What is METRICS?
The MEchanick Transculturalization Research and Innovation ConSortium (METRICS) is a decentralized, international research network to reduce the global burden of cardiometabolic-based chronic disease (CMBCD).
Our Mission
To address global gaps in research and practice that limit personalized care for diverse and vulnerable populations.
We achieve this through a dual mandate:
Sustainable Capacity Building:
Through our «train-the-trainer» paradigm, we nurture, empower, and champion the next generation of underrepresented, early-career physician-scientists and medical students, transforming them into independent research leaders directly within their home communities.
Advanced Transcultural Research:
We leverage advanced analytics to uncover how the biology of adversity, combined with genetic, environmental, behavioral, and structural factors, drives chronic metabolic disease.
Our Vision
To redefine global health research through equity, mentorship, and adaptive innovation.
METRICS envisions bias-free, transcultural health technologies and AI adaptable to any population worldwide
What We Study
Transculturalization & SDOH:
Investigating how cultural variations, migration, lifestyle, and social/structural determinants of health (SDOH) alter the expression of chronic diseases.
Advanced Analytics & Precision Medicine:
Utilizing tools like Bayesian network modeling, Clinical NLP, and big data to eliminate ethnocentric bias in risk prediction algorithms.
The CMBCD Framework:
Validating and implementing the Cardiometabolic-Based Chronic Disease model to shift care from late-stage intervention to early, culturally specific lifestyle and metabolic optimization.
Our Equity & Impact Dashboard
70+
Publications & Presentations
44.7%
Female Authorship (2x higher than in global cardiovascular literature)
41.5%
First-Authors who are Students or Early-Career Physician-Scientists
44.1%
Authors originating from and working within Adverse Environments
The Engine Behind METRICS
The Pyramidal Mentorship Model: Multi-Tiered, Self-Sustaining Knowledge Transfer
Traditional academic research often relies on a rigid, top-down hierarchy where capacity building is merely an afterthought. METRICS flips this script entirely. We utilize a structured, multi-level Pyramidal Mentorship Model that functions as a continuous «train-the-trainer» ecosystem.
In this model, knowledge transfer does not halt at a single layer; it cascades simultaneously across multiple generations of investigators:
Senior & Principal Investigators provide structural guardrails, methodology design, and global collaboration channels to early-career scholars.
Early-Career Physician-Scientists take on primary project leadership, actively translating high-level concepts while concurrently mentoring the layers below them.
Medical Students & Local Practitioners receive hands-on training in data collection, clinical NLP, and scientific writing, actively contributing to global literature as co-authors and future leaders.
The Result: A self-sustaining infrastructure where participation is driven by pure intrinsic motivation, ensuring that a researcher’s geographic or economic background never limits their scientific potential.
Crisis as an Epistemological Driver
Crisis as an Epistemological Driver
Where traditional, heavily funded research models pause during times of societal upheaval, METRICS accelerates. We do not view systemic adversity as a barrier to science; we treat crisis as a catalyst for innovation.
Our methodology was forged under some of the most demanding environmental constraints of the 21st century:
The Venezuelan Humanitarian Crisis: While facing severe localized resource scarcity, healthcare infrastructure strains, and mass migration, our network successfully mobilized over 300 regional collaborators to execute the ground-breaking EVESCAM epidemiological study. This experience pioneered our understanding of the «biology of adversity»—how chronic systemic stress accelerates cardiometabolic-based chronic disease (CMBCD).
The COVID-19 Pandemic: When global lockdowns threatened to freeze international collaborations, METRICS rapidly transitioned into a fully decentralized, highly structured virtual network. Monthly cross-border digital forums became our operational headquarters, expanding our reach to include active nodes across North America, South America, Europe, and Asia.
Our Philosophy: True scientific resilience cannot be bought with external institutional grants. By mastering decentralized, virtual infrastructure and anchoring our operations in collective motivation, METRICS has built an agile ecosystem capable of executing rigorous, peer-reviewed global health research in any hotspot, at any time.
Join the METRICS Journey
Whether you are a student discovering your research path or a global institution looking to reshape medical training, there is a place for your talent in our ecosystem.
Why Join METRICS?
Traditional academic models often gatekeep opportunities behind massive institutional funding or rigid hierarchies. At METRICS, we measure success by collective transformation and the individual growth of our researchers. By joining our decentralized global network, you don’t just participate in projects—you gain access to a battle-tested infrastructure built to elevate your scientific career, regardless of your geographic or economic background.
Empower Your Research Potential
Are you a medical student, resident, or early-career researcher passionate about transcultural health and advanced analytics? METRICS is designed to give you the keys to leadership from day one.
What you will gain:
Direct, Tiered Mentorship: Step directly into our «Pyramid of Researchers,» receiving active, hands-on guidance from senior investigators and peer-mentors who understand how to navigate the global scientific landscape.
Accelerated Authorship Opportunities: We actively invert standard academic hierarchies. In our consortium, students and early-career physicians represent over 41% of our first-authored publications. You will learn how to lead manuscripts, handle data, and see your name in high-impact, peer-reviewed literature.
Advanced Analytics Training: Gain practical experience utilizing cutting-edge tools—from Clinical NLP and Bayesian network modeling to validating transcultural chronic care metrics.
A Launchpad to Prestigious Institutions: Use your proven research output within METRICS to open doors to fellowships, advanced degrees, and career milestones at top-tier medical and public health institutions worldwide.
Ready to lead? “Are you a medical student or early-career researcher passionate about transcultural health? Join a global peer-mentorship network where you are empowered to lead.”
Replicate Success in Your Region
Are you an established investigator, public health advocate, or medical institution operating in an environment facing resource constraints, rapid migration, or systemic adversity? METRICS offers a proven blueprint to build sustainable local research capacity without relying on multi-million dollar external grants.
What we build together:
The «Train-the-Trainer» Framework: Learn how to implement our pyramidal training model to rapidly upscale the scientific output and writing capabilities of your own students and staff.
Cross-Border Data Integration: Connect your regional data streams into our global network, allowing for unprecedented comparative studies on the «biology of adversity» and social determinants of health.
Ethnocultural Validation: Partner with us to adapt and validate Cardiometabolic-Based Chronic Disease (CMBCD) risk scores and anthropometric cutoffs tailored precisely to your local population.
Unfunded Sustainability Architecture: Gain operational insights on how to keep research teams intensely motivated, unified, and productive using our virtual, decentralized infrastructure.
Let’s transform global health training together. “Partner with us to implement the METRICS framework or replicate our pyramidal training model in your region.”
METRICS Statements
Diversity, Equity, and Inclusion
We respect and interpret diversity, equity, and inclusion for all people as an advantage in our efforts to promote transcultural adaptations of healthcare and fulfill our mission. This not only applies to the care of our patients but also to how we interact with our colleagues and partners.
Policy statement on publications and Predatory journals
At METRICS, we are committed to maintaining the highest standards of EXCELLENCE in research AND COMMUNICATION TOWARD our mission of improving cardiometabolic health in diverse populations everywhere. As such, all our members are encouraged to report their research findings to peer-reviewed journals that follow the ICJME guidelines and are recognized for their Scientific credibility. By adhering to this practice, we ensure that our research and reporting are RIGOROUS and TRUSTWORTHY by colleagues in the global health community, thereby meaningfully contributing to the scientific knowledge BASE and upholding our commitment to ADVANCING GLOBAL CARDIOMETABOLIC HEALTH with the highest standards of quality, integrity, and impactful dissemination.
We encourage METRICS members to evaluate if the journal that they are planning to submit is indexed by MEDLINE/PubMed, and if the journal is open access, check if it is listed in the Directory of Open Access Journals.
Responsible Use of Artificial Intelligence (AI) in Research
We encourage our members to:
Adopt a critical approach when using generative AI, continuously learning responsible usage to achieve and maintain AI literacy.
Refrain from listing generative AI as an author, as it cannot assume responsibility or accountability for submitted work.
Ensure the appropriateness and accuracy of AI-generated outputs, acknowledging their potential for inaccuracies or biases.
Avoid using generative AI to analyze or formulate peer review critiques, following the «Use of Generative Artificial Intelligence Technologies is Prohibited for the NIH Peer Review Process» (Link).
Use AI tools like ChatGPT, Claude, or Gemini to assist in coding tasks (e.g., identifying errors, creating functions) and in enhancing article writing by improving grammar, conciseness, and clarity, ensuring AI is used responsibly, and outputs are critically evaluated while maintaining that the core content and authorship remain human-driven.