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How resilient were we in 2021? Results of a LinkedIn Survey including biomedical and pharmaceutical professionals using the Benatti Resiliency Model.

Songmao ZhengKarthik VenkatakrishnanBeth Benatti Kennedy
Published in: Clinical and translational science (2022)
Enhancing resiliency should elevate innovation and efficiency in biomedical research and development (R&D); however, compared with other professions, data on practice of resilience is lacking. Using the Benatti Resiliency Model (5 anchors: Well-Being, Self-Awareness, Brand, Connection, and Innovation), we surveyed professionals, including those in biomedical and pharmaceutical R&D. A structured LinkedIn questionnaire (March 16-May 23, 2021), surveyed each model anchor using five categories. One hundred fifty-eight participants (~6% student/trainee, 18%, 27%, and 49% in 1-5, 5-15 or >15 years post-terminal degree) took the survey (90 in biomedical and pharmaceutical R&D). Over 50% chose "always"/"often" across questions, except external influence or engagement. The question with one of the lowest "always" scores (~15%) was "I get feedback on my influence and impact in my career" in Brand, highlighting areas for leadership development and coaching. In the anchor of Well-being, nutrition and stress management also received some lowest "always" scores (~15% for both). Connection and Innovation scores trended slightly higher in biomedical and pharmaceutical R&D. No students/trainees chose "always" in Brand, indicating evolution of brand maturity over time. Self- and survey-assessed resiliency scores were associated (r s  = 0.37, p < 0.0001). Our survey yielded actionable insights on Resilience, including "best practices" through an open-ended question for one thing most useful to boost resilience in the survey and is the first application of the Benatti Model for crowdsourced research.
Keyphrases
  • cross sectional
  • healthcare
  • climate change
  • primary care
  • machine learning
  • social media
  • electronic health record
  • medical students
  • big data
  • stress induced
  • data analysis