The Patient: Patient-Centered Outcomes Research

, Volume 3, Issue 3, pp 145–157 | Cite as

Towards Patient-Centered Care for Depression

Conjoint Methods to Tailor Treatment Based on Preferences
  • Marsha N. WittinkEmail author
  • Mark Cary
  • Thomas TenHave
  • Jonathan Baron
  • Joseph J. Gallo
Original Research Article


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 that patients place on attributes of medication and counseling.

Objective: To examine, using conjoint analysis, 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, to predict what modifications in treatment characteristics are associated with a change in the stated preferred alternative.

Methods: A total of 86 adults who participated in an internet-based panel responded to an online 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 that 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 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 compared with the other attributes studied. Individual-level relative preferences for treatment type revealed a distribution that was roughly bimodal; 27 participants had a strong preference for counseling and 14 had a strong preference for medication.

Conclusions: 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. We found that participants preferred counseling over medication, avoided options with severe side effects, and wanted to be seen in the primary-care doctor’s office as opposed to other venues.


Counseling Session Choice Task Conjoint Analysis Depression Treatment Mild Depression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Dr Wittink was supported by a National Institute of Mental Health (NIMH) Mentored Patient-Oriented Research Career Development Award (MH19931) and an NIMH sponsored grant entitled ‘Developing Methods for Tailoring Depression Treatment to Older Adults 80’ (R34 MH085906).

The authors have no conflicts of interest that are directly relevant to the content of this study.

Dr Wittink also wishes to thank her late father, Dr Dick R. Wittink, a marketing and econometrics researcher, for introducing her to conjoint analysis.

Supplementary material

40271_2012_3030145_MOESM1_ESM.pdf (196 kb)
Supplementary material, approximately 200 KB.


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Copyright information

© Adis Data Information BV 2010

Authors and Affiliations

  • Marsha N. Wittink
    • 1
    • 2
    Email author
  • Mark Cary
    • 2
  • Thomas TenHave
    • 2
  • Jonathan Baron
    • 3
  • Joseph J. Gallo
    • 1
  1. 1.Department of Family Medicine and Community Health, School of MedicineUniversity of Pennsylvania School of MedicinePhiladelphiaUSA
  2. 2.Center for Clinical Epidemiology and BiostatisticsUniversity of Pennsylvania School of MedicinePhiladelphiaUSA
  3. 3.Department of Psychology, School of Arts and SciencesUniversity of PennsylvaniaPhiladelphiaUSA

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