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Open Access Classification Tree Analysis of Factors Associated with Oral Cancer Exam

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This article is Open Access under the terms of the Creative Commons CC BY-NC-ND licence.

Objective: In this study, we performed a classification tree analysis (CTA) to identify population subgroups that are less likely to have an oral cancer examination (OCE). Methods: We conducted telephone surveys (N = 2401) of adults residing in north Florida to collect data on OCE status and potential OCE predictors including demographics, medical and dental experience, and psychosocial factors. The CTA algorithm exhaustive chi-square automatic interaction detector (E- CHAID) was employed to determine the relationships between OCE status and the predictors. Results: The overall OCE rate was 46.8% in our sample. Participants' rating of the dentist was the first level splitting variable, leading to 15 unique participant subgroups: (1) high dentist rating (N = 1269) led to 5 splits and 11 subgroups; (2) low dentist rating (N = 308) led to zero splits; and (3) no regular dentist (N = 824) led to 2 splits and 3 subgroups. Conclusions: The CTA has identified unique population subgroups that could be targeted in future tailored public health interventions. Among underserved populations, it is important to develop and implement community-based interventions that encourage regular dental visits and provide oral cancer self- examination education..

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Document Type: Research Article

Publication date: May 1, 2019

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  • The American Journal of Health Behavior seeks to improve the quality of life through multidisciplinary health efforts in fostering a better understanding of the multidimensional nature of both individuals and social systems as they relate to health behaviors.

    The Journal aims to provide a comprehensive understanding of the impact of personal attributes, personality characteristics, behavior patterns, social structure, and processes on health maintenance, health restoration, and health improvement; to disseminate knowledge of holistic, multidisciplinary approaches to designing and implementing effective health programs; and to showcase health behavior analysis skills that have been proven to affect health improvement and recovery.

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