Collecting health-related data on the smart phone: mental models, cost of collection, and perceived benefit of feedback

Authors:
Daniel Gartenberg;Ross Thornton;Mortazavi Masood;Dustin Pfannenstiel;Daniel Taylor;Raja Parasuraman
Affiliations:
George Mason University, Fairfax, USA 22030-4444;George Mason University, Fairfax, USA 22030-4444;George Mason University, Fairfax, USA 22030-4444;George Mason University, Fairfax, USA 22030-4444;University of North Texas, Denton, USA;George Mason University, Fairfax, USA 22030-4444
Venue:
Personal and Ubiquitous Computing
Year:
2013

Citing 9
Cited 2

Charting past, present, and future research in ubiquitous computing

ACM Transactions on Computer-Human Interaction (TOCHI) - Special issue on human-computer interaction in the new millennium, Part 1
Pride and prejudice: learning how chronically ill people think about food

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Usability evaluation for mobile device: a comparison of laboratory and field tests

Proceedings of the 8th conference on Human-computer interaction with mobile devices and services
Neuroergonomics: The Brain at Work

Neuroergonomics: The Brain at Work
Computer Based Psychotherapy for Treatment of Depression and Anxiety

ECBS '07 Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems
Ubiquitous Psychotherapy

IEEE Pervasive Computing
Ubiquitous Computing for Capture and Access

Foundations and Trends in Human-Computer Interaction
Embedded capture and access: encouraging recording and reviewing of data in the caregiving domain

Personal and Ubiquitous Computing
Embedded assessment: overcoming barriers to early detection with pervasive computing

PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing

What health topics older adults want to track: a participatory design study

Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility
Implementation of the personal healthcare services on automotive environments

Personal and Ubiquitous Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We describe a mobile health application that collects data relevant to the treatment of insomnia and other sleep-related problems. The application is based on the principles from neuroergonomics, which emphasizes assessment of the brain's alertness system in everyday, naturalistic environments, and ubiquitous computing. Application benefits include the ability to incorporate both embedded data collection and retrospective manual data input--thus providing the user with a rewarding data access process. The retrospective data input feature was evaluated by comparing an older version of the retrospective editing interface with a newly developed one. The time course of user interactions was precisely measured by exporting time stamps of user interactions using the Google App Engine. We also developed models that closely fit the time course of user interactions using the Goals, Operators, Methods, and Selection rules (GOMS) modeling method. The user data and GOMS models demonstrated that the retrospective sleep tracking feature of the new interface was faster to use but that the retrospective habit tracking feature was slower. Survey results indicated that participants enjoyed using the newly developed interface more than the old interface for the assessment of both sleep and habits. These findings indicate that a mobile application should be designed not only to reduce the amount of time it takes a user to input data, but also to conform to the user's mental models of its behavior.