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.

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.

Perceived ethnic discrimination, suicidal ideation and mastery in a multi-ethnic cohort: the HELIUS study.

BACKGROUND: The association between perceived ethnic discrimination (PED) and mental health conditions is well studied. However, less is known about the association between PED and suicidal ideation, or the role of positive psychosocial factors in this association. AIMS: To examine the association between PED and suicidal ideation among ethnic minority groups in Amsterdam, The Netherlands, and investigate whether ethnicity and mastery (people's extent of feeling in control of their lives and environment) moderate this association. METHOD: Cross-sectional data from the multi-ethnic HELIUS study were analysed (n = 17 053) for participants of South-Asian Surinamese, African Surinamese, Ghanaian, Turkish and Moroccan origin. PED was measured using the Everyday Discrimination Scale, suicidal ideation using item 9 of the Patient Health Questionnaire-9 and mastery using the Pearlin-Schooler Mastery Scale. RESULTS: Logistic regression analyses demonstrated a small positive association between PED and suicidal ideation (OR = 1.068, 95% CI 1.059-1.077), which did not differ among ethnic minority groups. Mastery did not moderate the association between PED and suicidal ideation among the ethnic minority groups. CONCLUSIONS: Our findings support the hypothesis that PED is associated with suicidal ideation and this association does not significantly vary between ethnic minority groups. Although higher levels of mastery were associated with lower suicidal ideation, mastery did not moderate the relationship between PED and suicidal ideation. Besides targeting ethnic discrimination as a societal problem, future longitudinal research is needed to investigate whether interventions aimed at improving mastery could reduce suicidal ideation in ethnic minority groups.

Meta-Analysis: Relapse Prevention Strategies for Depression and Anxiety in Remitted Adolescents and Young Adults.

OBJECTIVE: Depression and anxiety cause a high burden of disease and have high relapse rates (39%-72%). This meta-analysis systematically examined effectiveness of relapse prevention strategies on risk of and time to relapse in youth who remitted. METHOD: PubMed, PsycInfo, Embase, Cochrane, and ERIC databases were searched up to June 15, 2021. Eligible studies compared relapse prevention strategies to control conditions among youth (mean age 13-25 years) who were previously depressed or anxious or with ≥30% improvement in symptoms. Two reviewers independently assessed titles, abstracts, and full texts; extracted study data; and assessed risk of bias and overall strength of evidence. Random-effects models were used to pool results, and mixed-effects models were used for subgroup analyses. Main outcome was relapse rate at last follow-up (PROSPERO ID: CRD42020149326). RESULTS: Of 10 randomized controlled trials (RCTs) that examined depression, 9 were eligible for analysis: 4 included psychological interventions (n = 370), 3 included antidepressants (n = 80), and 2 included combinations (n = 132). No RCTs for anxiety were identified. Over 6 to 75 months, relapse was half as likely following psychological treatment compared with care as usual conditions (k = 6; odds ratio 0.56, 95% CI 0.31 to 1.00). Sensitivity analyses including only studies with ≥50 participants (k = 3), showed similar results. Over 6 to 12 months, relapse was less likely in youth receiving antidepressants compared with youth receiving pill placebo (k = 3; OR 0.29, 95% CI 0.10 to 0.82). Quality of studies was suboptimal. CONCLUSION: Relapse prevention strategies for youth depression reduce risk of relapse, although adequately powered, high-quality RCTs are needed. This finding, together with the lack of RCTs on anxiety, underscores the need to examine relapse prevention in youth facing these common mental health conditions.

The relationship between cognitive functioning and psychopathology in patients with psychiatric disorders: a transdiagnostic network analysis.

BACKGROUND: Patients with psychiatric disorders often experience cognitive dysfunction, but the precise relationship between cognitive deficits and psychopathology remains unclear. We investigated the relationships between domains of cognitive functioning and psychopathology in a transdiagnostic sample using a data-driven approach. METHODS: Cross-sectional network analyses were conducted to investigate the relationships between domains of psychopathology and cognitive functioning and detect clusters in the network. This naturalistic transdiagnostic sample consists of 1016 psychiatric patients who have a variety of psychiatric diagnoses, such as depressive disorders, anxiety disorders, obsessive-compulsive and related disorders, and schizophrenia spectrum and other psychotic disorders. Psychopathology symptoms were assessed using various questionnaires. Core cognitive domains were assessed with a battery of automated tests. RESULTS: Network analysis detected three clusters that we labelled: general psychopathology, substance use, and cognition. Depressive and anxiety symptoms, verbal memory, and visual attention were the most central nodes in the network. Most associations between cognitive functioning and symptoms were negative, i.e. increased symptom severity was associated with worse cognitive functioning. Cannabis use, (subclinical) psychotic experiences, and anhedonia had the strongest total negative relationships with cognitive variables. CONCLUSIONS: Cognitive functioning and psychopathology are independent but related dimensions, which interact in a transdiagnostic manner. Depression, anxiety, verbal memory, and visual attention are especially relevant in this network and can be considered independent transdiagnostic targets for research and treatment in psychiatry. Moreover, future research on cognitive functioning in psychopathology should take a transdiagnostic approach, focusing on symptom-specific interactions with cognitive domains rather than investigating cognitive functioning within diagnostic categories.

Psychotherapy for co-occurring symptoms of depression, anxiety and obsessive-compulsive disorder in children and adults with autism spectrum disorder: a systematic review and meta-analysis.

Individuals with autism spectrum disorder (ASD) struggle accessing psychotherapy services for comorbidities, including anxiety-, depressive- and obsessive-compulsive disorders (OCD). Apart from cognitive behavioural therapy (CBT) for anxiety in children with ASD, it is unclear whether psychotherapy is effective for these comorbid disorders.We therefore systematically reviewed any form of psychotherapy for co-occurring symptoms of anxiety, depression and OCD in individuals with ASD.Database searches were conducted until February 2022 using EMBASE, PsycINFO and PubMed. Randomised controlled trials (RCT) were included investigating any form of psychotherapy for symptoms of anxiety, depression and OCD in individuals with ASD. Summary data were extracted, and random-effects meta-analyses were conducted.For CBT 26 RCTs (n = 1251), and for social skills training (SST) 11 RCTs (n = 475) met criteria for inclusion. Pooled effect sizes indicated a moderate reduction of anxiety in children (g = -0.70) and a small reduction of depressive symptoms in adults (g = -0.39). For SST overall effect sizes were small for reduction of anxiety in children (g = -0.35) and adults (g = -0.34) and moderate for reduction of depressive symptoms in children (g = -0.50). Risk of bias was high in 18, moderate in 16 and low in 3 RCTs.Our results provide new and age-specific evidence that: (1) CBT is effective for reducing anxiety in children and to a lesser extent for depressive symptoms in adults with ASD; and (2) social skills interventions are effective for reducing anxiety in children and adults and for depressive symptoms in children with ASD.

Is suboptimal effort an issue? A systematic review on neuropsychological performance validity in major depressive disorder.

BACKGROUND: In Major Depressive Disorder (MDD), emotion- and motivation related symptoms may affect effort during neuropsychological testing. Performance Validity Tests (PVT's) are therefore essential, but are rarely mentioned in research on cognitive functioning in MDD. We aimed to assess the proportion of MDD patients with demonstrated valid performance and determine cognitive functioning in patients with valid performance. This is the first systematic review on neuropsychological performance validity in MDD. METHODS: Databases PubMed, PsycINFO, Embase, and Cochrane Library were searched for studies reporting on PVT results of adult MDD patients. We meta-analyzed the proportion of MDD patients with PVT scores indicative of valid performance. RESULTS: Seven studies with a total of 409 MDD patients fulfilled inclusion criteria. Six studies reported the exact proportion of patients with PVT scores indicative of valid performance, which ranged from 60 to 100 % with a proportion estimate of 94 %. Four studies reported on cognitive functioning in MDD patients with valid performance. Two out of these studies found memory impairment in a minority of MDD patients and two out of these studies found no cognitive impairment. LIMITATIONS: Small number of studies and small sample sizes. CONCLUSIONS: A surprisingly small number of studies reported on PVT in MDD. About 94 % of MDD patients in studies using PVT's had valid neuropsychological test performance. Concessive information regarding cognitive functioning in MDD patients with valid performance was lacking. Neuropsychological performance validity should be taken into account since this may alter conclusions regarding cognitive functioning.