The NIH BEST Programs have a research agenda and are conducting a series of experiments to identify new and innovative approaches to broaden career and professional development for graduate and postdoctoral training. These training programs are designed to reflect the range of available career options required for a strong biomedical, behavioral, social and clinical research enterprise.

Question

What are effective ways to broaden career and professional development for biomedial PhD students and postdoctoral scientists?

Hypothesis

Innovative training paradigms used to encourage early career planning, exploration, and exposure to scientific research and science-related careers will broaden PhD and postdoctoral career education and decisions. Knowledge and exposure to a range of scientific career options will allow for a more prepared transition to successful, long-term career employment to preserve a strong and competitive U.S. biomedical research workforce.

Experiments

To test this hypothesis, the NIH BEST Programs are employing various models of participation and programming. NIH BEST programs are also exploring ways to build external partnerships and increase faculty engagement.

Target Population

PhD Students Only
Wayne State University (emphasis on International Scientists)

PhD & Postdoctoral Scientists
Boston University School of Medicine, Cornell University, Emory University and Georgia Institute of Technology, Michigan State University, New York University School of Medicine (emphasis on postdoctoral scientists), Rutgers University, University of California Davis, University of California San Francisco, University of California Irvine, University of Colorado Denver|Anschutz Medical Campus, University of Chicago, University of Massachusetts Medical School, University of North Carolina Chapel Hill, University of Rochester, Vanderbilt University School of Medicine, Virginia Polytechnic Institute and State University

Scientists Across Institutions
Emory University and Georgia Institute of Technology collaborate to form the Atlanta BEST program that supports trainees from both schools.

Participation Model

Cohort Model: a program with focused groups of scientists that fosters peer-to-peer mentoring and team building
Emory University and Georgia Institute of Technology, Michigan State University, University of California Davis, University of California San Francisco, University of North Carolina Chapel Hill, University of Rochester

Broad Exposure Model: All scientists are welcome to participate in all BEST-related activities.
Boston University School of Medicine, Cornell University, New York University School of Medicine, University of California Davis, University of California Irvine, University of Colorado Denver|Anschutz Medical Campus, University of Chicago, University of Massachusetts Medical School, Vanderbilt University School of Medicine, Virginia Polytechnic Institute and State University, Wayne State University

Alumni Mentoring Model: special emphasis on career-specific alumni serving as mentors for BEST scientists
University of California Irvine, Rutgers University

Programming

Career Development
Self-efficacy, career exploration, career decision making, individual development plans

Professional Development
Writing & presenting, networking, teamwork & leadership, wellness, professional readiness, job search skills

Experiential Learning
Site visits, job shadowing, internships

Mentoring
Peer and small group mentoring, career coaching, mentoring by faculty, external career mentorship

External Partnerships

The BEST programs are committed to establishing long-lasting relationships with partners within and outside of scientific disciplines and within and outside of their affiliate institutions. These partnerships help PhD and postdoctoral trainees broaden their exposure to find a suitable career. Examples of partners include alumni, peer institutions, other schools or programs, and career consultant companies.

Faculty Engagement

The BEST programs recognize faculty engagement and support as critical determinants for success. Some programs have developed approaches to inform and enlist support from faculty, such as informational meetings and focus groups, assessing faculty needs, faculty approval for student and postdoctoral scholar participation, and faculty participation in BEST program curriculum development and mentoring.

Results

The NIH, in partnership with the 17 awardee institutions, is doing a long-term study to identify, document, and disseminate best practices from the BEST program. This groundbreaking study will ultimately advance biomedical research training programs for graduate students and postdoctoral scientists. The NIH has contracted Windrose Vision, LLC, to conduct the national cross-site evaluation and work with awardees to support this study.

The NIH national cross-site evaluation will focus on the following outcomes:

  1. Changes in understanding of career opportunities, confidence to make career decisions, and attitudes towards career opportunities
  2. Time to desired career opportunities beyond the training period with opportunities for subsequent career growth
  3. Ability to sustain the BEST program after the NIH funding ends

The national cross-site evaluation is using a multi-method approach. It employs and draws on the strengths of both quantitative (survey research) and qualitative (telephone interviews) techniques.

Online Surveys

Population

  • Graduate students
  • Postdoctoral scientists

 

Information collected

  • Understanding of career paths
  • Support for pursuing desired career paths
  • Impact of career development activities
  • Publications
  • Financial support
  • Information about degree
  • Graduate school information
  • Employment status
  • Employment history
  • Background and demographic information

 

Frequency

  • Entry into evaluation study
  • Mid-way through study (graduate students only)
  • Exit from institution (graduate students)
  • Change in position for postdoctoral scientists (no longer holds postdoctoral scientist position, or no longer employed by institution)
  • Follow-up surveys at 2, 6, 10, and 15 years after Exit

 

Purpose

  • Assess changes in understanding of career opportunities
  • Assess confidence to make career decisions
  • Assess attitudes towards career opportunities
  • Assess career paths
Institutional Data Reporting

Population

  • Point of Contact at each Awardee Institution

 

Information collected

  • Description of BEST program activities
  • Graduate student and postdoctoral scientist participation in BEST program activities
  • Faculty attitudes
  • Elapsed time to doctorate (including leaves of absence and enrollment lapses)
  • Postdoctoral training for Ph.D. recipients (immediate job placement or post-doctoral activity)
  • Length of time in postdoctoral training
  • Career paths of Ph.D. recipients (research intensive, research-related, other)

 

Frequency

  • Section 1: submitted once per year (individual data)
  • Section 2: submitted once per year (aggregate data)
  • Section 3: submitted once in 2015 (aggregate data from five years prior to BEST award)
  • Section 4: submitted once in year four of the BEST award (aggregate data)

 

Purpose

  • Document program characteristics, components, and activities
  • Assess the level of participation by graduate students and postdoctoral scientists
  • Document data gathered by the local evaluation
  • Assess elapsed time to doctorate and time in postdoctoral training.
Program Staff Telephone Interviews

Population

  • Principal Investigators
  • Co-Principal Investigators
  • Local Evaluator
  • Program Directors and Managers of BEST program

 

Information collected

  • Successes, challenges, and lessons-learned
  • Plans to extend curricula and activities at the department and institutional level beyond the funding period
  • Local evaluation activities

 

Frequency

  • Once per year

 

Purpose

  • Document efforts toward sustainability of BEST activities after the NIH funding ends
  • Identify contextual factors unique to each site
  • Provide context for the statistical data analysis