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Development of a multi-level assistive technology focused technology translation training program.

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Summary
This summary is machine-generated.

This study shows a multi-level training program effectively boosts technology transfer readiness for rehabilitation technologies. Completing more training levels led to better outcomes, including market success and awards.

Keywords:
Assistive technologymassive open online coursetechnology translationtraining course

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Area of Science:

  • Biomedical Engineering
  • Technology Transfer
  • Rehabilitation Technology

Background:

  • Developing and commercializing rehabilitation technologies presents unique challenges.
  • Effective training is crucial for researchers and entrepreneurs to navigate the technology transfer process.
  • The Quality Implementation Framework (QIF) provides a structured approach to implementing new initiatives.

Purpose of the Study:

  • To assess the effectiveness of a three-level training intervention based on the QIF.
  • To enhance the technology transfer readiness of teams developing rehabilitation technologies.
  • To evaluate the impact of training on market commercialization and related outcomes.

Main Methods:

  • A three-level training intervention was designed and implemented.
  • The Technology Transfer Readiness Assessment Tool (TTRAT) was used to measure progress.
  • Participant data was collected on training completion and subsequent achievements.

Main Results:

  • Teams completing at least two training levels showed significantly increased technology transfer readiness.
  • Higher training completion correlated with outcomes such as federal awards, FDA designations, and sales.
  • The intervention demonstrated feasibility with 32 teams starting and 6 completing all three levels.

Conclusions:

  • The multi-level training initiative is a promising strategy for improving technology transfer.
  • The QIF-based training effectively prepares researchers and entrepreneurs for commercialization.
  • Further research should explore demographic influences and refine training content based on identified gaps.