Psychometric methods are used to remove underperforming items and reduce error in existing measures, albeit different approaches can produce different results. This study aimed to determine the implications of applying different psychometric methods for clinical trial outcomes.

Individual participant data from 15 antidepressant treatment trials from Vivli.org were analyzed. Baseline (pretreatment) and 8-week (range 4–12 weeks) outcome data from the Montgomery-Asberg Depression Rating Scale were subjected to best-practice factor analysis (FA), item response theory (IRT), and network analysis (NA) approaches. Trial outcomes for the original summative scores and psychometric-model scores were assessed using multilevel models. Percentage differences in Cohen’s d effect sizes for the original summative and psychometrically modeled scores were the effects of interest.

Each method produced unidimensional models, but the modified scales varied from 7 to 10 items. Treatment effects (d = 0.072) were unchanged for IRT (10 items), decreased by 1.3%–2.8% (eight-item abbreviated d = 0.070; weighted score d = 0.071) for NA, and increased by 11%–12.5% (seven-item abbreviated model d = 0.081; weighted score d = 0.080) for FA.

IRT and NA yielded negligible differences in effect outcomes relative to original trials. FA increased effect sizes and may be the most effective method for identifying the items on which placebo and treatment group outcomes differ.

Major depressive disorder (MDD) is a significant public health concern, and current treatments often have limitations in effectiveness and adherence. Psilocybin, a psychedelic compound found in certain mushrooms, is being explored as a potential treatment for depression. It primarily acts through the serotonin 5-HT2A receptor but interacts with 5-HT1A and 5-HT2C receptors. Its precise mechanisms remain under investigation.

(1) To consolidate evidence on psilocybin’s efficacy and safety for depression, (2) to identify limitations in the literature, and (3) to highlight areas needing further research.

This systematic review follows PRISMA guidelines and analyzes 20 studies, including randomized controlled trials (RCTs) and open-label studies. The studies cover various populations, including individuals with treatment-resistant depression, different dosing regimens, and adjunctive therapies.

Psilocybin therapy shows substantial and rapid antidepressant effects, often after one or two sessions with psychological support. Improvements are sustained for weeks or months in many cases. Psilocybin is generally well-tolerated, with mild adverse effects such as anxiety during administration and transient headaches, which are manageable in controlled settings .

Psilocybin demonstrates promise as a novel treatment for depression, especially for individuals unresponsive to conventional antidepressants. Further research is needed to refine dosing, explore long-term effects, and understand its mechanisms of action.

With numbers of very old adults (85+ years) expected to increase, and very old adults often being excluded from research and clinical trials, further knowledge about depressive disorders, antidepressant treatment and mortality among this demographic is of pressing importance.

To investigate the impact of depressive disorders and antidepressant treatment on 2-year mortality among very old adults and to explore any differences between men and women.

This cross-sectional study used data from the Umeå 85+/Gerontological Regional Database home visit interviews. The data were collected between 2000 and 2017. The total sample consisted of 2551 participants, of whom 918 had a depressive disorder. Logistic and Cox regression models were used to explore factors associated with depressive disorders and time to death. Mortality rates were illustrated and analysed using Kaplan–Meier curves and log-rank tests.

Having a depressive disorder both with and without antidepressant treatment was associated with increased risk of death within 2 years for both men and women. No survival differences were found between responders and non-responders to treatment. Depressive disorders were significant predictors of 2-year mortality in men. Antidepressant treatment was not independently associated with mortality.

Depressive disorders are significantly associated with increased 2-year mortality among very old adults, especially men, and measures to reduce mortality are urgently needed. Further exploration of the effects of antidepressant treatment among very old adults is warranted.

Increasing attention has been recently devoted to treatment-resistant depression (TRD); however, its clinical characteristics, potential risk factors, and course are still debated. Most recently, childhood trauma exposure has been correlated to TRD, but systematic investigation on the role of lifetime trauma is still lacking. The aim of this paper was to revise current evidence on early and recent trauma exposure in TRD.

A systematic search was conducted from the 1st of June to the 20th of February 2024 in accordance with the PRISMA 2020 guidelines and using the electronic databases PubMed, Web of Science, and Embase.

The primary database search produced a total of 1998 record, and finally, the search yielded a total of 22 publications, including 18 clinical studies, 3 case reports, and 1 case series, all from the period 2014 to 2024.

Limitations include a small sample size of some studies and the lack of homogeneity in the definition of TRD. Furthermore, we only considered articles in English, we excluded preprints or abstracts, and we included case reports.

This review highlights the role of early and recent trauma in TRD, even in the absence of a full-blown post-traumatic stress disorder (PTSD), highlighting the need for a thorough assessment of trauma in patients with TRD and of its role as a therapeutic target.

Attention deficit/hyperactivity disorder (ADHD) prevalence has increased in the last 10 years, most likely due to increased recognition by clinicians. Even so, an issue with under-diagnostics may persist. Historically ADHD has been described as a male-dominant disorder. However, recent evidence shows that ADHD prevalence is similar between the sexes, but that the related impairment or symptomatology might vary. This study estimated the prevalence of undiagnosed ADHD symptoms (pADHD) and explored the sex-stratified symptomatology and associations with self-perceived health-related quality of life (HRQL) and experience of depressive symptoms.

This was done in a unique cohort of 50,937 healthy blood donors – individuals who successfully maintain regular commitments despite potential ADHD symptoms. ADHD symptoms were estimated using the Adult ADHD Self-Report Scale (ASRS), health-related quality of life (HRQL) measured using mental and physical component scores (MCS/PCS) estimated based on a 12-item Short-Form Health Survey (SF-12) with a higher score indicating better HRQL, and depressive symptoms were measured using Major Depression Inventory (MDI) with higher score indicating more depressive symptoms.

In total, 3% were classified with pADHD (sex ratio 1:1). pADHD was associated with reduced MCS and PCS, and increased MDI score. Males scored on average higher on inattentive symptoms compared to females, whereas females scored on average higher on hyperactive-impulsive symptoms. Individuals scoring high on the combined inattentive and hyperactive-impulsive ADHD symptom presentation were most likely to be impaired in terms of higher MDI scores and lower PCS when compared to non-ADHD controls.

In conclusion, ADHD symptoms are common in this seemingly healthy and undiagnosed population. Symptom presentations differ between sexes and the type of presentation seems to impact the association with depressive symptoms and level of reduced HRQL.

This systematic review and meta-analysis evaluates the prevalence of disruptive mood dysregulation disorders (DMDD) in community-based and clinical populations.

PubMed and PsychINFO databases were searched, using terms specific to DMDD, for studies of prevalence and comorbidity rates conducted in youths below 18.

Fourteen studies reporting data from 2013 to 2023 were included. The prevalence of DMDD in the community-based samples was 3.3% (95% confidence interval [CI], 1.4–6.0) and 21.9% (95% CI, 15.5–29.0) in the clinical population. The differences in the identification strategy of DMDD were associated with significant heterogeneity between studies in the community-based samples, with a prevalence of 0.82% (95% CI, 0.11–2.13) when all diagnosis criteria were considered. Anxiety, depressive disorders, and ADHD were the most frequent comorbidity present with DMDD. The association with other neurodevelopmental disorders remained poorly investigated.

Caution is required when interpreting these findings, considering the quality of the reviewed data and the level of unexplained heterogeneity among studies. This review stresses the importance of considering a strict adhesion to DMDD criteria when exploring its clinical correlates.

Depressive disorders are a major public health issue in Western societies, particularly among adolescents, young adults and women. The COVID-19 pandemic has exacerbated mental health challenges, increasing depression and anxiety symptoms, especially in younger people. This study focuses on the hard-hit Emilia-Romagna Region (ERR) in Italy, examining changes in antidepressant (AD) drug use post-COVID-19 to understand the pandemic’s effect on mental health.

A population-based interrupted time series design and a segmented regression analysis was carried out on ERR pharmaceutical data (FED, direct dispensation pharmaceuticals, AFT, territorial pharmaceutical assistance) out to estimate changes in AD use during the three pandemic years (2020, 2021 and 2022) compared to 2017–2019.Analyses were stratified by age, gender, citizenship, population density of the area of residence.

A notable increase in AD consumption compared to what was expected was observed among younger age groups, and especially in females. In the 12–19 age group, a gradual increase was recorded from January 2021 until it reached +48% in 2022 (+58% among women, +30% among men). An even more remarkable growth in AD usage among non-Italian residents in the same age group was recorded compared to expected. A relevant increase, although smaller, was detected among individuals in the 20–34 age group, with a peak of +9% in 2022. These differences persisted up until the end of the observation period.

The study suggests that the COVID-19 pandemic may have had a lasting negative impact on the mental health of younger individuals. The observed increase in AD use may foreshadow a potential long-term need for enhanced mental healthcare and services directed at this subpopulation.

Despite the frequent co-occurrence of depression and diabetes, gender differences in their relationship remain unclear.

This exploratory study examined if gender modifies the association between depressive symptoms, prediabetes and diabetes with cognitive-affective and somatic depressive symptom clusters.

Cross-sectional analyses were conducted on 29 619 participants from the 2007–2018 National Health and Nutrition Examination Survey. Depressive symptoms were measured by the nine-item Patient Health Questionnaire. Multiple logistic regression was used to analyse the relationship between depressive symptoms and diabetes. Multiple linear regression was used to analyse the relationship between depressive symptom clusters and diabetes.

The odds of having depressive symptoms were greater in those with diabetes compared to those without. Similarly, total symptom cluster scores were higher in participants with diabetes. Statistically significant diabetes–gender interactions were found in the cognitive-affective symptom cluster model. Mean cognitive-affective symptom scores were higher for females with diabetes (coefficient = 0.23, CI: 0.10, 0.36, P = 0.001) than males with diabetes (coefficient = −0.05, CI: −0.16, 0.07, P = 0.434) when compared to the non-diabetic groups.

Diabetes was associated with higher cognitive-affective symptom scores in females than in males. Future studies should examine gender differences in causal pathways and how diabetic states interact with gender and influence symptom profiles.

Despite strong evidence of efficacy of electroconvulsive therapy (ECT) in the treatment of depression, no sensitive and specific predictors of ECT response have been identified. Previous meta-analyses have suggested some pre-treatment associations with response at a population level.

Using 10 years (2009–2018) of routinely collected Scottish data of people with moderate to severe depression (n = 2074) receiving ECT we tested two hypotheses: (a) that there were significant group-level associations between post-ECT clinical outcomes and pre-ECT clinical variables and (b) that it was possible to develop a method for predicting illness remission for individual patients using machine learning.

Data were analysed on a group level using descriptive statistics and association analyses as well as using individual patient prediction with machine learning methodologies, including cross-validation.

ECT is highly effective for moderate to severe depression, with a response rate of 73% and remission rate of 51%. ECT response is associated with older age, psychotic symptoms, necessity for urgent intervention, severe distress, psychomotor retardation, previous good response, lack of medication resistance, and consent status. Remission has the same associations except for necessity for urgent intervention and, in addition, history of recurrent depression and low suicide risk. It is possible to predict remission with ECT with an accuracy of 61%.

Pre-ECT clinical variables are associated with both response and remission and can help predict individual response to ECT. This predictive tool could inform shared decision-making, prevent the unnecessary use of ECT when it is unlikely to be beneficial and ensure prompt use of ECT when it is likely to be effective.

Psychotic symptoms and elevated fasting blood glucose (FBG) are frequently observed in people with major depressive disorder (MDD), but there is a lack of research into this relationship within this cohort.

This study aimed to preliminarily explore the prevalence of psychotic symptoms and their predictors among patients with MDD and elevated FBG.

This study enrolled 1718 patients with first-episode and drug-naïve (FEDN) MDD. Sociodemographic data and physical and biochemical indicators were collected. Clinical symptoms were assessed with tools such as the Hamilton Rating Scale for Anxiety, Hamilton Rating Scale for Depression (HRSD) and Positive and Negative Syndrome Scale positive subscale.

The odds ratio for psychotic symptoms in those with MDD and elevated FBG (18.7%) was 2.33 times higher than those with MDD without elevated FBG. Presence of psychotic symptoms was significantly correlated with HRSD score, suicide attempts, and total cholesterol and thyroid-stimulating hormone levels. The combination of HRSD score, suicide attempts and thyroid-stimulating hormone levels among patients with MDD and elevated FBG effectively distinguished between individuals with and without psychotic symptoms, achieving an area under the curve of 0.87.

Psychotic symptoms are frequently observed among FEDN MDD patients with elevated FBG, and depressive symptoms, suicide attempts and thyroid-stimulating hormone levels are related to psychotic symptoms in this cohort.

This study aims to explore the outcome with iv ketamine treatment in a real-world clinical setting, primarily measured as posttreatment days hospitalised.

The psychiatric medical records of 46 patients having received iv ketamine on a psychiatric treatment indication between 2015 and 2018 were retrospectively examined. Analysis comparing the number and duration of hospital admissions before and after ketamine treatment as well as logistic regression analysis to investigate clinical predictors of effectiveness, were performed. To assess patients’ severity of depressed symptoms records were screened for MADRS-S scores.

No significant difference between pre- and posttreatment hospital days (p = 0.170), or number of hospitalisations (p = 0.740) were found. The response rate was 31% and remission rate 21%. None of the predictors showed statistical significance in the logistic model.

Iv ketamine treatment showed effectiveness in reducing depressive symptoms even with complex patients in a real-world clinical setting. However, this did not translate to a reduction in hospitalisation. Highlighting the multifaceted challenges posed when implementing iv ketamine treatment in clinical practice.

Comorbid depression substantially affects the management of glycemia and diabetes-related complications among patients with type 2 diabetes mellitus. In this study, we sought to determine the association between weight change over 4 years and depression risk among patients with type 2 diabetes mellitus.

This population-based retrospective cohort study from the National Health Insurance Services of Korea included 1 111 345 patients with type 2 diabetes who were divided into groups according to body weight change over 4 years. Body weight changes were compared with the preceding 4-year period (2005–2008). Depression was defined according to the International Classification of Diseases 10th revision code for depression (F32 and F33) on one or more inpatient or outpatient claims.

During a median follow-up of 7.4 years, 244 081 cases of depression were identified. We observed a U-shaped association between body weight change and depression risk with a higher risk among both groups of weight loss (hazard ratio (HR) 1.17, 95% CI 1.15–1.19 for ⩾ −10%; HR 1.07, 95% CI 1.06–1.08 for −10 to −5%) and weight gain (HR 1.06, 95% CI 1.04–1.08 for ⩾10%; HR 1.02, 95% CI 1.01–1.04 for 5–10%) compared with the stable weight group (−5 to 5%).

A U-shaped association between body weight change and depression risk was observed in this large nationwide cohort study. Our study suggests that patients with type 2 diabetes and weight change, either gain or loss, could be considered a high-risk group for depression.

Despite mounting evidence demonstrates circulating endothelial progenitor cells (cEPCs) quantitative changes in depression, no study has investigated cEPC functions in major depressive disorder (MDD). We investigated the role of cEPC adhesive and apoptotic functions in MDD.

We recruited 68 patients with MDD and 56 healthy controls (HCs). The depression symptoms, anxiety, psychosomatic symptoms, subjective cognitive dysfunction, quality of life, and functional disability were evaluated using the Hamilton Depression Rating Scale and Montgomery–Åsberg Depression Rating Scale, Hamilton Anxiety Rating Scale, Depression and Somatic Symptoms Scale (DSSS), Perceived Deficits Questionnaire-Depression, 12-Item Short Form Health Survey (SF-12), and Sheehan Disability Scale (SDS), respectively. Working memory and executive function were assessed using a 2-back task and Wisconsin Card Sorting Test (WCST). Inflammatory marker (soluble interleukin-6 receptor, C-reactive protein, and tumor necrosis factor-α receptor-1), cEPC adhesive, and apoptotic levels were measured using in vitro assays.

The MDD patients showed significantly lower cEPC adhesive levels than the HCs, and this difference in adhesive function remained statistically significant even after adjusting for inflammatory marker levels. The cEPC adhesion levels were in inverse correlations with commission and omission errors in 2-back task, the percent perseverative response and percent perseverative errors in WCST, and the DSSS and SDS scores, but in positive correlations with SF-12 physical and mental component scores. cEPC apoptotic levels did not differ significantly between the groups.

The findings indicate that cEPC adhesive function is diminished in MDD and impacts various aspects of cognitive and psychosocial functions associated with the disorder.

Individuals with serious mental illness have a markedly shorter life expectancy. A major contributor to premature death is cardiovascular disease (CVD). We investigated associations of (genetic liability for) depressive disorder, bipolar disorder and schizophrenia with a range of CVD traits and examined to what degree these were driven by important confounders.

We included participants of the Dutch Lifelines cohort (N = 147 337) with information on self-reported lifetime diagnosis of depressive disorder, bipolar disorder, or schizophrenia and CVD traits. Employing linear mixed-effects models, we examined associations between mental illness diagnoses and CVD, correcting for psychotropic medication, demographic and lifestyle factors. In a subsample (N = 73 965), we repeated these analyses using polygenic scores (PGSs) for the three mental illnesses.

There was strong evidence that depressive disorder diagnosis is associated with increased arrhythmia and atherosclerosis risk and lower heart rate variability, even after confounder adjustment. Positive associations were also found for the depression PGSs with arrhythmia and atherosclerosis. Bipolar disorder was associated with a higher risk of nearly all CVD traits, though most diminished after adjustment. The bipolar disorder PGSs did not show any associations. While the schizophrenia PGSs was associated with increased arrhythmia risk and lower heart rate variability, schizophrenia diagnosis was not. All mental illness diagnoses were associated with lower blood pressure and a lower risk of hypertension.

Our study shows widespread associations of (genetic liability to) mental illness (primarily depressive disorder) with CVD, even after confounder adjustment. Future research should focus on clarifying potential causal pathways between mental illness and CVD.

Preventing the occurrence of depression/anxiety and suicide during adolescence can lead to substantive health gains over the course of an individual person’s life. This study set out to identify the expected population-level costs and health impacts of implementing universal and indicated school-based socio-emotional learning (SEL) programs in different country contexts.

A Markov model was developed to examine the effectiveness of delivering universal and indicated school-based SEL programs to prevent the onset of depression/anxiety and suicide deaths among adolescents. Intervention health impacts were measured in healthy life years gained (HLYGs) over a 100-year time horizon. Country-specific intervention costs were calculated and denominated in 2017 international dollars (2017 I$) under a health systems perspective. Cost-effectiveness findings were subsequently expressed in terms of I$ per HLYG. Analyses were conducted on a group of 20 countries from different regions and income levels, with final results aggregated and presented by country income group – that is, low and lower middle income countries (LLMICs) and upper middle and high-income countries (UMHICs). Uncertainty and sensitivity analyses were conducted to test model assumptions.

Implementation costs ranged from an annual per capita investment of I$0.10 in LLMICs to I$0.16 in UMHICs for the universal SEL program and I$0.06 in LLMICs to I$0.09 in UMHICs for the indicated SEL program. The universal SEL program generated 100 HLYGs per 1 million population compared to 5 for the indicated SEL program in LLMICs. The cost per HLYG was I$958 in LLMICS and I$2,006 in UMHICs for the universal SEL program and I$11,123 in LLMICs and I$18,473 in UMHICs for the indicated SEL program. Cost-effectiveness findings were highly sensitive to variations around input parameter values involving the intervention effect sizes and the disability weight used to estimate HLYGs.

The results of this analysis suggest that universal and indicated SEL programs require a low level of investment (in the range of I$0.05 to I$0.20 per head of population) but that universal SEL programs produce significantly greater health benefits at a population level and therefore better value for money (e.g., less than I$1,000 per HLYG in LLMICs). Despite producing fewer population-level health benefits, the implementation of indicated SEL programs may be justified as a means of reducing population inequalities that affect high-risk populations who would benefit from a more tailored intervention approach.

The elevated prevalence of metabolic syndrome (MetS) in patients with depression has been associated with increased mortality. This post hoc analysis assessed the effect of treatment with lurasidone on risk of MetS in patients with bipolar depression.

Data used in the current analyses consisted of 3 double-blind (DB), placebo-controlled, 6-week studies in adults with bipolar I depression (N = 1192), consisting of 1 monotherapy, and 2 adjunctive trials (lithium or valproate). Also analyzed was a 6-month open-label (OL) extension study (monotherapy, N = 316; adjunctive therapy, N = 497); and a 5-month, OL, stabilization phase followed by randomization to a 28-week DB, placebo-controlled, adjunctive therapy study with lurasidone (N = 490). MetS was defined based on NCEP ATP III criteria (2005 revision).

The proportion of patients with new-onset MetS was similar for lurasidone vs placebo in the short-term studies (monotherapy, 13.9% vs 15.3%; adjunctive therapy, 13.6% vs 11.0%); and remained stable during both the 6-month extension phase study (monotherapy, 15.2%; adjunctive therapy, 16.9%), and the 5-month stabilization study (adjunctive therapy, 12.2%). After 28 weeks of DB treatment (following 5-month treatment in the stabilization study), new onset MetS was observed at endpoint (OC) in 26.2% of the lurasidone group, and 30.8% of the placebo group.

This post hoc analysis found that both short and long-term treatment with lurasidone was associated with a relatively low risk for the development of MetS in patients with bipolar I disorder. These findings are consistent with similar analyses in patients with schizophrenia.