The role of interpersonal trauma and substance use in mental health: A large population-based study

Aas, Monica; Sideli, Lucia; Franceschini, Christian; Alameda, Luis; Trotta, Giulia; Coco, Gianluca Lo; Musetti, Alessandro; Schimmenti, Adriano

doi:10.1016/j.psychres.2023.115712

Psychiatry Research

2024

DOI: 10.1016/j.psychres.2023.115712

|View full text |Cite

The role of interpersonal trauma and substance use in mental health: A large population-based study

Monica Aas,

Lucia Sideli,

Christian Franceschini

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Potential suicide risk among the college student population: machine learning approaches for identifying predictors and different students’ risk profiles

Dagani,

Buizza,

Ferrari

et al. 2024

Psicol. Refl. Crít.

View full text Add to dashboard Cite

Background Suicide is one of the leading causes of death among young people and university students. Research has identified numerous socio-demographic, relational, and clinical factors as potential predictors of suicide risk, and machine learning techniques have emerged as promising ways to improve risk assessment. Objective This cross-sectional observational study aimed at identifying predictors and college student profiles associated with suicide risk through a machine learning approach. Methods A total of 3102 students were surveyed regarding potential suicide risk, socio-demographic characteristics, academic career, and physical/mental health and well-being. The classification tree technique and the multiple correspondence analysis were applied to define students’ profiles in terms of suicide risk and to detect the main predictors of such a risk. Results Among the participating students, 7% showed high potential suicide risk and 3.8% had a history of suicide attempts. Psychological distress and use of alcohol/substance were prominent predictors of suicide risk contributing to define the profile of high risk of suicide: students with significant psychological distress, and with medium/high-risk use of alcohol and psychoactive substances. Conversely, low psychological distress and low-risk use of alcohol and substances, together with religious practice, represented the profile of students with low risk of suicide. Conclusions Machine learning techniques could hold promise for assessing suicide risk in college students, potentially leading to the development of more effective prevention programs. These programs should address both risk and protective factors and be tailored to students’ needs and to the different categories of risk.

show abstract

Potential suicide risk among the college student population: machine learning approaches for identifying predictors and different students’ risk profiles

Dagani,

Buizza,

Ferrari

et al. 2024

Psicol. Refl. Crít.

View full text Add to dashboard Cite

show abstract

Herbal Cannabis and Depression: A Review of Findings Published over the Last Three Years

Haller

2024

Pharmaceuticals

View full text Add to dashboard Cite

Public perception contrasts scientific findings on the depression-related effects of cannabis. However, earlier studies were performed when cannabis was predominantly illegal, its production was mostly uncontrolled, and the idea of medical cannabis was incipient only. We hypothesized that recent changes in attitudes and legislations may have favorably affected research. In addition, publication bias against cannabis may have also decreased. To investigate this hypothesis, we conducted a review of research studies published over the last three years. We found 156 relevant research articles. In most cross-sectional studies, depression was higher in those who consumed cannabis than in those who did not. An increase in cannabis consumption was typically followed by an increase in depression, whereas withdrawal from cannabis ameliorated depression in most cases. Although medical cannabis reduced depression in most studies, none of these were placebo-controlled. In clinical studies published in the same period, the placebo also ameliorated depression and, in addition, the average effect size of the placebo was larger than the average effect size of medical cannabis. We also investigated the plausibility of the antidepressant effects of cannabis by reviewing molecular and pharmacological studies. Taken together, the reviewed findings do not support the antidepressant effects of herbal cannabis.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

The role of interpersonal trauma and substance use in mental health: A large population-based study

Cited by 2 publications

References 48 publications

Potential suicide risk among the college student population: machine learning approaches for identifying predictors and different students’ risk profiles

Potential suicide risk among the college student population: machine learning approaches for identifying predictors and different students’ risk profiles

Herbal Cannabis and Depression: A Review of Findings Published over the Last Three Years

Contact Info

Product

Resources

About