TY - JOUR
T1 - Towards personalizing treatment for depression
T2 - Developing treatment values markers
AU - Wittink, Marsha N.
AU - Morales, Knashawn H.
AU - Cary, Mark
AU - Gallo, Joseph J.
AU - Bartels, Stephen J.
N1 - Funding Information:
Acknowledgments Each of the authors contributed significantly to the conceptualization of this project and the writing of this manuscript. In particular, Dr. Wittink is the guarantor for the paper and was responsible for the overall conceptualization of the study, and the collection and interpretation of the data. Dr. Morales contributed to the LPAs and Dr. Cary was responsible for creating and analyzing the conjoint surveys using SAS. Drs. Gallo and Bartels contributed to the larger conceptualization of the notion of ‘values markers’ and to the writing of the manuscript. The authors gratefully acknowledge the support of the RAND/Hartford Center for Interdisciplinary Health Care Research (Principal Investigator [PI]: Mary Naylor PhD RN FAAN) and the National Institute of Mental Health (NIMH)-funded Advanced Center for Intervention Services Research (ACISR) focused on Depression and Medical Care (P30 MH066270) [PI: Ira Katz MD]. The authors have no conflicts of interest to declare.
Funding Information:
Funding: Dr. Wittink was supported by an NIMH Mentored Patient-Oriented Research Career Development Award (K23 MH19931) and an NIMH sponsored grant entitled ‘‘Developing Methods for Tailoring Depression Treatment to Older Adults’’ (R34 MH085906). Dr. Morales was supported by an NIMH Mentored Research Scientist Career Development Award (K01 MH073903).
PY - 2013/3
Y1 - 2013/3
N2 - Background: While 'personalized medicine' commonly refers to genetic markers or profiles associated with pharmacological treatment response, tailoring treatments to patient preferences and values is equally important. Objective: To describe and demonstrate a method to develop 'values markers,' or profiles based on the relative importance of attributes of depression treatment. Study Design: Discrete choice analysis was used to assess individuals' relative preferences for features of depression treatment. Preference profiles were developed using latent profile analysis. Patients or Other Participants: Eighty-six adults participating in an internet-based discrete choice questionnaire. Main Outcome Measure: Participants were presented with two depression scenarios representing mild and severe depression. For each scenario, they were asked to compare 18 choice sets based on the type of medication side effect (nausea, dizziness, and sexual dysfunction) and severity (mild, moderate, and severe); and for counseling frequency (once per week or every other week) and provider setting (the office of a mental health professional, primary care doctor, or spiritual counselor). Results: Three profiles were identified: profile 1 was associated with a preference for counseling and an avoidance of medication side effects; profile 2 with an avoidance of strong medication side effects and for receiving counseling in medical settings; and profile 3 with a preference for medication over counseling. When presented with a severe depression scenario, there was a higher prevalence for profile 1 and patients were more likely to prefer mental health over primary care and spiritual settings. Conclusions: Values markers may provide a foundation for personalized medicine, and reflect current initiatives emphasizing patient-centered care. Next steps should assess whether values markers are predictive of treatment initiation and adherence.
AB - Background: While 'personalized medicine' commonly refers to genetic markers or profiles associated with pharmacological treatment response, tailoring treatments to patient preferences and values is equally important. Objective: To describe and demonstrate a method to develop 'values markers,' or profiles based on the relative importance of attributes of depression treatment. Study Design: Discrete choice analysis was used to assess individuals' relative preferences for features of depression treatment. Preference profiles were developed using latent profile analysis. Patients or Other Participants: Eighty-six adults participating in an internet-based discrete choice questionnaire. Main Outcome Measure: Participants were presented with two depression scenarios representing mild and severe depression. For each scenario, they were asked to compare 18 choice sets based on the type of medication side effect (nausea, dizziness, and sexual dysfunction) and severity (mild, moderate, and severe); and for counseling frequency (once per week or every other week) and provider setting (the office of a mental health professional, primary care doctor, or spiritual counselor). Results: Three profiles were identified: profile 1 was associated with a preference for counseling and an avoidance of medication side effects; profile 2 with an avoidance of strong medication side effects and for receiving counseling in medical settings; and profile 3 with a preference for medication over counseling. When presented with a severe depression scenario, there was a higher prevalence for profile 1 and patients were more likely to prefer mental health over primary care and spiritual settings. Conclusions: Values markers may provide a foundation for personalized medicine, and reflect current initiatives emphasizing patient-centered care. Next steps should assess whether values markers are predictive of treatment initiation and adherence.
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U2 - 10.1007/s40271-013-0003-6
DO - 10.1007/s40271-013-0003-6
M3 - Article
C2 - 23420133
AN - SCOPUS:84874638814
SN - 1178-1653
VL - 6
SP - 35
EP - 43
JO - Patient
JF - Patient
IS - 1
ER -