Diagnosis Of Major Depressive Disorder Research Articles

Associations between social determinants of health and mental health disorders among U.S. population: a cross-sectional study.

The impact of social determinants of health (SDOH) on mental health is increasingly realized. A comprehensive study examining the associations of SDOH with mental health disorders has yet to be accomplished. This study evaluated the associations between five domains of SDOH and the SDOH summary score and mental health disorders in the United States. We analyzed data from a diverse group of participants enrolled in the All of Us research programme, a research programme to gather data from one million people living in the United States, in a cross-sectional design. The primary exposure was SDOH based on Healthy People 2030: education access and quality, economic stability, healthcare access and quality, social and community context, and neighbourhood and built environment. A summary SDOH score was calculated by adding each adverse SDOH risk (any SDOH vs. no SDOH). Our primary outcomes were diagnoses of major depression (MD) (i.e., major depressive disorder, recurrent MD or MD in remission) and anxiety disorders (AD) (i.e., generalized AD and other anxiety-related disorders). Multiple logistic regression models were used to determine adjusted odd ratios (aORs) for MD and/or ADs after controlling for covariates. A total of 63,162 participants with MD were identified (22,277 [35.3%] age 50-64years old; 41,876 [66.3%] female). A total of 77,624 participants with AD were identified (25,268 [32.6%] age 50-64years old; 52,224 [67.3%] female). Factors associated with greater odds of MD and AD included having less than a college degree, annual household income less than 200% of federal poverty level, housing concerns, lack of transportation, food insecurity, and unsafe neighbourhoods. Having no health insurance was associated with lower odds of both MD and AD (aOR, 0.48; 95% confidence interval [CI], 0.46-0.51 and aOR, 0.44; 95% CI, 0.42-0.47, respectively). SDOH summary score was strongly associated with the likelihood of having MD and AD (aOR, 1.97; 95% CI, 1.89-2.06 and aOR, 1.69; 95% CI, 1.63-1.75, respectively). This study found associations between all five domains of SDOH and the higher odds of having MD and/or AD. The strong correlations between the SDOH summary score and mental health disorders indicate a possible use of the summary score as a measure of risk of developing mental health disorders.

Emerging biomarkers in major depressive disorder: Diagnostic, prognostic, and therapeutic implications

Recent advancements in biomarker research for the diagnosis, prognosis, and treatment strategies of major depressive disorder (MDD) have yielded significant findings that warrant documentation. The clinical demand for biomarkers persists due to the limited accuracy and efficiency of subjective diagnostic approaches. This review scrutinized research papers related to MDD biomarkers published between January 2011 and till July 2024, focusing exclusively on human studies with statistically significant results. The compiled biomarkers encompass cellular membrane receptors, cytoplasmic organelles, and genomic and epigenomic intranuclear markers. Cell surface molecular receptors implicated in MDD pathogenesis include brain-derived neurotrophic factor (BDNF) receptors, N-methyl D-aspartate receptors (NMDAR), and interleukin (IL) receptors. Endogenous compounds with diagnostic and prognostic potential, such as L-carnitine and alpha-L-carnitine, have also been identified. Transcriptomic biomarkers, including mRNA expression levels of the BDNF, IL-1β, macrophage migration inhibitory factor, and tumor necrosis factor-alpha (TNF-α), have demonstrated utility in MDD management. MicroRNAs (miRNAs), the endogenous molecules that alter the structure of mRNA, show potential for diagnosis and treatment outcome prediction, with miR-221-3p, miR-129-5p, miR-134, and miR-184 emerging as key candidates for MDD monitoring. Long non-coding RNAs (lncRNAs), such as GSK3βAS1, GSK3βAS2, and GSK3βAS3 have been investigated for the evaluation of disease severity and treatment response. Most recently, the pathological role of circular (circRNA) and DNA methylation in MDD has also been documented. The rs155979 polymorphism in the lncRNA NOTHSAT102891 was significantly associated with depression and risk of suicide. The data compiled in this review aim to guide further research in the quest for biomarkers that will improve the management of MDD.

Patient-reported outcome measures to assess mental and physical health status, functionality, and quality of life in patients with major depression or schizophrenia

BackgroundPatient-reported outcomes measures (PROMs) are standardized self-administered tools that assess the patient’s opinion on the level of health, quality of life, and disability among other aspects. The objective of this study was to gather information on physical and mental health in patients with major mental illness using PROMs.MethodsThis was an observational, naturalistic, prospective study carried out in adult stabilized outpatients attended at nine Adult Mental Health Centers in Barcelona, Spain. All participants had a confirmed diagnosis of major depression disorder or schizophrenia (DSM-5) and were currently on drug treatment. Participants (n = 508) self-completed a baseline questionnaire for clinical data and PROMs scales (PHQ-19, SF-12, and WHODAS 2.0) at baseline and 9 months thereafter (n = 482).ResultsMean (SD) age was 50.9 (13.2) years, and 83% of patients lived with their families. Although 93.9% of patients recognized having a mental illness, 15.7% did not know their diagnosis. When asked if they considered that during the last year their treatment had offered some type of improvement, 83.9% answered affirmatively. Patients reported that their degree of adherence to treatment was high (77%) and most of them (80%) believed the medication had a beneficial effect. Depressed patients showed both at baseline and at follow up significantly more depressive symptoms than the group with schizophrenia. In the schizophrenia group, a statistically significant improvement in depressive symptoms was noted at 9 months follow-up. We did not find significant differences within or between groups in quality of life (SF-12 scores) obtained at baseline and after 9 months of follow-up Both at baseline and at follow-up, patients with depression reported a significantly higher degree of disability (WHODAS scores) than those with schizophrenia.ConclusionsPROMs can be used in real-world conditions to assess severity of disease, quality of life, and disability in major depression and schizophrenia. The present results are relevant for both patients and clinicians.

Major Depresyonda Bilişsel Davranışçı Terapi: Bir Olgu Sunumu

This article presents a case study on the treatment of major depression with cognitive behavioral therapy (CBT). The article examines the case of a 30-year-old male client who received a diagnosis of major depression and subsequently underwent a 12-session course of cognitive behavioral therapy. The article discusses the client's history, core beliefs, negative automatic thoughts, symptoms, and progress during therapy. In conclusion, cognitive behavioral therapy is noted as an effective option for the treatment of major depression, and this article is highlighted as an important example supporting the use of this therapy method. Keywords: Major Depression, Cognitive-Behavioral Therapy

The Trifecta of Industry, Academic, and Health System Partnership to Improve Mental Health Care Through Smartphone-Based Remote Patient Monitoring: Development and Usability Study.

Mental health treatment is hindered by the limited number of mental health care providers and the infrequency of care. Digital mental health technology can help supplement treatment by remotely monitoring patient symptoms and predicting mental health crises in between clinical visits. However, the feasibility of digital mental health technologies has not yet been sufficiently explored. Rhythms, from the company Health Rhythms, is a smartphone platform that uses passively acquired smartphone data with artificial intelligence and predictive analytics to alert patients and providers to an emerging mental health crisis. The objective of this study was to test the feasibility and acceptability of Rhythms among patients attending an academic psychiatric outpatient clinic. Our group embedded Rhythms into the electronic health record of a large health system. Patients with a diagnosis of major depressive disorder, bipolar disorder, or other mood disorder were contacted online and enrolled for a 6-week trial of Rhythms. Participants provided data by completing electronic surveys as well as by active and passive use of Rhythms. Emergent and urgent alerts were monitored and managed according to passively collected data and patient self-ratings. A purposively sampled group of participants also participated in qualitative interviews about their experience with Rhythms at the end of the study. Of the 104 participants, 89 (85.6%) completed 6 weeks of monitoring. The majority of the participants were women (72/104, 69.2%), White (84/104, 80.8%), and non-Hispanic (100/104, 96.2%) and had a diagnosis of major depressive disorder (71/104, 68.3%). Two emergent alerts and 19 urgent alerts were received and managed according to protocol over 16 weeks. More than two-thirds (63/87, 72%) of those participating continued to use Rhythms after study completion. Comments from participants indicated appreciation for greater self-awareness and provider connection, while providers reported that Rhythms provided a more nuanced understanding of patient experience between clinical visits. Rhythms is a user-friendly, electronic health record-adaptable, smartphone-based tool that provides patients and providers with a greater understanding of patient mental health status. Integration of Rhythms into health systems has the potential to facilitate mental health care and improve the experience of both patients and providers.

Mediators of a randomized controlled trial of a preventive intervention for youth of parents with depressive disorders.

The present study assessed two theory-driven mediators of the effects of a family group cognitive-behavioral (FGCB) preventive intervention for youth of parents with a history of major depressive disorder (MDD) or dysthymia on long-term youth psychopathology symptoms and diagnoses. Sample included 180 parents (Mage = 41.9, 89% female, 82% White, non-Hispanic) and one of their children/adolescents ages 9-15 years (Mage = 11.4, 49% female, 74% White, non-Hispanic). Changes in the hypothesized mediators, observations of positive parenting (Iowa Family Interaction Rating Scales) and youth secondary control coping (SCC) skills (Responses to Stress Questionnaire), were assessed at 6 months. Changes in youth psychopathology symptoms were assessed on the Child Behavior Checklist and Youth Self-Report at 18- and 24-month follow-ups and MDD diagnoses with the Kiddie Schedule for Affective Disorders and Schizophrenia at 12 and 24 months. Changes in youth SCC skills (e.g., acceptance, reappraisal) after the intervention mediated the effects of the FGCB program on changes in youth internalizing and externalizing symptoms at 18- and 24-month follow-ups. Effects for changes in positive parenting behaviors as a mediator were more limited. SCC skills were further shown to mediate the effects of the FGCB intervention on MDD diagnoses from 12 to 24 months. This study provides clear and strong evidence that changes in youth SCC skills mediated the long-term effects of preventive intervention for families of depressed parents. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Residual symptoms following trauma-focused treatment for comorbid posttraumatic stress disorder and major depressive disorder.

Despite effective psychotherapy options for posttraumatic stress disorder (PTSD), some patients do not fully respond, and even among those reporting substantial improvement, residual symptoms following treatment are common. Psychiatric conditions frequently co-occur with PTSD, yet research on residual symptoms among comorbid samples is lacking. This study examined residual symptoms of PTSD and depression among 71 active duty service members with PTSD and comorbid major depressive disorder (MDD). As part of a clinical trial, participants were randomized to cognitive processing therapy (CPT) or a novel treatment designed to address PTSD and comorbid MDD, behavioral activation-enhanced CPT (BA+CPT). Analyses compared individual residual symptoms between treatments and groups based on PTSD and MDD diagnostic status at posttreatment. For both PTSD and MDD, the conditional probabilities for each residual symptom did not differ between CPT and BA+CPT, suggesting treatment type did not influence which symptoms persisted. For the 36 service members who lost their PTSD diagnosis at posttreatment, conditional probabilities of residual PTSD symptoms were highest for sleep problems, concentration difficulties, and hypervigilance; for MDD symptoms, conditional probabilities were highest for sleep problems, concentration difficulties, and low energy. These most common residual symptoms were identical for the 31 service members who lost their MDD diagnosis at posttreatment. Residual symptoms observed among service members with PTSD and comorbid MDD mirrored those commonly identified among single disorder PTSD or MDD samples. Identifying and addressing residual symptoms most meaningful to patients will maximize benefit from PTSD treatment.

Marriage and postpartum major depressive disorder: A systematic review and meta-analysis of cohort studies.

Many studies have explored the relationships between demographic variables and postpartum major depressive disorder. However, there is no clear conclusion on the impact of different marital statuses and quality on postpartum major depressive disorder. This systematic review and meta-analysis examined the combined effects of different marital status and quality on postpartum major depressive disorder with cohort studies. Two authors independently searched 6 English databases (PubMed, Medline, Web of Science, PsycARTICLES, EBSCOhost and Scopus) and 3 Chinese databases (China Knowledge Resource Integrated Database (CNKI), Weipu database and Wanfang database) from the beginning of database construction to October 25, 2024. Studies that met the inclusion criteria included maternal diagnosis of postpartum major depressive disorder by clinical diagnostic criteria, inclusion of marital status, and reporting risk estimate. There were no language limitations in this study. The quality of the included studies was assessed using the Newcastle-Ottawa scale (NOS). Publication bias was assessed using a funnel plot and Egger's test. Finally, nineteen cohort studies were included in this meta-analysis. Low marital satisfaction was the most significant predictor of postpartum major depressive disorder (pooled RR=3.47, 95% CI: 1.96, 6.12) followed by being single/divorced/separated/widowed/unmarried (pooled RR=1.19, 95% CI: 1.02, 1.39). However, there was not a significant relationship between "worsening relationship/dissatisfaction with partner/problems in marital relationship" and postpartum major depressive disorder (pooled RR=2.30, 95% CI:0.69, 7.62) yet. Marital status and marriage quality impacted heavily on maternal postpartum major depressive disorder. There is an urgent need to focus on family therapy and marital intervention for pregnant women and to enhance the sense of involvement of the husband or partner.

Individualized Spectral Features in First-episode and Drug-naïve Major Depressive Disorder: Insights from Periodic and Aperiodic EEG Analysis.

The detection of abnormal brain activity plays an important role in the early diagnosis and treatment of major depressive disorder (MDD). Recent studies have shown that the decomposition of the electroencephalography (EEG) spectrum into periodic and aperiodic components is useful for identifying the drivers of electrophysiologic abnormalities and avoiding individual differences. This study aimed to elucidate the pathologic changes in individualized periodic and aperiodic activities and their relationships with the symptoms of MDD. EEG data in the eyes-closed resting state were continuously recorded from 97 first-episode and drug-naïve patients with MDD and 90 healthy control (HC) participants. Both periodic oscillations and aperiodic components were obtained via the "fitting oscillations and one-over f" (FOOOF) algorithm and then used to compute individualized spectral features. MDD patients presented higher canonical alpha and beta band power but lower aperiodic-adjusted alpha and beta power. Furthermore, we found that alpha power was strongly correlated with the age of patients but not with disease symptoms. The aperiodic intercept was lower in the parietal‒occipital region and was positively correlated with the Hamilton Depression Rating Scale (HAMD) score after accounting for age and sex. In the asymmetry analysis, alpha activity appeared asymmetrical only in the HC group, whereas aperiodic activity was symmetrical in both groups. The findings of this study provide insights into the role of abnormal neural spiking activity and impaired neuroplasticity in MDD progression and suggest that the aperiodic intercept in resting-state EEG may be a potential biomarker of MDD.

Abnormal regional brain activity in patients with first-episode medication-naïve depressive disorder: a longitudinal fNIRS study

The potential relationship between abnormal brain activity and clinical symptoms in patients with major depressive disorder (MDD) is important for auxiliary diagnosis and prediction of the curative effect of treatments for MDD. Before antidepressant treatment (T1), 4 weeks after treatment (T2), and 8 weeks after treatment (T3), 33 patients with first-episode medication-naïve MDD and 30 healthy controls (HCs) were examined using functional near-infrared spectroscopy (fNIRS) to evaluate the cerebral hemodynamic response in the frontal and temporal cortex during the Verbal Fluency Task (VFT). Compared with HCs, VFT scores and activation levels of the frontal pole, inferior frontal gyrus, and dorsolateral prefrontal cortex were significantly decreased in the first-episode medication-naïve depressive disorder patients (FMD). Compared with T2, the activation levels of the superior temporal gyrus and inferior central gyrus were increased at T3 in the FMD. The low activation pattern of the frontal pole, inferior frontal gyrus, and dorsolateral prefrontal cortex in the FMD during VFT is helpful for clinical diagnosis of MDD. The superior temporal gyrus and inferior central gyrus may be sensitive brain regions that reflect the clinical effect of MDD in patients.

Occupational Injury and Suicide in Washington State, Adjusting for Pre-Injury Depression.

Occupational injuries have been associated with increased suicide mortality, but prior studies have not accounted for pre-injury depression. We linked injuries that occurred from 1994 to 2000 in the Washington State workers' compensation system with Social Security Administration data on earnings and mortality through 2018. We estimated the subdistribution hazard ratio (sHR) and 95% confidence interval using competing risks regression of suicide deaths with lost time compared with medical-only injuries separately for men and women, adjusting for age, pre-injury annual earnings, and industry. We further adjusted for pre-injury diagnosis of major depressive disorder by using a quantitative bias analysis (QBA), with the prevalence of this disorder in workers derived from an external health insurance claims data set. Elevated suicide mortality was observed following lost-time injuries compared with medical-only injuries for men (sHR = 1.49, 95% CI [1.14, 1.93]) and women (sHR = 1.30, 95% CI [1.00, 1.69]), adjusting for age, pre-injury earnings, and industry. Adjusted for pre-injury depression using a QBA, elevated suicide risk in men remained statistically significant (median sHR = 1.33, simulation interval [1.18, 1.47]) but not for women. Workplace injury requiring time off work appeared to remain influential in increasing suicide risk among men, even after controlling for pre-injury depression. The relationship between mental health before and after occupational injury is complex and studies should better integrate mental health pre-injury. Though many questions remain on the complex relationship between work, depression, injuries, and suicide, employers should work to prevent injuries and consider implementing mental health programs, which could be helpful in reducing suicide risk.

Depression and emotion regulation strategy use moderate age-related attentional positivity bias.

Effective emotion regulation is critical for maintaining emotional health in the face of adverse events that accumulate over the lifespan. These abilities are thought to be generally maintained in older adults, accompanied by the emergence of attentional biases to positive information. Such age-related positivity biases, however, are not always reported and may be moderated by individual differences in affective vulnerabilities and competencies, such as those related to dispositional negative affect and emotion regulation styles. To examine these relationships, we analyzed eye-tracking data from 72 participants (35-74 years; 50 female), 44 without and 28 with a diagnosis of Major Depressive Disorder during a free-viewing task comprising neutral-neutral, negative-neutral, and positive-neutral image pairs. Emotional bias scores were calculated based on the ratio of time spent dwelling on the emotional image vs. the neutral image in each emotional-neutral pair. Results indicate that healthy participants exhibited a stronger positivity bias than a negativity bias, whereas individuals with higher depressive symptom scores showed no difference. Next, we examined how age and emotion regulation strategy use (reappraisal vs. suppression, measured with the Emotion Regulation Questionnaire) impacted these effects. Individuals with Major Depressive Disorder did not exhibit a significant relationship between age and positivity bias. However, for healthy participants who self-reported a preference for using reappraisal in daily life, increased age was associated with an increased positivity bias. These findings indicate that the emergence of the positivity effect in older adults is related to reappraisal regulatory preferences in the absence of depressive symptoms.

Predicting Diagnostic Conversion From Major Depressive Disorder to Bipolar Disorder: An EHR Based Study From Colombia.

Most bipolar disorder (BD) patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study aims to identify features predictive of the conversion from Major Depressive Disorder (MDD) to BD by leveraging electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia. We employed a multivariable Cox regression model to identify important predictors of conversion from MDD to BD. Analyzing 15 years of EHR data from 13,607 patients diagnosed with MDD, a total of 1610 (11.8%) transitioned to BD. Predictive features of the conversion to BD included severity of the initial MDD episode, presence of psychosis and hospitalization at first episode, family history of BD, and female gender. Additionally, we observed associations with medication classes (positive associations with prescriptions of mood stabilizers, antipsychotics, and negative associations with antidepressants) and a positive association with suicidality, a feature derived from natural language processing (NLP) of clinical notes. Together, these risk factors predicted BD conversion within 5 years of the initial MDD diagnosis, with a recall of 72% and a precision of 38%. Our study confirms previously identified risk factors identified through registry-based studies (female gender and psychotic depression at the index MDD episode) and identifies novel ones (suicidality extracted from clinical notes). These results simultaneously demonstrate the validity of using EHR data for predicting BD conversion and underscore its potential for the identification of novel risk factors, thereby improving early diagnosis.

Exhaustion Disorder in Primary Care: A Comparison With Major Depressive Disorder and Adjustment Disorder.

Exhaustion disorder (ED) was introduced to the Swedish version of the International Classification of Diseases, 10th edition (ICD-10) 2005. Primarily characterized by general fatigue and cognitive deficits, ED has become one of the most common mental health diagnoses in Sweden. Little is still known regarding the discriminative validity of the ED diagnosis and how it relates to other diagnostic constructs. The study aimed to investigate the discriminative validity of ED compared with two similar diagnoses, major depressive disorder (MDD) and adjustment disorder (AD). Using data from a sample of patients with a principal diagnosis of either ED (n = 352), MDD (n = 99), or AD (n = 302), we compared demographic and clinical variables and scores on self-report symptom scales. Results showed that ED patients were of a higher age and had a higher frequency of sickness absence than MDD and AD patients. There was a substantial overlap of symptoms between ED and MDD, only differing on two of nine self-report symptom scales, with ED patients rating lower work ability d = -0.37 and alcohol consumption d = -0.57. Compared with AD patients, ED patients reported more severe symptoms in every symptom domain. Given the prevalent use of ED diagnosis, its diagnostic validity and clinical usefulness merit further attention.

Examining the Use of Virtual Reality to Support Mindfulness Skills Practice in Mood and Anxiety Disorders: Mixed Methods Study.

Virtual reality (VR) has been proposed as a technology to support mindfulness practice through promoting increased engagement and presence. The proposed benefits of this technology have been largely unexamined with clinical populations. Further research is required to understand its clinical potential and utility in improving and managing mental health symptoms. This study aims to investigate the proximal impacts of a single, brief, VR-supported mindfulness practice for individuals with a mood or anxiety disorder and to understand user experiences, which may affect the acceptability and efficacy of VR mindfulness for this population. This mixed methods study recruited 28 participants with a primary diagnosis of major depressive disorder, bipolar disorder, or anxiety disorder. Participants completed a mindfulness practice wearing a VR headset that was presenting an omnidirectional video of a forest scene, which was overlaid with a guided audio voiceover. Before and after the practice, measures were completed assessing state mindfulness (Toronto Mindfulness Scale), affect (Positive and Negative Affect Schedule), and anxiety (State-Trait Anxiety Inventory Y-1; n=27). Semistructured interviews were then held inquiring about the user experience and were analyzed using thematic analysis (n=24). After completing the VR-supported mindfulness practice, both measures of state mindfulness on the Toronto Mindfulness Scale, mean curiosity and decentering, increased significantly (Cohen d=1.3 and 1.51, respectively; P<.001). Negative affect on the Positive and Negative Affect Schedule (Cohen d=0.62; P=.003) and State-Trait Anxiety Inventory Y-1 state anxiety (Cohen d=0.84; P<.001) significantly reduced. There was no significant change in positive affect (Cohen d=0.29; P=.08). Qualitative analysis of interviews identified 14 themes across 5 primary theme categories. The results suggested that being mindful during the use of the app was experienced as relatively effortless because of the visual and immersive elements. It was also experienced as convenient and safe, including when compared with prior traditional experiences of mindfulness. Participants also identified the uses for VR-supported mindfulness in managing emotions and symptoms of mental illness. The results provide preliminary evidence that VR-supported mindfulness can improve emotional states and manage mental health symptoms for those with mood or anxiety disorders. It offers some potential clinical applications for those with mood or anxiety disorders for exploration within future research.

A study of impulsivity and adverse childhood experiences in a population health setting.

As complex mental health traits and life histories are often poorly captured in hospital systems, the utility of using the Barratt Impulsivity Scale (BIS) and Adverse Childhood Experiences (ACEs) for assessing adult disease risks is unknown. Here, we use participants from the Healthy Nevada Project (HNP) to determine if two standard self-assessments could predict the incidence and onset of disease. We conducted a retrospective cohort study involving adult participants who completed the Behavioral and Mental Health Self-Assessment (HDSA) between September 2018 and March 2024. Impulsivity levels were measured using the BIS-15, and retrospective self-reports of ACEs were collected through a standardized questionnaire. In total, 17,482 HNP participants completed the HDSA. Our findings indicate that ACEs were significantly associated with impulsivity. Disease associations with impulsivity and ACEs were evaluated using a phenome-wide association study, identifying 230 significant associations with impulsivity. Among these, 44 were related to mental health diagnoses, including major depressive disorder (MDD). Kaplan-Meier survival estimates characterized the differences in the lifetime predicted probability between high and low impulsivity for major depressive disorder and essential hypertension. This analysis showed that having both high ACEs and high impulsivity confer substantial risk of MDD diagnosis (hazard ratios 2.81, 2.17, respectively). Additionally, lifetime predicted probability of MDD was approximately 40% higher for high ACEs and high impulsivity compared to no ACEs and low impulsivity. Essential hypertension demonstrated similar trends, with an approximate 20% increase in predicted lifetime probability of diagnosis. These results demonstrate that high ACES and elevated impulsivity scores are associated with a range of negative health outcomes and a simple self-assessment of complex traits and life history may significantly impact clinical risk assessments.

Practice of Electroconvulsive Therapy in Catalonia in 2022: Results From a Large Cross-Sectional Survey.

The practice of electroconvulsive therapy (ECT) exhibits variability across various domains, both between regions, and between centers within the same region. The ECT Working Group of the Catalan Society of Psychiatry conducted a comprehensive survey in Catalonia, Spain, to assess the current status of those variables essential in the clinical practice of ECT. The survey comprised 50 items, including various question types such as multiple-choice, numerical response, and open-ended questions. It was administered to the 20 public hospitals that currently provide ECT in Catalonia during the year 2022. Information was gathered on 4 main areas: Organization of the ECT Unit, Specific Technique of ECT Application, Strategies and Organization of the Therapeutic Plan, and Epidemiological Data, Training, and Healthcare Resource Management. Some notable findings include an application rate of 1.1 per 10,000 inhabitants, major depression diagnosis as the primary indication for ECT in 80% of the centers, and the ability to perform maintenance ECT in 100% of centers. Following the survey and analysis, 3 main findings emerged: minimal variation in ECT application rates compared to the previous decade, increased complexity in current ECT practices with a focus on quality and patient safety, and identified areas for improvement in resource management and the necessity for a well-trained and stable multidisciplinary team.

Lived experiences of mothers: A longitudinal study of impacts and adjustment following adolescent psychiatric hospitalization for suicide attempts or other reasons.

Parents play crucial roles in monitoring and supporting youth who have been hospitalized after suicide attempts, but their adjustment in the period following hospitalization has been understudied. This study assessed the adjustment and impacts on mothers during the year following hospitalization. Participants included 135 mothers of suicidal adolescents and 117 mothers of adolescents hospitalized for other reasons. The Structured Clinical Interview for DSM (SCID) and the Child and Adolescent Impact Assessment were used to assess psychiatric diagnoses of Major Depressive Disorder [MDD], Generalized Anxiety Disorder [GAD], and Post-Traumatic Stress Disorder [PTSD], and impacts on caregivers at one, three, six, and 12 months after hospitalization. Higher rates of MDD, GAD, and PTSD, and greater impacts were evidenced closer in time to the hospitalization. There were few overall differences between mothers of youth with and without suicidal behavior. However, family history of suicidal behavior was related to higher rates of MDD and PTSD, and greater severity of youth suicidal thoughts and behavior over the follow-up was related to greater impact upon mothers of suicidal youth. This study highlights the mental health struggles of mothers of suicidal and other hospitalized youth and underscores the importance of support for caregivers.

Major depression symptom severity associations with willingness to exert effort and patch foraging strategy.

Individuals with major depressive disorder (MDD) can experience reduced motivation and cognitive function, leading to challenges with goal-directed behavior. When selecting goals, people maximize 'expected value' by selecting actions that maximize potential reward while minimizing associated costs, including effort 'costs' and the opportunity cost of time. In MDD, differential weighing of costs and benefits are theorized mechanisms underlying changes in goal-directed cognition and may contribute to symptom heterogeneity. We used the Effort Foraging Task to quantify cognitive and physical effort costs, and patch leaving thresholds in low effort conditions (reflecting perceived opportunity cost of time) and investigated their shared versus distinct relationships to clinical features in participants with MDD (N = 52, 43 in-episode) and comparisons (N = 27). Contrary to our predictions, none of the decision-making measures differed with MDD diagnosis. However, each of the measures was related to symptom severity, over and above effects of ability (i.e. performance). Greater anxiety symptoms were selectively associated with lower cognitive effort cost (i.e. greater willingness to exert effort). Anhedonia and behavioral apathy were associated with increased physical effort costs. Finally, greater overall depression was related to decreased patch leaving thresholds. Markers of effort-based decision-making may inform understanding of MDD heterogeneity. Increased willingness to exert cognitive effort may contribute to anxiety symptoms such as worry. Decreased leaving threshold associations with symptom severity are consistent with reward rate-based accounts of reduced vigor in MDD. Future research should address subtypes of depression with or without anxiety, which may relate differentially to cognitive effort decisions.

Diagnosis of major depressive disorder using a novel interpretable GCN model based on resting state fMRI.

The diagnosis and analysis of major depressive disorder (MDD) faces some intractable challenges such as dataset limitations and clinical variability. Resting-state functional magnetic resonance imaging (Rs-fMRI) can reflect the fluctuation data of brain activity in a resting state, which can find the interrelationships, functional connections, and network characteristics among brain regions of the patients. In this paper, a brain functional connectivity matrix is constructed using Pearson correlation based on the characteristics of multi-site Rs-fMRI data and brain atlas, and an adaptive propagation operator graph convolutional network (APO-GCN) model is designed. The APO-GCN model can automatically adjust the propagation operator in each hidden layer according to the data features to control the expressive power of the model. By adaptively learning effective information in the graph, this model significantly improves its ability to capture complex graph structural patterns. The experimental results on Rs-fMRI data from 1601 participants (830 MDD and 771 HC) and 16 sites of REST-meta-MDD project show that the APO-GCN achieved a classification accuracy of 93.8%, outperforming those of the state-of-the-art classifier methods. The classification process is driven by multiple significant brain regions, and our method further reveals functional connectivity abnormalities between these brain regions, which are important biomarkers of classification. It is worth noting that the brain regions identified by the classifier and the networks involved are consistent with existing research results, which suggest that the pathogenesis of depression may be related to dysfunction of multiple brain networks.