Remote sampling of biomarkers of inflammation with linked patient generated health data in patients with rheumatic and musculoskeletal diseases: an Ecological Momentary Assessment feasibility study.

Background: People with rheumatic diseases experience troublesome fluctuations in fatigue. Debated causes include pain, mood and inflammation. To determine the relationships between these potential causes, serial assessments are required but are methodologically challenging.

Sleep Disturbance and Quality of Life in Rheumatoid Arthritis: Prospective mHealth Study.

Background: Sleep disturbances and poor health-related quality of life (HRQoL) are common in people with rheumatoid arthritis (RA). Sleep disturbances, such as less total sleep time, more waking periods after sleep onset, and higher levels of nonrestorative sleep, may be a driver of HRQoL. However, understanding whether these sleep disturbances reduce HRQoL has, to date, been challenging because of the need to collect complex time-varying data at high resolution.

Pilot study of smartphone-based health outcome tracking (OurBrainBank) for glioblastoma patients.

Background: Patients with glioblastoma (GBM) typically have high symptom burden impacting on quality of life. Mobile apps may help patients track their condition and provide real-time data to clinicians and researchers. We developed a health outcome reporting app (OurBrainBank [OBB]) for GBM patients.

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

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.

The BRadykinesia Akinesia INcoordination (BRAIN) Tap Test: Capturing the Sequence Effect.

Background: The BRadykinesia Akinesia INcoordination (BRAIN) tap test is an online keyboard tapping task that has been previously validated to assess upper limb motor function in Parkinson's disease (PD).

Objectives: To develop a new parameter that detects a sequence effect and to reliably distinguish between PD patients and medication. In addition, we sought to validate a mobile version of the test for use on smartphones and tablet devices.

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.

: This study aims to assess the specific difference of the health-related quality of life between people with Parkinson's and non-Parkinson's. : A total of 1710 people were drawn from a prospective study with a smartphone-based survey named '100 for Parkinson's' to assess health-related quality of life. The EQ-5D-5L descriptive system and the EQ visual analogue scale were used to measure health-related quality of life and a linear mixed model was used to analyze the difference.

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.

Introduction: People with rheumatoid arthritis (RA) frequently report reduced health-related quality of life (HRQoL), the impact one's health has on physical, emotional and social well-being. There are likely numerous causes for poor HRQoL, but people with RA have identified sleep disturbances as a key contributor to their well-being. This study will identify sleep/wake rhythm-associated parameters that predict HRQoL in patients with RA.

Erratum: Author Correction: Using a smartphone-based self-management platform to support medication adherence and clinical consultation in Parkinson's disease.

[This corrects the article DOI: 10.1038/s41531-016-0003-z.].

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

Background: The huge increase in smartphone use heralds an enormous opportunity for epidemiology research, but there is limited evidence regarding long-term engagement and attrition in mobile health (mHealth) studies.

Objective: The objective of this study was to examine how representative the Cloudy with a Chance of Pain study population is of wider chronic-pain populations and to explore patterns of engagement among participants during the first 6 months of the study.

Methods: Participants in the United Kingdom who had chronic pain (≥3 months) and enrolled between January 20, 2016 and January 29, 2016 were eligible if they were aged ≥17 years and used the study app to report any of 10 pain-related symptoms during the study period.

Using a smartphone-based self-management platform to support medication adherence and clinical consultation in Parkinson's disease.

The progressive nature of Parkinson's disease, its complex treatment regimens and the high rates of comorbid conditions make self-management and treatment adherence a challenge. Clinicians have limited face-to-face consultation time with Parkinson's disease patients, making it difficult to comprehensively address non-adherence. Here we share the results from a multi-centre (seven centres) randomised controlled trial conducted in England and Scotland to assess the impact of using a smartphone-based Parkinson's tracker app to promote patient self-management, enhance treatment adherence and quality of clinical consultation.

Cloudy with a Chance of Pain: Engagement and Subsequent Attrition of Daily Data Entry in a Smartphone Pilot Study Tracking Weather, Disease Severity, and Physical Activity in Patients With Rheumatoid Arthritis.

Background: The increasing ownership of smartphones provides major opportunities for epidemiological research through self-reported and passively collected data.

Objective: This pilot study aimed to codesign a smartphone app to assess associations between weather and joint pain in patients with rheumatoid arthritis (RA) and to study the success of daily self-reported data entry over a 60-day period and the enablers of and barriers to data collection.

Methods: A patient and public involvement group (n=5) and 2 focus groups of patients with RA (n=9) supported the codesign of the app collecting self-reported symptoms.

Smartphone- and internet-assisted self-management and adherence tools to manage Parkinson's disease (SMART-PD): study protocol for a randomised controlled trial (v7; 15 August 2014).

Background: Nonadherence to treatment leads to suboptimal treatment outcomes and enormous costs to the economy. This is especially important in Parkinson's disease (PD). The progressive nature of the degenerative process, the complex treatment regimens and the high rates of comorbid conditions make treatment adherence in PD a challenge.