Exploring the Strategies People with Parkinson's Disease Use to Self-track Symptoms and Medications
Charlotte Tang, Imrul K. Shuva, Matthew Thelen, Linda Zhu, Nathaniel S. Miller · 2024 · ACM Transactions on Accessible Computing · doi:10.1145/3649454
Summary
This qualitative study investigates how people with Parkinson's Disease (PwPD) track their symptoms, medications, and physical activities, with the goal of informing inclusive design of self-tracking technologies. The researchers conducted semi-structured interviews with 26 people with PD (ages 42-81, averaging 66.69 years), six caregivers (all spouses), and three healthcare providers (a neurologist, physical therapist, and speech language pathologist). Parkinson's Disease presents unique self-tracking challenges because it manifests differently in each person, with a wide range of motor symptoms (tremors, rigidity, bradykinesia, freezing of gait) and non-motor symptoms (depression, sleep disorders, cognitive changes, speech impairment). Symptoms also fluctuate throughout the day based on medication timing, creating "on" and "off" periods that are difficult to capture. The study found that approximately 90% of PwPD will experience speech and voice issues at some point, complicating voice-based input methods. The research employed a user-centered design approach, recruiting participants through PD support groups across the U.S. The interview protocol explored current tracking practices, challenges encountered, the role of caregivers, and desired features in tracking applications. Data analysis used open coding followed by axial coding to identify themes around tracking strategies and challenges.
Key findings
The study identified five distinct self-tracking strategies: (1) Mental tracking—relying on memory to note symptom patterns, used by 8 participants who either found explicit tracking unnecessary or too difficult; (2) Analog tracking—paper journals, calendars, spreadsheets, and physical pill organization systems used by 8 participants; (3) General-purpose technology—smartphones, tablets, smartwatches, and standard apps like calendars and notes, used by 14 participants; (4) Specialized technology—PD-specific apps, Fitbits, heart rate monitors, and C-PAP machines, with mixed satisfaction; (5) Tracking by proxy—7 participants relied on caregivers to observe symptoms they couldn't perceive themselves, like nightmares, gait changes, or acting out dreams. Key challenges included: symptoms being indistinguishable from normal aging (difficulty differentiating PD tremor from arthritis); symptoms being hard to describe ("it's an out of body experience"); tracking technology misinterpreting movements (watches mistaking tooth brushing for tremor); lack of perceived usefulness when healthcare providers didn't review tracked data; and significant interaction barriers—tremors making small touchscreens difficult to use, stiffness preventing key presses, and vision impairments compounding small screen issues.
Relevance
This research provides essential guidance for designing accessible health technology for users with progressive motor and cognitive conditions. The design guidelines are immediately applicable: minimize manual input through automatic data capture; design for integration with existing routines rather than requiring new behaviors; accommodate dexterity issues with large buttons and voice input options; support caregiver involvement as tracking proxies; and present data in visualizations that demonstrate clear value to both patients and clinicians. The finding that healthcare providers often lack time to review self-tracked data—and that some explicitly discouraged tracking—highlights a systemic barrier that technology alone cannot solve. For accessibility practitioners, this study demonstrates that designing for chronic progressive conditions requires understanding fluctuating abilities throughout the day, not just accommodating a static disability profile. The emphasis on customization (tracking only relevant symptoms) and educational resources built into apps reflects broader inclusive design principles applicable beyond PD.
Tags: Parkinson's disease · self-tracking · chronic illness · health technology · inclusive design · caregivers · wearable technology · motor impairment · user study