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Comprehensive Personal Health Knowledge Graph for Effective Management and Utilization of Personal Health Data
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This article discusses novel research methods used to examine how Augmented Reality (AR) can be utilized to present “omic” (i.e., genomes, microbiomes, pathogens, allergens) information to non-expert users. While existing research shows the potential of AR as a tool for personal health, methodological challenges pose a barrier to the ways in which AR research can be conducted. There is a growing need for new evaluation methods for AR systems, especially as remote testing becomes increasingly popular. In this article, we present two AR studies adapted for remote research environments in the context of personal health. The first study ( n = 355) is a non-moderated remote study conducted using an AR web application to explore the effect of layering abstracted pathogens and mitigative behaviors on a user, on perceived risk perceptions, negative affect, and behavioral intentions. This study introduces methods that address participant precursor requirements, diversity of platforms for delivering the AR intervention, unsupervised setups, and verification of participation as instructed. The second study ( n = 9) presents the design and moderated remote evaluation of a technology probe, a prototype of a novel AR tool that overlays simulated timely and actionable environmental omic data in participants' living environment, which helps users to contextualize and make sense of the data. Overall, the two studies contribute to the understanding of investigating AR as a tool for health behavior and interventions for remote, at-home, empirical studies.more » « less
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Older adults often rely on information provided during doctors’ visits or online to manage their health but can experience challenges accessing this information at home. Recently, conversational assistants are being explored to aid navigation of health information included in online portals, but we still know little about users’ perceptions of using these tools for managing personal health information. In this paper, we conducted a wizard-of-oz study to better understand older adults’ perceptions of a conversational assistant, MIHA, to help with navigating personal health information. Participants saw value in using a tool such as MIHA to help facilitate access to their personal health information and to help them become more engaged in their health. Participants believed MIHA’s features helped build confidence in the responses returned, but made suggestions for improving the interactions. We share insights of potential uses and design implications for conversational assistants that help older adults navigate personal health information.more » « less
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Background: Personal health technologies, including wearable tracking devices and mobile apps, have great potential to equip the general population with the ability to monitor and manage their health. However, being designed for sighted people, much of their functionality is largely inaccessible to the blind and low-vision (BLV) population, threatening the equitable access to personal health data (PHD) and health care services. Objective: This study aims to understand why and how BLV people collect and use their PHD and the obstacles they face in doing so. Such knowledge can inform accessibility researchers and technology companies of the unique self-tracking needs and accessibility challenges that BLV people experience. Methods: We conducted a web-based and phone survey with 156 BLV people. We reported on quantitative and qualitative findings regarding their PHD tracking practices, needs, accessibility barriers, and work-arounds. Results: BLV respondents had strong desires and needs to track PHD, and many of them were already tracking their data despite many hurdles. Popular tracking items (ie, exercise, weight, sleep, and food) and the reasons for tracking were similar to those of sighted people. BLV people, however, face many accessibility challenges throughout all phases of self-tracking, from identifying tracking tools to reviewing data. The main barriers our respondents experienced included suboptimal tracking experiences and insufficient benefits against the extended burden for BLV people. Conclusions: We reported the findings that contribute to an in-depth understanding of BLV people’s motivations for PHD tracking, tracking practices, challenges, and work-arounds. Our findings suggest that various accessibility challenges hinder BLV individuals from effectively gaining the benefits of self-tracking technologies. On the basis of the findings, we discussed design opportunities and research areas to focus on making PHD tracking technologies accessible for all, including BLV people.more » « less
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/AIMHC59811.2024.00026
