Patterns and predictors of variability in patient-generated daily pain severity collected via a mobile health smartphone app.

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Bibliographic Details
Title: Patterns and predictors of variability in patient-generated daily pain severity collected via a mobile health smartphone app.
Authors: Little CL; Centre for Epidemiology Versus Arthritis, University of Manchester, Manchester, United Kingdom., Yimer BB; Centre for Epidemiology Versus Arthritis, University of Manchester, Manchester, United Kingdom., House T; Department of Mathematics, University of Manchester, Manchester, United Kingdom., Dixon WG; Centre for Epidemiology Versus Arthritis, University of Manchester, Manchester, United Kingdom.; NIHR Manchester Musculoskeletal Biomedical Research Unit, Central Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom., Schultz DM; Centre for Atmospheric Science, Department of Earth and Environmental Sciences, University of Manchester, Manchester, United Kingdom.; Centre for Crisis Studies and Mitigation, University of Manchester, Manchester, United Kingdom., McBeth J; Centre for Epidemiology Versus Arthritis, University of Manchester, Manchester, United Kingdom.; NIHR Manchester Musculoskeletal Biomedical Research Unit, Central Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom.
Source: PloS one [PLoS One] 2026 Apr 02; Vol. 21 (4), pp. e0345420. Date of Electronic Publication: 2026 Apr 02 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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