Published on in Vol 5, No 11 (2017): November

Recruitment and Ongoing Engagement in a UK Smartphone Study Examining the Association Between Weather and Pain: Cohort Study

Recruitment and Ongoing Engagement in a UK Smartphone Study Examining the Association Between Weather and Pain: Cohort Study

Recruitment and Ongoing Engagement in a UK Smartphone Study Examining the Association Between Weather and Pain: Cohort Study

Journals

  1. Druce K, Dixon W, McBeth J. Maximizing Engagement in Mobile Health Studies. Rheumatic Disease Clinics of North America 2019;45(2):159 View
  2. Dixon W, Beukenhorst A, Yimer B, Cook L, Gasparrini A, El-Hay T, Hellman B, James B, Vicedo-Cabrera A, Maclure M, Silva R, Ainsworth J, Pisaniello H, House T, Lunt M, Gamble C, Sanders C, Schultz D, Sergeant J, McBeth J. How the weather affects the pain of citizen scientists using a smartphone app. npj Digital Medicine 2019;2(1) View
  3. Schultz D, Beukenhorst A, Yimer B, Cook L, Pisaniello H, House T, Gamble C, Sergeant J, McBeth J, Dixon W. Weather Patterns Associated with Pain in Chronic-Pain Sufferers. Bulletin of the American Meteorological Society 2020;101(5):E555 View
  4. Costello R, Anand A, Jameson Evans M, Dixon W. Associations Between Engagement With an Online Health Community and Changes in Patient Activation and Health Care Utilization: Longitudinal Web-Based Survey. Journal of Medical Internet Research 2019;21(8):e13477 View
  5. Austin L, Sharp C, van der Veer S, Machin M, Humphreys J, Mellor P, McCarthy J, Ainsworth J, Sanders C, Dixon W. Providing ‘the bigger picture’: benefits and feasibility of integrating remote monitoring from smartphones into the electronic health record. Rheumatology 2020;59(2):367 View
  6. Fan X, Wang D, Hellman B, Janssen M, Bakker G, Coghlan R, Hursey A, Matthews H, Whetstone I. Assessment of Health-Related Quality of Life between People with Parkinson’s Disease and Non-Parkinson’s: Using Data Drawn from the ‘100 for Parkinson’s’ Smartphone-Based Prospective Study. International Journal of Environmental Research and Public Health 2018;15(11):2538 View
  7. Chao D, Lin T, Ma W. Enhanced Self-Efficacy and Behavioral Changes Among Patients With Diabetes: Cloud-Based Mobile Health Platform and Mobile App Service. JMIR Diabetes 2019;4(2):e11017 View
  8. Pratap A, Neto E, Snyder P, Stepnowsky C, Elhadad N, Grant D, Mohebbi M, Mooney S, Suver C, Wilbanks J, Mangravite L, Heagerty P, Areán P, Omberg L. Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants. npj Digital Medicine 2020;3(1) View
  9. Stubberud A, Linde M. Digital Technology and Mobile Health in Behavioral Migraine Therapy: a Narrative Review. Current Pain and Headache Reports 2018;22(10) View
  10. Beukenhorst A, Parkes M, Cook L, Barnard R, van der Veer S, Little M, Howells K, Sanders C, Sergeant J, O'Neill T, McBeth J, Dixon W. Collecting Symptoms and Sensor Data With Consumer Smartwatches (the Knee OsteoArthritis, Linking Activity and Pain Study): Protocol for a Longitudinal, Observational Feasibility Study. JMIR Research Protocols 2019;8(1):e10238 View
  11. Dixon W, Michaud K. Using technology to support clinical care and research in rheumatoid arthritis. Current Opinion in Rheumatology 2018;30(3):276 View
  12. Minen M, Schaubhut K, Morio K. Smartphone based behavioral therapy for pain in multiple sclerosis (MS) patients: A feasibility acceptability randomized controlled study for the treatment of comorbid migraine and ms pain. Multiple Sclerosis and Related Disorders 2020;46:102489 View
  13. Croft P. Environmental Hazards: A Coverage Response Approach. Future Internet 2019;11(3):72 View
  14. Meyerowitz-Katz G, Ravi S, Arnolda L, Feng X, Maberly G, Astell-Burt T. Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2020;22(9):e20283 View
  15. Minen M, Adhikari S, Padikkala J, Tasneem S, Bagheri A, Goldberg E, Powers S, Lipton R. Smartphone‐Delivered Progressive Muscle Relaxation for the Treatment of Migraine in Primary Care: A Randomized Controlled Trial. Headache: The Journal of Head and Face Pain 2020;60(10):2232 View
  16. Bourke A, Dixon W, Roddam A, Lin K, Hall G, Curtis J, van der Veer S, Soriano‐Gabarró M, Mills J, Major J, Verstraeten T, Francis M, Bartels D. Incorporating patient generated health data into pharmacoepidemiological research. Pharmacoepidemiology and Drug Safety 2020;29(12):1540 View
  17. Minen M, Corner S, Berk T, Levitan V, Friedman S, Adhikari S, Seng E. Heartrate variability biofeedback for migraine using a smartphone application and sensor: A randomized controlled trial. General Hospital Psychiatry 2021;69:41 View
  18. Allan S, Mcleod H, Bradstreet S, Bell I, Whitehill H, Wilson-Kay A, Clark A, Matrunola C, Morton E, Farhall J, Gleeson J, Gumley A. Perspectives of Trial Staff on the Barriers to Recruitment in a Digital Intervention for Psychosis and How to Work Around Them: Qualitative Study Within a Trial. JMIR Human Factors 2021;8(1):e24055 View
  19. Hulme W, Martin G, Sperrin M, Casson A, Bucci S, Lewis S, Peek N. Adaptive Symptom Monitoring Using Hidden Markov Models – An Application in Ecological Momentary Assessment. IEEE Journal of Biomedical and Health Informatics 2021;25(5):1770 View
  20. De Cock D, Myasoedova E, Aletaha D, Studenic P. Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs). Therapeutic Advances in Musculoskeletal Disease 2022;14:1759720X2211059 View
  21. Doumen M, De Cock D, Van Lierde C, Betrains A, Pazmino S, Bertrand D, Westhovens R, Verschueren P. Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis. RMD Open 2022;8(2):e002625 View
  22. Gates E, Hole B, Hayward S, Chesnaye N, Meuleman Y, Dekker F, Evans M, Heimburger O, Torino C, Porto G, Szymczak M, Drechsler C, Wanner C, Jager K, Roderick P, Caskey F. Converting from face-to-face to postal follow-up and its effects on participant retention, response rates and errors: lessons from the EQUAL study in the UK. BMC Medical Research Methodology 2022;22(1) View
  23. Leonard K, Pauley A, Guo P, Hohman E, Rivera D, Savage J, Symons Downs D. Feasibility and user acceptability of Breezing™, a mobile indirect calorimetry device, in pregnant women with overweight or obesity. Smart Health 2023;27:100372 View
  24. Jones S, Hue W, Kelly R, Barnett R, Henderson V, Sengupta R. Determinants of Longitudinal Adherence in Smartphone-Based Self-Tracking for Chronic Health Conditions. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2021;5(1):1 View
  25. Rogers A, De Paoli G, Subbarayan S, Copland R, Harwood K, Coyle J, Mitchell L, MacDonald T, Mackenzie I. A systematic review of methods used to conduct decentralised clinical trials. British Journal of Clinical Pharmacology 2022;88(6):2843 View
  26. Doumen M, Westhovens R, Pazmino S, Bertrand D, Stouten V, Neys C, Creten N, Van Laeken E, Verschueren P, De Cock D. The ideal mHealth-application for rheumatoid arthritis: qualitative findings from stakeholder focus groups. BMC Musculoskeletal Disorders 2021;22(1) View
  27. Beukenhorst A, Druce K, De Cock D. Smartphones for musculoskeletal research – hype or hope? Lessons from a decennium of mHealth studies. BMC Musculoskeletal Disorders 2022;23(1) View
  28. Humphreys J, Cook L, Clarkson P, Dixon W. The Influence of Chronic Pain on Social Care Service Use in the UK. Journal of Long-Term Care 2022;0(2022):40 View
  29. Schreurs L, Steenhout I, Bosmans J, Buyl R, De Cock D. Can mHealth bridge the digital divide in rheumatic and musculoskeletal conditions?. BMC Digital Health 2023;1(1) View
  30. Hasan B, Fike A, Hasni S. Health disparities in systemic lupus erythematosus—a narrative review. Clinical Rheumatology 2022;41(11):3299 View
  31. Daniore P, Nittas V, von Wyl V. Enrollment and Retention of Participants in Remote Digital Health Studies: Scoping Review and Framework Proposal. Journal of Medical Internet Research 2022;24(9):e39910 View
  32. Das R, Muldoon M, Lunt M, McBeth J, Yimer B, House T, Buchan I. Modelling and classifying joint trajectories of self-reported mood and pain in a large cohort study. PLOS Digital Health 2023;2(3):e0000204 View
  33. Druce K, Cordingley L, Short V, Moore S, Hellman B, James B, Lunt M, Kyle S, Dixon W, McBeth J. Quality of life, sleep and rheumatoid arthritis (QUASAR): a protocol for a prospective UK mHealth study to investigate the relationship between sleep and quality of life in adults with rheumatoid arthritis. BMJ Open 2018;8(1):e018752 View
  34. Little C, Schultz D, House T, Dixon W, McBeth J. Identifying Weekly Trajectories of Pain Severity Using Daily Data From an mHealth Study: Cluster Analysis. JMIR mHealth and uHealth 2024;12:e48582 View