Tensions in designing capture technologies for an evidence-based care community

Abstract

Evidence-based care is an increasingly popular process for long term diagnosis and monitoring of education and healthcare disabilities. Because this evidence must also be collected in everyday life, it is a technique that can greatly benefit from automated capture technologies. These solutions, however, can raise significant concerns about privacy, control, and surveillance. In this paper, we present an analysis of these concerns with regard to evidence-based care. This analysis underscores the need to consider community-based risk and reward analyses in addition to the traditionally used analyses for individual users when designing socially appropriate technologies.