Human Factors Testing: Neuroscience Toolkit
Supported the design and implementation of a formative human factors project to assess the usability and safety of patient facing, remotely completed, neuroscience assessments within a specific therapeutic population.
I supported the formative human factors testing initiative for a collection of patient facing neuroscience measures using a digital tool within an in-clinic and remote environment for a population experiencing early stage Parkinson’s Disease.
The digital neuroscience tool encompassed a range of neurocognitive motor activities and ePROs (electronic Patient Reported Outcomes) delivered via a mobile device over an extended period of time. This included assessments such as the 'Timed Walk Test,' 'Finger Tap Test,' and 'Pronation/Supination Test.'
These measures were slated for implementation in a forthcoming large-scale clinical research study, to be completed by participants using a mobile device. The human factors testing focused on assessing patient safety, usability across different scenarios, overall user experience, and content meaningfulness within the target population utilizing the digital tool. Insights gleaned from the human factors findings drove updates to the digital health tool, study training protocols, and study implementation strategies for the broader LEARNS Observational Study.
I led the study design and was responsible for creating study materials, including protocol development, specifications for digital tool use, participant-facing materials, moderator guides, and evaluation/scoring matrices for coding patient observations during digital project activities.
The formative human factors testing approach that was conducted was in alignment with Digital Medicine Society (DiMe), V3+ framework which focuses on the verification, analytical validation, clinical validation and usability validation when developing a new digital health technology. The human factors testing initiative that I supported was used as a case study when rolling out the new V3+ framework to the broader scientific community.