A prediction algorithm for first onset of major depression in the general population: development and validation

Purpose The NESARC, a “third generation” psychiatric epidemiologic survey that integrated detailed measures of alcohol and drug use and problems, has been the data source for over >850 publications. A comprehensive review of NESARC findings and their implications is lacking. Method NESARC was a survey of 43,093 participants that covered alcohol, drug and psychiatric disorders, risk factors, and consequences. Wave 1 of the NESARC was conducted in 2001-2002. Three years later, Wave 2 follow-up re-interviews were conducted with 34,653 of the original participants. Scopus and Pubmed were used to search for NESARC papers, which were sorted into topic areas and summarized. Result The most common disorders were alcohol and post-traumatic stress disorders, and major depression. Females had more internalizing disorders and males had more externalizing disorders, although the preponderance of males with alcohol disorders (the “gender gap”) is less pronounced than it was in previous decades. A race/ethnic “paradox” (lower risk among disadvantaged minorities than whites) remains unexplained. Younger participants had higher risk for substance and personality disorders, but not unipolar depressive or anxiety disorders. Psychiatric comorbidity was extensive and often formed latent trans-diagnostic domains. Since 1991-1992, risk for marijuana and prescription drug disorders increased, while smoking decreased, although smoking decreases were less pronounced among those with comorbidity. A nexus of comorbidity, social support, and stress predicted transitions in diagnostic status between Waves 1 and 2. Childhood maltreatment predicted psychopathology. Alcohol and drug use disorders were seldom treated; attitudinal barriers (little perceived need, perceived alcoholism stigma, pessimism about efficacy) were more important in predicting non-treatment than financial barriers. Conclusions Understanding comorbidity and the effects of early stressors will require research incorporating biologic components, e.g., genetic variants and brain imaging. The lack of treatment for alcohol and drug disorders, predicted by attitudinal rather than financial variables, suggests urgent need for public and professional education to reduce the stigma associated with these disorders, and increase knowledge of treatment options.

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“…Screening, including for psychiatric [409,512-517], alcohol [195,518-526], and substance disorders [527];…”

Section: Resultsmentioning

confidence: 99%

The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Waves 1 and 2: review and summary of findings

Hasin

Grant

2015

Soc Psychiatry Psychiatr Epidemiol

385

293

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“…Furthermore, we will explore variables associated with depression (72)(73)(74) or that have shown to predict treatment outcome for depression and anxiety (75). Clinical characteristics that shall be investigated include depressive symptom severity (76), lifetime history of MDD or any mental disorder (77)(78)(79)(80), past or present suicidal thoughts or plans (35,(79)(80)(81), experience with psychotherapy (82), treatment motivation (83), treatment preference (84)(85)(86), family history of mental illness (77, 87-89) (chronic) illness, self-perceived health and energy (61,78,(90)(91)(92)(93)(94)(95), traumatic or adverse childhood experience (abuse, parental death, or divorce) (80,87,88,(96)(97)(98)(99)(100)(101), body satisfaction and eating disorder (94,(102)(103)(104)(105)(106)(107), sleep quality (44,90,94,108,…”

Section: Other Assessmentsmentioning

confidence: 99%

Clinical and Cost-Effectiveness of Personalized Tele-Based Coaching for Farmers, Foresters and Gardeners to Prevent Depression: Study Protocol of an 18-Month Follow-Up Pragmatic Randomized Controlled Trial (TEC-A)

et al. 2020

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Background: Farmers show high levels of depressive symptoms and mental health problems in various studies. This study is part of a nationwide prevention project carried out by a German social insurance company for farmers, foresters, and gardeners (SVLFG) to implement internet-and tele-based services among others to improve mental health in this population. The aim of the present study is to evaluate the (cost-)effectiveness of personalized tele-based coaching for reducing depressive symptom severity and preventing the onset of clinical depression, compared to enhanced treatment as usual.Methods: In a two-armed, pragmatic randomized controlled trial (N = 312) with follow-ups at post-treatment (6 months), 12 and 18 months, insured farmers, foresters, and gardeners, collaborating family members and pensioners with elevated depressive symptoms (PHQ-9 ≥ 5) will be randomly allocated to personalized tele-based coaching or enhanced treatment as usual. The coaching is provided by psychologists and consists of up to 34 tele-based sessions for 25-50 min delivered over 6 months. Primary outcome is depressive symptom severity at post-treatment. Secondary outcomes include depression onset, anxiety, stress, and quality of life. A health-economic evaluation will be conducted from a societal perspective.Discussion: This study is the first pragmatic randomized controlled trial evaluating the (cost-)effectiveness of a nationwide tele-based preventive service for farmers. If proven effective, the implementation of personalized tele-based coaching has the potential to reduce disease burden and health care costs both at an individual and societal level.

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“…A similar study was conducted based on the US National Epidemiological Survey on Alcohol and Related Conditions 2001-2003(Wang et al, 2014. Depression was diagnosed using Alcohol Use Disorder and Associated Disabilities Interview Schedule, which reflects the diagnostic criteria for depression according to the DSM-IV.…”

Section: The Presence Of Depression Was Diagnosed Using the Compositementioning

confidence: 99%

Development Of A Method For Assessing Personalized Risks Of Depression

Kiselnikova¹

2018

The European Proceedings of Social and Behavioural Sciences

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Identification of depressive disorders risk factors still remains a relevant task, and the studies do not show sufficiently consistent data. The strongest risk factors are already known, but there is no general model of depression risk prediction and there are no calculators and predictive algorithms based on it. The results of attempts to develop complex predictive models and algorithms are considered in the paper. Advantages and limitations of available algorithms and calculators are discussed. It is shown that: 1) the most powerful risk factors are the same in different studies; 2) there is a great variety of both depression criteria and methods for measuring variables in predictive models and algorithms. That makes it impossible to compare the proposed models; 3) the way of information gathering may indirectly affect the findings: the answers given by subjects in the national study may differ from those that they might give in a specially organized study of depression. The absence of objective markers and using self-reports makes it difficult to make unambiguous conclusions from the presented studies; 4) the universality of predictive models for different cultures and especially Russian-speaking sample is questioned. Authors present a study aimed at developing a predictive algorithm for assessing depression risk among Russian-speaking adults based on an online health assessment system, that is collecting information about users history, current status and behavior. This online screening service will include identification of four groups of depression predictors and protective factors, as well as situational triggers that can contribute to depression development.

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A prediction algorithm for first onset of major depression in the general population: development and validation

Cited by 44 publications

References 49 publications

The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Waves 1 and 2: review and summary of findings

The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Waves 1 and 2: review and summary of findings

Clinical and Cost-Effectiveness of Personalized Tele-Based Coaching for Farmers, Foresters and Gardeners to Prevent Depression: Study Protocol of an 18-Month Follow-Up Pragmatic Randomized Controlled Trial (TEC-A)

Development Of A Method For Assessing Personalized Risks Of Depression

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