Abigail G. O'Brien , William B. Meese , Jennifer M. Taber , Angela E. Johnson , Bianca M. Hinojosa , Raven Burton , Sheemrun Ranjan , Evelyn D. Rodarte , Charlie Coward , Jennifer L. Howell
{"title":"Why do people avoid health risk information? A qualitative analysis","authors":"Abigail G. O'Brien , William B. Meese , Jennifer M. Taber , Angela E. Johnson , Bianca M. Hinojosa , Raven Burton , Sheemrun Ranjan , Evelyn D. Rodarte , Charlie Coward , Jennifer L. Howell","doi":"10.1016/j.ssmqr.2024.100461","DOIUrl":null,"url":null,"abstract":"<div><p>Despite the potential benefit of receiving personalized health risk information, when given the opportunity to learn their risk, some people avoid that information. An extensive body of research has revealed various reasons for such information avoidance. Most of this existing work has used quantitative methods, with less focus on self-reported reasons for avoiding health risk information. We used a content analysis approach across four datasets (Dataset 1: <em>n</em> = 174, Dataset 2: <em>n</em> = 326, Dataset 3: <em>n</em> = 83, Dataset 4: <em>n</em> = 168), with the goal of identifying a broad range of self-reported reasons for avoidance. In each study, U.S. adults had the opportunity to learn their personalized risk estimate for a health condition through an online risk calculator (Health condition contexts: Dataset 1: heart disease, stroke, diabetes, prediabetes, lung cancer, colon cancer, melanoma skin cancer, breast cancer, or prostate cancer; Datasets 2 and 3: prediabetes; Dataset 4: melanoma skin cancer, stroke, lung cancer, osteoporosis, prediabetes, or diabetes). Participants who avoided their risk were asked to explain their reason(s) for avoidance via an open-ended question. Coding of these responses resulted in four overarching categories of self-reported reasons for information avoidance: information appraisal, self-perceptions of health, low utility, and affective consequences. The reasons identified both support and extend the current understanding of why people avoid health risk information.</p></div>","PeriodicalId":74862,"journal":{"name":"SSM. Qualitative research in health","volume":"6 ","pages":"Article 100461"},"PeriodicalIF":1.8000,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667321524000702/pdfft?md5=d2ec6dd442cb8261b503fa1f5f75436c&pid=1-s2.0-S2667321524000702-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SSM. Qualitative research in health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667321524000702","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Despite the potential benefit of receiving personalized health risk information, when given the opportunity to learn their risk, some people avoid that information. An extensive body of research has revealed various reasons for such information avoidance. Most of this existing work has used quantitative methods, with less focus on self-reported reasons for avoiding health risk information. We used a content analysis approach across four datasets (Dataset 1: n = 174, Dataset 2: n = 326, Dataset 3: n = 83, Dataset 4: n = 168), with the goal of identifying a broad range of self-reported reasons for avoidance. In each study, U.S. adults had the opportunity to learn their personalized risk estimate for a health condition through an online risk calculator (Health condition contexts: Dataset 1: heart disease, stroke, diabetes, prediabetes, lung cancer, colon cancer, melanoma skin cancer, breast cancer, or prostate cancer; Datasets 2 and 3: prediabetes; Dataset 4: melanoma skin cancer, stroke, lung cancer, osteoporosis, prediabetes, or diabetes). Participants who avoided their risk were asked to explain their reason(s) for avoidance via an open-ended question. Coding of these responses resulted in four overarching categories of self-reported reasons for information avoidance: information appraisal, self-perceptions of health, low utility, and affective consequences. The reasons identified both support and extend the current understanding of why people avoid health risk information.