Using patient characteristics and attitudinal data to identify depression treatment preference groups: A latent-class model

摘要

A latent-class model is used to identify and characterize groups of patients who share similar attitudes towards treating depression. The results predict the probability of preference-g-roup membership on the basis of observable characteristics and answers to attitudinal questions. Understanding the types of preference groups that exist and a patient's probability of membership in each of the groups can help clinicians tailor the treatment to the patient and may increase patient adherence. One hundred four depressed patients completed a survey on attitudes towards treatment of Major Depressive Disorder. Analysis shows that treatment preferences vary among depressed patients. Three classes are identified that differ in their sensitivity to treatment costs and side effects. One class cares primarily about treatment effectiveness; side effects and the cost of treatment have little impact on this class's treatment decisions. Another class is highly sensitive to cost and side effects. A third class is somewhat sensitive to cost and side effects. Younger and male patients are more likely to be sensitive to treatment costs and side effects. © 2005 Wiley-Liss, Inc.