Purpose: To describe the process and preliminary qualitative development of a new symptom-based patient-reported outcome measure (PROM) intended to assess hemodialysis treatment-related physical symptoms.
Methods: Experienced interviewers conducted concept elicitation and cognitive debriefing interviews with individuals receiving in-center hemodialysis in the United States. Concept elicitation interviews involved eliciting spontaneous reports of symptom experiences and probing to further explore and confirm concepts. We used patient-reported concepts to generate a preliminary symptom PROM. We conducted 3 rounds of cognitive debriefing interviews to evaluate symptom relevance, item interpretability, and draft item structure. We iteratively refined the measure based on cognitive interview findings.
Results: Forty-two adults receiving in-center hemodialysis participated in the concept elicitation interviews. A total of 12 symptoms were reported by > 10% of interviewees. We developed a 13-item initial draft instrument for testing in 3 rounds of cognitive interviews with an additional 52 hemodialysis patients. Participant responses and feedback during cognitive interviews led to changes in symptom descriptions, division of the single item "nausea/vomiting" into 2 distinct items, removal of daily activity interference items, addition of instructions, and clarification about the recall period, among other changes.
Conclusions: Symptom Monitoring on Renal Replacement Therapy-Hemodialysis (SMaRRT-HD™) is a 14-item PROM intended for use in hemodialysis patents. SMaRRT-HD™ uses a single treatment recall period and a 5-point Likert scale to assess symptom severity. Qualitative interview data provide evidence of its content validity. SMaRRT-HD™ is undergoing additional testing to assess measurement properties and inform measure scoring.
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http://dx.doi.org/10.1007/s11136-018-2000-7 | DOI Listing |
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Department of Dermatology, University of Pennsylvania, Philadelphia.
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Centre for Data Science, Queensland University of Technology, Brisbane, 4000, Australia.
Quantitative population modelling is an invaluable tool for identifying the cascading effects of conservation on an ecosystem. When population data from monitoring programs is not available, deterministic ecosystem models have often been calibrated using the theoretical assumption that ecosystems have a stable, coexisting equilibrium. However, a growing body of literature suggests these theoretical assumptions are inappropriate for conservation contexts.
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School of Health Professions Education (SHE), Faculty of Health, Medicine and Life sciences, Maastricht University, Maastricht, The Netherlands.
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