Abstract
OBJECTIVES: This study aims to evaluate individual preferences that influence responsiveness in oral healthcare services through a discrete choice experiment (DCE), and to estimate the marginal willingness to pay (MWTP) associated with each attribute. DESIGN: Six key attributes influencing responsiveness in oral health services were identified and refined through a literature review, pilot testing and expert consultation: clinic cleanliness, dentist specialisation, dentist attitude, clarity of explanation, treatment initiation time and contribution fee. To enable independent (orthogonal) estimation of attribute effects, minimise confounding due to interactions and ensure balanced representation of factor levels, an orthogonal fractional factorial design was employed to construct the DCE questionnaire. Data were collected using paper-based questionnaires, and MWTP estimates were derived from the resulting regression coefficients. SETTING: The DCE was conducted at Hacettepe University's Beytepe Campus in Ankara, Türkiye, between April and May 2024. PARTICIPANTS: 375 administrative staff actively work at Hacettepe University's Beytepe Campus. MAIN OUTCOME MEASURES: A conditional logit model was used to estimate preferences and MWTP for different attribute levels. RESULTS: The attribute with the highest MWTP was the provision of specialised oral health services ($12.26), followed by clinic cleanliness, a concerned dentist, timely treatment initiation, clear explanations provided by the dentist and contribution fee. Upon incorporating interaction terms-namely age, gender, equivalised disposable income, preferred clinic type and alcohol use-significant variations in preferences were observed across subgroups. CONCLUSIONS: Policy responsiveness in oral healthcare requires identifying prioritised non-clinical service attributes. Policymakers must integrate this evidence into resource allocation and service planning. DCEs across diverse populations are essential for adapting service delivery to evolving public priorities and optimising care quality.