UNLABELLED: We studied the ranking of osteoporosis (OP) medication attributes in a convenience sample of four different racial/ethnic groups in the United States. Our study showed that postmenopausal women differ in the ranking of OP medication attributes based on age, educational level, income, and prior fracture history. INTRODUCTION: Decision making about OP medication-related behavior relies heavily on patient preferences about specific medication attributes. Patients may decide to initiate, change, or stop therapies based on ranking of perceived attributes of the therapy and their personal attitudes toward those attributes. We used MaxDiff, a form of conjoint analysis (Ryan and Farrar 2000), to explore patient weighting of attributes across four racial/ethnic groups at two sites in the United States and defined four critical attributes that influence such decisions (safety, efficacy, cost, and convenience) from qualitative interviews. METHODS: We recruited a sample of 367 Postmenopausal (PM) women at risk of OP fractures from four racial/ethnic groups: Caucasian (n = 100), African American (n = 100), Asian American (n = 82), and Hispanic American (n = 85). Respondents completed a laptop-based questionnaire that included demographic items, several short scales on medical care preference and OP patient perceptions, and a MaxDiff procedure that determines comparative ranking of attributes either as least important or most important to their decisions. RESULTS: MaxDiff analyses were done to evaluate the relative weight of specific statements for each participant and to determine whether racial/ethnic groups differed across dimensions. Overall, participants in all four groups rated efficacy > safety > cost > convenience. CONCLUSIONS: Although there were no significant differences among the racial/ethnic groups on overall ranking of attributes, subgroup analyses revealed significant impact of age, education, income, and prior fracture on these decisions. The findings from this study suggest that postmenopausal women differ in their ranking of OP medication attributes, and healthcare providers must account for personal preferences in their communication about and selection of OP medications.
UNLABELLED: We studied the ranking of osteoporosis (OP) medication attributes in a convenience sample of four different racial/ethnic groups in the United States. Our study showed that postmenopausal women differ in the ranking of OP medication attributes based on age, educational level, income, and prior fracture history. INTRODUCTION: Decision making about OP medication-related behavior relies heavily on patient preferences about specific medication attributes. Patients may decide to initiate, change, or stop therapies based on ranking of perceived attributes of the therapy and their personal attitudes toward those attributes. We used MaxDiff, a form of conjoint analysis (Ryan and Farrar 2000), to explore patient weighting of attributes across four racial/ethnic groups at two sites in the United States and defined four critical attributes that influence such decisions (safety, efficacy, cost, and convenience) from qualitative interviews. METHODS: We recruited a sample of 367 Postmenopausal (PM) women at risk of OP fractures from four racial/ethnic groups: Caucasian (n = 100), African American (n = 100), Asian American (n = 82), and Hispanic American (n = 85). Respondents completed a laptop-based questionnaire that included demographic items, several short scales on medical care preference and OP patient perceptions, and a MaxDiff procedure that determines comparative ranking of attributes either as least important or most important to their decisions. RESULTS: MaxDiff analyses were done to evaluate the relative weight of specific statements for each participant and to determine whether racial/ethnic groups differed across dimensions. Overall, participants in all four groups rated efficacy > safety > cost > convenience. CONCLUSIONS: Although there were no significant differences among the racial/ethnic groups on overall ranking of attributes, subgroup analyses revealed significant impact of age, education, income, and prior fracture on these decisions. The findings from this study suggest that postmenopausal women differ in their ranking of OP medication attributes, and healthcare providers must account for personal preferences in their communication about and selection of OP medications.
Authors: Deborah Marshall; John F P Bridges; Brett Hauber; Ruthanne Cameron; Lauren Donnalley; Ken Fyie; F Reed Johnson Journal: Patient Date: 2010-12-01 Impact factor: 3.883
Authors: Dima M Qato; Stacy Tessler Lindau; Rena M Conti; L Philip Schumm; G Caleb Alexander Journal: Pharmacoepidemiol Drug Saf Date: 2010-08 Impact factor: 2.890
Authors: J Darbà; G Restovic; L Kaskens; M A Balbona; A Carbonell; P Cavero; M Jordana; C Prieto; A Molina; I Padró Journal: Osteoporos Int Date: 2010-09-14 Impact factor: 4.507
Authors: Esther W de Bekker-Grob; Marie-Louise Essink-Bot; Willem Jan Meerding; Bart W Koes; Ewout W Steyerberg Journal: Pharmacoeconomics Date: 2009 Impact factor: 4.981
Authors: Annette M O'Connor; Carol L Bennett; Dawn Stacey; Michael Barry; Nananda F Col; Karen B Eden; Vikki A Entwistle; Valerie Fiset; Margaret Holmes-Rovner; Sara Khangura; Hilary Llewellyn-Thomas; David Rovner Journal: Cochrane Database Syst Rev Date: 2009-07-08
Authors: Lindsay A Hampson; Tracy K Lin; Leslie Wilson; Isabel E Allen; Thomas W Gaither; Benjamin N Breyer Journal: World J Urol Date: 2017-06-29 Impact factor: 4.226
Authors: Lindsay A Hampson; Isabel E Allen; Thomas W Gaither; Tracy Lin; Jie Ting; E Charles Osterberg; Leslie Wilson; Benjamin N Breyer Journal: Urology Date: 2016-09-16 Impact factor: 2.649
Authors: Leslie Wilson; Tracy Kuo Lin; Lindsay A Hampson; Anna Oh; Jie Ting; Thomas Gaither; Isabel Allen; Benjamin N Breyer Journal: J Particip Med Date: 2017-01-14
Authors: Mickaël Hiligsmann; Benedict G Dellaert; Carmen D Dirksen; Trudy van der Weijden; Stefan Goemaere; Jean-Yves Reginster; Verity Watson; Annelies Boonen Journal: Arthritis Res Ther Date: 2014-01-31 Impact factor: 5.156