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<p>While improvisation is a frequent practice for emergency responders during their interventions, it remains an informal skill—one that is not yet systematically incorporated into training programs. Although techniques to foster creativity exist, there are currently no structured methods to guide healthcare practitioners in devising makeshift solutions when conventional resources are unavailable. Using an analysis of cognitive creative processes, we developed the CAP’ (Constraints, Affordances, Performance) thinking technique. This technique aims to clarify the constraints, affordances, and performance that typify a care situation. The application of the CAP’ technique to an observed case of improvisation leading to a frugal innovation in a dispensary in Madagascar shows that this technique can track the inventor’s reasoning and structure a relevant request posed to a generative AI, helping to discover alternative and original solutions in highly atypical environments.</p>

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CAP’: a thinking technique to facilitate improvisation in healthcare, illustrated by a case study in Madagascar

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月12日

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  • Rémi Girerd,
  • Belinda Ferrere,
  • Lise Peipoch,
  • Jean Pactelin Sely,
  • Anaïs Godeluck,
  • Thierry Morineau

摘要

While improvisation is a frequent practice for emergency responders during their interventions, it remains an informal skill—one that is not yet systematically incorporated into training programs. Although techniques to foster creativity exist, there are currently no structured methods to guide healthcare practitioners in devising makeshift solutions when conventional resources are unavailable. Using an analysis of cognitive creative processes, we developed the CAP’ (Constraints, Affordances, Performance) thinking technique. This technique aims to clarify the constraints, affordances, and performance that typify a care situation. The application of the CAP’ technique to an observed case of improvisation leading to a frugal innovation in a dispensary in Madagascar shows that this technique can track the inventor’s reasoning and structure a relevant request posed to a generative AI, helping to discover alternative and original solutions in highly atypical environments.