Journal of Affective Disorders Reports

BackgroundStudies suggest that good self-management is associated with better coping with chronic mental conditions. However, an encompassing assessment of the relationship between depression and self-management competence is lacking. MethodsThis study assesses the relationship between depressiveness and self-management competence in a sample of 83 depressed in-patients. Beck Depression Inventory II (BDI-II) was used to assess depressiveness. The Self-Management Self-Test (SMST) was used to assess self-management competence. Patient surveys took place at the time of hospital admission (T1) and at the time of hospital discharge or approximately 4 to 6 weeks after (T2). ResultsSelf-management competence correlated negatively with depressiveness at T1. Four out of five specific dimensions of self-management competence correlated inversely with depressiveness at T1. Self-management competence differed depending on the severity of the depressive syndrome and was higher the lower the severity of the depressive syndrome was. In the course of clinical treatment, self-management competence increased. Change of self-management competence during clinical treatment was not dependent on the sociodemographic variables gender or age. Change of self-management competence during clinical treatment predicted the change of depressiveness between hospital admission and discharge (T2 vs. T1) as well as depressiveness at T2. LimitationsSample size was relatively small. The SMST is a relatively new psychometric instrument that has not yet found widespread use in clinical research. ConclusionOur findings offer clinical evidence that in depressed in-patients, self-management competence and depressiveness are associated constructs. These results suggest that self-management competence may be a valuable resource in the treatment of depressive disorders.

BackgroundMajor depressive disorder (MDD) with suicidality represents a significant public health concern, as suicide ranks among the leading causes of death worldwide. While electroencephalography (EEG) has shown promise in depression diagnosis, its utility in identifying suicidal risk remains underexplored. This study aims to develop and validate a Suicidal Risk Index (SR Index) using EEG biomarkers and machine learning (ML) algorithms for distinguishing between MDD patients with and without suicidality. MethodsIn this retrospective observational study, resting-state EEG data were collected using Stress EEG Assessment (SEA) system. SR Index was developed by integrating the PHQ-9 scale with EEG-derived features, including band power, coherence, and fractal dimension, optimized using ML algorithms to enhance accuracy. ResultsThe study included 268 participants (159 without suicidality, 109 with suicidality). The SR Index demonstrated robust discriminative ability with an AUC of 0.8117 (p=2.63x10-18). At the optimal cutoff value of 8, the model achieved 88.99% sensitivity, 57.23% specificity, 67.86% positive predictive value, and 78.85% negative predictive value, with a balanced accuracy of 73.11%. ConclusionsThe SR Index shows promise as an objective tool for identifying suicidality in MDD patients, potentially complementing traditional clinical assessments. This approach may enhance early detection and risk stratification in clinical settings, potentially improving suicide prevention strategies. HighlightsO_LINovel EEG- and ML-based Suicidal Risk Index distinguishes MDD patients with and without suicidality. C_LIO_LISR Index achieves 88.99% sensitivity and 73.11% balanced accuracy in identifying suicidal risk. C_LI

Major depressive disorder (MDD) imposes significant disability on patients. In addition to antidepressants, brain stimulation modalities such as electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS) have been helpful in treatment of MDD. Novel TMS paradigms like theta burst stimulation (TBS) have rapidly become popular due to their effectiveness. Given that both antidepressants and TMS are commonly used together and affect neuroplasticity, we reviewed studies that administered both these as treatments for MDD. Unlike ECT wherein previous trials have shown that continuing pharmacotherapy is useful while giving ECT, there are no consensus guidelines on what to do with antidepressants when starting TMS. So, we reviewed two groups of studies - 1) those that administered TMS and antidepressant pharmacotherapy concurrently and 2) those wherein TMS augmented antidepressants or were an adjunctive intervention to antidepressants. We performed a meta-analysis for randomized clinical trials (RCTs) that administered TMS and antidepressants concurrently. We found ten RCTs fulfilling criteria 1 and compared uniformly titrated antidepressant regimens combined with active versus sham TMS. We also found twenty studies fulfilling criterion 2, that used TMS as an augmenting or adjunctive intervention. Both groups of studies showed TMS combined with antidepressants had greater efficacy for treatment of MDD. We advocate for laboratory studies examining the interaction between TMS and antidepressants in a parametric fashion; in addition to randomized controlled trials that examine this combination to expedite remission in MDD.

ObjectiveRepetitive transcranial magnetic stimulation (rTMS) is an effective, evidence-based treatment for major depressive disorder (MDD) and is publicly funded in Australia. However, there is no published data to date concerning its use in private TMS service provider clinics in Australia. There is further limited data as to its efficacy and safety in treating MDD in youth populations. MethodsThis retrospective study examined routinely collected data of 46 outpatients aged 17 to 25 years old, who received rTMS treatment for MDD in a private TMS clinic. Primary outcomes measures were the Montgomery-Asberg Depression Rating Scale (MADRS) and the depression subscale of the 21-item Depression, Anxiety and Stress Scale (DASS-21). Secondary measures included the anxiety and stress sub-scales of the DASS-21, a measure of Quality of Life (QoL) Enjoyment and Satisfaction Questionnaire, and the Cognitive Failures Questionnaire (CFQ). ResultsA 4-7-week course of rTMS significantly reduce symptoms of self-reported depression (42.5% response) and clinician-assessed depression (40.7% response). Both anxiety and stress significantly reduced across the course of rTMS treatment and significant improvements to QoL and self-reported cognition were observed. Reported side effects following rTMS in youth included a mild headache and fatigue. ConclusionsThe findings of this naturalistic study suggest that an acute course of rTMS provided in private clinical settings is safe and effective - resulting in similar response rates in youth patients as reported in adult patients. In real world practice, rTMS proves to be a well-tolerated and highly effective intervention for MDD in youth, across diverse clinical settings. Implications and ContributionThe findings of this naturalistic study suggest that in real world practice, rTMS proves to be a well-tolerated and highly effective intervention for treating depression and anxiety in youth (17-25-year-olds), with additional benefits to cognitive symptoms of depression and overall well-being.

BackgroundRepetitive transcranial magnetic stimulation (rTMS) has been increasingly used worldwide in the treatment of depression, however, we currently lack the means to reliably predict whether patients will respond to the treatment. Recent research suggests that the neurophysiological measures of beta power and correlation dimension may have predictive potential, however, studies of beta power and correlation dimension to differentiate rTMS group response in individuals with major depression are limited. MethodsFifty treatment-resistant patients with major depressive disorder were recruited. Forty-two participants underwent baseline resting EEG sessions and 5-8 weeks of rTMS treatments and 12 participants were responders to the treatment. Beta power and correlation dimension from baseline resting EEG were compared between responders and non-responders. ResultsResponders demonstrated significantly lower beta power in baseline resting EEG, however, correlation dimension did not show a significant difference between groups. LimitationsThere were a small number of responders in this study. ConclusionBaseline resting beta power may help to differentiate responders from non-responders to rTMS treatment. However, further studies are needed with larger sample sizes.

IntroductionDepression is a highly prevalent and potentially chronic mental disorder with significant impact on quality of life and social support, with a frequent onset in early adulthood. Despite the existence of effective treatments, many individuals do not have access to care, do not respond to, or do not tolerate medications. Additionally, access to mental health services remains limited, especially in low- and middle-income countries, where the World Health Organization estimates that 75% of individuals do not receive adequate care. Group Interpersonal Therapy (IPT-G) is an evidence-based, structured psychotherapy recommended by international guidelines for the treatment of depression and is adaptable for task-shifting approaches in primary care. Previous research has shown promising results for IPT-G delivered by non-specialists in low-resource settings in an open study, but randomized trials by non-specialists are still lacking. ObjectivesTo evaluate the improvement in depressive symptoms after eight sessions of IPT-G among young adults with depressive symptoms in a community setting, conducted by non-specialists in a randomized trial, representing a new step in demonstrating scientific evidence for novel clinical treatments. MethodsThis randomized controlled clinical trial is planned to include 80 participants randomized (1:1) between an interventional (IPT-G) and a control (waiting list) group. Our study will enroll young adults aged 18 to 24 years with depressive symptoms. The intervention will focus on interpersonal relationships within the IPT model and will be delivered by a university student and a medical doctor trained in IPT. The primary outcomes are depressive symptoms; secondary outcomes include quality of life and social support. ResultsThe trial was approved by the Research Ethics Committee (CEP) of the HCPA (Project number: 2023-0283, CAAE: 73830223.7.0000.5327) and registered on ClinicalTrials.gov (NCT06480019). Recruitment started in February 2024 and is ongoing. ConclusionThis study could support the integration of IPT-G delivered by non-specialists into public health systems worldwide as a low-cost and accessible intervention. Findings could help reduce mental health service gaps and increase the capacity of public health systems to treat depression. STRENGTHS AND LIMITATIONS OF THIS STUDYThis study has the strength of being the first randomized controlled trial evaluating IPT-G delivered by non-specialists. It is conducted in a middle-income country, where, despite the existence of guidelines recommending IPT-G implementation by non-specialists, there are no randomized trials. The study also has some limitations: participants are not restricted from seeking other mental health treatments during the trial, and the intervention is compared with a waitlist control rather than an active treatment condition. Version 2.0 - 10 October 2025 (Final version submitted)

BackgroundDepression is a leading global cause of disability, significantly affecting individuals quality of life and contributing to a substantial worldwide health burden. Self-help practices have emerged as cost-effective and scalable strategies for managing mild to moderate depression, empowering individuals to take an active role in their mental health care. Theory-based interventions, which are grounded in established psychological frameworks, provide a systematic approach to designing, implementing and evaluating these self-help practices. However, despite the growing availability of self-help interventions, their effectiveness varies, and many lack a solid theoretical foundation. Summarized evidence of the effects of theory-based interventions remains limited. ObjectivesThis systematic review aims to evaluate the effects of theory-based interventions incorporating self-help practices in reducing depressive symptoms severity among adults with mild to moderate depression. MethodsThe review will follow PRISMA guidelines and has been registered with the International Prospective Register of Systematic Reviews (PROSPERO). Randomised trials evaluating theory-based interventions, such as Cognitive Behavioral Therapy (CBT), Acceptance and Commitment Therapy (ACT), and Mindfulness-Based Interventions (MBIs), delivered via digital platforms will be included. Studies will be identified through searches of PubMed, Scopus, Web of Science, Science Direct and Cochrane bibliographic databases. Data extraction and risk of bias assessment will be conducted independently by two reviewers, focusing on study characteristics, intervention details and critical outcomes (reduction in depressive symptom severity and adverse effects). ResultsThe review will synthesize evidence on the effects and adaptability of theory-based interventions, highlighting the specific contributions of theoretical frameworks to intervention outcomes. Findings will be presented in tabular and narrative formats, identifying gaps and implications for clinical practice and future research. ConclusionThis systematic review will provide actionable insights into the design and implementation of theory-based interventions for managing mild to moderate depression. The findings aim to inform evidence-based guidelines for primary care integration, promoting accessible, scalable and effective mental health solutions globally.

BackgroundPatients recovering from COVID-19 often suffer long-term Long-COVID (e.g., depression, poor concentration, anxiety, sleep disturbances, and fatigue). Similar symptoms also rarely seem to occur after COVID-19 vaccination. There is still no effective treatment for these symptoms. We have had a clinical experience that patients presenting with psychiatric/physical symptoms due to COVID-19 or COVID-19 vaccination (defined as Long-COVID and Post-Vaccine patients) often recover after transcranial magnetic stimulation (TMS) and that TMS poorly heals depression in strongly fatigued patients. Aims1. Determine whether there are differences in background characteristics and symptoms between Long-COVID and Post-Vaccine patients; 2. Examine whether TMS led to an improvement in their symptoms; 3. Test the involvement of fatigue in the recovery of depression of Long-COVID and Post-Vaccine patients with TMS. MethodsWe conducted a retrospective analysis using the medical records of the outpatient clinic of Tokyo TMS Clinic. Results1. We found no differences in initial symptoms and courses of treatment between Long-COVID and Post-Vaccine patients. 2. All psychiatric/physical symptom scores after 10 TMS treatments were significantly better than before. Though these results are of before-and-after studies, numerous reports have suggested that TMS effectively improves depression, insomnia, anxiety, and related neuropsychiatric symptoms, which were also primary complaints of patients in this study. We thus attributed the improvement in QIDS, PHQ9 (Both indices of depression), and GAD7 (anxiety indicator) to TMS. 3. The recovery rate of depression in Long-Covid and Post-Vaccine patients with TMS decreased with the severity of fatigue. ConclusionsThis is the first report to elucidate the efficacy of TMS and the factors affecting it for psychiatric symptoms after COVID-19 and COVID-19 vaccination. Our study may lead to further validation of the effectiveness and mechanisms of TMS in patients suffering from Long-COVID and COVID-19 vaccine long-term adverse reactions.

ObjectivesCombined oral contraceptive (COC) use is linked to increased depression risk, potentially via serotonergic pathways. This study examined whether serotonin 2A/2C receptor (5-HT2AR/5-HT2CR) brain binding differs between healthy women using COCs and non-users. Methods71 healthy women had been scanned with either [18F]Altanserin (17 COC users, 22 non-users) or [11C]Cimbi-36 Positron Emission Tomography (17 COC users, 15 non-users). Multiple linear regression and latent variable models were used to assess associations between COC use and neocortical 5-HT2AR and subcortical-HT2AR/5-HT2CR binding, respectively.. Analyses were performed on data pooled across both radiotracers and on each tracer, separately. ResultsIn pooled analyses across both tracers, COC use was not significantly associated with 5-HT2AR binding in the neocortex (-7.7%, 95% CI [-18.9;5.2], p=0.22), nor with 5-HT2AR/5-HT2CR in subcortical regions (-7.8, 95% CI [-21.7;7.7], p=0.31). In [11C]Cimbi-36-only analyses, COC use was associated with -12.6% (95% CI [-22.1;-1.9], p=0.02) lower 5-HT2AR binding in neocortex and -23.5% lower 5-HT2AR/5-HT2CR binding in subcortical regions (95% CI [-35.6;-9.1], p=0.002). No significant differences were observed in the [18F]Altanserin-only analyses. ConclusionThe [11C]Cimbi-36 data indicated lower cortical 5-HT2AR and subcortical 5-HT2AR/5-HT2CR binding in COC users compared to non-users, but this was not observed in the [18F]Altanserin data. This may reflect better signal-to-noise properties of [11C]Cimbi-36 and the fact that it binds more selectively to the high-affinity, biologically active receptor state. These results offer potential mechanistic insights into the depression risk associated with COC use and may have implications for treatments targeting 5-HT2AR/5-HT2CR, underscoring the need for replication and further investigation. Highlights1) COC use was associated with lower 5-HT2AR/CR brain binding in Cimbi-36 PET data 2) COC use was not associated with 5-HT2AR brain binding in [18F]Altanserin PET data 3) We speculate if lower 5-HT2AR/CR levels may affect treatments targeting 5-HT2AR/CR

BackgroundRepetitive transcranial magnetic stimulation (TMS) is now widely accepted as an effective non-pharmacologic treatment for treatment-resistant depression. However, whether repeated acute TMS courses can recapture the antidepressant effects of the initial acute course is still an open question, especially in the Veteran population. We present here a retrospective analysis of a specialty clinic within the Veteran Affairs Hospital System to help address this question. AimsFollowing an acute treatment course of TMS, we sought to determine the treatment response of a subsequent TMS course. We hypothesized that those who responded to an initial acute TMS course would respond in a similar manner to a subsequent treatment course. Methods116 cases referred for evaluation for TMS between September 2017 to April 2021 were reviewed. 63 Veterans completed at least one acute course of TMS and 12 completed at least two courses and met inclusion criteria for this review. Symptoms were evaluated via self-reported scales at baseline and weekly throughout treatment. Clinical response to subsequent treatment (>50% symptom reduction as measured by the PHQ-9) was compared to initial treatment response. ResultsOf the initial treatment responders (n = 6), all six responded to a second acute course, with an 85.3% symptom reduction. Of the initial treatment nonresponders (n = 6), three responded to a second acute course. Exploratory regression analysis predicted change in depression symptoms (PHQ-9) during a second TMS course using initial treatment response, time into treatment, and baseline symptom severity. Together, these factors explained 72% of the variance. No adverse events were reported in those who completed a second course, and the Veterans tolerated the treatment well. ConclusionsOur findings support the growing understanding that a second acute TMS treatment course for treatment-resistant depression is safe, well-tolerated, and effective in initial responders and some non-responders. Despite multiple confounders in a naturalistic setting, robust initial treatment response was sustained in a second acute course. Low power limits generalizability, and larger powered, prospective studies are needed.

BackgroundApproximately 25% of all patients with bipolar disorder are considered treatment-resistant. Accelerated intermittent Theta Burst Stimulation (aiTBS) is an innovative form of repetitive transcranial magnetic stimulation (rTMS), delivering bursts of stimulation at theta wave frequencies, which are believed to enhance synaptic plasticity. This pilot study aimed to explore the safety, tolerability, and preliminary efficacy of aiTBS in individuals with treatment-resistant bipolar depression (TRBD). MethodsThis open-label pilot study (Overview of Medical Research in the Netherlands (OMON): NL-OMON53634) included eight patients diagnosed with TRBD. Participants received eight daily sessions of intermittent Theta Burst Stimulation (iTBS) over five consecutive days, with 50-minute intervals between sessions. Stimulation targeted the left dorsolateral prefrontal cortex (dlPFC) using the BeamF3 targeting method. Primary outcomes were safety, tolerability, and efficacy. Safety was assessed by recording (serious) adverse events; tolerability was evaluated through side effect reports and dropout rates. Efficacy was measured as the mean reduction in depression severity, as assessed by the 17-item Hamilton Depression Rating Scale (HDRS-17). ResultsaiTBS was well tolerated and no SAEs occurred during the treatment week. Most observed adverse events were discomfort at the site of stimulation and fatigue [7/8, 87.5%]. No treatment-emergent [hypo]mania was observed during intervention week or during the follow-up. One patient experienced hypomanic symptoms [YMRS=13] at the 3 month follow-up visit. The mean HDRS decreased from 22.9 [SD=4.4] at baseline to 16.6 [SD=4.2] at day 3 of treatment [difference= -6.3 (95% CI, 1.6 - 10.9); 27.3% improvement, p=0.01*], decreased significantly to 12.3 [SD=4.1] at day 5 [difference= -10.1 (95% CI, 2.2 - 18.1); 44.3% improvement, p=0.02*], decreased significantly to 11.1 [SD=3.8] at week 2 of FU [difference= -11.8 (95% CI, 4.5 - 19.0); 51.4% improvement, p=0.004**] and decreased significantly to 13.5 [SD=3.9] at week 4 of FU [difference= -9.4 (95% CI, 1.0 - 17.7); 41.0% improvement, p=0.03*]. ConclusionThis study extends on the previous of rapid antidepressant effects, safety and tolerability of aiTBS in patients with TRBD. We suggest future RCTs to investigate maintenance aiTBS or tapering studies, to possibly prolongate the antidepressant effect. Conflict of Interest declarationThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

ObjectiveElectroconvulsive therapy (ECT) is one of the most studied and validated available treatments for severe or treatment-resistant depression. However, little is known about the neural mechanisms underlying the ECT treatment. This systematic review aims to critically review all structural magnetic resonance imaging studies investigating longitudinal cortical thickness (CT) changes after ECT in patients with unipolar or bipolar depression. MethodsWe performed a search on PubMed, Medline, and Embase to identify all available studies published before April 20, 2023. A total of 10 studies were included. ResultsThe investigations showed widespread increases in CT after ECT in depressed patients, involving mainly the temporal, insular, and frontal regions. In five studies, CT increases in a non-overlapping set of brain areas correlated with the clinical efficacy of ECT. The small sample size, heterogeneity in terms of populations, medications, comorbidities, and ECT protocols, and the lack of a control group in some investigations limit the generalizability of the results. ConclusionsOur findings support the idea that ECT can increase CT in patients with unipolar and bipolar depression. It remains unclear whether these changes are related to the clinical response. Future larger studies with longer follow-up are warranted to thoroughly address the potential role of CT as a biomarker of clinical response after ECT. SummationsO_LIThis review summarizes how ECT affects CT in patients with unipolar or bipolar depression. C_LIO_LIThe areas that were predominantly affected by ECT were temporo-insular and frontal regions. An association between the antidepressant effect of ECT and CT changes was reported by half of the included studies. C_LIO_LIIdentifying the possible cortical changes associated with the clinical efficacy of ECT opens new targets to ameliorate ECT protocols. C_LI ConsiderationsThe review is based on studies with small numbers of patients and considerable heterogeneity in terms of patients characteristics and ECT protocols. Most studies cited did not have a randomized design, thus reducing the strength of evidence supporting a causal link between ECT and CT changes.

Electroencephalography (EEG) characteristics associated with treatment response show potential for informing treatment choices for major depressive disorder, but to date, no robust markers have been identified. Variable findings might be due to the use of group analyses on a relatively heterogeneous population, which neglect individual variation. However, the correspondence between group level findings and individual brain characteristics has not been extensively investigated. Using single-subject analyses, we explored the extent to which group-based EEG connectivity and complexity characteristics associated with treatment response could be identified in individual patients. Resting-state EEG data and Montgomery-[A]sberg Depression Rating Scale symptom scores were collected from 43 patients with depression (23 females) before, at 1 and 12 weeks of treatment with escitalopram, bupropion or both. The multivariate statistical technique partial least squares was used to: 1) identify differences in EEG connectivity (weighted phase lag index) and complexity (multiscale entropy) between responders and non-responders to treatment ([&ge;]50% and <50% reduction in symptoms, respectively, by week 12), and 2) determine whether group patterns could be identified in individual patients. The group analyses distinguished groups. Responders showed decreased alpha and increased beta connectivity and early, widespread decreases in coarse scale entropy over treatment. Non-responders showed an opposite connectivity pattern, and later, spatially confined decreases in coarse scale entropy. These EEG characteristics were identified in [~]40-60% of individual patients. Substantial individual variation highlighted by the single-subject analyses might explain why robust EEG markers of antidepressant treatment response have not been identified. As up to 60% of patients in our sample was not well represented by the group results, individual variation needs to be considered when investigating clinically useful characteristics of antidepressant treatment response. Author summaryMajor depression affects over 300 million people worldwide, placing great personal and financial burden on individuals and society. Although multiple forms of treatment exist, we are not able to predict which treatment will work for which patients, so finding the right treatment can take months to years. Neuroimaging biomarker research aims to find characteristics of brain function that can predict treatment outcomes, allowing us to identify the most effective treatment for each patient faster. While promising findings have been reported, most studies look at group-average differences at intake between patients who do and do not recover with treatment. We do not yet know if such group-level characteristics can be identified in individual patients, however, and therefore if they can indeed be used to personalize treatment. In our study, we conducted individual patient analyses, and compared the individual patterns identified to group-average brain characteristics. We found that only [~]40-60% of individual patients showed the same brain characteristics as their group-average. These results indicate that commonly conducted group-average studies miss potentially important individual variation in the brain characteristics associated with antidepressant treatment outcome. This variation should be considered in future research so that individualized prediction of treatment outcomes can become a reality. Trial registrationclinicaltrials.gov; https://clinicaltrials.gov; NCT00519428

ObjectiveTo synthesise quantitative evidence on the effectiveness of Transcranial Magnetic Stimulation (TMS) as an intervention for individuals with long COVID/post-COVID syndrome. IntroductionAn estimated 65 million people worldwide meet the WHOs criteria for post-COVID-19 condition, a multisystem disorder with persistent symptoms following SARS-CoV-2 infection. Despite its global impact, effective treatments are limited. A recent review highlighted early but promising results from non-invasive brain stimulation techniques, including transcranial magnetic stimulation (TMS), though the underlying mechanisms remain unclear. Given the expanding use of TMS in long COVID, a follow-up meta-analysis is needed to reflect recent developments. This review aims to evaluate the efficacy of TMS in treating post-COVID-19 symptoms. Inclusion criteriaThis review will include studies that investigate interventions involving TMSin individuals diagnosed with long COVID or post-COVID syndrome, limited to those published in the English language. Studies will be excluded if they do not involve rTMS as a therapeutic intervention, do not involve TMS at all, focus on populations other than those with long COVID or post-COVID condition, are review articles or case studies, or are not published in English. MethodsA comprehensive search will be conducted in CINAHL Ultimate, MEDLINE, ScienceDirect, and Scopus using a strategy developed with the research team. Retrieved citations will be managed in Rayyan. Two independent reviewers will screen titles and abstracts, followed by full-text screening and data extraction by two other independent reviewers. All stages will follow predefined, pilot-tested inclusion and exclusion criteria. Discrepancies will be resolved by a third reviewer or team discussion. Intra-rater reliability at both screening stages will be assessed using Cohens Kappa. Study characteristics and findings will be presented using both narrative synthesis and tabular formats. Review registrationhttps://doi.org/10.17605/OSF.IO/RE235

The existing gold standard assessments of depression suffer various issues, which include the evaluation of constructs extraneous to the core symptoms of the illness, and low sensitivity to change over time. Members of our team developed a new, simple visual analogue scale that aims to address these issues (M3VAS). Initial validation of the scale demonstrated good internal consistency and convergent validity. Still, we have not yet investigated how well it assesses changes in the severity of depressive symptoms over time. This project will analyse data from a longitudinal study (Hampsey et al., 2022), aiming to ascertain whether the M3VAS is sensitive to change i.e., how well it detects either a worsening or improvement of symptoms over a number of weeks (repeated measures). Validating this scales longitudinal validity could provide a better way for future longitudinal (observational and interventional) studies to identify changes in the severity of depressive illness.

BackgroundVagus nerve stimulation (VNS) is an FDA-approved invasive neuromodulatory treatment for Difficult-to-treat-Depression (DTD). However, approximately 50% of patients do not respond sufficiently to VNS. A previous study found that the baseline corrected QT (QTc) interval correlates with later VNS treatment response. We aimed to replicate this finding and further explored physiological and blood-based predictors of VNS response. MethodsData of 53 patients treated with VNS were pooled between three VNS centres. All available QTc data and blood-based parameters were used. We conducted a regression analysis with baseline QTc length and Montgomery-[A]sperg Depression Rating Scale (MADRS) changes after six- and 12- months of VNS. For analysis of blood-based variables, we used exploratory correlation analysis with a stepwise forward regression approach. ResultsAfter correction for sex, age and body mass index (BMI) and medication, baseline QTc intervals did not correlate with MADRS change at either follow-up. Exploratory regression analysis identified four factors associated with MADRS reduction after six-months of VNS: lower absolute neutrophil count (ANC), BMI, younger age, and higher low-density lipoprotein (LDL) levels. Only absolute neutrophil count correlated with MADRS change after 12-months VNS. DiscussionWith a larger sample and relevant covariates, we did not replicate a previous finding that baseline QTc interval correlates with later MADRS change upon antidepressant VNS. However, in exploratory analyses, blood-based markers indicated links between MADRS change and ANC, BMI, age, and serum LDL. These findings need to be verified in prospective, controlled studies to facilitate optimal prescription of antidepressant VNS.

ObjectiveTo assess depression response and remission rates with electroconvulsive therapy (ECT) in a community clinic and to identify factors predicting success in treatment. MethodsWe identified 35 patients by a retrospective chart review with a diagnosis of major depressive disorder or depressive disorder not otherwise specified (according to the Diagnostic and Statistical Manual of Mental Disorders IV-TR) who were treated with an acute series of ECT at the Pine Rest ECT Clinic from March, 2014 to March, 2015. Clinical variables, demographics, depression response rates (based on Patient Health Questionnaire-9; PHQ-9), and anxiety response rates (based on Generalized Anxiety Disorder 7-item) were analyzed. ResultsDepression response (defined as [&ge;] 50% reduction in PHQ-9 score) and remission rates (defined as final PHQ-9 score < 5) were 54.3% and 31.4%, respectively. This was a highly treatment resistant sample, with an average of 5.3 antidepressant failures prior to initiating ECT. Logistic regression analysis found that depression response rates were predicted by an improvement in anxiety symptoms (odds ratio 1.41; 95% confidence interval, 1.11, 1.78). Additionally, patients with initial severe anxiety scores were less likely than other patients to exhibit a response in depression (p = .027). ConclusionAlmost half of this sample of patients with treatment resistant depression did not respond to ECT in this community-based clinic. Patients who experienced a response in anxiety symptoms were more likely to experience a depression response while those with severe anxiety were less likely to respond.

While repetitive transcranial magnetic stimulation (rTMS) is safe and effective for 50-60% of those treatment-resistant depression, it is critical to identify factors to optimize therapy to help those who do not respond. Baseline sleep characteristics have been investigated as a potential predictor of TMS efficacy but results from various studies have been conflicting. We aimed to explore whether baseline sleep quality, specifically insomnia related symptoms, is associated with TMS outcomes in a naturalistic sample of 975 patients receiving a standard course of rTMS from two sites. One site recorded information on concurrent medication use. Among these 353 patients, we also examined whether pharmacological treatment of insomnia affected TMS treatment response. Depression was measured using the 30-item Inventory of Depressive Symptomology Self Report (IDS-SR) in site one and an abbreviated 16-item Quick Inventory of Depressive Symptomology (QIDS) in site two. Sleep disturbances were measured using three sleep-related questions overlapping between the two questionnaires. We found that sleep quality improves after TMS and correlates with improvement in depression. Upon dichotomous categorization of the sample by insomnia and hypnotics use, we found that among those who had significant insomnia at baseline, those not using sleep medications had significantly worse post-treatment IDS-SR scores compared to those receiving pharmacological treatments for sleep (p=.021). Together, our results suggest that while baseline insomnia is not associated with response to TMS treatment, treating insomnia may affect the trajectory of TMS therapy. Future prospective studies are necessary to examine the effect of insomnia treatment alongside TMS for depression.

BackgroundRepetitive transcranial magnetic stimulation (rTMS) has shown efficacy for treating depression, but not for all patients. Accurate treatment response prediction could lower treatment burden. Research suggests machine learning trained with electroencephalographic (EEG) data may predict response, but only a limited range of measures have been tested. ObjectivesWe used >7000 time-series features to comprehensively test whether rTMS treatment response could be predicted in a discovery dataset and an independent dataset. MethodsBaseline EEG from 188 patients with depression treated with rTMS (125 responders) were decomposed into the top five principal components (PCs). The hctsa toolbox was used to extract 7304 time-series features from each participant and PC. A classification algorithm was trained to predict responders from the feature matrix separately for each PC. The classifier was applied to an independent dataset (N = 58) to test generalizability on an unseen sample. ResultsWithin the discovery dataset, the third PC (which showed a posterior-maximum and prominent alpha power) showed above-chance classification accuracy (68%, pFDR = 0.005, normalised positive predictive value = 114%). Other PCs did not outperform chance. The model generalized to the independent dataset with above-chance balanced accuracy (60%, p = 0.046, normalised positive predictive value = 114%). Analysis of feature-clusters suggested responders showed more high frequency power relative to total power, and a more negative skew in the distribution of their time-series values. ConclusionThe dynamical properties of PC3 predicted treatment response with moderate accuracy, which generalized to an independent dataset. Results suggest treatment stratification from pre-treatment EEG may be possible, potentially enabling better outcomes than one-size-fits-all treatment approaches.

ObjectiveNo studies have yet evaluated whether light therapy or negative ion therapy can be used as maintenance treatment after acute treatment with antidepressants in patients with major depressive disorder. To address the importance of this question, we surveyed participants with depression to determine their knowledge and attitudes about light therapy and negative ion therapy, and their willingness to participate in a randomized clinical trial with these therapies substituting for antidepressants for maintenance treatment. MethodsParticipants with a self-reported diagnosis of depression were recruited by email, newsletters, and social media to complete an online survey with questions about awareness and effectiveness of light therapy and negative ion therapy for depression. Vignettes describing the use of these therapies for maintenance treatment were presented with follow up questions about the ease of use and reasons for wanting (and not wanting) to use the therapies instead of antidepressants. Another vignette described a randomized study with these therapies followed by questions on whether participants would likely volunteer for the study. Chi-square tests were used to examine differences in responses between therapies. ResultsA total of 221 participants completed the survey. Most of them were aware of both therapies, but more participants had heard of light therapy (95% compared to 62% for negative ion therapy, p<0.0001), had used light therapy (28% versus 16%, p<0.003), and regarded light therapy as effective (54% versus 37%, p<0.001). Both therapies were considered easy to use. The majority of participants (78%) thought that it was important to find non-medication therapies for maintenance treatment, and 77% responded that they would likely volunteer for a randomized study to determine efficacy of the two therapies for maintenance treatment. ConclusionPeople with depression are generally aware of light therapy and negative ion therapy and believe they would be good therapies to substitute for antidepressants in maintenance treatment. These findings support the importance and feasibility for a randomized relapse prevention trial with light therapy and negative ion therapy in patients with depression.