Previously submitted to: JMIR Formative Research (no longer under consideration since Jan 25, 2024)
Date Submitted: Aug 13, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Comparing Online Crowdsourcing with Clinic Patient Enrollment: Findings from the IP4IC Study on Interstitial Cystitis/Bladder Pain Syndrome
ABSTRACT
Introduction: Interstitial cystitis/bladder pain syndrome (IC/BPS) manifests as urinary symptoms including urgency, frequency, and pain. The IP4IC Study aimed to establish a urine-based biomarker score for diagnosing IC/BPS. To accomplish this objective, we investigated the parallels and variances between patients enrolled via physician/hospital clinics and those recruited through online crowdsourcing.
Methods:
Through a nationwide crowdsource effort we collected surveys from patients with history of IC/BPS. Study participants were asked to complete the validated instruments of Interstitial Cystitis Symptom Index (ICSI) and Interstitial Cystitis Problem Index (ICPI) as well as provide demographic information. We then compared the survey responses of patients recruited through crowdsourcing with those recruited from three specialized tertiary care urology clinics engaged in clinical research.
Results:
Survey responses of 1300 participants were collected from all 50 states of the USA via crowdsourcing and 319 from a clinical setting. ICSI and ICPI were similar for IC/BPS patients diagnosed by the physicians in clinic and self-reported by subjects via crowdsourcing stating they have a history of previous physician diagnosis of IC/BPS. Surprisingly, ICSI and ICPI were significantly lower in crowdsourced control than in clinic control subjects. Conclusion: The IP4IC Study provides valuable insights into the similarities and differences between patients recruited through clinics and those recruited through online crowdsourcing. There were no significant differences in disease symptoms among these groups. Individuals who express an interest in digital health research and self-identify as having been previously diagnosed by physicians with IC/BPS can be regarded as reliable candidates for crowdsourcing research.
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