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1.
BMC Psychiatry ; 24(1): 141, 2024 Feb 19.
Article in English | MEDLINE | ID: mdl-38373948

ABSTRACT

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.


Subject(s)
Depressive Disorder, Major , Mindfulness , Humans , Mindfulness/methods , Depression/psychology , Depressive Disorder, Major/prevention & control , Depressive Disorder, Major/psychology , Cross-Over Studies , Cognition , Recurrence , Randomized Controlled Trials as Topic
2.
BMC Psychiatry ; 23(1): 835, 2023 11 13.
Article in English | MEDLINE | ID: mdl-37957596

ABSTRACT

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.


Subject(s)
Antidepressive Agents , Humans , Antidepressive Agents/therapeutic use , Decision Trees , Logistic Models , Recurrence , Risk Factors , Randomized Controlled Trials as Topic
3.
Front Psychiatry ; 14: 1229713, 2023.
Article in English | MEDLINE | ID: mdl-37840790

ABSTRACT

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.

4.
J Psychiatr Res ; 165: 305-314, 2023 09.
Article in English | MEDLINE | ID: mdl-37556963

ABSTRACT

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.


Subject(s)
Depressive Disorder, Major , Humans , Depressive Disorder, Major/diagnostic imaging , Depression , Brain/diagnostic imaging , Frontal Lobe , Magnetic Resonance Imaging , Recurrence , Brain Mapping
5.
BJPsych Open ; 9(1): e21, 2023 Jan 20.
Article in English | MEDLINE | ID: mdl-36660955

ABSTRACT

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.

6.
J Am Acad Child Adolesc Psychiatry ; 62(3): 306-317, 2023 03.
Article in English | MEDLINE | ID: mdl-35513189

ABSTRACT

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.


Subject(s)
Depression , Psychotherapy , Adolescent , Young Adult , Humans , Adult , Psychotherapy/methods , Depression/therapy , Secondary Prevention , Anxiety/therapy , Antidepressive Agents , Recurrence
7.
Psychol Med ; 53(2): 476-485, 2023 01.
Article in English | MEDLINE | ID: mdl-34165065

ABSTRACT

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.


Subject(s)
Cognition Disorders , Psychotic Disorders , Schizophrenia , Humans , Cross-Sectional Studies , Psychotic Disorders/epidemiology , Psychotic Disorders/psychology , Cognition , Cognition Disorders/psychology
8.
Psychol Med ; 53(1): 17-33, 2023 01.
Article in English | MEDLINE | ID: mdl-36404645

ABSTRACT

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.


Subject(s)
Autism Spectrum Disorder , Obsessive-Compulsive Disorder , Adult , Child , Humans , Depression , Anxiety , Psychotherapy , Autism Spectrum Disorder/complications , Autism Spectrum Disorder/therapy , Obsessive-Compulsive Disorder/therapy
9.
Neuropharmacology ; 223: 109318, 2023 Feb 01.
Article in English | MEDLINE | ID: mdl-36334762

ABSTRACT

The microbiota-gut-brain axis (MGBA) refers to the bidirectional communication between the brain and the gut microbiota and recent studies have linked the MGBA to health and disease. Research has so far investigated this axis mainly from microbiota to brain but less is known about the other direction. One approach to examine the MGBA from brain to microbiota is through understanding if and how neuromodulation might impact microbiota. Neuromodulation encompasses a wide range of stimulation techniques and is used to treat neurological, psychiatric and metabolic disorders, like Parkinson's Disease, depression and obesity. Here, we performed a systematic review to investigate whether neuromodulation is associated with subsequent changes in the gut microbiota. Searches in PsycINFO and MEDLINE were performed up to March 2022. Included studies needed to be clinical or preclinical studies comparing the effects of deep brain stimulation, electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation or vagal nerve stimulation on the gut microbiota before and after treatment or between active and control groups. Seven studies were identified. Neuromodulation was associated with changes in relative bacterial abundances, but not with (changes in) α-diversity or ß-diversity. Summarizing, currently reported findings suggest that neuromodulation interventions are associated with moderate changes in the gut microbiome. However, findings remain inconclusive due to the limited number and varying quality of included studies, as well as the large heterogeneity between studies. More research is required to more conclusively establish whether, and if so, via which mechanism(s) of action neuromodulation interventions might influence the gut microbiota.


Subject(s)
Deep Brain Stimulation , Transcranial Direct Current Stimulation , Vagus Nerve Stimulation , Transcranial Direct Current Stimulation/methods , Transcranial Magnetic Stimulation/methods , Vagus Nerve Stimulation/methods , Deep Brain Stimulation/methods , Brain
10.
Front Psychiatry ; 14: 1134071, 2023.
Article in English | MEDLINE | ID: mdl-38268558

ABSTRACT

Background: The highly recurrent nature of Major Depressive Disorder is a major contributor to disability and health care costs. Several studies indicate that recurrence may be prevented with Preventive Cognitive Therapy (PCT). This study is the first to perform an economic evaluation of PCT in comparison with care as usual for recurrently depressed patients who experienced two or more depressive episodes and remitted after receiving Cognitive Behavioural Therapy. Methods: An economic evaluation from the societal perspective was performed alongside a randomized trial (N = 214). Health-related quality of life (QALYs), depression-free days, health care utilization, and productivity losses were measured between randomization and 15 months follow-up. The costs were indexed to the reference year 2014. Results: QALY gains did not differ significantly between the groups (p = 0.69). Depression-free days were higher after PCT (p = 0.02). Societal costs of PCT were 10,417 euro and for care as usual 9,545 euro per person. We found a 47% likelihood that PCT led to additional QALYs at higher costs, and there was a 26% likelihood that PCT led to fewer QALYs at higher costs. When depression-free days was used as an outcome, we found PCT had a 72% likelihood of leading to more depression-free days at higher costs than care as usual and a 27% likelihood of leading to more depression-free days at lower societal costs. Limitations: The 15-month follow-up might be too short to draw long-term conclusions about the cost-effectiveness of the PCT. The data collected for this study is part of an RCT to examine the effectiveness of adding PCT to care as usual. Therefore, the study was powered primarily to detect an effect in time to relapse/recurrences. Conclusion: The economic evaluation is slightly in favour of the PCT condition when depression-free days is used as an outcome. PCT is not cost-effective given the high costs per additional QALYs from the societal perspective when QALYs are the effect measure. Clinical trial registration: https://www.onderzoekmetmensen.nl/en, identifier NL2482.

11.
J Psychiatr Res ; 151: 65-72, 2022 07.
Article in English | MEDLINE | ID: mdl-35461004

ABSTRACT

INTRODUCTION: Each year almost 800.000 people die from suicide, of which up to 87% are affected by major depressive disorder (MDD). Despite the strong association between suicidality and MDD, it remains unknown if suicidal symptoms during remission put remitted recurrent MDD patients (rrMDD) at risk for recurrence. METHODS: At baseline we compared sociodemographic characteristics and suicidal symptoms in un-medicated rrMDD participants to matched never-depressed controls. We used the HDRS17 and IDS-SR30 to assess suicidal symptoms and depressive symptomatology. Next, we studied the longitudinal association between baseline suicidal symptoms and time to recurrence(s) in rrMDD during a 2.5-year follow-up period using cox regression analyses. Further, we studied with longitudinal data whether suicidal symptoms and depressive symptomatology were cross-sectionally associated using mixed model analysis. RESULTS: At baseline, rrMDD participants (N = 73) had higher self-reported suicidal symptoms than matched never-depressed controls (N = 45) (χ2 = 12.09 p < .002). Self-reported suicidal symptoms were almost four times higher (27.9% versus 6.9%) compared to clinician-rated suicidal symptoms in rrMDD at baseline. Self-reported baseline suicidal symptoms, but not clinician-rated symptoms, predicted earlier MDD-recurrence during follow-up, independent of other residual depressive symptoms (χ2 = 7.26, p < .026). Higher suicidal symptoms were longitudinally related to higher depressive symptoms (HDRS17; F = 49.87, p < .001), IDS-SR30; (F = 22.36, p < .001). CONCLUSION: This study showed that self-reported - but not clinician-rated - suicidal symptoms persist during remission in rrMDD and predict recurrence, independent from residual symptoms. We recommend to monitor both suicidal and depressive symptomatology during remission in rrMDD, preferably also including self-reported questionnaires apart from clinician-rated. It would be beneficial for future research to assess suicidality using questionnaires primarily designed for measuring suicidal ideation.


Subject(s)
Depressive Disorder, Major , Suicide , Depressive Disorder, Major/drug therapy , Humans , Self Report , Suicidal Ideation , Surveys and Questionnaires
12.
Neuroimage Clin ; 34: 102988, 2022.
Article in English | MEDLINE | ID: mdl-35298997

ABSTRACT

The recurrent nature of Major Depressive Disorder (MDD) necessitates a better understanding of mechanisms facilitating relapse. MDD has often been associated with abnormal emotion regulation, underpinned by aberrant interactions between the prefrontal cortex and subcortical areas. We assessed whether neural regulation abnormalities remain after remission and relate to emotion regulation problems in daily life. At the baseline measurement of a randomized controlled trial, an emotion regulation task was performed during fMRI scanning by 46 remitted recurrent (rrMDD) patients and 24 healthy controls. We assessed both fMRI peak activity and the temporal dynamics of the neural response during passive attendance and explicit regulation of positive and negative emotions. Furthermore, we assessed regulation strategy use in daily life using questionnaires, and attentional biases using a modified attentional dot-probe task. RrMDD patients showed lower activation and different temporal dynamics in occipital, parietal, and prefrontal brain regions during passive attendance of emotional material compared to healthy controls. During explicit downregulation of negative emotions, no group differences were found. However, during explicit upregulation of positive emotions, rrMDD patients showed a different neural response over time in the insula. Behaviourally, rrMDD patients were characterized by dysfunctional regulation strategies in daily life. Within rrMDD patients, rumination was associated with activation within a limbic- prefrontal network. After remission, immediate emotional processing seems unaffected, but regulatory abnormalities remain, especially uninstructed and in daily life. Abnormal insula activation during positive upregulation suggests decreased monitoring of positive emotions. The relation between inadequate rumination and brain activity during emotion regulation suggests that regulation of both positive and negative affect is important in understanding neurocognitive underpinnings of resilience.


Subject(s)
Depressive Disorder, Major , Emotional Regulation , Brain/diagnostic imaging , Brain Mapping , Depression , Emotions/physiology , Humans , Magnetic Resonance Imaging
13.
Behav Res Ther ; 151: 104048, 2022 04.
Article in English | MEDLINE | ID: mdl-35121385

ABSTRACT

The ability to retrieve specific, single-incident autobiographical memories has been consistently posited as a predictor of recurrent depression. Elucidating the role of autobiographical memory specificity in patient-response to depressive treatments may improve treatment efficacy and facilitate use of science-driven interventions. We used recent methodological advances in individual patient data meta-analysis to determine a) whether memory specificity is improved following mindfulness-based cognitive therapy (MBCT), relative to control interventions, and b) whether pre-treatment memory specificity moderates treatment response. All bar one study evaluated MBCT for relapse prevention for depression. Our initial analysis therefore focussed on MBCT datasets only(n = 708), then were repeated including the additional dataset(n = 880). Memory specificity did not significantly differ from baseline to post-treatment for either MBCT and Control interventions. There was no evidence that baseline memory specificity predicted treatment response in terms of symptom-levels, or risk of relapse. Findings raise important questions regarding the role of memory specificity in depressive treatments.


Subject(s)
Cognitive Behavioral Therapy , Depressive Disorder, Major , Memory, Episodic , Mindfulness , Depressive Disorder, Major/psychology , Humans , Treatment Outcome
14.
Neurobiol Stress ; 15: 100410, 2021 Nov.
Article in English | MEDLINE | ID: mdl-34926732

ABSTRACT

BACKGROUND: Social stress is an important environmental risk factor for the development of psychiatric disorders, including depression and anxiety disorders. Social stress paradigms are commonly used in rats and mice to gain insight into the pathogenesis of these disorders. The social instability stress (SIS) paradigm entails frequent (up to several times a week) introduction of one or multiple unfamiliar same-sex home-cage partners. The subsequent recurring formation of a new social hierarchy results in chronic and unpredictable physical and social stress. PURPOSE: We compare and discuss the stress-related behavioral and physiological impact of SIS protocols in rat and mouse, and address limitations due to protocol variability. We further provide practical recommendations to optimize reproducibility of SIS protocols. METHODS: We conducted a systematic review in accordance with the PRISMA statement in the following three databases: PubMed, Web of Science and Scopus. Our search strategy was not restricted to year of publication but was limited to articles in English that were published in peer-reviewed journals. Search terms included "social* instab*" AND ("animal" OR "rodent" OR "rat*" OR "mice" OR "mouse"). RESULTS: Thirty-three studies met our inclusion criteria. Fifteen articles used a SIS protocol in which the composition of two cage mates is altered daily for sixteen days (SIS16D). Eleven articles used a SIS protocol in which the composition of four cage mates is altered twice per week for 49 days (SIS49D). The remaining seven studies used SIS protocols that differed from these two protocols in experiment duration or cage mate quantity. Behavioral impact of SIS was primarily assessed by quantifying depressive-like, anxiety-like, social-, and cognitive behavior. Physiological impact of SIS was primarily assessed using metabolic parameters, hypothalamus-pituitary-adrenal axis activity, and the assessment of neurobiological parameters such as neuroplasticity and neurogenesis. CONCLUSION: Both shorter and longer SIS protocols induce a wide range of stress-related behavioral and physiological impairments that are relevant for the pathophysiology of depression and anxiety disorders. To date, SIS16D has only been reported in rats, whereas SIS49D has only been reported in mice. Given this species-specific application as well as variability in reported SIS protocols, additional studies should determine whether SIS effects are protocol duration- or species-specific. We address several issues, including a lack of consistency in the used SIS protocols, and suggest practical, concrete improvements in design and reporting of SIS protocols to increase standardization and reproducibility of this etiologically relevant preclinical model of social stress.

15.
World Psychiatry ; 20(3): 387-396, 2021 Oct.
Article in English | MEDLINE | ID: mdl-34505365

ABSTRACT

Major depression is often a relapsing disorder. It is therefore important to start its treatment with therapies that maximize the chance of not only getting the patients well but also keeping them well. We examined the associations between initial treatments and sustained response by conducting a network meta-analysis of randomized controlled trials (RCTs) in which adult patients with major depression were randomized to acute treatment with a psychotherapy (PSY), a protocolized antidepressant pharmacotherapy (PHA), their combination (COM), standard treatment in primary or secondary care (STD), or pill placebo, and were then followed up through a maintenance phase. By design, acute phase treatment could be continued into the maintenance phase, switched to another treatment or followed by discretionary treatment. We included 81 RCTs, with 13,722 participants. Sustained response was defined as responding to the acute treatment and subsequently having no depressive relapse through the maintenance phase (mean duration: 42.2±16.2 weeks, range 24-104 weeks). We extracted the data reported at the time point closest to 12 months. COM resulted in more sustained response than PHA, both when these treatments were continued into the maintenance phase (OR=2.52, 95% CI: 1.66-3.85) and when they were followed by discretionary treatment (OR=1.80, 95% CI: 1.21-2.67). The same applied to COM in comparison with STD (OR=2.90, 95% CI: 1.68-5.01 when COM was continued into the maintenance phase; OR=1.97, 95% CI: 1.51-2.58 when COM was followed by discretionary treatment). PSY also kept the patients well more often than PHA, both when these treatments were continued into the maintenance phase (OR=1.53, 95% CI: 1.00-2.35) and when they were followed by discretionary treatment (OR=1.66, 95% CI: 1.13-2.44). The same applied to PSY compared with STD (OR=1.76, 95% CI: 0.97-3.21 when PSY was continued into the maintenance phase; OR=1.83, 95% CI: 1.20-2.78 when PSY was followed by discretionary treatment). Given the average sustained response rate of 29% on STD, the advantages of PSY or COM over PHA or STD translated into risk differences ranging from 12 to 16 percentage points. We conclude that PSY and COM have more enduring effects than PHA. Clinical guidelines on the initial treatment choice for depression may need to be updated accordingly.

16.
Transl Psychiatry ; 11(1): 168, 2021 03 15.
Article in English | MEDLINE | ID: mdl-33723229

ABSTRACT

No tools are currently available to predict whether a patient suffering from major depressive disorder (MDD) will respond to a certain treatment. Machine learning analysis of magnetic resonance imaging (MRI) data has shown potential in predicting response for individual patients, which may enable personalized treatment decisions and increase treatment efficacy. Here, we evaluated the accuracy of MRI-guided response prediction in MDD. We conducted a systematic review and meta-analysis of all studies using MRI to predict single-subject response to antidepressant treatment in patients with MDD. Classification performance was calculated using a bivariate model and expressed as area under the curve, sensitivity, and specificity. In addition, we analyzed differences in classification performance between different interventions and MRI modalities. Meta-analysis of 22 samples including 957 patients showed an overall area under the bivariate summary receiver operating curve of 0.84 (95% CI 0.81-0.87), sensitivity of 77% (95% CI 71-82), and specificity of 79% (95% CI 73-84). Although classification performance was higher for electroconvulsive therapy outcome prediction (n = 285, 80% sensitivity, 83% specificity) than medication outcome prediction (n = 283, 75% sensitivity, 72% specificity), there was no significant difference in classification performance between treatments or MRI modalities. Prediction of treatment response using machine learning analysis of MRI data is promising but should not yet be implemented into clinical practice. Future studies with more generalizable samples and external validation are needed to establish the potential of MRI to realize individualized patient care in MDD.


Subject(s)
Depressive Disorder, Major , Electroconvulsive Therapy , Antidepressive Agents/therapeutic use , Depressive Disorder, Major/diagnostic imaging , Depressive Disorder, Major/drug therapy , Humans , Machine Learning , Magnetic Resonance Imaging
17.
Clin Psychol Eur ; 3(2): e6871, 2021 Jun.
Article in English | MEDLINE | ID: mdl-36397958
18.
Clin Psychol Eur ; 3(3): e5467, 2021 Sep.
Article in English | MEDLINE | ID: mdl-36398097

ABSTRACT

Background: Behavioral activation is an effective treatment for depression that is theorized to facilitate structured increases in enjoyable activities that increase opportunities for contact with positive reinforcement; to date, however, only few mechanistic studies focused on a standalone intervention. Method: Interventions using internet-based behavioral activation or psychoeducation were compared based on data from a randomized-controlled trial of 313 patients with major depressive disorder. Activation level and depression were measured fortnightly (baseline, Weeks 2, 4, 6, 8, 10), using the Patient Health Questionnaire-9 and the Behavioral Activation for Depression Scale-Short Form, respectively. Analysis was performed to determine if a change in activation level mediated treatment efficacy. Results: Latent growth modeling showed that internet-based behavioral activation treatment significantly reduced depressive symptoms from baseline to the end of treatment (standardized coefficient = -.13, p = .017) by increasing the rate of growth in the activation level (mediated effect estimate = -.17, 95% CI [-.27, -.07]. Results from mixed effects and simplex models showed that it took 4 weeks before mediation occurred (i.e., a significant change in activation that led to a reduction in depressive symptoms). Conclusion: Activation level likely mediated the therapeutic effect of behavioral activation on depression in our intervention. This finding may be of significant value to clinicians and depressed individuals who should anticipate a 4-week window before seeing a prominent change in activation level and a 6-week window before depressive symptomatology reduces. Future research must consolidate our findings on how behavioral activation works and when mediation occurs.

19.
Front Psychiatry ; 11: 574357, 2020.
Article in English | MEDLINE | ID: mdl-33192705

ABSTRACT

Background: Previous studies indicated that affect fluctuations, the use of antidepressant medication (ADM), as well as depression during pregnancy might have adverse effects on offspring outcomes. The aim of the current proof-of-principle study is to explore the effect of tapering ADM while receiving online preventive cognitive therapy (PCT) on pregnant women and the offspring as compared to pregnant women continuing ADM. Objectives: We sought to compare positive and negative affect fluctuations in pregnant women receiving online PCT while tapering ADM vs. pregnant women continuing ADM, and to investigate if affect fluctuations in early pregnancy were related to offspring birth weight. Method: An experience sampling methodology (ESM)-trial ran alongside a Dutch randomized controlled trial (RCT) and prospective observational cohort of women using ADM at the start of pregnancy. In the ESM-trial fluctuations of positive and negative affect were assessed in the first 8 weeks after inclusion. Recurrences of depression were assessed up to 12 weeks post-partum, and birth records were used to assess offspring birth weight. The RCT has been registered at the Netherlands Trial Register (NTR4694, https://www.trialregister.nl/trial/4551). Results: In total, 19 pregnant women using ADM at start of their pregnancy participated in the ESM-trial. There were no significant differences in positive and negative affect fluctuations, nor recurrence rates between women receiving PCT while tapering ADM vs. women continuing ADM. We found no association between affect fluctuations, pre-natal depressive symptoms, and birth weight (all p > 0.05). Conclusion: This explorative study showed that tapering ADM while receiving online PCT may protect pregnant women against recurrences of depression and affect fluctuations, without affecting birth weight. There is a high need for more controlled studies focusing on tapering ADM with (online) psychological interventions during pregnancy.

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Lancet Psychiatry ; 7(10): 851-864, 2020 10.
Article in English | MEDLINE | ID: mdl-32866459

ABSTRACT

BACKGROUND: The effectiveness of digital psychological interventions in low-income and middle-income countries (LMICs) remains unclear. We aimed to systematically investigate the available evidence for digital psychological interventions in reducing mental health problems in LMICs. METHODS: In this systematic review and meta-analysis, we searched PubMed, PsycINFO, Embase, and Cochrane databases for articles published in English from database inception to March 9, 2020. We included randomised controlled trials investigating digital psychological interventions in individuals with mental health problems in LMICs. We extracted data on demographics, inclusion and exclusion criteria, details of the intervention, including the setting, digital delivery method, control group conditions, number of sessions, therapeutic orientation (eg, cognitive therapy or behaviour therapy), presence or absence of guidance, and length of follow-up, and statistical information to calculate effect sizes. If a study reported insufficient data to calculate effect sizes, the corresponding authors were contacted to provide data that could be aggregated. We did random-effects meta-analyses, and calculated the standardised mean difference in scores of digital psychological interventions versus control conditions (Hedges'g). Quality of evidence was assessed by use of the Grading of Recommendations Assessment, Development, and Evaluation approach. The primary outcome was post-intervention mental health problems, as measured by self-reporting instruments or clinical interviews. This study is registered with PROSPERO, CRD42019137755. FINDINGS: We identified 22 eligible studies that were included in the meta-analysis. The included studies involved a total of 4104 participants (2351 who received a digital psychological intervention and 1753 who were in the control group), and mainly focused on young adults (mean age of the study population was 20-35 years) with depression or substance misuse. The results showed that digital psychological interventions are moderately effective when compared with control interventions (Hedges'g 0·60 [95% CI 0·45-0·75]; Hedges'g with treatment as usual subgroup for comparison 0·54 [0·35-0·73]). Heterogeneity between studies was substantial (I2=74% [95% CI 60-83]). There was no evidence of publication bias, and the quality of evidence according to the GRADE criteria was generally high. INTERPRETATION: Digital psychological interventions, which have been mostly studied in individuals with depression and substance misuse, are superior to control conditions, including usual care, and are moderately effective in LMICs. However, the considerable heterogeneity observed in our analysis highlights the need for more studies to be done, with standardised implementation of digital psychological intervention programmes to improve their reproducibility and efficiency. Digital psychological interventions should be considered for regions where usual care for mental health problems is minimal or absent. FUNDING: None. TRANSLATIONS: For the Persian, Chinese, Hindi, Portuguese, Bahasa, Turkish, Romanian, Spanish and Thai translations of the abstract see Supplementary Materials section.


Subject(s)
Depressive Disorder/therapy , Psychotherapy/methods , Substance-Related Disorders/therapy , Telemedicine/methods , Developing Countries , Humans , Outcome Assessment, Health Care , Randomized Controlled Trials as Topic
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