Toward a generalized developmental model of psychopathological liabilities and psychiatric disorders

Blanco, Carlos; Wall, Melanie M.; Hoertel, Nicolas; Krueger, Robert F.; Olfson, Mark

doi:10.1017/s0033291721005468

Cited by 5 publications

(1 citation statement)

References 42 publications

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“…Interventions at earlier stages of the cascade may be more likely to decrease down stream risk for SUD. Furthermore, to the extent that risk factors for SUD are shared with other psychiatric disorders, interventions on those shared factors can have spillover effects in preventing other disorders 77 .…”

Section: Risk Factorsmentioning

confidence: 99%

Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention

Volkow

Blanco

2023

World Psychiatry

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Substance use disorders (SUDs) are highly prevalent and exact a large toll on individuals' health, well-being, and social functioning. Long-lasting changes in brain networks involved in reward, executive function, stress reactivity, mood, and self-awareness underlie the intense drive to consume substances and the inability to control this urge in a person who suffers from addiction (moderate or severe SUD). Biological (including genetics and developmental life stages) and social (including adverse childhood experiences) determinants of health are recognized factors that contribute to vulnerability for or resilience against developing a SUD. Consequently, prevention strategies that target social risk factors can improve outcomes and, when deployed in childhood and adolescence, can decrease the risk for these disorders. SUDs are treatable, and evidence of clinically significant benefit exists for medications (in opioid, nicotine and alcohol use disorders), behavioral therapies (in all SUDs), and neuromodulation (in nicotine use disorder). Treatment of SUDs should be considered within the context of a Chronic Care Model, with the intensity of intervention adjusted to the severity of the disorder and with the concomitant treatment of comorbid psychiatric and physical conditions. Involvement of health care providers in detection and management of SUDs, including referral of severe cases to specialized care, offers sustainable models of care that can be further expanded with the use of telehealth. Despite advances in our understanding and management of SUDs, individuals with these conditions continue to be stigmatized and, in some countries, incarcerated, highlighting the need to dismantle policies that perpetuate their criminalization and instead develop policies to ensure support and access to prevention and treatment.

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Section: Risk Factorsmentioning

confidence: 99%

Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention

Volkow

Blanco

2023

World Psychiatry

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Development and Validation of a Simple Risk Calculator for Alcohol-Related Adverse Outcomes: Results from a Composite Scale Approach in a Nationally Representative Sample

Hoertel,

Dosquet,

Sánchez-Rico

et al. 2024

Int J Ment Health Addiction

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We tested how 5 simple variables, routinely collected in primary care (i.e., the 3 AUDIT-C items, age, and sex), could constitute a clinician-friendly risk calculator tool of the 3-year risk of several alcohol-related adverse outcomes (i.e., alcohol use disorder, withdrawal symptoms, occurrence of tremors or seizures, and alcohol related interpersonal relationship problems, legal problems, and psychological problems) among non-alcohol-dependent individuals consuming alcohol. Data were drawn from a nationally representative sample of US adults, the National Epidemiologic Survey on Alcohol and Related Conditions (wave 1, 2001–2002; wave 2, 2004–2005). We used scaled and rounded composite scoring systems to combine information derived from these predictors and quantify the risks for each subject. Analyses were limited to 16,710 respondents without a lifetime history of alcohol use disorder who completed both interviews and had consumed alcohol during the year prior to wave 1 (development sample N = 8355, validation sample N = 8355). The risk equations calibrated well (Hosmer and Lemeshow test p values ≥ 0.072) and showed good predictive values (C indices ranging from 0.727 to 0.872) in the validation sample. This risk calculator can be clinically useful in primary care for identification of at-risk individuals, encourage respondents to reduce their drinking, and improve prevention.

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Antecedents and risk factors for borderline personality disorder: Etiopathogenic models based on a multi-level meta-analysis

Cavicchioli,

Scalabrini,

Vai

et al. 2024

Journal of Affective Disorders

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Toward a generalized developmental model of psychopathological liabilities and psychiatric disorders

Cited by 5 publications

References 42 publications

Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention

Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention

Development and Validation of a Simple Risk Calculator for Alcohol-Related Adverse Outcomes: Results from a Composite Scale Approach in a Nationally Representative Sample

Antecedents and risk factors for borderline personality disorder: Etiopathogenic models based on a multi-level meta-analysis

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