Background: Remote measurement technology (RMT), including the use of mobile phone apps and wearable devices, may provide the opportunity for real-world assessment and intervention that will streamline clinical input for years to come. In order to establish the benefits of this approach, we need to operationalize what is expected in terms of a successful measurement. We focused on three clinical long-term conditions where a novel case has been made for the benefits of RMT: major depressive disorder (MDD), multiple sclerosis (MS), and epilepsy.
Objective: The aim of this study was to conduct a consultation exercise on the clinical end point or outcome measurement priorities for RMT studies, drawing on the experiences of people with chronic health conditions.
Methods: A total of 24 participants (16/24 women, 67%), ranging from 28 to 65 years of age, with a diagnosis of one of three chronic health conditions-MDD, MS, or epilepsy-took part in six focus groups. A systematic thematic analysis was used to extract themes and subthemes of clinical end point or measurement priorities.
Results: The views of people with MDD, epilepsy, and MS differed. Each group highlighted unique measurements of importance, relevant to their specific needs. Although there was agreement that remote measurement could be useful for tracking symptoms of illness, some symptoms were specific to the individual groups. Measuring signs of wellness was discussed more by people with MDD than by people with MS and epilepsy. However, overlap did emerge when considering contextual factors, such as life events and availability of support (MDD and epilepsy) as well as ways of coping (epilepsy and MS).
Conclusions: This is a unique study that puts patients' views at the forefront of the design of a clinical study employing novel digital resources. In all cases, measuring symptom severity is key; people want to know when their health is getting worse. Second, symptom severity needs to be placed into context. A holistic approach that, in some cases, considers signs of wellness as well as illness, should be the aim of studies employing RMT to understand the health of people with chronic conditions.
Keywords: mHealth; patient involvement; qualitative analysis; remote measurement technology.
©Sara Simblett, Faith Matcham, Hannah Curtis, Ben Greer, Ashley Polhemus, Jan Novák, Jose Ferrao, Peter Gamble, Matthew Hotopf, Vaibhav Narayan, Til Wykes, Remote Assessment Of Disease And Relapse – Central Nervous System (RADAR-CNS) Consortium. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 10.06.2020.