Downloads provided by UsageCounts
TRIFoRM brought together computer science, health science, social science and engineering to explore the trusting beliefs of users of IT systems, looking at factors that influence individual trust of systems and ways to model those factors and trust levels. The TRIFoRM team, based across three different faculties at the University of Southampton, focused particularly on healthcare technologies for monitoring chronic conditions. During the project, the team brought together existing theoretical work on trust, before interviewing people who may use or provide healthcare monitoring technology to understand what was important to them as individuals. Analysis of the interviews let the team identify possible threats to trust of the technology and controls to mitigate those threats. Two major threats were identified. The first is User Disengagement – if the medical team don’t adopt the technology, then patients will lose interest in that technology. The second is an Unusable System – causing all users, clinicians as well as patients, to lose interest and disengage. User Disengagement can be mitigated with appropriate training and support; Unusable System can be helped with appropriate design expertise. The team also identified two key issues. Firstly, it is clear that people using a monitoring technology to manage pain are more likely to take risks and tolerate faults: this means that those people are more vulnerable than otherwise. This has clear implications for the need to be cognisant of user motivation and application domain when designing this kind of system. The second issue is the importance of relationships. The people we interviewed who might use monitoring technology were concerned about whether such technology might change their relationship with healthcare providers, as well as with whether healthcare providers themselves trust the technology.
This is a report submitted as an IT as a Utility Network+ working paper
Technology acceptance, Trust in technology, Qualitative methods, Rheumatoid arthritis
Technology acceptance, Trust in technology, Qualitative methods, Rheumatoid arthritis
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 3 | |
| downloads | 2 |

Views provided by UsageCounts
Downloads provided by UsageCounts