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      How the weather affects the pain of citizen scientists using a smartphone app

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          Abstract

          Patients with chronic pain commonly believe their pain is related to the weather. Scientific evidence to support their beliefs is inconclusive, in part due to difficulties in getting a large dataset of patients frequently recording their pain symptoms during a variety of weather conditions. Smartphones allow the opportunity to collect data to overcome these difficulties. Our study Cloudy with a Chance of Pain analysed daily data from 2658 patients collected over a 15-month period. The analysis demonstrated significant yet modest relationships between pain and relative humidity, pressure and wind speed, with correlations remaining even when accounting for mood and physical activity. This research highlights how citizen-science experiments can collect large datasets on real-world populations to address long-standing health questions. These results will act as a starting point for a future system for patients to better manage their health through pain forecasts.

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          Pain relief that matters to patients: systematic review of empirical studies assessing the minimum clinically important difference in acute pain

          Background The minimum clinically important difference (MCID) is used to interpret the clinical relevance of results reported by trials and meta-analyses as well as to plan sample sizes in new studies. However, there is a lack of consensus about the size of MCID in acute pain, which is a core symptom affecting patients across many clinical conditions. Methods We identified and systematically reviewed empirical studies of MCID in acute pain. We searched PubMed, EMBASE and Cochrane Library, and included prospective studies determining MCID using a patient-reported anchor and a one-dimensional pain scale (e.g. 100 mm visual analogue scale). We summarised results and explored reasons for heterogeneity applying meta-regression, subgroup analyses and individual patient data meta-analyses. Results We included 37 studies (8479 patients). Thirty-five studies used a mean change approach, i.e. MCID was assessed as the mean difference in pain score among patients who reported a minimum degree of improvement, while seven studies used a threshold approach, i.e. MCID was assessed as the threshold in pain reduction associated with the best accuracy (sensitivity and specificity) for identifying improved patients. Meta-analyses found considerable heterogeneity between studies (absolute MCID: I2 = 93%, relative MCID: I2 = 75%) and results were therefore presented qualitatively, while analyses focused on exploring reasons for heterogeneity. The reported absolute MCID values ranged widely from 8 to 40 mm (standardised to a 100 mm scale) and the relative MCID values from 13% to 85%. From analyses of individual patient data (seven studies, 918 patients), we found baseline pain strongly associated with absolute, but not relative, MCID as patients with higher baseline pain needed larger pain reduction to perceive relief. Subgroup analyses showed that the definition of improved patients (one or several categories improvement or meaningful change) and the design of studies (single or multiple measurements) also influenced MCID values. Conclusions The MCID in acute pain varied greatly between studies and was influenced by baseline pain, definitions of improved patients and study design. MCID is context-specific and potentially misguiding if determined, applied or interpreted inappropriately. Explicit and conscientious reflections on the choice of a reference value are required when using MCID to classify research results as clinically important or trivial.
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            Feasibility of Obtaining Measures of Lifestyle From a Smartphone App

            Studies have established the importance of physical activity and fitness, yet limited data exist on the associations between objective, real-world physical activity patterns, fitness, sleep, and cardiovascular health.
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              Exchangeability in the case-crossover design.

              In cohort and case-control studies, confounding that arises as a result of differences in the distribution of determinants of the outcome between exposure groups leading to non-exchangeability are addressed by restriction, matching or with statistical models. In case-only studies, this issue is addressed by comparing each individual with his/herself. Although case-only designs use self-matching and only include individuals who develop the outcome of interest, issues of non-exchangeability are identical to those that arise in traditional case-control and cohort studies. In this review, we describe one type of case-only design, the case-crossover design, and discuss how the concept of exchangeability can be used to understand issues of confounding, carryover effects, period effects and selection bias in case-crossover studies.
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                Author and article information

                Contributors
                will.dixon@manchester.ac.uk
                Journal
                NPJ Digit Med
                NPJ Digit Med
                NPJ Digital Medicine
                Nature Publishing Group UK (London )
                2398-6352
                24 October 2019
                24 October 2019
                2019
                : 2
                : 105
                Affiliations
                [1 ]ISNI 0000000121662407, GRID grid.5379.8, Centre for Epidemiology Versus Arthritis, Manchester Academic Health Science Centre, , The University of Manchester, ; Manchester, UK
                [2 ]ISNI 0000000121662407, GRID grid.5379.8, Health eResearch Centre, Manchester Academic Health Science Centre, , The University of Manchester, ; Manchester, UK
                [3 ]ISNI 0000000121662407, GRID grid.5379.8, NIHR Greater Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, , The University of Manchester, ; Manchester, UK
                [4 ]ISNI 0000 0004 0425 469X, GRID grid.8991.9, Department of Public Health Environments and Society, , London School of Hygiene & Tropical Medicine, ; London, UK
                [5 ]ISNI 0000 0004 0425 469X, GRID grid.8991.9, Centre for Statistical Methodology, , London School of Hygiene & Tropical Medicine, ; London, UK
                [6 ]GRID grid.11447.37, IBM Research, ; Haifa, Israel
                [7 ]uMotif Limited, London, UK
                [8 ]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, Department of Anesthesiology, Pharmacology and Therapeutics, , University of British Columbia, ; Vancouver, BC Canada
                [9 ]Department of Statistical Science, UCL London, UK
                [10 ]ISNI 0000 0004 5903 3632, GRID grid.499548.d, Alan Turing Institute, ; London, UK
                [11 ]ISNI 0000 0004 1936 7304, GRID grid.1010.0, Discipline of Medicine, , The University of Adelaide, ; Adelaide, Australia
                [12 ]ISNI 0000000121662407, GRID grid.5379.8, School of Mathematics, , The University of Manchester, ; Manchester, UK
                [13 ]IBM Research, Hartree Centre, Sci-Tech, Daresbury, UK
                [14 ]ISNI 0000000121662407, GRID grid.5379.8, Greater Manchester Patient Safety Translational Research Centre, , The University of Manchester, ; Manchester, UK
                [15 ]ISNI 0000000121662407, GRID grid.5379.8, NIHR School of Primary Care, Manchester Academic Health Science Centre, , The University of Manchester, ; Manchester, UK
                [16 ]ISNI 0000000121662407, GRID grid.5379.8, Centre for Atmospheric Science, School of Earth and Environmental Sciences, , The University of Manchester, ; Manchester, UK
                [17 ]ISNI 0000000121662407, GRID grid.5379.8, Centre for Biostatistics, Manchester Academic Health Science Centre, , The University of Manchester, ; Manchester, UK
                Author information
                http://orcid.org/0000-0001-5881-4857
                http://orcid.org/0000-0002-2271-3568
                http://orcid.org/0000-0002-2156-1558
                http://orcid.org/0000-0002-8015-8187
                http://orcid.org/0000-0002-6502-9563
                http://orcid.org/0000-0002-2187-9195
                http://orcid.org/0000-0001-5835-8062
                http://orcid.org/0000-0002-2391-5575
                http://orcid.org/0000-0003-1558-6975
                http://orcid.org/0000-0002-9000-4413
                Article
                180
                10.1038/s41746-019-0180-3
                6811599
                31304351
                7848124a-d83b-4eba-ab86-e169bc4be51e
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 May 2019
                : 23 September 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000270, RCUK | Natural Environment Research Council (NERC);
                Award ID: NE/I026545/1, and NE/N003918/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000341, Arthritis Research UK;
                Award ID: 21225
                Award ID: 21225
                Award ID: 21225
                Award ID: 21225
                Award ID: 21225
                Award ID: 21225
                Award ID: 21225
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000265, RCUK | Medical Research Council (MRC);
                Award ID: MR/M022625/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100012338, Alan Turing Institute;
                Award ID: EP/N510129/1
                Award Recipient :
                Funded by: Alan Turing Institute, EP/N510129/1
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                risk factors,chronic pain,epidemiology
                risk factors, chronic pain, epidemiology

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