Abstract
Depression threatens people's lives and imposes huge economic burden. Antidepressant therapy is the first-line treatment for depression, and patient adherence to medication is the key to successful treatment. Depression patients have poor medication adherence, which leads to failure of depression management and significantly poorer clinical outcomes. Incorporating patient preferences into clinical decisions can improve uptake rates, optimize treatment adherence. A discrete choice experiment (DCE) can elicit and quantify individual preferences. Previous DCE studies were conducted in developed countries and ignored the influences of factors other than the medication. This paper outlines an ongoing DCE that aims to (1) explore medication-management-related characteristics that may affect depression patients' adherence to antidepressant, (2) elicit how depression patients consider the trade-offs among different medication managements. The six attributes and their levels were developed through a literature review, semi-structured interviews and experts and focus group discussions. A fractional factorial design in the software Ngene 1.2 version was used to generate 36 choice sets, and they were divided into 3 blocks. A mixed logit model will be used to explore the patients' preferences, willingness to pay and uptake rate of depression patients for medication management attributes. The final questionnaire consists of three parts. The first is the introduction, which introduces the purpose of the study and the requirements of completing the questionnaire. This was followed by a general information questionnaire, which included sociodemographic characteristics. The last part is DCE tasks, which include 13 DCE choice sets, and each choice set include two alternative and one "opt-out" option. The pilot-test results showed the questionnaire was easy to understand and could be used in formal surveys. Our study shows how the development process of the study can be conducted and reported systematically and rigorously according to the theoretical foundation and design principles in DCE.
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