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Supporting Pain Self-Management in Patients With Cancer: App Development Based on a Theoretical and Evidence-Driven
Asma A Abahussin1, Robert M West2, David C Wong2
1Department of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
This study systematically designed a cancer pain self-management app using the Behavior Change Wheel (BCW) framework. The app targets capability, opportunity, and motivation deficits to improve patient self-management.
Area of Science:
- Digital health interventions
- Behavioral science
- Oncology patient support
Background:
- Complex interventions require theoretical foundations for effective development, as per UK Medical Research Council guidelines.
- Mobile health (mHealth) app development for cancer pain self-management often lacks theoretical underpinnings.
Purpose of the Study:
- To systematically design a theory- and evidence-driven mobile application for cancer pain self-management.
- To identify and specify the active features of the pain self-management app.
Main Methods:
- The Behavior Change Wheel (BCW) framework was employed for a structured, step-by-step intervention development process.
- Behavioral sources (capability, opportunity, motivation) for pain self-management were identified.
- The Behavior Change Technique Taxonomy (v1) was used to define the app's active contents.
Main Results:
- Theoretical analysis indicated that deficits in capability, opportunity, and motivation hinder cancer pain self-management.
- Education, persuasion, training, and enablement were identified as key intervention functions.
- Eighteen specific behavior change techniques were selected to operationalize these functions within the app.
Conclusions:
- A theory- and evidence-based design for a cancer pain self-management app has been developed and is reported.
- This study offers a model application of the BCW framework for health app development.
- The systematic approach enhances clarity for evaluating intervention mechanisms and facilitates future replication.
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