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Using patient characteristics and attitudinal data to identify depression treatment preference groups: a latent-class
Jennifer A Thacher1, Edward Morey, W Edward Craighead
1Department of Economics, University of New Mexico, Albuquerque, New Mexico 87131, USA. jthacher@unm.edu
Depression and Anxiety
|May 11, 2005
Summary
Patient preferences for depression treatment vary. A study identified three groups based on sensitivity to effectiveness, cost, and side effects, aiding personalized care for Major Depressive Disorder.
Area of Science:
- Psychiatry
- Behavioral Science
- Health Services Research
Background:
- Patient preferences significantly influence treatment adherence and outcomes in managing Major Depressive Disorder (MDD).
- Understanding diverse patient attitudes towards treatment is crucial for effective clinical decision-making.
Purpose of the Study:
- To identify and characterize distinct patient groups based on their treatment preferences for depression.
- To predict the likelihood of a patient belonging to a specific preference group using observable characteristics and attitudinal data.
Main Methods:
- Latent-class modeling was applied to survey data from 104 patients with Major Depressive Disorder.
- Attitudinal questions and observable characteristics were used to define patient preference classes.
Main Results:
- Three distinct patient preference classes emerged, varying in their sensitivity to treatment costs and side effects.
- Class 1 prioritized treatment effectiveness, largely disregarding costs and side effects.
- Class 2 exhibited high sensitivity to costs and side effects, while Class 3 showed moderate sensitivity. Younger and male patients were more inclined towards sensitivity to costs and side effects.
Conclusions:
- Patient preferences for depression treatment are heterogeneous.
- Identifying these preference groups allows clinicians to tailor treatment strategies, potentially improving patient adherence and outcomes for Major Depressive Disorder.