Methamphetamine use is increasing in the U.S. and in Missouri, as are the number of deaths associated with its use. Many systemic and mental health issues are associated with methamphetamine use or methamphetamine use disorder (MUD). Given the range of health issues associated with methamphetamine use or MUD, a collaborative approach to the care of patients can improve outcomes. This article provides an overview of a collaborative approach to caring for patients using or have used methamphetamine, from the perspective of the primary care, behavioral and dental clinician.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9762214PMC

Publication Analysis

Top Keywords

collaborative approach
12
caring patients
8
health issues
8
issues associated
8
associated methamphetamine
8
methamphetamine
5
patients methamphetamines
4
methamphetamines interprofessional
4
interprofessional collaborative
4
approach methamphetamine
4

Similar Publications

Background: Cardiovascular disease (CVD) morbidity and mortality is increasing in Africa, largely due to undiagnosed and untreated hypertension. Approaches that leverage existing primary health systems could improve hypertension treatment and reduce CVD, but cost-effectiveness is unknown. We evaluated the cost-effectiveness of population-level hypertension screening and implementation of chronic care clinics across eastern, southern, central, and western Africa.

View Article and Find Full Text PDF

Automating alloy design and discovery with physics-aware multimodal multiagent AI.

Proc Natl Acad Sci U S A

January 2025

Laboratory for Atomistic and Molecular Mechanics, Massachusetts Institute of Technology, Cambridge, MA 02139.

The design of new alloys is a multiscale problem that requires a holistic approach that involves retrieving relevant knowledge, applying advanced computational methods, conducting experimental validations, and analyzing the results, a process that is typically slow and reserved for human experts. Machine learning can help accelerate this process, for instance, through the use of deep surrogate models that connect structural and chemical features to material properties, or vice versa. However, existing data-driven models often target specific material objectives, offering limited flexibility to integrate out-of-domain knowledge and cannot adapt to new, unforeseen challenges.

View Article and Find Full Text PDF

Optimal management of adult congenital heart disease (ACHD) requires a multidisciplinary team (MDT) approach, fostering a collaborative culture over an individualistic approach. Within this framework, subspecialty-trained radiologists provide crucial imaging expertise, supporting cardiologists, surgeons, and interventional cardiologists in diagnoses, treatment planning, and follow-up evaluations. Advanced imaging tools and a nuanced understanding of surgical and interventional procedures enable radiologists to provide valuable insights to clinicians.

View Article and Find Full Text PDF

Chain of Risks Evaluation (CORE): A framework for safer large language models in public mental health.

Psychiatry Clin Neurosci

January 2025

Shanghai Artificial Intelligence Laboratory, Shanghai, China.

Large language models (LLMs) have gained significant attention for their capabilities in natural language understanding and generation. However, their widespread adoption potentially raises public mental health concerns, including issues related to inequity, stigma, dependence, medical risks, and security threats. This review aims to offer a perspective within the actor-network framework, exploring the technical architectures, linguistic dynamics, and psychological effects underlying human-LLMs interactions.

View Article and Find Full Text PDF

Background: Post-activation performance enhancement (PAPE) has demonstrated efficacy in acutely improving athletic performance. However, its distinction from general warm-up (GW) effects remains ambiguous, and experimental designs adopted in most PAPE studies exhibit important limitations.

Objectives: The aims of this work are to (i) examine the effects of research methodology on PAPE outcomes, (ii) explore PAPE outcomes in relation to comparison methods, performance measures, GW comprehensiveness, recovery duration, participants' characteristics, conditioning activity (CA) parameters, and (iii) make recommendations for future PAPE experimental designs on the basis of the results of the meta-analysis.

View Article and Find Full Text PDF

Want 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!