Validation and measurement invariance of the Occupational Depression Inventory in South Africa.

This study aimed to validate the recently developed Occupational Depression Inventory (ODI) in South Africa. A total of 327 employees (60% female) participated in the study. Bifactor exploratory structural equation modeling analysis indicated that the ODI can be considered essentially unidimensional. The ODI displayed strong scalability (e.g., scale-level H = 0.657). No monotonicity violation was detected. The reliability of the instrument, as indexed by Cronbach's alpha, McDonald's omega-total, Guttman's λ2, and the Molenaar-Sijtsma statistic, was highly satisfactory. Measurement invariance was observed across age groups, sexes, and ethnicities, as well as between our sample and the ODI's original validation sample. As expected, the ODI showed both a degree of convergent validity and a degree of discriminant validity vis-à-vis a measure of "cause-neutral" depressive symptoms. Moreover, the ODI manifested substantial associations, in the anticipated directions, with measures of work engagement, job satisfaction, and life satisfaction. Overall, the ODI exhibited excellent structural and psychometric properties within the South African context. Consistent with previous research, this study suggests that occupational health specialists can confidently rely on the ODI to investigate job-related distress.

Maternal depression trajectories and child BMI in a multi-ethnic sample: a latent growth modeling analysis.

BACKGROUND: Perinatal (antenatal and postpartum) depression impacts approximately 12% of mothers. Perinatal depression can impact everyday functioning for mothers, and the relationship with, and development of, their children. The purpose of this study was to investigate depression trajectories from the antenatal period through 54-months postpartum and associations with child body mass index at 54-months postpartum. METHODS: This study applied latent growth modeling to the Growing Up in New Zealand study, which is a longitudinal pregnancy cohort study that provides nationally representative-level data, to investigate associations between depression at three time points (antenatal, 9-months postpartum, 54-months postpartum) and child body mass index at 54-months (n=4897). RESULTS: The average slope of depression for this sample is low and decreases over time. When child BMI was added to the model as an outcome variable, both antenatal depression (B=.25, p<.01), and the rate of change of depression across the perinatal and postpartum periods (B=.09, p<.01) were associated with child BMI at 54-months postpartum. After controlling for sociodemographic characteristics, antenatal depression, but not the slope of depression, remained significantly associated with child BMI (B=.05, p<.05). When controlling for maternal pre-pregnancy BMI the effect of antenatal depression on child BMI at 54-months was entirely attenuated (χ2 (9) = 39.60, p < .05, SRMR = 0.01, CFI = .99, RMSEA = 0.03, BIC=53213). CONCLUSIONS: Our findings align with the Developmental Origins of Health and Disease theory and imply that both the physical and mental health of mothers during pregnancy may be important indicators of child growth and development outcomes. Early intervention directed towards women who have even mild depression scores during pregnancy may promote healthy child development outcomes. Additionally, given the heterogeneity of depressive symptoms over time seen in this study, multiple assessment periods across the postpartum period may be valuable to adequately address and support maternal mental health.

Usefulness of Hamilton rating scale for depression subset scales and full versions for electroconvulsive therapy.

OBJECTIVES: We investigated the predictive value of subset scales and full versions of the Hamilton Rating Scale for Depression (HAMD) for therapeutic outcomes in ECT. METHODS: This secondary analysis of patients with major depression (N = 136; 63% female; age = 56.7 [SD = 14.8]) from the EFFECT-Dep trial (NCT01907217) examined the predictive value of Evans-6, Toronto-7, Gibbons-8 and Maier-Philip 6 HAMD subset scales and three 'full' versions (HAMD-17, HAMD-21 and HAMD-24) on therapeutic outcomes. We also examined early improvement on subset scales and full versions as predictors of response and remission and explored predictive abilities of individual HAMD-24 items. RESULTS: The subset scales and full scales lacked sufficient predictive ability for response and remission. Receiver operating characteristic curves identified a lack of discriminative capacity of HAMD subset scales and full versions at baseline to predict response and remission. Only the Maier-Philip-6 was significantly associated with percentage reduction in HAMD-24 scores from baseline to end of ECT course. Early improvement on most of the subset scales and full versions was a sensitive and specific predictor of response and remission. Four of the HAMD-24 items were significantly associated with response and one with remission. CONCLUSIONS: Limited utility of the HAMD subset scales and full versions in this context highlight a need for more tailored depression rating scales for ECT.

Identifying subtypes of depression in clinician-annotated text: a retrospective cohort study.

Current criteria for depression are imprecise and do not accurately characterize its distinct clinical presentations. As a result, its diagnosis lacks clinical utility in both treatment and research settings. Data-driven efforts to refine criteria have typically focused on a limited set of symptoms that do not reflect the disorder's heterogeneity. By contrast, clinicians often write about patients in depth, creating descriptions that may better characterize depression. However, clinical text is not commonly used to this end. Here we show that clinically relevant depressive subtypes can be derived from unstructured electronic health records. Five subtypes were identified amongst 18,314 patients with depression treated at a large mental healthcare provider by using unsupervised machine learning: severe-typical, psychotic, mild-typical, agitated, and anergic-apathetic. Subtypes were used to place patients in groups for validation; groups were found to be associated with future outcomes and characteristics that were consistent with the subtypes. These associations suggest that these categorizations are actionable due to their validity with respect to disease prognosis. Moreover, they were derived with automated techniques that might theoretically be widely implemented, allowing for future analyses in more varied populations and settings. Additional research, especially with respect to treatment response, may prove useful in further evaluation.

Trajectories of depression in sepsis survivors: an observational cohort study.

BACKGROUND: Advances in critical care medicine have led to a growing number of critical illness survivors. A considerable part of them suffers from long-term sequelae, also known as post-intensive care syndrome. Among these, depressive symptoms are frequently observed. Depressive symptom trajectories and associated factors of critical illness survivors have rarely been investigated. Study objective was to explore and compare different trajectories of depressive symptoms in sepsis survivors over 1 year after discharge from ICU. METHODS: Data of a randomized controlled trial on long-term post-sepsis care were analyzed post hoc. Depressive symptoms were collected at 1, 6 and 12 months post-ICU discharge using the Major Depression Inventory (MDI), among others. Statistical analyses comprised descriptive analysis, univariate and multivariate, linear and logistic regression models and Growth Mixture Modeling. RESULTS: A total of 224 patients were included into this analysis. We identified three latent classes of depressive symptom trajectories: Over the course of 1 year, 152 patients recovered from mild symptoms, 27 patients showed severe persistent symptoms, and 45 patients recovered from severe symptoms. MDI sum scores significantly differed between the three classes of depressive symptom trajectories at 1 and 6 months after ICU discharge (p < 0.024 and p < 0.001, respectively). Compared with other classes, patients with the mild recovered trajectory showed lower levels of chronic pain (median sum score of 43.3 vs. 60.0/53.3 on the Graded Chronic Pain Scale, p < 0.010) and posttraumatic stress (4.6% with a sum score of ≥ 35 on the Posttraumatic Stress Scale 10 vs. 48.1%/33.3%, p < 0.003); and higher levels of health-related quality of life (HRQOL) using the Short Form-36 scale within 1 month after ICU discharge (p < 0.035). CONCLUSIONS: In the first year after discharge from ICU, sepsis survivors showed three different trajectories of depressive symptoms. Course and severity of depressive symptoms were associated with chronic pain, posttraumatic stress and reduced HRQOL at discharge from ICU. Regular screening of sepsis survivors on symptoms of depression, chronic pain and posttraumatic stress within 1 year after ICU may be considered. Trial registration ISRCTN, ISRCTN 61744782. Registered April 19, 2011-Retrospectively registered, http://www.isrctn.com/ISRCTN61744782 .

Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach.

Diagnostic heterogeneity within and across psychotic and affective disorders challenges accurate treatment selection, particularly in the early stages. Delineation of shared and distinct illness features at the phenotypic and brain levels may inform the development of more precise differential diagnostic tools. We aimed to identify prototypes of depression and psychosis to investigate their heterogeneity, with common, comorbid transdiagnostic symptoms. Analyzing clinical/neurocognitive and grey matter volume (GMV) data from the PRONIA database, we generated prototypic models of recent-onset depression (ROD) vs. recent-onset psychosis (ROP) by training support-vector machines to separate patients with ROD from patients with ROP, who were selected for absent comorbid features (pure groups). Then, models were applied to patients with comorbidity, ie, ROP with depressive symptoms (ROP+D) and ROD participants with sub-threshold psychosis-like features (ROD+P), to measure their positions within the affective-psychotic continuum. All models were independently validated in a replication sample. Comorbid patients were positioned between pure groups, with ROP+D patients being more frequently classified as ROD compared to pure ROP patients (clinical/neurocognitive model: χ2 = 14.874; P < .001; GMV model: χ2 = 4.933; P = .026). ROD+P patient classification did not differ from ROD (clinical/neurocognitive model: χ2 = 1.956; P = 0.162; GMV model: χ2 = 0.005; P = .943). Clinical/neurocognitive and neuroanatomical models demonstrated separability of prototypic depression from psychosis. The shift of comorbid patients toward the depression prototype, observed at the clinical and biological levels, suggests that psychosis with affective comorbidity aligns more strongly to depressive rather than psychotic disease processes. Future studies should assess how these quantitative measures of comorbidity predict outcomes and individual responses to stratified therapeutic interventions.

Determinants of anxiety and depression among pheochromocytoma patients: A case-control study.

ABSTRACT: Phaeochromocytomas are catecholamine-producing neuroendocrine tumors that may manifest in many ways, specifically as sustained or paroxysmal hypertension. Data, including data from mental status screening, were prospectively collected from suspected patients. The Hospital Anxiety and Depression Scale was used as a screening tool to identify abnormal mental status. Results showed phaeochromocytoma patients were more likely to experience anxiety and depression. For future phaeochromocytoma treatment, early screening for anxiety and depression should be recommended.

The Psychopathology and Neuroanatomical Markers of Depression in Early Psychosis.

Depression frequently occurs in first-episode psychosis (FEP) and predicts longer-term negative outcomes. It is possible that this depression is seen primarily in a distinct subgroup, which if identified could allow targeted treatments. We hypothesize that patients with recent-onset psychosis (ROP) and comorbid depression would be identifiable by symptoms and neuroanatomical features similar to those seen in recent-onset depression (ROD). Data were extracted from the multisite PRONIA study: 154 ROP patients (FEP within 3 months of treatment onset), of whom 83 were depressed (ROP+D) and 71 who were not depressed (ROP-D), 146 ROD patients, and 265 healthy controls (HC). Analyses included a (1) principal component analysis that established the similar symptom structure of depression in ROD and ROP+D, (2) supervised machine learning (ML) classification with repeated nested cross-validation based on depressive symptoms separating ROD vs ROP+D, which achieved a balanced accuracy (BAC) of 51%, and (3) neuroanatomical ML-based classification, using regions of interest generated from ROD subjects, which identified BAC of 50% (no better than chance) for separation of ROP+D vs ROP-D. We conclude that depression at a symptom level is broadly similar with or without psychosis status in recent-onset disorders; however, this is not driven by a separable depressed subgroup in FEP. Depression may be intrinsic to early stages of psychotic disorder, and thus treating depression could produce widespread benefit.

A study on classification features of depressive symptoms in adolescents.

Although extensive literature has addressed depression among adolescents, few studies have emphasized the classification features of depressive symptoms in adolescents. To gain insight into the hierarchy and heterogeneity of depression in adolescents based on symptoms, 5086 adolescents completed the Chinese version of the Center for Epidemiological Studies Depression Scale (CES-D). Using Latent Class Analysis (LCA), we identified different subgroups of adolescents based on depressive symptoms. Multivariate logistic regression analysis was implemented to examine the relations between latent classes and demographic covariates. Four latent classes of individuals with depressive symptoms displaying a pattern of hierarchical organization were identified. The four classes were ordered by the degree of severity, ranging from the students reporting the highest number of depressive symptoms to the lowest number: "probable clinical depression", "subthreshold depression", "mild depression" and "low depression", accounting for 8.2%, 19.2%, 41.8% and 30.8% of total sample respectively. Further analyses revealed that compared to the "mild depression" class, the rest of three classes differed significantly across age groups and only child (vs. sibling) status. In conclusion, classifying the groups of adolescents based on features of depressive symptoms is potentially useful for understanding risk factors and developing tailored prevention and intervention programs for this age group.

Subtypes of Late-Life Depression: A Data-Driven Approach on Cognitive Domains and Physical Frailty.

BACKGROUND: With increasing age, symptoms of depression may increasingly overlap with age-related physical frailty and cognitive decline. We aim to identify late-life-related subtypes of depression based on measures of depressive symptom dimensions, cognitive performance, and physical frailty. METHODS: A clinical cohort study of 375 depressed older patients with a DSM-IV depressive disorder (acronym NESDO). A latent profile analysis was applied on the three subscales of the Inventory of Depressive Symptomatology, as well as performance in five cognitive domains and two proxies for physical frailty. For each class, we investigated remission, dropout, and mortality at 2-year follow-up as well as change over time of depressive symptom severity, cognitive performance, and physical frailty. RESULTS: A latent profile analysis model with five classes best described the data, yielding two subgroups suffering from pure depression ("mild" and "severe" depression, 55% of all patients) and three subgroups characterized by a specific profile of cognitive and physical frailty features, labeled as "amnestic depression," "frail-depressed, physically dominated," and "frail-depressed, cognitively dominated." The prospective analyses showed that patients in the subgroup of "mild depression" and "amnestic depression" had the highest remission rates, whereas patients in both frail-depressed subgroups had the highest mortality rates. CONCLUSIONS: Late-life depression can be subtyped by specific combinations of age-related clinical features, which seems to have prospective relevance. Subtyping according to the cognitive profile and physical frailty may be relevant for studies examining underlying disease processes as well as to stratify treatment studies on the effectiveness of antidepressants, psychotherapy, and augmentation with geriatric rehabilitation.

Natural volatile oils derived from herbal medicines: A promising therapy way for treating depressive disorder.

Depression is a common global mental disorder that seriously harms human physical and mental health. With the development of society, the increase of pressure and the role of various other factors make the incidence of depression increase year by year. However, there is a lack of drugs that have a fast onset, significant effects, and few side effects. Some volatile oils from traditional natural herbal medicines are usually used to relieve depression and calm emotions, such as Lavender essential oil and Acorus tatarinowii essential oil. It was reported that these volatile oils, are easy to enter the brain through the blood-brain barrier and have good antidepressant effects with little toxicity and side effects. In this review, we summarized the classification of depression, and listed the history of using volatile oils to fight depression in some countries. Importantly, we summarized the anti-depressant natural volatile oils and their monomers from herbal medicine, discussed the anti-depressive mechanisms of the volatile oils from natural medicine. The volatile oils of natural medicine and antidepressant drugs were compared and analyzed, and the application of volatile oils was explained from the clinical use and administration routes. This review would be helpful for the development of potential anti-depressant medicine and provide new alternative treatments for depressive disorders.

Classification of Depression Through Resting-State Electroencephalogram as a Novel Practice in Psychiatry: Review.

BACKGROUND: Machine learning applications in health care have increased considerably in the recent past, and this review focuses on an important application in psychiatry related to the detection of depression. Since the advent of computational psychiatry, research based on functional magnetic resonance imaging has yielded remarkable results, but these tools tend to be too expensive for everyday clinical use. OBJECTIVE: This review focuses on an affordable data-driven approach based on electroencephalographic recordings. Web-based applications via public or private cloud-based platforms would be a logical next step. We aim to compare several different approaches to the detection of depression from electroencephalographic recordings using various features and machine learning models. METHODS: To detect depression, we reviewed published detection studies based on resting-state electroencephalogram with final machine learning, and to predict therapy outcomes, we reviewed a set of interventional studies using some form of stimulation in their methodology. RESULTS: We reviewed 14 detection studies and 12 interventional studies published between 2008 and 2019. As direct comparison was not possible due to the large diversity of theoretical approaches and methods used, we compared them based on the steps in analysis and accuracies yielded. In addition, we compared possible drawbacks in terms of sample size, feature extraction, feature selection, classification, internal and external validation, and possible unwarranted optimism and reproducibility. In addition, we suggested desirable practices to avoid misinterpretation of results and optimism. CONCLUSIONS: This review shows the need for larger data sets and more systematic procedures to improve the use of the solution for clinical diagnostics. Therefore, regulation of the pipeline and standard requirements for methodology used should become mandatory to increase the reliability and accuracy of the complete methodology for it to be translated to modern psychiatry.

Is it depression or is it bipolar depression?

This review is intended to guide primary care providers in differentiating patients with bipolar depression from those with unipolar depression and inform patient management. Up to 64% of clinical encounters for depression occur in primary care, with misdiagnosis of bipolar depression common in both primary care and psychiatry. Although bipolar disorder is characterized by manic, hypomanic, and depressive episodes, the most common and debilitating symptomatic presentation is depression. Misdiagnosis as unipolar depression is common, often resulting in mistreatment with an unopposed monoamine antidepressant. Antidepressants are often ineffective for treating bipolar depression and may cause detrimental consequences such as treatment-emergent hypomania/mania, rapid cycling, or increased suicidality. Factors that are suggestive of bipolar disorder versus unipolar depression include early-onset depression, frequent depressive episodes, family history of serious mental illness, hypomania/mania symptoms within the depressive episode, and nonresponse to antidepressants. Comorbid medical (e.g., cardiovascular disease, hypertension, obesity) and psychiatric (e.g., attention-deficit/hyperactivity disorder, anxiety disorder, personality disorders, and substance use disorder) conditions are common and contribute to premature mortality for patients with bipolar disorder compared with the general public. Cariprazine, fluoxetine/olanzapine, lurasidone, and quetiapine are approved to treat bipolar depression; only cariprazine and quetiapine are approved to treat both bipolar mania and depression. Primary care providers who can differentiate presenting symptoms of bipolar depression from unipolar depression and offer appropriate treatment options will optimize patient care in clinical practice. Relevant information for this review was identified through a multistep literature search of PubMed using the terms bipolar depression/bipolar disorder plus other relevant terms.

Prevalence and factors associated with depression, anxiety, and stress symptoms among older adults: A cross-sectional population-based study.

Despite population aging and the increase in mental health problems, studies on the mental health of older people in developing countries are lacking. This population-based cross-sectional study estimated the prevalence and associated factors for depression, anxiety and stress symptoms among older adults in Nepal. Community-dwelling older adults (N = 794) were interviewed using a questionnaire which consisted of the 21-item Depression Anxiety Stress Scales; and a wide range of sociodemographic, health-related, and lifestyle characteristics; functional ability, social support, participation in social activities, and adverse life events. The prevalence of symptoms was 15.4% for depression, 18.1% for anxiety, and 12.1% for stress. Risk factors for symptoms included female gender, working in agriculture, lower household wealth, perceived poor health, smoking, chronic conditions, migration of adult children, and exposure to adverse life events. Receiving an allowance, physical exercise, functional ability, social support, and participation in social activities were found to have protective effects. The findings indicate the need for community-based interventions, including appropriate diagnosis and treatment of mental health conditions, and mental health promotion programs targeting the risk and protective factors.

Developing and testing a nurse-led intervention to support bereavement in relatives in the intensive care (BRIC study): a protocol of a pre-post intervention study.

BACKGROUND: When a patient is approaching death in the intensive care unit (ICU), patients' relatives must make a rapid transition from focusing on their beloved one's recovery to preparation for their unavoidable death. Bereaved relatives may develop complicated grief as a consequence of this burdensome situation; however, little is known about appropriate options in quality care supporting bereaved relatives and the prevalence and predictors of complicated grief in bereaved relatives of deceased ICU patients in the Netherlands. The aim of this study is to develop and implement a multicomponent bereavement support intervention for relatives of deceased ICU patients and to evaluate the effectiveness of this intervention on complicated grief, anxiety, depression and posttraumatic stress in bereaved relatives. METHODS: The study will use a cross-sectional pre-post design in a 38-bed ICU in a university hospital in the Netherlands. Cohort 1 includes all reported first and second contact persons of patients who died in the ICU in 2018, which will serve as a pre-intervention baseline measurement. Based on existing policies, facilities and evidence-based practices, a nurse-led intervention will be developed and implemented during the study period. This intervention is expected to use 1) communication strategies, 2) materials to make a keepsake, and 3) a nurse-led follow-up service. Cohort 2, including all bereaved relatives in the ICU from October 2019 until March 2020, will serve as a post-intervention follow-up measurement. Both cohorts will be performed in study samples of 200 relatives per group, all participants will be invited to complete questionnaires measuring complicated grief, anxiety, depression and posttraumatic stress. Differences between the baseline and follow-up measurements will be calculated and adjusted using regression analyses. Exploratory subgroup analyses (e.g., gender, ethnicity, risk profiles, relationship with patient, length of stay) and exploratory dose response analyses will be conducted. DISCUSSION: The newly developed intervention has the potential to improve the bereavement process of the relatives of deceased ICU patients. Therefore, symptoms of grief and mental health problems such as depression, anxiety and posttraumatic stress, might decrease. TRIAL REGISTRATION: Netherlands Trial Register Registered on 27/07/2019 as NL 7875, www.trialregister.nl.

Carving depression at its joints? Psychometric properties of the Sydney Melancholia Prototype Index.

Parker and colleagues developed the Sydney Melancholia Prototype Index (SMPI), a 24-item measure to assess a potential subtype of depression: melancholia. While research supports the validity of the measure, no study has assessed its psychometric properties. We recruited 1633 participants online, of whom 487 reported a lifetime period of depressed mood or anhedonia and were administered the SMPI. We conducted confirmatory factor analyses (CFA) of the SMPI, to assess the proposed fit of the measure. We also conducted exploratory factor analyses (EFA) to explore the structure implied by the current data. CFA did not support the hypothesized factor structure of the SMPI, no matter what structure we assumed as primary (i.e., a one factor, two factor, or bifactor model). An EFA suggested a five-factor solution wherein several items did not appear to co-vary reliably and other factors captured the severity of melancholic symptoms, negative mood reactivity, positive mood reactivity, emotionality and family relationships, and early life adversity. The SMPI may not measure a single construct. Future research should explore the longitudinal association between depression severity, contaminant symptoms, positive and negative mood reactivity, and early life experiences.

Depression development: From lifestyle changes to motivational deficits.

Until now, depression research has taken a surprisingly narrow approach to modelling the disease, mainly focusing on some form of psychomotor retardation within a mechanistic framework of depression etiology. However, depression has many symptoms and each is associated with a vast number of substrates. Thus, to deepen our insights, this SI ("Depression Symptoms") reviewed the behavioral and neurobiological sequelae of individual symptoms, specifically, psychomotor retardation, sadness, low motivation, fatigue, sleep/circadian disruption, weight/appetite changes, and cognitive affective biases. This manuscript aims to integrate the most central information provided by the individual reviews. As a result, a dynamic model of depression development is proposed, which views depression as a cumulative process, where different symptoms develop at different stages, referred to as early, intermediate, and advanced, that require treatment with different pharmaceutical agents, that is, selective serotonin reuptake inhibitors early on and dopamine-based antidepressants at the advanced stage. Furthermore, the model views hypothalamic disruption as the source of early symptoms and site of early intervention. Longitudinal animal models that are capable of modelling the different stages of depression, including transitions between the stages, may be helpful to uncover novel biomarkers and treatment approaches.

Depression is associated with efavirenz-containing treatments in newly antiretroviral therapy initiated HIV patients in Ecuador.

BACKGROUND: It is well known that people living with HIV (PLWH) is in higher risk for the development of depression and it has also been suggested that the use of efavirenz into the antiretroviral regimens increases even that risk. OBJECTIVE: To evaluate the effect of efavirenz-containing antiretroviral regimens on the development of depression in newly ART initiated HIV patients in Ecuador. METHODS: In a prospective cohort study from June 2016 to May 2017, all newly HIV diagnosed patients at the HIV/AIDS Unit of the Hospital Eugenio Espejo in Quito, Ecuador were evaluated using the Hamilton Rating Scale for Depression followed by a second assessment 8-12 weeks after antiretroviral therapy containing efavirenz was initiated. RESULTS: A total of 79 patients, mainly males younger than 35 years were studied. Majority of them were on TDF/FTC/EFV. Initial score in Hamilton Rating Scale revealed that less than 30% had no depression symptoms while almost 40% had mild depression. However, in the second assessment, 22.6% of the subjects had a score in the Hamilton Rating Scale compatible with severe or very severe depression (RR 1.58, 95% CI 1.09 to 2.28; p = 0.05). CONCLUSION: In our cohort study, depression was much higher in patients on Efavirenz-containing treatments. Therefore, assessment for depression must be essential as part of follow-up in these patients.

Assessment and management of depression and suicidality: Pediatric resident perspectives on training and practice.

INTRODUCTION: Primary care is a common access point for children and adolescents with depression and suicidality concerns. In this setting, pediatricians typically function as front-line providers given barriers that patients face in accessing mental health clinicians. METHOD: This study surveyed chief residents from all pediatric residency programs in the United States (N = 214) to evaluate (a) their attitudes, knowledge, practices, and comfort in managing depression and suicidality concerns in primary care, and (b) the relationship between residency training processes and pediatric residents' practices, knowledge, and comfort related to identifying and managing depression and suicidality. RESULTS: The usable response rate was 37.6%. The large majority of respondents are involved in evaluation and management of depression and suicidality; yet many respondents reported a lack of knowledge and comfort in these roles. CONCLUSIONS: Recommendations for pediatric residency program training processes are discussed, including the potential added value of colocating mental health clinicians into the primary care continuity training clinic. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Subgroups with typical courses of depressive symptoms in an elderly population during 13 years of observation: Results from the Heinz Nixdorf Recall Study.

BACKGROUND: Depressive symptoms are volatile over time but empirical studies of intra-individual variations of depressive symptoms over longer periods are sparse. AIMS: We aim to examine fluctuation patterns of depressive symptoms and to investigate the possible influence of age, sex and socioeconomic factors on fluctuation in a population-based sample over a period of 13 years. METHODS: We used data of 4,251 participants (45-75 years; 51.0% women at baseline) of the Heinz Nixdorf Recall Study with at least two of nine possible measurements obtained in the period between 2000 and 2017. Depressive symptoms were assessed via the Center for Epidemiologic Studies Depression Scale (CES-D) short form. Based on the individual mean values and standard deviation from all measurements, we categorized participants as G1 'stable low', G2 'stable high', G3 'stable around cutoff' and G4 'large fluctuations'. RESULTS: Most participants (82.3%) showed stable low depressive symptoms (G1), whereas 2.3% performed stable high values (G2), 6.9% stable around the cutoff (G3) and 8.6% large fluctuations (G4). CONCLUSION: Our longitudinal results reveal that almost 18% (G2, G3 and G4) of the participants have an increased depression score or strong fluctuations at times. According to our classification, a higher proportion of the participants show anomalies with regard to depression compared to a simple classification into depressed and nondepressed, especially if this is based on a single measurement. Thus, longitudinal measurements of depression can prevent misclassification and provide valuable information about the course of depressive symptoms for a better understanding of the changes of depression.