Background Dental care decision-making is a multifaceted process influenced by various factors such as socioeconomic status, cultural beliefs, and access to healthcare resources. The research aims to elucidate the prevalence and determinants of the preference for tooth extraction over root canal treatment (RCT) in rural communities.

Methodology A structured self-administered questionnaire comprising 15 close-ended questions was formulated for the purpose of data collection for this cross-sectional survey and a sample size of 384 was estimated. Following a total enumeration sampling technique, the study was performed on individuals visiting the rural center aged over 18 years and persons who are willing to participate in the study. The data were analyzed using descriptive statistics and subjected to multinomial logistic regression.

Results Among the participants, 33.1% had undergone RCT in the past and 63.5% had undergone extraction in the past with decay being the most common reason for seeking treatment. About 60.2% individuals preferred extraction and only 39.8% individuals preferred RCT wherein age, gender, and area of residence had a significant influence on the decision-making.

Conclusion Majority of the participants in the study preferred extraction over RCT. Understanding the dynamics driving patient preferences in rural health settings is crucial for tailoring effective oral health interventions. The findings of this study have implications for healthcare practitioners, policymakers, and public health initiatives, providing valuable insights to enhance dental care delivery and promote informed decision-making in rural communities.

S.S., D.K., S.B., and S.A.A.G.A. all played significant roles in the conceptualization of the topic, conducting literature searches, collecting data, and writing and finalizing the manuscript. D.K. specifically contributed to the data analysis in addition to these tasks.

Article published online:
21 October 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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