Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain

Area of Science:

• Digital Health
• Clinical Research Methods
• Pain Management

Background:

• Smartphone-based ecological momentary assessment (EMA) is underutilized in clinical settings despite its potential for healthcare data collection.
• Low back pain management can benefit from innovative data collection methods due to limited treatment efficacy.

Purpose of the Study:

• To assess the feasibility of smartphone EMA for collecting low back pain and function data.
• To compare EMA-collected pain data with traditional assessment methods.
• To characterize individual patient progress and investigate technology adoption using the Model of Technology Appropriation.

Main Methods:

• Feasibility study employing smartphone-based ecological momentary assessment (EMA) for pain and function data collection.
• Comparison of EMA-derived pain intensity index with traditional change in pain intensity measures.
• Qualitative and quantitative analysis of participant data and technology appropriation.

Main Results:

• Smartphone EMA is a feasible method for collecting low back pain and function data.
• The 'pain intensity index' from EMA provides a unique measure of pain burden, complementing traditional metrics.
• Significant individual variations in pain and function were observed, which are missed by cohort-based mean scores.

Conclusions:

• Smartphone-based EMA is a highly acceptable and effective tool for enhancing outcome data collection in low back pain research.
• EMA facilitates a personalized approach to managing low back pain by capturing dynamic individual experiences.
• The study supports the integration of EMA into clinical practice for more nuanced patient monitoring and care.