Applying “Stages of Readiness to Change” Model to Dentists’ Decisions to Participate in Medicaid: An Exploratory Study

BACKGROUND: The Stages of Readiness to Change (SOC) behavioral model describes behavior change as a process and distinguishes individuals based on their current behavior and readiness to change that behavior. SOC can be used to improve dentists’ participation in a state public dental benefit program (Medicaid) by targeting them at different SOC with interventions, strategies, and tools tailored to those stages. Therefore, this study assessed the usefulness of using SOC to describe dentists’ attitudes towards and participation in Medicaid. Dentists’ participation in Medicaid is of interest to policymakers, and this study demonstrates a method to identify potential opportunities for intervention. METHODS: A modified SOC algorithm used data from a periodic survey of Iowa Dentists to categorize dentists (N=514) into: 1) pre-contemplation, 2) considering participation (SOC contemplation and preparation), 3) acting (SOC action and maintenance), and 4) risk of relapse (at risk for discontinuing participation). The four SOC stages were compared using ANOVA and post hoc Tukey’s test among: practice characteristics, Dentists Altruism scale, Attitude about Program Administration scale, Attitude about Medicaid patients scale and Perception of Importance of Medicaid Problems scale. RESULTS: Among survey respondents, 36% were categorized as pre-contemplation, 6% were considering Medicaid participation, 12% were acting as Medicaid providers with minimal risk of relapse, and 46% were participating and at risk of discontinuing. Dentists’ attitudes towards program administration, Medicaid patients, and access to care varied across the SOC cycle. CONCLUSION: Nearly, 46% dentists in this analysis were identified as at risk of discontinuing participation – a much larger proportion than dentists considering Medicaid participation. Categorizing dentists using this approach has important implications for programmatic interventions. For example, policymakers targeting our study population could focus their efforts on reducing the likelihood of dentists dropping out of the program, with less emphasis targeting dentists in the precontemplation stage.