William E Rosa1, Jesse Chittams2, Barbara Riegel3, Connie M Ulrich3, Salimah H Meghani3. 1. University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania. Electronic address: wrosa@nursing.upenn.edu. 2. BECCA Lab, Office of Nursing Research, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania. 3. University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania.
Abstract
PURPOSE: Many patients with cancer pain deviate from prescribed analgesic regimens. Our aim was to elicit the trade-offs patients make based on their beliefs about analgesic use and rank utilities (importance scores) using maximum difference (MaxDiff) scaling. We also investigated if there were unique clusters of patients based on their analgesic beliefs. METHODS: This was a secondary analysis of a three-month, prospective observational study. Patients (N = 207) were self-identified African Americans and Whites, >18 years, diagnosed with multiple myeloma or solid tumor, and were prescribed at least one around-the-clock analgesic for cancer pain. MaxDiff analysis allowed us to identify patients utilities. Second, a cluster analysis assisted in ranking how analgesic beliefs differed by groups. Third, clusters were described by comparing key sociodemographic and clinical variables. RESULTS: Participants' beliefs were a significant factor in choices related to analgesic use (chi-square = 498.145, p < .0001). The belief, 'Pain meds keep you from knowing what is going on in your body', had the highest patient endorsement. Two distinct clusters of patients based on analgesic beliefs were identified; 'knowing body' was ranked as top priority for both clusters. The belief that cancer patients become addicted to analgesics was moderately important for both clusters. Severity of side effects was the only key variable significantly different between clusters (p = .043). CONCLUSIONS: Our findings support tailored pain management interventions that attend to individual beliefs about cancer pain and analgesic use. Future research should explore the relationship between analgesic utilities, actual analgesic taking behaviors, and how they impact patients' cancer pain outcomes.
PURPOSE: Many patients with cancer pain deviate from prescribed analgesic regimens. Our aim was to elicit the trade-offs patients make based on their beliefs about analgesic use and rank utilities (importance scores) using maximum difference (MaxDiff) scaling. We also investigated if there were unique clusters of patients based on their analgesic beliefs. METHODS: This was a secondary analysis of a three-month, prospective observational study. Patients (N = 207) were self-identified African Americans and Whites, >18 years, diagnosed with multiple myeloma or solid tumor, and were prescribed at least one around-the-clock analgesic for cancer pain. MaxDiff analysis allowed us to identify patients utilities. Second, a cluster analysis assisted in ranking how analgesic beliefs differed by groups. Third, clusters were described by comparing key sociodemographic and clinical variables. RESULTS:Participants' beliefs were a significant factor in choices related to analgesic use (chi-square = 498.145, p < .0001). The belief, 'Pain meds keep you from knowing what is going on in your body', had the highest patient endorsement. Two distinct clusters of patients based on analgesic beliefs were identified; 'knowing body' was ranked as top priority for both clusters. The belief that cancerpatients become addicted to analgesics was moderately important for both clusters. Severity of side effects was the only key variable significantly different between clusters (p = .043). CONCLUSIONS: Our findings support tailored pain management interventions that attend to individual beliefs about cancer pain and analgesic use. Future research should explore the relationship between analgesic utilities, actual analgesic taking behaviors, and how they impact patients' cancer pain outcomes.
Authors: Wendy H Oldenmenger; Jenske I Geerling; Irina Mostovaya; Kris C P Vissers; Alexander de Graeff; Anna K L Reyners; Yvette M van der Linden Journal: Cancer Treat Rev Date: 2017-12-13 Impact factor: 12.111
Authors: Judith A Paice; Russell Portenoy; Christina Lacchetti; Toby Campbell; Andrea Cheville; Marc Citron; Louis S Constine; Andrea Cooper; Paul Glare; Frank Keefe; Lakshmi Koyyalagunta; Michael Levy; Christine Miaskowski; Shirley Otis-Green; Paul Sloan; Eduardo Bruera Journal: J Clin Oncol Date: 2016-07-25 Impact factor: 44.544
Authors: Karen L Schumacher; Vicki L Plano Clark; Claudia M West; Marylin J Dodd; Michael W Rabow; Christine Miaskowski Journal: J Pain Symptom Manage Date: 2014-04-05 Impact factor: 3.612
Authors: William E Rosa; Barbara Riegel; Connie M Ulrich; Jesse Chittams; Ryan Quinn; Salimah H Meghani Journal: Oncol Nurs Forum Date: 2021-01-04 Impact factor: 2.172