Co-creating the visualisation of digital mobility outcomes: a Delphi-process with patients. (Preprint)
Authors: Lumsdon Jack , Wilson Cameron , Alcock Lisa , Becker Clemens , Benvenuti Francesco , Bonci Tecla , van den Brande Koen , Brittain Gavin , Brown Phillip , Buckley Ellen , Caruso Marco , Caulfield Brian , Cereatti Andrea , Delgadi-Ortiz Laura , Del DIn Silvia , Evers Jordi , Gracia-Aymerich Judith , Gaßner Heiko , Gur Arieh Tova , Hansen Clint , Hausdorff Jeffrey M , Hiden Hugo , Hume Emily , Kirk Cameron , Maetzler Walter , Megaritis Dimitrios , Rochester Lynn , Scott Kirsty , Sharrack Basil , Sutton Norman , Vereijken Beatrix , Vogiatzis Ioannis , Yarnall Alison , Keogh Alison , Cantu Alma 
Published: November 2024

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.