Identifying Sociodemographic Disparities in Negative Cancer Beliefs and Health-Information-Seeking Attitudes Among Oregonians

Abstract

BackgroundBeliefs and perceptions about cancer risks and accessibility of health information play an important role in influencing cancer screening behaviors and various health outcomes. However, these beliefs and attitudes are not well understood, especially across different racial and socioeconomic groups. The aim of this study was to identify sociodemographic factors associated with cancer risk perceptions and health-information-seeking attitudes among adults.MethodsThis study utilized data from the Understanding Cancer in Oregon (UCanOR) project, which administered a 47-item cross-sectional survey to capture sociodemographic and behavioral information. Participants were recruited through area-based random sampling and public convenience sampling across Oregon. Multivariable generalized linear and logistic regression analyses were used to evaluate attitudes towards cancer risk and accessing health information.ResultsThe study included a total of 1357 respondents [mean age of 50.0 (SD = 17.8)], primarily Non-Hispanic White (87.3%), followed by Asians/Pacific Islanders (8.4%), Hispanic White (3.5%), and Black (0.8%). Compared to Non-Hispanic Whites, Asians/Pacific Islanders were 2.5 times more likely to believe cancer is caused by behavior or lifestyle, 2.8 times more likely to agree that there is little one can do to prevent cancer, and 1.6 times more likely to associate cancer with death.ConclusionAsians/Pacific Islanders were more likely to agree with statements expressing frustration and distrust towards cancer beliefs and health information searches. Future community outreach efforts should consider tailoring the message to their target audiences. Understanding and addressing the underlying reasons for these negative perceptions is crucial for developing effective education and health promotion strategies.

Keywords: Oregon; cancer beliefs; cancer fatalism; health behaviors; health information search; survey.

Figure 1.

Analytic Sample Size Flow Chart