Publications

News

Call for Applications: Work Group Leaders for Underrepresented in Medicine Initiative

Deadline for applications is September 13, 2019.

The Society of Teachers of Family Medicine is now accepting applications from interprofessional leaders to serve as Work Group Leaders on the Underrepresented in Medicine (URM) Initiative. The URM Initiative aims to:

  • Increase the percentage of URM family medicine faculty, and
  • Increase the number of solutions-focused, adaptable URM leaders within and across our healthcare system

The Work Group Leaders will lead small teams that will focus on achieving the objectives in one of the following four areas: 

  • Mentorship
    • Create opportunities for developing meaningful relationships that lead to career advancement and leadership within STFM and academic medicine
    • Develop mentors who have the skills to help URM students, residents, and faculty improve resiliency, satisfaction, and retention in academic family medicine
  • Leadership
    • Increase the number of URM family medicine faculty in leadership positions in academic medicine
    • Raise awareness of the structural barriers to URM achievement
  • URM Faculty Pipeline
    • Increase the number of URM students and URM family medicine residents with an interest in teaching
    • Increase the number of URM family medicine faculty
    • Increase the number of URM community preceptors in family medicine teaching sites who receive resources to improve their teaching skills
  • Scholarship
    • Increase the number of URM students, residents, and faculty who have the skills to produce scholarly research 

Responsibilities
Work Group Leaders will also serve as members of a new URM Oversight Committee and will participate in an initial 1½ day in-person planning/work session on February 24-25, 2020, and regular conference calls. The Oversight Committee will guide the progress of the work and communicate with STFM members and the STFM Foundation about the work being done by the teams in each focus area. Edgar Figueroa, MD, MPH, has been selected as chair of the URM Oversight Committee. He is the Director of Student Health at Weill Cornell Medical College and serves on the STFM Program Committee.

The four Work Group Leaders will lead the development of strategies, budgets, timeframes, and measures for their Focus Area. Each Work Group Leader will then lead a small team of 2-4 in the implementation of those strategies. STFM will provide administrative support and travel expenses will be reimbursed. Time commitment will be approximately 3 years.

Those interested in applying for Work Group Leader should have expertise one of the Focus Areas, relationships with others with expertise, and the time and energy to lead a team in successful implementation of the plan.

How to Apply
To be considered for the committee, click this survey link to submit your application by September 13, 2019. You’ll be asked to rank your interest in each focus area and upload a 1-page letter of interest with an overview of the skills and experience that make you a good candidate for the position.

Questions?
Email Emily Walters at ewalters@stfm.org.

 

Details

URM Definition:
The AAMC definition of underrepresented in medicine is: "those racial and ethnic populations that are underrepresented in the medical profession relative to their numbers in the general population."

Timeline:

  • Nov/Dec. 2019: First URM Oversight Committee conference call
  • Jan. 2020: Work Group Leaders identify core members of their work group
  • Feb. 24-25, 2020: 1½ day URM Oversight Committee meeting in Kansas City
  • June 2020: First progress reports due from work groups
  • Aug./Sept. 2020: In-person meetings of work groups
  • 2020 - 2022: Work continues with guidance from Oversight Committee
Ask a Question
AI Chatbot Tips

Tips for Using STFM's AI Assistant

STFM's AI Assistant is designed to help you find information and answers about Family Medicine education. While it's a powerful tool, getting the best results depends on how you phrase your questions. Here's how to make the most of your interactions:

1. Avoid Ambiguous Language

Be Clear and Specific: Use precise terms and avoid vague words like "it" or "that" without clear references.

Example:
Instead of: "Can you help me with that?"
Try: "Can you help me update our Family Medicine clerkship curriculum?"
Why this is important: Ambiguous language can confuse the AI, leading to irrelevant or unclear responses. Clear references help the chatbot understand exactly what you're asking.

2. Use Specific Terms

Identify the Subject Clearly: Clearly state the subject or area you need information about.

Example:
Instead of: "What resources does STFM provide?"
Try: "I'm a new program coordinator for a Family Medicine clerkship. What STFM resources are available to help me design or update clerkship curricula?"
Why this is better: Providing details about your role ("program coordinator") and your goal ("design or update clerkship curricula") gives the chatbot enough context to offer more targeted information.

3. Don't Assume the AI Knows Everything

Provide Necessary Details:The STFM AI Assistant has been trained on STFM's business and resources. The AI can only use the information you provide or that it has been trained on.

Example:
Instead of: "How can I improve my program?"
Try: "As a program coordinator for a Family Medicine clerkship, what resources does STFM provide to help me improve student engagement and learning outcomes?"
Why this is important: Including relevant details helps the AI understand your specific situation, leading to more accurate and useful responses.

4. Reset if You Change Topics

Clear Chat History When Switching Topics:

If you move to a completely new topic and the chatbot doesn't recognize the change, click the Clear Chat History button and restate your question.
Note: Clearing your chat history removes all previous context from the chatbot's memory.
Why this is important: Resetting ensures the AI does not carry over irrelevant information, which could lead to confusion or inaccurate answers.

5. Provide Enough Context

Include Background Information: The more context you provide, the better the chatbot can understand and respond to your question.

Example:
Instead of: "What are the best practices?"
Try: "In the context of Family Medicine education, what are the best practices for integrating clinical simulations into the curriculum?"
Why this is important: Specific goals, constraints, or preferences allow the AI to tailor its responses to your unique needs.

6. Ask One Question at a Time

Break Down Complex Queries: If you have multiple questions, ask them separately.

Example:
Instead of: "What are the requirements for faculty development, how do I register for conferences, and what grants are available?"
Try: Start with "What are the faculty development requirements for Family Medicine educators?" Then follow up with your other questions after receiving the response.
Why this is important: This approach ensures each question gets full attention and a complete answer.

Examples of Good vs. Bad Prompts

Bad Prompt

"What type of membership is best for me?"

Why it's bad: The AI Chat Assistant has no information about your background or needs.

Good Prompt

"I'm the chair of the Department of Family Medicine at a major university, and I plan to retire next year. I'd like to stay involved with Family Medicine education. What type of membership is best for me?"

Why it's good: The AI Chat Assistant knows your role, your future plans, and your interest in staying involved, enabling it to provide more relevant advice.

Double Check Important Information

While the AI Chat Assistant is a helpful tool, it can still produce inaccurate or incomplete responses. Always verify critical information with reliable sources or colleagues before taking action.

Technical Limitations

The Chat Assistant:

  • Cannot access external websites or open links
  • Cannot process or view images
  • Cannot make changes to STFM systems or process transactions
  • Cannot access real-time information (like your STFM Member Profile information)

STFM AI Assistant
Disclaimer: The STFM Assistant can make mistakes. Check important information.