Development and validation of a pain monitoring app for patients with musculoskeletal conditions (The Keele pain recorder feasibility study)

John Bedson*, Jonathon Hill, David White, Ying Chen, Simon Wathall, Stephen Dent, Kendra Cooke, Danielle Van Der Windt

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

Background: Assessing daily change in pain and related symptoms help in diagnosis, prognosis, and monitoring response to treatment. However, such changes are infrequently assessed, and usually reviewed weeks or months after the start of treatment. We therefore developed a smartphone application (Keele Pain Recorder) to record information on the severity and impact of pain on daily life. Specifically, the study goal was to assess face, content and construct validity of data collection using the Pain Recorder in primary care patients receiving new analgesic prescriptions for musculoskeletal pain, as well as to assess its acceptability and clinical utility. Methods: The app was developed with Keele's Research User Group (RUG), a clinical advisory group (CAG) and software developer for use on Android devices. The app recorded pain levels, interference, sleep disturbance, analgesic use, mood and side effects. In a feasibility study, patients aged > 18 attending their general practitioner (GP) with a painful musculoskeletal condition were recruited to use the app twice per day for 28 days. Face and construct validity were assessed through baseline and post-study questionnaires (Spearman's rank correlation coefficient). Usability and acceptability were determined through post-study questionnaires, and patient, GP, RUG and CAG interviews. Results: An app was developed which was liked by both patients and GPs. It was felt that it offered the opportunity for GPs to discuss pain control with their patients in a new way. All participants found the app easy to use (it did not interfere with their activities) and results easy to interpret. Strong associations existed between the first 3 days (Spearman r = 0.79) and last 3 days (r = 0.60) of pain levels and intensity scores on the app with the validated questionnaires. Conclusions: Collaborating with patient representatives and clinical stakeholders, we developed an app which can be used to help clinicians and patients monitor painful musculoskeletal conditions in response to analgesic prescribing. Recordings were accurate and valid, especially, for pain intensity ratings, and it was easy to use. Future work needs to examine how pain trajectories can help manage changes in a patient's condition, ultimately assisting in self-management.

Original languageEnglish
Article number24
JournalBMC Medical Informatics and Decision Making
Volume19
Issue number1
DOIs
Publication statusPublished - 25 Jan 2019
Externally publishedYes

Keywords

  • App
  • Application
  • Assessment
  • Musculoskeletal
  • Pain
  • Primary care
  • Smartphone
  • Telehealth
  • eHealth

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