutiny to improve patient response in routine practice.