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Related Experiment Videos

How to translate science into community action

P Hamet1, A Petrásovits

  • 1Research Centre, Hôtel-Dieu de Montréal, University of Montreal, Quebec, Canada.

Journal of Human Hypertension
|February 1, 1996
PubMed
Summary

Scientific knowledge progresses from basic research to clinical research and community action. Integrated efforts among academia, government, and industry are crucial for effective translation and targeted interventions.

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Area of Science:

  • Translational science
  • Health services research
  • Biomedical research

Background:

  • Scientific knowledge typically flows sequentially from basic to clinical research, then to community action.
  • A multilateral interaction model is proposed, involving academia, government, and industry at all research stages.
  • Current community health actions rely on established clinical research, but future interventions can be more targeted.

Purpose of the Study:

  • To advocate for integrated, multilateral interactions between basic research, clinical research, and community action.
  • To highlight the roles of academia, government, and industry in scientific translation.
  • To explore future possibilities for targeted health interventions.

Main Methods:

  • Conceptual analysis and argumentation.
  • Review of the scientific knowledge translation process.
  • Discussion of stakeholder roles (academia, government, industry).

Main Results:

  • The study argues for a dynamic, multilateral interaction rather than a linear progression in scientific translation.
  • Integrated action among academia, government, and industry is essential for optimizing research translation.
  • Future interventions may target high-risk groups using genetically determined markers for prevention and treatment.

Conclusions:

  • An integrated approach involving academia, government, and industry is vital for advancing scientific knowledge translation.
  • Genetically determined markers are expected to enable more precise, targeted health interventions in the future.
  • The model supports a more efficient pathway from research discovery to community health impact.

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