Better Understanding Of Depression Research Articles

Secular trends in the incidence of major depressive disorder and dysthymia in China from 1990 to 2019

BackgroundDepression is increasingly recognized as a worldwide serious, public health concern. A better understanding of depression is important for advancing its management and learning the difference between major depressive disorder (MDD) and dysthymia. Our aim is to conduct a concurrent analysis of the trends of both MDD and dysthymia in China.MethodsThe data on depression from 1990 to 2019 were collected from the Global Burden of Disease Study 2019 (GBD 2019). To determine the average annual percent changes (AAPC) and relative risks (RRs), joinpoint regression and the age-period-cohort models were employed, respectively.ResultsThe incidence number of MDD and dysthymia continuously increased in China from 1990 to 2019, however, the age-standardized rates (ASR) had a decreasing trend in both men and women. The results from joinpoint regression showed that a declining trend was presented in young people (< 50 years) but an increased trend in the elderly (≥ 50 years) both in men and women, during 1990–2019. Age is the most influential factor for MDD and dysthymia. Age RRs for MDD incidence had an overall increasing trend with age. Period RR in MDD presented a U-shaped pattern, while Cohort RRs presented an inverted U-shaped pattern. On the other hand, RRs in dysthymia for period and cohort effects had no statistical significance, only the age effect presented an inverted U-shaped pattern.ConclusionsThe disparities in trends observed between MDD and dysthymia during the period of 1990–2019 indicated the significance of distinguishing between these two disorders. The age, period and cohort effects all had a greater impact on MDD than on dysthymia, and age effects presented different influential patterns in these two. To alleviate the burden of depressive disorders in China, proactive measures need to be implemented, with particular attention to the elderly population.

Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning-Based Exploratory Study.

BackgroundDepression levels in adolescents have trended upward over the past several years. According to a 2020 survey by the National Survey on Drug Use and Health, 4.1 million US adolescents have experienced at least one major depressive episode. This number constitutes approximately 16% of adolescents aged 12 to 17 years. However, only 32.3% of adolescents received some form of specialized or nonspecialized treatment. Identifying worsening symptoms earlier using mobile and wearable sensors may lead to earlier intervention. Most studies on predicting depression using sensor-based data are geared toward the adult population. Very few studies look into predicting depression in adolescents.ObjectiveThe aim of our work was to study passively sensed data from adolescents with depression and investigate the predictive capabilities of 2 machine learning approaches to predict depression scores and change in depression levels in adolescents. This work also provided an in-depth analysis of sensor features that serve as key indicators of change in depressive symptoms and the effect of variation of data samples on model accuracy levels.MethodsThis study included 55 adolescents with symptoms of depression aged 12 to 17 years. Each participant was passively monitored through smartphone sensors and Fitbit wearable devices for 24 weeks. Passive sensors collected call, conversation, location, and heart rate information daily. Following data preprocessing, 67% (37/55) of the participants in the aggregated data set were analyzed. Weekly Patient Health Questionnaire-9 surveys answered by participants served as the ground truth. We applied regression-based approaches to predict the Patient Health Questionnaire-9 depression score and change in depression severity. These approaches were consolidated using universal and personalized modeling strategies. The universal strategies consisted of Leave One Participant Out and Leave Week X Out. The personalized strategy models were based on Accumulated Weeks and Leave One Week One User Instance Out. Linear and nonlinear machine learning algorithms were trained to model the data.ResultsWe observed that personalized approaches performed better on adolescent depression prediction compared with universal approaches. The best models were able to predict depression score and weekly change in depression level with root mean squared errors of 2.83 and 3.21, respectively, following the Accumulated Weeks personalized modeling strategy. Our feature importance investigation showed that the contribution of screen-, call-, and location-based features influenced optimal models and were predictive of adolescent depression.ConclusionsThis study provides insight into the feasibility of using passively sensed data for predicting adolescent depression. We demonstrated prediction capabilities in terms of depression score and change in depression level. The prediction results revealed that personalized models performed better on adolescents than universal approaches. Feature importance provided a better understanding of depression and sensor data. Our findings can help in the development of advanced adolescent depression predictions.

Similarities Between Depression and Neurodegenerative Diseases: Pathophysiology, Challenges in Diagnosis and Treatment Options.

Depressive disorder and neurodegenerative diseases are two different clinical entities. Depression is a common psychiatric disorder in the general population. However, when present concomitantly with neurodegenerative disorders, its diagnosis becomes challenging. In many cases, patients remain undiagnosed and hence, untreated, worsening the prognosis of the neurodegenerative diseases and impairing the quality of life.One of the possible reasons for the difficulties in diagnosis in such cases is that both conditions affect the central nervous system, so there might be an overlap of symptoms leading to a missed diagnosis of depression in a neurodegenerative disease patient and vice versa. Symptoms such as irritability, apathy, and decreased cognition are common to both types of disorders. Some neurodegenerative diseases, especially Alzheimer's disease, can initially present as a depressive prodrome. This may cause a difficulty in differentiating between these two conditions and a diagnosis of either conditions may be missed; hence an opportunity for timely intervention and improved outcomes is missed.An approach towards analyzing and comparing the pathological mechanisms common to both disease types will create a better understanding of depression and neurodegenerative diseases, identify their similarities, and develop improved clinical criteria to help clinicians make a timely diagnosis of these conditions present together. In the present review, various studies related to common pathological links, concomitant diagnosis challenges, and ongoing research about different treatment options are discussed.

Depression in Psoriatic Arthritis: Dimensional Aspects and Link with Systemic Inflammation.

Studying comorbidities in patients with psoriatic arthritis (PsA) provides a better understanding of the extended burden of the disease. Depression and anxiety are well recognized but understudied comorbidities in patients with PsA. The prevalence of depression is significantly higher in this patient population than in the general population, with far reaching consequences in terms of long-term quality of life. Over the past few years there has been an increasing interest in the link between inflammation and depression, with several novel studies being conducted. Recent evidence suggests a significant improvement of depression in PsA patients treated with biologic disease-modifying anti-rheumatic drugs (bDMARDs) as compared to conventional DMARDs. Depression in PsA is multidimensional, with recognized phenotypes, including cognitive disorder, alexithymia and anhedonia. The paucity of standardized, validated tools to screen these dimensional phenotypes remains an unmet need. Prevalence studies on depression in patients with PsA, mostly based on patient-reported outcomes, are only able to highlight the tip of the iceberg. A comprehensive, multi-disciplinary approach addressing the subdomains of depression is imperative for a better understanding of depression in PsA patients, as well as to find a way forward for improving their quality of life. In this scoping review, we explore existing evidence on the burden of depression in PsA patients, the link between inflammation and depression in these patients and the screening tools used to evaluate the subdomains of depression.

Development and internal validation of a depression severity prediction model for tinnitus patients based on questionnaire responses and socio-demographics

Tinnitus is a complex condition that is associated with major psychological and economic impairments – partly through various comorbidities such as depression. Understanding the interaction between tinnitus and depression may thus improve either symptom cluster’s prevention, diagnosis and treatment. In this study, we developed and validated a machine learning model to predict depression severity after outpatient therapy (T1) based on variables obtained before therapy (T0). 1,490 patients with chronic tinnitus (comorbid major depressive disorder: 52.2%) who completed a 7-day multimodal treatment encompassing tinnitus-specific components, cognitive behavioural therapy, physiotherapy and informational counselling were included. 185 variables were extracted from self-report questionnaires and socio-demographic data acquired at T0. We used 11 classification methods to train models that reliably separate between subclinical and clinical depression at T1 as measured by the general depression questionnaire. To ensure highly predictive and robust classifiers, we tuned algorithm hyperparameters in a 10-fold cross-validation scheme. To reduce model complexity and improve interpretability, we wrapped model training around an incremental feature selection mechanism that retained features that contributed to model prediction. We identified a LASSO model that included all 185 features to yield highest predictive performance (AUC = 0.87 ± 0.04). Through our feature selection wrapper, we identified a LASSO model with good trade-off between predictive performance and interpretability that used only 6 features (AUC = 0.85 ± 0.05). Thus, predictive machine learning models can lead to a better understanding of depression in tinnitus patients, and contribute to the selection of suitable therapeutic strategies and concise and valid questionnaire design for patients with chronic tinnitus with or without comorbid major depressive disorder.

Self-Reported and Diagnosed Depression in Rural Colorado: Findings from the San Luis Valley Community Health Survey.

To gain a better understanding of depression in a rural community, survey results were used to compare differences in self-reported depressive symptoms and medical professional diagnosed depression among demographic groups. A chi-square test of independence was performed to examine relationships among the depression-related variables. Logistic regression analyses were also performed to ascertain the effects of demographic characteristics and social support on depression. A statistically significant association was found between the two depression-related variables (X2=145.17, P &lt;.001). Income was significantly associated with both depression-related variables. Hispanic ethnicity, higher income, and some high school education were associated with decreased odds of self-reported medically diagnosed depression. Those reporting no or some social support had increased odds of both depression-related variables compared with those who reported always having social support. These findings provide a better understanding of depression in a rural community and may inform future public health interventions.

Impact of perceived social support on depression in Chinese rural-to-urban migrants: The mediating effects of loneliness and resilience.

The present study aimed to examine whether loneliness and resilience played the roles of mediators on the relationship between perceived social support and depression. A total of 712 Chinese rural-to-urban migrants from Nanjing, who were measured with perceived social support, resilience, loneliness, and depression, participated in the study. Results indicated that perceived social support and resilience were negatively associated with depression. Loneliness was a significant and negative predictor for depression. In addition, we also revealed that resilience and loneliness partially mediated the relationship between perceived social support and depression. These findings might develop a better understanding of depression in the course of migration.

FDA Updates Guidance for Developing Antidepressant Medications

Back to table of contents Previous article Professional NewsFull AccessFDA Updates Guidance for Developing Antidepressant MedicationsNick ZagorskiNick ZagorskiSearch for more papers by this authorPublished Online:31 Jul 2018https://doi.org/10.1176/appi.pn.2018.8a9AbstractRecommendations in the FDA’s first antidepressant guidance update in over 40 years include specifics on conducting clinical trials with rapid-acting antidepressants such as ketamine.For the first time in over 40 years, the Food and Drug Administration (FDA) is proposing updates and revisions to its guidance on how industries should develop and clinically test drugs intended to treat major depressive disorder (MDD). This new guidance finally reflects the many antidepressant advances made since 1977, such as finding new rapid mechanisms of action and gaining a better understanding of depression relapse.Perhaps the most noticeable updates are the new recommendations for clinical trials involving fast-acting antidepressants such as ketamine. Whereas short-term efficacy studies of traditional antidepressants typically need six to eight weeks to demonstrate an effect, the new guidance states that efficacy of rapid-acting drugs should be demonstrated within one week. However, clinical trials of rapid-acting drugs should be continued after this period so that the durability of rapid-acting antidepressants can be determined. The FDA also highlighted that rapid-acting drugs have their own specific set of safety concerns. NMDA receptor-targeting drugs like ketamine, for example, can cause Olney lesions—fluid-filled vesicles in the brain that sometimes precede permanent neuronal injury or death. Therefore, for all NMDA receptor drugs, investigators should complete preclinical studies testing for acute neurotoxic effects before conducting any human studies, according to the FDA.These are among other notable recommendations in the new guidance:Given the high placebo response increasingly seen in clinical antidepressant studies, noninferiority trials that compare two active drugs are not practical, and thus all trials of new antidepressant agents should include a placebo group.Studies for maintenance treatment should last at least six months; long-term safety and tolerability measurements should also be incorporated into the design of all maintenance trials. The FDA also noted that it was interested in maintenance studies that explored the effects of lower drug doses; the results of these studies could be included in drug labeling.Even for antidepressants already approved for adult MDD, at least two adequately sized and well-controlled efficacy trials should be conducted in relevant pediatric patients (along with pharmacology and safety studies) before an approved drug can be given a pediatric indication. For pediatric MDD, children aged 7 through 12 and adolescents aged 13 through 17 are considered unique populations with their own needs.Clinical trial sponsors are encouraged to enroll demographically broad populations in studies whenever possible. This includes special populations such as elderly patients or individuals with medical problems such as renal insufficiency, cardiac disease, HIV, or hepatitis C. In addition, patients with a history of substance abuse and/or a history of suicidal ideation should not be automatically excluded from trials.Related to the above, the FDA made no comments on enrollment restrictions typically applied to pregnant women. However, the guidance did suggest that drug sponsors should collect and register safety data from women who become pregnant during a trial and become inadvertently exposed to an antidepressant or pregnant women who use approved antidepressants in a postmarketing study.As with the existing industry guidance, the FDA noted these updates reflect the agency’s current thinking on MDD and represent recommendations and not requirements. The draft guidance is intended to stimulate continued discussions among the Division of Psychiatry Products, pharmaceutical companies, the academic community, and the public.The FDA will accept public comments and suggestions on the new draft guidance until August 20, at which point it will finalize the document. ■The draft document, “Major Depressive Disorder: Developing Drugs for Treatment. Guidance for Industry,” can be accessed here. Comments may be submitted here. ISSUES NewArchived

Depression in Young People: More than Just a Bad Day—A Concept Analysis

ABSTRACTAim: Suicide from depression is the second leading cause of death in young people. To better understand depression, a concept analysis was conducted using the Lorraine Walker and Kay Avant method. Source of Data: Three electronic databases searched using keywords such as depress*, stigma, and feeling depressed yielded 40 articles in English from 2006 through 2016. Results: Primary attribute was depressed mood; stress was the primary antecedent found in young people. Consequences included health, emotional, and financial well-being. Conclusion: A better understanding of depression by healthcare providers can foster quicker assessment and treatment in young people and impact final outcome—suicide.

Is treatment-resistant depression a useful concept?

The term treatment-resistant depression (TRD) is widely used in the context of managing mood disorders, but defining it, both conceptually and in practice, has proven difficult. Most definitions have focused...

うつ病患者に対する薬局薬剤師の応対に関与する要因の検討

Patients who have mental health issues, including depression, tend to have lower adherence and have higher recurrence than those with other diseases. The aim of this study is to comprehend the state of community pharmacists' feeling of their services for patients with depression and determine factors capable of improving pharmacists' services for patients with depression in community pharmacies. A questionnaire was sent to 1000 pharmacies chosen at random between July-August 2015. The survey was completed by 365 community pharmacists with a response rate of 36.5％. We used 272 responses of 365 (74.5％) after excluding missing values. Path analysis was applied to the results of the survey. The strength of stigma towards depression had the most influence on the feeling of difficulty in dealing with patients who have depression. A statistically significant positive path was observed from the frequency of participating in an academic meeting about mental disorders, including depression, against the understanding of depression. It is considered that relieving the difficulty in dealing with patients who have depression can improve pharmacists' services to the patients. The results indicate that we cannot relieve the difficulty in dealing with patients who have depression only by gaining common experience as a pharmacist. Along with gaining a better understanding of depression, it is important to remove misunderstandings and prejudices surrounding depression in order to improve the pharmacists' services for patients with depression.

Prevalence and determinants of depressive symptoms among university students in Ghana

BackgroundOver two million Ghanaians suffer from moderate to mild mental disorders but prevalence levels and determinants among university students remains fairly unknown. A better understanding of depression and its determinants is necessary in developing appropriate interventions in this population group. MethodA convenient sample of 270 students from a public university (132 males and 138 females) were interviewed using a questionnaire to record socio-demographic variables, HIV risk behaviours. Depressive symptoms were measured using Centre for Epidemiological Studies Short Depression Scale (CES-D 10). Multiple logistic regression was used to identify the determinants. ResultsThe mean age was 22 (SD=2.39). Using a cut-off point of 10 of the CES-D10, the overall prevalence of depression was 39.2%; with 31.1% of mild to moderate depression and 8.1% severe depressive symptoms. Significant predictors included lack of social support, religion not having an impact on life, heavy alcohol consumption and traumatic experiences such as being forced to have sex, physically and sexually abused as a child, and beaten by a sex partner. LimitationsGiven the cross-sectional nature of the research, the findings are limited highlighting the need for further research. Also, relying on self-report of symptoms could have influenced the outcome. The use of a single university means that there could be regional differences in depression in other universities. ConclusionDepression occurs in a significant number of students. An appropriate intervention must be implemented to help reduce the burden of depression, especially to those found to be at risk.

Depression among university students in Kenya: Prevalence and sociodemographic correlates

BackgroundDepression is a common cause of morbidity but prevalence levels among Kenyan university students are poorly understood. A better understanding of depression and its correlates is essential in planning for appropriate interventions in this population group. MethodA random sample of 923 University of Nairobi students (525 male and 365 female) were interviewed using a questionnaire to record sociodemographic variables. Depressive symptoms were measured using Centre for Epidemiological Studies Short Depression Scale (CES – D 10). ResultsThe mean age was 23 (s.d. 4.0). Using a cut-off point of 10, the overall prevalence of moderate depressive symptoms was 35.7% (33.5% males and 39.0% females) and severe depression was 5.6% (5.3% males and 5.1% female). Depressive illness was significantly more common among the first year students, those who were married; those who were economically disadvantaged and those living off campus. Other variables significantly related to higher depression levels included year of study, academic performance, religion and college attended. Logistic regression showed that those students who used tobacco, engaged in binge drinking and those who had an older age were more likely to be depressed. No difference was noted with respect to gender. LimitationsThis was a cross sectional study relying on self report of symptoms and could therefore be inaccurate. Although the study was conducted in the largest university in the country that admits students from diverse backgrounds in the country there could still be regional differences in other local universities. ConclusionDepression occurs in a significant number of students. Appropriate interventions should be set up in higher institutions of learning to detect and treat these disorders paying particular attention to those at risk.

Reduced metabotropic glutamate receptor 5 in the Flinders Sensitive Line of rats, an animal model of depression: An autoradiographic study

Depression is a brain disorder and there is still only a partial understanding of its underlying pathophysiology. Antidepressant medications with a fast onset have not yet been developed. In addition to the monoaminergic systems, the brain glutaminergic system has been implicated in the etiology of depression. Animal studies of depression have gained importance because they permit a more invasive manipulation of the subjects than human studies. In the present study, we measured the densities of the brain regional metabotropic glutaminergic receptor 5 (mGluR5) in the Flinders Sensitive Line (FSL) rat model of depression and two groups of control rats, the Flinders Resistant Line (FRL) and Sprague Dawley (SPD), the parent strain for both the FSL and FRL rats. The FSL rats showed lower densities of mGluR5 in many brain regions compared to either the SPD and/or FRL rats. In addition, the densities in the FRL rats were larger than in the SPD rats, suggesting possible problems in using FRL rats as controls. The presented data suggest that mGluR5 is lower in animal models of depression which could be related to the cognitive and emotional dysfunctions in the FSL rat model of depression and could be relevant to a better understanding of depression in humans.

Understanding Depression as It Occurs in the Context of Post-Traumatic Stress Disorder

The aim of the current special issue is to gain a better understanding of depression as it occurs in the context of posttraumatic stress disorder (PTSD). Depression and major depressive disorder (MDD) are often present in the context of PTSD, but it is not clear whether the high prevalence of depressive disorders in PTSD should be best understood as true comorbid conditions, with a separate underlying cause and pathophysiology or rather, whether it should best be considered an artifact of overlapping symptoms. Indeed, when individuals with PTSD also meet criteria for depression, this may signal the presence of a single depressive subtype of PTSD rather than two separate syndromes. Epidemiologic data support the idea that a depressive diathesis can be a risk factor for the development of PTSD following trauma exposure. However, the question of childhood trauma as an even earlier antecedent of depression suggests that the depression that contributes to PTSD risk may relate to earlier forms of trauma exposure rather than genetic diatheses per se. Prospective studies assessing the development of major depressive disorder (MDD) show that, although the prevalence of PTSD is higher shortly after exposure, later on approximately the same prevalences of PTSD and MDD are seen after exposure to traumatic events. Severe depressive symptoms in the early aftermath of trauma exposure can be considered more relevant in predicting an unfavorable course of mental health than severity of PTSD symptoms, underlining the relevance of broad mental health assessment after trauma exposure. Whether depression in PTSD represents a phenomenological expression of the same underlying pathophysiology becomes interesting to consider in the context of the rather distinct biological alterations that have been observed in PTSD and major depressive disorder, particularly in the context of neuroendocrine, neurochemical, and brain metabolic factors. Beside clinical characteristics, biological markers may help to further improve identification of biologically distinct endophenotypes and, ultimately, to devise more specific treatment strategies. Although antidepressants are among the only FDA-approved pharmacological treatments for PTSD, these medications have only limited utility in PTSD, and it is not clear whether the efficacy of these agents results from the treatment of comorbid depression or PTSD per se.

Toward a better understanding of depression and anxiety. The importance of tryptophan hydroxylase activation blockade: The origin of a unique anxiolytic antidepressant

AbstractThe serotonin (5‐HT) deficiency theory of depression has misled medical science. Inhibitors of 5‐HT reuptake were the basis of the hypothesis and display limited efficacy with a pronounced delay of onset in action coupled with a side‐effect profile that includes increased anxiety. In the present commentary, a recommendation for the reinstatement of the prolongation of the d‐amphetamine stereotypy test is made as a means to generate new molecules capable of blocking stress‐induced tryptophan hydroxylase (TPH) activation and its elevation of 5‐HT, now regarded as the cause of depression The selective TPH activation inhibitor, AGN 2979, is already known to exert powerful, rapid antidepressant and anxiolytic properties in the clinic with a notable lack of the side effects associated with monoamine reuptake inhibition. Drug Dev Res 71:331–334, 2010. © 2010 Wiley‐Liss, Inc.

P.1.i.006 The effect of ultra-low doses of anti-S100 antibodies on stress-induced increase in c-Fos immunoreactivity in rats

Depression is a brain disorder and there is still only a partial understanding of its underlying pathophysiology. Antidepressant medications with a fast onset have not yet been developed. In addition to the monoaminergic systems, the brain glutaminergic system has been implicated in the etiology of depression. Animal studies of depression have gained importance because they permit a more invasive manipulation of the subjects than human studies. In the present study, we measured the densities of the brain regional metabotropic glutaminergic receptor 5 (mGluR5) in the Flinders Sensitive Line (FSL) rat model of depression and two groups of control rats, the Flinders Resistant Line (FRL) and Sprague Dawley (SPD), the parent strain for both the FSL and FRL rats. The FSL rats showed lower densities of mGluR5 in many brain regions compared to either the SPD and/or FRL rats. In addition, the densities in the FRL rats were larger than in the SPD rats, suggesting possible problems in using FRL rats as controls. The presented data suggest that mGluR5 is lower in animal models of depression which could be related to the cognitive and emotional dysfunctions in the FSL rat model of depression and could be relevant to a better understanding of depression in humans.

Understanding depression – the ‘black dog’

THE veterinary profession is recognising that rates of depression, stress and suicide are particularly high among its members, and it is taking steps both to investigate this more fully and...

Postpartum Depression in Adolescent Mothers: An Integrative Review of the Literature

Research on adolescent mothers has revealed increasing rates of depressive symptoms in the postpartum period. This review integrated 12 research-based articles to provide a better understanding of depression among adolescent mothers in the first year postpartum. The results revealed that more family conflict, fewer social supports, and low self-esteem all were associated with increased rates of depressive symptoms in adolescent mothers during the first postpartum year. To prevent adverse outcomes associated with depression, it is important that nurse practitioners working with these families screen adolescent mothers for depression and refer them for treatment as needed.

Depression and apathy in Parkinson’s disease

This article provides an update on depression and apathy in Parkinson's disease (PD), both of which are common but often misunderstood. The diagnosis of depression in PD can be challenging and we still do not have solid evidence on which to base our treatment decisions. Apathy is most commonly seen in the setting of dementia or depression but emerging evidence suggests that it may be a core feature of PD. There are conflicting reports about the effects of deep brain stimulation (DBS) on mood and apathy, but studies suggest that at least some patients may develop depression and apathy after the procedure. Although we are making strides toward a better understanding of depression and apathy in PD, it is clear that more research is needed about these non-motor features.