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Purpose: Public mental health services (MHS) are crucial in preventing psychiatric disability pensions (DP). We studied the associations between mood disorder DP risk and the characteristics of Finnish municipalities' MHS provision using the ESMS-R mapping tool and Finnish population registers, based on first-time granted mood disorder DPs between 2010 and 2015. Methods: The final data set included 13,783 first-time mood disorder DP recipients and 1088 mental health service units in 104 municipalities. We focused on five different MHS types: all MHS, outpatient care provision, local services without and with gatekeeping, and centralized services. Three factors for each MHS type were studied: service resources, richness, and diversity index. Negative binomial regression models were used in the analysis. Results: In all the municipalities, higher service richness and diversity regarding all MHS, outpatient care and local services with gatekeeping were associated with a lower DP risk. In urban municipalities, service richness was mainly associated with lower DP risk, and in semi-urban municipalities service diversity and resources were primarily associated with lower DP risk in outpatient care and local services with gatekeeping. In rural municipalities, DP risk indicated no association with MHS factors. Conclusion: The organization and structure of MHS play a role in psychiatric disability pensioning. MHS richness and diversity are associated with lower mood disorder DP in specific societal contexts indicating their role as quality indicators for regional MHS. The diversity of service provision should be accounted for in MHS planning to offer services matching population needs. [ABSTRACT FROM AUTHOR]

Background Postnatal mental health problems (PMHPs) are prevalent and negatively affect mothers, children, and society. International and local guidelines recommend that Singapore primary care physicians (PCP) screen, assess, and manage mothers with PMHPs. However, little is known about their experiences and views. Methods We conducted semi-structured interviews with 14 PCPs in Singapore. Interview questions elicited perspectives on the identification and management of mothers with PMHPs. The interview guide was developed from a conceptual framework incorporating the knowledge-attitudes-practices, self-efficacy, and socio-ecological models. Interviews were audio-recorded and transcribed. Thematic analysis was used to identify emergent themes. Results Singapore PCPs viewed themselves as key providers of first-contact care to mothers with PMHPs. They believed mothers preferred them to alternative providers because of greater accessibility and trust. In detection, they were vigilant in identifying at-risk mothers and favoured clinical intuition over screening tools. PCPs were confident in diagnosing common PMHPs and believed that mothers not meeting diagnostic criteria must be readily recognized and supported. In managing PMHPs, PCPs expressed varying confidence in prescribing antidepressants, which were viewed as second-line to supportive counselling and psychoeducation. Impeding physician factors, constraining practice characteristics and health system limitations were barriers. Looking forward, PCPs aspired to leverage technology and multidisciplinary teams to provide comprehensive, team-based care for the mother-child dyad. Conclusion Singapore PCPs are key in identifying and managing mothers with PMHPs. To fully harness their potential in providing comprehensive care, PCPs need greater multidisciplinary support and technological solutions that promote remote disclosure and enhanced preparation for their role. [ABSTRACT FROM AUTHOR]

Background: Suicide is a primary health concern worldwide, and has a negative impact on the individual, family, and society. The literature suggests that females are more prone to attempt suicide and have more suicidal inclinations; however, males are more serious suicide attempters compared to females. Objective: The objective of this study was to assess the sociodemographic and clinical profile of patients admitted to acute care with the current suicide attempt. Materials and Methods: One hundred consecutive patients, aged between 18 and 60 years, who were medically stable and presented to the emergency or medical wards at the hospital with suicidal attempt, were included in this study. Beck's Suicide Intent Scale (SIS), Beck Scale for Suicidal Ideation, Beck Hopelessness Scale, and Beck Depression Inventory--II were administered to assess the current suicidal intent and ideation, depression, and hopelessness. Results: The diagnostic breakup was -- 69% mood (affective) disorders, 21% adjustment disorders, 4% schizophrenia, and 6% other disorders. Most suicide attempters were female (66% vs. 34%) and belonged to a younger age group (28.30 ± 10.08 years vs. 34.73 ± 13.97 years) compared to males (P < 0.05). Although both genders displayed high suicide intent, a significant difference in the SIS score was noted between females and males (36.53 ± 7.68 vs. 41.47 ± 8.82; P < 0.05). Conclusion: There is a difference in the clinical and demographic profile among male and female suicide attempters. Hence, appropriate interventions can be devised to prevent the future suicide attempts as per the demographic and clinical characteristics specific to the study population. [ABSTRACT FROM AUTHOR]

It has been argued that the history of anxiety and depression should be interpreted as an interaction of cultural changes as well as changes not only in psychopathological symptoms per se, but also in their scientific interpretation, hence the increased interest in addressing such a topic and in carrying out an approach of knowing the peculiarities and emphases characteristic to such an analysis. The current fascination of clinicians and researchers with the biological approach, therefore, comes as no surprise. This approach seems to hold the promise of control and tangible results, in contrast to the unpredictable and much less concrete results achieved by the psychological and social intervention. However, it is necessary to issue a warning at this time, since history has shown us how difficult psychopathological reality can be resolved. The history of the classification of anxiety and depression serves to emphasize that a dose of scepticism was often appropriate. Whenever attempts have been made to refine a particular theory, or combination of theories, the clinical reality has always been shown to have an overabundance of ambiguity and unpredictability. In general, the longitudinal clinical observation has advanced the idea of classifying anxiety disorders, and especially mood disorders, more than any other classification based on preconceived theoretical assumptions. Given the controversy between unitarians and separatists, a combination of longitudinal and interdisciplinary (biopsychosocial) research would seem to hold a particular promise for the future (Kasper et al., 2003). [ABSTRACT FROM AUTHOR]

Background: One of the most robust risk factors for developing a mood disorder is having a parent with a mood disorder. Unfortunately, mechanisms explaining the transmission of mood disorders from one generation to the next remain largely elusive. Since timely intervention is associated with a better outcome and prognosis, early detection of intergenerational transmission of mood disorders is of paramount importance. Here, we describe the design of the Mood and Resilience in Offspring (MARIO) cohort study in which we investigate: 1. differences in clinical, biological and environmental (e.g., psychosocial factors, substance use or stressful life events) risk and resilience factors in children of parents with and without mood disorders, and 2. mechanisms of intergenerational transmission of mood disorders via clinical, biological and environmental risk and resilience factors. Methods: MARIO is an observational, longitudinal cohort study that aims to include 450 offspring of parents with a mood disorder (uni- or bipolar mood disorders) and 100-150 offspring of parents without a mood disorder aged 10-25 years. Power analyses indicate that this sample size is sufficient to detect small to medium sized effects. Offspring are recruited via existing Dutch studies involving patients with a mood disorder and healthy controls, for which detailed clinical, environmental and biological data of the index-parent (i.e., the initially identified parent with or without a mood disorder) is available. Over a period of three years, four assessments will take place, in which extensive clinical, biological and environmental data and data on risk and resilience are collected through e.g., blood sampling, face-to-face interviews, online questionnaires, actigraphy and Experience Sampling Method assessment. For co-parents, information on demographics, mental disorder status and a DNA-sample are collected. Discussion: The MARIO cohort study is a large longitudinal cohort study among offspring of parents with and without mood disorders. A unique aspect is the collection of granular data on clinical, biological and environmental risk and resilience factors in offspring, in addition to available parental data on many similar factors. We aim to investigate the mechanisms underlying intergenerational transmission of mood disorders, which will ultimately lead to better outcomes for offspring at high familial risk. [ABSTRACT FROM AUTHOR]

Ghrelin is primarily responsible for regulating energy balance, as it increases appetite. However, in recent years, its new physiological functions have been discovered--it regulates lipogenesis, plays a role in the development of insulin resistance, and even acts protectively on heart muscle. Moreover, ghrelin was associated with many psychiatric disorders, including major depressive disorder (MDD) or schizophrenia. Ghrelin levels were elevated in patients diagnosed with depression and in patients after suicide attempts. Moreover, ghrelin was connected to depression among postmenopausal women and was shown to be a predictive marker of MDD among the elderly. Ghrelin may influence mood disorders in various ways: by regulating stress response or inflammation or altering neurotransmission in the amygdala, dorsal raphe nucleus, or hippocampus, brain regions previously connected to the pathophysiology of MDD. Genetic variants of ghrelin and its receptor have also been associated with depression. Moreover, ghrelin can interfere with the antidepressant's action and may play a role in treatment resistance. This review highlights ghrelin's role in depression, summarizes the existing knowledge on the subject, and presents ideas for further research. [ABSTRACT FROM AUTHOR]

Background Few studies have evaluated mental health disorders comprehensively among patients with prostate cancer on long-term follow-up. The primary aim of our study was to assess the incidence of mental health disorders among patients with prostate cancer compared with a general population cohort. A secondary aim was to investigate potential risk factors for mental health disorders among patients with prostate cancer. Methods Cohorts of 18 134 patients with prostate adenocarcinomas diagnosed between 2004 and 2017 and 73470 men without cancer matched on age, birth state, and follow-up time were identified. Mental health diagnoses were identified from electronic health records and statewide health-care facilities data. Cox proportional hazard models were used to estimate hazard ratios. All statistical tests were 2-sided. Results The hazard ratios for mood disorders, including depression, among prostate cancer survivors increased for all follow-up periods compared with the general population. The hazard ratios for any mental illness increased with Hispanic, Black, or multiple races; people who were underweight or obese; those with advanced prostate cancer; and those undergoing their first course cancer treatment. We also observed statistically significantly increased hazard ratios for mental health disorders among patients with lower socioeconomic status (P  < .0001) and increasing duration of androgen-deprivation therapy (P  = .0348). Prostate cancer survivors had a 61% increased hazard ratio for death with a depression diagnosis. Conclusion Prostate cancer diagnosis was associated with a higher risk of mental health disorders compared with the general population, which was observed as long as 10-16 years after cancer diagnosis. Providing long-term mental health support may be beneficial to increasing life expectancy for patients with prostate cancer. [ABSTRACT FROM AUTHOR]

Background: The intricate correlation between environmental exposures and mental health outcomes is increasingly acknowledged in psychiatric research. This study investigated the relationship between cumulative environmental risk factors, as represented by the exposome score (ES), and various domains of psychopathology within a non-clinical sample using a network analysis. Methods: We recruited 1100 participants (aged 18–35 years, 51.4% females) via a computer-assisted web interview, assessing psychopathological symptoms using standardized questionnaires. Environmental exposures, including season of birth, obstetric complications, advanced paternal age, childhood trauma, cannabis use, and urban upbringing, were self-reported to calculate the ES. Results: A network analysis revealed significant associations of the ES with psychotic-like experiences (PLEs) (weight = 0.113), manic (weight = 0.072), and attention-deficit/hyperactivity disorder symptoms (weight = 0.062). These connections did not differ significantly with respect to their weights. Depressive symptoms had the highest centrality and predictability. The mean predictability across all nodes included in the network was 0.344. Conclusions: These findings underscore the transdiagnostic nature of environmental exposures, aligning with previous research indicating broad associations between the ES and various facets of psychopathology. Our results suggest that the ES may not specifically correlate with PLEs but may indicate the risk of a broader psychopathology. [ABSTRACT FROM AUTHOR]

Background Patients with inflammatory bowel disease (IBD) are at increased risk of anxiety and mood disorders. This study examines the temporal trends and clinical impact of anxiety and mood disorder diagnoses in hospitalized IBD patients in the United States during a 10-year period. Methods Using the National Inpatient Sample from 2009-2018, all IBD-related discharges in adults were analyzed. Primary outcomes were the prevalence and temporal trends of mood disorder and anxiety diagnoses for IBD-related admissions. The impact of the psychiatric comorbidities on clinical outcomes was also evaluated. Results A total of 1,718,736 IBD-related discharged were identified. A diagnosis of anxiety or a mood disorder was found to have a prevalence of 16.44% and 18.97%, respectively, amongst IBDrelated admissions. The prevalence of anxiety disorders amongst hospitalized IBD patients increased significantly (from 12.13% to 20.26%), whereas the prevalence of mood disorders did not (17.46% and 18.9%). IBD admissions with psychiatric comorbidities had lower rates of IBD-related complications or mortality during hospitalization compared to IBD admissions without comorbid psychiatric diagnoses. This population, however, was more likely to experience certain comorbidities such as Clostridioides difficile, pneumonia, and venous thromboembolism, as well as a longer hospitalization. Conclusions The prevalence of comorbid anxiety among hospitalized IBD patients in the United States matches or exceeds the prevalence of anxiety in the general hospitalized population. Given its association with more in-hospital complications and a longer hospital stay, it is important to further understand how psychological screening and mental health services can improve the management of hospitalized IBD patients. [ABSTRACT FROM AUTHOR]

Individuals at familial risk for mood disorders exhibit deficits in emotional processing and associated brain dysfunction prior to illness onset. However, such brain-behavior abnormalities related to familial predisposition remain poorly understood. To investigate robust abnormal functional activation patterns during emotional processing in unaffected at-risk relatives of patients with major depressive disorder (UAR-MDD) and bipolar disorder (UAR-BD), we performed a meta-analysis of task-based functional magnetic resonance imaging studies using Seed-based d Mapping (SDM) toolbox. Common and distinct patterns of abnormal functional activation between UAR-MDD and UAR-BD were detected via conjunction and differential analyses. A total of 17 studies comparing 481 UAR and 670 healthy controls (HC) were included. Compared with HC, UAR-MDD exhibited hyperactivation in the parahippocampal gyrus, amygdala and cerebellum, while UAR-BD exhibited parahippocampal hyperactivation and hypoactivation in the striatum and middle occipital gyrus (MOG). Conjunction analysis revealed shared hyperactivated PHG in both groups. Differential analysis indicated that the activation patterns of amygdala and MOG significantly differed between UAR-MDD and UAR-BD. These findings provide novel insights into common and distinct neural phenotypes for familial risk and associated risk mechanisms in MDD and BD, which may have implications in guiding precise prevention strategies tailored to the family context. • The first neuroimaging meta-analysis comparing UAR-MDD and UAR-BD • Robust functional activation patterns during emotional processing in UAR • Shared and distinct functional abnormalities between UAR-MDD and UAR-BD • Different co-activation networks in UAR-MDD and UAR-BD during emotional processing [ABSTRACT FROM AUTHOR]

Background: Literature reveals that both substance use and sleep are interlinked, and even various aspects of substance use are relevant to sleep. Sleep disturbances are among the most common and consistent symptoms in patients with acute episodes of mood disorders. These psychiatric illnesses commonly co‑occur with substance use disorders (SUDs), and the combination has adverse clinical consequences. Aim: To compare the pattern of substance use and quality of sleep in patients with depression and mania. Materials and Methods: A total of 150 patients (75 in each group) of either sex in the age group of 18‑65 years visiting the psychiatry department who gave written informed consent were diagnosed using International Classification of Diseases‑10 (ICD‑10) for either mania or depression including recurrent depressive disorder and bipolar affective disorder. The patients in each group were evaluated using WHO ASSIST version 3 for substance pattern and PSQI for quality of sleep. Results: The most common substance used was tobacco followed by alcohol in both groups with a significant P value of 0.01. When comparing WHO ASSIST grades, 62.7% of depression had low grades whereas 48% of patients with mania had a moderate grade, with a P value of 0.002 which is significant. There was a significant difference in the individual component of PSQI between the two groups and patients in mania had a higher score. Conclusion: There was a significant association between the pattern of substance use and mood disorder. In the study subjects, all the patients in both groups had poor sleep quality. Further substance use and quality of sleep are interrelated with both mood disorders. [ABSTRACT FROM AUTHOR]

Several types of mood disorders lie along a continuum, with nebulous boundaries between them. Understanding the mechanisms that contribute to mood disorder complexity is critical for effective treatment. However, present treatments are largely centered around neurotransmission and receptor-based hypotheses, which, given the high instance of treatment resistance, fail to adequately explain the complexities of mood disorders. In this opinion piece, based on our recent results, we propose a ribosome hypothesis of mood disorders. We suggest that any hypothesis seeking to explain the diverse nature of mood disorders must incorporate infrastructure diversity that results in a wide range of effects. Ribosomes, with their mobility across neurites and complex composition, have the potential to become specialized during stress; thus, ribosome diversity and dysregulation are well suited to explaining mood disorder complexity. Here, we first establish a framework connecting ribosomes to the current state of knowledge associated with mood disorders. Then, we describe the potential mechanisms through which ribosomes could homeostatically regulate systems to manifest diverse mood disorder phenotypes and discuss approaches for substantiating the ribosome hypothesis. Investigating these mechanisms as therapeutic targets holds promise for transdiagnostic avenues targeting mood disorders. [ABSTRACT FROM AUTHOR]

Background: Experimental and clinical studies have reported increased levels of pro-inflammatory cytokines in patients with major depressive disorder (MDD), suggesting that immune system dysregulation may contribute to MDD pathophysiology. Aim: Due to the lack of knowledge about the immune potential of antidepressants, this study investigated the immunomodulatory effects of bupropion, a norepinephrine--dopamine reuptake inhibitor. Methods: This study involved 18 patients with MDD treated with bupropion (150 mg/d) for 4 weeks and 23 healthy volunteers. All participants underwent multiplex bead-based cytokine assessment before and after bupropion treatment to quantify the following cytokines: interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12, IL-13, IL-17, interferon-γ, tumor necrosis factor-α, granulocyte colony-stimulating factor, granulocyte-macrophage CSF, monocyte chemotactic protein-1, and macrophage inflammatory protein-1β. Results: Four-week treatment with bupropion significantly increased the levels of IL-1β (P = 0.011), IL-4 (P = 0.019), IL-5 (P = 0.019), IL-7 (P = 0.021), and IL-8 (P = 0.023) compared to the control group. Furthermore, the percentage change in most cytokines, including anti-inflammatory cytokines such as IL-4, IL-5, IL-10, and IL-13, was significantly increased after bupropion treatment. Conclusion: The promoted synthesis of anti-inflammatory cytokines to surpass the pro-inflammatory cytokines may be a crucial step in the treatment of MDD patients with bupropion. [ABSTRACT FROM AUTHOR]

Purpose of Review: Review the current evidence on biomarkers for bipolar disorder in the older adults. We conducted a systematic search of PubMed MEDLINE, PsycINFO, and Web of Science databases using the MeSH search terms "Biomarkers", "Bipolar Disorder", "Aged" and and "Aged, 80 and over". Studies were included if they met the following criteria: (1) the mean age of the study population was 50 years old or older, (2) the study included patients with bipolar disorder, and (3) the study examined one type of biomarkers or more including genetic, neuroimaging, and biochemical biomarkers. Reviews, case reports, studies not in English and studies for which no full text was available were excluded. A total of 26 papers were included in the final analysis. Recent Findings: Genomic markers of bipolar disorder in older adults highlighted the implication of serotonin metabolism, while the expression of genes involved in angiogenesis was dysregulated. Peripheral blood markers were mainly related with low grade inflammation, axonal damage, endothelial dysfunction, and the dysregulation of the HPA axis. Neuroanatomical markers reflected a dysfunction of the frontal cortex, a loss of neurones in the anterior cingulate cortex and a reduction of the hippocampal volume (in patients older than 50 years old). While not necessarily limited to older adults, some of them may be useful for differential diagnosis (neurofilaments), disease staging (homocysteine, BDNF) and the monitoring of treatment outcomes (matrix metalloproteinases). Summary: Our review provides a comprehensive overview of the current evidence on biomarkers for bipolar disorder in the older adults. The identification of biomarkers may aid in the diagnosis, treatment selection, and monitoring of bipolar disorder in older adults, ultimately leading to improved outcomes for this population. Further research is needed to validate and further explore the potential clinical utility of biomarkers in this population. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 pandemic has increased the global experience of anxiety and depression owing to social isolation and government-mandated quarantine for transmission reduction. To date, literature surrounding the mental health effects of COVID-19 for the U.S. population is limited. Methods: This is a retrospective study from a large metropolitan Detroit health system. Patient encounters between December 23, 2018 and June 22, 2021, with March 23, 2020 being the start of Michigan state-wide lockdown, were used to define pre– and post–COVID-19 encounters, respectively. The data were divided into Detroit and non-Detroit on the basis of patient ZIP code. All patients aged ≥13 years with a visit with a family medicine provider were included. Outcome variables included Patient Health Questionnaires-2 and -9 and General Anxiety Disorder-7 scores; diagnoses of depression, anxiety, adjustment, and grief disorders; antidepressant prescriptions; and behavioral health referrals. Logistic regression was used to determine the incidence of composite mood disorder, depression, and anxiety. Results: A total of 20,970 individuals were included in this study: 10,613 in the Detroit subgroup and 10,357 in the non-Detroit subgroup. A total of 88.2% of the Detroit population were Black, and 70% were female. Logistic regression shows that the incidence of composite mood disorder decreased with increasing age (OR=0.787, 0.608, 0.422, and 0.392; p

Oxcarbazepine is often utilized off-label for bipolar and depressive disorders in outpatient settings despite limited evidence. We performed a retrospective chart review on 38 adult outpatients diagnosed with bipolar and depressive disorders (ICD-10 codes F30-39), treated with oxcarbazepine by psychiatrists and psychiatric nurse practitioners between 2015 and 2021. Primary outcomes were Clinical Global Impression Severity (CGI-S) and Improvement (CGI-I) scores, assigned retrospectively from clinical documentation. Patients were predominantly female (70%), aged 20–76 (mean 36), with a mean of 1.8 DSM diagnoses (range 1–4) and 1.7 (range 0–5) concurrent psychotropic medications. A starting mean oxcarbazepine dose of 489 mg/day, titrated to a mean final dose of 663 mg/day, was associated with a CGI-I of 2.5 [2.25, 2.75] and a pre-to-post treatment decrease in CGI-S from 3.4 to 2.4. Overall response and remission rates were 52% and 29%, respectively. Limitations of this study include potential sample bias, documentation bias and rater bias among other limitations inherent to retrospective study designs.

Abstract Background Mood disorders are strongly associated with melatonin disturbances. However, it is unclear whether there is a difference in melatonin concentrations and melatonin circadian rhythm profiles between depression and bipolar disorder. In addition, the relationship between anhedonia, a common symptom of affective disorders, and its melatonin circadian rhythm remains under-investigated. Methods Thirty-four patients with depression disorder, 20 patients diagnosed with bipolar disorder and 21 healthy controls participated in this study. The Revised Physical Anhedonia Scale (RPAS) was performed to assess anhedonia. Saliva samples were collected from all subjects at fixed time points (a total of 14 points) in two consecutive days for measuring the melatonin concentrations to fit circadian rhythms of subjects. Melatonin circadian rhythms were compared between the three groups using ANOVA. Partial correlation analysis and linear regression analysis were used to explore the correlation between melatonin rhythm variables and anhedonia. Results We found that the peak phase of melatonin in the depression group was significantly advanced compared to the control group (P

Abstract Objective Major depressive disorder (MDD) and bipolar disorder (BD) are serious chronic disabling mental and emotional disorders, with symptoms that often manifest atypically in children and adolescents, making diagnosis difficult without objective physiological indicators. Therefore, we aimed to objectively identify MDD and BD in children and adolescents by exploring their voiceprint features. Methods This study included a total of 150 participants, with 50 MDD patients, 50 BD patients, and 50 healthy controls aged between 6 and 16 years. After collecting voiceprint data, chi-square test was used to screen and extract voiceprint features specific to emotional disorders in children and adolescents. Then, selected characteristic voiceprint features were used to establish training and testing datasets with the ratio of 7:3. The performances of various machine learning and deep learning algorithms were compared using the training dataset, and the optimal algorithm was selected to classify the testing dataset and calculate the sensitivity, specificity, accuracy, and ROC curve. Results The three groups showed differences in clustering centers for various voice features such as root mean square energy, power spectral slope, low-frequency percentile energy level, high-frequency spectral slope, spectral harmonic gain, and audio signal energy level. The model of linear SVM showed the best performance in the training dataset, achieving a total accuracy of 95.6% in classifying the three groups in the testing dataset, with sensitivity of 93.3% for MDD, 100% for BD, specificity of 93.3%, AUC of 1 for BD, and AUC of 0.967 for MDD. Conclusion By exploring the characteristics of voice features in children and adolescents, machine learning can effectively differentiate between MDD and BD in a population, and voice features hold promise as an objective physiological indicator for the auxiliary diagnosis of mood disorder in clinical practice.

Context: Mood and anxiety disorders appear to be overrepresented in adults with cardiovascular diseases (CVDs). These disorders have been associated with poorer biopsychosocial outcomes in this population. Mood and anxiety disorders often co-occur, but the prevalence of this comorbidity and their potential additive effects in patients with CVD remain understudied. Aims: This study aimed to estimate the prevalence and co-occurrence rates of mood and anxiety disorders in the general adult population living with CVD. Associations between mood and anxiety disorder status and sociodemographic characteristics, somatic comorbidities, perceived mental health, and health-care service use were also investigated. Methods: A total of 6,792 adults aged 25 years or older and living with CVD were selected from the 2015–2016 Canadian Community Health Survey. Mood and anxiety disorders were identified based on self-report diagnoses made by a qualified health professional. All other variables were assessed using questionnaires. Results: An estimated 17.7% of the studied population reported having been diagnosed with a mood or anxiety disorder. More precisely, 6.6% reported a mood disorder, 5.5% reported an anxiety disorder, and an additional 5.6% reported both. The presence of mood or anxiety disorders was associated with poorer perceived mental health and higher health-care service use, and these associations were stronger when mood and anxiety co-occurred. Conclusions: Approximately one in six adults with CVD reported suffering from mood or anxiety disorders, and a third of them presented both conditions. This study also suggests that co-occurring anxiety and mood disorders lead to greater vulnerability than either disorder in adults with CVD.

Psychiatric illness may develop or relapse during pregnancy, and understanding best practices is paramount. In 2017, the British Association for Psychopharmacology (BAP) consensus guidance on the use of psychotropic medication preconception, in pregnancy, and postpartum was released. The BAP guidelines provide concise evidence and additional insight and flexibility for use of psychiatric medication. Key takeaways of these guidelines are highlighted serving as a concise reference for practitioners. Additionally, practice points, such as recommendations for rapid tranquilization and the role of long-acting injectable antipsychotic medications as well as additional insights to the growing body of literature associated with psychiatric medications in pregnancy since 2017 are summarized. Providers are strongly encouraged to stay up to date to provide optimal care for pregnant patients and their babies.

Background: Mood disorders are strongly associated with melatonin disturbances. However, it is unclear whether there is a difference in melatonin concentrations and melatonin circadian rhythm profiles between depression and bipolar disorder. In addition, the relationship between anhedonia, a common symptom of affective disorders, and its melatonin circadian rhythm remains under-investigated. Methods: Thirty-four patients with depression disorder, 20 patients diagnosed with bipolar disorder and 21 healthy controls participated in this study. The Revised Physical Anhedonia Scale (RPAS) was performed to assess anhedonia. Saliva samples were collected from all subjects at fixed time points (a total of 14 points) in two consecutive days for measuring the melatonin concentrations to fit circadian rhythms of subjects. Melatonin circadian rhythms were compared between the three groups using ANOVA. Partial correlation analysis and linear regression analysis were used to explore the correlation between melatonin rhythm variables and anhedonia. Results: We found that the peak phase of melatonin in the depression group was significantly advanced compared to the control group (P < 0.001) and the bipolar disorder group (P = 0.004). The peak phase of melatonin and RPAS showed a negative correlation (P = 0.003) in depression patients, which was also demonstrated in the multiple linear regression model (B=-2.47, P = 0.006). Conclusions: These results suggest that circadian rhythms of melatonin are differentiated in depression and bipolar disorder and correlate with anhedonia in depression. Future research needs to explore the neurobiological mechanisms linking anhedonia and melatonin circadian rhythms in depressed patients. [ABSTRACT FROM AUTHOR]

Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep--circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep--circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and treatment of mood, anxiety, and psychosis spectrum disorders, with a transdiagnostic perspective; b) highlight the need to reframe existing knowledge and adopt an integrated approach which recognizes the interaction between sleep and circadian factors; and c) identify important gaps and opportunities for further research. [ABSTRACT FROM AUTHOR]

We examined whether women with prenatal mood and anxiety disorders would exhibit differential pro- and anti-inflammatory marker trajectories during the prenatal and postpartum periods compared to women without these disorders. Approximately 179 pregnant women participated in a longitudinal study conducted in two urban areas. Blood samples for inflammatory markers were collected at six study visits. The Structured Clinical Interview for the DSM-IV (SCID) was administered to participants scoring above cutoffs on anxiety and depression. Pregnant women with SCID Axis I diagnoses of mood and/or anxiety disorders were compared to other participants on inflammatory markers. Multilevel modeling tested associations between SCID diagnoses and within-person interleukin (IL)6 and IL10 trajectories. Prenatal SCID diagnoses were associated with linear, quadratic and cubic change in IL6 from prenatal to postpartum timepoints. Women with a prenatal SCID diagnosis had steeper decreases and increases in IL6 during prenatal and postpartum periods. SCID diagnoses were associated with lower IL10 in mid-pregnancy to postpartum (b = −0.078, SE = 0.019; p =.015). Future studies would benefit from a larger sample size and a larger number of participants with SCID diagnoses. Future research should also examine whether different prenatal Axis 1 diagnoses are associated with different patterns of immune response in pregnancy. Pregnant women with prenatal mood and anxiety disorders had greater fluctuations in IL6 across prenatal and postpartum periods and lower IL10 through pregnancy and postpartum. They may have different proinflammatory states that remain after birth without a reciprocal anti-inflammatory response. • Prenatal mood and anxiety disorders are linked to postpartum inflammation. • Women with prenatal SCID diagnoses had greater fluctuations of inflammatory markers. • Lower anti-inflammatory markers in pregnancy associated with prenatal SCID diagnoses [ABSTRACT FROM AUTHOR]

Background: White matter hyperintensities are lesions of presumed vascular origin associated with Cerebral small vessel disease. WMH are common findings that and are associated with increased risk of cognitive impairment and dementia. A higher prevalence of WMH has been also reported in patients with bipolar disorder (BD), although the evidence is conflicting. Objective: To compare the prevalence of WMH in adults with BD, with the prevalence found in healthy controls. Methods: We searched the Embase, Medline/PubMed, and references cited in articles retrieved on May 20, 2023. We included case-control studies that compared the prevalence of WMH in adult BD patients with the prevalence of WMH in healthy controls, using T2-weighted magnetic resonance imaging. We performed a meta-analysis using a random-effects method based on the inverse-variance approach. Findings: We included 22 case-control studies reporting data of 1313 people. The overall rate of WMH was 46.5% in BD patients and 28% in controls (pooled Odds Ratio 2.89, 95% CI 1.76; 4.75). We found a moderate heterogeneity across studies (I2 = 0.49). Publication bias was not significant. Interpretation: We found evidence that BD patients have a higher burden of WMH than healthy controls. Main limitations were impossibility of analyzing gender differences and bipolar type, moderate heterogeneity between studies, non-representative samples, lack of control for major confounders and search in two electronic databases. [ABSTRACT FROM AUTHOR]

This article discusses a new method for monitoring drug concentrations in blood samples from patients with mood disorders. The method uses solid-phase microextraction to extract analytes directly from blood samples. It has been adapted to identify the most commonly used drugs in mood disorders, including amitriptyline, citalopram, fluoxetine, paroxetine, sertraline, trazodone, duloxetine, venlafaxine, lamotrigine, quetiapine, olanzapine, and mirtazapine. The analysis is carried out using high-performance liquid chromatography coupled with mass spectroscopy. The proposed DI-SPME/LC-MS method allows for a simple and quick screening analysis while minimizing the volume of the tested sample and solvent, in line with the principles of green analytical chemistry. The method was used to analyze 38 blood samples taken from patients with mood disorders, and drug concentrations were determined and compared with therapeutic and toxic dose ranges. This allowed for better control of the course of treatment. [ABSTRACT FROM AUTHOR]

There is a lack of information regarding the impact of the physical symptoms associated with endometriosis and chronic pain on the mental health and well-being of affected women. Thus, our study aimed to evaluate the relationship between endometriosis, chronic pain, anxiety, and depression. Our study aimed to evaluate the relationship between endometriosis, chronic pain, and mental health disorders among women registered in a large database until 2014. This was a retrospective population-based study involving 12,904,324 hospitalized women from the Healthcare Cost and Utilization Project (HCUP) database between 2007 and 2014. We calculated the prevalence of chronic pain, endometriosis, anxiety, and depression during the study period. We used multivariate logistic regression to examine the relationship between these variables. An upward pattern was noted in the prevalence of chronic pain, while an opposite trend was seen for endometriosis during the study period. After adjusting for sociodemographic characteristics and comorbidities, including depression, the highest odds ratio of experiencing anxiety appeared in the group with both chronic pain and endometriosis (OR = 2.719, 95 % CI 2.481–2.979). HCUP is a cross-sectional administrative database that does not link patients' records over the years. Thus, we could not establish any temporal association between endometriosis, chronic pain, anxiety, and depression. Potential associations were identified between endometriosis, with and without chronic pain, anxiety, and depression. We recommended that clinicians provide proper medical management of endometriosis-related pain through symptom management and adequate counseling for those suffering from anxiety and depression. • We found associations between endometriosis, chronic pain, anxiety, and depression. • Concurrent chronic pain and endometriosis had the strongest association with anxiety. • Comprehensive care for endometriosis cases is essential. [ABSTRACT FROM AUTHOR]

Objective: Major depressive disorder (MDD) and bipolar disorder (BD) are serious chronic disabling mental and emotional disorders, with symptoms that often manifest atypically in children and adolescents, making diagnosis difficult without objective physiological indicators. Therefore, we aimed to objectively identify MDD and BD in children and adolescents by exploring their voiceprint features. Methods: This study included a total of 150 participants, with 50 MDD patients, 50 BD patients, and 50 healthy controls aged between 6 and 16 years. After collecting voiceprint data, chi-square test was used to screen and extract voiceprint features specific to emotional disorders in children and adolescents. Then, selected characteristic voiceprint features were used to establish training and testing datasets with the ratio of 7:3. The performances of various machine learning and deep learning algorithms were compared using the training dataset, and the optimal algorithm was selected to classify the testing dataset and calculate the sensitivity, specificity, accuracy, and ROC curve. Results: The three groups showed differences in clustering centers for various voice features such as root mean square energy, power spectral slope, low-frequency percentile energy level, high-frequency spectral slope, spectral harmonic gain, and audio signal energy level. The model of linear SVM showed the best performance in the training dataset, achieving a total accuracy of 95.6% in classifying the three groups in the testing dataset, with sensitivity of 93.3% for MDD, 100% for BD, specificity of 93.3%, AUC of 1 for BD, and AUC of 0.967 for MDD. Conclusion: By exploring the characteristics of voice features in children and adolescents, machine learning can effectively differentiate between MDD and BD in a population, and voice features hold promise as an objective physiological indicator for the auxiliary diagnosis of mood disorder in clinical practice. [ABSTRACT FROM AUTHOR]

The gut-brain axis (GBA) is a network responsible for the bidirectional communication between the central nervous system and the gastrointestinal tract. This multifaceted system is comprised of a complex microbiota, which may be altered by both intrinsic and extrinsic factors. During critical periods of development, these intrinsic and extrinsic factors can cause long-lasting sex-dependent changes in the GBA, which can affect brain structure and function. However, there is limited understanding of how the GBA is altered by stress and how it may be linked to the onset of mental illness during puberty. This article reviews current literature on the relationships between the GBA, the effects of stress during puberty, and the implications for mental health. [ABSTRACT FROM AUTHOR]

Acoustic stimuli such as music or ambient noise can significantly affect physiological and psychological health in humans. We here summarize positive effects of music therapy in premature infant distress regulation, performance enhancement, sleep quality control, and treatment of mental disorders. Specifically, music therapy exhibits promising effects on treatment of neurological disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD). We also highlight regulatory mechanisms by which auditory intervention affects an organism, encompassing modulation of immune responses, gene expression, neurotransmitter regulation and neural circuitry. As a safe, cost-effective and non-invasive intervention, music therapy offers substantial potential in treating a variety of neurological conditions. [ABSTRACT FROM AUTHOR]

The subtype diagnosis and severity classification of mood disorder have been made through the judgment of verified assistance tools and psychiatrists. Recently, however, many studies have been conducted using biomarker data collected from subjects to assist in diagnosis, and most studies use heart rate variability (HRV) data collected to understand the balance of the autonomic nervous system on statistical analysis methods to perform classification through statistical analysis. In this research, three mood disorder severity or subtype classification algorithms are presented through multimodal analysis of data on the collected heart-related data variables and hidden features from the variables of time and frequency domain of HRV. Comparing the classification performance of the statistical analysis widely used in existing major depressive disorder (MDD), anxiety disorder (AD), and bipolar disorder (BD) classification studies and the multimodality deep neural network analysis newly proposed in this study, it was confirmed that the severity or subtype classification accuracy performance of each disease improved by 0.118, 0.231, and 0.125 on average. Through the study, it was confirmed that deep learning analysis of biomarker data such as HRV can be applied as a primary identification and diagnosis aid for mental diseases, and that it can help to objectively diagnose psychiatrists in that it can confirm not only the diagnosed disease but also the current mood status. [ABSTRACT FROM AUTHOR]

Objective: We aimed to investigate the characteristics and psychological mechanism of non-suicidal self-injury (NSSI) in adolescents with mood disorders. We examined how self-compassion and emotional regulation affected NSSI and tested the mediating role of self-compassion in the link between emotional regulation and NSSI. Method: We recruited outpatient and inpatient adolescent patients with bipolar and related disorders or depressive disorders (DSM-5), with a focus on NSSI. We also recruited healthy controls from the community. We collected demographic and clinical data. The Adolescent Self-injury Questionnaire, Selfcompassion Scale (SCS), and Emotion Regulation Questionnaire (ERQ) were used to assess the frequency and severity of NSSI, level of self-compassion, and emotional regulation. Results: In total, we recruited 248 adolescent patients with mood disorders (N = 196 with NSSI, and 52 without NSSI) and 212 healthy controls. NSSI was significantly associated with the female sex, lower levels of education and less use of cognitive reappraisal strategies, lower levels of self-warmth, and higher levels of self-coldness. Multivariate analysis of variance showed that there were significant differences in the scores of ERQ, cognitive reassessment score, and the scores of SCS among the three groups, but no statistical differences in expressive suppression score among the three groups. Self-warmth had a mediating effect between cognitive reappraisal and NSSI behavior. Conclusion: NSSI is prevalent among adolescent patients with mood disorders in clinical settings, especially among girls and those with lower levels of education and less cognitive reappraisal strategies. More clinical attention is needed. Selfcompassion and its factors may mediate the association between emotional regulation and NSSI. Clinical implications and future research directions were discussed. [ABSTRACT FROM AUTHOR]

Background: Perinatal depression (PND) is often under-treated and under-recognized. It has a negative impact on infant development and mother–child interactions. This study aims to estimate the prevalence of PND during pregnancy and in the postpartum period and the effect of sociodemographic factors, psychosocial stressors, and obstetric and neonatal factors on PND. Methods: 166 antenatal mothers attending tertiary center, who completed the 1st-trimester, were evaluated on baseline sociodemographic, psychosocial, obstetric, neonatal, and post neonatal factors by using a semi-structured questionnaire. Periodic prospective assessments were done using Hamilton depression rating scale (HAMD) at the end of the second and third trimesters and first and sixth weeks of the postpartum period. Results: Prevalence of PND was 21.7%, 32.2%, 35%, 30.4%, and 30.6%, at the end of the first trimester, during second, and third trimesters, and first and sixth week postpartum, respectively. Factors significantly associated with depressive symptoms included history of previous children with illness (P: 0.013, OR—5.16, CI—1.3-19.5) and preterm birth (P: 0.037, OR—3.73, CI—1.1- 13.2) at the time of recruitment; history of abuse (P: 0.044, OR—3.26, CI—1.1-10.8) and marital conflicts (P: 0.003, OR—3.2, CI—1.4-6.9) by the end of second trimester; history of miscarriages (P: 0.012, OR—2.58, CI—1.2-5.4) by the end of third trimester; lower SES (P: 0.001, OR—3.48, CI—1.64-7.37), unsatisfied living conditions (P: 0.004, OR—2.9, CI—1.4-6.04), alcohol use in husband (P: 0.049, OR—2.01, CI—1.1-4.11), history of depressive episodes (P: 0.049, OR—2.09, CI—1.1-4.46), history of high-risk pregnancy (P: 0.008, OR—2.7, CI—1.29-5.64), history of miscarriages (P: 0.049, OR—2.04, CI—1.1-4.2), stressful events in the postpartum period (P: 0.043, OR—2.58, CI—1.01-6.59), IUD (P: 0.002), preterm birth (P: 0.001), congenital malformations (P: 0.001), dissatisfaction with the sex of the child (P: 0.005, OR—3.75, CI—1.42-9.91), poor family support (P: 0.001), and low birth weight (P: 0.001, OR—16.78, CI—6.32-44.53) in the postpartum period. These analyses are purely exploratory. Conclusions: PND is highly prevalent from the early antenatal period onwards; this warrants periodic assessment of depression among high-risk mothers, using a validated tool, for early diagnosis and management. [ABSTRACT FROM AUTHOR]

Mixed depressive states are defined by the co-presence of depressive and manic symptoms. They represent extremely variable conditions from the point of view of clinical expressiveness and are difficult to recognize, ranging from clear schizophrenic-like psychoses and pseudodemented pictures to subsyndromal psychopathology. At the basis of the extreme variability of depressive pictures with mixed features are the different combinations that depressive and manic symptoms can assume. Furthermore, the intensity of depressive symptoms and manic symptoms, combined, can be variable, a factor that contributes to making the picture even more variable. Each form of mixed depressive state therefore presents its own specific symptomatic characteristics and specific difficulties in differential diagnosis and each form requires a different therapeutic strategy. In this work we have distinguished four possible specific subtypes of mixed depressive states, describing their specific clinical presentation and the therapeutic options most supported by the literature with the aim of contributing to a better recognition of mixed depressive states, to avoid incorrect diagnoses at patient and treatments that are useless if not worsening. [ABSTRACT FROM AUTHOR]

Background: Digital mental health is a rapidly growing field with an increasing evidence base due to its potential scalability and impacts on access to mental health care. Further, within underfunded service systems, leveraging personal technologies to deliver or support specialized service delivery has garnered attention as a feasible and cost-effective means of improving access. Digital health relevance has also improved as technology ownership in individuals with schizophrenia has improved and is comparable to that of the general population. However, less digital health research has been conducted in groups with schizophrenia spectrum disorders compared to other mental health conditions, and overall feasibility, efficacy, and clinical integration remain largely unknown. Objective: This review aims to describe the available literature investigating the use of personal technologies (ie, phone, computer, tablet, and wearables) to deliver or support specialized care for schizophrenia and examine opportunities and barriers to integrating this technology into care. Methods: Given the size of this review, we used scoping review methods. We searched 3 major databases with search teams related to schizophrenia spectrum disorders, various personal technologies, and intervention outcomes related to recovery. We included studies from the full spectrum of methodologies, from development papers to implementation trials. Methods and reporting follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Results: This search resulted in 999 studies, which, through review by at least 2 reviewers, included 92 publications. Included studies were published from 2010 to 2023. Most studies examined multitechnology interventions (40/92, 43%) or smartphone apps (25/92, 27%), followed by SMS text messaging (16/92, 17%) and internet-based interventions (11/92, 12%). No studies used wearable technology on its own to deliver an intervention. Regarding the stage of research in the field, the largest number of publications were pilot studies (32/92, 35%), followed by randomized control trials (RCTs; 20/92, 22%), secondary analyses (16/92, 17%), RCT protocols (16/92, 17%), development papers (5/92, 5%), and nonrandomized or quasi-experimental trials (3/92, 3%). Most studies did not report on safety indices (55/92, 60%) or privacy precautions (64/92, 70%). Included studies tend to report consistent positive user feedback regarding the usability, acceptability, and satisfaction with technology; however, engagement metrics are highly variable and report mixed outcomes. Furthermore, efficacy at both the pilot and RCT levels report mixed findings on primary outcomes. Conclusions: Overall, the findings of this review highlight the discrepancy between the high levels of acceptability and usability of these digital interventions, mixed efficacy results, and difficulties with sustained engagement. The discussion highlights common patterns that may underscore this observation in the field; however, as this was a scoping review, a more in-depth systematic review or meta-analysis may be required to better understand the trends outlined in this review. [ABSTRACT FROM AUTHOR]

Background: Depression and anxiety have become increasingly prevalent across the globe. The rising need for treatment and the lack of clinicians has resulted in prolonged waiting times for patients to receive their first session. Responding to this gap, digital mental health interventions (DMHIs) have been found effective in treating depression and anxiety and are potentially promising pretreatments for patients who are awaiting face-to-face psychotherapy. Nevertheless, whether digital interventions effectively alleviate symptoms for patients on waiting lists for face-to-face psychotherapy remains unclear. Objective: This review aimed to synthesize the effectiveness of DMHIs for relieving depression and anxiety symptoms of patients on waiting lists for face-to-face therapy. This review also investigated the features, perceived credibility, and usability of DMHIs during waiting times. Methods: In this systematic review, we searched PubMed, PsycINFO, Cochrane, and Web of Science for research studies investigating the effectiveness of DMHIs in reducing either depression or anxiety symptoms among individuals waiting for face-to-face psychotherapy. The search was conducted in June 2024, and we have included the studies that met the inclusion criteria and were published before June 6, 2024. Results: Of the 9267 unique records identified, 8 studies met the eligibility criteria and were included in the systematic review. Five studies were randomized controlled trials (RCTs), and 3 studies were not. Among the RCTs, we found that digital interventions reduced depression and anxiety symptoms, but the majority of interventions were not more effective compared to the control groups where participants simply waited or received a self-help book. For the non-RCTs, the interventions also reduced symptoms, but without control groups, the interpretation of the findings is limited. Finally, participants in the included studies perceived the digital interventions to be credible and useful, but high dropout rates raised concerns about treatment adherence. Conclusions: Due to the lack of effective interventions among the reviewed studies, especially among the RCTs, our results suggest that waiting list DMHIs are not more effective compared to simply waiting or using a self-help book. However, more high-quality RCTs with larger sample sizes are warranted in order to draw a more robust conclusion. Additionally, as this review revealed concerns regarding the high dropout rate in digital interventions, future studies could perhaps adopt more personalized and human-centered functions in interventions to increase user engagement, with the potential to increase treatment adherence and effectiveness. [ABSTRACT FROM AUTHOR]

Recent breakthroughs in artificial intelligence (AI) language models have elevated the vision of using conversational AI support for mental health, with a growing body of literature indicating varying degrees of efficacy. In this paper, we ask when, in therapy, it will be easier to replace humans and, conversely, in what instances, human connection will still be more valued. We suggest that empathy lies at the heart of the answer to this question. First, we define different aspects of empathy and outline the potential empathic capabilities of humans versus AI. Next, we consider what determines when these aspects are needed most in therapy, both from the perspective of therapeutic methodology and from the perspective of patient objectives. Ultimately, our goal is to prompt further investigation and dialogue, urging both practitioners and scholars engaged in AI-mediated therapy to keep these questions and considerations in mind when investigating AI implementation in mental health. [ABSTRACT FROM AUTHOR]

Background: Large language models (LLMs) hold potential for mental health applications. However, their opaque alignment processes may embed biases that shape problematic perspectives. Evaluating the values embedded within LLMs that guide their decision-making have ethical importance. Schwartz's theory of basic values (STBV) provides a framework for quantifying cultural value orientations and has shown utility for examining values in mental health contexts, including cultural, diagnostic, and therapist-client dynamics. Objective: This study aimed to (1) evaluate whether the STBV can measure value-like constructs within leading LLMs and (2) determine whether LLMs exhibit distinct value-like patterns from humans and each other. Methods: In total, 4 LLMs (Bard, Claude 2, Generative Pretrained Transformer [GPT]-3.5, GPT-4) were anthropomorphized and instructed to complete the Portrait Values Questionnaire--Revised (PVQ-RR) to assess value-like constructs. Their responses over 10 trials were analyzed for reliability and validity. To benchmark the LLMs' value profiles, their results were compared to published data from a diverse sample of 53,472 individuals across 49 nations who had completed the PVQ-RR. This allowed us to assess whether the LLMs diverged from established human value patterns across cultural groups. Value profiles were also compared between models via statistical tests. Results: The PVQ-RR showed good reliability and validity for quantifying value-like infrastructure within the LLMs. However, substantial divergence emerged between the LLMs'value profiles and population data. The models lacked consensus and exhibited distinct motivational biases, reflecting opaque alignment processes. For example, all models prioritized universalism and self-direction, while de-emphasizing achievement, power, and security relative to humans. Successful discriminant analysis differentiated the 4 LLMs' distinct value profiles. Further examination found the biased value profiles strongly predicted the LLMs' responses when presented with mental health dilemmas requiring choosing between opposing values. This provided further validation for the models embedding distinct motivational value-like constructs that shape their decision-making. Conclusions: This study leveraged the STBV to map the motivational value-like infrastructure underpinning leading LLMs. Although the study demonstrated the STBV can effectively characterize value-like infrastructure within LLMs, substantial divergence from human values raises ethical concerns about aligning these models with mental health applications. The biases toward certain cultural value sets pose risks if integrated without proper safeguards. For example, prioritizing universalism could promote unconditional acceptance even when clinically unwise. Furthermore, the differences between the LLMs underscore the need to standardize alignment processes to capture true cultural diversity. Thus, any responsible integration of LLMs into mental health care must account for their embedded biases and motivation mismatches to ensure equitable delivery across diverse populations. Achieving this will require transparency and refinement of alignment techniques to instill comprehensive human values. [ABSTRACT FROM AUTHOR]

Background: Identifying individuals with depressive symptomatology (DS) promptly and effectively is of paramount importance for providing timely treatment. Machine learning models have shown promise in this area; however, studies often fall short in demonstrating the practical benefits of using these models and fail to provide tangible real-world applications. Objective: This study aims to establish a novel methodology for identifying individuals likely to exhibit DS, identify the most influential features in a more explainable way via probabilistic measures, and propose tools that can be used in real-world applications. Methods: The study used 3 data sets: PROACTIVE, the Brazilian National Health Survey (Pesquisa Nacional de Saúde [PNS]) 2013, and PNS 2019, comprising sociodemographic and health-related features. A Bayesian network was used for feature selection. Selected features were then used to train machine learning models to predict DS, operationalized as a score of ≥10 on the 9-item Patient Health Questionnaire. The study also analyzed the impact of varying sensitivity rates on the reduction of screening interviews compared to a random approach. Results: The methodology allows the users to make an informed trade-off among sensitivity, specificity, and a reduction in the number of interviews. At the thresholds of 0.444, 0.412, and 0.472, determined by maximizing the Youden index, the models achieved sensitivities of 0.717, 0.741, and 0.718, and specificities of 0.644, 0.737, and 0.766 for PROACTIVE, PNS 2013, and PNS 2019, respectively. The area under the receiver operating characteristic curve was 0.736, 0.801, and 0.809 for these 3 data sets, respectively. For the PROACTIVE data set, the most influential features identified were postural balance, shortness of breath, and how old people feel they are. In the PNS 2013 data set, the features were the ability to do usual activities, chest pain, sleep problems, and chronic back problems. The PNS 2019 data set shared 3 of the most influential features with the PNS 2013 data set. However, the difference was the replacement of chronic back problems with verbal abuse. It is important to note that the features contained in the PNS data sets differ from those found in the PROACTIVE data set. An empirical analysis demonstrated that using the proposed model led to a potential reduction in screening interviews of up to 52% while maintaining a sensitivity of 0.80. Conclusions: This study developed a novel methodology for identifying individuals with DS, demonstrating the utility of using Bayesian networks to identify the most significant features. Moreover, this approach has the potential to substantially reduce the number of screening interviews while maintaining high sensitivity, thereby facilitating improved early identification and intervention strategies for individuals experiencing DS. [ABSTRACT FROM AUTHOR]

Background: Individuals with developmental disabilities (DD) experience increased rates of emotional and behavioral crises that necessitate assessment and intervention. Psychiatric disorders can contribute to crises; however, screening measures developed for the general population are inadequate for those with DD. Medical conditions can exacerbate crises and merit evaluation. Screening tools using checklist formats, even when designed for DD, are too limited in depth and scope for crisis assessments. The Sources of Distress survey implements a web-based branching logic format to screen for common psychiatric and medical conditions experienced by individuals with DD by querying caregiver knowledge and observations. Objective: This paper aims to (1) describe the initial survey development, (2) report on focus group and expert review processes and findings, and (3) present results from the survey's clinical implementation and evaluation of validity. Methods: Sources of Distress was reviewed by focus groups and clinical experts; this feedback informed survey revisions. The survey was subsequently implemented in clinical settings to augment providers' psychiatric and medical history taking. Informal and formal consults followed the completion of Sources of Distress for a subset of individuals. A records review was performed to identify working diagnoses established during these consults. Results: Focus group members (n=17) expressed positive feedback overall about the survey's content and provided specific recommendations to add categories and items. The survey was completed for 231 individuals with DD in the clinical setting (n=161, 69.7% men and boys; mean age 17.7, SD 10.3; range 2-65 years). Consults were performed for 149 individuals (n=102, 68.5% men and boys; mean age 18.9, SD 10.9 years), generating working diagnoses to compare survey screening results. Sources of Distress accuracy rates were 91% (95% CI 85%-95%) for posttraumatic stress disorder, 87% (95% CI 81%-92%) for anxiety, 87% (95% CI 81%-92%) for episodic expansive mood and bipolar disorder, 82% (95% CI 75%-87%) for psychotic disorder, 79% (95% CI 71%-85%) for unipolar depression, and 76% (95% CI 69%-82%) for attention-deficit/hyperactivity disorder. While no specific survey items or screening algorithm existed for unspecified mood disorder and disruptive mood dysregulation disorder, these conditions were caregiver-reported and working diagnoses for 11.7% (27/231) and 16.8% (25/149) of individuals, respectively. Conclusions: Caregivers described Sources of Distress as an acceptable tool for sharing their knowledge and insights about individuals with DD who present in crisis. As a screening tool, this survey demonstrates good accuracy. However, better differentiation among mood disorders is needed, including the addition of items and screening algorithm for unspecified mood disorder and disruptive mood dysregulation disorder. Additional validation efforts are necessary to include a more geographically diverse population and reevaluate mood disorder differentiation. Future study is merited to investigate the survey's impact on the psychiatric and medical management of distress in individuals with DD. [ABSTRACT FROM AUTHOR]

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Context: Mood and anxiety disorders appear to be overrepresented in adults with cardiovascular diseases (CVDs). These disorders have been associated with poorer biopsychosocial outcomes in this population. Mood and anxiety disorders often co-occur, but the prevalence of this comorbidity and their potential additive effects in patients with CVD remain understudied. Aims: This study aimed to estimate the prevalence and co-occurrence rates of mood and anxiety disorders in the general adult population living with CVD. Associations between mood and anxiety disorder status and sociodemographic characteristics, somatic comorbidities, perceived mental health, and health-care service use were also investigated. Methods: A total of 6,792 adults aged 25 years or older and living with CVD were selected from the 2015-2016 Canadian Community Health Survey. Mood and anxiety disorders were identified based on self-report diagnoses made by a qualified health professional. All other variables were assessed using questionnaires. Results: An estimated 17.7% of the studied population reported having been diagnosed with a mood or anxiety disorder. More precisely, 6.6% reported a mood disorder, 5.5% reported an anxiety disorder, and an additional 5.6% reported both. The presence of mood or anxiety disorders was associated with poorer perceived mental health and higher health-care service use, and these associations were stronger when mood and anxiety co-occurred. Conclusions: Approximately one in six adults with CVD reported suffering from mood or anxiety disorders, and a third of them presented both conditions. This study also suggests that co-occurring anxiety and mood disorders lead to greater vulnerability than either disorder in adults with CVD. [ABSTRACT FROM AUTHOR]

Background: Parental depression increases risk for anxiety and depression in offspring. The transition from adolescence to adulthood is a common risk period for onset of such disorders. However, relatively few studies have considered development of these disorders from childhood to adulthood including multiple assessments during this transition period. Method: Offspring of depressed parents aged 9–17 years at baseline were followed prospectively for 13 years (n = 337). Average length of follow‐up was 16 months between the first and second waves, 13 months between the second and third, and 8 years between the third and fourth. Current (3‐month) psychopathology was assessed at each wave using diagnostic interviews. We derived estimates of 3‐month prevalence, age at first diagnosis, course and comorbidity of disorders. Social functioning in adult life was assessed at the final wave and we assessed how prior and current disorder impacted adult functioning. Results: A quarter of young people met criteria for a mood disorder and a third for anxiety disorder at least once. Mood and anxiety disorder prevalence increased from 4.5% and 15.8% respectively in childhood (9–11 years) to 22.3% and 20.9% respectively by age 23–28. Increased prevalence across the transition from adolescence to adulthood was particularly marked in males, while prevalence increased earlier in adolescence in females. Age at first diagnosis varied widely (mood disorder mean = 16.5 years (range 9–26); anxiety disorder mean = 14.5 years (range 9–28)). Over half (52%) reported functional impairment in early adulthood, 31% harmful alcohol use, and 10% self‐harm or a suicide attempt. Both previous and current mood or anxiety disorder were associated with functional impairment in early adulthood. Conclusions: There is a prolonged risk period for mood and anxiety disorders in this group, with prevalence peaking in early adulthood. This highlights the need for prolonged vigilance and effective targeted interventions in the offspring of depressed parents. [ABSTRACT FROM AUTHOR]

Aims: Job satisfaction plays an important role for the life quality and health of working individuals. While studies have shown that self-reported mental health conditions such as stress, anxiety and depression are associated with job satisfaction, a large population-based study exploring and comparing self-reported physician posed diagnosed conditions and their association with job satisfaction and job tenure is missing. This study addresses the gap along with exploring the impact of the neurotic personality trait and other possible contributing factors. Methods: Sixteen mental health disorders diagnosed by physicians, categorised into four major groups were investigated in relation to employment status (108,711 participants) and in relation to job satisfaction and job tenure (34,808 participants). Analyses were performed using linear regression adjusted for age, sex, townsend deprivation index, body mass index, education, physical activity, work hours and neuroticism. Results: Neurotic and stress disorders, eating disorders and other mental health disorders were strongly associated with lower job satisfaction and shorter job tenure in both unadjusted and adjusted analyses. Neuroticism was strongly linked to job satisfaction but was not associated with job tenure. Conclusions: Study findings clarify the complex relationship of mental health with job satisfaction and job tenure, which is very important to understand in designing measures to improve working life participation of individuals with mental health issues. [ABSTRACT FROM AUTHOR]

La maladie d'Alzheimer et les maladies apparentées entraînent des troubles de l'humeur et des troubles anxieux chez les résidents institutionnalisés. La thérapie par réminiscence a démontré un intérêt dans le traitement de ces symptômes. L'étude pilote randomisée « Réminiscences et Émotions » utilise la réalité virtuelle personnalisée pour diminuer les troubles de l'humeur des résidents. Les objectifs secondaires visent à évaluer l'acceptabilité du dispositif et la qualité de vie des résidents. Monsieur G. présente des troubles cognitifs modérés ainsi que des troubles de l'humeur. Il participe à dix séances de réalité virtuelle personnalisée pendant une période de six semaines. Les variables sont mesurées en amont et à la fin du protocole. Une analyse visuelle des scores illustre les résultats. Le dispositif de réalité virtuelle est accepté et toléré par le participant. Les scores aux échelles de l'humeur (dépression, apathie) et de l'anxiété diminuent. Aucune différence n'apparaît sur l'échelle de qualité de vie. Les interventions génèrent du plaisir et de la vivacité en lien avec l'émergence de souvenirs positifs. Il existe un intérêt de la thérapie par réminiscence en réalité virtuelle pour améliorer l'humeur du participant. Les futurs résultats permettront de conclure sur la méthode et son indication thérapeutique en institution gériatrique. The World Health Organization defined dementia as a syndrome in which there is deterioration in cognitive function beyond what might be expected from the usual consequences of biological aging. Currently, 55 million people live with Alzheimer's in the world. Unfortunately, there isn't any drug treatment to cure the degenerative disease although clinical trials are promising regarding the use of monoclonal antibodies. But, Alzheimer's disease and associated diseases lead to behavioral and psychological symptoms (anxiety, apathy, depression) which can be frequent in nursing homes. In the context of pandemic, these conditions are amplified because of the sanitary restrictions. Since the beginning of the sars-cov2 pandemic, residents have felt alone, sad and more anxious. Nowadays, non-drug interventions are recommended by health organizations for the treatment of behavioral and mood disorders in the elderly with cognitive disorders. Reminiscence therapy is a non drug intervention which has been shown to be effective in the treatment of mood disorders on elderly. Many nursing homes use this non pharmacological treatment for their residents. Some studies take interest in reminiscence and virtual reality. The use of new technologies is innovative in geriatric care and it can be used as a personalized support for reminiscence therapy. The "Bien Vieillir Nice 2030" Project of Nice's University Hospital supports this research on virtual reality and mood disorders in nursing homes/long term care unit. The objective of this study (University Hospital of Nice, CoBTeK France) is to evaluate the effects of personalized virtual reality on reduction of mood disorders in nursing homes residents with minors and moderates neurocognitive disorders. The secondary objectives are to assess the acceptability of the device, the emotional valence and the resident's quality of life. A single case study is presented to illustrate reminiscences and emotions protocol. Participants are randomized into two groups: neutral versus personalized. The neutral videos consist of unknown places like random streets or public gardens while the personalized videos are known places that mattered to the residents. Places are filmed with a camera GoPro Fusion 360°. The healthcare team and families are actively involved in the research protocol. Their help is invaluable in targeting memories related to the resident's life history. A clinical psychologist specializing in gerontology is in charge of the virtual reality sessions. The therapeutic alliance is central to our study. A humanistic method of person-centered approach allows communication with the resident to offer him to participate in the sessions. The sessions always start and end in the same way in order not to cause stress in the resident. The hardware is tested before the protocol starts, for familiarization purpose. Potential side effects related to virtual reality are identified using a cybermalaise questionnaire. The sessions are held in a sitting position for the participant's safety. In this paper, Mr. G, 92 years old benefits from personalized video according to his life story. He has moderate cognitive impairment as well as mood disorders. He received ten virtual reality sessions over a period of six weeks. The exposure time varies between five to ten minutes. We use an Oculus Rift S headset and a computer in partnership with C2Care. Variables were measured before and at the end of the protocol. We performed a visual analysis of the scores. The results indicated a decrease on mood rating scales scores (Geriatric Depression Scale, Apathy Inventory, Neuropsychiatric Inventory and Hamilton Depression Rating scale). The interventions produced pleasure and alertness in connection along with the emergence of positive memories. The headset was well tolerated by the participant, but we did not observe any effect on quality of life. There is an interest in the use of reminiscence therapy using virtual reality to improve participants' mood. Future results will allow us to conclude on the method and on its indication in nursing homes after the inclusion of 30 participants. [ABSTRACT FROM AUTHOR]

Objective: To explore the prevalence of mood disorders and utilization of health services inadults in the Ningxia Hui Autonomous Region, thus providing the scientific basis for disease prevention and control. Methods: Using Composite International Diagnostic Interview with the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-Ⅳ), the first survey on mood disorders was carried out by multiple stage sampling. The Rao-Scott χ² test was used to compare the prevalence rate of mood disorders in populations with different characteristics. Results: The 12-month prevalence rate of mood disorder was 4.0%, while lifetime prevalence rate of mood disorder was 7. 4%. The 12-month prevalence rate was higher in female than male (4.9 vs. 3.3%), and the 12-month prevalence rate in rural area was higher than that in urban area (5.0%vs. 3.0%) (Ps ＜0. 05). The 12-month prevalence rate of bipolar I disorder decreased with age growth (P ＜0. 001), and the 12-month prevalence rate of any mood disorder and major depressive disorder decreased with the increase of education level (Ps ＜0. 05). Among those who met any mood disorder’s criteria, 92. 6% never sought help, 45. 8% of the help secekers didn’t receive any effective help. Conclusion: The prevalence of mood disorder in Ningxia adults is relatively high, but the utilization of mental health services is very low. Females, rural residents, and persons with low education level are the key groups for the prevention of mood disorder. [ABSTRACT FROM AUTHOR]

Objective. To compare the incidence of total knee arthroplasty (TKA) within the first 5 years after knee osteoarthritis (OA) diagnoses between matched groups of individuals with or without comorbid diagnoses of obesity and/or depression. We hypothesized that the greatest incidence of TKA within 5 years of OA diagnosis would be in the cohort of individuals with combined obesity and depression. Methods. The PearlDiver Mariner Ortho157 database was used to identify 4 cohorts of individuals with knee OA based on diagnosis codes that were matched by age, sex, and the Charlson Comorbidity Index: those without diagnoses associated with depression or obesity (Control), those with obesity but not depression (Obesity), those with depression but not obesity (Depression), and those with diagnoses of both obesity and depression (Depression + Obesity). The incidence of subsequent TKA within the first 5 years after the index OA diagnosis were compared between the 4 matched cohorts. Results. Each cohort comprised 274,403 unique individuals (180,563 females, 93,840 males; mean age = 55 [SD 7] years). The incidence of TKA was greatest for the Depression + Obesity group (11.9%) when compared to the Control group (8.3%, P < 0.001; risk ratios [RR] 1.43, 95% CI 1.41-1.45, P < 0.001), Obesity group (10.2%, P < 0.001; RR 1.13, 95% CI 1.11-1.14, P < 0.001), or Depression group (7.8%, P < 0.001; RR 1.53, 95% CI 1.50-1.55, P < 0.001). Conclusion. The incidence of subsequent TKA was greatest for those with the combination of obesity and depression when compared to the control group and those with an individual diagnosis of obesity or depression. [ABSTRACT FROM AUTHOR]

Research conducted on individuals with depression reveals that major depressive disorders (MDDs) coincide with diminished levels of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) in the brain, as well as modifications in the subunit composition of the primary receptors (GABAA receptors) responsible for mediating GABAergic inhibition. Furthermore, there is substantial evidence supporting the significant role of GABA in regulating stress within the brain, which is a pivotal vulnerability factor in mood disorders. GABA is readily available and approved as a food supplement in many countries. Although there is substantial evidence indicating that orally ingested GABA may affect GABA receptors in peripheral tissues, there is comparatively less evidence supporting its direct action within the brain. Emerging evidence highlights that oral GABA intake may exert beneficial effects on the brain and psyche through the gut–brain axis. While GABA enjoys wide consumer acceptance in Eastern Asian markets, with many consumers reporting favorable effects on stress regulation, mood, and sleep, rigorous independent research is still largely lacking. Basic research, coupled with initial clinical findings, makes GABA an intriguing neuro-nutritional compound deserving of clinical studies in individuals with depression and other psychological problems. [ABSTRACT FROM AUTHOR]

IntroductionNon-adherence to treatment recommendations is a significant problem, as it contributes to the progression of the disease and to the exacerbation of distressing symptoms. Failure to cope with the disease and elevated levels of stress, in turn, influence the choice of strategy for coping with a difficult situation, and thus adherence to recommendations.ObjectivesThe purpose of our study was to evaluate the impact of the subjects’ stress coping styles on therapeutic adherence, life satisfaction, disease acceptance and quality of life (QoL) in people with mood disorders.MethodsThis survey-based study included 102 respondents diagnosed with mood disorders, living in the West Pomeranian Voivodeship. It was performed using the sociodemographic questionnaire and standardized tools: The Coping Inventory for Stressful Situations (CISS), The Satisfaction with Life Scale (SWLS), The Short Form-36 (SF-36) Health Survey, The Adherence to Refills and Medication Scale (ARMS), and The Acceptance of Illness Scale (AIS).ResultsSome 47.06% of the respondents suffered from depressive disorders, while 34.31% had depression or mixed anxiety disorder. Patients who made greater use of an emotion-focused style were found to have significantly lower life satisfaction than other patients. Moreover, this style was related to such SF-36 domains as general health, social functioning, role emotional, vitality, and mental health, as well as to physical component summary (PCS) and mental component summary (MCS).ConclusionTreatment non-adherence is a serious challenge in the treatment of patients with mood disorders. Individuals who do not adequately follow treatment recommendations often resort to alternative activities as a mechanism for coping with difficult situations. Patients who predominantly adopt an emotion-oriented coping style tend to experience lower life satisfaction and greater difficulty accepting their condition compared to their peers. Conversely, patients who adopt a task-oriented coping style report better quality of life than those who rely on emotion-oriented coping or alternative activities.

Abstract Objectives To estimate 12‐month prevalence, persistence, severity, and treatment of mental disorders and socio‐demographic correlates in Qatar. Methods We conducted the first national population‐based telephone survey of Arab adults between 2019 and 2022 using the Composite International Diagnostic Interview and estimated 12‐month DSM‐5 mood and anxiety disorders and their persistence (the proportion of lifetime cases who continue to meet 12‐month criteria). Results The 12‐month prevalence of any disorder was 21.1% (10.4% mild, 38.7% moderate, and 50.9% severe) and was associated with: younger age, female, previously married, and with persistence of any disorder. Persistence was 74.7% (64.0% mood and 75.6% anxiety) and was significantly associated with secondary education or lower. Minimally adequate treatment received among those with any 12‐month mental disorder was 10.6% (74.6% in healthcare and 64.6% non‐healthcare sectors). Severity and the number of disorders significantly associated with each other and with treatment received (χ 2 = 7.24, p = 0.027) including adequate treatment within the mental health specialty sector (χ 2 = 21.42, p