Diagnosis Of Depression Research Articles

Stimulus-Response Patterns: The Key to Giving Generalizability to Text-Based Depression Detection Models.

Text content analysis for depression detection using machine learning techniques has become a prominent area of research. However, previous studies focused mainly on analyzing the textual content, neglecting the fundamental factors driving text generation. Consequently, existing models face the challenge of poor generalization to out-of-domain data as they struggle to capture the crucial features of depression. To address this, we propose a novel computational perspective of "stimulus-response patterns" that brings us closer to the essence of clinical diagnosis of depression. Adopting this computational perspective allows us to conceptually unify diverse datasets and generalize this perspective to common datasets in the field. We introduce the Stimulus-Response Patterns-aware Network (SRP-Net) as an exemplary approach within this computational perspective. To assess the performance of the SRP-Net, we constructed a multi-stimulus dataset and conducted experimental evaluations, demonstrating its exceptional cross-stimulus generalizability. Furthermore, we demonstrated the promising performance of SPR-Net in real medical scenarios and conducted an interpretability analysis of the stimulus-response patterns. Our research investigates the critical role of stimulus-response patterns in enhancing the generalizability of text-based depression detection models, which can potentially facilitate data-driven depression detection to approach the diagnostic accuracy of psychiatrists.

Outcomes of cobalt-chrome 3D-printed total talus replacement with and without combined total ankle replacement

BackgroundCollapse of the talus and peri-talar arthritis pose treatment challenges due to the anatomy and location of the talus as a keystone of the foot and ankle. Custom 3D-printed total talus replacement (TTR) and combined total ankle total talus replacement (TATTR) have emerged as treatment options for these pathologies. However, the safety and efficacy of these implants is unknown due to the limited number of cases and short follow-up durations. MethodsThis was a retrospective study to assess surgical outcomes of patients who underwent a TTR and TATTR with or without subtalar fusion. Patient demographics, intraoperative parameters, device related surgical and non-surgical events, imaging and clinical evaluations, and patient reported outcome (PRO) measures were compiled. ResultsA total of 38 patients received a custom 3D-printed implant with mean follow-up time of 22.1 (range: 12–45) months. In this cohort, 7 (18.4 %) required secondary surgery and 3 (7.9 %) required implant removal. Multivariate logistic regression revealed that patient diagnosis of depression was a significant predictor of secondary surgery with an OR 17.50 (p = 0.037). Significant postoperative improvements were observed in the talocalcaneal height (p = 0.005) and talar declination angle (p = 0.013) for the TATTR group. VAS and PROMIS pain interference (PI) scores demonstrated an initial significant improvement in pain, but this improvement did not maintain significance at most recent follow-up. However, there was a significant increase in the PROMIS physical function (PF) scores (p = 0.037) at most recent follow-up. ConclusionThese results demonstrate that TTR and TATTR provide significant improvement in post-operative radiographic foot and ankle alignment and physical function at the two-year timepoint. PRO findings suggest that patients are more active after surgery. Surgeons considering proceeding with either of these procedures should counsel patients about pain and functional outcomes as well as realistic expectations in patients with depression. Level of evidenceLevel 3

Spousal Age Difference and Mental Health by Sex: Korean Survey Results

Purpose: Problems in marital relationships due to age gap between a couple may lead to depression and other mental health issues. However, there is a lack of studies that investigated the association between age gap in couples and mental health. Therefore, this study aimed to identify the relationship between spouse age differences and mental health.Methodology: The data of 7,454 couples from the 2008 and 2012 Korean National Health and Nutrition Examination Surveys were used. Multiple logistic regression analysis was performed.Findings: Women who were ≥10 years older or younger than their husbands displayed poor mental health. Odds ratios (ORs) for women who were ≥10 years younger were 1.72, 1.77, 2.24, and 1.69 for stress perception, depression experiences, depression diagnosis, and suicidal ideation, respectively. Furthermore, in women who were older than their husbands, the ORs for cognition of stress and suicidal ideation were 1.32 and 1.41, respectively.Conclusion: These findings support the development of mental health programs and couples’ education via national promotions and projects. Managing women's mental health in couples with large age gap groups could contribute to family stability and reduce divorce rates.

Lymphomatosis cerebri caused by adult T cell leukemia/lymphoma: a differential diagnosis for depression: a case report

BackgroundPrimary central nervous system lymphoma is rare, and primary central nervous system T cell lymphoma is relatively uncommon, contributing to < 5% of all cases. Lymphomatosis cerebri, a rare subtype of primary central nervous system lymphoma, is characterized by extensive white-matter lesions on magnetic resonance imaging and nonspecific symptoms, such as cognitive decline and depression. Reports of lymphomatosis cerebri in adult T cell leukemia/lymphoma are limited.Case presentationA 49-year-old Japanese man gradually developed insomnia, anorexia, and weight loss over a 2-month period following work-related promotion. Initially diagnosed with depression, his condition rapidly deteriorated with cognitive decline and motor dysfunction. Despite various treatments, his symptoms persisted within a month. Upon admission, the presence of neurological abnormalities suggestive of a central nervous system disorder raised suspicion of a cerebral lesion. Diagnostic tests revealed extensive brain lesions on imaging and the presence of atypical lymphocytes (flower cells) in the cerebrospinal fluid. The patient was diagnosed with lymphomatosis cerebri due to adult T cell leukemia/lymphoma, a rare presentation in the literature. Due to irreversible brainstem damage and poor neurological prognosis, aggressive treatment was not initiated, and the patient died, with an autopsy confirming the diagnosis.ConclusionLymphomatosis cerebri with adult T cell leukemia/lymphoma is very rare. It is crucial to promptly consider lymphomatosis cerebri as a differential diagnosis, particularly in cases of rapid cognitive decline and poor treatment response. Recognition of lymphomatosis cerebri as an important differential diagnosis for cognitive decline, and depression is necessary for timely intervention and management. Further research is required to better understand this unique and rare presentation in adult T cell leukemia/lymphoma.

“Our similarities are different” The relationship between alexithymia and depression

Alexithymia is a multi-faceted personality trait, which is the inability to recognize and describe emotions. It is associated with a multitude of mental health problems, and its implication for the diagnosis and treatment of depression remains unclear. The current study explored the nuances of the relationship between alexithymia and depression in a sample of 210 patients with depression. We assessed alexithymia with the 20-Item Toronto Alexithymia Scale (TAS-20) and depression with the Beck Depression Inventory (BDI-I). The mean TAS-20 score was 57.47 ± 10.63, and the mean BDI-I score was 49.33±9.24. We explored the network structure of alexithymia and depression. Items related to difficulties in identifying, describing, and expressing feelings were prominent in the alexithymia network. Joy, guilt, and self-dislike stand out in the depression network. In our analysis, we were able to show the crescent relationship between depression and alexithymia, with an inflection point at a TAS-20 score of 53. Although the correlation-concordance index was moderate (0.41; 95 %CI: 0.29–0.51), both scales greatly overlap. In the joint network of alexithymia and depression, we could identify bridge (i.e., connecting) items between alexithymia and depression. These were difficulties understanding and relating feelings to physical and body sensations on the alexithymia side, and self-dislike, crying, and somatic concern on the depression side. Taken together, they point to the pivotal role of alexithymia in the somatization/embodiment of emotions and feelings in depression.

Harnessing Data Analytics for Enhanced Understanding and Management of Depression Disorders in Mental Health Care

Depression is a widespread and incapacitating mental health condition that affects millions of people around the world.The integration of data analytics into mental health care presents a transformative opportunity to enhance the understanding, diagnosis, and management of depression. This paper explores the application of data analytics in identifying patterns and trends from diverse data sources such as electronic health records (EHRs) and social media. Through advanced techniques including machine learning, natural language processing (NLP), and predictive modeling, data analytics facilitates early detection of depressive symptoms, the development of personalized treatment plans, and continuous patient monitoring. Additionally, the aggregation and analysis of large- scale data provide valuable insights for public health strategies aimed at reducing the prevalence and impact of depression. This paper highlights the critical role of interdisciplinary collaboration in leveraging data analytics to improve mental health outcomes and underscores the importance of robust safeguards to ensure patient confidentiality and trust. Keywords Data Analytics, Depression, Mental Health, Predictive Modeling, Machine Learning, Natural Language Processing, Electronic Health Records

Using Multimodal Assessments to Reevaluate Depression Designations for Spine Surgery Candidates.

Depression is common in spine surgery candidates and may influence postoperative outcomes. Ecological momentary assessments (EMAs) can overcome limitations of existing depression screening methods (e.g., recall bias, inaccuracy of historical diagnoses) by longitudinally monitoring depression symptoms in daily life. In this study, we compared EMA-based depression assessment with retrospective self-report (a 9-item Patient Health Questionnaire [PHQ-9]) and chart-based depression diagnosis in lumbar spine surgery candidates. We further examined the associations of each depression assessment method with surgical outcomes. Adult patients undergoing lumbar spine surgery (n = 122) completed EMAs quantifying depressive symptoms up to 5 times daily for 3 weeks preoperatively. Correlations (rank-biserial or Spearman) among EMA means, a chart-based depression history, and 1-time preoperative depression surveys (PHQ-9 and Psychache Scale) were analyzed. Confirmatory factor analysis was used to categorize PHQ-9 questions as somatic or non-somatic; subscores were compared with a propensity score-matched general population cohort. The associations of each screening modality with 6-month surgical outcomes (pain, disability, physical function, pain interference) were analyzed with multivariable regression. The association between EMA Depression scores and a depression history was weak (rrb = 0.34 [95% confidence interval (CI), 0.14 to 0.52]). Moderate correlations with EMA-measured depression symptoms were observed for the PHQ-9 (rs = 0.51 [95% CI, 0.37 to 0.63]) and the Psychache Scale (rs = 0.68 [95% CI, 0.57 to 0.76]). Compared with the matched general population cohort, spine surgery candidates endorsed similar non-somatic symptoms but significantly greater somatic symptoms on the PHQ-9. EMA Depression scores had a stronger association with 6-month surgical outcomes than the other depression screening modalities did. A history of depression in the medical record is not a reliable indication of preoperative depression symptom severity. Cross-sectional depression assessments such as PHQ-9 have stronger associations with daily depression symptoms but may conflate somatic depression symptoms with spine-related disability. As an alternative to these methods, mobile health technology and EMAs provide an opportunity to collect real-time, longitudinal data on depression symptom severity, potentially improving prognostic accuracy. Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Seasonality and sun exposure in incidence of major depression, bipolar disorder, and first-time use of antidepressant medication

Introduction Seasonality in depressive and bipolar disorders, are recognized in the ICD-10/11 and DSM-5 diagnostic systems. The existence of a seasonal pattern of hospital diagnosis of major depression, bipolar disorder and prescription of antidepressant medications has not been evaluated in the Danish population. Methods We retrieved date and year for all first-time hospital contacts with depression or bipolar disorder between 1999 and 2019, registered in the Danish National Patient Registry. Depression was defined using the ICD-10 F32-F33 codes, and for bipolar disorder the F30 or F31 codes. Date and year of all first-time purchases of antidepressant medications with ATC codes (N06A) between 1999 and 2021 were retrieved from the Danish National Prescription Registry, containing information on all prescribed drugs dispensed at pharmacies since 1995. Data on sunlight hours from 2012 to 2021 were retrieved from the Danish Metrological Institute. Results Incidences of hospital diagnoses as well as purchases of medication varied with month and season. The monthly variations were larger for antidepressant medication and smallest for bipolar disorder. The multiple linear regression analysis showed that number of first-time diagnoses of depression or bipolar disorder did not correlate with season. For antidepressant medication the number of first-time prescriptions was significantly lower in summer compared to the winter season. Conclusion This study found a seasonal variation of first-time prescriptions of antidepressant medication. We did not find a seasonal variation in first-time hospital diagnoses. Further research looking into depression severity, polarity of bipolar illness episodes, lag-time for sunlight exposure, and specific parts of the yearly photoperiods should be conducted.

Biomarkers in the Diagnosis and Prediction of Medication Response in Depression and the Role of Nutraceuticals.

Depression continues to be a significant and growing public health concern. In clinical practice, it involves a clinical diagnosis. There is currently no defined or agreed upon biomarker/s for depression that can be readily tested. A biomarker is defined as a biological indicator of normal physiological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention that can be objectively measured and evaluated. Thus, as there is no such marker for depression, there is no objective measure of depression in clinical practice. The discovery of such a biomarker/s would greatly assist clinical practice and potentially lead to an earlier diagnosis of depression and therefore treatment. A biomarker for depression may also assist in determining response to medication. This is of particular importance as not all patients prescribed with medication will respond, which is referred to as medication resistance. The advent of pharmacogenomics in recent years holds promise to target treatment in depression, particularly in cases of medication resistance. The role of pharmacogenomics in routine depression management within clinical practice remains to be fully established. Equally so, the use of pharmaceutical grade nutrients known as nutraceuticals in the treatment of depression in the clinical practice setting is largely unknown, albeit frequently self-prescribed by patients. Whether nutraceuticals have a role in not only depression treatment but also in potentially modifying the biomarkers of depression has yet to be proven. The aim of this review is to highlight the potential biomarkers for the diagnosis, prediction, and medication response of depression.

Psychological impact of life events in systemic lupus erythematosus patients - Differences between flares and remission.

Stress has been linked to worsening symptoms and increased disease activity in patients with Systemic lupus erythematosus (SLE). Life-events are individual stress points, and there is conflicting evidence regarding their role in SLE activity and disease perception. Adult SLE patients were recruited for the study. Clinical and laboratory features of SLE were recorded, and previous diagnosis of anxiety or depression were retrieved from patients' electronic charts. Flares were defined by the Systemic Lupus Erythematosus Disease Activity (SLEDAI) flare Index, and flares during the previous year were documented. During a routine visit, they completed validated Portuguese translations of the 10-item Perceived Stress Scale (PSS-10), Hospital Anxiety and Depression Scale (HADS) and Life Experience Survey (LES) for the previous year. A total of 47 female SLE patients were recruited. Ten patients (21.3%) had experienced recent flares. Patients with recent flares reported fewer life events, with lower positive, negative, and total weightings sums compared to those without recent flares. Although 42.2% of patients perceived pathological levels of stress in the previous month, 48.9% had anxiety symptoms, and 34% were at high risk for an anxiety disorder, these psychometric measures did not differ significantly between the recent flare and no-flare groups. There is a high prevalence of pathological levels of stress among SLE patients. SLE patients with recent flares report less psychological impact from life events, both positive and negative, independent of other psychological or pharmacological factors.

Association between pre-hip fracture depression and days at home after fracture and assessing sex differences.

Hip fracture and depression are important public health issues among older adults, but how pre-fracture depression impacts recovery after hip fracture is unknown, especially among males who often experience greater depression severity. Days at home (DAH), or the days spent outside a hospital or healthcare facility, is a novel, patient-centered outcome that can capture meaningful aspects of fracture recovery. How pre-fracture depression impacts DAH after fracture, and related sex differences, remains unclear. Participants included 63,618 Medicare fee-for-service beneficiaries aged 65+ years, with a hospitalization claim for hip fracture surgery between 2010 and 2017. The primary exposure was a diagnosis of depression at hospital admission, and the primary outcome was total DAH over 12 months post-discharge. Longitudinal associations between pre-fracture depression and the count of DAH among beneficiaries were estimated using Poisson regression models after adjustment for covariates; sex-by-depression interactions were also assessed. Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) reflecting relative differences were estimated from these models. Overall, beneficiaries with depression were younger, White females, and spent 11 fewer average DAH compared to counterparts without depression when demographic factors (age and sex) (IRR = 0.91; 95% CI = 0.90, 0.92; p < 0.0001) and social determinants of health (race, Medicaid dual eligibility, and poverty) were adjusted for (IRR = 0.92; 95% CI = 0.91, 0.93; p < 0.0001), but this association attenuated after adjusting for medical complexities (IRR = 0.99; 95% CI = 0.98, 1.01; p = 0.41) and facility and geographical factors (IRR = 1.0037; 95% CI = 0.99, 1.02; p = 0.66). There was no evidence of effect modification by sex. The comorbidity burden of preexisting depression may impact DAH among both male and female Medicare beneficiaries with hip fracture. Results suggest a holistic health approach and secondary prevention of depressive symptoms after hip fracture.

The association of depression and sleep disorders in patients with type 1 diabetes in Taiwan.

The association between depression and sleep disorders in patients with type 1 diabetes mellitus (T1DM) in Taiwan is underexplored. We used a nationwide population-based dataset to evaluate the association of T1DM with these conditions in Taiwan from 2001 to 2019. Patients with T1DM were identified as cases, and 2 control groups were used for comparison: patients with type 2 diabetes mellitus (T2DM) and nondiabetic patients. Age, sex, date of diagnosis, and multiple comorbidities were included and matched using propensity score matching between cases and controls. The primary outcome of this study was to identify new occurrences of the first diagnosis of depression or sleep disorders. After matching, this study included 27,029 T1DM cases, 54,058 T2DM controls, and 108,116 nondiabetic controls. Patients with T1DM exhibited a 1.55-fold higher risk of developing depression (hazard ratio [HR] 1.55, 95% confidence intervals [CI] 1.48-1.61) and a 1.41-fold higher risk of experiencing sleep disorders (HR 1.41, 95% CI 1.37-1.46) compared to nondiabetic controls. Similarly, patients with T2DM displayed elevated risks of both depression (HR 1.39, 95% CI 1.34-1.43) and sleep disorders (HR 1.40, 95% CI 1.37-1.44) relative to non-diabetic controls. When comparing the T1DM and T2DM groups, T1DM patients demonstrated a slightly higher risk of depression (HR 1.11, 95% CI 1.07-1.16) but no significant difference in the risk of sleep disorders compared to T2DM patients. These results were consistent regardless of different ages or sexes. This study demonstrates a significant association between diabetes mellitus and the risk of depression and sleep disorders in a large cohort of Taiwanese patients.

Medical Debt and the Mental Health Treatment Gap Among US Adults

Medical debt is common in the US and may hinder timely access to care for mental disorders. To estimate the prevalence of medical debt among US adults with depression and anxiety and its association with delayed and forgone mental health care. Cross-sectional, nationally representative survey study of US adult participants in the 2022 National Health Interview Survey who had current or lifetime diagnoses of depression or anxiety. Self-reported lifetime clinical diagnoses of depression and anxiety; moderate to severe symptoms of current depression (Patient Health Questionnaire-8 score ≥10) and anxiety (Generalized Anxiety Disorder-7 score ≥10) irrespective of lifetime diagnoses; and past-year medical debt. Self-reported delaying and forgoing mental health care because of cost in the past year. Among 27 651 adults (15 050 [54.4%] female; mean [SD] age, 52.9 [18.4] years), 5186 (18.2%) reported lifetime depression, 1948 (7.3%) reported current depression, 4834 (17.7%) reported lifetime anxiety, and 1689 (6.6%) reported current anxiety. Medical debt was more common among adults with lifetime depression (19.9% vs 8.6%; adjusted prevalence ratio [aPR], 1.97; 95% CI, 1.96-1.98), lifetime anxiety (19.4% vs 8.8%; aPR, 1.91; 95% CI, 1.91-1.92), current depression (27.3% vs 9.4%; aPR, 2.34; 95% CI, 2.34-2.36), and current anxiety (26.2% vs 9.6%; aPR, 2.24; 95% CI, 2.24-2.26) compared with adults without the respective mental disorders. Medical debt was associated with delayed health care among adults with lifetime depression (29.0% vs 11.6%; aPR, 2.68; 95% CI, 2.62-2.74), lifetime anxiety (28.0% vs 11.5%; aPR, 2.45; 95% CI, 2.40-2.50), current depression (36.9% vs 17.4%; aPR, 2.25; 95% CI, 2.13-2.38), and current anxiety (38.4% vs 16.9%; aPR, 2.48; 95% CI, 2.35-2.66) compared with those without these diagnoses. Medical debt was associated with forgone health care among adults with lifetime depression (29.4% vs 10.6%; aPR, 2.66; 95% CI, 2.61-2.71), lifetime anxiety (28.2% vs 10.7%; aPR, 2.63; 95% CI, 2.57-2.68), current depression (38.0% vs 17.2%; aPR, 2.35; 95% CI, 2.23-2.48), and current anxiety (40.8% vs 17.1%; aPR, 2.57; 95% CI, 2.43-2.75) compared with those without the diagnoses. Medical debt is prevalent among adults with depression and anxiety and may contribute to the mental health treatment gap. In the absence of structural reform, new policies are warranted to protect against this financial barrier to mental health care.

Changing Neighborhood Income Deprivation Over Time, Moving in Childhood, and Adult Risk of Depression

Complex biological, socioeconomic, and psychological variables combine to cause mental illnesses, with mounting evidence that early-life experiences are associated with adulthood mental health. To evaluate whether changing neighborhood income deprivation and residential moves during childhood are associated with the risk of receiving a diagnosis of depression in adulthood. This cohort study included the whole population of 1 096 916 people born in Denmark from January 1, 1982, to December 31, 2003, who resided in the country during their first 15 years of life. Individuals were followed up from 15 years of age until either death, emigration, depression diagnosis, or December 31, 2018. Longitudinal data on residential location was obtained by linking all individuals to the Danish longitudinal population register. Statistical analysis was performed from June 2022 to January 2024. Exposures included a neighborhood income deprivation index at place of residence for each year from birth to 15 years of age and a mean income deprivation index for the entire childhood (aged ≤15 years). Residential moves were considered by defining "stayers" as individuals who lived in the same data zone during their entire childhood and "movers" as those who did not. Multilevel survival analysis determined associations between neighborhood-level income deprivation and depression incidence rates after adjustment for individual factors. Results were reported as incidence rate ratios (IRRs) with 95% credible intervals (95% CrIs). The hypotheses were formulated before data collection. A total of 1 096 916 individuals (563 864 male participants [51.4%]) were followed up from 15 years of age. During follow-up, 35 098 individuals (23 728 female participants [67.6%]) received a diagnosis of depression. People living in deprived areas during childhood had an increased risk of depression (IRR, 1.10 [95% CrI, 1.08-1.12]). After full individual-level adjustment, the risk was attenuated (IRR, 1.02 [95% CrI, 1.01-1.04]), indicating an increase of 2% in depression incidence for each 1-SD increase in income deprivation. Moving during childhood, independent of neighborhood deprivation status, was associated with significantly higher rates of depression in adulthood compared with not moving (IRR, 1.61 [95% CrI, 1.52-1.70] for 2 or more moves after full adjustment). This study suggests that, rather than just high or changing neighborhood income deprivation trajectories in childhood being associated with adulthood depression, a settled home environment in childhood may have a protective association against depression. Policies that enable and support settled childhoods should be promoted.

Applying natural language processing to patient messages to identify depression concerns in cancer patients.

This study aims to explore and develop tools for early identification of depression concerns among cancer patients by leveraging the novel data source of messages sent through a secure patient portal. We developed classifiers based on logistic regression (LR), support vector machines (SVMs), and 2 Bidirectional Encoder Representations from Transformers (BERT) models (original and Reddit-pretrained) on 6600 patient messages from a cancer center (2009-2022), annotated by a panel of healthcare professionals. Performance was compared using AUROC scores, and model fairness and explainability were examined. We also examined correlations between model predictions and depression diagnosis and treatment. BERT and RedditBERT attained AUROC scores of 0.88 and 0.86, respectively, compared to 0.79 for LR and 0.83 for SVM. BERT showed bigger differences in performance across sex, race, and ethnicity than RedditBERT. Patients who sent messages classified as concerning had a higher chance of receiving a depression diagnosis, a prescription for antidepressants, or a referral to the psycho-oncologist. Explanations from BERT and RedditBERT differed, with no clear preference from annotators. We show the potential of BERT and RedditBERT in identifying depression concerns in messages from cancer patients. Performance disparities across demographic groups highlight the need for careful consideration of potential biases. Further research is needed to address biases, evaluate real-world impacts, and ensure responsible integration into clinical settings. This work represents a significant methodological advancement in the early identification of depression concerns among cancer patients. Our work contributes to a route to reduce clinical burden while enhancing overall patient care, leveraging BERT-based models.

Detecting depression severity using weighted random forest and oxidative stress biomarkers

This study employs machine learning to detect the severity of major depressive disorder (MDD) through binary and multiclass classifications. We compared models that used only biomarkers of oxidative stress with those that incorporate sociodemographic and health-related factors. Data collected from 830 participants, based on the Patient Health Questionnaire (PHQ-9) score, inform our analysis. In binary classification, the Random Forest (RF) classifier achieved the highest Area Under the Curve (AUC) of 0.84 when all features were included. In multiclass classification, the AUC improved from 0.84 with only oxidative stress biomarkers to 0.88 when all characteristics were included. To address data imbalance, weighted classifiers, and Synthetic Minority Over-sampling Technique (SMOTE) approaches were applied. Weighted random forest (WRF) improved multiclass classification, achieving an AUC of 0.91. Statistical tests, including the Friedman test and the Conover post-hoc test, confirmed significant differences between model performances, with WRF using all features outperforming others. Feature importance analysis shows that oxidative stress biomarkers, particularly GSH, are top ranked among all features. Clinicians can leverage the results of this study to improve their decision-making processes by incorporating oxidative stress biomarkers in addition to the standard criteria for depression diagnosis.

Age of onset of major depressive episode and association with lifetime psychiatric disorders, health-related quality of life and impact of gender: A cross sectional and retrospective cohort study

ObjectiveTo assess the long-term impact of the age of onset (AOO) of the first major depressive episode (MDE) according to 3 age groups and considering gender. MethodsData were extracted from NESARC III, a representative U.S. sample. We included 8053 participants with an MDE history in a cross-sectional and retrospective cohort study. We defined 3 AOO groups: childhood-onset (< 13 yo), adolescence-onset (13–18 yo), and adult-onset (> 18 yo). We compared sociodemographic characteristics, lifetime psychiatric disorders per DSM-5 criteria, and health-related quality of life (HRQOL) in each group and performed gender-stratified analyses. ResultsPrevalence of childhood-onset MDE was 10.03 %, adolescence-onset was 14.12 %, and adult-onset was 75.85 %. Suicide attempts (AOR = 3.61; 95 % CI 2.90–4.50), anxiety disorders (AOR = 1.92; 95 % CI 1.62–2.27), and personality disorders (AOR = 3.08; 95 % CI 2.56–3.71) were more frequent in the childhood-onset than in the adult-onset one. Adolescence-onset group showed similar results. Physical Disability scale (p < 0.001) and Mental Disability scale (p < 0.001) were significantly lower in the childhood-onset group. Results were more nuanced in the adolescence-onset group. Women in childhood-onset and adolescence-onset groups had poorer outcomes than the adult-onset group. Differences were less pronounced in men. LimitationsRecall and classification biases inherent to survey design. ConclusionIndividuals, particularly women, who experienced their first MDE during childhood or adolescence exhibit higher lifetime psychiatric disorder prevalence and poorer HRQOL than those with adult-onset MDE. These findings highlight the importance of preventive measures, early diagnosis, and treatment of youth depression.

Association between fear of falling and mortality in middle-aged and older adults: A systematic review and meta-analysis

BackgroundFear of falling (FOF) has emerged as a significant public health issue, contributing to excess disability among middle-aged and older adults. The association between FOF and mortality remains unclear. MethodsProminent electronic databases (PubMed, Web of Science, the Cochrane Library, Embase, CINHAL, PsycINFO, Scopus, China National Knowledge Infrastructure, China Biology Medicine disc, and Wanfang Database) were searched from inception until October 21, 2023 (data updated on June 9, 2024), for cohort or longitudinal studies investigating the association between FOF and mortality. The heterogeneity between studies was quantitatively assessed using I2. A fixed-effect model calculated the pooled effect size. ResultsA total of seven cohort studies, including 27,714 participants, were analyzed in this systematic review and meta-analysis. The meta-analysis results demonstrated a positive association between FOF and mortality, with a significant increase in the risk of mortality for those with FOF (hazard ratio [HR]:1.29, 95 % confidence interval [CI]: 1.19–1.41, p < 0.05). Subgroup analysis indicated that age, male sex, clinical diagnosis of depression, number of chronic diseases, activity restriction due to FOF, and FOF levels were associated with mortality. ConclusionsFOF and mortality have a positive association, which needs to be confirmed by further prospective studies with large samples and long-term follow-up to provide evidence for clinicians to intervene in FOF to reduce mortality in middle-aged and older adults.

Childhood trauma as a mediator between autistic traits and depression: evidence from the ALSPAC birth cohort.

Autism and autistic traits have been associated with greater risk of childhood trauma and adulthood psychopathology. However, the role that childhood trauma plays in the association between autism, autistic traits and depression in adulthood is poorly understood. We used a UK-based birth cohort with phenotype and genotype data on autism, autistic traits, childhood trauma and depression in up to 9,659 individuals prospectively followed up from birth until age 28 years. Using mixed-effects growth-curve models, we assessed trajectories of depression symptoms over time according to the presence or absence of autism/ autistic traits and explored whether these differed by trauma exposure. We further investigated the association between autism/ autistic traits and depression in adulthood using confounder-adjusted logistic regression models and undertook mediation analyses to investigate the relationship with childhood trauma. All autism variables demonstrated increased depressive symptom trajectories between ages 10-28 years. Social communication difficulties (SCDs) were the most strongly associated with a depression diagnosis in adulthood (age 24 OR= 2.15; 95%CIs: 1.22-3.76). Trauma and autistic traits combined to further increase depression symptom scores. Mediation analyses provided evidence for direct pathways between autistic traits and increased risk of depression alongside indirect pathways through increased risk of trauma. Autism/ autistic traits increase the odds of experiencing childhood trauma and of being diagnosed with depression at age 18 and 24. Depressive symptom trajectories emergent in childhood persist into adulthood. The combined effect of SCDs and childhood trauma is greater than the individual exposures, suggesting worse depression symptomatology following trauma in individuals with SCDs.

Depression: Symptoms, Causes, and Effective Coping Strategies

Depression is not merely feeling sad; it encompasses a range of symptoms that can affect various aspects of life. The exact cause of depression isn't fully understood, even though biological factors like imbalance in neurotransmitters such as serotonin and dopamine play a significant role. Psychological factors, such as trauma, chronic stress, low self-esteem, and negative thinking patterns, can contribute to the development and exacerbation of depression. Diagnosis of depression involves assessing persistent feelings of sadness or loss of interest in daily activities, along with other accompanying symptoms, lasting for at least two weeks. Depression is a treatable condition, which may include psychotherapy (such as cognitive-behavioral therapy or interpersonal therapy), medication (such as antidepressants), and lifestyle changes.