ArticleNeurourology and urodynamics2024
Ecological momentary assessment of pelvic pain and urinary urgency variability in urologic chronic pelvic pain syndrome and their association with illness impact and quality of life: Findings from the multidisciplinary approach to the study of chronic pelvic pain symptom patterns study.
Article in Neurourology and urodynamics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 3 citations in OpenAlex.
- Smartphone-Based Ecological Momentary Assessment of Pain in Older Adults Undergoing Auricular Point Acupressure for Chronic Low Back Pain: Secondary Analysis of a Randomized Controlled Trial.JMIR formative research · 2026Trial
- Ecological Momentary Assessment Reveals Greater Anxiety and Marked Instability of Urinary Urgency in Overactive Bladder.International urogynecology journal · 2026Article
- Urologic chronic pelvic pain syndrome 3-year symptom trajectories: the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Symptom Patterns Study.BJU international · 2026Article
- Urologic Chronic Pelvic Pain Syndrome: A Scoping Review of Syndrome-Specific Instruments.Neurourology and urodynamics · 2025Article
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Authors and funding
19 authors at 9 institutions in 1 country.
Funding
Abstract
purposeThis study tested the hypothesis that ecological momentary assessment (EMA) of pelvic pain (PP) and urinary urgency (UU) would reveal unique Urologic Chronic Pelvic Pain Syndrome (UCPPS) phenotypes that would be associated with disease specific quality of life (QOL) and illness impact metrics (IIM). MATERIALS AND
methodsA previously validated smart phone app (M-app) was provided to willing Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) participants. M-app notifications were sent 4-times daily for 14 days inquiring about PP and UU severity. A clustering algorithm that accounted for variance placed participants into PP and UU variability? clusters. Associations between clusters and QOL and IIM were then determined.
resultsA total of 204 participants enrolled in the M-app study (64% female). M-app compliance was high (median 63% of surveys). Cluster analysis revealed k = 3 (high, low, none) PP clusters and k = 2 (high, low) UU clusters. When adjusting for baseline pain severity, high PP variability, but not UU variability, was strongly associated with QOL and IIM; specifically worse mood, worse sleep and higher anxiety. UU and PP clusters were associated with each other (p < 0.0001), but a large percentage (33%) of patients with high PP variability had low UU variability.
conclusionsPP variability is an independent predictor of worse QOL and more severe IIM in UCPPS participants after controlling for baseline pain severity and UU. These findings suggest alternative pain indices, such as pain variability and unpredictability, may be useful adjuncts to traditional measures of worst and average pain when assessing UCPPS treatment responses.
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