Quality of life after response to acute-phase cognitive therapy for recurrent depression

Evaluating a Comprehensive Model of Euthymia

INTRODUCTION

In research and treatment of mood disorders, "euthymia" traditionally denotes the absence of clinically significant mood disturbance. A newer, expanded definition of euthymia also includes positive affect and psychological well-being.

OBJECTIVE

We aimed to test this comprehensive model of euthymia and estimate the coherence and predictive power of each factor in the model.

METHODS

Community-dwelling adults (N = 601), including both mental health outpatients and non-patients at high risk for personality pathology, completed a battery of interviews and questionnaires at time 1. Most (n = 497) were reassessed on average 8 months later (time 2). We modeled euthymia using standard mood, personality, and psychosocial functioning assessments rather than measures designed specifically for euthymia.

RESULTS

The hypothesized model of euthymia was supported by confirmatory factor analysis: specific measures loaded on three lower order factors (mood disturbance, positive affect, and psychological well-being) that reflected general euthymia at time 1. Each factor (general euthymia plus lower order factors) demonstrated moderately strong concurrent (time 1) and predictive (time 1-2) correlations with outcomes, including employment status, income, mental health treatment consumption, and disability. Compared to positive affect and psychological well-being, mood disturbance had stronger incremental (i.e., nonoverlapping) relations with these outcomes.

CONCLUSIONS

Support for a comprehensive model of euthymia reinforces efforts to improve assessment and treatment of mood and other disorders. Beyond dampening of psychological distress, euthymia-informed treatment goals encompass full recovery, including enjoyment and meaning in life.

Cognitive behavior therapy for adult depressive disorders in routine clinical care: A systematic review and meta-analysis

BACKGROUND

Different cognitive behavioral therapies (CBT) have strong research support for treatment of adult depressive disorders (DD). Given the scarcity of knowledge about the performance of CBT in routine clinical care, a systematic review and meta-analysis of CBT for adults with DD treated in this context was conducted.

METHODS

Published studies until the end of September 2022, were systematically searched in Ovid MEDLINE, Embase OVID, and PsycINFO. The effectiveness of CBT, methodological quality, and moderators of treatment outcome were examined, and benchmarked by meta-analytically comparing with efficacy studies for DD.

RESULTS

Twenty-eight studies, comprising 3734 participants, were included. Large within-group effect sizes (ES) were obtained for DD-severity at post-treatment, and follow-up, on average 8 months post-treatment. Benchmarking analysis showed that effectiveness studies had very similar ESs as efficacy studies at post-treatment (1.51 vs. 1.71) and follow-up (1.71 vs. 1.85). Remission rates were also very similar; effectiveness studies 44 % and 46 %, efficacy studies 45 % and 46 %, at post-treatment and follow-up, respectively.

LIMITATIONS

Only studies published in English-language peer-reviewed journals were included and the use of pre-post ES in the meta-analyses could contribute to biased outcomes.

CONCLUSIONS

CBT for DD is an effective treatment when delivered in routine clinical care and the outcomes of effectiveness studies for DD are comparable to the effects obtained in efficacy studies.

PROSPERO REGISTRATION

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Biomarkers in Psychiatric Drug Development: From Precision Medicine to Novel Therapeutics

Burden of psychiatric disorders is compounded by their wide prevalence as well as the limited efficacy of currently available treatments and the current approaches for prescribing these treatments. The selection of treatments continues to be subjective and often results in a trial-and-error approach. Emerging research suggests that biological markers (or biomarkers) can be used to develop precision medicine approaches for psychiatric disorders. Furthermore, the biomarkers also promise to elucidate the underlying pathophysiological mechanisms which in turn can be used to develop novel therapeutic treatments. In this chapter we have focused on mood disorders and reviewed studies on electroencephalography (EEG), magnetic resonance imaging (MRI), and blood-based biomarkers that can guide selection of one treatment versus another (treatment-selection biomarker) as well as biomarkers that can guide the development of novel therapeutics. These studies suggest that the use of objective physiological data is poised to alter the landscape of psychiatric diagnosis and treatment. However, practical and economic barriers remain as major hurdles. The key to finding such translational diagnostic and therapeutic biomarkers is a better understanding of the underlying pathophysiology, and despite the tremendous advances in neuroscience, it is clear there remains much left to be elucidated.

Low predictive power of clinical features for relapse prediction after antidepressant discontinuation in a naturalistic setting

The risk of relapse after antidepressant medication (ADM) discontinuation is high. Predictors of relapse could guide clinical decision-making, but are yet to be established. We assessed demographic and clinical variables in a longitudinal observational study before antidepressant discontinuation. State-dependent variables were re-assessed either after discontinuation or before discontinuation after a waiting period. Relapse was assessed during 6 months after discontinuation. We applied logistic general linear models in combination with least absolute shrinkage and selection operator and elastic nets to avoid overfitting in order to identify predictors of relapse and estimated their generalisability using cross-validation. The final sample included 104 patients (age: 34.86 (11.1), 77% female) and 57 healthy controls (age: 34.12 (10.6), 70% female). 36% of the patients experienced a relapse. Treatment by a general practitioner increased the risk of relapse. Although within-sample statistical analyses suggested reasonable sensitivity and specificity, out-of-sample prediction of relapse was at chance level. Residual symptoms increased with discontinuation, but did not relate to relapse. Demographic and standard clinical variables appear to carry little predictive power and therefore are of limited use for patients and clinicians in guiding clinical decision-making.

Outcomes of student trainee-delivered cognitive-behavioral therapy (CBT) on internalizing symptoms, CBT skills, and life satisfaction

Increased quality of life (QoL) is rated by patients as a primary factor in determining recovery from psychopathology. Cognitive-behavioral therapies (CBTs) are the most well-researched psychotherapies for internalizing disorders and appear effective at reducing symptoms even when delivered by trainees. Existing research suggests that the effects of CBTs on QoL are more modest than their effects on symptoms. However, little is known about the effects of trainee-delivered CBT on life satisfaction, a subjective measure of QoL. We analyzed data from 93 clients treated by students (n=23) in a graduate-level training clinic using an intent-to-treat approach, completers case analyses, and random forest imputation. Across methods of handling missing data, improvements in anxiety, depression, and CBT skills were more marked than improvements in QoL. Exploratory analyses suggested baseline life satisfaction was the strongest predictor of end-of-treatment life satisfaction. Future research should explore alternatives to "standard" CBT for clients with low life satisfaction.