TY - JOUR
T1 - Data Visualization Preferences in Remote Measurement Technology for Individuals Living With Depression, Epilepsy, and Multiple Sclerosis
T2 - Qualitative Study
AU - RADAR-CNS Consortium
AU - Simblett, Sara
AU - Dawe-Lane, Erin
AU - Gilpin, Gina
AU - Morris, Daniel
AU - White, Katie
AU - Erturk, Sinan
AU - Devonshire, Julie
AU - Lees, Simon
AU - Zormpas, Spyridon
AU - Polhemus, Ashley
AU - Temesi, Gergely
AU - Cummins, Nicholas
AU - Hotopf, Matthew
AU - Wykes, Til
N1 - ©Sara Simblett, Erin Dawe-Lane, Gina Gilpin, Daniel Morris, Katie White, Sinan Erturk, Julie Devonshire, Simon Lees, Spyridon Zormpas, Ashley Polhemus, Gergely Temesi, Nicholas Cummins, Matthew Hotopf, Til Wykes, RADAR-CNS Consortium. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.10.2024.
PY - 2024/10/18
Y1 - 2024/10/18
N2 - BACKGROUND: Remote measurement technology (RMT) involves the use of wearable devices and smartphone apps to measure health outcomes in everyday life. RMT with feedback in the form of data visual representations can facilitate self-management of chronic health conditions, promote health care engagement, and present opportunities for intervention. Studies to date focus broadly on multiple dimensions of service users' design preferences and RMT user experiences (eg, health variables of perceived importance and perceived quality of medical advice provided) as opposed to data visualization preferences.OBJECTIVE: This study aims to explore data visualization preferences and priorities in RMT, with individuals living with depression, those with epilepsy, and those with multiple sclerosis (MS).METHODS: A triangulated qualitative study comparing and thematically synthesizing focus group discussions with user reviews of existing self-management apps and a systematic review of RMT data visualization preferences. A total of 45 people participated in 6 focus groups across the 3 health conditions (depression, n=17; epilepsy, n=11; and MS, n=17).RESULTS: Thematic analysis validated a major theme around design preferences and recommendations and identified a further four minor themes: (1) data reporting, (2) impact of visualization, (3) moderators of visualization preferences, and (4) system-related factors and features.CONCLUSIONS: When used effectively, data visualizations are valuable, engaging components of RMT. Easy to use and intuitive data visualization design was lauded by individuals with neurological and psychiatric conditions. Apps design needs to consider the unique requirements of service users. Overall, this study offers RMT developers a comprehensive outline of the data visualization preferences of individuals living with depression, epilepsy, and MS.
AB - BACKGROUND: Remote measurement technology (RMT) involves the use of wearable devices and smartphone apps to measure health outcomes in everyday life. RMT with feedback in the form of data visual representations can facilitate self-management of chronic health conditions, promote health care engagement, and present opportunities for intervention. Studies to date focus broadly on multiple dimensions of service users' design preferences and RMT user experiences (eg, health variables of perceived importance and perceived quality of medical advice provided) as opposed to data visualization preferences.OBJECTIVE: This study aims to explore data visualization preferences and priorities in RMT, with individuals living with depression, those with epilepsy, and those with multiple sclerosis (MS).METHODS: A triangulated qualitative study comparing and thematically synthesizing focus group discussions with user reviews of existing self-management apps and a systematic review of RMT data visualization preferences. A total of 45 people participated in 6 focus groups across the 3 health conditions (depression, n=17; epilepsy, n=11; and MS, n=17).RESULTS: Thematic analysis validated a major theme around design preferences and recommendations and identified a further four minor themes: (1) data reporting, (2) impact of visualization, (3) moderators of visualization preferences, and (4) system-related factors and features.CONCLUSIONS: When used effectively, data visualizations are valuable, engaging components of RMT. Easy to use and intuitive data visualization design was lauded by individuals with neurological and psychiatric conditions. Apps design needs to consider the unique requirements of service users. Overall, this study offers RMT developers a comprehensive outline of the data visualization preferences of individuals living with depression, epilepsy, and MS.
KW - Humans
KW - Multiple Sclerosis/psychology
KW - Epilepsy/psychology
KW - Qualitative Research
KW - Depression/psychology
KW - Focus Groups
KW - Adult
KW - Female
KW - Male
KW - Middle Aged
KW - Mobile Applications
KW - Data Visualization
KW - Patient Preference/psychology
KW - Telemedicine
KW - Aged
KW - Wearable Electronic Devices
UR - http://www.scopus.com/inward/record.url?scp=85207664768&partnerID=8YFLogxK
U2 - 10.2196/43954
DO - 10.2196/43954
M3 - Article
C2 - 39423366
AN - SCOPUS:85207664768
SN - 1438-8871
VL - 26
JO - Journal of Medical Internet Research
JF - Journal of Medical Internet Research
M1 - e43954
ER -