Currently submitted to: JMIR Formative Research
Date Submitted: Nov 13, 2024
Open Peer Review Period: Nov 13, 2024 - Jan 8, 2025
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Co-creating the visualisation of digital mobility outcomes: a Delphi-process with patients.
ABSTRACT
Background:
Recent technological advances in wearable devices offer new potential for measuring mobility in real-world contexts. Mobilise-D has validated digital mobility outcomes to provide novel outcomes and endpoints in clinical research of four different long-term health conditions (Parkinson’s disease (PD), Multiple Sclerosis (MS), Chronic Obstructive Pulmonary Disease (COPD), and Proximal Femoral Fracture (PFF)). These outcomes also provide unique information that is important to patients, however there is limited literature that explores the optimal methods to achieve this such as the best way to visualise their data.
Objective:
This study aims to identify meaningful outcomes for each condition and how to best visualise them from the perspective of end users.
Methods:
Using a Delphi-type protocol with patients as subject matter experts, we gathered iterative feedback on the co-creation of visualisations through several rounds of questionnaires. An open-ended questionnaire was used in Round one to understand what aspects of mobility were most influenced by their health condition. These responses were mapped onto relevant digital mobility outcomes and walking experiences then prioritised for visualisation. Using patient responses, we worked alongside researchers, clinicians, and a patient advisory group to develop visualisations that depicted a week of mobility data. During rounds two and three, participants rated usefulness and ease of understanding on a 5-point Likert scale and provided unstructured feedback in comment boxes for each visualisation. Visualisations were refined using the feedback from Round two before receiving further feedback in Round three.
Results:
Participation varied across rounds one to three (n=48, n=79, n=79, respectively). Round one identified important outcomes and contexts for each health condition such as walking speed and stride length for people with PD and MS and number of steps for people with COPD and PFF. Consensus was not reached for any visualisation reviewed in round two or three. Feedback was generally positive, and some participants reported they were able to understand the visualisation and interpret what the visualisation represented.
Conclusions:
Through the feedback provided, we developed some recommendations for future visualisations of mobility and health-related data. Visualisations should be readable by ensuring large and clear font and should be friendly for potential vision impairments such as colour blindness. Patients have a strong understanding of their own condition and its variability, adding additional factors into visualisations is recommended. Ensure outcomes and visualisations are meaningful by working alongside patients throughout the development process. Ensuring that outcomes and visualisations are meaningful requires close collaboration with patients throughout the development process.
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