Analysis of the awareness of core knowledge on lung cancer prevention and treatment among relatives of medical students

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This practice plays a crucial role in enhancing awareness of core knowledge on lung cancer prevention and treatment (CK-LCPT). Our research aims to evaluate CK-LCPT awareness among medical students' relatives and identify influencing factors. Methods An electronic survey was administered to relatives of medical students in China.. The survey collected respondents' basic details (11 items), their knowledge of CK-LCPT (24 items), and their interest in receiving popular science education on lung cancer prevention. Multivariate logistic regression identified predictors of inadequate CK-LCPT knowledge. Results Out of 713 completed questionnaires (a 75.5% response rate), 217 respondents (30.4%) had inadequate knowledge, whereas 496 (69.6%) possessed adequate knowledge. The multivariate logistic regression analysis indicated that being female, having a higher education level, and experiencing cancer screening were significant factors associated with adequate CK-LCPT knowledge. Additionally, Participants preferred to acquire this information primarily through social media. The most favored methods for disseminating science were articles, expert lectures, and patient-doctor communication sessions. Conclusions Targeted interventions should focus on males, less-educated individuals, and those without screening experience. This study is limited by its cross-sectional design and potential selection bias due to reliance on medical students' relatives. Lung cancer Core knowledge on lung cancer prevention and treatment Awareness rate Survey and questionnaire Multivariate analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Lung cancer remains the leading cause of cancer-related deaths globally, accounting for approximately 2.48 million new cases and 1.81 million deaths annually[1]. In China, lung cancer is the most commonly diagnosed cancer and the leading cause of cancer mortality, with 1.06 million new cases and 0.73 million deaths reported in 2022[2]. Compared to other major cancers, such as breast, colorectal, and prostate cancer, lung cancer has a disproportionately higher mortality rate.[3]. For instance, while breast cancer is the most commonly diagnosed cancer among women worldwide, its mortality rate is significantly lower than that of lung cancer. Similarly, colorectal cancer, despite its high incidence, has a lower mortality rate due to advancements in early detection and treatment. In contrast, lung cancer is frequently diagnosed at advanced stages, with only about 15% of cases detected early, leading to poor survival rates. Early detection through screening programs is critical to reducing lung cancer mortality [4]. Studies have identified awareness of core knowledge on lung cancer prevention and treatment (CK-LCPT) and willingness to participate in screening as key factors related to screening adherence [5]. Thus, boosting the awareness rate of CK-LCPT is essential for the early diagnosis and effective treatment of lung cancer. Medical students gain in-depth knowledge of lung cancer prevention and treatment through their curriculum, which enables them to effectively share accurate prevention information with their relatives. This dissemination significantly increases their relatives' understanding of CK-LCPT, thereby aiding in the improvement of lung cancer prevention measures. Consequently, our study focuses on assessing the current knowledge of lung cancer prevention among medical students' relatives, exploring their demand for educational outreach, and identifying factors that influence their knowledge levels. The aim is to establish a foundation for targeted educational initiatives on lung cancer prevention, facilitated through medical students, for this specific group. Method Survey Participants The study was approved by the Ethics Committee/Institutional Review Board of affiliated hospital of Shaanxi University of Chinese medicine. All participants provided written informed consent prior to participation. An electronic questionnaire survey was conducted with relatives of undergraduate students at a medical university in Shaanxi Province, China, from October 8th to November 1st, 2022. This survey used cluster sampling and was based on voluntary participation. To be eligible, participants needed to be 20 years or older and fully competent legally. All participants provided informed consent before taking part in the survey. Survey Content and Methodology The questionnaire was structured according to the "Core Knowledge and Essential Points for Cancer Prevention and Treatment" as outlined on the National Health Commission of China's website [6]. It consisted of three main parts: a. Basic Information of Survey Participants: This section collected data on 11 variables such as age, gender, marital status (with "Married" including divorced and widowed individuals), educational level, occupation, place of residence, annual income, smoking status, family history of lung cancer, history of lung diseases, and past participation in cancer screenings. Age groups were categorized by a 45-year threshold, as recommended in the Clinical Diagnosis Guidelines for Lung Cancer by the Chinese Medical Association (2023 Edition) [7]. b. CK-LCPT: This section comprised 24 questions covering basic information on lung cancer, its risk factors, and the significance of early screening and prompt treatment. Details are provided in Appendix 1. c. Needs Assessment for Popularizing Knowledge on Early Lung Cancer Screening: This part included three single-choice questions (with logical jumps based on selected options), two multiple-choice questions, and two open-ended questions that required prioritizing or ranking responses. The questionnaire was distributed electronically via online platforms, accessible through a QR code scanned with a smartphone. Medical students played a key role in distributing the questionnaire by sharing the link with their relatives. To maintain data integrity, a random 20% sample of completed questionnaires was selected for verification to ensure the accuracy of the responses. Definition of Observation Indicators In line with the "Healthy China Action - Cancer Prevention and Control Implementation Plan (2019–2022)" [8], an awareness rate of 70% or higher is considered adequate, while a rate below 70% is deemed inadequate. For the 24 lung cancer-related knowledge items in the survey, respondents who answered 17 or more questions correctly were categorized as having adequate knowledge of the core aspects of lung cancer prevention and control. Those who answered fewer than 17 questions correctly were considered to have inadequate knowledge. Statistical Analysis Statistical analyses were performed using SPSS version 27.0, setting the significance level at α = 0.05. Categorical data were presented as frequencies (percentages) [n (%)]. The χ² test was used to compare categorical variables between groups. Insufficient knowledge of the core aspects of lung cancer prevention and control was used as the dependent variable in these analyses. Variables that showed significant differences in the χ² test were analyzed through univariate logistic regression. Significant variables from this initial analysis were then included in a multivariate logistic regression to adjust for confounding factors and identify independent factors associated with inadequate CK-LCPT. The independent variable selection method adopts the forward stepwise regression method based on maximum likelihood estimation. For ranking questions, a reverse scoring method assigned weights to responses, giving higher weights to more highly ranked choices. Results Comparison of Participant Characteristics A total of 944 questionnaires were collected, of which 713 (75.5%) were valid. Details on the awareness rates and ranking of CK-LCPT are provided in the Appendix. The top three items with the highest awareness rates included questions on the age of high-risk populations for lung cancer, the impact of working in dusty environments, and the effects of smoking on lung cancer risk, with awareness rates of 95.93%, 94.53%, and 93.13%, respectively. Conversely, the items with the lowest awareness rates were about the risks associated with long-term exposure to secondhand smoke, the effectiveness of chest X-rays in early lung cancer detection, and the smoking index among high-risk individuals. These items had awareness rates of 44.18%, 43.34%, and 23.14%, respectively. Ultimately, 217 (30.4%) individuals were classified as having inadequate knowledge of core knowledge on lung cancer prevention and treatment (CK-LCPT), while 496 (69.6%) participants displayed adequate awareness. The data comparison between these two groups is shown in Table 1 . Table 1 Comparison of data between two groups of respondents. Parameter Total Inadequate knowledge of CK-LCPT (n = 217) Adequate knowledge of CK-LCPT (n = 496) χ 2 p Age, n(%) 7.353 0.007 < 45 years old 425(59.6) 113(52.1) 312(62.9) ≥ 45 years old 288(40.4) 104(47.9) 184(37.1) Gender, n(%) 7.635 0.006 Female 410(57.5) 108(49.8) 302(60.9) Male 303(42.5) 109(50.2) 194(39.1) Marital status, n(%) 1.582 0.208 Unmarried 224(31.4) 61(28.1) 163(32.9) Married 489(68.6) 156(71.9) 333(67.1) Education level, n(%) 74.295 < 0.001 Middle school or below 52(7.3) 38(17.5) 14(2.8) High/vocational school 92(12.9) 42(19.4) 50(10.1) Junior college 115(16.1) 39(18.0) 76(15.3) Undergraduate degree 327(45.9) 77(35.5) 250(50.4) Master or above 127(17.8) 21(9.7) 106(21.4) Occupation, n(%) 23.373 < 0.001 Farmers 84(11.8) 38(17.5) 46(9.3) Technicians 93(13.0) 31(14.3) 62(12.5) Business people 66(9.3) 22(10.1) 44(8.9) Retired personnel 106(14.9) 38(17.5) 68(13.7) Civil servants 288(40.4) 61(28.1) 227(45.8) Other 76(10.7) 27(12.4) 49(9.9) Residence, n(%) 8.870 < 0.001 Countryside 128(18.0) 53(24.4) 75(15.1) City 585(82.0) 164(75.6) 421(84.9) Annual income, n(%) 13.405 0.009 150K RMB 166(23.3) 45(20.7) 121(24.4) Smoking Status, n(%) 12.901 0.002 Never 512(71.8) 136(62.7) 376(75.8) Stopped smoking 71(10.0) 28(12.9) 43(8.7) Current smoking 130(18.2) 53(24.4) 77(15.5) Family history of lung cancer, n(%) 1.673 0.196 Negative 588(82.5) 185(85.3) 403(81.3) Positive 125(17.5) 32(14.7) 93(18.8) History of lung disease, n(%) 0.895 0.344 Negative 646(90.6) 200(92.2) 446(89.9) Positive 67(9.4) 17(7.8) 50(10.1) Cancer screening experience, n(%) 17.984 < 0.001 Negative 511(71.7) 179(82.5) 332(66.9) Positive 202(28.3) 38(17.5) 164(33.1) CK-LCPT:core knowledge on lung cancer prevention and treatment. Factors related to awareness rates of CK-LCPT Using inadequate knowledge of CK-LCPT as the dependent variable, univariate binary logistic regression analysis was conducted on the statistically significant variables listed in Table 1 .Participants aged < 45 years, males, those with junior high school education or below, farmers, rural residents, individuals with annual income < 30,000 CNY, non-smokers, and those without cancer screening experience were designated as reference categories for their respective categorical variables. The analysis identified age, gender, education level, occupation, place of residence, annual income, smoking status, and cancer screening experience as the factors related to insufficient awareness of CK-LCPT. Subsequent multivariate binary logistic regression analysis demonstrated that gender (female), education level, and cancer screening experience were factors associated with inadequate awareness of CK-LCPT, with all differences being statistically significant. Other variables were not included in the model as they were deemed confounding factors. Notably, compared to participants with education levels of middle school or below, those with higher educational attainments—senior high/vocational school, junior college, undergraduate degree, and master's degree or above—showed a progressive decrease in the risk of inadequate knowledge. The Odds Ratios (OR) for these groups decreased by 2.967, 4.587, 7.692, and 11.628 times, respectively. This decreasing trend was highly statistically significant (trend-p < 0.001), as illustrated in Fig. 2 . Popular science needs for CK-LCPT among surveyed participants Out of the 713 respondents, 624 individuals (87.52%) expressed a desire to learn more about CK-LCPT. The preferred platform for acquiring such knowledge was social media, as indicated in Fig. 3 . The top three favored methods for disseminating scientific information were popular science articles, expert lectures, and patient-doctor communication sessions, as shown in Fig. 4 . Discussion Contrary to common assumptions, our survey reveals that relatives of medical students do not exhibit a significantly higher awareness rate of CK-LCPT. They barely meet the 70% minimum awareness rate specified in the "Healthy China Action - Cancer Prevention and Control Implementation Plan (2019–2022)," and fall short of the 80% target set by the more recent "Healthy China Action - Cancer Prevention and Control Implementation Plan (2023–2030)" [9]. A vast majority of survey respondents recognized that smoking is a risk factor for lung cancer (93.13%), but fewer understood the correlation between the number of cigarettes smoked and the increased risk of lung concerns (23.14%), or the risks associated with secondhand smoke exposure (44.18%). The most effective method for early detection of lung cancer is low-dose CT (computed tomography) scans of the chest [10], a technique shown to significantly reduce mortality rates [11,12]. However, our survey results reveal that most participants have insufficient awareness of lung cancer screening methods, not meeting even the basic recommended standards. The data suggest that while there is a general awareness of the main risk factors and characteristics of lung cancer, likely due to extensive and accessible educational campaigns, significant gaps remain in understanding crucial aspects of early screening, accurate diagnosis, and timely treatment. This highlights the need for widespread dissemination of comprehensive and accurate information on early detection, diagnosis, and intervention for lung cancer. Particularly, it emphasizes the importance of thoroughness and precision in the content provided. Our findings also indicate that the benefits of low-dose CT scans have not been sufficiently communicated to the public. Additionally, respondents demonstrated limited knowledge regarding lung cancer treatments. Therefore, there is an urgent need to develop tailored health education models and public science communication strategies to close these knowledge gaps, aiming to improve screening and early diagnosis rates, and thus decrease mortality rates from lung cancer. Our findings indicate that certain groups, such as males, individuals with lower education levels, and those who have not undergone cancer screening, exhibit lower awareness of CK-LCPT. This is consistent with studies from other regions, such as the Middle East [13]. Despite higher lung cancer incidence and mortality rates among males [1], being female was associated with better knowledge of lung cancer prevention. This may be due to women's roles as caregivers in families and communities, which could lead them to actively seek and share health information. women are more likely to take on caregiving roles within families, which may lead them to actively seek out health information. Additionally, women often have more frequent interactions with healthcare systems due to reproductive health needs, which may enhance their overall health literacy. Conversely, men may be less likely to engage in health information-seeking behaviors due to cultural norms that discourage vulnerability or health-related discussions. These sociocultural factors should be considered when designing targeted educational interventions, as they may significantly influence the effectiveness of health communication strategies. Regarding educational level, the odds ratio (OR) for inadequate knowledge about CK-LCPT decreased among individuals with higher education compared to those with education at the middle school level or below, and this difference was statistically significant. Higher education typically equips individuals with better skills for retrieving high-quality information from various sources, such as the internet, professional literature, and health seminars. These individuals are more proactive in learning about preventive measures, recognizing early symptoms, and understanding treatment options for lung cancer. They are also more likely to engage in cancer screening programs, which helps in early detection. A recent comprehensive study confirmed that educational attainment significantly influences public awareness of cancer risk factors and symptoms [14]. Overall, higher education enhances capabilities in information retrieval, critical evaluation, learning, and application, thereby increasing attention to crucial knowledge about lung cancer prevention and control. Furthermore, the lack of screening experience among certain participants may contribute to their lower awareness. Screening programs often serve as educational opportunities, providing individuals with information about lung cancer risks and prevention strategies. Those who have not undergone screening miss out on these educational interactions, which could explain their lower awareness levels. This finding is supported by a study in Saudi Arabia, which found that individuals who had participated in cancer screening programs had significantly higher awareness of lung cancer risk factors compared to those who had not. To address these gaps, medical students can play a pivotal role in improving CK-LCPT awareness among their relatives. Given their access to scientifically validated information, medical students are well-positioned to educate their families about lung cancer prevention. They can leverage social media platforms, which were identified as the preferred method for disseminating health information in our study and prior studies [15,16], to share accurate and engaging content. Additionally, medical students can organize family discussions to address specific knowledge gaps, particularly for males, less-educated individuals, and those without screening experience. Tailored educational interventions, such as simplified informational materials for individuals with lower education levels, could also be effective in bridging these gaps. As a cross-sectional study impairing the ability to establish causality, this study also have several limitations. First, it was conducted solely among relatives of students from a single medical school, potentially limiting the representativeness of the sample. Second, the proportion of elderly individuals in our sample was relatively small, which could introduce bias into our results. This may be due, in part, to the unfamiliarity of some older adults with electronic questionnaires on mobile devices. Additionally, the use of an electronic survey may have excluded certain demographic groups, such as elderly individuals who are less familiar with digital platforms. This limitation should be considered when interpreting the results, as it may affect the generalizability of our findings. Lastly, the reliance on self-reported data introduces the potential for biases, such as social desirability bias, where participants may overestimate their knowledge to present themselves in a favorable light. Future studies should consider incorporating objective measures of knowledge to mitigate this issue. In summary, being female, possessing a higher education level, and having cancer screening experience are independent factors associated with inadequate knowledge of CK-LCPT. Medical students should focus on males, individuals with lower education levels, and those without cancer screening experience as key groups lacking adequate knowledge about lung cancer prevention. These groups and their relatives should be primary targets for educational interventions. Declarations Abbreviations List all abbreviations used in the text, providing their full forms. Ethics approval and consent to participate The study was approved by the Ethics Committee/Institutional Review Board of affiliated hospital of Shaanxi University of Chinese medicine. All participants provided written informed consent prior to participation.The study adhered to the Declaration of Helsinki Consent for publication Not Applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing Interests "The authors declare that they have no competing interests." Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors' contributions Y.N. conceived and designed the experiments; H.D and Y.N. performed the experiments; Z.L analyzed the data; M.G contributed reagents/materials/analysis tools; H.D and D.S wrote the paper. Acknowledgements Not Applicable References Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al . Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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Promoting lung cancer awareness, help-seeking and early detection: a systematic review of interventions. Health Promot Int 2021;36:1656–1671. doi: 10.1093/heapro/daab016 . Additional Declarations No competing interests reported. Supplementary Files Appendix.docx questionared1.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 12 Apr, 2025 Reviewers agreed at journal 10 Apr, 2025 Reviewers invited by journal 09 Apr, 2025 Submission checks completed at journal 04 Apr, 2025 First submitted to journal 29 Mar, 2025 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. 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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-5534849","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":441156822,"identity":"ed9acc00-d1ed-4eb4-b9f1-e56e804e5853","order_by":0,"name":"Nan 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CK-LCPT.\u003c/p\u003e","description":"","filename":"1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5534849/v1/758c5941ec20ab6eb518aa67.jpeg"},{"id":80578801,"identity":"ea9c9403-f149-465c-ab31-7dd006eb94a6","added_by":"auto","created_at":"2025-04-14 23:05:18","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":868275,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate binary logistic regression analysis of factors related to inadequate awareness of CK-LCPT.\u003c/p\u003e","description":"","filename":"2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5534849/v1/de70bbf323888988ce6a8c20.jpeg"},{"id":80578806,"identity":"e7615b64-2135-475b-b22e-b1abbbfab4e4","added_by":"auto","created_at":"2025-04-14 23:05:18","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":45935,"visible":true,"origin":"","legend":"\u003cp\u003eThe channel in which the respondents hope to learn about CK-LCPT\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5534849/v1/3b4fe4512affb830abc44d89.jpg"},{"id":80577524,"identity":"013f89db-7497-4e33-801e-f700a3c13abb","added_by":"auto","created_at":"2025-04-14 22:57:18","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":55049,"visible":true,"origin":"","legend":"\u003cp\u003eThe form in which the respondents hope to obtain about CK-LCPT\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5534849/v1/09453cdd21c40b734d0eb34d.jpg"},{"id":80580133,"identity":"63921fdc-da18-4280-8e3d-c00d775fcbec","added_by":"auto","created_at":"2025-04-14 23:13:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2935891,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5534849/v1/731784a6-46d7-43b1-abf9-25f9ede5084e.pdf"},{"id":80578800,"identity":"6ef4098f-e343-4526-b31c-696fe1543261","added_by":"auto","created_at":"2025-04-14 23:05:18","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18080,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5534849/v1/130a5ff4db1ccd863519589c.docx"},{"id":80577523,"identity":"6e86476b-2313-415c-915a-9bce35af3bdd","added_by":"auto","created_at":"2025-04-14 22:57:18","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15625,"visible":true,"origin":"","legend":"","description":"","filename":"questionared1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5534849/v1/3bf86f9c4e3ba18b78f86e71.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of the awareness of core knowledge on lung cancer prevention and treatment among relatives of medical students","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLung cancer remains the leading cause of cancer-related deaths globally, accounting for approximately 2.48\u0026nbsp;million new cases and 1.81\u0026nbsp;million deaths annually[1]. In China, lung cancer is the most commonly diagnosed cancer and the leading cause of cancer mortality, with 1.06\u0026nbsp;million new cases and 0.73\u0026nbsp;million deaths reported in 2022[2]. Compared to other major cancers, such as breast, colorectal, and prostate cancer, lung cancer has a disproportionately higher mortality rate.[3]. For instance, while breast cancer is the most commonly diagnosed cancer among women worldwide, its mortality rate is significantly lower than that of lung cancer. Similarly, colorectal cancer, despite its high incidence, has a lower mortality rate due to advancements in early detection and treatment. In contrast, lung cancer is frequently diagnosed at advanced stages, with only about 15% of cases detected early, leading to poor survival rates. Early detection through screening programs is critical to reducing lung cancer mortality [4]. Studies have identified awareness of core knowledge on lung cancer prevention and treatment (CK-LCPT) and willingness to participate in screening as key factors related to screening adherence [5]. Thus, boosting the awareness rate of CK-LCPT is essential for the early diagnosis and effective treatment of lung cancer.\u003c/p\u003e \u003cp\u003eMedical students gain in-depth knowledge of lung cancer prevention and treatment through their curriculum, which enables them to effectively share accurate prevention information with their relatives. This dissemination significantly increases their relatives' understanding of CK-LCPT, thereby aiding in the improvement of lung cancer prevention measures. Consequently, our study focuses on assessing the current knowledge of lung cancer prevention among medical students' relatives, exploring their demand for educational outreach, and identifying factors that influence their knowledge levels. The aim is to establish a foundation for targeted educational initiatives on lung cancer prevention, facilitated through medical students, for this specific group.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSurvey Participants\u003c/h2\u003e \u003cp\u003e The study was approved by the Ethics Committee/Institutional Review Board of affiliated hospital of Shaanxi University of Chinese medicine. All participants provided written informed consent prior to participation. An electronic questionnaire survey was conducted with relatives of undergraduate students at a medical university in Shaanxi Province, China, from October 8th to November 1st, 2022. This survey used cluster sampling and was based on voluntary participation. To be eligible, participants needed to be 20 years or older and fully competent legally. All participants provided informed consent before taking part in the survey.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSurvey Content and Methodology\u003c/h3\u003e\n\u003cp\u003eThe questionnaire was structured according to the \"Core Knowledge and Essential Points for Cancer Prevention and Treatment\" as outlined on the National Health Commission of China's website [6]. It consisted of three main parts:\u003c/p\u003e\u003cp\u003ea. Basic Information of Survey Participants: This section collected data on 11 variables such as age, gender, marital status (with \"Married\" including divorced and widowed individuals), educational level, occupation, place of residence, annual income, smoking status, family history of lung cancer, history of lung diseases, and past participation in cancer screenings. Age groups were categorized by a 45-year threshold, as recommended in the Clinical Diagnosis Guidelines for Lung Cancer by the Chinese Medical Association (2023 Edition) [7].\u003c/p\u003e\u003cp\u003eb. CK-LCPT: This section comprised 24 questions covering basic information on lung cancer, its risk factors, and the significance of early screening and prompt treatment. Details are provided in Appendix 1.\u003c/p\u003e\u003cp\u003ec. Needs Assessment for Popularizing Knowledge on Early Lung Cancer Screening: This part included three single-choice questions (with logical jumps based on selected options), two multiple-choice questions, and two open-ended questions that required prioritizing or ranking responses.\u003c/p\u003e \u003cp\u003eThe questionnaire was distributed electronically via online platforms, accessible through a QR code scanned with a smartphone. Medical students played a key role in distributing the questionnaire by sharing the link with their relatives. To maintain data integrity, a random 20% sample of completed questionnaires was selected for verification to ensure the accuracy of the responses.\u003c/p\u003e\n\u003ch3\u003eDefinition of Observation Indicators\u003c/h3\u003e\n\u003cp\u003eIn line with the \"Healthy China Action - Cancer Prevention and Control Implementation Plan (2019\u0026ndash;2022)\" [8], an awareness rate of 70% or higher is considered adequate, while a rate below 70% is deemed inadequate. For the 24 lung cancer-related knowledge items in the survey, respondents who answered 17 or more questions correctly were categorized as having adequate knowledge of the core aspects of lung cancer prevention and control. Those who answered fewer than 17 questions correctly were considered to have inadequate knowledge.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS version 27.0, setting the significance level at \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05. Categorical data were presented as frequencies (percentages) [n (%)]. The \u003cem\u003eχ\u0026sup2;\u003c/em\u003e test was used to compare categorical variables between groups. Insufficient knowledge of the core aspects of lung cancer prevention and control was used as the dependent variable in these analyses. Variables that showed significant differences in the \u003cem\u003eχ\u0026sup2;\u003c/em\u003e test were analyzed through univariate logistic regression. Significant variables from this initial analysis were then included in a multivariate logistic regression to adjust for confounding factors and identify independent factors associated with inadequate CK-LCPT. The independent variable selection method adopts the forward stepwise regression method based on maximum likelihood estimation. For ranking questions, a reverse scoring method assigned weights to responses, giving higher weights to more highly ranked choices.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eComparison of Participant Characteristics\u003c/h2\u003e \u003cp\u003eA total of 944 questionnaires were collected, of which 713 (75.5%) were valid. Details on the awareness rates and ranking of CK-LCPT are provided in the Appendix. The top three items with the highest awareness rates included questions on the age of high-risk populations for lung cancer, the impact of working in dusty environments, and the effects of smoking on lung cancer risk, with awareness rates of 95.93%, 94.53%, and 93.13%, respectively.\u003c/p\u003e \u003cp\u003eConversely, the items with the lowest awareness rates were about the risks associated with long-term exposure to secondhand smoke, the effectiveness of chest X-rays in early lung cancer detection, and the smoking index among high-risk individuals. These items had awareness rates of 44.18%, 43.34%, and 23.14%, respectively.\u003c/p\u003e \u003cp\u003eUltimately, 217 (30.4%) individuals were classified as having inadequate knowledge of core knowledge on lung cancer prevention and treatment (CK-LCPT), while 496 (69.6%) participants displayed adequate awareness. The data comparison between these two groups is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of data between two groups of respondents.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInadequate knowledge of CK-LCPT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;217)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdequate knowledge of CK-LCPT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;496)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003cem\u003e2\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;45 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e425(59.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113(52.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e312(62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;45 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288(40.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104(47.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e184(37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e410(57.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108(49.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e302(60.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e303(42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109(50.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e194(39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e224(31.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61(28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e163(32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e489(68.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156(71.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e333(67.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle school or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52(7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38(17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14(2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh/vocational school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92(12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42(19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50(10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115(16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39(18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76(15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUndergraduate degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e327(45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77(35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e250(50.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e127(17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21(9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e106(21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarmers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84(11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38(17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46(9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnicians\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93(13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31(14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBusiness people\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66(9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22(10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44(8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetired personnel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e106(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38(17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68(13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCivil servants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288(40.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61(28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e227(45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76(10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27(12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49(9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountryside\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e128(18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53(24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75(15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e585(82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e164(75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e421(84.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnual income, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;30K RMB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e137(19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55(25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82(16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30-70K RMB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e152(21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54(24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e98(19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70-100K RMB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e162(22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41(18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e121(24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100-150K RMB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22(10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;150K RMB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e166(23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45(20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e121(24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking Status, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e512(71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e136(62.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e376(75.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStopped smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71(10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28(12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43(8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e130(18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53(24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77(15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of lung cancer, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e588(82.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e185(85.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e403(81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125(17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32(14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e93(18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of lung disease, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.344\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e646(90.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e200(92.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e446(89.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67(9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17(7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50(10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer screening experience, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e511(71.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e179(82.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e332(66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e202(28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38(17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e164(33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCK-LCPT:core knowledge on lung cancer prevention and treatment.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFactors related to awareness rates of CK-LCPT\u003c/h3\u003e\n\u003cp\u003eUsing inadequate knowledge of CK-LCPT as the dependent variable, univariate binary logistic regression analysis was conducted on the statistically significant variables listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.Participants aged\u0026thinsp;\u0026lt;\u0026thinsp;45 years, males, those with junior high school education or below, farmers, rural residents, individuals with annual income\u0026thinsp;\u0026lt;\u0026thinsp;30,000 CNY, non-smokers, and those without cancer screening experience were designated as reference categories for their respective categorical variables. The analysis identified age, gender, education level, occupation, place of residence, annual income, smoking status, and cancer screening experience as the factors related to insufficient awareness of CK-LCPT.\u003c/p\u003e \u003cp\u003eSubsequent multivariate binary logistic regression analysis demonstrated that gender (female), education level, and cancer screening experience were factors associated with inadequate awareness of CK-LCPT, with all differences being statistically significant. Other variables were not included in the model as they were deemed confounding factors. Notably, compared to participants with education levels of middle school or below, those with higher educational attainments\u0026mdash;senior high/vocational school, junior college, undergraduate degree, and master's degree or above\u0026mdash;showed a progressive decrease in the risk of inadequate knowledge. The Odds Ratios (OR) for these groups decreased by 2.967, 4.587, 7.692, and 11.628 times, respectively. This decreasing trend was highly statistically significant (trend-p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \n\u003ch3\u003ePopular science needs for CK-LCPT among surveyed participants\u003c/h3\u003e\n\u003cp\u003eOut of the 713 respondents, 624 individuals (87.52%) expressed a desire to learn more about CK-LCPT. The preferred platform for acquiring such knowledge was social media, as indicated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The top three favored methods for disseminating scientific information were popular science articles, expert lectures, and patient-doctor communication sessions, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eContrary to common assumptions, our survey reveals that relatives of medical students do not exhibit a significantly higher awareness rate of CK-LCPT. They barely meet the 70% minimum awareness rate specified in the \"Healthy China Action - Cancer Prevention and Control Implementation Plan (2019\u0026ndash;2022),\" and fall short of the 80% target set by the more recent \"Healthy China Action - Cancer Prevention and Control Implementation Plan (2023\u0026ndash;2030)\" [9].\u003c/p\u003e \u003cp\u003eA vast majority of survey respondents recognized that smoking is a risk factor for lung cancer (93.13%), but fewer understood the correlation between the number of cigarettes smoked and the increased risk of lung concerns (23.14%), or the risks associated with secondhand smoke exposure (44.18%). The most effective method for early detection of lung cancer is low-dose CT (computed tomography) scans of the chest [10], a technique shown to significantly reduce mortality rates [11,12]. However, our survey results reveal that most participants have insufficient awareness of lung cancer screening methods, not meeting even the basic recommended standards. The data suggest that while there is a general awareness of the main risk factors and characteristics of lung cancer, likely due to extensive and accessible educational campaigns, significant gaps remain in understanding crucial aspects of early screening, accurate diagnosis, and timely treatment. This highlights the need for widespread dissemination of comprehensive and accurate information on early detection, diagnosis, and intervention for lung cancer. Particularly, it emphasizes the importance of thoroughness and precision in the content provided.\u003c/p\u003e \u003cp\u003eOur findings also indicate that the benefits of low-dose CT scans have not been sufficiently communicated to the public. Additionally, respondents demonstrated limited knowledge regarding lung cancer treatments. Therefore, there is an urgent need to develop tailored health education models and public science communication strategies to close these knowledge gaps, aiming to improve screening and early diagnosis rates, and thus decrease mortality rates from lung cancer.\u003c/p\u003e \u003cp\u003eOur findings indicate that certain groups, such as males, individuals with lower education levels, and those who have not undergone cancer screening, exhibit lower awareness of CK-LCPT. This is consistent with studies from other regions, such as the Middle East [13]. Despite higher lung cancer incidence and mortality rates among males [1], being female was associated with better knowledge of lung cancer prevention. This may be due to women's roles as caregivers in families and communities, which could lead them to actively seek and share health information. women are more likely to take on caregiving roles within families, which may lead them to actively seek out health information. Additionally, women often have more frequent interactions with healthcare systems due to reproductive health needs, which may enhance their overall health literacy. Conversely, men may be less likely to engage in health information-seeking behaviors due to cultural norms that discourage vulnerability or health-related discussions. These sociocultural factors should be considered when designing targeted educational interventions, as they may significantly influence the effectiveness of health communication strategies.\u003c/p\u003e \u003cp\u003eRegarding educational level, the odds ratio (OR) for inadequate knowledge about CK-LCPT decreased among individuals with higher education compared to those with education at the middle school level or below, and this difference was statistically significant. Higher education typically equips individuals with better skills for retrieving high-quality information from various sources, such as the internet, professional literature, and health seminars. These individuals are more proactive in learning about preventive measures, recognizing early symptoms, and understanding treatment options for lung cancer. They are also more likely to engage in cancer screening programs, which helps in early detection. A recent comprehensive study confirmed that educational attainment significantly influences public awareness of cancer risk factors and symptoms [14]. Overall, higher education enhances capabilities in information retrieval, critical evaluation, learning, and application, thereby increasing attention to crucial knowledge about lung cancer prevention and control.\u003c/p\u003e \u003cp\u003eFurthermore, the lack of screening experience among certain participants may contribute to their lower awareness. Screening programs often serve as educational opportunities, providing individuals with information about lung cancer risks and prevention strategies. Those who have not undergone screening miss out on these educational interactions, which could explain their lower awareness levels. This finding is supported by a study in Saudi Arabia, which found that individuals who had participated in cancer screening programs had significantly higher awareness of lung cancer risk factors compared to those who had not.\u003c/p\u003e \u003cp\u003eTo address these gaps, medical students can play a pivotal role in improving CK-LCPT awareness among their relatives. Given their access to scientifically validated information, medical students are well-positioned to educate their families about lung cancer prevention. They can leverage social media platforms, which were identified as the preferred method for disseminating health information in our study and prior studies [15,16], to share accurate and engaging content. Additionally, medical students can organize family discussions to address specific knowledge gaps, particularly for males, less-educated individuals, and those without screening experience. Tailored educational interventions, such as simplified informational materials for individuals with lower education levels, could also be effective in bridging these gaps.\u003c/p\u003e \u003cp\u003eAs a cross-sectional study impairing the ability to establish causality, this study also have several limitations. First, it was conducted solely among relatives of students from a single medical school, potentially limiting the representativeness of the sample. Second, the proportion of elderly individuals in our sample was relatively small, which could introduce bias into our results. This may be due, in part, to the unfamiliarity of some older adults with electronic questionnaires on mobile devices. Additionally, the use of an electronic survey may have excluded certain demographic groups, such as elderly individuals who are less familiar with digital platforms. This limitation should be considered when interpreting the results, as it may affect the generalizability of our findings. Lastly, the reliance on self-reported data introduces the potential for biases, such as social desirability bias, where participants may overestimate their knowledge to present themselves in a favorable light. Future studies should consider incorporating objective measures of knowledge to mitigate this issue.\u003c/p\u003e \u003cp\u003eIn summary, being female, possessing a higher education level, and having cancer screening experience are independent factors associated with inadequate knowledge of CK-LCPT. Medical students should focus on males, individuals with lower education levels, and those without cancer screening experience as key groups lacking adequate knowledge about lung cancer prevention. These groups and their relatives should be primary targets for educational interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eList all abbreviations used in the text, providing their full forms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee/Institutional Review Board of affiliated hospital of Shaanxi University of Chinese medicine. All participants provided written informed consent prior to participation.The study adhered to the Declaration of Helsinki\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026quot;The authors declare that they have no competing interests.\u0026quot;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.N. conceived and designed the experiments; H.D and Y.N. performed the experiments; Z.L analyzed the data; M.G contributed reagents/materials/analysis tools; H.D and D.S wrote the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, \u003cem\u003eet al\u003c/em\u003e. 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Health Promot Int 2021;36:1656\u0026ndash;1671. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/heapro/daab016\u003c/span\u003e\u003cspan address=\"10.1093/heapro/daab016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Lung cancer, Core knowledge on lung cancer prevention and treatment, Awareness rate, Survey and questionnaire, Multivariate analysis","lastPublishedDoi":"10.21203/rs.3.rs-5534849/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5534849/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMedical students are well-positioned to share scientifically valid and precise information about lung cancer prevention with their families. This practice plays a crucial role in enhancing awareness of core knowledge on lung cancer prevention and treatment (CK-LCPT). Our research aims to evaluate CK-LCPT awareness among medical students' relatives and identify influencing factors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eAn electronic survey was administered to relatives of medical students in China.. The survey collected respondents' basic details (11 items), their knowledge of CK-LCPT (24 items), and their interest in receiving popular science education on lung cancer prevention. Multivariate logistic regression identified predictors of inadequate CK-LCPT knowledge.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOut of 713 completed questionnaires (a 75.5% response rate), 217 respondents (30.4%) had inadequate knowledge, whereas 496 (69.6%) possessed adequate knowledge. The multivariate logistic regression analysis indicated that being female, having a higher education level, and experiencing cancer screening were significant factors associated with adequate CK-LCPT knowledge. Additionally, Participants preferred to acquire this information primarily through social media. The most favored methods for disseminating science were articles, expert lectures, and patient-doctor communication sessions.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eTargeted interventions should focus on males, less-educated individuals, and those without screening experience. This study is limited by its cross-sectional design and potential selection bias due to reliance on medical students' relatives.\u003c/p\u003e","manuscriptTitle":"Analysis of the awareness of core knowledge on lung cancer prevention and treatment among relatives of medical students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-14 22:57:13","doi":"10.21203/rs.3.rs-5534849/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-04-12T09:35:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"99943383795888980055849087187955955203","date":"2025-04-10T12:01:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-09T18:27:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-05T02:24:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2025-03-29T15:34:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d2adb8c-390d-4437-8c1d-0d72954191b4","owner":[],"postedDate":"April 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-04-17T06:53:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-14 22:57:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5534849","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5534849","identity":"rs-5534849","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}