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Community Health Worker Training in Clinical Research

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    This research training provides community health workers with a basic level of competency in clinical research to better advocate for their communities’ health needs and enhance the quality and effectiveness of their work. These courses aim to enhance the knowledge and skills of community health workers, patient navigators, and community-based research coordinators to extend beyond the clinical settings and address the growing need to decentralize our approach to recruitment of underserved populations in research for our communities. Note that the total Seminar 1 and Seminar 2 series includes 29 distinct modules (some may have quizzes) offered asynchronously for internal and external audiences. Seminar 1: Clinical Research 101, consists of 21 modules, and Seminar 2: Research History & the Importance of Diversity and Equity in Research, consists of 8 modules. Topics include the fundamentals of clinical research, scientific concepts, and research design, research ethics, study management, clinical study operations, and communications and teamwork, as well as the importance of diversity and equity in research and the barriers to participation. You must complete all the modules, the related quizzes, and a short survey at the end of Seminar 2 Module 8 in order for your to gain credit for this learning event. Follow these instructions to access the modules: 1. Click Link to Training to access the training modules. 2. Enter your email and click “Send Registration Email” 3. A registration email will be sent to your mailbox with a link to create a password. Open the email and click the link to create a password. 4. Once the password is created, you will be logged in to the NYULH RISE Platform 5. You should see the NYU Langone Health CHW Research Training once you log in. Click the course and navigate through the modules. It will start with Seminar 1, Module 1 6. If you plan to leave the course and come back at another time, please use the following link, which will take you directly to the registration page to enter your email and password: https://nyu-langone-health.rise.com/ 7. At the conclusion of the final module, you will be provided with a certificate of completion and directed to a REDCap exit survey to provide your feedback on the course

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    Michigan Institute for Clinical & Health Research (University of Michigan)

    Michigan Institute for Clinical Health Research (MICHR)
    1600 Huron Parkway, Building 400, Ann Arbor, MI 48109
    [email protected]

    © 2026 Regents of the University of Michigan.

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    Characteristics of a Translational Scientist

    BOUNDARY CROSSER: Breaks down disciplinary silos and collaborates with others across research areas and professions to collectively advance the development of a medical intervention.

    DOMAIN EXPERT: Possesses deep disciplinary knowledge and expertise within one or more domains of the translational science spectrum ranging from basic to clinical to public health research and domains in between.

    TEAM PLAYER: Practices a team science approach by leveraging the strengths and expertise and valuing the contributions of all players on the translational science team.

    PROCESS INNOVATOR: Seeks to better understand the scientific and operational principles underlying the translational process, and innovates to overcome bottlenecks and accelerate that process.

    SKILLED COMMUNICATOR: Communicates with understanding with all stakeholders in the translational process across diverse social, cultural, economic and scientific backgrounds, including patients and community members.

    SYSTEMS THINKER: Evaluates the complex external forces, interactions and relationships impacting the development of medical interventions, including patient needs and preferences, regulatory requirements, current standards of care, and market and business demands.

    RIGOROUS RESEARCHER: Conducts research at the highest levels of rigor and transparency, possesses strong statistical analysis skills, and designs research projects to maximize reproducibility.