Journal of Medical Internet Research (Nov 2021)
The Sociological Perspective of Users’ Invisible Work: A Qualitative Research Framework for Studying Digital Health Innovations Integration
Abstract
BackgroundWhen new technology is integrated into a care pathway, it faces resistance due to the changes it introduces into the existing context. To understand the success or failure of digital health innovations, it is necessary to pay attention to the adjustments that users must perform to make them work, by reshaping the context and sometimes by altering the ways in which they perform activities. This adaptation work, most of which remains invisible, constitutes an important factor in the success of innovations and the ways in which they transform care practices. ObjectiveThis work aims to present a sociological framework for studying new health technology uses through a qualitative analysis of the different types of tasks and activities that users, both health professionals and patients, must perform to integrate these technologies and make them work in their daily routine. MethodsThis paper uses a three-part method to structure a theoretical model to study users’ invisible work. The first part of the method includes a thematic literature review, previously published by one of the coauthors, of major sociological studies conducted on digital health innovations integration into existing care organizations and practices. The second part extends this review to introduce definitions and applications of the users’ invisible work concept. The third part consists of producing a theoretical framework to study the concept according to the different contexts and practices of the users. ResultsThe paper proposes four dimensions (organizational, interactional, practical, and experiential), each composed of a set of criteria that allow a comparative analysis of different users’ work according to different health technologies. ConclusionsThis framework can be applied both as an analytical tool in a research protocol and as an agenda to identify less visible adoption criteria for digital health technologies.