Working mechanisms of the use and acceptability of ecological momentary interventions: a realist evaluation of a guided self-help ecological momentary intervention targeting self-esteem.

BACKGROUND: Technology improves accessibility of psychological interventions for youth. An ecological momentary intervention (EMI) is a digital intervention geared toward intervening in daily life to enhance the generalizability and ecological validity, and to be able to intervene in moments most needed. Identifying working mechanisms of the use of ecological momentary interventions might generate insights to improve interventions. METHODS: The present study investigates the working mechanisms of the use and acceptability of an ecological momentary intervention, named SELFIE, targeting self-esteem in youth exposed to childhood trauma, and evaluates under what circumstances these mechanisms of use and acceptability do or do not come into play. A realist evaluation approach was used for developing initial program theories (data: expert interviews and a stakeholders focus group), and subsequently testing (data: 15 interviews with participants, a focus group with therapists, debriefing questionnaire), and refining them. RESULTS: The SELFIE intervention is offered through a smartphone application enabling constant availability of the intervention and thereby increasing accessibility and feasibility. When the intervention was offered on their personal smartphone, this enhanced a sense of privacy and less hesitance in engaging with the app, leading to increased disclosure and active participation. Further, the smartphone application facilitates the practice of skills in daily life, supporting the repeated practice of exercises in different situations leading to the generalizability of the effect. Buffering against technical malfunction seemed important to decrease its possible negative effects. CONCLUSIONS: This study enhanced our understanding of possible working mechanisms in EMIs, such as the constant availability supporting increased accessibility and feasibility, for which the use of the personal smartphone was experienced as a facilitating context. Hereby, the current study contributes to relatively limited research in this field. For the field to move forward, mechanisms of use, and acceptability of EMIs need to be understood. It is strongly recommended that alongside efficacy trials of an EMI on specific target mechanisms, a process evaluation is conducted investigating the working mechanisms of use. TRIAL REGISTRATION: The current paper reports on a realist evaluation within the SELFIE trial (Netherlands Trial Register NL7129 (NTR7475)).

A Dynamical Systems View of Psychiatric Disorders-Theory: A Review.

Importance: Psychiatric disorders may come and go with symptoms changing over a lifetime. This suggests the need for a paradigm shift in diagnosis and treatment. Here we present a fresh look inspired by dynamical systems theory. This theory is used widely to explain tipping points, cycles, and chaos in complex systems ranging from the climate to ecosystems. Observations: In the dynamical systems view, we propose the healthy state has a basin of attraction representing its resilience, while disorders are alternative attractors in which the system can become trapped. Rather than an immutable trait, resilience in this approach is a dynamical property. Recent work has demonstrated the universality of generic dynamical indicators of resilience that are now employed globally to monitor the risks of collapse of complex systems, such as tropical rainforests and tipping elements of the climate system. Other dynamical systems tools are used in ecology and climate science to infer causality from time series. Moreover, experiences in ecological restoration confirm the theoretical prediction that under some conditions, short interventions may invoke long-term success when they flip the system into an alternative basin of attraction. All this implies practical applications for psychiatry, as are discussed in part 2 of this article. Conclusions and Relevance: Work in the field of dynamical systems points to novel ways of inferring causality and quantifying resilience from time series. Those approaches have now been tried and tested in a range of complex systems. The same tools may help monitoring and managing resilience of the healthy state as well as psychiatric disorders.

A Dynamical Systems View of Psychiatric Disorders-Practical Implications: A Review.

Importance: Dynamical systems theory is widely used to explain tipping points, cycles, and chaos in complex systems ranging from the climate to ecosystems. It has been suggested that the same theory may be used to explain the nature and dynamics of psychiatric disorders, which may come and go with symptoms changing over a lifetime. Here we review evidence for the practical applicability of this theory and its quantitative tools in psychiatry. Observations: Emerging results suggest that time series of mood and behavior may be used to monitor the resilience of patients using the same generic dynamical indicators that are now employed globally to monitor the risks of collapse of complex systems, such as tropical rainforest and tipping elements of the climate system. Other dynamical systems tools used in ecology and climate science open ways to infer personalized webs of causality for patients that may be used to identify targets for intervention. Meanwhile, experiences in ecological restoration help make sense of the occasional long-term success of short interventions. Conclusions and Relevance: Those observations, while promising, evoke follow-up questions on how best to collect dynamic data, infer informative timescales, construct mechanistic models, and measure the effect of interventions on resilience. Done well, monitoring resilience to inform well-timed interventions may be integrated into approaches that give patients an active role in the lifelong challenge of managing their resilience and knowing when to seek professional help.

Development and validation of the Autonomy Scale Amsterdam.

This paper describes the development and validation of the Autonomy Scale Amsterdam (ASA). We propose that a new measure of autonomy is needed and, as such, we developed and validated an autonomy scale relevant for psychiatry. Based on literature, an expert meeting and three samples of the general population (N = 298, N = 207, N = 309) we provide evidence (a) that supports a 6-factor structure model as a better fit than alternative models with a high reliability to capture the concept of autonomy consisting of: Self-integration, Engagement with life, Goal-directedness, Self-control, External constraints and Social support, (b) for the scale's convergent and discriminant validity with constructs in autonomy's nomological network and (c) for the scale's criterion validity with well-established well-being outcomes, and (d) that the measure is not redundant with a prior measure of autonomy, the autonomy-connectedness scale, and demonstrates incremental validity in the prediction of mental health over and above an existing measure of autonomy. Taken together, the results suggest that the ASA is a useful scale that shows positive evidence of psychometric quality to measure autonomy in a sample of the general population (total N = 856), accounting for a unique predictive value over and above an existing measure of autonomy concerning several mental health outcomes. The ASA can further help our understanding of the role of autonomy in mental disorders.

Internet-based behavioural activation therapy versus online psychoeducation for self-reported suicidal ideation in individuals with depression in Indonesia: a secondary analysis of an RCT.

BACKGROUND: Southeast Asia has the highest suicide mortality worldwide. To improve our knowledge on the effectiveness of interventions for suicidal ideation (SI) in individuals with depression in Indonesia, we conducted a secondary analysis of a randomised controlled trial. OBJECTIVE: We explored whether an internet-based behavioural activation (BA) intervention ('Guided Act and Feel Indonesia' (GAF-ID)) was superior in targeting SI compared with online-delivered psychoeducation (PE). METHODS: In total, 313 participants were randomised between treatment allocation. The SI item of the Patient Health Questionnaire-9 was the primary outcome measure. Mediation analyses were conducted to identify if BA at week 10 mediated the relationship between intervention and SI at week 24. FINDINGS: The GAF-ID intervention was not superior in reducing SI compared with online minimal PE at week 10 (OR 0.61, 95% CI (0.37 to 1.01)), nor at week 24 (OR 0.84, 95% CI (0.47 to 1.52)). SI at week 24 was not mediated by BA at week 10 (b=-0.03, 95% CI (-0.05 to 0.00), p=0.07). CONCLUSIONS: In individuals with depression in Indonesia, the GAF-ID intervention was not superior in reducing self-reported SI compared with PE. Also, the association between treatment condition and SI at week 24 was not mediated via BA at week 10. CLINICAL IMPLICATIONS: This study supports the need for further research on the efficacy of psychological treatments targeting SI in the Southeast Asia context.

Understanding mechanisms of depression prevention: study protocol of a randomized cross-over trial to investigate mechanisms of mindfulness and positive fantasizing as intervention techniques for reducing perseverative cognition in remitted depressed individuals.

BACKGROUND: Major Depressive Disorder (MDD) is one of the most prevalent psychiatric disorders, and involves high relapse rates in which persistent negative thinking and rumination (i.e., perseverative cognition [PC]) play an important role. Positive fantasizing and mindfulness are common evidence-based psychological interventions that have been shown to effectively reduce PC and subsequent depressive relapse. How the interventions cause changes in PC over time, is unknown, but likely differ between the two. Whereas fantasizing may change the valence of thought content, mindfulness may operate through disengaging from automatic thought patterns. Comparing mechanisms of both interventions in a clinical sample and a non-clinical sample can give insight into the effectivity of interventions for different individuals. The current study aims to 1) test whether momentary psychological and psychophysiological indices of PC are differentially affected by positive fantasizing versus mindfulness-based interventions, 2) test whether the mechanisms of change by which fantasizing and mindfulness affect PC differ between remitted MDD versus never-depressed (ND) individuals, and 3) explore potential moderators of the main effects of the two interventions (i.e., what works for whom). METHODS: In this cross-over trial of fantasizing versus mindfulness interventions, we will include 50 remitted MDD and 50 ND individuals. Before the start of the measurements, participants complete several individual characteristics. Daily-life diary measures of thoughts and feelings (using an experience sampling method), behavioural measures of spontaneous thoughts (using the Sustained Attention to Response Task), actigraphy, physiological measures (impedance cardiography, electrocardiography, and electroencephalogram), and measures of depressive mood (self-report questionnaires) are performed during the week before (pre-) the interventions and the week during (peri-) the interventions. After a wash-out of at least one month, pre- and peri-intervention measures for the second intervention are repeated. DISCUSSION: This is the first study integrating self-reports, behavioural-, and physiological measures capturing dynamics at multiple time scales to examine the differential mechanisms of change in PC by psychological interventions in individuals remitted from multiple MDD episodes and ND individuals. Unravelling how therapeutic techniques affect PC in remitted individuals might generate insights that allows development of personalised targeted relapse prevention interventions. TRIAL REGISTRATION: ClinicalTrials.gov: NCT06145984, November 16, 2023.

Implementation of 'IBD-Specific Cognitive Behavioural Therapy' for Patients with Inflammatory Bowel Diseases with Poor Mental Quality of Life, Anxiety and Depression.

This paper describes the implementation of inflammatory bowel disease (IBD)-specific cognitive behavioural therapy (CBT) for IBD patients with poor quality of life (QoL), anxiety and depression, in four hospitals in the Netherlands. Treatment outcomes were compared with those of a previously published randomized control trial (RCT) of 'IBD-specific CBT', following a benchmark strategy. Primary outcome was IBD-specific QoL (IBDQ) completed before and after CBT, secondary outcomes were anxiety and depressive symptoms (HADS, CES-D). Semi-structured interviews were conducted among a pilot of gastroenterologists, nurse specialists and psychologists to evaluate 'IBD-specific CBT'. 94 patients started treatment (280 screened). At follow-up, 63 participants (67% compared to 81% in the RCT benchmark) completed the IBDQ. Treatment effect sizes of the implementation study were comparable and slightly larger than those of RCT benchmark. Gastroenterologists, IBD nurses and psychologists found CBT necessary for IBD patients with poor QoL, depression and/or anxiety disorders. 'IBD-specific CBT' can be successfully implemented. Regular supervision of psychologists performing 'IBD-specific CBT' treatment is needed.

Transdiagnostic Ecological Momentary Intervention for Improving Self-Esteem in Youth Exposed to Childhood Adversity: The SELFIE Randomized Clinical Trial.

Importance: Targeting low self-esteem in youth exposed to childhood adversity is a promising strategy for preventing adult mental disorders. Ecological momentary interventions (EMIs) allow for the delivery of youth-friendly, adaptive interventions for improving self-esteem, but robust trial-based evidence is pending. Objective: To examine the efficacy of SELFIE, a novel transdiagnostic, blended EMI for improving self-esteem plus care as usual (CAU) compared with CAU only. Design, Setting, and Participants: This was a 2-arm, parallel-group, assessor-blinded, randomized clinical trial conducted from December 2018 to December 2022. The study took place at Dutch secondary mental health services and within the general population and included youth (aged 12-26 years) with low self-esteem (Rosenberg Self-Esteem Scale [RSES] <26) exposed to childhood adversity. Interventions: A novel blended EMI (3 face-to-face sessions, email contacts, app-based, adaptive EMI) plus CAU or CAU only. Main Outcomes and Measures: The primary outcome was RSES self-esteem at postintervention and 6-month follow-up. Secondary outcomes included positive and negative self-esteem, schematic self-beliefs, momentary self-esteem and affect, general psychopathology, quality of life, observer-rated symptoms, and functioning. Results: A total of 174 participants (mean [SD] age, 20.7 [3.1] years; 154 female [89%]) were included in the intention-to-treat sample, who were primarily exposed to childhood emotional abuse or neglect, verbal or indirect bullying, and/or parental conflict. At postintervention, 153 participants (87.9%) and, at follow-up, 140 participants (80.5%), provided primary outcome data. RSES self-esteem was, on average, higher in the experimental condition (blended EMI + CAU) than in the control condition (CAU) across both postintervention and follow-up as a primary outcome (B = 2.32; 95% CI, 1.14-3.50; P < .001; Cohen d-type effect size [hereafter, Cohen d] = 0.54). Small to moderate effect sizes were observed suggestive of beneficial effects on positive (B = 3.85; 95% CI, 1.83-5.88; P < .001; Cohen d = 0.53) and negative (B = -3.78; 95% CI, -6.59 to -0.98; P = .008; Cohen d = -0.38) self-esteem, positive (B = 1.58; 95% CI, 0.41-2.75; P = .008; Cohen d = 0.38) and negative (B = -1.71; 95% CI, -2.93 to -0.48; P = .006; Cohen d = -0.39) schematic self-beliefs, momentary self-esteem (B = 0.29; 95% CI, 0.01-0.57; P = .04; Cohen d = 0.24), momentary positive affect (B = 0.23; 95% CI, 0.01-0.45; P = .04; Cohen d = 0.20), momentary negative affect (B = -0.33; 95% CI, -0.59 to -0.03, P = .01, Cohen d = -0.27), general psychopathology (B = -17.62; 95% CI, -33.03 to -2.21; P = .03; Cohen d = -0.34), and quality of life (B = 1.16; 95% CI, 0.18-2.13; P = .02; Cohen d = 0.33) across postintervention and follow-up. No beneficial effects on symptoms and functioning were observed. Conclusions and Relevance: A transdiagnostic, blended EMI demonstrated efficacy on the primary outcome of self-esteem and signaled beneficial effects on several secondary outcomes. Further work should focus on implementing this novel EMI in routine public mental health provision. Trial Registration: Dutch Trial Register Identifier:NL7129(NTR7475).

Which individual, social, and urban factors in early childhood predict psychopathology in later childhood, adolescence and young adulthood? A systematic review.

Background: A comprehensive picture is lacking of the impact of early childhood (age 0-5) risk factors on the subsequent development of mental health symptoms. Objective: In this systematic review, we investigated which individual, social and urban factors, experienced in early childhood, contribute to the development of later anxiety and depression, behavioural problems, and internalising and externalising symptoms in youth. Methods: Embase, MEDLINE, Scopus, and PsycInfo were searched on the 5th of January 2022. Three additional databases were retrieved from a mega-systematic review source that focused on the identification of both risk and protective indicators for the onset and maintenance of prospective depressive, anxiety and substance use disorders. A total of 46,450 records were identified and screened in ASReview, an AI-aided systematic review tool. We included studies with experimental, quasi-experimental, prospective and longitudinal study designs, while studies that focused on biological and genetical factors, were excluded. Results: Twenty studies were included. The majority of studies explored individual-level risk factors (N = 16). Eleven studies also explored social risk factors and three studied urban risk factors. We found evidence for early predictors relating to later psychopathology measures (i.e., anxiety and depression, behavioural problems, and internalising and externalising symptoms) in childhood, adolescence and early adulthood. These were: parental psychopathology, exposure to parental physical and verbal violence and social and neighbourhood disadvantage. Conclusions: Very young children are exposed to a complex mix of risk factors, which operate at different levels and influence children at different time points. The urban environment appears to have an effect on psychopathology but it is understudied compared to individual-level factors. Moreover, we need more research exploring the interaction between individual, social and urban factors.

Differential impact of preventive cognitive therapy while tapering antidepressants versus maintenance antidepressant treatment on affect fluctuations and individual affect networks and impact on relapse: a secondary analysis of a randomised controlled trial.

Background: There is an urgent need to better understand and prevent relapse in major depressive disorder (MDD). We explored the differential impact of various MDD relapse prevention strategies (pharmacological and/or psychological) on affect fluctuations and individual affect networks in a randomised setting, and their predictive value for relapse. Methods: We did a secondary analysis using experience sampling methodology (ESM) data from individuals with remitted recurrent depression that was collected alongside a randomised controlled trial that ran in the Netherlands, comparing: (I) tapering antidepressants while receiving preventive cognitive therapy (PCT), (II) combining antidepressants with PCT, or (III) continuing antidepressants without PCT, for the prevention of depressive relapse, as well as ESM data from 11 healthy controls. Participants had multiple past depressive episodes, but were remitted for at least 8 weeks and on antidepressants for at least six months. Exclusion criteria were: current (hypo)mania, current alcohol or drug abuse, anxiety disorder that required treatment, psychological treatment more than twice per month, a diagnosis of organic brain damage, or a history of bipolar disorder or psychosis. Fluctuations (within-person variance, root mean square of successive differences, autocorrelation) in negative and positive affect were calculated. Changes in individual affect networks during treatment were modelled using time-varying vector autoregression, both with and without applying regularisation. We explored whether affect fluctuations or changes in affect networks over time differed between treatment conditions or relapse outcomes, and predicted relapse during 2-year follow-up. This ESM study was registered at ISRCTN registry, ISRCTN15472145. Findings: Between Jan 1, 2014, and Jan 31, 2015, 72 study participants were recruited, 42 of whom were included in the analyses. We found no indication that affect fluctuations differed between treatment groups, nor that they predicted relapse. We observed large individual differences in affect network structure across participants (irrespective of treatment or relapse status) and in healthy controls. We found no indication of group-level differences in how much networks changed over time, nor that changes in networks over time predicted time to relapse (regularised models: hazard ratios [HR] 1063, 95% CI <0.0001->10 000, p = 0.65; non-regularised models: HR 2.54, 95% CI 0.23-28.7, p = 0.45) or occurrence of relapse (regularised models: odds ratios [OR] 22.84, 95% CI <0.0001->10 000, p = 0.90; non-regularised models: OR 7.57, 95% CI 0.07-3709.54, p = 0.44) during complete follow-up. Interpretation: Our findings should be interpreted with caution, given the exploratory nature of this study and wide confidence intervals. While group-level differences in affect dynamics cannot be ruled out due to low statistical power, visual inspection of individual affect networks also revealed no meaningful patterns in relation to MDD relapse. More studies are needed to assess whether affect dynamics as informed by ESM may predict relapse or guide personalisation of MDD relapse prevention in daily practice. Funding: The Netherlands Organisation for Health Research and Development, Dutch Research Council, University of Amsterdam.

Treatments for partial remission of major depressive disorder: a systematic review and meta-analysis.

QUESTION: Partial remission of major depressive disorder (MDD) is a debilitating and distressing clinical state related to chronicity, morbidity and relapse. Although one-third of patients remit partially, evidence for treatment efficacy is unclear. We provide an overview of treatment options and their efficacy. STUDY SELECTION AND ANALYSIS: Embase, PsycINFO, Medline and SCOPUS were systematically searched through February 2023. Included were randomised controlled trials (RCTs) examining any treatment in patients with partially remitted MDD aged 13-65 years, reporting data on severity, remission or relapse. FINDINGS: Seven RCTs examining psychotherapy including 1024 patients were eligible. There were not enough RCTs to examine effects of pharmacotherapy. Psychotherapy was associated with lower depressive symptom severity at post-treatment (Hedges' g=0.50; 95% CI 0.23 to 0.76), but not at follow-up up to 1 year (Hedges' g=0.36; 95% CI -0.30 to 1.02) or longer (Hedges' g=0.02; 95% CI -0.09 to 0.12). Psychotherapy was associated with superior remission rates at post-treatment (OR 2.57; 95% CI 1.71 to 3.87) and follow-up 6 months or longer (OR 1.75; 95% CI 1.21 to 2.53), although not with improved relapse rates at post-treatment (OR 0.17; 95% CI 0.01 to 4.83) or follow-up 6 months or longer (OR 0.46; 95% CI 0.21 to 1.03). Overall methodological quality was poor. CONCLUSIONS: Psychotherapy targeting partial remission may be effective in lowering depressive symptom severity and patients may potentially achieve full remission twice as likely. Yet, long-term and prophylactic effects are lacking. Given the risk of chronicity, more high-quality RCTs are needed. PROSPERO REGISTRATION NUMBER: CRD42020188451.

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.

Congruency of multimodal data-driven personalization with shared decision-making for StayFine: individualized app-based relapse prevention for anxiety and depression in young people.

Tailoring interventions to the individual has been hypothesized to improve treatment efficacy. Personalization of target-specific underlying mechanisms might improve treatment effects as well as adherence. Data-driven personalization of treatment, however, is still in its infancy, especially concerning the integration of multiple sources of data-driven advice with shared decision-making. This study describes an innovative type of data-driven personalization in the context of StayFine, a guided app-based relapse prevention intervention for 13- to 21-year-olds in remission of anxiety or depressive disorders (n = 74). Participants receive six modules, of which three are chosen from five optional modules. Optional modules are Enhancing Positive Affect, Behavioral Activation, Exposure, Sleep, and Wellness. All participants receive Psycho-Education, Cognitive Restructuring, and a Relapse Prevention Plan. The personalization approach is based on four sources: (1) prior diagnoses (diagnostic interview), (2) transdiagnostic psychological factors (online self-report questionnaires), (3) individual symptom networks (ecological momentary assessment, based on a two-week diary with six time points per day), and subsequently, (4) patient preference based on shared decision-making with a trained expert by experience. This study details and evaluates this innovative type of personalization approach, comparing the congruency of advised modules between the data-driven sources (1-3) with one another and with the chosen modules during the shared decision-making process (4). The results show that sources of data-driven personalization provide complementary advice rather than a confirmatory one. The indications of the modules Exposure and Behavioral Activation were mostly based on the diagnostic interview, Sleep on the questionnaires, and Enhancing Positive Affect on the network model. Shared decision-making showed a preference for modules improving positive concepts rather than combating negative ones, as an addition to the data-driven advice. Future studies need to test whether treatment outcomes and dropout rates are improved through personalization.

Understanding and predicting future relapse in depression from resting state functional connectivity and self-referential processing.

BACKGROUND: The recurrent nature of Major Depressive Disorder (MDD) asks for a better understanding of mechanisms underlying relapse. Previously, self-referential processing abnormalities have been linked to vulnerability for relapse. We investigated whether abnormalities in self-referential cognitions and functioning of associated brain-networks persist upon remission and predict relapse. METHODS: Remitted recurrent MDD patients (n = 48) and never-depressed controls (n = 23) underwent resting-state fMRI scanning at baseline and were additionally assessed for their implicit depressed self-associations and ruminative behaviour. A template-based dual regression approach was used to investigate between-group differences in default mode, cingulo-opercular and frontoparietal network resting-state functional connectivity (RSFC). Additional prediction of relapse status at 18-month follow-up was investigated within patients using both regression analyses and machine learning classifiers. RESULTS: Remitted patients showed higher rumination, but no implicit depressed self-associations or RSFC abnormalities were observed between patients and controls. Nevertheless, relapse was related to i) baseline RSFC between the ventral default mode network and the precuneus, dorsomedial frontal gyrus, and inferior occipital lobe, ii) implicit self-associations, and iii) uncontrollability of ruminative thinking, when controlled for depressive symptomatology. Moreover, preliminary machine learning classifiers demonstrated that RSFC within the investigated networks predicted relapse on an individual basis. CONCLUSIONS: Remitted MDD patients seem to be commonly characterized by abnormal rumination, but not by implicit self-associations or abnormalities in relevant brain networks. Nevertheless, relapse was predicted by self-related cognitions and default mode RSFC during remission, suggesting that variations in self-relevant processing play a role in the complex dynamics associated with the vulnerability to developing recurrent depressive episodes. CLINICAL TRIAL REGISTRATION: Netherlands Trial Register, August 18, 2015, trial number NL53205.042.15.

The Ghent Psychotherapy Study: A Pragmatic, Stratified, Randomized Parallel Trial into the Differential Efficacy of Psychodynamic and Cognitive-Behavioral Interventions in Dependent and Self-Critical Depressive Patients.

INTRODUCTION: Different types of psychotherapy are effective for treating major depressive disorder across groups yet show large within-group differences. Patient personality style is considered a potentially useful variable for treatment matching. OBJECTIVE: This study is the first experimental test of the interaction between therapeutic approach and patients' dependent versus self-critical personality styles. METHODS: A pragmatic stratified parallel trial was carried out with 100 adult patients diagnosed with DSM-IV-TR major depressive disorder. They were randomly assigned to short-term (16-20 sessions) cognitive behavioral therapy (CBT) or short-term psychodynamic psychotherapy (STPP). Patients were assessed at baseline, during therapy, post-therapy, and at 3- and 6-month follow-up. Primary outcome is depression severity measured by the Hamilton Rating Scale for Depression posttreatment. Primary analysis was by intention to treat. This trial is registered with the ISRCTN registry (www.isrctn.com), number ISRCTN17130982. RESULTS: The intention-to-treat sample consisted of 100 participants; 40 with self-critical and 60 with dependent personality styles were randomized to either CBT (n = 50) or STPP (n = 50). We observed no interaction effect (-0.34 [-6.14, 5.46]) between therapy and personality style and found no evidence for a difference in effectiveness between the treatments in general in terms of symptom reduction and maintained benefits at 6-month follow-up. CONCLUSION: We found no evidence that dependent versus self-critical personality styles moderate the relation between treatment and outcome in depression. Research using individual patient data could gain further insight into why specific therapeutic approaches work better for specific patients.

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.

Clinical Psychology and the COVID-19 Pandemic: A Mixed Methods Survey Among Members of the European Association of Clinical Psychology and Psychological Treatment (EACLIPT).

Background: The COVID-19 pandemic has affected people globally both physically and psychologically. The increased demands for mental health interventions provided by clinical psychologists, psychotherapists and mental health care professionals, as well as the rapid change in work setting (e.g., from face-to-face to video therapy) has proven challenging. The current study investigates European clinical psychologists and psychotherapists' views on the changes and impact on mental health care that occurred due to the COVID-19 pandemic. It further aims to explore individual and organizational processes that assist clinical psychologists' and psychotherapists' in their new working conditions, and understand their needs and priorities. Method: Members of the European Association of Clinical Psychology and Psychological Treatment (EACLIPT) were invited (N = 698) to participate in a survey with closed and open questions covering their experiences during the first wave of the pandemic from June to September 2020. Participants (n = 92) from 19 European countries, mostly employed in universities or hospitals, completed the online survey. Results: Results of qualitative and quantitative analyses showed that clinical psychologists and psychotherapists throughout the first wave of the COVID-19 pandemic managed to continue to provide treatments for patients who were experiencing emotional distress. The challenges (e.g., maintaining a working relationship through video treatment) and opportunities (e.g., more flexible working hours) of working through this time were identified. Conclusions: Recommendations for mental health policies and professional organizations are identified, such as clear guidelines regarding data security and workshops on conducting video therapy.