Research & Project Updates

My dissertation aims to provide personalized feedback and tailored recommendations to the collaborating researcher based on participant data, with the goal of improving engagement in Health HCI research. Recommendations will be organized into three groups: researchers, institutions, and the broader Health HCI field—with a central focus on making studies more accessible through universal design and appropriate accommodations, while emphasizing ways to minimize harm to researchers by addressing emotional strain and advocating for better support systems. Findings will be analyzed through three lenses: individual participant factors (e.g., beliefs, health literacy), societal influences (e.g., norms, policies), and organizational characteristics (e.g., institutional practices). Grounded in participants’ lived experiences, the resulting insights will guide more inclusive, empathetic, and effective research practices across the Health HCI community.

This study endeavors to systematically identify and categorize the barriers encountered by participants in engaging with health research. Participants will provide detailed accounts of their experiences that contributed to withdrawal and attrition, alongside proposed solutions or strategies they have employed or recommend for overcoming these challenges. The overarching objective of the findings is to inform strategies that enhance participant accessibility and foster more inclusive and effective research methodologies.

This project examined how Health HCI researchers approached participant engagement in studies involving patient-generated data, long-term participation, and collaborations with healthcare providers. Through interviews with researchers at various career stages, I found that it was perceived that academic and industry priorities shaped engagement strategies differently—academia often prioritizing publishable data, while industry focused on user experience. These differing goals influenced who was included in studies and how participants were engaged. Participants described how Mentorship, hands-on experience, and even tools like AI helped them navigate these challenges, while creative approaches such as social media and livestreaming could offer new ways to build transparency and rapport. However, many cited institutional pressures often limited deep engagement, leading researchers to call for improved training, alternative dissemination methods, and mentorship programs to support more inclusive practices. Across the field, researchers emphasized the importance of early communication, human-centered design, and trust-building and advocated for cultural shifts through peer mentorship, workshops, and shared resources. Overall, the project highlighted the need to realign systems and values in Health HCI to support meaningful, participant-informed research better.

A collaboration with Kaiser Permanente Washington to examine the reach of a pilot home blood pressure measurement outreach program. This project examined research of the secure email program by patient characteristics (e.g., age, sex, race/ethnicity) and clinic characteristics (e.g., clinic size, clinic region). It evaluated patient perception of the secure email program (e.g., usability, acceptability, experience of care). I helped design the interviews and analyze the resulting data.

This project is examining the design, development, and evaluation of a highly-personalizable mobile app for self-tracking of symptoms, potential contributors, and treatments by patients with migraine. In collaboration with the University of Washington Migraine Clinic, the team's prior research has found that many self-tracking applications emphasize detailed data collection but fail to account for how data is likely to be used by a patient or their provider. This commonly results in high burdens of tracking irrelevant data that can lead to low engagement or abandonment, but can also lead to breakdowns when tracked data does not correspond to the goals of a patient or their provider. The team proposed a design strategy for self-tracking applications that explicitly represents patient and provider goals for self-tracking data, using that representation to scaffold appropriate choices in what data to track and how to analyze and visualize collected data.

This project is addressing the design of a mobile app for supporting an evidence-based self-management intervention in patients with irritable bowel syndrome and depression. In collaboration with a team from the University of Washington School of Nursing, I led an analysis of data from eight patient interviews in a pilot study of the app. The team had designed and developed the app, then found low usability and engagement in their pilot deployment, but were unsure how to attribute those findings. My interview analyses identified a mismatch in assumptions about patient experiences with their irritable bowel syndrome, wherein the app design assumed an individual was new to the self-management intervention. Still, patient participants already had significant experience managing their irritable bowel syndrome. Patient participants, therefore, did not engage in the intervention because they found the technology support inflexible concerning variability in existing individual understanding of the intervention. Based on these results, we intend to conduct follow-up interviews and design sessions to examine how patients could adapt such an intervention to their existing personalized understanding. We also intend to prepare a manuscript based on this redesign process.

This project is addressing the design, development, and evaluation of a novel platform for technology-enhanced collaborative care in patients with cancer and depression, currently deployed in 5 urban and rural cancer centers. In collaboration with a multidisciplinary team from the University of Washington Department of Psychiatry and the Fred Hutchinson Cancer Center, the UW Scope platform combines a web-based provider registry with a patient mobile application. The design of this platform is based in part on the team's prior research on breakdowns in co-occurring cancer and depression, which also informed the development of the parallel journeys framework for understanding and designing for multiple patient journeys associated with co-morbid conditions.

As part of my Master's degree at Kennesaw State University, I led a collaboration between the Kennesaw State University BrainLab, the United in Gaming platform, and the Kennesaw State University Esports program. The project examined mental well-being in gamers playing social games amidst the COVID-19 pandemic. I hypothesized that, within gaming skill levels, player gaming motivation would correlate with player well-being. I led data collection and analysis, combining pre- and post-gameplay collection of the Scale of Positive and Negative Experiences, post-gameplay collection of the Player Experience and Need Satisfaction Scale, and facial expression analysis data obtained from video recording during gameplay.
This work was coauthored with Dr. Adriane B. Randolph and Dr. Sweta Sneha. I presented the findings at the NeuroIS Retreat 2021 and was accepted for publication in Information Systems and Neuroscience.

I submitted a research paper on preliminary findings, "Vital monitoring Wearables and Communication Applications" for Initial Review of Health Information Technology Symposium (HITS). Updates and research pending/on hold.

I completed my research and paper: “Using NeuroIS Tools to Understand How Individual Characteristics Relate to Cognitive Behaviors of Students” coauthored with Dr. Adriane B. Randolph, Dr. Kimberly Cortes, and Dr. Cassidy Terrell. Our paper was accepted for publication in Information Systems and Neuroscience. I also presented my findings at the NeuroIS Retreat 2020.

At Kennesaw State University's BrainLab under Dr. Adriane B. Randolph I used EEG and Tobii Eye tracking to analyze perception of Motus Nova’s website with intentions to increase user buy-in for their product line.

At Kennesaw State University's BrainLab under Dr. Adriane B. Randolph I used EEG and Tobii Eye tracking to analyze user brand preferences.