title: Who does not get screened? A simple model of the complex relationships in mammogram non-attendance.
abstract: With increasing mammogram rates, identifying attributes of non-attending women entails going beyond differences in demographic groups to reveal complex interactions among personality attributes. In this study, we analyzed survey data from 474 women aged 41 years and older using decision trees. By incorporating personality, religiousness, and age, we were able to correctly classify 42.9 percent of non-attenders compared to 4.4 percent with logistic regression analysis. Our findings suggest that incorporating personality and religiousness attributes may increase non-attender identification. Furthermore, the simple profile generated by decision trees provides a clear map useful for intervention planning.
authors.affiliation: Koç University, Turkey csen@ku.edu.tr.
authors.forename: Celia Kn
authors.initials: CK
authors.lastname: Sen
authors.affiliation: Koç University, Turkey.
authors.forename: G Tarcan
authors.initials: GT
authors.lastname: Kumkale
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000523:psychology; D003663:Decision Trees; D005260:Female; D006801:Humans; D016015:Logistic Models; D008327:Mammography / Q000523:psychology* / Q000706:statistics & numerical data; D008403:Mass Screening / Q000523:psychology*; D008875:Middle Aged; D008960:Models, Psychological; D010349:Patient Compliance / Q000523:psychology*; D010551:Personality; D011581:Psychological Tests; D012067:Religion; D011795:Surveys and Questionnaires; D014481:United States
keywords: cancer; decision trees; mammography; personality; screening