Recruitment and ongoing engagement in a UK smartphone study examining the association between weather and pain

Katie Druce, John Mcbeth, Sabine Van Der Veer, David Selby, Bertie Vidgen, Konstantinos Georgatzis, Bruce Hellman , Rashmi Lakshminarayana , Afiqul chowdhury, David Schultz, Caroline Sanders, Jamie Sergeant, William Dixon

Research output: Contribution to journalArticlepeer-review

Abstract

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 studies.
Objectives:
Methods: Participants who had chronic pain (≥3months) and enrolled between 20/01/16 and 29/01/16 were eligible if they were aged ≥17 years and used the study app to report any of ten pain-related symptoms during the study period. Participant characteristics were compared to data from the Health Survey for England (HSE) 2011. Distinct clusters of engagement over time were determined using first-order hidden Markov models and participant characteristics were compared between the clusters.
Results: Compared to the data from the HSE, our sample comprised a higher proportion of women (81% vs 56%) and fewer persons at the extremes of age. Four clusters of engagement were identified: high (14%), moderate (22%), low (39%) and tourists (25%), between which median days of data entry ranged from 1 (IQR:1-1;tourist) to 149 (124-163;high). Those in the high engagement cluster were typically older, whilst the tourist cluster was more commonly male. Few other differences distinguished the clusters.
Conclusions: Cloudy with a Chance of Pain demonstrates a rapid and successful recruitment of a large, representative and engaged sample of people with chronic pain, and provides strong evidence to suggest that smartphones could provide a viable alternative to traditional data collection methods.
Original languageEnglish
Article numbere168
JournalJMIR mHealth and uHealth
Volume5
Issue number11
DOIs
Publication statusPublished - 1 Nov 2017

Keywords

  • Epidemiology
  • mHealth
  • Chronic pain
  • Methods

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