BACKGROUND: Although antidepressants and counseling have been shown to be effective in treating patients with depression, non-treatment or under-treatment for depression is common especially among the elderly and minorities. Previous work on patient preferences has focused on medication versus counseling, but less is known about the value patients place on attributes of medication and counseling. OBJECTIVE: Conjoint analysis has been recognized as a valuable means of assessing patient treatment preferences. We examine how conjoint analysis be used to determine the relative importance of various attributes of depression treatment at the group level as well as to determine the range of individual-level relative preference weights for specific depression treatment attributes. In addition we use conjoint analysis to predict what modifications in treatment characteristics are associated with a change in the stated preferred alternative. STUDY DESIGN: 86 adults who participated in an internet-based panel responded to an on-line discrete choice task about depression treatment. Participants chose between medication and counseling based on choice sets presented first for a "mild depression" scenario and then for a "severe depression" scenario. Participants were given 18 choice sets which varied for medication based on type of side effect (nausea, dizziness, and sexual dysfunction) and severity of side effect (mild, moderate, and severe); and for counseling based on frequency of counseling sessions (once per week or every other week) and location of the sessions (mental health professional's office, primary care doctor's office or office of a spiritual counselor). RESULTS: Treatment type (counseling vs. medication) appeared to be more important in driving treatment choice than any specific attribute that was studied. Specifically counseling was preferred by most of the respondents. After treatment type, location of treatment and frequency of treatment were important considerations. Preferred attributes were similar in both the mild and severe depression scenarios. Side effect severity appeared to be most important in driving treatment choice as compared with the other attributes studied. Individual-level relative preferences for treatment type revealed a distribution that was roughly bimodal with 27 participants who had a strong preference for counseling and 14 respondents who had a strong preference for medication. CONCLUSION: Estimating individual-level preferences for treatment type allowed us to see the variability in preferences and determine which participants had a strong affinity for medication or counseling.
BACKGROUND: Although antidepressants and counseling have been shown to be effective in treating patients with depression, non-treatment or under-treatment for depression is common especially among the elderly and minorities. Previous work on patient preferences has focused on medication versus counseling, but less is known about the value patients place on attributes of medication and counseling. OBJECTIVE: Conjoint analysis has been recognized as a valuable means of assessing patient treatment preferences. We examine how conjoint analysis be used to determine the relative importance of various attributes of depression treatment at the group level as well as to determine the range of individual-level relative preference weights for specific depression treatment attributes. In addition we use conjoint analysis to predict what modifications in treatment characteristics are associated with a change in the stated preferred alternative. STUDY DESIGN: 86 adults who participated in an internet-based panel responded to an on-line discrete choice task about depression treatment. Participants chose between medication and counseling based on choice sets presented first for a "mild depression" scenario and then for a "severe depression" scenario. Participants were given 18 choice sets which varied for medication based on type of side effect (nausea, dizziness, and sexual dysfunction) and severity of side effect (mild, moderate, and severe); and for counseling based on frequency of counseling sessions (once per week or every other week) and location of the sessions (mental health professional's office, primary care doctor's office or office of a spiritual counselor). RESULTS: Treatment type (counseling vs. medication) appeared to be more important in driving treatment choice than any specific attribute that was studied. Specifically counseling was preferred by most of the respondents. After treatment type, location of treatment and frequency of treatment were important considerations. Preferred attributes were similar in both the mild and severe depression scenarios. Side effect severity appeared to be most important in driving treatment choice as compared with the other attributes studied. Individual-level relative preferences for treatment type revealed a distribution that was roughly bimodal with 27 participants who had a strong preference for counseling and 14 respondents who had a strong preference for medication. CONCLUSION: Estimating individual-level preferences for treatment type allowed us to see the variability in preferences and determine which participants had a strong affinity for medication or counseling.
Authors: Bernard van den Berg; Paula Van Dommelen; Piet Stam; Trea Laske-Aldershof; Tom Buchmueller; Frederik T Schut Journal: Soc Sci Med Date: 2008-04-08 Impact factor: 4.634
Authors: Paul A Nutting; Kathryn Rost; Miriam Dickinson; James J Werner; Perry Dickinson; Jeffrey L Smith; Beth Gallovic Journal: J Gen Intern Med Date: 2002-02 Impact factor: 5.128
Authors: Marsha N Wittink; David Oslin; Kathryn A Knott; James C Coyne; Joseph J Gallo; Cynthia Zubritsky Journal: Int J Geriatr Psychiatry Date: 2005-10 Impact factor: 3.485
Authors: Lisa A Cooper; Junius J Gonzales; Joseph J Gallo; Kathryn M Rost; Lisa S Meredith; Lisa V Rubenstein; Nae-Yuh Wang; Daniel E Ford Journal: Med Care Date: 2003-04 Impact factor: 2.983
Authors: Marsha N Wittink; Patrick Walsh; Sule Yilmaz; Michael Mendoza; Richard L Street; Benjamin P Chapman; Paul Duberstein Journal: Patient Educ Couns Date: 2017-08-08
Authors: Patricia M Herman; Maia Ingram; Charles E Cunningham; Heather Rimas; Lucy Murrieta; Kenneth Schachter; Jill Guernsey de Zapien; Scott C Carvajal Journal: Patient Date: 2016-08 Impact factor: 3.883
Authors: Marjan J M Hummel; Fabian Volz; Jeannette G van Manen; Marion Danner; Charalabos-Markos Dintsios; Maarten J Ijzerman; Andreas Gerber Journal: Patient Date: 2012 Impact factor: 3.883
Authors: Cynthia J Mollen; Melissa K Miller; Katie L Hayes; Marsha N Wittink; Frances K Barg Journal: Acad Emerg Med Date: 2013-11 Impact factor: 3.451