Longitudinal monitoring of the course of depressive disorders: Careful monitoring of the course of depressive episode

No modern studies of the natural course of depression have been done since the nineteen fourties of the last century. A large number of depressive episodes spontaneously remit. Because of this, some psychiatrists call for more use of a therapeutic approach called watchful waiting, especially for milder forms of depression. At the Institute of mental health in Belgrade, from November 2019 until November 2021, a study in watchful waiting will be done. In this paper the methodology of the planned study is described.

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Time to recurrence after recovery from major depressive episodes and its predictors

Psychological Medicine ◽

10.1017/s0033291703007827 ◽

2003 ◽

Vol 33 (5) ◽

pp. 839-845 ◽

Cited By ~ 78

Author(s):

T. KANAI ◽

H. TAKEUCHI ◽

T. A. FURUKAWA ◽

R. YOSHIMURA ◽

T. IMAIZUMI ◽

...

Keyword(s):

Depressive Episode ◽

Cumulative Probability ◽

Residual Symptoms ◽

Time To Recurrence ◽

Recorded Data ◽

Spectrum Of Patients ◽

Major Depressive Episodes ◽

Depressive Episodes ◽

Course Of Depression

Background. Depression is a remitting but recurring disease. However, there is a paucity of prospectively recorded data on the course of depression after recovery.Method. A multi-centre prospective serial follow-up study of an inception cohort of hitherto untreated unipolar major depression (N=95) for 6 years. We report the time to recurrence after recovery from the index depressive episode and their predictors.Results. The cumulative probability of remaining well without subthreshold symptoms was 57% (95% CI, 46 to 68%) at 1 year, 47% (95% CI, 36 to 58%) at 2 years and 35% (95% CI, 23 to 47%) at 5 years. The same without full relapse was 79% (95% CI, 70 to 88%) at 1 year, 70% (95% CI, 60 to 80%) at 2 years and 58% (95% CI, 46 to 70%) at 5 years. The median duration of well-interval from the end of the index episode to the beginning of the subthreshold episode was 19·0 months (95% CI, 2·4 to 35·7), and that to the end of the full episode was over 6 years. Residual symptoms at time of recovery predicted earlier recurrence.Conclusions. The median length of the well-interval was much longer than previously reported in studies employing similar definitions but dealing with a more severe spectrum of patients. However, the sobering fact remains that less than half of the patients can expect to remain virtually symptom-free for 2 years or more after recovery from the depressive episode.

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Depressive episodes–evidence for a causal role of primary anxiety disorders?

European Psychiatry ◽

10.1016/j.eurpsy.2003.10.001 ◽

2003 ◽

Vol 18 (8) ◽

pp. 384-393 ◽

Cited By ~ 100

Author(s):

Hans-Ulrich Wittchen ◽

Katja Beesdo ◽

Antje Bittner ◽

Renee D. Goodwin

Keyword(s):

Risk Factors ◽

Anxiety Disorders ◽

Depressive Disorders ◽

Common Mental Disorders ◽

Future Research ◽

Severe Impairment ◽

First Onset ◽

Depressive Episodes ◽

Course Of Depression

AbstractAnxiety and depressive disorders are common mental disorders in general population, imposing tremendous burden on both affected persons and society. Moreover, comorbidity between anxiety and depressive conditions is high, leading to substantial disability and functional impairment. Findings consistently suggest that anxiety disorders are primary to depression in the majority of comorbid cases. Yet, the question of whether anxiety disorders are risk factors for depression, and potentially even causal risk factors for the first onset of depression, remains unresolved. Recent results have shown that anxiety disorders increase the risk for subsequent depression, and also affect the course of depression, resulting in a poorer prognosis. Further, some results suggest a dose–response-relationship in revealing that a higher number of anxiety disorders and more severe impairment associated with anxiety disorders additionally increase the risk for subsequent depression. The goal of this paper is to review recent literature, summarize implications of previous findings, and suggest directions for future research regarding preventive and intervention strategies.

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Emotion-modulated startle in anxiety disorders is blunted by co-morbid depressive episodes

Psychological Medicine ◽

10.1017/s003329171000036x ◽

2010 ◽

Vol 41 (1) ◽

pp. 129-139 ◽

Cited By ~ 31

Author(s):

A. Taylor-Clift ◽

B. H. Morris ◽

J. Rottenberg ◽

M. Kovacs

Keyword(s):

Anxiety Disorder ◽

Anxiety Disorders ◽

Depressive Episode ◽

Emotional Reactivity ◽

Depressive Disorders ◽

Late Onset ◽

Response Patterns ◽

Emotional Responding ◽

Depressive Episodes ◽

A Current

BackgroundWhile anxiety has been associated with exaggerated emotional reactivity, depression has been associated with blunted, or context insensitive, emotional responding. Although anxiety and depressive disorders are frequently co-morbid, surprisingly little is known about emotional reactivity when the two disorders co-occur.MethodWe utilized the emotion-modulated startle (EMS) paradigm to examine the effects of a concurrent depressive episode on emotional reactivity in young adults with anxiety disorders. Using an archival dataset from a multi-disciplinary project on risk factors in childhood-onset depression, we examined eye-blink startle reactions to late-onset auditory startle probes while participants viewed pictures with affectively pleasant, unpleasant and neutral content. EMS response patterns were analyzed in 33 individuals with a current anxiety (but no depressive) disorder, 24 individuals with a current anxiety disorder and co-morbid depressive episode and 96 healthy controls.ResultsControl participants and those with a current anxiety disorder (but no depression) displayed normative linearity in startle responses, including potentiation by unpleasant pictures. By contrast, individuals with concurrent anxiety and depression displayed blunted EMS.ConclusionsAn anxiety disorder concurrent with a depressive episode is associated with reactivity that more closely resembles the pattern of emotional responding that is typical of depression (i.e. context insensitive) rather than the pattern that is typical for anxiety (i.e. exaggerated).

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From depressive symptoms to depressive disorders: the relevance of thresholds

The British Journal of Psychiatry ◽

10.1192/bjp.bp.109.071191 ◽

2010 ◽

Vol 196 (5) ◽

pp. 365-371 ◽

Cited By ~ 157

Author(s):

José L. Ayuso-Mateos ◽

Roberto Nuevo ◽

Emese Verdes ◽

Nirmala Naidoo ◽

Somnath Chatterji

Keyword(s):

Risk Factors ◽

Health Status ◽

Depressive Episode ◽

Depressive Disorders ◽

World Health ◽

World Health Survey ◽

The World ◽

The Unemployed ◽

Depressive Episodes ◽

The Impact

BackgroundNosological boundaries for depressive disorders as well as the prevalence and impact of ‘subsyndromal’ depression remain unclear.AimsTo examine the impact of subsyndromal depressive disorders on health status and to assess if depressive disorders lie on a continuum of severity.MethodThe sample was composed of randomly selected respondents from the general population in 68 countries from across the world participating in the World Health Organization's World Health Survey.ResultsThe pattern of risk factors for depressive disorders was consistent across all types of depression (subsyndromal, brief depressive episode and depressive episode): odds ratios for females ranged between 1.49 and 1.80, and for the unemployed from 1.19 to 1.25. All types of depression produced a significant decrement in health status compared with no depression after controlling for demographic variables, income and country.ConclusionsSubthreshold depressive disorders occur commonly all across the world and are associated with the same risk factors everywhere. They produce significant decrements in health and do not qualitatively differ from full-blown episodes of depression as currently defined, and lie on a continuum with more severe forms of depressive episodes but are distinct from normal mood changes.

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Ethiopathogenesis of Depressive Disorders

Clinical Practice and Epidemiology in Mental Health ◽

10.2174/1745017901410010166 ◽

2014 ◽

Vol 10 (1) ◽

pp. 166-171 ◽

Cited By ~ 13

Author(s):

M Pasquini ◽

I Berardelli ◽

M Biondi

Keyword(s):

Family Member ◽

Mood Disorders ◽

Life Events ◽

Depressive Episode ◽

Depressive Disorders ◽

Negative Life Event ◽

Vulnerability Factors ◽

Life Event ◽

Depressive Episodes

Etiology of depressive disorders is still unknown. Several factors are involved in its pathophysiology such as neurotransmitters and neuroendocrine alterations, genetics, life events and their appraisal. Some of these components are strictly linked. Subjects with a family member affected by mood disorders are more prone to suffer from depressive disorders. It is also true that receiving feedbacks of indifference or neglect during childhood from one parent who suffer from depression may represent a factor of vulnerability. Indeed, reaction to a specific negative event may determine an increased allostasis which lead to a depressive episode. Thus, a psychological cause does not exclude a neurobiological cascade. Whereas in other cases recurrent depressive episodes appear in absence of any negative life event. This review provides a set of data regarding the current etiopathogenesis models of depression, with a particular attention to the neurobiological correlates and vulnerability factors.

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An intervention for depressive symptoms using a commercial game in a mental health impatient setting. (Preprint)

10.2196/preprints.13890 ◽

2019 ◽

Author(s):

Pablo Rodrigo Guzman Cortez ◽

Matias Marzocchi ◽

Neus Freixa Fontanals ◽

Mercedes Balcells-Olivero

Keyword(s):

Mental Health ◽

Depressive Symptoms ◽

Health Outcomes ◽

Serious Games ◽

Rating Scale ◽

Depressive Symptomatology ◽

Pilot Test ◽

Potential Health ◽

Depressive Episodes ◽

Hamilton Rating Scale

BACKGROUND Computerized mental health interventions have shown evidence of their potential benefit for mental health outcomes in young users. All of the studied interventions available in the review and scientific literature can be classified as "serious games". Serious games are computerized interventions designed from the start with the objective of improving specific desired health outcomes. Moreover, there are reports of users experiencing subjective benefits in mental health after playing specific commercial games. These were games not intentionally made with a therapeutic objective in the design process. An example is the videogame "Journey", first released for the Playstation 3 console in 2012 which won "Game of the Year" in the 2013 D.I.C.E awards. The creator of the game describes the game as a short, 2-3-hour narrative experience in which the player goes through the "Hero's Journey" following a classic 3-part structure. There were more than 100 testimonials from players describing how the game helped them cope with psychological or personal issues. Some of them explicitly described recovering from depressive episodes through playing the game. OBJECTIVE To conduct a pilot test of the efficacy of the videogame Journey in reducing depressive symptoms in an acute impatient setting METHODS Depressive symptomatology was measured before and after the intervention using the Hamilton Rating Scale for Depression (HRSD) The intervention was conducted in an isolated room using a Playstation 3 console with the videogame "Journey" developed by Thatgamecompany. No internet access was allowed. The game was played over the course of 4 30-45 min sessions in a two week period. RESULTS The initial score in the Hamilton Rating Scale for Depression (HRSD) was 30, indicating a very severe depression. After the intervention the HRSD score was 10, showing a mild depression. CONCLUSIONS The Videogame Journey, a commercial game first available for the Playstation 3 console in 2012, was not created as a serious game with potential health benefits. Our pilot test is the first case report of a commercial game showing a potential effect in reducing depressive symptoms, which is consistent with the previous informal reports of users online.

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Adverse childhood experiences and depression among women in rural Pakistan

BMC Public Health ◽

10.1186/s12889-021-10409-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Katherine LeMasters ◽

Lisa M. Bates ◽

Esther O. Chung ◽

John A. Gallis ◽

Ashley Hagaman ◽

...

Keyword(s):

Mental Health ◽

Symptom Severity ◽

Adverse Childhood Experiences ◽

Linear Regression Models ◽

Childhood Experiences ◽

Link Type ◽

Rural Pakistan ◽

Adverse Childhood ◽

Major Depressive Episodes ◽

Depressive Episodes

Abstract Background Adverse Childhood Experiences (ACEs) are a common pathway to adult depression. This pathway is particularly important during the perinatal period when women are at an elevated risk for depression. However, this relationship has not been explored in South Asia. This study estimates the association between ACEs and women’s (N = 889) depression at 36 months postpartum in rural Pakistan. Method Data come from the Bachpan Cohort study. To capture ACEs, an adapted version of the ACE-International Questionnaire was used. Women’s depression was measured using both major depressive episodes (MDE) and depressive symptom severity. To assess the relationship between ACEs and depression, log-Poisson models were used for MDE and linear regression models for symptom severity. Results The majority (58%) of women experienced at least one ACE domain, most commonly home violence (38.3%), followed by neglect (20.1%). Women experiencing four or more ACEs had the most pronounced elevation of symptom severity (β = 3.90; 95% CL = 2.13, 5.67) and MDE (PR = 2.43; 95% CL = 1.37, 4.32). Symptom severity (β = 2.88; 95% CL = 1.46, 4.31), and MDE (PR = 2.01; 95% CL = 1.27, 3.18) were greater for those experiencing community violence or family distress (β = 2.04; 95%; CL = 0.83, 3.25) (PR = 1.77; 95% CL = 1.12, 2.79). Conclusions Findings suggest that ACEs are substantively distinct and have unique relationships to depression. They signal a need to address women’s ACEs as part of perinatal mental health interventions and highlight women’s lifelong experiences as important factors to understanding current mental health. Trial registration NCT02111915. Registered 11 April 2014. NCT02658994. Registered 22 January 2016. Both trials were prospectively registered.

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Factors associated with depressive episode among first year University students in Serbia

European Journal of Public Health ◽

10.1093/eurpub/ckaa166.1037 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

S Čanković ◽

D Čanković ◽

I Radić ◽

D Rakić ◽

S Ukropina ◽

...

Keyword(s):

Mental Health ◽

Logistic Regression ◽

Depressive Symptoms ◽

University Students ◽

Depressive Episode ◽

Social Health ◽

Support Network ◽

First Year ◽

Behavioral Factors ◽

First Year University

Abstract Background Some findings indicate that university students are at higher risk of depression despite being a socially advantaged population, showing that 15 to 25% of them develop some type of mental disorder during graduation, and depression is one of the most prevalent. The aim of this study was to investigate the prevalence of depressive symptoms and its association with gender, material status, social health, and behavioral factors among university students. Methods The research represents a cross-sectional study conducted at the University of Novi Sad, Serbia. The research involved 455 first-year students. The average age of participants was 19.3 years (72.1% girls and 27.9% boys). Patient Health Questionnaire (PHQ-9) was used to measure depressive symptoms (cut point for depressive episode ≥10). Additional questions were focused on self-assessed material status, social health, and behavioral factors (smoking and alcohol use). The binary logistic regression model was used to estimate the association between depression and observed independent variables. Results The prevalence of moderate to severe depressive episode among students was 18.0%, with no gender differences. Out of the total, 11.0% of students had suicidal thoughts or thoughts of hurting themselves. Multivariable logistic regression showed that self-assessed poor material status (OR = 2.04; 95%CI: 1.06-3.89), self-assessed poor social health (OR = 8.9; 95%CI:4.87-16.42) and smoking (OR = 2.18; 95%CI: 1.09-4.39) were significant predictors of depression among first-year university students. Conclusions High prevalence of depressive episode among university students call for the action for the promotion of mental health, particularly among those of lower socioeconomic status, and points out the importance of social health and social network in the prevention of mental disorders. Key messages Students on the first year of University should be screened for depressive symptoms. It is important to educate students on how to create a strong support network and to implement intervention programs for improving mental health through fostering healthy lifestyles change.

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Using a Person-Centered Approach to Identify Patterns of Exposure to Intimate Partner Violence and Child Abuse in Women: Associations With Mental Health

Child Maltreatment ◽

10.1177/10775595211031655 ◽

2021 ◽

pp. 107755952110316

Author(s):

Bre’Anna L. Free ◽

Alexandra J. Lipinski ◽

Rivian K. Lewin ◽

Rimsha Majeed ◽

Rebecca J. Zakarian ◽

...

Keyword(s):

Mental Health ◽

Intimate Partner Violence ◽

Child Abuse ◽

Partner Violence ◽

Depressive Disorders ◽

Latent Class ◽

Intimate Partner ◽

Health Conditions ◽

Mental Health Conditions ◽

Class Differences

Patterns of exposure to intimate partner violence (IPV) and child abuse (CA) were explored in 467 women seeking psychological assistance following IPV. Using latent class analysis, three classes were obtained: women who had experienced physical, sexual, and psychological IPV, along with childhood physical and sexual abuse (IPV + CA; 38.5%); women who had experienced physical, sexual, and psychological IPV only (IPV/no CA; 52.9%); and women who had experienced psychological IPV only (Psych IPV only; 8.6%). Associations of class membership with severity of specific mental health conditions were examined, along with the number of diagnosed conditions. Significant between-class differences were noted on severity of IPV-related posttraumatic stress disorder, depressive disorders, alcohol and substance use disorders, and social phobia. Classes also differed significantly on the number of mental health conditions. Understanding patterns of betrayal-based trauma (e.g., IPV and CA) can inform care within agencies that serve IPV survivors by highlighting individuals at-risk for mental health conditions.

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Machine Learning in Mental Health: Recognizing the Symptoms of Depressive and Anxiety Disorders

10.31234/osf.io/edpnj ◽

2021 ◽

Author(s):

Olga Troitskaya ◽

Andrey Zakharov

Keyword(s):

Mental Health ◽

Machine Learning ◽

Depressive Disorders ◽

Learning Technologies ◽

Emotional Symptoms ◽

Full Spectrum ◽

Large Classes ◽

Machine Learning Model ◽

Self Talk ◽

Potential Possibility

Machine learning technologies can be used to extract important information about mental health of individuals from unstructured texts, including social media posts and transcriptions of counselling sessions. So far machines have been trained to detect the presence of mental disorder, but they still need to learn to recognize individual symptoms in order to make a valid diagnosis. This study presents an attempt to train a machine learning model to recognize individual symptoms of anxiety and depressive disorders. We collected 1065 posts about depression and anxiety from online psychological forums; divided messages into 7149 replicas and classified each replica according to the DSM-5 criteria. We found that users mention emotional symptoms far more often than physical ones. An imbalanced dataset did not allow us to recognize the full spectrum of symptoms with sufficient accuracy. A two-stage model was developed: at the first stage the model recognized large classes of depression, anxiety or irritability. At the second stage it recognized sub-classes of symptoms, such as depressed mood, suicidal intent and negative self-talk within the depression class; and excessive worry and social anxiety within the anxiety class. The research has demonstrated the potential possibility of extracting symptoms of mental disorders from unstructured data on a larger dataset.

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