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Data Visualization Preferences in Remote Measurement Technology for Individuals Living With Depression, Epilepsy, and Multiple Sclerosis: Qualitative Study
S. Simblett, E. Dawe-Lane, G. Gilpin, D. Morris, K. White, S. Erturk, J. Devonshire, S. Lees, S. Zormpas, A. Polhemus, G. Temesi, N. Cummins, M. Hotopf, T. Wykes, RADAR-CNS Consortium
Jazyk angličtina Země Kanada
Typ dokumentu časopisecké články
NLK
Directory of Open Access Journals
od 1999
Free Medical Journals
od 1999
Freely Accessible Science Journals
od 1999
PubMed Central
od 1999
Europe PubMed Central
od 1999
ProQuest Central
od 2001-01-01
Open Access Digital Library
od 1999-01-01
Open Access Digital Library
od 1999-01-01
Medline Complete (EBSCOhost)
od 2005-02-24
Nursing & Allied Health Database (ProQuest)
od 2001-01-01
Health & Medicine (ProQuest)
od 2001-01-01
ROAD: Directory of Open Access Scholarly Resources
od 1999
PubMed
39423366
DOI
10.2196/43954
Knihovny.cz E-zdroje
- MeSH
- deprese * psychologie MeSH
- dospělí MeSH
- epilepsie * psychologie MeSH
- kvalitativní výzkum * MeSH
- lidé středního věku MeSH
- lidé MeSH
- mobilní aplikace MeSH
- nositelná elektronika MeSH
- pacientova volba psychologie statistika a číselné údaje MeSH
- roztroušená skleróza * psychologie MeSH
- senioři MeSH
- telemedicína MeSH
- vizualizace dat MeSH
- zjišťování skupinových postojů * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
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.
Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom
Medical Science Division IT Services Prague Czech Republic
South London and Maudsley NHS Foundation Trust London United Kingdom
Citace poskytuje Crossref.org
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