Introduction: We created and tested a mobile app that facilitates the ecological momentary assessment of pain intensity and pain location and identifies heterogeneous patient pain phenotypes.

Methods: A mobile app was created with patient, clinician and researcher input. A sample of 20 participants with urologic chronic pelvic pain syndrome were then asked to complete a 14-day pain assessment using the app. Data were analyzed to assess compliance, usability and the ability for the app to capture variation in pain intensity and pain location. Ecological momentary assessment pain data were then compared to end-of-week pain summary questions to determine construct validity.

Results: Mean compliance was 70±8%, higher earlier in the study period (p <0.0005) and better in older individuals (p <0.0001). During the 14-day assessment, 90% of participants reported daily variation in pelvic pain intensity (SD 0.64-3.02; out of 10), 95% reported variation in their nonpelvic pain (SD 0.17-3.63; out of 10) and 100% reported variations in number of sites with pain (SD 0.22-1.44; out of 7). Pelvic pain and nonpelvic pain intensity, as determined by cumulative app scores, were associated with patient reported end-of-week scores; worst pain ( =0.67; =0.53) and average pain ( =0.78; =0.73).

Conclusions: The easy-to-use app captured unique patterns of pain not fully captured by traditional end-of-day/week summary questions or by traditional in-office assessments. Mobile apps for assessing chronic conditions will become increasingly important as telehealth becomes more commonplace.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9662822PMC
http://dx.doi.org/10.1097/UPJ.0000000000000203DOI Listing

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