Distributed Cognition: Understanding Complex Sociotechnical Informatics.

Clicks: 279
ID: 85058
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #68 of 170 articles by views in Studies in health technology and informatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 170 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Distributed cognition theory posits that our cognitive tasks are so tightly coupled to the environment that cognition extends into the environment, beyond the skin and the skull. It uses cognitive concepts to describe information processing across external representations, social networks and across different periods of time. Distributed cognition lends itself to exploring how people interact with technology in the workplace, issues to do with communication and coordination, how people's thinking extends into the environment and sociotechnical system architecture and performance more broadly. We provide an overview of early work that established distributed cognition theory, describe more recent work that facilitates its application, and outline how this theory has been used in health informatics. We present two use cases to show how distributed cognition can be used at the formative and summative stages of a project life cycle. In both cases, key determinants that influence performance of the sociotechnical system and/or the technology are identified. We argue that distributed cognition theory can have descriptive, rhetorical, inferential and application power. For evidence-based health informatics it can lead to design changes and hypotheses that can be tested.
Reference Key
furniss2019distributedstudies Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Furniss, Dominic;Garfield, Sara;Husson, Fran;Blandford, Ann;Franklin, Bryony Dean;
Journal Studies in health technology and informatics
Year 2019
DOI
10.3233/SHTI190113
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.