Objective: Due to little knowledge regarding the contextual factors related to cannabis use, we aimed to provide descriptive statistics regarding contextual factors related to use and examine the predictive ability of contextual factors.
Method: We included college student participants ( = 5,700; male = 2,893, female = 3,702, other gender identity = 48, missing = 57) from three multi-site studies in our analyses. We examined the means and standard deviations of contextual factors related to cannabis use (social context/setting, form of cannabis, route of administration, source of purchase, and proxies of use). Additionally, we tested the predictive ability of the contextual factors on cannabis use consequences, protective behavioral strategies, and severity of cannabis use disorder, via an exploratory machine learning model (random forest).
Results: Descriptive statistics and the correlations between the contextual factors and the three outcomes are provided. Exploratory random forests indicated that contextual factors may be helpful in predicting consequences and protective behavioral strategies and especially useful in predicting the severity of cannabis use disorder.
Conclusions: Contextual factors of cannabis use warrants further exploration, especially considering the difficulty in assessing dosage when individuals are likely to consume in a group context. We propose considering measuring contextual factors along with use in the past 30 days and consequences of use.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11831902 | PMC |
| http://dx.doi.org/10.26828/cannabis/2024/000225 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Spatial prediction of immunity gaps during a pandemic to inform decision making: A geostatistical case study of COVID-19 in Dominican Republic.
Trop Med Int Health
March 2025
UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Background: To demonstrate the application and utility of geostatistical modelling to provide comprehensive high-resolution understanding of the population's protective immunity during a pandemic and identify pockets with sub-optimal protection.
Methods: Using data from a national cross-sectional household survey of 6620 individuals in the Dominican Republic (DR) from June to October 2021, we developed and applied geostatistical regression models to estimate and predict Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spike (anti-S) antibodies (Ab) seroprevalence at high resolution (1 km) across heterogeneous areas.
Results: Spatial patterns in population immunity to SARS-CoV-2 varied across the DR.
Evolution of intimate partner violence impacts from cash transfers, food transfers, and behaviour change communication: Mixed-method experimental evidence from a nine-year post-programme follow-up in Bangladesh.
Soc Sci Med
February 2025
London School of Hygiene and Tropical Medicine, London, United Kingdom.
Cash or food transfers can reduce intimate partner violence (IPV), but knowledge gaps remain on how impacts evolve over time, and the role of complementary 'plus' activities and contextual factors. We conducted a mixed-method analysis of how the Transfer Modality Research Initiative in Bangladesh affected IPV over time. The programme was implemented from 2012 to 2014, following a randomised controlled trial (RCT) design, across Northern and Southern Bangladesh.
View Article and Find Full Text PDFCancer gene identification through integrating causal prompting large language model with omics data-driven causal inference.
Brief Bioinform
March 2025
School of Artificial Intelligence, Jilin University, 3003 Qianjin Street, Changchun 130012, Jilin Province, China.
Identifying genes causally linked to cancer from a multi-omics perspective is essential for understanding the mechanisms of cancer and improving therapeutic strategies. Traditional statistical and machine-learning methods that rely on generalized correlation approaches to identify cancer genes often produce redundant, biased predictions with limited interpretability, largely due to overlooking confounding factors, selection biases, and the nonlinear activation function in neural networks. In this study, we introduce a novel framework for identifying cancer genes across multiple omics domains, named ICGI (Integrative Causal Gene Identification), which leverages a large language model (LLM) prompted with causality contextual cues and prompts, in conjunction with data-driven causal feature selection.
View Article and Find Full Text PDFThe Digital Media-use Effects (d-MUsE) Model: A comprehensive framework for exploring/studying functional and dysfunctional effects on adolescent wellbeing.
J Behav Addict
March 2025
1General Psychology: Cognition, University of Duisburg-Essen, Duisburg, Germany.
Background And Aims: Digital media have become a fundamental aspect of daily life for children and adolescents, influencing cognitive, emotional, and social development. The present work explores the dual nature of digital media use, identifying both positive and negative impacts on well-being and development.
Methods: A comprehensive review of existing literature was conducted to explore the interplay between digital media use and its effects on child and adolescent well-being.
Cathodal Transcranial Direct Current Stimulation Does Not Change Implicit Associations Against Alcohol in Alcohol Use Disorder: A Preregistered Clinical Trial.
Addict Biol
March 2025
Department of Psychiatry and Psychotherapy, Neurophysiology and Interventional Neuropsychiatry, University of Tübingen, Tübingen, Germany.
Addictive behaviour is shaped by the dynamic interaction of implicit, bottom-up and explicit, top-down cognitive processes. In alcohol use disorder (AUD), implicit alcohol-related associations have been shown to predict increased subsequent alcohol consumption and are linked to the risk of relapse. Explicit cognitive processes, exerting prefrontal top-down control, are particularly significant during the critical period following the decision to abstain.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!