High Public Trust in Scientists for Cancer Information Across Political Ideologies in the U.S

High Public Trust in Scientists for Cancer Information Across Political Ideologies in the U.S | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report High Public Trust in Scientists for Cancer Information Across Political Ideologies in the U.S Christopher W. Wheldon, Meghnaa Tallapragada, Erika L. Thompson This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6656977/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Dec, 2025 Read the published version in JAMA Network Open → Version 1 posted You are reading this latest preprint version Abstract Purpose: To examine whether political ideology is associated with trust in scientists as sources of cancer information in a nationally representative sample of U.S. adults. Methods: We conducted a secondary analysis of the 2024 Health Information National Trends Survey (HINTS). The analytic sample included 6,260 non-institutionalized adults aged ≥18 years (response rate: 27.3%). Political ideology was measured on a 7-point scale ranging from “very liberal” to “very conservative.” Trust in scientists for cancer information was measured on a 4-point scale and dichotomized as high (some or a lot) vs low (not at all or a little). Survey-weighted logistic regression models were used to assess the association, controlling for demographic factors and trust in physicians. Results: Overall, 86.9% of respondents (95% CI, 84.4–87.5) reported high trust in scientists for cancer information. In multivariable models, each one-point shift toward greater conservatism on the political ideology scale was associated with a 25% decrease in the odds of high trust (adjusted odds ratio [aOR], 0.75; 95% CI, 0.68–0.84). Adjusted predicted probabilities ranged from 93.7% among very liberal respondents to 70.5% among those identifying as very conservative. Conclusions: Despite a politically polarized climate, trust in scientists as cancer information sources remains high across the U.S. adult population. However, the presence of an ideological gradient suggests the need for communication strategies that engage politically diverse audiences to ensure broad reach and effectiveness of cancer prevention and control messaging. Political ideology public trust cancer communication health information scientists health communication Figures Figure 1 Background Public trust in scientific authorities is a foundational element of effective public health communication, especially in areas like cancer prevention, screening, and treatment. Scientists are among the most trusted sources of information [1], yet recent data suggest that trust in scientists may be increasingly shaped by political ideology [2]. In the United States, political polarization has widened across numerous domains of public life. Surveys show that conservative-leaning individuals tend to express more skepticism toward vaccinations and other health interventions, as was prominent during the COVID-19 pandemic [3]. Moreover, the COVID-19 pandemic instigated angst and anger against scientists and public health officials [4]. This ideological gap has significant implications for cancer communication, particularly when scientific recommendations are perceived as politically charged or when trust in the messenger is as influential as the message itself. While skepticism is a critical component of the scientific process, trust in the available science and government based on the public is critical for adoption of cancer-related public health interventions. The present study s uses nationally representative data from the Health Information National Trends Survey (HINTS) to estimate public trust in scientists as sources of cancer information and examine its association with political ideology. The following hypothesis was tested: Individuals with more conservative political ideologies will report significantly lower levels of trust in scientists as sources of cancer information compared to individuals with more liberal political ideologies. Findings from this study can inform future cancer information communication strategies that are tailored to different segments of the United States’ population. Methods Data were from the National Cancer Institute, Health Information National Trends Survey (HINTS) collected in 2024 (N = 7,278; 27.3% response rate). Details on the survey methodology can be found elsewhere [5]. This study was determined to be exempt from human subjects research by Temple University Institutional Review Board. The primary dependent variable was trust in scientists for cancer information and the primary independent variable was political viewpoint. Respondents were asked “In general, how much would you trust information about cancer from scientists,” which they responded on a 4-point unipolar scale from Not at all to A lot . Trust was operationalized as “High” ( Some / A lot responses) and “Low” ( Not at all / A little responses) as was done in previous research [6]. They were also asked one question about their political ideology: “Thinking about politics these days, how would you describe your own political viewpoint?” Responses were recorded on a 7-point bipolar scale from Very Liberal (1) to Very Conservative (7) with a Moderate mid-point. Several control variables were considered including sociodemographics (age, birth sex, marital status, educational attainment, race/ethnicity), previous cancer diagnosis (self and biological relatives), and trust in cancer information from “a doctor” (i.e., Not at all/A little vs. A lot/Some). Data were analyzed with SAS 9.4 using survey-weighting procedures to adjust point estimates and standard errors for household nonresponse and non-coverage bias. The final analytic dataset (N = 6,260) was created by removing missing cases on the trust (n = 208) and political ideology variables (n = 810). Bivariate and multivariable logistic regression models were used to regress a binary trust outcome (i.e., high trust vs. low trust) on political ideology. Control variables were added to the multivariable model if they exhibited a bivariate association with trust and political ideology (e.g., age, marital status, education, race, cancer diagnosis in biological relative, and trust in government cancer information). Hot-deck imputation was used to replace missing responses for the following variables: age, birth sex, marital status, educational attainment, and Hispanic ethnicity. All results are weighted and adjusted to represent the non-institutionalized adult U.S. population. Sensitivity analyses were conducted to examine the impact of different coding schemes for political ideology on trust. These included a non-linear specification using a squared term, a 3-category version (left of center, moderate, right of center), and an expanded version modeling skipped or refused responses as a separate category. We also tested for potential non-random missingness based on item skip patterns. None of these alternate specifications substantively altered the direction or significance of the main findings. Results Sample characteristics are reported in Table 1. Most respondents rated high trust in cancer information from scientists (86.9%; 95% CI: 84.4-87.5); however, there was a significant inverse association between conservative political ideology and trust. In the bivariate model, higher scores on political ideology (i.e., indicating greater political conservatism) was associated with a 27% decline in the odds of high trust in scientists for cancer information (OR = 0.73; 95% CI: 0.66-0.81). This estimate remained largely unchanged after adjusting for control variables, including age, educational attainment, family member with history of cancer, and trust in doctors for cancer information (aOR = 0.75; 95% CI: 0.68-0.84). In the multivariate model, older age was associated with lower trust; college education and trust in cancer information from doctors were associated with higher trust. Adjusted predicted probabilities of high trust in scientists for cancer information decreased across the political spectrum (Figure 1), from 93.7% among liberals to 70.5% among very conservative respondents. Discussion Trust in scientists as sources of cancer information was generally high among U.S. adults, with more than 86% reporting “some” or “a lot” of trust. While political ideology was a significant predictor of trust—showing a clear gradient from higher trust among liberals to lower trust among conservatives—trust levels remained relatively strong across the ideological spectrum. Even among those identifying as very conservative, over 70% expressed high trust in scientists for cancer information. These findings underscore important implications for science communication. First, scientists have an important role in public health communication regarding cancer risk, prevention, screening recommendations, and treatment advances. Second, there is a need to identify trusted messengers who can connect with ideologically diverse audiences on these issues in a manner that communicates the key cancer messaging for prevention or treatment. Third, this work serves as a call to action for the scientific community to prioritize science and health literacy in public health communication. Notably, National Cancer Institute–designated Cancer Centers have a particular responsibility to engage their catchment area communities in these efforts, as part of their mandate to reduce the burden of cancer through outreach, education, and equitable access to evidence-based prevention and care strategies [7]. Strengthening public trust can enhance the reach and impact of cancer communication efforts. There are important limitations from this study to consider. The overall response rate was low, which increases potential for nonresponse bias, though analytic weights were applied to minimize this impact. In addition, trust and political ideology were assessed using single-item measures, which may not capture the full complexity or multidimensionality of these constructs. Lastly, this was a cross-sectional study. Additional research is needed to examine trends in these associations over time. Nevertheless, these findings offer encouraging news. Despite being collected during a time of heightened political polarization in 2024, the data show that scientists remain broadly trusted figures in cancer communication. This resilience in public trust provides a valuable foundation for continued efforts to promote science-based information and reduce the burden of cancer across all communities. References Krause NM, Brossard D, Scheufele DA, et al (2019) Americans’ Trust in Science and Scientists. Public Opinion Quarterly 83:817–836. https://doi.org/10.1093/poq/nfz041 Kennedy AT and B (2024) Public Trust in Scientists and Views on Their Role in Policymaking. In: Pew Research Center. https://www.pewresearch.org/science/2024/11/14/public-trust-in-scientists-and-views-on-their-role-in-policymaking/. Accessed 23 Apr 2025 Fridman A, Gershon R, Gneezy A (2021) COVID-19 and vaccine hesitancy: A longitudinal study. PLoS ONE 16:e0250123. https://doi.org/10.1371/journal.pone.0250123 Mello MM, Greene JA, Sharfstein JM (2020) Attacks on Public Health Officials During COVID-19. JAMA 324:741. https://doi.org/10.1001/jama.2020.14423 Methodology Reports | HINTS. https://hints.cancer.gov/data/methodology-reports.aspx. Accessed 23 Apr 2025 Hesse BW, Nelson DE, Kreps GL, et al (2005) Trust and sources of health information: the impact of the Internet and its implications for health care providers: findings from the first Health Information National Trends Survey. Arch Intern Med 165:2618–2624. https://doi.org/10.1001/archinte.165.22.2618 Pohl SA, Nelson BA, Patwary TR, et al (2024) Evolution of community outreach and engagement at National Cancer Institute‐Designated Cancer Centers, an evolving journey. CA A Cancer J Clinicians 74:383–396. https://doi.org/10.3322/caac.21841 Tables Table 1. Analysis of trust in scientists as sources of cancer information (Health Information National Trends Survey 7, N = 6,260) Variable Total Sample Low Trust High Trust Bivariate Models Multivariable Model a % (95% CI) % (95% CI) % (95% CI) OR (95% CI) aOR (95% CI) Total 14.0 (12.5-15.6) 86.0 (84.4-87.5) Political ideology, M (95% CI) b 4.0 (4.0-4.1) 4.7 (4.5-4.9) 3.9 (3.8-4.0) 0.73 (0.66-0.81) 0.75 (0.68-0.83) Age, M (95% CI) 48.4 (47.9-48.9) 52.2 (49.7-54.6) 47.8 (47.2-48.4) 0.99 (0.98-1.00) 0.98 (0.98-0.99) Sex Female 47.9 (47.1-48.8) 14.1 (12.2-16.0) 85.9 (84.0-87.8) 1.00 Male 52.1 (51.2-52.9) 14.0 (11.8-16.2) 86.0 (83.8-88.2) 1.01 (0.80-1.28) Marital Status Not married 43.2 (42.2-44.6) 14.5 (11.5-17.4) 85.5 (82.6-88.5) 1.00 Married or partnered 56.6 (55.4-57.8) 13.7 (11.8-15.6) 86.3 (84.4-88.2) 1.07 (0.78-1.45) Education High school or less 26.2 (24.7-27.7) 19.0 (15.6-22.3) 81.0 (77.7-84) 1.00 1.00 Some college 38.7 (37.1-40.2) 16.3 (13.1-19.5) 83.7 (80.5-86.9) 1.21 (0.87-1.68) 1.24 (0.88-1.76) College graduate 20.7 (19.4-22.0) 9.5 (7.2-11.8) 90.5 (88.2-92.8) 2.23 (1.54-3.23) 1.86 (1.28-2.72) Postgraduate 14.4 (13.3-15.5) 5.5 (3.8-7.2) 94.5 (92.8-96.2) 4.02 (2.74-5.90) 2.89 (1.86-4.48) Hispanic Ethnicity Non-Hispanic 83.2 (82.6-83.7) 14.1 (12.5-15.7) 85.9 (84.3-87.5) 1.00 Hispanic 16.8 (16.3-17.4) 13.7 (9.8-17.6) 86.3 (82.4-90.2) 1.03 (0.73-1.47) Race White 73.0 (71.9-74.1) 13.2 (11.5-14.9) 86.8 (85.1-88.5) 1.00 Black 11.5 (11.0-12.1) 18.2 (13.0-23.4) 81.8 (76.6-87.0) 0.69 (0.47-1.00) American Indian 1.1 (0.6-1.5) 6.9 (0.5-13.2) 93.1 (86.8-99.5) 2.06 (0.73-5.85) East Asian 2.2 (1.5-2.9) 11.8 (1.9-21.7) 88.2 (78.3-98.1) 1.14 (0.40-3.28) Southeast Asian 0.70 (0.34- 1.06) 19.8 (0-45.8) 80.2 (54.22-100.0) 0.62 (0.08-5.05) Multiracial/Other 11.4 (10.1-12.7) 15.8 (11.5-20.1) 84.2 (79.9-88.5) 0.81 (0.58-1.14) Cancer History No personal history 90.4 (90.1-90.8) 13.4 (11.8-15.0) 86.6 (85.0-88.2) 1.00 Personal history 9.6 (9.2-9.9) 19.9 (14.6-25.3) 80.1 (74.7-85.4) 0.62 (0.43-0.90) Family Cancer History No family history 34.2 (32.6-35.8) 16.7 (13.3-20.0) 83.3 (80.0-86.7) 1.00 1.00 Family history 64.2 (62.4-65.9) 12.6 (11.0-14.2) 87.4 (85.8-89.0) 1.39 (1.04-1.87) 1.19 (0.85-1.66) Missing 1.6 (1.1-2.2) 15.5 (6.8-24.1) 84.5 (75.9-93.2) 1.10 (0.53-2.27) 1.51 (0.62-3.68) Trust in doctors for cancer information Low Trust 5.8 (4.6-6.9) 67.2 (59.2-75.1) 32.8 (24.9-40.8) 1.00 1.00 High Trust 94.2 (93.1-95.4) 10.8 (9.6-11.9) 89.2 (88.1-90.4) 16.95 (11.86-24.21) a 17.14 (10.88-27.00) Note. Bold Odds ratios (OR) indicate statistically significant associations, p<0.05; The final model was adjusted for age, educational attainment, and cancer diagnosis in biological relative, which all exhibited bivariate correlations with trust and political ideology. a Analytic sample, N = 6,236 b Range 0-7 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Dec, 2025 Read the published version in JAMA Network Open → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6656977","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":462597620,"identity":"94173f0f-0695-4f4c-aeba-131f2605d475","order_by":0,"name":"Christopher W. Wheldon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIiWNgGAWjYBAC/hkMDAeAdAIDO4MBA0MFSIy5AUTg1CJxA6aFGaTlDBAzMOLXYhABoSFaGNuI0SLd+/DgD4bDefzMzBsfF877I6c7u7HxAUOFdWIDLi0yxw0O8zAcLpZsZis2nrnNwNjszsFmA4Yz6bi1SKQxHGZguJ244TCPmTTvNoPEbTcS2yQY2w7j1QJ02O3E/WAtcwzqgVrafzD+w6MlIo3hAA/IFmaQlgaDBDOgLcAQwK1F4gbQYTwG/xNnHAb6heeYseE2oF8kEo6lG+PSwj8jjfnjj4q0xP725o2PeWrk5M1uNx/88KHGWhaXFqjzUCxmAEUTSUCCNOWjYBSMglEw/AEAzFdb6W5tZssAAAAASUVORK5CYII=","orcid":"","institution":"Temple University","correspondingAuthor":true,"prefix":"","firstName":"Christopher","middleName":"W.","lastName":"Wheldon","suffix":""},{"id":462597621,"identity":"cae0a575-414c-4c7c-b447-9cc07cb98ebd","order_by":1,"name":"Meghnaa Tallapragada","email":"","orcid":"","institution":"Temple University","correspondingAuthor":false,"prefix":"","firstName":"Meghnaa","middleName":"","lastName":"Tallapragada","suffix":""},{"id":462597622,"identity":"f710b780-f26f-4ccc-9482-d19f787718a6","order_by":2,"name":"Erika L. Thompson","email":"","orcid":"","institution":"The University of Texas Health Science Center at San Antonio","correspondingAuthor":false,"prefix":"","firstName":"Erika","middleName":"L.","lastName":"Thompson","suffix":""}],"badges":[],"createdAt":"2025-05-13 15:23:22","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6656977/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6656977/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1001/jamanetworkopen.2025.46818","type":"published","date":"2025-12-04T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83639504,"identity":"09067d00-8fc6-4086-b393-e0a0419ea5a7","added_by":"auto","created_at":"2025-05-30 02:52:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":57860,"visible":true,"origin":"","legend":"\u003cp\u003eAverage predicted probability of high trust in cancer information from scientists across political ideologies.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6656977/v1/53e9f59a77b0caa371c8ef57.png"},{"id":97829981,"identity":"248ae78d-c089-4592-b16f-faed2f175f79","added_by":"auto","created_at":"2025-12-09 23:00:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":710933,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6656977/v1/89a222f6-733c-4814-afdc-5a926a17ba74.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"High Public Trust in Scientists for Cancer Information Across Political Ideologies in the U.S","fulltext":[{"header":"Background","content":"\u003cp\u003ePublic trust in scientific authorities is a foundational element of effective public health communication, especially in areas like cancer prevention, screening, and treatment. Scientists are among the most trusted sources of information [1], yet recent data suggest that trust in scientists may be increasingly shaped by political ideology [2].\u003c/p\u003e\n\u003cp\u003eIn the United States, political polarization has widened across numerous domains of public life. Surveys show that conservative-leaning individuals tend to express more skepticism toward vaccinations and other health interventions, as was prominent during the COVID-19 pandemic [3]. Moreover, the COVID-19 pandemic instigated angst and anger against scientists and public health officials [4]. This ideological gap has significant implications for cancer communication, particularly when scientific recommendations are perceived as politically charged or when trust in the messenger is as influential as the message itself. While skepticism is a critical component of the scientific process, trust in the available science and government based on the public is critical for adoption of cancer-related public health interventions.\u003c/p\u003e\n\u003cp\u003eThe present study s uses nationally representative data from the Health Information National Trends Survey (HINTS) to estimate public trust in scientists as sources of cancer information and examine its association with political ideology. The following hypothesis was tested: Individuals with more conservative political ideologies will report significantly lower levels of trust in scientists as sources of cancer information compared to individuals with more liberal political ideologies. Findings from this study can inform future cancer information communication strategies that are tailored to different segments of the United States\u0026rsquo; population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eData were from the National Cancer Institute, Health Information National Trends Survey (HINTS) collected in 2024 (N = 7,278; 27.3% response rate). Details on the survey methodology can be found elsewhere [5]. This study was determined to be exempt from human subjects research by Temple University Institutional Review Board.\u003c/p\u003e\n\u003cp\u003eThe primary dependent variable was trust in scientists for cancer information and the primary independent variable was political viewpoint. Respondents were asked \u0026ldquo;In general, how much would you trust information about cancer from scientists,\u0026rdquo; which they responded on a 4-point unipolar scale from \u003cem\u003eNot at all\u003c/em\u003e to \u003cem\u003eA lot\u003c/em\u003e. \u0026nbsp;Trust was operationalized as \u0026ldquo;High\u0026rdquo; (\u003cem\u003eSome\u003c/em\u003e/\u003cem\u003eA lot responses)\u003c/em\u003e and \u0026ldquo;Low\u0026rdquo; (\u003cem\u003eNot at all\u003c/em\u003e/\u003cem\u003eA little responses)\u003c/em\u003e as was done in previous research [6]. They were also asked one question about their political ideology: \u0026ldquo;Thinking about politics these days, how would you describe your own political viewpoint?\u0026rdquo; Responses were recorded on a 7-point bipolar scale from \u003cem\u003eVery Liberal (1)\u0026nbsp;\u003c/em\u003eto \u003cem\u003eVery Conservative (7)\u0026nbsp;\u003c/em\u003ewith a \u003cem\u003eModerate\u003c/em\u003e mid-point. Several control variables were considered including sociodemographics (age, birth sex, marital status, educational attainment, race/ethnicity), previous cancer diagnosis (self and biological relatives), and trust in cancer information from \u0026ldquo;a doctor\u0026rdquo; (i.e., Not at all/A little vs. A lot/Some).\u003c/p\u003e\n\u003cp\u003eData were analyzed with SAS 9.4 using survey-weighting procedures to adjust point estimates and standard errors for household nonresponse and non-coverage bias. The final analytic dataset (N = 6,260) was created by removing missing cases on the trust (n = 208) and political ideology variables (n = 810). Bivariate and multivariable logistic regression models were used to regress a binary trust outcome (i.e., high trust vs. low trust) on political ideology.\u003c/p\u003e\n\u003cp\u003eControl variables were added to the multivariable model if they exhibited a bivariate association with trust and political ideology (e.g., age, marital status, education, race, cancer diagnosis in biological relative, and trust in government cancer information). Hot-deck imputation was used to replace missing responses for the following variables: age, birth sex, marital status, educational attainment, and Hispanic ethnicity. All results are weighted and adjusted to represent the non-institutionalized adult U.S. population.\u003c/p\u003e\n\u003cp\u003eSensitivity analyses were conducted to examine the impact of different coding schemes for political ideology on trust. These included a non-linear specification using a squared term, a 3-category version (left of center, moderate, right of center), and an expanded version modeling skipped or refused responses as a separate category. We also tested for potential non-random missingness based on item skip patterns. None of these alternate specifications substantively altered the direction or significance of the main findings.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eSample characteristics are reported in Table 1. Most respondents rated high trust in cancer information from scientists (86.9%; 95% CI: 84.4-87.5); however, there was a significant inverse association between conservative political ideology and trust. In the bivariate model, higher scores on political ideology (i.e., indicating greater political conservatism) was associated with a 27% decline in the odds of high trust in scientists for cancer information (OR = 0.73; 95% CI: 0.66-0.81). This estimate remained largely unchanged after adjusting for control variables, including age, educational attainment, family member with history of cancer, and trust in doctors for cancer information (aOR = 0.75; 95% CI: 0.68-0.84). In the multivariate model, older age was associated with lower trust; college education and trust in cancer information from doctors were associated with higher trust.\u003c/p\u003e\n\u003cp\u003eAdjusted predicted probabilities of high trust in scientists for cancer information decreased across the political spectrum (Figure 1), from 93.7% among liberals to 70.5% among very conservative respondents.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTrust in scientists as sources of cancer information was generally high among U.S. adults, with more than 86% reporting \u0026ldquo;some\u0026rdquo; or \u0026ldquo;a lot\u0026rdquo; of trust. While political ideology was a significant predictor of trust\u0026mdash;showing a clear gradient from higher trust among liberals to lower trust among conservatives\u0026mdash;trust levels remained relatively strong across the ideological spectrum. Even among those identifying as very conservative, over 70% expressed high trust in scientists for cancer information.\u003c/p\u003e\n\u003cp\u003eThese findings underscore important implications for science communication. First, scientists have an important role in public health communication regarding cancer risk, prevention, screening recommendations, and treatment advances. Second, there is a need to identify trusted messengers who can connect with ideologically diverse audiences on these issues in a manner that communicates the key cancer messaging for prevention or treatment. Third, this work serves as a call to action for the scientific community to prioritize science and health literacy in public health communication. Notably, National Cancer Institute\u0026ndash;designated Cancer Centers have a particular responsibility to engage their catchment area communities in these efforts, as part of their mandate to reduce the burden of cancer through outreach, education, and equitable access to evidence-based prevention and care strategies [7]. Strengthening public trust can enhance the reach and impact of cancer communication efforts.\u003c/p\u003e\n\u003cp\u003eThere are important limitations from this study to consider. \u0026nbsp;The overall response rate was low, which increases potential for nonresponse bias, though analytic weights were applied to minimize this impact. In addition, trust and political ideology were assessed using single-item measures, which may not capture the full complexity or multidimensionality of these constructs. Lastly, this was a cross-sectional study. Additional research is needed to examine trends in these associations over time.\u003c/p\u003e\n\u003cp\u003eNevertheless, these findings offer encouraging news. Despite being collected during a time of heightened political polarization in 2024, the data show that scientists remain broadly trusted figures in cancer communication. This resilience in public trust provides a valuable foundation for continued efforts to promote science-based information and reduce the burden of cancer across all communities.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKrause NM, Brossard D, Scheufele DA, et al (2019) Americans\u0026rsquo; Trust in Science and Scientists. Public Opinion Quarterly 83:817\u0026ndash;836. https://doi.org/10.1093/poq/nfz041\u003c/li\u003e\n\u003cli\u003eKennedy AT and B (2024) Public Trust in Scientists and Views on Their Role in Policymaking. In: Pew Research Center. https://www.pewresearch.org/science/2024/11/14/public-trust-in-scientists-and-views-on-their-role-in-policymaking/. Accessed 23 Apr 2025\u003c/li\u003e\n\u003cli\u003eFridman A, Gershon R, Gneezy A (2021) COVID-19 and vaccine hesitancy: A longitudinal study. PLoS ONE 16:e0250123. https://doi.org/10.1371/journal.pone.0250123\u003c/li\u003e\n\u003cli\u003eMello MM, Greene JA, Sharfstein JM (2020) Attacks on Public Health Officials During COVID-19. JAMA 324:741. https://doi.org/10.1001/jama.2020.14423\u003c/li\u003e\n\u003cli\u003eMethodology Reports | HINTS. https://hints.cancer.gov/data/methodology-reports.aspx. Accessed 23 Apr 2025\u003c/li\u003e\n\u003cli\u003eHesse BW, Nelson DE, Kreps GL, et al (2005) Trust and sources of health information: the impact of the Internet and its implications for health care providers: findings from the first Health Information National Trends Survey. Arch Intern Med 165:2618\u0026ndash;2624. https://doi.org/10.1001/archinte.165.22.2618\u003c/li\u003e\n\u003cli\u003ePohl SA, Nelson BA, Patwary TR, et al (2024) Evolution of community outreach and engagement at National Cancer Institute‐Designated Cancer Centers, an evolving journey. CA A Cancer J Clinicians 74:383\u0026ndash;396. https://doi.org/10.3322/caac.21841\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Analysis of trust in scientists as sources of cancer information (Health Information National Trends Survey 7, N = 6,260)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Sample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow Trust\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh Trust\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBivariate Models\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable Model\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e14.0 (12.5-15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e86.0 (84.4-87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePolitical ideology, M (95% CI)\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e4.0 (4.0-4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e4.7 (4.5-4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e3.9 (3.8-4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.73 (0.66-0.81)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.75 (0.68-0.83)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, M (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e48.4 (47.9-48.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e52.2 (49.7-54.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e47.8 (47.2-48.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.99 (0.98-1.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.98 (0.98-0.99)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Female\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e47.9 (47.1-48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e14.1 (12.2-16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e85.9 (84.0-87.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e52.1 (51.2-52.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e14.0 (11.8-16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e86.0 (83.8-88.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.01 (0.80-1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Not married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e43.2 (42.2-44.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e14.5 (11.5-17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e85.5 (82.6-88.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Married or partnered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e56.6 (55.4-57.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e13.7 (11.8-15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e86.3 (84.4-88.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.07 (0.78-1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;High school or less\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e26.2 (24.7-27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e19.0 (15.6-22.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e81.0 (77.7-84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Some college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e38.7 (37.1-40.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e16.3 (13.1-19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e83.7 (80.5-86.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.21 (0.87-1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.24 (0.88-1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;College graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e20.7 (19.4-22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e9.5 (7.2-11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e90.5 (88.2-92.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.23 (1.54-3.23)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.86 (1.28-2.72)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Postgraduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e14.4 (13.3-15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e5.5 (3.8-7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e94.5 (92.8-96.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.02 (2.74-5.90)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.89 (1.86-4.48)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHispanic Ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Non-Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e83.2 (82.6-83.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e14.1 (12.5-15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e85.9 (84.3-87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e16.8 (16.3-17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e13.7 (9.8-17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e86.3 (82.4-90.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.03 (0.73-1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e73.0 (71.9-74.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e13.2 (11.5-14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e86.8 (85.1-88.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e11.5 (11.0-12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e18.2 (13.0-23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e81.8 (76.6-87.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e0.69 (0.47-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;American Indian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e1.1 (0.6-1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e6.9 (0.5-13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e93.1 (86.8-99.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e2.06 (0.73-5.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;East Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e2.2 (1.5-2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e11.8 (1.9-21.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e88.2 (78.3-98.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.14 (0.40-3.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Southeast Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e0.70 (0.34- 1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e19.8 (0-45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e80.2 (54.22-100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e0.62 (0.08-5.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Multiracial/Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e11.4 (10.1-12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e15.8 (11.5-20.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e84.2 (79.9-88.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e0.81 (0.58-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer History\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;No personal history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e90.4 (90.1-90.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e13.4 (11.8-15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e86.6 (85.0-88.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Personal history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e9.6 (9.2-9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e19.9 (14.6-25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e80.1 (74.7-85.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.62 (0.43-0.90)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily Cancer History\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;No family history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e34.2 (32.6-35.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e16.7 (13.3-20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e83.3 (80.0-86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026emsp;Family history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e64.2 (62.4-65.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e12.6 (11.0-14.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e87.4 (85.8-89.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.39 (1.04-1.87)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.19 (0.85-1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Missing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e1.6 (1.1-2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e15.5 (6.8-24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e84.5 (75.9-93.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.10 (0.53-2.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.51 (0.62-3.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrust in doctors for cancer information\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003eLow Trust\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e5.8 (4.6-6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e67.2 (59.2-75.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e32.8 (24.9-40.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24.3056%;\"\u003e\n \u003cp\u003eHigh Trust\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e94.2 (93.1-95.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e10.8 (9.6-11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5833%;\"\u003e\n \u003cp\u003e89.2 (88.1-90.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2778%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16.95 (11.86-24.21)\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17.14 (10.88-27.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. Bold Odds ratios (OR) indicate statistically significant associations, p\u0026lt;0.05; The final model was adjusted for age, educational attainment, and cancer diagnosis in biological relative, which all exhibited bivariate correlations with trust and political ideology.\u0026nbsp;\u003cbr\u003e\u003csup\u003ea\u003c/sup\u003eAnalytic sample, N = 6,236\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eRange 0-7\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Political ideology, public trust, cancer communication, health information, scientists, health communication","lastPublishedDoi":"10.21203/rs.3.rs-6656977/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6656977/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e\u003cbr\u003e\nTo examine whether political ideology is associated with trust in scientists as sources of cancer information in a nationally representative sample of U.S. adults.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003cbr\u003e\nWe conducted a secondary analysis of the 2024 Health Information National Trends Survey (HINTS). The analytic sample included 6,260 non-institutionalized adults aged ≥18 years (response rate: 27.3%). Political ideology was measured on a 7-point scale ranging from “very liberal” to “very conservative.” Trust in scientists for cancer information was measured on a 4-point scale and dichotomized as high (some or a lot) vs low (not at all or a little). Survey-weighted logistic regression models were used to assess the association, controlling for demographic factors and trust in physicians.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003cbr\u003e\nOverall, 86.9% of respondents (95% CI, 84.4–87.5) reported high trust in scientists for cancer information. In multivariable models, each one-point shift toward greater conservatism on the political ideology scale was associated with a 25% decrease in the odds of high trust (adjusted odds ratio [aOR], 0.75; 95% CI, 0.68–0.84). Adjusted predicted probabilities ranged from 93.7% among very liberal respondents to 70.5% among those identifying as very conservative.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u003cbr\u003e\nDespite a politically polarized climate, trust in scientists as cancer information sources remains high across the U.S. adult population. However, the presence of an ideological gradient suggests the need for communication strategies that engage politically diverse audiences to ensure broad reach and effectiveness of cancer prevention and control messaging.\u003c/p\u003e","manuscriptTitle":"High Public Trust in Scientists for Cancer Information Across Political Ideologies in the U.S","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-30 02:52:48","doi":"10.21203/rs.3.rs-6656977/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"aa6294c7-0957-4845-b735-8095ca2963b8","owner":[],"postedDate":"May 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-09T23:00:44+00:00","versionOfRecord":{"articleIdentity":"rs-6656977","link":"https://doi.org/10.1001/jamanetworkopen.2025.46818","journal":{"identity":"jama-network-open","isVorOnly":true,"title":"JAMA Network Open"},"publishedOn":"2025-12-04 00:00:00","publishedOnDateReadable":"December 4th, 2025"},"versionCreatedAt":"2025-05-30 02:52:48","video":"","vorDoi":"10.1001/jamanetworkopen.2025.46818","vorDoiUrl":"https://doi.org/10.1001/jamanetworkopen.2025.46818","workflowStages":[]},"version":"v1","identity":"rs-6656977","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6656977","identity":"rs-6656977","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}