Police officers regularly face dangerous, high-stress scenarios exposing them to a variety of physical and mental health disorders. Emerging research provides innovative solutions that include biological resilience-building approaches to stress for public safety personnel (PSP) while they are at home. However, a Big Data pipeline is required to monitor improvement and to support these interventions. This paper utilizes a web-based, randomized control trial (RCT) in resilience building, designed for police officers, to expose the challenges that exist in acquiring data from participants while they are in their homes. Existing Big Data pipeline systems typically assume proximity between participants and researchers. This paper will outline the challenges surrounding the existing RCT framework and presents an advanced health analytical framework that can be extended to facilitate remote acquisition of physiological data.

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Challenges and Opportunities in a Big Data Pipeline for Resilience and Wellness Development: A Case Study for Police Training

  • Tina Cloutier,
  • Carolyn McGregor,
  • Judith P. Andersen

摘要

Police officers regularly face dangerous, high-stress scenarios exposing them to a variety of physical and mental health disorders. Emerging research provides innovative solutions that include biological resilience-building approaches to stress for public safety personnel (PSP) while they are at home. However, a Big Data pipeline is required to monitor improvement and to support these interventions. This paper utilizes a web-based, randomized control trial (RCT) in resilience building, designed for police officers, to expose the challenges that exist in acquiring data from participants while they are in their homes. Existing Big Data pipeline systems typically assume proximity between participants and researchers. This paper will outline the challenges surrounding the existing RCT framework and presents an advanced health analytical framework that can be extended to facilitate remote acquisition of physiological data.