UNASSIGNED: Many existing measures of prejudiced attitudes toward people with mental illness have conceptual, theoretical, and psychometric problems. The recently created Prejudice toward People with Mental Illness (PPMI) scale has addressed many of these limitations, but prejudice toward people with different mental disorders may be unique and require further exploration. This study aimed to facilitate this exploration by adapting the PPMI to focus on schizophrenia and depression, and investigate the structure, distinctiveness, and the nomological network of prejudice toward people with these mental disorders.
UNASSIGNED: We adapted the original 28-item PPMI scale to create the Prejudice toward People with Schizophrenia (PPS) and Prejudice toward People with Depression (PPD) scales. There were 406 participants from the general population, who completed these scales and related measures.
UNASSIGNED: The original 4-factor structure (fear/avoidance, unpredictability, authoritarianism, and malevolence) was supported for each scale. Participants expressed the highest levels of prejudice toward people with schizophrenia, followed by prejudice toward people with mental illness, and lastly by prejudice toward people with depression. Analyses supported the proposed nomological network of prejudice, which involves theoretical antecedents of social dominance orientation, right-wing authoritarianism, empathy, personality traits, disgust sensitivity, and prior contact.
UNASSIGNED: This research provides evidence for the validity and psychometric properties of the PPMI, PPS, and PPD scales, expanding our understanding of antecedents to prejudice toward people with different mental disorders. This research also shows that we gain more insight into prejudice when we use measures targeting specific disorders rather than mental illness in general.

BACKGROUND: The present longitudinal investigation had two major goals. First, we intended to clarify whether depressed patients are characterized by impairments of emotional awareness for the self and the other during acute illness and whether these impairments diminish in the course of an inpatient psychiatric treatment program. Previous research based on the performance measure Levels of Emotional Awareness Scale (LEAS) provided inconsistent findings concerning emotional self-awareness in clinical depression. Second, we investigated whether cognitive and affective empathic abilities change from acute illness to recovery in depressed patients.
METHODS: Fifty-eight depressed patients were tested on admission and after 6-8 weeks of inpatient psychiatric treatment. A sample of fifty-three healthy individuals were also examined twice at an interval of 6-8 weeks. The LEAS and the Interpersonal Reactivity Index (IRI) were administered to assess emotional awareness and empathic abilities. Written texts were digitalized and then analyzed using the electronic scoring program geLEAS, the German electronic Levels of Emotional Awareness Scale.
RESULTS: Depressed patients reported more depressive symptoms than healthy controls and less severe depressive symptomatology at time 2 compared to time 1. Independent of time, depressed individuals tended to show lower geLEAS self scores and had lower geLEAS other scores than healthy individuals. Depressed patients showed higher personal distress scores than healthy individuals at both measurement times. No group differences were observed for the cognitive empathy scales of the IRI (perspective taking and fantasy) and empathic concern, but empathic concern decreased significantly in depressed patients from time 1 to time 2. Empathic abilities as assessed by the IRI were not significantly correlated with emotional awareness for others, neither in the whole sample, nor in the patient and control subsample.
CONCLUSIONS: Depressed patients seem to be characterized by impairments in emotional awareness of others during acute illness and recovery, but they also tend to show deficits in emotional self-awareness compared to healthy individuals. Self-reported cognitive empathic abilities seem to be at normal levels in depressed patients, but their heightened self-focused affective empathy may represent a vulnerability factor for depressive disorders.

UNASSIGNED: Depression is a leading cause of disability and the conventional management has several limitations. Recent studies demonstrated the benefits of yoga in psychological disorders.
UNASSIGNED: To evaluate the efficacy of the Integrated Yoga Module (IYM) to standard care with added yogic education on lifestyle modification (YELM) in patients with clinical depression.
UNASSIGNED: A PROBE trial was conducted at a single tertiary care hospital in India. Adults aged 18 to 64 with clinical depression were randomized to either an IYM or an active control group using a computer-generated mixed block randomization sequence. Both groups received YELM in addition to standard care and the intervention group practiced IYM, for 8 weeks. The primary outcome was the reduction in depression symptoms assessed using the Beck Depression Inventory (BDI-II), and secondary outcomes involved self-compassion, brief resilience, positive and negative experiences, and quality of life, evaluated at 8 weeks.
UNASSIGNED: The mean ± SD age of participants was 32.2 ± 10.0 and 54.3% were females. The IYM group showed statistically significant improvements in BDI-II scores β = -6.7 (95% CI [-10.8, -2.5]; p = .001), resilience β = 0.4 (95% CI [0.02, 0.80]; p = .037), physical health domain of WHOQOL - BREF β = 10.1 (95% CI [0.7, 19.5]; p = .035) and negative emotions (SPANE-N) β = 2.8 (95% CI [0.1, 5.4]; p = .037). However, no significant differences were found in SCS-SF β = -0.3 (95% CI [-0.7, 0.0]; p = .053).
UNASSIGNED: IYM as an adjunct is superior to conventional medical management in reducing symptoms and improving positive psychological resources in clinical depression.

UNASSIGNED: Depression is a prevalent disorder worldwide, with potentially severe implications. It contributes significantly to an increased risk of diseases associated with multiple risk factors. Early accurate diagnosis of depressive symptoms is a critical first step toward management, intervention, and prevention. Various nutritional and dietary compounds have been suggested to be involved in the onset, maintenance, and severity of depressive disorders. Despite the challenges to better understanding the association between nutritional risk factors and the occurrence of depression, assessing the interplay of these markers through supervised machine learning remains to be fully explored.
UNASSIGNED: This study aimed to determine the ability of machine learning-based decision support methods to identify the presence of depression using publicly available health data from the Korean National Health and Nutrition Examination Survey. Two exploration techniques, namely, uniform manifold approximation and projection and Pearson correlation, were performed for explanatory analysis among datasets. A grid search optimization with cross-validation was performed to fine-tune the models for classifying depression with the highest accuracy. Several performance measures, including accuracy, precision, recall, F1 score, confusion matrix, areas under the precision-recall and receiver operating characteristic curves, and calibration plot, were used to compare classifier performances. We further investigated the importance of the features provided: visualized interpretation using ELI5, partial dependence plots, and local interpretable using model-agnostic explanations and Shapley additive explanation for the prediction at both the population and individual levels.
UNASSIGNED: The best model achieved an accuracy of 86.18% for XGBoost and an area under the curve of 84.96% for the random forest model in original dataset and the XGBoost algorithm with an accuracy of 86.02% and an area under the curve of 85.34% in the quantile-based dataset. The explainable results revealed a complementary observation of the relative changes in feature values, and, thus, the importance of emergent depression risks could be identified.
UNASSIGNED: The strength of our approach is the large sample size used for training with a fine-tuned model. The machine learning-based analysis showed that the hyper-tuned model has empirically higher accuracy in classifying patients with depressive disorder, as evidenced by the set of interpretable experiments, and can be an effective solution for disease control.

UNASSIGNED: Depression is a commonly prevailing condition that goes undetected in clinical settings. Both abdominal obesity and periodontal disease have a bearing on mental health and have an impact on the quality of life.
UNASSIGNED: To assess the level of clinical depression in abdominally obese subjects with periodontal disease.
UNASSIGNED: Two hundred and ten subjects with a mean age of 37.45 ± 9.59 years (males = 117; females = 93) were grouped as per their abdominal obesity and periodontal status and assessed for their clinical depression levels (mental health) using the Centre for Epidemiologic Studies-Depression Scale (CES-D). Collected data were analysed.
UNASSIGNED: The clinical depression score significantly varied in subjects with different periodontal status in both non-obese (F (2,102) = 113.66, P < 0.0001) and abdominally obese subjects (F (2,102) = 132.04, P < 0.001). Significantly higher depression score was demonstrated in healthy (P < 0.001), gingivitis (P < 0.001), and periodontitis (P < 0.001) groups in abdominally obese subjects.
UNASSIGNED: Clinical depression is significantly associated with abdominal obesity and periodontal disease in subjects with abdominal obesity and severe periodontal disease demonstrating higher depression scores.

BACKGROUND: Depression (Major Depressive Disorder) is one of the most common mental illnesses. According to the World Health Organization, more than 300 million people in the world are affected. A first depressive episode can be solved by a spontaneous remission within 6 to 12 months. It has been shown that depression affects speech production and facial expressions. Although numerous studies are proposed in the literature for depression recognition using audiovisual cues, depression relapse using audiovisual cues has not been studied in the literature.
METHODS: In this paper, we propose a deep learning-based approach for depression recognition and depression relapse prediction using audiovisual data. For more versatility and reusability, the proposed approach is based on a Model of Normality inspired framework where we define depression relapse by the closeness of the audiovisual patterns of a subject after a symptom-free period to the audiovisual patterns of depressed subjects. A model of Normality is an anomaly detection distance-based approach that computes a distance of normality between the deep audiovisual encoding of a test sample and a learned representation from audiovisual encodings of anomaly-free data.
RESULTS: The proposed approach shows a very promising results with an accuracy of 87.4% and a F1-score of 82.3% for relapse/depression prediction using a Leave-One-Subject-Out training strategy on the DAIC-Woz dataset.
CONCLUSIONS: The proposed model of normality-based framework is accurate in detecting depression and in predicting depression relapse. A prospective monitoring system is proposed for assisting depressed patients. The proposed framework is easily extensible and others modalities will be integrated in future works.

BACKGROUND: The objectives of this study were: 1) estimate the impact and severity of both diagnosed and undiagnosed depression in the general US population 2) explore the demographics of depression based on its common symptoms 3) interpret Patient Health Questionnaire-9 (PHQ-9) scores to improve accuracy in identifying individuals with depression.
METHODS:  A random sample of 200 individuals was selected from a general US adult population to complete the Patient Health Questionnaire-9 (PHQ-9).
RESULTS: Only 39.4% of respondents indicated that they had a formal diagnosis of depression. In contrast, 53% of participants have considered seeking help from a mental health professional. More importantly, 31.45% of respondents without a formal diagnosis had a PHQ-9 score of over 10 (moderate to severe depression).
CONCLUSIONS: The results indicate that undiagnosed depression exists in the US population and suggest that access to mental health services needs to expand across the nation.

The optimal intensity of physical activity for alleviating depression in middle-aged and older adults remains unclear. The World Health Organization (WHO) physical activity guidelines recommend adults and older adults to accumulate at least 150-300 minutes of moderate or 75-150 minutes of vigorous aerobic-type physical activity weekly or an equivalent combination of both for health benefits including reduced risk of depression. This parallel, assessor-blinded, pilot randomized controlled trial preliminarily compared the effectiveness of the minimal volume of aerobic-type physical activity at different intensities as recommended by WHO (150 minutes of moderate walking exercise and 75 minutes of vigorous walking exercise weekly) on alleviating depression in middle-aged and older adults. Thirty-five participants were randomized to the control group (CON), moderate walking exercise group (MOD), or vigorous walking exercise group (VIG). The exercise frequency was three times a week and the intervention duration was 12 weeks. The primary outcome was the severity of depression assessed by Beck Depression Inventory. Secondary outcomes included severity of anxiety, sleep quality, quality of life, and cardiorespiratory fitness. Thirty participants completed the study (CON: n = 10, MOD: n = 10, VIG: n = 10). Participants in both MOD and VIG had significantly decreased depression severity after the intervention compared to CON (both p < 0.001). There was no significant difference between MOD and VIG (p = 0.92). Both MOD and VIG interventions also mitigated anxiety severity, improved quality of life and cardiorespiratory fitness. The minimum volume of walking exercise at either moderate or vigorous intensity was found to alleviate depression in middle-aged and older adults.Trial registration: ClinicalTrials.gov identifier: NCT04403373.HighlightsThe 12-week 150-minute moderate walking exercise and 75-minute vigorous walking exercise (the minimal weekly volumes of aerobic-type physical activity recommended by WHO guidelines) similarly reduced the severity of depression in middle-aged and older adults.The 12-week walking exercise interventions significantly reduced anxiety severity concomitant with improved quality of life and cardiorespiratory fitness in middle-aged and older adults with depression.

BACKGROUND: Periprosthetic joint infection (PJI) is a devastating complication after total joint arthroplasty. Patients undergoing revision for PJI may experience psychological distress and symptoms of depression, both of which are linked to poor postoperative outcomes. We, therefore, aim to identify the prevalence of depression and depressive symptoms in patients before treatment for PJI and their link to functional outcomes.
METHODS: Patients undergoing either debridement with implant retention (DAIR) or 2-stage exchange for PJI with minimum 1-year follow-up were retrospectively reviewed. The 2-stage (n = 37) and single-stage (n = 39) patients that met inclusion criteria were matched based off age (±5 years), gender, and body mass index (±5) to patients undergoing aseptic revisions. Outcomes evaluated included a preoperative diagnosis of clinical depression and preoperative and postoperative Veterans RAND 12 Item Health Survey mental component score and physical component score.
RESULTS: Compared to matched controls, the prevalence of depressive symptoms was significantly greater in patients undergoing 2-stage exchange preoperatively (40.5% vs 10.8%, P < .01) but not postoperatively (21.6% vs 10.8%, P = .20). Patients undergoing DAIR with either preoperative depressive symptoms (31.3 vs 40.9, P = .05) or a preoperative diagnosis of depression (27.7 vs 43.1, P < .01) had significantly lower physical component scores postoperatively.
CONCLUSIONS: Patients undergoing 2-stage exchange for PJI have a four times higher prevalence of preoperative depressive symptoms than patients undergoing aseptic revision. Patients undergoing DAIR with depression or preoperative depressive symptoms have lower functional scores postoperatively. Orthopedic surgeon screening of PJI patients with referral for treatment of depression may help improve outcomes postoperatively.

According to the Center for Disease Control (CDC), 3.2% of children aged 3-17 years have been diagnosed with depression. Many genetic conditions predispose children and adolescents to various mental health problems. Turner syndrome is a common sporadic genetic condition in females with medical issues, developmental delays, and psychiatric comorbidities. There is limited literature about adolescents with a late diagnosis of Turner syndrome and struggles with affective psychopathology. The early recognition and understanding of its unique genetics, neurobiology, and specific clinical manifestations are critical for addressing the needs of these patients.