Can-Pain - a digital intervention to optimise cancer pain control in the community: development and feasibility testing

Rosalind Adam* (Corresponding Author), Christine M. Bond, Christopher D. Burton, Marijn de Bruin, Peter Murchie

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
3 Downloads (Pure)

Abstract

Purpose: To develop a novel digital intervention to optimise cancer pain control in the community. This paper describes intervention development, content/rationale and initial feasibility testing. Methods: Determinants of suboptimal cancer pain management were characterised through two systematic reviews; patient, caregiver and healthcare professional (HCP) interviews (n = 39); and two HCP focus groups (n = 12). Intervention mapping was used to translate results into theory-based content, creating the app “Can-Pain”. Patients with/without a linked caregiver, their general practitioners and community palliative care nurses were recruited to feasibility test Can-Pain over 4 weeks. Results: Patients on strong opioids described challenges balancing pain levels with opioid intake, side effects and activities and communicating about pain management problems with HCPs. Can-Pain addresses these challenges through educational resources, contemporaneous short-acting opioid tracking and weekly patient-reported outcome monitoring. Novel aspects of Can-Pain include the use of contemporaneous breakthrough analgesic reports as a surrogate measure of pain control and measuring the level at which pain becomes bothersome to the individual. Patients were unwell due to advanced cancer, making recruitment to feasibility testing difficult. Two patients and one caregiver used Can-Pain for 4 weeks, sharing weekly reports with four HCPs. Can-Pain highlighted unrecognised problems, promoted shared understanding about symptoms between patients and HCPs and supported shared decision-making. Conclusions: Preliminary testing suggests that Can-Pain is feasible and could promote patient-centred pain management. We will conduct further small-scale evaluations to inform a future randomised, stepped-wedge trial. Trial registration: Qualitative research: ClinicalTrials.gov, reference NCT02341846 Feasibility study: NIHR CPMS database ID 34172.

Original languageEnglish
Pages (from-to)759-769
Number of pages11
JournalSupportive Care in Cancer
Volume29
Issue number2
Early online date28 May 2020
DOIs
Publication statusPublished - Feb 2021

Bibliographical note

Open Access Via the Springer Compact Agreement
Acknowledgements
The authors would like to acknowledge the patients, their caregivers and clinicians who volunteered their time to contribute to intervention development and testing, and Stephanie Inglis, a computer scientist, who completed software programming for the intervention.

Funding
This work was supported by the Chief Scientist Office (CSO), Scottish Government (grant number CAF/14/02), and sponsored by the University of Aberdeen. Neither the funders nor the sponsors had any role in the study design, data collection, data analysis, decision to publish or preparation of the manuscript.

Keywords

  • Behaviour change
  • Cancer
  • Health informatics
  • Intervention mapping
  • Pain
  • Palliative care

Fingerprint

Dive into the research topics of 'Can-Pain - a digital intervention to optimise cancer pain control in the community: development and feasibility testing'. Together they form a unique fingerprint.

Cite this