Treatment Of Major Depressive Disorder Research Articles

The Challenges in Treating Obesity Patients with Major Depressive Disorder (MDD) Treatment: a Case Report

The Challenges in Treating Obesity Patients with Major Depressive Disorder (MDD) Treatment: a Case Report

Principal component analysis on the effect of early morning awakening in major depressive disorder

Sleep disturbance is one of the most prevalent symptoms associated with Major Depressive Disorder (MDD). A recent article (Wu et al., 2022, Journal of Multiscale Neuroscience 1, 133-139) explored the significant relationship between early morning awakening (EMA), a type of sleep disturbance, and recovery in MDD patients. In the paper, the authors examined the relationship between EMA and the treatment of MDD with twelve neuropsychological parameters. The authors employed two univariate statistical techniques, students’ t-test and ANOVA, to analyze their data. While their analysis derived a meaningful conclusion that EMA may result in a statistically and clinically significant delay in recovery, we found that a multivariate statistical technique, principal component analysis (PCA), extracted additional quantitative information from their study. In this paper, we present quantitative features in the interaction between EMA and the treatment of MDD obtained from PCA.

Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB)

BackgroundThe diagnosis of major depressive disorder (MDD) is commonly based on the subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is particularly important to find more objective biomarkers to aid in diagnosis and further treatment. Alpha-band activity (7-13 Hz) is the most prominent component in resting electroencephalogram (EEG), which is also thought to be a potential biomarker. Recent studies have shown the existence of multiple sub-oscillations within the alpha band, with distinct neural underpinnings. However, the specific contribution of these alpha sub-oscillations to the diagnosis and treatment of MDD remains unclear. MethodsIn this study, we recorded the resting-state EEG from MDD and HC populations in both open and closed-eye state conditions. We also assessed cognitive processing using the MATRICS Consensus Cognitive Battery (MCCB). ResultsWe found that the MDD group showed significantly higher power in the high alpha range (10.5–11.5 Hz) and lower power in the low alpha range (7–8.5 Hz) compared to the HC group. Notably, high alpha power in the MDD group is negatively correlated with working memory performance in MCCB, whereas no such correlation was found in the HC group. Furthermore, using five established classification algorithms, we discovered that combining alpha oscillations with MCCB scores as features yielded the highest classification accuracy compared to using EEG or MCCB scores alone. ConclusionsOur results demonstrate the potential of sub-oscillations within the alpha frequency band as a potential distinct biomarker. When combined with psychological scales, they may provide guidance relevant for the diagnosis and treatment of MDD.

Intranasal delivery of paroxetine: A preclinical study on pharmacokinetics, depressive-like behaviour, and neurochemical sex differences

Treatment of major depressive disorder remains a major unmet clinical need. Given the advantages of intranasal administration for targeted brain delivery, the present study aimed at investigating the pharmacokinetics of paroxetine, after its intranasal instillation and assessing its potential therapeutic effect on female and male mice subjected to unpredictable chronic mild stress (UCMS) protocol.IN administration revealed direct nose-to-brain paroxetine delivery but dose- and sex-dependent differences. Pharmacokinetics was nonlinear and paroxetine concentrations were consistently higher in plasma and brain of male mice. Additionally, UCMS decreased animal preference for sucrose in both male and female mice following acute (p < 0.01) and chronic stress (p < 0.05), suggesting anhedonia. Both male and female mice exhibited depressive-like behavior in the forced swimming test. UCMS females displayed a significantly longer immobility time and shorter climbing time than the control group (p < 0.05), while no differences were found between male mice. Two weeks of paroxetine intranasal administration reduced immobility time and lengthened climbing and swimming time, approaching values similar to those observed in the healthy control group. The therapeutic effect was stronger on female mice.Importantly, melatonin plasma levels were significantly decreased in female mice following UCMS (p < 0.05), while males exhibited heightened corticosterone levels. On the other hand, treatment with IN paroxetine significantly increased corticosterone and melatonin levels in both sexes compared to healthy mice (p < 0.05).Intranasal paroxetine delivery undoubtedly ameliorated the behavioral despair, characteristic of depressive-like animals. Despite its efficiency in male and female mice subjected to UCMS, females were more prone to this novel therapeutic strategy.

Just a gut feeling: Faecal microbiota transplant for treatment of depression - A mini-review.

The microbiota-gut-brain axis (MGBA) allows bidirectional crosstalk between the brain and gut microbiota (GM) and is believed to contribute to regulating mood/cognition/behaviour/metabolism/health and homeostasis. Manipulation of GM through faecal microbiota transplant (FMT) is a new, exciting and promising treatment for major depressive disorder (MDD). This mini-review examines current research into GM and FMT as a therapy for depression. Original research articles published in Medline/Cochrane Library/PubMed/EMBASE/PsycINFO databases/National Institute of Health website Clinicaltrials.gov/controlled-trials.com were searched. Full articles included in reference lists were evaluated. We summarise current data on GM and depression and discuss communication through the MGBA and the interaction of antidepressants and GM through this. We review compositions of dysbiosis in depressed cohorts, focusing on future directions in the treatment of MDD. Studies have demonstrated significant gut dysbiosis in depressed patients compared to healthy cohorts, with overgrowth of pro-inflammatory microbiota, reduction in anti-inflammatory species and reduced overall stability and taxonomic richness. FMT allows the introduction of healthy microbiota into the gastrointestinal tract, facilitating the restoration of eubiosis. The GM plays an integral role in human health and disease through its communication with the rest of the body via the MGBA. FMT may provide a means to transfer the healthy phenotype into the recipient and this concept in humans is attracting enormous attention as a prospective treatment for psychopathologies, such as MDD, in the future. It may be possible to manipulate the GM in a number of ways, but further research is needed to determine the exact likelihood and profiles involved in the development and amelioration of MDD in humans, as well as the long-term effects and potential risks of this procedure.

Treatment of Depression in Huntington's Disease: A Systematic Review.

Depression is a common psychiatric disorder among individuals with Huntington's disease (HD). Depression in HD and major depressive disorder appear to have different pathophysiological mechanisms. Despite the unique pathophysiology, the treatment of depression in HD is based on data from the treatment of major depressive disorder in the general population. The objective of this systematic review was to conduct a comprehensive evaluation of the available evidence. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Studies on the treatment of depression in HD were identified by searching MEDLINE, Embase, and PsycInfo. The initial search yielded 2,771 records, 41 of which were ultimately included. There were 19 case reports, seven case series, three cross-sectional studies, one qualitative study, nine nonrandomized studies, and two randomized trials among the included studies. The most common assessment tools were the Hospital Anxiety and Depression Scale (N=8), the Beck Depression Inventory (N=6), and the Hamilton Depression Rating Scale (N=6). Only 59% of the included studies assessed depressive symptoms with a scoring system. The pharmacological options for the treatment of depression included antidepressants and antipsychotics. Nonpharmacological approaches were multidisciplinary rehabilitation, psychotherapy, and neurostimulation. Limited evidence on the treatment of depression in HD was available, and this literature consisted mainly of case reports and case series. This systematic review highlights the knowledge gap and the pressing need for HD-specific research to determine the efficacy of treatment approaches for depression in HD.

A Canadian Simulation Model for Major Depressive Disorder: Study Protocol.

Major depressive disorder (MDD) is a common, often recurrent condition and a significant driver of healthcare costs. People with MDD often receive pharmacological therapy as the first-line treatment, but the majority of people require more than one medication trial to find one that relieves symptoms without causing intolerable side effects. There is an acute need for more effective interventions to improve patients' remission and quality of life and reduce the condition's economic burden on the healthcare system. Pharmacogenomic (PGx) testing could deliver these objectives, using genomic information to guide prescribing decisions. With an already complex and multifaceted care pathway for MDD, future evaluations of new treatment options require a flexible analytic infrastructure encompassing the entire care pathway. Individual-level simulation models are ideally suited for this purpose. We sought to develop an economic simulation model to assess the effectiveness and cost effectiveness of PGx testing for individuals with major depression. Additionally, the model serves as an analytic infrastructure, simulating the entire patient pathway for those with MDD. Key stakeholders, including patient partners, clinical experts, researchers, and modelers, designed and developed a discrete-time microsimulation model of the clinical pathways of adults with MDD in British Columbia (BC), including all publicly-funded treatment options and multiple treatment steps. The Simulation Model of Major Depression (SiMMDep) was coded with a modular approach to enhance flexibility. The model was populated using multiple original data analyses conducted with BC administrative data, a systematic review, and an expert panel. The model accommodates newly diagnosed and prevalent adult patients with MDD in BC, with and without PGx-guided treatment. SiMMDep comprises over 1500 parameters in eight modules: entry cohort, demographics, disease progression, treatment, adverse events, hospitalization, costs and quality-adjusted life-years (payoff), and mortality. The model predicts health outcomes and estimates costs from a health system perspective. In addition, the model can incorporate interactive decision nodes to address different implementation strategies for PGx testing (or other interventions) along the clinical pathway. We conducted various forms of model validation (face, internal, and cross-validity) to ensure the correct functioning and expected results of SiMMDep. SiMMDep is Canada's first medication-specific, discrete-time microsimulation model for the treatment of MDD. With patientpartner collaboration guiding its development, it incorporates realistic care journeys. SiMMDep synthesizes existing information and incorporates provincially-specific data to predict the benefits and costs associated with PGx testing. These predictions estimate the effectiveness, cost-effectiveness, resource utilization, and health gains of PGx testing compared with the current standard of care. However, the flexible analytic infrastructure can be adapted to support other policy questions and facilitate the rapid synthesis of new data for a broader search for efficiency improvements in the clinical field of depression.

MicroRNAs as Diagnostic Biomarkers and Predictors of Antidepressant Response in Major Depressive Disorder: A Systematic Review.

Despite the hardships of major depressive disorder (MDD), biomarkers for the diagnosis and pharmacological management of this condition are lacking. MicroRNAs are epigenetic mechanisms that could provide promising MDD biomarkers. Our aim was to summarize the findings and provide validation for the selection and use of specific microRNAs as biomarkers in the diagnosis and treatment of MDD. A systematic review was conducted using the PubMed/Medline, Cochrane, PsycINFO, Embase, and LILACS databases from March 2022 to November 2023, with clusters of terms based on "microRNA" and "antidepressant". Studies involving human subjects, animal models, and cell cultures were included, whereas those that evaluated herbal medicines, non-pharmacological therapies, or epigenetic mechanisms other than miRNA were excluded. The review revealed differences in the expression of various microRNAs when considering the time of assessment (before or after antidepressant treatment) and the population studied. However, due to the heterogeneity of the microRNAs investigated, the limited size of the samples, and the wide variety of antidepressants used, few conclusions could be made. Despite the observed heterogeneity, the following microRNAs were determined to be important factors in MDD and the antidepressant response: mir-1202, mir-135, mir-124, and mir-16. The findings indicate the potential for the use of microRNAs as biomarkers for the diagnosis and treatment of MDD; however, more homogeneous studies are needed.

"I can't escape my scars, even if I do get better": A qualitative exploration of how adolescents talk about their self-harm and self-harm scars during cognitive behavioural therapy for depression.

Emerging evidence indicates that perceptions of self-harm behaviours and self-harm scars may thwart recovery from depression, yet limited research has explored adolescent accounts of their self-harm and scars during therapy. This study sought to explore how adolescents describe their self-harm behaviours and scars during Cognitive Behavioural Therapy (CBT) and explore the sociocultural discourses that may influence these descriptions. The participants were six female adolescents (aged 14-17years old) with clinical depression, who were engaging in self-harm. All participants accessed CBT as part of clinical trial evaluating three psychological treatments for major depressive disorder in Child and Adolescent Mental Health Services. Audio-taped CBT sessions were analyzed using discourse analysis. Within CBT sessions, adolescents drew upon stigma discourses in talking about their self-harm. Adolescent also described their self-harm scars as shameful and stigmatizing, and as "proof" of the legitimacy of their depression. It is important for CBT practitioners to understand the context of sociocultural discourses around self-harm behaviours and self-harm scars, which are reflected in how adolescents with depression describe these within therapy and may serve to maintain distress. The study indicates that awareness of use of language and intersecting sociocultural discourses can inform CBT practice.

FDA gives breakthrough designation for psychedelic treatment

A clinical‐stage biopharmaceutical company that officials said is committed to revolutionizing mental health care by developing new and innovative next‐generation psychedelic‐based treatment options, announced last week that the U.S. Food and Drug Administration (FDA) has granted Breakthrough Therapy Designation (BTD) for an adjunctive psychedelic‐based therapy for the treatment of major depressive disorder (MDD), according to the press release news outlet, Businesswire.

The utility of measuring daily hassles and uplifts in understanding outcomes to treatments for major depressive disorder

Little is known about the effects of common daily experiences in patients with major depressive disorder (MDD). The Daily Hassles and Uplifts Scale (HUPS) was assessed in 142 treatment-naïve adult MDD outpatients randomized to 12 weeks of treatment with either antidepressant medication (ADM) or Cognitive Behavior Therapy (CBT). Three HUPS measures were analyzed: hassle frequency (HF), uplift frequency (UF), and the mean hassle intensity to mean uplift intensity ratio (MHI:MUI). Remission after treatment was not predicted by these baseline HUPS measures and did not moderate outcomes by treatment type. In contrast, HUPS measures significantly changed with treatment and were impacted by remission status. Specifically, HF and MHI:MUI decreased and UF increased from baseline to week 12, with remission leading to significantly greater decreases in HF and MHI:MUI compared to non-remission. ADM-treated patients demonstrated significant improvements on all three HUPS measures regardless of remission status. In contrast, remitters to CBT demonstrated significant improvements in HF and MHI:MUI but not UF; among CBT non-remitters the only significant change was a reduction in HF. The changes in HUPS measures are consistent with how affective biases are impacted by treatments and support the potential value of increasing attention to positive events in CBT.

Duloxetine: An update

Duloxetine, a serotonin-norepinephrine reuptake inhibitor (SNRI), has established itself as a versatile therapeutic agent across a spectrum of psychiatric and neurological disorders. The objective of this article is to update the pharmacological properties of duloxetine. To this end, a review was carried out on the pharmacology, clinical efficacy, safety and tolerability of duloxetine, focusing on its application in the treatment of major depressive disorder (MDD), generalized anxiety disorder (GAD), diabetic peripheral neuropathic pain, fibromyalgia and musculoskeletal pain. chronic. Comparative analyzes highlight the relative effectiveness of duloxetine versus other antidepressants and its unique advantage in managing conditions with overlapping mood and pain symptoms. Safety profiles and pharmacological interactions, particularly with NSAIDs and tamoxifen, highlight the importance of personalized treatment plans and vigilant monitoring. The review concludes with an assessment of the clinical utility of duloxetine, emphasizing individual patient assessment to maximize therapeutic outcomes while minimizing risks. Future research directions are suggested to further delineate the role of duloxetine in treatment algorithms and explore potential new indications.

Pediatric Extrapolation Approach for U.S. Food and Drug Administration Approval of Brexpiprazole in Patients Aged 13 to 17 Years with Schizophrenia.

A pharmacokinetic (PK) bridging approach was successfully employed to support the dosing regimen and approval of brexpiprazole in pediatric patients aged 13-17 years with schizophrenia. Brexpiprazole was approved in 2015 for the treatment of schizophrenia and the adjunctive treatment of major depressive disorder in adults based on efficacy and safety data from clinical trials. On January 13, 2020, the US Food and Drug Administration issued a general advice letter to sponsors highlighting the acceptance of efficacy extrapolation of certain atypical antipsychotics from adult patients to pediatric patients considering the similarity in disease and exposure-response relationships. Brexpiprazole is the first atypical antipsychotic approved in pediatrics using this approach. The PK data available from pediatric patients aged 13-17 years have shown high variability due to the limited number of PK evaluable subjects, which limits a robust estimation of differences between adult and pediatric patients. The PK model-based approach was thus utilized to evaluate the appropriateness of the dosing regimen by comparing PK exposures in pediatric patients aged 13-17 years with exposures achieved in adults at the approved doses. In addition to exposure matching, safety data from a long-term open-label clinical study in pediatric patients informed the safety profile in pediatric patients. This report illustrates the potential of leveraging previously collected efficacy, safety, and PK data in adult patients to make a regulatory decision in pediatric patients for the indication of schizophrenia.

The protective effect of vitamin D supplementation as adjunctive therapy to antidepressants on brain structural and functional connectivity of patients with major depressive disorder: a randomized controlled trial.

Growing evidence points to the pivotal role of vitamin D in the pathophysiology and treatment of major depressive disorder (MDD). However, there is a paucity of longitudinal research investigating the effects of vitamin D supplementation on the brain of MDD patients. We conducted a double-blind randomized controlled trial in 46 MDD patients, who were randomly allocated into either VD (antidepressant medication + vitamin D supplementation) or NVD (antidepressant medication + placebos) groups. Data from diffusion tensor imaging, resting-state functional MRI, serum vitamin D concentration, and clinical symptoms were obtained at baseline and after an average of 7 months of intervention. Both VD and NVD groups showed significant improvement in depression and anxiety symptoms but with no significant differences between the two groups. However, a greater increase in serum vitamin D concentration was found to be associated with greater improvement in depression and anxiety symptoms in VD group. More importantly, neuroimaging data demonstrated disrupted white matter integrity of right inferior fronto-occipital fasciculus along with decreased functional connectivity between right frontoparietal and medial visual networks after intervention in NVD group, but no changes in VD group. These findings suggest that vitamin D supplementation as adjunctive therapy to antidepressants may not only contribute to improvement in clinical symptoms but also help preserve brain structural and functional connectivity in MDD patients.

Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records.

Efforts to develop an individualized treatment rule (ITR) to optimize major depressive disorder (MDD) treatment with antidepressant medication (ADM), psychotherapy, or combined ADM-psychotherapy have been hampered by small samples, small predictor sets, and suboptimal analysis methods. Analyses of large administrative databases designed to approximate experiments followed iteratively by pragmatic trials hold promise for resolving these problems. The current report presents a proof-of-concept study using electronic health records (EHR) of n = 43,470 outpatients beginning MDD treatment in Veterans Health Administration Primary Care Mental Health Integration (PC-MHI) clinics, which offer access not only to ADMs but also psychotherapy and combined ADM-psychotherapy. EHR and geospatial databases were used to generate an extensive baseline predictor set (5,865 variables). The outcome was a composite measure of at least one serious negative event (suicide attempt, psychiatric emergency department visit, psychiatric hospitalization, suicide death) over the next 12 months. Best-practices methods were used to adjust for nonrandom treatment assignment and to estimate a preliminary ITR in a 70% training sample and to evaluate the ITR in the 30% test sample. Statistically significant aggregate variation was found in overall probability of the outcome related to baseline predictors (AU-ROC = 0.68, S.E. = 0.01), with test sample outcome prevalence of 32.6% among the 5% of patients having highest predicted risk compared to 7.1% in the remainder of the test sample. The ITR found that psychotherapy-only was the optimal treatment for 56.0% of patients (roughly 20% lower risk of the outcome than if receiving one of the other treatments) and that treatment type was unrelated to outcome risk among other patients. Change in aggregate treatment costs of implementing this ITR would be negligible, as 16.1% fewer patients would be prescribed ADMs and 2.9% more would receive psychotherapy. A pragmatic trial would be needed to confirm the accuracy of the ITR.

Alterations of the amplitude of low-frequency fluctuation induced by repetitive transcranial magnetic stimulation combined with antidepressants treatment for major depressive disorder

We investigated the neuroimaging changes and clinical efficacy of repetitive transcranial magnetic stimulation (rTMS) combined with antidepressants in major depressive disorder (MDD) patients. We scanned 35 patients with MDD and 27 healthy controls (HC) with resting-state functional magnetic resonance imaging (fMRI) before and after treatment. We analyzed amplitude of low-frequency fluctuation (ALFF) and the correlation with clinical variables. The rate of significant efficacy after treatment was higher in the combination treatment group than in the antidepressant group, although not statistically significant. At baseline, ALFF increased in the left middle temporal, brain stem, and left cerebellum and decreased in the right anterior cingulate (ACC), right orbital frontal cortex (OFC), and right caudate. ALFF increased in the left fusiform and decreased in the right lingual gyrus, left middle occipital gyrus, and left superior occipital gyrus after antidepressants. ALFF increased in the right ACC, right OFC, and right rectus after combination treatment. ALFF changes in the right ACC/OFC were negatively correlated with HAMD changes. After treatment, abnormal activity in some brain regions normalized, but these regions differed between the two treatment groups. rTMS combined with antidepressants therapy may improve MDD symptoms by improving neuronal activity levels in the right ACC and right OFC.

Predictive modeling of antidepressant efficacy based on cognitive neuropsychological theory

BackgroundWe aimed to develop a clinical predictive model based on the cognitive neuropsychological (CNP) theory and machine-learning to examine SSRI efficacy in the treatment of MDD. MethodsBaseline assessments including clinical symptoms (HAMD, HAMA, BDI, and TEPS scores), negative biases (NEO-PI-R-N and NCPBQ scores), sociodemographic characteristics (social support and SES), and a 5-min eye-opening resting-state EEG were completed by 69 participants with first-episode major depressive disorder (MDD) and 36 healthy controls. The clinical symptoms and negative bias were again assessed after an 8-week treatment of depression with selective serotonin reuptake inhibitors (SSRIs). A multi-modality machine-learning model was developed to predict the effectiveness of SSRI antidepressants. ResultsAt baseline, we observed significant differences between MDD patients and healthy controls in terms of social support, clinical symptoms, and negative bias characteristics (p < 0.001). A negative association was found (p < 0.05) between neuroticism and alpha asymmetry in both the central and central-parietal areas, as well as between negative cognitive processing bias and alpha asymmetry in the parietal region. Compared to responders, non-responders exhibited less negative cognitive processing bias and greater alpha asymmetry in both central and central-parietal regions. Importantly, we developed a multi-modality machine-learning model with 83 % specificity using the above salient features. ConclusionsResearch results support the CNP theory of depression treatment. To some extent, the multimodal clinical model constructed based on the CNP theory effectively predicted the efficacy of this treatment in this population. LimitationsSmall sample and only focus on the mechanisms of delayed-onset SSRI treatment.

A Real-life Study of Brexpiprazole as an Adjunctive Treatment for Major Depressive Disorder in Asian Patients in Singapore (BADA)

A Real-life Study of Brexpiprazole as an Adjunctive Treatment for Major Depressive Disorder in Asian Patients in Singapore (BADA)

Niosomal Bupropion: Exploring Therapeutic Frontiers through Behavioral Profiling.

Bupropion (Bup) belongs to the norepinephrine-dopamine reuptake inhibitor (NDRI) class and it is the only FDA-approved drug of its class for the treatment of major depressive disorder (MDD), sold under the name of Wellbutrin. Although bupropion is effective in suppressing the symptoms, its regular use and overdose might lead to seizures and liver failure. Thus, we aimed to nanoformulate bupropion onto a niosomal vesicle to improve its efficacy and achieve the same therapeutic effect at lower scheduled doses. A thin film hydration method was adopted to synthesize and optimize Bup entrapped niosomes using three different surfactants of the sorbitan ester series (Span 20, 40, and 60) in combination with cholesterol. The optimization data determined that the niosome formulated with a cholesterol-to-surfactant ratio of 1:1.5 is the most stable system, with the Bup entrapped niosomes containing Span 20 (Bup@N20C) exhibiting minimal in vitro and in vivo toxicity, and demonstrating the sustained release of Bup in artificial cerebrospinal fluid (ACSF). The Bup@N20C formulation showed increased exploration activity and reduced irregular movements in reserpine-induced depression in the adult zebrafish model, suggesting the potential for mood improvement through the suppression of depression-like behavior which was established by statistical analysis and trajectory data. The Bup@N20C-treated group even surpasses the treatment effect of the positive control group and is comparable to the control group. Hence, it can be inferred that niosomal formulations of Bup represent a promising delivery system capable of achieving the brain delivery of the cargo by bypassing the blood-brain barrier facilitated by their small architectural structure.

Who benefits from indirect prevention and treatment of depression using an online intervention for insomnia? Results from an individual-participant data meta-analysis.

Major depressive disorder (MDD) is highly prevalent and burdensome for individuals and society. While there are psychological interventions able to prevent and treat MDD, uptake remains low. To overcome structural and attitudinal barriers, an indirect approach of using online insomnia interventions seems promising because insomnia is less stigmatized, predicts MDD onset, is often comorbid and can outlast MDD treatment. This individual-participant-data meta-analysis evaluated the potential of the online insomnia intervention GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics. Efficacy on depressive symptom outcomes was evaluated using multilevel regression models controlling for baseline severity. To identify potential effect moderators, clinical, sociodemographic, and work-related variables were investigated using univariable moderation and random-forest methodology before developing a multivariable decision tree. IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-assessment (d = -0.71 [95% CI-0.92 to -0.51]) and at follow-up (d = -0.84 [95% CI -1.11 to -0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d = -0.48 and -0.87 (post) and d = - 0.66 to -0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators. An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.