Login to Access Video or Poster Abstract: MP86-08
Sources of Funding: MAPP Research Network grants (U01, NIDDK) to the University of Iowa and Northwestern University.

Introduction

Pain in patients with chronic pelvic pain varies widely by location, intensity, severity and by its intermittency. Static assessment of pain does not allow for a comprehensive description of this inherent heterogeneity of pain, potentially obscuring phenotypic differences in UCPPS patients that could help predict treatment response and disease course. Ecological Momentary Assessment (EMA) of pain is a way to describe pain more comprehensively. Mobile apps can communicate directly with patients at all times of the day in most locations and are thus, perfectly suited to collect EMA pain data. For the Multidisciplinary Approach to Pelvic Pain (MAPP) Research Network, we developed a mobile app to capture pain and associated symptoms in a time-efficient manner. We present the results from the app beta testing herein. We hypothesized that participants would find the app easy to use and that utilization of the app would reveal significant daily pain variability.

Methods

A total of 22 participants completed beta testing for 14 days, locating and rating their pain and other symptoms. Mobile phone notifications that linked to and opened the app were sent at wake up, 4 and 8 hours after wake-up and bedtime. On Day 15 participants completed the NASA task load index to assess app usability and satisfaction. Participants then completed a qualitative exit interview to give us feedback on all aspects of the app and testing. Thus, we obtained both quantitative and qualitative information during the beta-testing period.

Results

We created a summary score for pain using the maximum pain rating across different areas of the body at a particular time. Using a linear model with time of day, nested with testing day, we found that pain varied significantly during the day, F (37, 257) = 1.75, p = .007. Qualitative interviews and App ratings (see figure) suggested that the app was simple and easy to use (e.g. low mental demand, high app compliance)

Conclusions

Our quantitative and qualitative results show that our app is easy to use for participants and is able to capture intra-day variability in pain across multiple areas of the body. Moreover, our participants indicated that they would be willing to use this app going forward both for research and clinical/treatment purposes. Mobile apps appear to be well-suited to study chronic urologic conditions. Utilization of the app for EPA testing is currently underway within the MAPP Research Network.

Funding

MAPP Research Network grants (U01, NIDDK) to the University of Iowa and Northwestern University.