Psychological theories of depressive relapse and recurrence: A systematic review and meta-analysis of prospective studies

Neuroticism/negative emotionality is associated with increased reactivity to uncertain threat in the bed nucleus of the stria terminalis, not the amygdala

Neuroticism/Negative Emotionality (N/NE)-the tendency to experience anxiety, fear, and other negative emotions-is a fundamental dimension of temperament with profound consequences for health, wealth, and wellbeing. Elevated N/NE is associated with a panoply of adverse outcomes, from reduced socioeconomic attainment to psychiatric illness. Animal research suggests that N/NE reflects heightened reactivity to uncertain threat in the bed nucleus of the stria terminalis (BST) and central nucleus of the amygdala (Ce), but the relevance of these discoveries to humans has remained unclear. Here we used a novel combination of psychometric, psychophysiological, and neuroimaging approaches to rigorously test this hypothesis in an ethnoracially diverse, sex-balanced sample of 220 emerging adults selectively recruited to encompass a broad spectrum of N/NE. Cross-validated robust-regression analyses demonstrated that N/NE is preferentially associated with heightened BST activation during the uncertain anticipation of a genuinely distressing threat (aversive multimodal stimulation), whereas N/NE was unrelated to BST activation during certain-threat anticipation, Ce activation during either type of threat anticipation, or BST/Ce reactivity to threat-related faces. It is often assumed that different threat paradigms are interchangeable assays of individual differences in brain function, yet this has rarely been tested. Our results revealed negligible associations between BST/Ce reactivity to the anticipation of threat and the presentation of threat-related faces, indicating that the two tasks are non-fungible. These observations provide a framework for conceptualizing emotional traits and disorders; for guiding the design and interpretation of biobank and other neuroimaging studies of psychiatric risk, disease, and treatment; and for informing mechanistic research.

Stressful life events exhibit complex patterns of associations with depressive symptoms in two population-based samples using network analysis

BACKGROUND

Stressful life events (SLEs) constitute key risk factors for depression. However, previous studies examining associations between SLEs and depression have been limited by focusing on single events, combining events into broad categories, and/or ignoring interrelationships between events in statistical analyses. Network analysis comprises a set of statistical methods well-suited for assessing relationships between multiple variables and can help surpass several limitations of previous studies.

METHODS

We applied network analysis using mixed graphical models combining two large-scale population-based samples and >34,600 randomly sampled adults to investigate the associations between SLEs and current depressive symptoms in the general population.

RESULTS

Numerous SLEs were uniquely associated with specific symptoms. Strong pairwise links were observed between SLEs during the past year and individual symptoms, e.g., between having experienced illness or injury and sleeping problems, having been degraded or humiliated and feeling blue, and between financial problems and hopelessness and being worried and anxious. Several SLEs, such as financial problems, sexual abuse, and having been degraded or humiliated, were associated with symptoms across more than one timepoint. More recent SLEs were generally more strongly associated with depressive symptoms. Several life events were strongly interrelated, such as multiple forms of abuse, and financial problems, unemployment, divorce, and serious illness or injury.

LIMITATIONS

Limitations include a retrospective SLE measure, cross-sectional data, a brief self-report measure of depressive symptoms, and possible attrition bias in the sample.

CONCLUSIONS

Our findings may have implications for public health efforts seeking to improve population mental health.

Identifying relapse predictors in individual participant data with decision trees

BACKGROUND

Depression is a highly common and recurrent condition. Predicting who is at most risk of relapse or recurrence can inform clinical practice. Applying machine-learning methods to Individual Participant Data (IPD) can be promising to improve the accuracy of risk predictions.

METHODS

Individual data of four Randomized Controlled Trials (RCTs) evaluating antidepressant treatment compared to psychological interventions with tapering ([Formula: see text]) were used to identify predictors of relapse and/or recurrence. Ten baseline predictors were assessed. Decision trees with and without gradient boosting were applied. To study the robustness of decision-tree classifications, we also performed a complementary logistic regression analysis.

RESULTS

The combination of age, age of onset of depression, and depression severity significantly enhances the prediction of relapse risk when compared to classifiers solely based on depression severity. The studied decision trees can (i) identify relapse patients at intake with an accuracy, specificity, and sensitivity of about 55% (without gradient boosting) and 58% (with gradient boosting), and (ii) slightly outperform classifiers that are based on logistic regression.

CONCLUSIONS

Decision tree classifiers based on multiple-rather than single-risk indicators may be useful for developing treatment stratification strategies. These classification models have the potential to contribute to the development of methods aimed at effectively prioritizing treatment for those individuals who require it the most. Our results also underline the existing gaps in understanding how to accurately predict depressive relapse.

Psychological interventions for the prevention of depression relapse: systematic review and network meta-analysis

Depression is highly prevalent and easily relapses. Psychological interventions are effective for the prevention of depression relapse. This systematic review and network meta-analysis aimed to compare the efficacy at the same follow-up time points of psychological interventions in depression. We searched PubMed, Embase, and PsycINFO via OVID, and the Cochrane Library published up to December 12, 2021, and PubMed up to July 1, 2022. The primary outcome was depression relapse, considering the same time points that were extracted on survival curves or relapse curves. The study protocol was registered with PROSPERO, CRD42022343327. A total of 2,871 patients were included from 25 RCTs. Mindfulness-based cognitive therapy (MBCT) was significantly better than placebo at the 3 months, the 6 months, and the 9 months at follow-up. Cognitive behavioral therapy (CBT) was significantly better than treatment as usual at the 3 months, the 9 months, the 12 months, and the 15 months at follow-up. CBT was significantly better than placebo at the 21 months and the 24 months at follow-up. Behavioral activation therapy was significantly better than placebo at the 21 months and the 24 months at follow-up. Interpersonal psychotherapy was significantly better than placebo at the 24-month follow-up. All psychological interventions included in the study were significantly better than supportive counseling most of the time. The results were robust in various sensitivity and subgroup analyses. In conclusion, MBCT had a continuous effect in preventing relapse of depression. CBT had the longest but not continuous effect in preventing relapse of depression. The effects of behavioral activation therapy and interpersonal therapy for the prevention of depression appeared late. All psychological interventions included in the study were more effective than supportive counseling. More evidence is needed from large comparative trials that provide long-term follow-up data.

Active learning-based systematic reviewing using switching classification models: the case of the onset, maintenance, and relapse of depressive disorders

Introduction

This study examines the performance of active learning-aided systematic reviews using a deep learning-based model compared to traditional machine learning approaches, and explores the potential benefits of model-switching strategies.

Methods

Comprising four parts, the study: 1) analyzes the performance and stability of active learning-aided systematic review; 2) implements a convolutional neural network classifier; 3) compares classifier and feature extractor performance; and 4) investigates the impact of model-switching strategies on review performance.

Results

Lighter models perform well in early simulation stages, while other models show increased performance in later stages. Model-switching strategies generally improve performance compared to using the default classification model alone.

Discussion

The study's findings support the use of model-switching strategies in active learning-based systematic review workflows. It is advised to begin the review with a light model, such as Naïve Bayes or logistic regression, and switch to a heavier classification model based on a heuristic rule when needed.

Multiple examinations indicated associations between abnormal regional homogeneity and cognitive dysfunction in major depressive disorder

Background

This study aimed to investigate the relationships between regional neural activity and multiple related indicators in patients with major depressive disorder (MDD).

Methods

Forty-two patients and 42 healthy controls (HCs) were enrolled. Pearson/Spearman correlation analyses were applied to examine the associations between abnormal regional homogeneity (ReHo) and different indicators in the patients.

Results

Compared with HCs, patients with MDD had increased ReHo in the left inferior temporal gyrus (ITG) and decreased ReHo values in the left putamen, anterior cingulate cortex (ACC), and precentral gyrus. The ReHo of the left putamen was positively correlated with the PR interval, Repeatable Battery for the Assessment of Neuropsychological Status 4A, and Discriminant analysis (D), and negatively correlated with Ae (block) and Ae (total) in the patients. The ReHo value of the left ACC was positively correlated with the severity of depression, Stroop Color Word Test of C - 2B + 100 in reaction time, and negatively correlated with Ce (Missay) and Perseverative Responses in the patients. The ReHo of the left ITG was positively correlated with the Neuroticism scores and negatively correlated with the Lie scores in the patients.

Conclusion

These results suggested that the decreased ReHo of the salience network might be the underpinning of cognitive impairments in patients with MDD.

What does "staying well" after depression mean? Chronic low grade symptomatology after treatment for depression is common

BACKGROUND

Persistent low grade depression symptoms are common and impairing in major depressive disorder (MDD) yet rarely reported in treatment follow-up studies (Judd et al., 1998a; Kennedy et al., 2004), suggesting that extant sustained remission rates may not reflect this important clinical feature. Furthermore, no long-term MDD treatment follow-up study has reported on quality of life ratings across functioning levels and years throughout the follow-up period, thus the severity, breadth, and persistence of functional impairment remain unclear. Accordingly, the current study evaluated the course of MDD with consideration of low grade depressive symptomatology and holistic features (e.g., quality of life).

METHODS

We report long-term (9-14 years) follow-up data from individuals with MDD (N = 37) who underwent either Cognitive Therapy (CBT) or a course of selective serotonin reuptake inhibitor (SSRI) treatment. Patients provided retrospective reports of depression symptoms and quality of life in the years following treatment.

RESULTS

Chronic depression symptoms (most often mild in severity) and decreased quality of life in multiple domains are frequent and suggest poorer sustained remission rates than previously observed in the literature.

LIMITATIONS

Study limitations include small sample size recruited via convenience sampling methods.

CONCLUSIONS

Findings support a conceptualization of depression recovery that entails persistent symptoms and vulnerabilities. Clinical recommendations are provided for discussing these features of depression recovery with patients.

Twelve-month follow-up of a randomised clinical trial of a brief group psychological intervention for common mental disorders in Syrian refugees in Jordan

AIMS

There is increasing evidence that brief psychological interventions delivered by lay providers can reduce common mental disorders in the short-term. This study evaluates the longer-term impact of a brief, lay provider delivered group psychological intervention (Group Problem Management Plus; gPM+) on the mental health of refugees and their children's mental health.

METHODS

This single-blind, parallel, controlled trial randomised 410 adult Syrians in Azraq Refugee Camp in Jordan who screened positive for distress and impaired functioning to either five sessions of gPM+ or enhanced usual care (EUC). Primary outcomes were scores on the Hopkins Symptom Checklist-25 (HSCL-25; depression and anxiety scales) assessed at baseline, 6 weeks, 3 months and 12 months Secondary outcomes included disability, posttraumatic stress, personally identified problems, prolonged grief, prodromal psychotic symptoms, parenting behaviour and children's mental health.

RESULTS

Between 15 October 2019 and 2 March 2020, 204 participants were assigned to gPM + and 206 to EUC, and 307 (74.9%) were retained at 12 months. Intent-to-treat analyses indicated that although participants in gPM + had greater reductions in depression at 3 months, at 12 months there were no significant differences between treatment arms on depression (mean difference -0.9, 95% CI -3.2 to 1.3; p = 0.39) or anxiety (mean difference -1.7, 95% CI -4.8 to -1.3; p = 0.06). There were no significant differences between conditions for secondary outcomes except that participants in gPM + had greater increases in positive parenting.

CONCLUSIONS

The short-term benefits of a brief, psychological programme delivered by lay providers may not be sustained over longer time periods, and there is a need for sustainable programmes that can prolong benefits gained through gPM + .

Revisiting the theoretical and methodological foundations of depression measurement

Depressive disorders are among the leading causes of global disease burden, but there has been limited progress in understanding the causes and treatments for these disorders. In this Perspective, we suggest that such progress crucially depends on our ability to measure depression. We review the many problems with depression measurement, including limited evidence of validity and reliability. These issues raise grave concerns about common uses of depression measures, such as diagnosis or tracking treatment progress. We argue that shortcomings arise because depression measurement rests on shaky methodological and theoretical foundations. Moving forward, we need to break with the field's tradition that has, for decades, divorced theories about depression from how we measure it. Instead, we suggest that epistemic iteration, an iterative exchange between theory and measurement, provides a crucial avenue for depression measurement to progress.

Neural basis of positive and negative emotion regulation in remitted depression

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RRMDD patients show deviant uninstructed neural emotion regulation.

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This is reflected in residual problems in daily strategy use.

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RRMDD patients are capable to engage frontolimbic areas upon instructed reappraisal.

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Neural regulation capacity is related to inadequate rumination.

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Positive, next to negative, affect is highly relevant for understanding vulnerability.

The recurrent nature of Major Depressive Disorder (MDD) necessitates a better understanding of mechanisms facilitating relapse. MDD has often been associated with abnormal emotion regulation, underpinned by aberrant interactions between the prefrontal cortex and subcortical areas. We assessed whether neural regulation abnormalities remain after remission and relate to emotion regulation problems in daily life.

At the baseline measurement of a randomized controlled trial, an emotion regulation task was performed during fMRI scanning by 46 remitted recurrent (rrMDD) patients and 24 healthy controls. We assessed both fMRI peak activity and the temporal dynamics of the neural response during passive attendance and explicit regulation of positive and negative emotions. Furthermore, we assessed regulation strategy use in daily life using questionnaires, and attentional biases using a modified attentional dot-probe task.

RrMDD patients showed lower activation and different temporal dynamics in occipital, parietal, and prefrontal brain regions during passive attendance of emotional material compared to healthy controls. During explicit downregulation of negative emotions, no group differences were found. However, during explicit upregulation of positive emotions, rrMDD patients showed a different neural response over time in the insula. Behaviourally, rrMDD patients were characterized by dysfunctional regulation strategies in daily life. Within rrMDD patients, rumination was associated with activation within a limbic- prefrontal network.

After remission, immediate emotional processing seems unaffected, but regulatory abnormalities remain, especially uninstructed and in daily life. Abnormal insula activation during positive upregulation suggests decreased monitoring of positive emotions. The relation between inadequate rumination and brain activity during emotion regulation suggests that regulation of both positive and negative affect is important in understanding neurocognitive underpinnings of resilience.

Longitudinal outcome evaluations of Interdisciplinary Multimodal Pain Treatment programmes for patients with chronic primary musculoskeletal pain: A systematic review and meta-analysis

BACKGROUND AND OBJECTIVES

Although Interdisciplinary Multimodal Pain Treatment (IMPT) programmes share a biopsychosocial approach to increase the wellbeing of patients with chronic pain, substantial variation in content and duration have been reported. In addition, it is unclear to what extent any favourable health outcomes are maintained over time. Therefore, our first aim was to identify and analyse the change over time of patient-related outcome measures in cohorts of patients who participated in IMPT programmes. Our second aim was to acquire insight into the heterogeneity of IMPT programmes.

DATABASES AND DATA TREATMENT

The study protocol was registered in Prospero under CRD42018076093. We searched Medline, Embase, PsycInfo and Cinahl from inception to May 2020. All study selection, data extraction and risk of bias assessments were independently performed by two researchers. Study cohorts were eligible if they included adult patients with chronic primary musculoskeletal pain for at least 3 months. We assessed the change over time, by calculating pre-post, post-follow-up and pre-follow-up contrasts for seven different patient-reported outcome domains. To explore the variability between the IMPT programmes, we summarized the patient characteristics and treatment programmes using the intervention description and replication checklist.

RESULTS

The majority of the 72 included patient cohorts significantly improved during treatment. Importantly, this improvement was generally maintained at follow-up. In line with our expectations and with previous studies, we observed substantial methodological and statistical heterogeneity.

CONCLUSIONS

This study shows that participation in an IMPT programme is associated with considerable improvements in wellbeing that are generally maintained at follow-up. The current study also found substantial heterogeneity in dose and treatment content, which suggests different viewpoints on how to optimally design an IMPT programme.

SIGNIFICANCE

The current study provides insight into the different existing approaches regarding the dose and content of IMPT programs. This analysis contributes to an increased understanding of the various approaches by which a biopsychosocial perspective on chronic pain can be translated to treatment programs. Furthermore, despite theoretical and empirical assertions regarding the difficulty to maintain newly learned health behaviors over time, the longitudinal analysis of health outcomes did not find a relapse pattern for patients who participated in IMPT programs.

Psychopathological networks: Theory, methods and practice

In recent years, network approaches to psychopathology have sparked much debate and have had a significant impact on how mental disorders are perceived in the field of clinical psychology. However, there are many important challenges in moving from theory to empirical research and clinical practice and vice versa. Therefore, in this article, we bring together different points of view on psychological networks by methodologists and clinicians to give a critical overview on these challenges, and to present an agenda for addressing these challenges. In contrast to previous reviews, we especially focus on methodological issues related to temporal networks. This includes topics such as selecting and assessing the quality of the nodes in the network, distinguishing between- and within-person effects in networks, relating items that are measured at different time scales, and dealing with changes in network structures. These issues are not only important for researchers using network models on empirical data, but also for clinicians, who are increasingly likely to encounter (person-specific) networks in the consulting room.

Psychological factors for the onset of depression: a meta-analysis of prospective studies

OBJECTIVES

A comprehensive overview of the evidence for factors derived from leading psychological theories of the onset of major depressive disorder (MDD) that underpin psychological interventions is scarce . We aimed to systematically investigate the prospective evidence for factors derived from the behavioural, cognitive, diathesis-stress, psychodynamic and personality-based theories for the first onset of MDD.

DESIGN

Systematic review and meta-analysis.

METHODS

Databases PubMed, PsycINFO, Cochrane and Embase and published articles were systematically searched from inception up to August 2019. Prospective, longitudinal studies that investigated theory-derived factors before the first onset of MDD, established by a clinical interview, were included. Screening, selection and data extraction of articles were conducted by two screeners. The Grading of Recommendations Assessment, Development and Evaluation criteria were used to estimate level of confidence and risk of bias. Meta-analysis was conducted using random-effects models and mixed-method subgroup analyses.

PRIMARY AND SECONDARY OUTCOME MEASURES

Effect size of a factor predicting the onset of MDD (OR, risk ratio or HR).

RESULTS

From 42 133 original records published to August 2019, 26 studies met the inclusion criteria. Data were only available for the cognitive (n=6585) and personality-based (n=14 394) theories. Factors derived from cognitive theories and personality-based theories were related to increased odds of MDD onset (pooled OR=2.12, 95% CI: 1.12 to 4.00; pooled OR=2.43, 95% CI: 1.41 to 4.19). Publication bias and considerable heterogeneity were observed.

CONCLUSION

There is some evidence that factors derived from cognitive and personality-based theories indeed predict the onset of MDD (ie, dysfunctional attitudes and negative emotionality). There were no studies that prospectively studied factors derived from psychodynamic theories and not enough studies to examine the robust evidence for behavioural and diathesis-stress theories. Overall, the prospective evidence for psychological factors of MDD is limited, and more research on the leading psychological theories is needed.

PROSPERO REGISTRATION NUMBER

CRD42017073975.

Metabolic features of recurrent major depressive disorder in remission, and the risk of future recurrence

Recurrent major depressive disorder (rMDD) is a relapsing-remitting disease with high morbidity and a 5-year risk of recurrence of up to 80%. This was a prospective pilot study to examine the potential diagnostic and prognostic value of targeted plasma metabolomics in the care of patients with rMDD in remission. We used an established LC-MS/MS platform to measure 399 metabolites in 68 subjects with rMDD (n = 45 females and 23 males) in antidepressant-free remission and 59 age- and sex-matched controls (n = 40 females and 19 males). Patients were then followed prospectively for 2.5 years. Metabolomics explained up to 43% of the phenotypic variance. The strongest biomarkers were gender specific. 80% of the metabolic predictors of recurrence in both males and females belonged to 6 pathways: (1) phospholipids, (2) sphingomyelins, (3) glycosphingolipids, (4) eicosanoids, (5) microbiome, and (6) purines. These changes traced to altered mitochondrial regulation of cellular redox, signaling, energy, and lipid metabolism. Metabolomics identified a chemical endophenotype that could be used to stratify rrMDD patients at greatest risk for recurrence with an accuracy over 0.90 (95%CI = 0.69-1.0). Power calculations suggest that a validation study of at least 198 females and 198 males (99 cases and 99 controls each) will be needed to confirm these results. Although a small study, these results are the first to show the potential utility of metabolomics in assisting with the important clinical challenge of prospectively identifying the patients at greatest risk of recurrence of a depressive episode and those who are at lower risk.

Depression alters the circadian pattern of online activity

Human sleep/wake cycles follow a stable circadian rhythm associated with hormonal, emotional, and cognitive changes. Changes of this cycle are implicated in many mental health concerns. In fact, the bidirectional relation between major depressive disorder and sleep has been well-documented. Despite a clear link between sleep disturbances and subsequent disturbances in mood, it is difficult to determine from self-reported data which specific changes of the sleep/wake cycle play the most important role in this association. Here we observe marked changes of activity cycles in millions of twitter posts of 688 subjects who explicitly stated in unequivocal terms that they had received a (clinical) diagnosis of depression as compared to the activity cycles of a large control group (n = 8791). Rather than a phase-shift, as reported in other work, we find significant changes of activity levels in the evening and before dawn. Compared to the control group, depressed subjects were significantly more active from 7 PM to midnight and less active from 3 to 6 AM. Content analysis of tweets revealed a steady rise in rumination and emotional content from midnight to dawn among depressed individuals. These results suggest that diagnosis and treatment of depression may focus on modifying the timing of activity, reducing rumination, and decreasing social media use at specific hours of the day.

Prospective biomarkers of major depressive disorder: a systematic review and meta-analysis

Leading biological hypotheses propose that biological changes may underlie major depressive disorder onset and relapse/recurrence. Here, we investigate if there is prospective evidence for biomarkers derived from leading theories. We focus on neuroimaging, gastrointestinal factors, immunology, neurotrophic factors, neurotransmitters, hormones, and oxidative stress. Searches were performed in Pubmed, Embase and PsychInfo for articles published up to 06/2019. References and citations of included articles were screened to identify additional articles. Inclusion criteria were having an MDD diagnosis as outcome, a biomarker as predictor, and prospective design search terms were formulated accordingly. PRISMA guidelines were applied. Meta-analyses were performed using a random effect model when three or more comparable studies were identified, using a random effect model. Our search resulted in 67,464 articles, of which 75 prospective articles were identified on: Neuroimaging (N = 24), Gastrointestinal factors (N = 1), Immunology (N = 8), Neurotrophic (N = 2), Neurotransmitters (N = 1), Hormones (N = 39), Oxidative stress (N = 1). Meta-analyses on brain volumes and immunology markers were not significant. Only cortisol (N = 19, OR = 1.294, p = 0.024) showed a predictive effect on onset/relapse/recurrence of MDD, but not on time until MDD onset/relapse/recurrence. However, this effect disappeared when studies including participants with a baseline clinical diagnosis were removed from the analyses. Other studies were too heterogeneous to compare. Thus, there is a lack of evidence for leading biological theories for onset and maintenance of depression. Only cortisol was identified as potential predictor for MDD, but results are influenced by the disease state. High-quality (prospective) studies on MDD are needed to disentangle the etiology and maintenance of MDD.