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. A separate "capture app" was designed to collect global positioning system (GPS) and continuous raw accelerometer data, with the GPS-linking providing local weather data. A total of 20 patients with RA were then recruited to collect daily data for 60 days, with entry and exit interviews. Of these, 17 were loaned an Android smartphone, whereas 3 used their own Android smartphones.


RESULTS
Of the 20 patients, 6 (30%) withdrew from the study: 4 because of technical challenges and 2 for health reasons. The mean completion of daily entries was 68% over 2 months. Patients entered data at least five times per week 65% of the time. Reasons for successful engagement included a simple graphical user interface, automated reminders, visualization of data, and eagerness to contribute to this easily understood research question. The main barrier to continuing engagement was impaired battery life due to the accelerometer data capture app. For some, successful engagement required ongoing support in using the smartphones.


CONCLUSIONS
This successful pilot study has demonstrated that daily data collection using smartphones for health research is feasible and achievable with high levels of ongoing engagement over 2 months. This result opens important opportunities for large-scale longitudinal epidemiological research.
Manchester Medical School, University of Manchester, Manchester, United Kingdom.|Manchester Academic Health Science Centre, Arthritis Research UK Centre for Epidemiology, University of Manchester, Manchester, United Kingdom.
Samuel
http://orcid.org/0000-0002-2769-874X
S
Reade
Manchester Academic Health Science Centre, Arthritis Research UK Centre for Epidemiology, University of Manchester, Manchester, United Kingdom.
Karen
http://orcid.org/0000-0003-2038-2600
K
Spencer
Manchester Academic Health Science Centre, Arthritis Research UK Centre for Epidemiology, University of Manchester, Manchester, United Kingdom.|National Institute of Health Research, Manchester Musculoskeletal Biomedical Research Unit, Central Manchester NHS Foundation Trust, Manchester, United Kingdom.
Jamie C
http://orcid.org/0000-0002-9000-4413
JC
Sergeant
The Farr Institute @ Health eResearch Centre, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom.
Matthew
http://orcid.org/0000-0002-5351-9960
M
Sperrin
School of Earth, Atmospheric & Environmental Sciences, The University of Manchester, United Kingdom.
David M
http://orcid.org/0000-0003-1558-6975
DM
Schultz
National Institute of Health Research, Manchester Musculoskeletal Biomedical Research Unit, Central Manchester NHS Foundation Trust, Manchester, United Kingdom.
John
http://orcid.org/0000-0002-2187-9195
J
Ainsworth
uMotif Limited, London, United Kingdom.
Rashmi
http://orcid.org/0000-0001-9183-9079
R
Lakshminarayana
uMotif Limited, London, United Kingdom.
Bruce
http://orcid.org/0000-0002-8015-8187
B
Hellman
uMotif Limited, London, United Kingdom.
Ben
http://orcid.org/0000-0003-2381-6531
B
James
Manchester Academic Health Science Centre, Arthritis Research UK Centre for Epidemiology, University of Manchester, Manchester, United Kingdom.
John
http://orcid.org/0000-0001-7047-2183
J
McBeth
Manchester Academic Health Science Centre, Centre for Primary Care, The University of Manchester, Manchester, United Kingdom.
Caroline
http://orcid.org/0000-0002-0539-928X
C
Sanders
Manchester Academic Health Science Centre, Arthritis Research UK Centre for Epidemiology, University of Manchester, Manchester, United Kingdom.|The Farr Institute @ Health eResearch Centre, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom.|Salford Royal NHS Foundation Trust, Rheumatology Department, Salford, United Kingdom.
William G
http://orcid.org/0000-0001-5881-4857
WG
Dixon
arthritis; attrition; mHealth; smartphone; weather