Social Desirability Bias and Engagement in Systems Designed for Long-Term Health Tracking

In the coming years, remote health monitoring is an area that is expected to grow significantly. Systems designed to follow-up with patients at home can be used not only to reduce visits to the doctor but also to augment the face-to-face interactions between patients and physicians. These systems could also provide much-needed care to the millions of people living in rural areas.;While many researchers are investigating remote sensing technologies, the use of self-report in technological systems for long-term health monitoring remains a relatively understudied area. In this thesis, we investigate two main challenges in building systems designed for the collection of self-reported health data: 1) maximizing the accuracy of the reported data, and 2) maintaining user engagement with the system over potentially long periods of time.;We describe results from three field trials of systems designed to collect self-reported health data. Results indicate that personified interfaces and designs that include personalized health messages may negatively impact data quality. Results also indicated that, despite incentives designed to promote use, the time commitment needed to interact with the system predicts the likelihood of continued use.