Latent classes of nonresponders, rapid responders, and gradual responders in depressed outpatients receiving antidepressant medication and psychotherapy

Identifying latent subtypes of symptom trajectories in major depressive disorder patients and their predictors

This study aimed to identify different symptom trajectories based on the severity of depression symptoms within a 2-month follow-up, and to explore predictive factors for different symptom trajectories. Three hundred and ninety-two adults diagnosed with major depressive disorder (MDD) were recruited from two longitudinal cohorts. Patients received antidepressant treatment as usual, and the depression symptoms were evaluated by the 17-item Hamilton depression rating scale (HAMD-17) at baseline, two weeks, and eight weeks. Based on the HAMD-17 scores, different trajectories of symptom change were distinguished by applying Growth Mixture Modeling (GMM). Furthermore, the baseline sociodemographic, clinical, and cognitive characteristics were compared to identify potential predictors for different trajectories. Through GMM, three unique depressive symptom trajectories of MDD patients were identified: (1) mild-severity class with significant improvement (Mild, n = 255); (2) high-severity class with significant improvement (High, n = 39); (3) moderate-severity class with limited improvement (Limited, n = 98). Among the three trajectories, the Mild class had a relatively low level of anxiety symptoms at baseline, whereas the High class had the lowest education level and the worst cognitive performance. Additionally, participants in the Limited class exhibited an early age of onset and experienced a higher level of emotional abuse. MDD patients could be categorised into three distinct latent subtypes through different symptom trajectories in this study, and the characteristics of these subtype patients may inform identifications for trajectory-specific intervention targets.

Trajectories of depression symptoms, anxiety symptoms and functional impairment during internet-enabled cognitive-behavioural therapy

Underlying classes capture differences between patient symptom trajectories during psychological therapy. This has not been explored for one-to-one internet-delivered therapy or functional impairment trajectories. Patients experiencing depression or anxiety received cognitive-behavioural therapy with a therapist using an online chat platform (N = 52,029). Trajectory classes of depression symptoms (PHQ9), anxiety symptoms (GAD7) and functional impairment (WSAS) were investigated using growth mixture modelling. Multinomial regressions tested associations between baseline variables and trajectory class. A four-class trajectory model was selected for each outcome, and these were highly similar. Each outcome showed three classes with initially moderate-severe symptoms or impairment: one demonstrated no change, one gradual improvement and one fast improvement. A fourth class had mild baseline scores and minimal improvement. In the moderate-severe classes, patients in the two with improvement were more likely to be employed and not to have obsessive-compulsive disorder. Fast improvement was likelier than gradual improvement or no change for patients with older age, no disability (e.g., physical, learning), or lower comorbid symptom or impairment scores. Associations with functional impairment classes were more similar to associations with depression classes than anxiety classes. Results were largely consistent with findings from face-to-face therapy. This study is an important step towards personalising therapy in terms of suitability and continuation.

Response trajectories during escitalopram treatment of patients with major depressive disorder

Depression is a leading global cause of disability, yet about half of patients do not respond to initial antidepressant treatment. This treatment difficulty may be in part due to the heterogeneity of depression and corresponding response to treatment. Unsupervised machine learning allows underlying patterns to be uncovered, and can be used to understand this heterogeneity by finding groups of patients with similar response trajectories. Prior studies attempting this have clustered patients using a narrow range of data primarily from depression scales. In this work, we used unsupervised machine learning to cluster patients receiving escitalopram therapy using a wide variety of subjective and objective clinical features from the first eight weeks of the Canadian Biomarker Integration Network in Depression-1 trial. We investigated how these clusters responded to treatment by comparing changes in symptoms and symptom categories, and by using Principal Component Analysis (PCA). Our algorithm found three clusters, which broadly represented non-responders, responders, and remitters. Most categories of features followed this response pattern except for objective cognitive features. Using PCA with our clusters, we found that subjective mood state/anhedonia is the core feature of response with escitalopram, but there exists other distinct patterns of response around neurovegetative symptoms, activation, and cognition.

Common factors, Responsiveness and Outcome in Psychotherapy (CROP): study protocol for a naturalistic prospective cohort study of psychotherapy in Denmark

INTRODUCTION

The aim of the Common factors, Responsiveness and Outcome in Psychotherapy (CROP) study is to identify client and psychologist characteristics and therapeutic processes associated with the outcome of psychotherapy delivered by psychologists employed in the Danish primary sector or fully self-employed. The study addresses two main questions. First, how are specific characteristics of clients and psychologists related to the outcome of therapy and do these characteristics moderate the outcome of different psychotherapeutic approaches? Second, to what extent do therapists adapt their approach to client characteristics and preferences and how does such responsiveness impact the process and outcome of therapy?

METHODS AND ANALYSIS

The study is a naturalistic prospective cohort study carried out in collaboration with psychologists in private practice in Denmark. Self-reported data are collected from the participating psychologists and their participating clients before, during (weekly and postsession) and after psychotherapy (at end of treatment and 3 months follow-up). The estimated target sample size is 573 clients. The data are analysed using multilevel modelling and structural equation modelling approaches to capture predictors and moderators of the effect and rate of change in psychotherapy as well as session-to-session changes during the therapy process.

ETHICS AND DISSEMINATION

The study has been approved by the IRB at the Department of Psychology, University of Copenhagen (IRB number: IP-IRB/01082018) and the Danish Data Protection Agency. All study data are fully anonymised and all clients have given informed consent to participation in the study. The study findings will be presented in articles in international, peer-reviewed journals as well as to psychotherapy practitioners and other professionals across Denmark.

TRIAL REGISTRATION NUMBER

NCT05630560.

Group-Based Symptom Trajectory of Intramuscular Administration of Scopolamine Augmentation in Moderate to Severe Major Depressive Disorder: A Post-Hoc Analysis

Objective

Developing new strategies for rapid and sustained relief of depressive symptom has been the focus of research in the field of major depressive disorder (MDD). Scopolamine exerts rapid antidepressant effect in recent years but is controversial. Therefore, we aimed to identify a sensitive patient who may respond to intramuscular injections of scopolamine added to antidepressants based on distinct trajectory patterns.

Methods

We analyzed longitudinal post hoc data collected from 66 MDD patients at Beijing Anding Hospital, Capital Medical University, over a 4-week period. In addition to demographics, depressive symptoms were assessed using the 16-item Quick Inventory of Depressive Symptomatology and Self-Report (QIDS-SR16) Scale and 17-item Hamilton Rating Scale for Depression (HRSD-17) following an i.m. injection of scopolamine. We explored different longitudinal patterns of depressive symptoms using a group-based trajectory model (GBTM). We used multiple logistic regression models to help identify predictors of different depressive symptom trajectories.

Results

A two-class GBTM was identified as optimal for classifying depressive symptoms: high/rapidly declining (39.4%) and moderate/gradually declining depression trajectories (60.6%) were distinguished based on the HRSD-17. The high/rapidly declining depression trajectory was characterized by high initial depression followed by a rapid decrease at the end of the study. The moderate/gradual decline trajectory was dominated by moderate depression and gradual decline over 4 weeks. There were no significant associations of age, gender, education, or age of onset with the two trajectory groups.

Conclusion

Scopolamine added to antidepressants can effectively relieve the symptoms of patients with severe depression, and it decreases faster than patients with moderate depression.

Trajectories of depression symptom change during and following treatment in adolescents with unipolar major depression

OBJECTIVE

To classify a cohort of depressed adolescents recruited to the UK IMPACT trial, according to trajectories of symptom change. We examined for predictors and compared the data-driven categories of patients with a priori operational definitions of treatment response.

METHOD

Secondary data analysis using growth mixture modelling (GMM). Missing data were imputed. Trajectories of self-reported depressive symptoms were plotted using scores taken at six nominal time points over 86 weeks from randomisation in all 465 patients.

RESULTS

A piecewise GMM categorised patients into two classes with initially similar and subsequently distinct trajectories. Both groups had a significant decline in depressive symptoms over the first 18 weeks. Eighty-four per cent (84.1%, n = 391) of patients were classed as 'continued-improvers' with symptoms reducing over the duration of the study. A further class of 15.9% (n = 74) of patients were termed 'halted-improvers' with higher baseline depression scores, faster early recovery but no further improvement after 18 weeks. Presence of baseline comorbidity somewhat increased membership to the halted-improvers class (OR = 1.40, CI: 1.00-1.96). By end of study, compared with classes, a clinical remission cut-off score (≤27) and a symptom reduction score (≥50%) indexing treatment response misclassified 15% and 31% of cases, respectively.

CONCLUSIONS

A fast reduction in depressive symptoms in the first few weeks of treatment may not indicate a good prognosis. Halted improvement is only seen after 18 weeks of treatment. Longitudinal modelling may improve the precision of revealing differential responses to treatment. Improvement in depressive symptoms may be somewhat better in the year after treatment than previously considered.

Personality Traits and Psychopathology Over the Course of Six Months of Outpatient Psychotherapy: A Prospective Observational Study

There is a lack of prospective studies that test pre-specified hypotheses on the role of personality traits in outpatient psychotherapy. A total of 47 patients with a broad range of psychopathological syndromes were enrolled in a prospective 6-month observational study conducted in Zurich, Switzerland. We found evidence for remarkably high differential stability in all Big Five personality traits during the first 6 months of psychotherapy. Mean-level stability was very high in agreeableness and conscientiousness, while modest changes were observed in neuroticism, extraversion and openness. Baseline scores in neuroticism and conscientiousness at the beginning of therapy predicted modest change in self-reported severity of psychopathology over 6 months, but no effect was found in association with therapist-rated functional deficits. We conclude that personality trait levels may change slightly over the course of 6 months of psychotherapy and that both neuroticism and conscientiousness may have weak associations with the self-perceived improvement in psychopathology.

The latent structure of depression symptoms and suicidal thoughts in Brazilian youths

BACKGROUND

Many studies have investigated the existence of discrete groups comprising the clinical concept of depression. Nevertheless, identifying true latent depression groups might require the inclusion of indicators of severe manifestations of depression, such as suicidal thoughts, in the analysis. Another issue is that relatively few studies have addressed the latent structure of depression in children and adolescents from Latin American cultures.

METHODS

In the present study, we combined latent profile and taxometric analysis to investigate the latent structure underlying depression symptoms (negative emotionality and low positive emotionality indicators) and suicidal thoughts in four aggregated Brazilian youth samples (total N = 2587; mean age = 12.86 years; SD = 2.60; 50.8% females).

RESULTS

Latent profile analysis indicated five classes that clearly represented distinct levels on a continuum of depression. However, taxometric results were ambiguous with regard to highlighting depression as a purely dimensional or categorical latent entity (mean CCFI = 0.497).

LIMITATIONS

The use of few indicators from a single instrument, the potential heterogeneity in the clinical group, and the non-random nature of the samples included in the study.

CONCLUSION

The mixed findings support the existence of a dimension of depression, as well as latent classes of individuals. Factor mixture models are discussed as a strategy for further exploring the nature of depression among young people.

Extraversion modulates cortisol responses to acute social stress in chronic major depression

BACKGROUND

Chronic Major Depressive Disorder (CMDD) is a common, disabling illness that is often complicated by high reactivity to social stress. To further elucidate the nature of this reactivity, the current study evaluated whether the personality dimensions of neuroticism and extraversion influenced cortisol responses to a social challenge in CMDD patients vs. controls.

METHODS

Fifty participants with CMDD and 58 healthy controls completed the Trier Social Stress Test (TSST) using a standard protocol. Neuroticism and extraversion were measured using the Revised NEO Personality Inventory. Hierarchical linear regressions assessed associations between independent variables neuroticism and extraversion and dependent variable cortisol area-under-the-curve increase (AUCi) in response to the TSST in the two study groups.

RESULTS

The extraversion-by-group interaction was a significant predictor of cortisol AUCi, while no significant findings related to neuroticism were found. Simple slopes analysis revealed a significant negative association between extraversion and AUCi in the CMDD group, but not in healthy controls. Post-hoc analysis of the raw cortisol data over time found that CMDD participants with higher extraversion scores had significantly higher pre-challenge cortisol levels than did other study participants, however this did not explain or confound the AUCi results.

CONCLUSIONS

In participants with CMDD but not in controls, higher levels of extraversion were associated with higher pre-challenge cortisol levels and decreased cortisol reactivity during the TSST, however these two findings were statistically independent. These findings underline the importance of considering personality factors when studying stress biology in CMDD patients. Extraversion may prove to be an important intermediate target for both research and clinical work in this complex, heterogenous and often treatment-resistant population.

Latent trajectories of change for clients at a psychodynamic training clinic

OBJECTIVE

Employing practice-based research methods, we addressed the need to examine the effectiveness of psychodynamic treatment as a supplement to the efficacy evidence offered by randomized clinical trials.

METHOD

We used person-centered analyses to generate latent subgroups of clients (N = 118; M _age  = 40.92; 53.4% female; 81.4% Caucasian; 80.5% heterosexual) receiving contemporary relational psychotherapy (CRP) at a psychodynamic community mental health training clinic.

RESULTS

Subgroups of clients reported a change in depression, social conflict, and anxiety symptomatology, and overall life satisfaction, depicted by significant quadratic growth curves. Findings also offered exploratory support for a theoretical proposition from CRP that improved relational functioning would correspond to improved affect dysregulation and overall life satisfaction.

CONCLUSION

Clinical and training implications highlight the need to distinguish subgroups of "responders" and "nonresponders" to inform treatment.

Early Change Trajectories in Cognitive-Behavioral Therapy for Binge-Eating Disorder

Rapid response is considered the most well-established outcome predictor across treatments of binge-eating disorder (BED), including cognitive-behavioral therapy (CBT). This study sought to identify latent trajectories of early change in CBT and compare them to common rapid response classifications. In a multicenter randomized trial, 86 adults with BED (DSM-IV) or subsyndromal BED provided weekly self-reports of binge eating over the first 4 weeks of CBT, which were analyzed to predict binge eating, depression, and body mass index at posttreatment, 6-, and 18-month follow-up. Using latent growth mixture modeling, three patterns of early change-including moderate and low decreasing-as well as low stable binge eating were identified, which significantly predicted binge-eating remission at 6-month follow-up. Other classifications of rapid response based on Receiver Operating Characteristics curve analyses or on the literature (≥ 10% reduction in binge eating at week 1, ≥ 70% reduction in binge eating at week 4) only predicted posttreatment remission or overall depression, respectively. Latent change trajectories, but not other rapid response classifications, predicted binge-eating frequency over time. A fine-grained analysis of change over the first 4 weeks of CBT for BED revealed different trajectories of early change in binge eating that led to an improved prediction of binge-eating outcome, compared to that of common rapid response classifications. Thorough monitoring of early change trajectories during treatment may have clinical utility.

Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review

BACKGROUND

No previous study has comprehensively reviewed the application of machine learning algorithms in mood disorders populations. Herein, we qualitatively and quantitatively evaluate previous studies of machine learning-devised models that predict therapeutic outcomes in mood disorders populations.

METHODS

We searched Ovid MEDLINE/PubMed from inception to February 8, 2018 for relevant studies that included adults with bipolar or unipolar depression; assessed therapeutic outcomes with a pharmacological, neuromodulatory, or manual-based psychotherapeutic intervention for depression; applied a machine learning algorithm; and reported predictors of therapeutic response. A random-effects meta-analysis of proportions and meta-regression analyses were conducted.

RESULTS

We identified 639 records: 75 full-text publications were assessed for eligibility; 26 studies (n=17,499) and 20 studies (n=6325) were included in qualitative and quantitative review, respectively. Classification algorithms were able to predict therapeutic outcomes with an overall accuracy of 0.82 (95% confidence interval [CI] of [0.77, 0.87]). Pooled estimates of classification accuracy were significantly greater (p < 0.01) in models informed by multiple data types (e.g., composite of phenomenological patient features and neuroimaging or peripheral gene expression data; pooled proportion [95% CI] = 0.93[0.86, 0.97]) when compared to models with lower-dimension data types (pooledproportion=0.68[0.62,0.74]to0.85[0.81,0.88]).

LIMITATIONS

Most studies were retrospective; differences in machine learning algorithms and their implementation (e.g., cross-validation, hyperparameter tuning); cannot infer importance of individual variables fed into learning algorithm.

CONCLUSIONS

Machine learning algorithms provide a powerful conceptual and analytic framework capable of integrating multiple data types and sources. An integrative approach may more effectively model neurobiological components as functional modules of pathophysiology embedded within the complex, social dynamics that influence the phenomenology of mental disorders.

Response rate profiles for major depressive disorder: Characterizing early response and longitudinal nonresponse

BACKGROUND

Definition of response is critical when seeking to establish valid predictors of treatment success. However, response at the end of study or endpoint only provides one view of the overall clinical picture that is relevant in testing for predictors. The current study employed a classification technique designed to group subjects based on their rate of change over time, while simultaneously addressing the issue of controlling for baseline severity.

METHODS

A set of latent class trajectory analyses, incorporating baseline level of symptoms, were performed on a sample of 344 depressed patients from a clinical trial evaluating the efficacy of cognitive behavior therapy and two antidepressant medications (escitalopram and duloxetine) in patients with major depressive disorder.

RESULTS

Although very few demographic and illness-related features were associated with response rate profiles, the aggregated effect of candidate genetic variants previously identified in large pharmacogenetic studies and meta-analyses showed a significant association with early remission as well as nonresponse. These same genetic scores showed a less compelling relationship with endpoint response categories. In addition, consistent nonresponse throughout the study treatment period was shown to occur in different subjects than endpoint nonresponse, which was verified by follow-up augmentation treatment outcomes.

CONCLUSIONS

When defining groups based on the rate of change, controlling for baseline depression severity may help to identify the clinically relevant distinctions of early response on one end and consistent nonresponse on the other.

The role of perceived social support after psychiatric hospitalisation: Post hoc analysis of a randomised controlled trial testing the effectiveness of a transitional intervention

BACKGROUND

The association between social support, readmissions and psychopathology following discharge from psychiatric hospitals is not clear.

AIMS

To examine the prospective effects of perceived social support on rehospitalisation rates and psychopathology and to focus on the moderators of a transitional intervention.

METHOD

This post hoc analysis of a multisite randomised controlled trial included 151 patients with no more than three hospitalisations within the last 3 years, a Global Assessment of Functioning (GAF) score ≤60 and aged 18-64 years, assessed at two psychiatric hospitals from Zurich, Switzerland, between September 2011 and February 2014. Participants received either a transitional intervention aimed at improving social support during the transition from inpatient to outpatient care provided by a social worker or treatment as usual.

RESULTS

Lack of perceived social support at discharge significantly predicted subsequent rehospitalisation rates and increased psychopathological impairment across 12-month follow-up. Significant interaction effects between patient characteristics and the intervention on perceived social support comprised living at parent's home, having no children and being of younger age.

CONCLUSION

Perceived social support at discharge from inpatient care may reduce rehospitalisation rates and psychopathological impairment in the long term. A transitional intervention aimed at improving social support may negatively impact on the perceived social support in some patient groups.

Personality, Psychopathology, and Psychotherapy: A Pre-specified Analysis Protocol for Confirmatory Research on Personality-Psychopathology Associations in Psychotherapy Outpatients

The role of personality trait variation in psychopathology and its influence on the outcome of psychotherapy is a burgeoning field. However, thus far most findings were based on controlled clinical trials that may only poorly represent real-world clinical settings due to highly selective samples mostly restricted to patients with major depression undergoing antidepressive medication. Focusing on personality and psychopathology in a representative naturalistic sample of psychotherapy patients is therefore worthwhile. Moreover, up to date hardly any confirmatory research has been conducted in this field. Strictly confirmatory research implies two major requirements: firstly, specific hypotheses, including expected effect sizes and statistical approaches to data analysis, must be detailed prior to inspection of the data, and secondly, corresponding protocols have to be published online and freely available. Here, we introduce a longitudinal naturalistic study aimed at examining, firstly, the prospective impact of baseline personality traits on the outcome of psychotherapy over a 6-month observation period; secondly, the stability and change in personality traits over time; thirdly, the association between longitudinal change in psychopathology and personality; fourthly, the agreement between self-reports and informant rating of personality; and fifthly, the predictive validity of personality self-reports compared to corresponding informant ratings. For it, we comprehensively state a priori hypotheses, predict the expected effect sizes and detail the statistical analyses that we intend to conduct to test these predictions. Such a stringent confirmatory design increases the transparency and objectivity of psychopathological research, which is necessary to reduce the rate of false-positive findings and to increase the yield of scientific research.

Influences of the Big Five personality traits on the treatment response and longitudinal course of depression in patients with acute coronary syndrome: A randomised controlled trial

BACKGROUND

Influences of the Big Five personality traits on the treatment response and longitudinal course of depression in patients with acute coronary syndrome: A randomised controlled trial.

METHODS

This naturalistic observational study initially recruited 1152 ACS patients; 685 patients completed personality assessments at baseline, of whom 630 were followed-up one year later. Of the 294 patients with depression, 207 participated in a 24-week double blind trial of escitalopram or placebo. The remaining 87 patients who received medical treatment only and the 391 who had not depression were also followed in a one year naturalistic observational study. The Big five personality traits were assessed using the Big Five Inventory. The influences of personality on the Hamilton Depression Rating Scale score changes were analysed using a mixed-model repeated-measures analysis of covariance.

RESULTS

A Cluster analysis identified two personality types: resilient and vulnerable. The vulnerable personality type was characterized by lower extraversion, agreeableness, and conscientiousness - but higher neuroticism - than the resilient type. This personality type was independently associated with a poorer outcome of depression in ACS patients during the 24-week treatment period and the one year longitudinal follow-up period compared to the resilient personality type, irrespective of treatment allocation.

LIMITATIONS

Recruitment from a single institution may limit generalisability. Personality traits were investigated 12-weeks after ACS; thus, the responses may have been influenced by the prior receipt of escitalopram.

CONCLUSIONS

Personality types influences the treatment outcome and longitudinal course of depression in ACS patients independent of antidepressant treatment.

GROUP-BASED SYMPTOM TRAJECTORIES IN INDICATED PREVENTION OF ADOLESCENT DEPRESSION

BACKGROUND

Adolescent depression prevention research has focused on mean intervention outcomes, but has not considered heterogeneity in symptom course. Here, we empirically identify subgroups with distinct trajectories of depressive symptom change among adolescents enrolled in two indicated depression prevention trials and examine how cognitive-behavioral (CB) interventions and baseline predictors relate to trajectory membership.

METHODS

Six hundred thirty-one participants were assigned to one of three conditions: CB group intervention, CB bibliotherapy, and brochure control. We used group-based trajectory modeling to identify trajectories of depressive symptoms from pretest to 2-year follow-up. We examined associations between class membership and conditions using chi-square tests and baseline predictors using multinomial regressions.

RESULTS

We identified four trajectories in the full sample. Qualitatively similar trajectories were found in each condition separately. Two trajectories of positive symptom course (low-declining, high-declining) had declining symptoms and were distinguished by baseline symptom severity. Two trajectories of negative course (high-persistent, resurging), respectively, showed no decline in symptoms or decline followed by symptom reappearance. Participants in the brochure control condition were significantly more likely to populate the high-persistent trajectory relative to either CB condition and were significantly less likely to populate the low-declining trajectory relative to CB group. Several baseline factors predicted trajectory classes, but gender was the most informative prognostic factor, with males having increased odds of membership in a high-persistent trajectory relative to other trajectories.

CONCLUSIONS

Findings suggest that CB preventive interventions do not alter the nature of trajectories, but reduce the risk that adolescents follow a trajectory of chronically elevated symptoms.

The Post-Discharge Network Coordination Programme: A Randomized Controlled Trial to Evaluate the Efficacy of an Intervention Aimed at Reducing Rehospitalizations and Improving Mental Health

PURPOSE

To evaluate the efficacy of a post-discharge intervention for psychiatric inpatients aimed at preventing hospital readmissions and at improving patients' mental health and psychosocial functioning.

METHODS

Randomized controlled trial using parallel group block randomization including 151 patients with ≤3 hospitalizations within the last 3 years, a GAF score ≤60, and aged 18-64 years, assessed at two psychiatric hospitals from the canton of Zurich, Switzerland, between September 2011 and February 2014. Primary outcomes were rate and duration of rehospitalization; secondary outcomes were mental health and functioning. Outcome measures were assessed before discharge from the index hospitalization (t 0), 3 months after discharge when the intervention terminated (t 1), and 12 months after discharge (t 2). Participants received either a brief case management post-discharge intervention or treatment as usual.

RESULTS

In the short-term (i.e., t 0-t 1), no significant effect emerged in any outcome. In the long term (i.e., t 0-t 2), the two groups did not differ significantly with respect to the rate and duration of rehospitalization. Also, the intervention did not reduce psychiatric symptoms, did not improve social support, and did not improve quality of life. However, it did slightly increase assessor-rated general (d = 0.30) and social functioning (d = 0.42), although self-reports revealed a deteriorative effect on symptom remission (d = -0.44).

CONCLUSION

This psychosocial post-discharge intervention showed no efficacy in the primary outcome of rehospitalization. With respect to secondary outcomes, in the long term it might lead to slightly increased social functioning but revealed no significant effect on psychopathology, social support, and quality of life. By contrast, with respect to self-reported symptom remission, it was revealed to have a negative effect. In this high-resource catchment area with comprehensive community psychiatric and social services, the intervention thus cannot be recommended for implementation in routine care.