title: How can we reach them? Information seeking and preferences for a cancer family history campaign in underserved communities.
abstract: Individuals with a family history of cancer are at elevated risk for the disease, and web-based tools are available to assist in assessing risk. Preferences for a potential campaign to promote awareness of the role of family history in cancer risk were sought, guided by McGuire's Input-Output Persuasion Model. A randomized telephone survey administered to five underserved communities assessed potential campaign messages, channels, sources, receivers, and destinations and use of the Internet (n = 101). Information sources sought about hereditary cancer and their predictors were assessed. Nearly half of the sample was African American and had annual income below $25,000. Most (59%) had Internet access at home. Few differences emerged as a function of race (African American vs. Other). The Internet was the most common (43%) first source sought for hereditary cancer information, followed by physicians (23%). In univariate multinomial logistic regression models, those with a high school education or more and those with greater family history (trend) were more likely than those without to choose the Internet as their first source of information over physicians. Our survey provided a wealth of information for understanding how to best launch our family history cancer risk communication campaign. Education level affected information seeking, and efforts are under way to lessen this potential barrier.
authors.affiliation: Human Cancer Genetics, The Ohio State University, Columbus, Ohio, USA. kimberly.kelly@osumc.edu
authors.forename: Kimberly M
authors.initials: KM
authors.lastname: Kelly
authors.forename: Amy C
authors.initials: AC
authors.lastname: Sturm
authors.forename: Kathleen
authors.initials: K
authors.lastname: Kemp
authors.forename: Jacquelin
authors.initials: J
authors.lastname: Holland
authors.forename: Amy K
authors.initials: AK
authors.lastname: Ferketich
mesh_terms: D022126:Access to Information; D000293:Adolescent; D000328:Adult; D000368:Aged; D003625:Data Collection; D005260:Female; D006266:Health Education / Q000706:statistics & numerical data*; D006801:Humans; D057226:Information Seeking Behavior; D020407:Internet; D016015:Logistic Models; D008297:Male; D008487:Medical History Taking / Q000706:statistics & numerical data*; D008507:Medically Underserved Area; D008875:Middle Aged; D008962:Models, Theoretical; D015999:Multivariate Analysis; D009369:Neoplasms / Q000175:diagnosis*; D016017:Odds Ratio; D009820:Ohio; D017060:Patient Satisfaction / Q000706:statistics & numerical data*; D018570:Risk Assessment; D012307:Risk Factors; D012959:Socioeconomic Factors; D055815:Young Adult