Introduction

Hepatitis B virus (HBV) remains a significant global public health challenge. The global seroprevalence of hepatitis B surface antigen (HBsAg) was estimated to be 3.9% in 2016, reflecting widespread chronic infection rates worldwide.1 In China, the burden is even greater, with an estimated HBsAg prevalence of 6.1% and over 80 million people living with chronic hepatitis B virus (CHB) infections as of 2018.1–3 According to the World Health Organization (WHO), an estimated 254 million people were living with chronic hepatitis B infection globally in 2022, with 1.2 million new infections occurring each year. The same year, hepatitis B accounted for approximately 1.1 million deaths, predominantly due to complications such as cirrhosis and hepatocellular carcinoma (HCC), a major form of primary liver cancer.4

Patients with chronic hepatitis B often face severe complications, including cirrhosis and HCC, which is the third leading cause of cancer-related deaths globally.5 In China, the association between hepatitis B and liver cancer is particularly striking, with approximately 80% of all HCC cases attributed to HBV infections.6 Recent national reports have highlighted continuing increases in liver cancer rehabilitation needs and disparities in disease outcomes across regions.7

Addressing these challenges requires not only clinical interventions but also a deep understanding of public knowledge, attitudes, and practices (KAP) regarding hepatitis B and liver cancer. KAP surveys serve as essential diagnostic tools to assess a population’s comprehension, beliefs, and behaviors surrounding specific health issues. Based on the premise that knowledge positively influences attitudes, which subsequently shape behaviors, KAP studies provide a framework to identify deficiencies and inform targeted interventions in health literacy and behavior change.8,9 Recent KAP research in China has further emphasized gaps in screening awareness and prevention behaviors among high-risk groups.10

Given the significant public health burden of hepatitis B and liver cancer in China, this study investigates the Knowledge, Attitudes, and Practices (KAP) of hepatobiliary surgery liver cancer patients and their family members. The survey questions were designed to evaluate essential aspects of awareness, beliefs, and behaviors related to hepatitis B and liver cancer. Specifically, the study examines gaps in knowledge about the disease’s risk factors, transmission pathways, prevention methods, and management strategies. Additionally, it explores attitudes toward disease disclosure, stigma, and psychological burdens, as well as practical barriers to treatment adherence, such as cost and accessibility of healthcare services.

These insights are crucial because hepatobiliary surgery patients and their families are at the center of care and decision-making processes, influencing disease outcomes through their understanding and behaviors. By identifying deficiencies in KAP, this study highlights areas requiring targeted interventions, such as public education campaigns, counseling support, and policy reforms to improve affordability and accessibility of care. Recent analyses in China have shown that the liver cancer burden and disease mortality have significant urban-rural disparities, with rural populations consistently demonstrating worse outcomes.11 Several recent KAP studies among high-risk Chinese populations, including screening behavior, reinforce the observed gaps in knowledge and practice.10 The findings also provide a foundation for developing tailored health promotion strategies and clinical education programs to enhance early detection, treatment compliance, and disease management outcomes for both patients and their families. Furthermore, rising rehabilitation needs among liver cancer patients and increasing attributable risk factors, including demographic aging and regional inequality, have been documented in recent years.7

Materials and MethodsStudy Design and Participants

This cross-sectional study was conducted between February 15, 2023, and August 31, 2024, at four institutions: the First Affiliated Hospital of Army Medical University, the Second Affiliated Hospital of Chongqing Medical University, the First Affiliated Hospital of Zhengzhou University, and Xuanhan County People’s Hospital. The study population included inpatients with liver cancer in hepatobiliary surgery departments and their family members. Ethical approval was obtained from Ethics Committee the First Affiliated Hospital of Army Medical University (Approval No.: (A) KY2023025). This study was registered on the website of Chinese Clinical Trial Registry (registration number: ChiCTR2300068582), and informed consent was secured from all participants. Inclusion Criteria: 1) Patients diagnosed with primary liver cancer and their family members (including informed family members or immediate relatives), with no restrictions on age, gender, or treatment status (initial or repeat treatment). 2) Individuals who were aware of the patient’s condition and voluntarily agreed to participate in the study. 3) In cases where the patient was unaware of their condition, the patient was excluded from the questionnaire survey, but their family members could still participate. Exclusion Criteria: 1) Patients with severe liver failure, such as hepatic coma, mental confusion, or other conditions that would impede the completion of the questionnaire. 2) Patients or their family members who declined to participate in the study. This study protocol has been approved by the Ethics Committee of the First Affiliated Hospital of Army Medical University Hospital and obtained the written consent of all participants.

Questionnaire Design

The questionnaire was designed and refined based on feedback from four experts, including one professor of statistics, one professor of epidemiology, and two professors of surgery. A pilot test was conducted with a sample of 39 participants, yielding a reliability score of 0.886, indicating strong internal consistency.

The final version of the questionnaire, written in Chinese, consists of 56 items divided into four dimensions (Figures S1 and S2). The demographic characteristics section includes 18 items, the knowledge dimension comprises 13 items, the attitude dimension includes 14 items, and the practice dimension contains 11 items (Figure S2). Scoring was tailored to the specific format of each dimension. In the knowledge dimension, correct answers were awarded 1 point, while incorrect or “unsure” answers were assigned 0 points. The attitude and practice dimensions were assessed using a 5-point Likert scale. For the attitude dimension, items 1–3, 5–7, 10, and 12 were scored on a scale from 5 to 1 for response options a toe, while items 4, 8, 9, and 11 were reverse-scored from 1 to 5. Items 13 and 14 were excluded from scoring, resulting in a total possible score range of 12–60. Attitude scores were categorized as follows: 12–30 indicated a negative attitude, 31–42 indicated a neutral attitude, and 43–60 indicated a positive attitude. In the practice dimension, items 1 and 3–10 were scored from 5 to 1 for options a to e, while item 2 was reverse-scored from 1 to 5. Item 11 was not scored, yielding a total possible score range of 10–50. Practice scores were similarly categorized: scores of 10–25 indicated negative practices, 26–35 indicated neutral practices, and 36–50 indicated positive practices. The scoring criteria were based on prior research, where a score below 50% was defined as poor, while a score above 70% was regarded as good.12 These thresholds were adapted for pragmatic classification in this study, but we acknowledge that they may not be universally accepted and should be interpreted with caution.

Data Collection and Quality Control

Six well-trained research assistants conducted regular reviews of hepatobiliary surgery inpatients to identify and enroll eligible participants. For patients and family members who met the inclusion criteria, the research assistants provided on-site guidance to access and complete the questionnaire online via SoJump (https://www.wjx.cn/) platform by scanning a QR code. Although SoJump is widely used in China, we acknowledge that relying on an online self-administered platform may introduce potential digital literacy or access bias, particularly among older or rural participants. To mitigate this, trained research assistants were present to provide technical support and ensure that participants could complete the questionnaire without undue difficulty. While assistants addressed any questions regarding unclear items, they ensured that their explanations did not influence the participants’ responses. The hospital centers involved in this study were recruited through the researchers’ personal networks, engaging collaborators who expressed interest in participating in the study.

Sample Size Calculation

The sample size for this cross-sectional study was calculated using the standard formula:13 n = Z² × P × (1 − P)/d², where n represents the required sample size, Z is the Z-score corresponding to the desired confidence level (1.96 for 95% confidence), p is the estimated prevalence of the outcome in the target population, and d denotes the margin of error or precision (commonly set at 0.05 for ±5%). In this study, a conservative prevalence estimates of p=0.5 was used to maximize the required sample size, ensuring sufficient power for detecting statistically significant results. Substituting these values into the formula, the calculation yielded n=384, which represents the minimum number of participants required to achieve reliable and valid results. Considering a potential 20% non-response rate, the final adjusted sample size was increased to n=480, ensuring adequate participation to account for incomplete or missing data.

Statistical Analysis

Statistical analyses were conducted using SPSS version 27 (IBM, Armonk, NY, USA) and AMOS version 26 (IBM, Armonk, NY, USA). The overall reliability of the questionnaire was confirmed with a Cronbach’s α of 0.886 based on a pilot test of 39 participants. Normality of data was assessed prior to analysis. For normally distributed data, results are presented as means and standard deviations (SD), and for non-normally distributed data, as medians and interquartile ranges (IQR; 25th and 75th percentiles). Categorical data are expressed as n (%). Group comparisons were performed using t-tests or Wilcoxon-Mann–Whitney tests for two groups and ANOVA or Kruskal–Wallis tests for three or more groups, depending on the distribution and homogeneity of variance. Correlations between dimension scores were assessed using Pearson’s or Spearman correlation coefficients, as appropriate. Univariate and multivariate logistic regression analyses were conducted to examine the associations between demographic characteristics and dimension scores, with variables meeting p < 0.1 in univariate analysis included in the multivariate model. Multicollinearity was assessed using variance inflation factors (VIFs) and tolerance values for all covariates. Tolerance ranged from 0.574 to 0.971 and VIF from 1.029 to 1.743, indicating no significant multicollinearity. A two-sided p-value < 0.05 was considered statistically significant. Structural equation modeling (SEM) was used to evaluate the mediating effect of attitudes on the relationship between knowledge and practice, with model fit indices set as RMSEA < 0.08, SRMR < 0.08, TLI > 0.8, and CFI > 0.8. If the model fit was inadequate, path analysis was conducted.

Results

After collecting the questionnaires, the following cases were excluded: 2 cases where the age was incorrectly filled or the participant was under 18 years old; 4 cases where the response to Question 13 was non-standardized; 9 cases with logical errors in responses to Question 16 of the basic questions; and 3 cases where all three dimensions of the KAP responses were “A”. These resulted in 810 valid questionnaires.

Demographic Characteristics

Among the 810 respondents, 722 (89.14%) were from the Southwest Hospital Center, 432 (53.33%) were family members of patients, and 510 (62.96%) were male, with a mean age of 45.00 ± 13.19 years. A total of 98 (12.10%) participants were still consuming alcohol, while 564 (69.63%) were either patients or family members diagnosed with hepatitis B. Additionally, 529 (65.31%) had been diagnosed for more than one year, and 257 (31.73%) had a history of surgery for liver cancer. The mean scores for knowledge, attitude, and practice were 7.19 ± 3.68 (possible range: 0–18), 43.71 ± 4.30 (possible range: 12–60), and 39.93 ± 6.06 (possible range: 10–50), respectively. Moreover, knowledge scores varied significantly based on group (P < 0.001), residence (P < 0.001), education level (P < 0.001), employment status (P < 0.001), monthly per capita income (P < 0.001), smoking status (P = 0.019), health insurance coverage (P = 0.002), hepatitis B diagnosis (P < 0.001), duration of hepatitis B virus infection (P < 0.001), HCC status (P < 0.001), duration of liver cancer diagnosis (P < 0.001), diabetes status (P < 0.001), and history of liver cancer surgery (P < 0.001). Similarly, attitude scores were significantly influenced by group (P < 0.001), relationship with the patient (P = 0.003), residence (P = 0.001), education level (P < 0.001), employment status (P < 0.001), monthly per capita income (P < 0.001), health insurance (P = 0.003), hyperlipidemia (P = 0.010), diabetes (P < 0.001), and history of liver cancer surgery (P = 0.001). Practice scores also varied significantly by group (P < 0.001), relationship with the patient (P < 0.001), gender (P < 0.001), residence (P < 0.001), education level (P < 0.001), employment status (P < 0.001), monthly per capita income (P < 0.001), smoking status (P < 0.001), alcohol consumption status (P = 0.013), health insurance (P < 0.001), hepatitis B diagnosis (P = 0.049), presence of other chronic conditions (P = 0.002), hyperlipidemia (P = 0.002), and diabetes (P < 0.001) (Table 1).

Table 1 Demographic Characteristics and KAP Scores

Distribution of Responses to Knowledge, Attitude, and Practice

Within the knowledge domain, the items with the lowest correctness rates were: “Hepatitis B ‘big three positive’ is more harmful than ‘small three positive’” (K4) at 5.80%, “All primary liver cancers originate from chronic hepatitis B” (K9) at 11.23%, and “Liver function tests cannot indicate liver damage” (K10) at 28.52%. Regarding attitudes, 35.93% of respondents felt depressed, tense, or anxious about liver cancer and its treatment (A8), 31.11% were embarrassed to disclose their diagnosis publicly (A11), and 24.32% believed hepatitis B carriers only needed regular blood tests (A2). For practices, 8.64% of respondents always and 27.28% often forwent treatment due to high costs (P2). Additionally, 7.90% reported never avoiding shared tableware after a hepatitis B diagnosis (P9). Among reasons for not performing regular screening before liver cancer diagnosis (P11), 42.96% were unaware of HCC screening, 43.83% cited lack of symptoms, and 13.21% attributed it to insufficient advice from doctors (Table S1).

Correlations Between KAP

Correlation analysis showed significant positive relationships between knowledge and attitude (r = 0.445, P < 0.001), knowledge and practice (r = 0.342, P < 0.001), and attitude and practice (r = 0.477, P < 0.001) (Table S2).

Univariate and Multivariate Analysis

Using the top 70% of scores as the cut-off for each dimension, the number of participants above the cut-off was 298 (36.79%) for knowledge, 489 (60.37%) for attitude, and 629 (77.65%) for practice (Table S3). Multivariate logistic regression showed that with high school/technical school education (OR = 3.009, 95% CI: [1.577, 5.741], P = 0.001), with associate degree or above (OR = 6.771, 95% CI: [3.46, 13.251], P < 0.001), diagnosed with hepatitis B (OR = 1.530, 95% CI: [1.074, 2.178], P = 0.018), and suffered from liver cancer for 1–3 years (OR = 1.690, 95% CI: [1.072, 2.665], P = 0.024) were independently associated with good knowledge (Table 2). Concurrently, knowledge score (OR = 1.212, 95% CI: [1.154, 1.273], P < 0.001), with high school/technical school education (OR = 1.831, 95% CI: [1.005, 3.336], P = 0.048), with monthly per capita income of 10000–20000 yuan (OR = 2.964, 95% CI: [1.005, 8.737], P = 0.049), and with diabetes (OR = 2.031, 95% CI: [1.215, 3.395], P = 0.007) were independently associated with positive attitude (Table 3). In this analysis, “positive attitude” was defined according to the cutoff score range of 43–60 points, as specified in the Methods section. Moreover, knowledge score (OR = 1.067, 95% CI: [1.008, 1.131], P = 0.026), attitude score (OR = 1.241, 95% CI: [1.171, 1.314], P < 0.001), non-disclosure of monthly per capita income (OR = 3.311, 95% CI: [1.481, 7.404], P = 0.004), currently drink (OR = 0.303, 95% CI: [0.156, 0.590], P < 0.001), and with diabetes (OR = 2.175, 95% CI: [1.035, 4.568], P = 0.040) were independently associated with practice (Table 4). Diagnostic checks indicated no concerning multicollinearity across models (tolerance 0.574–0.971; VIF 1.029–1.743).

Table 2 Multivariate Logistic Regression Analysis for Knowledge

Table 3 Multivariate Logistic Regression Analysis for Attitude

Table 4 Multivariate Logistic Regression Analysis for Practice

SEM Analysis

The SEM model demonstrated good fit indices (CMIN/DF = 2.585, RMSEA = 0.044; IFI = 0.917; TLI = 0.909; CFI = 0.917) (Table S4). Results indicated that knowledge had a direct effect on attitude (β = 1.136, P < 0.001), while attitude directly influenced practice (β = 0.816, P < 0.001) (Table S5 and Figure 1).

Figure 1 SEM Path.

Discussion

Liver cancer patients and their family members demonstrated inadequate knowledge but relatively positive attitudes and proactive practices regarding hepatitis B and liver cancer in Chinese hospitals. Targeted educational interventions focusing on improving knowledge about hepatitis B and liver cancer are essential to strengthen attitudes and practices, which may enhance prevention, early detection, and management of these conditions. This apparent contradiction, where practices seem relatively proactive despite limited knowledge, may be explained by cultural and social factors. In China’s collectivist family structures, caregivers often enforce preventive and treatment behaviors on behalf of patients, and long-standing public health campaigns around hepatitis B and liver cancer may further encourage action even in the absence of deep understanding.

These findings are consistent with prior studies that have identified inadequate knowledge as a persistent issue that limits preventive efforts and contributes to poor health outcomes, such as delayed diagnoses and suboptimal compliance with medical recommendations.14,15 For instance, misconceptions surrounding hepatitis B transmission, progression to liver cancer, and the utility of liver function tests are prevalent globally and have been linked to inadequate screening and late-stage detection of liver cancer.16,17 The inadequate knowledge observed in this study underscores the need for tailored educational interventions to address these specific misconceptions, which likely hinder effective disease prevention and management. At the same time, the relatively positive attitudes and proactive practices suggest that, when knowledge gaps are addressed, there is a strong foundation upon which to build more effective health behaviors.

The relationships among the KAP dimensions were further clarified through correlation analyses and SEM, which showed that knowledge significantly influenced attitudes, and attitudes, in turn, had a direct and substantial impact on practices. This finding aligns with established health behavior models, which posit that knowledge serves as the foundation for shaping attitudes and motivating positive behaviors.18,19 However, the SEM results also revealed that knowledge alone did not have a direct effect on practices, emphasizing the critical mediating role of attitudes in transforming knowledge into action. This suggests that educational programs must go beyond simply disseminating information and instead focus on fostering supportive attitudes to drive meaningful behavioral changes. Similar conclusions have been drawn in studies of other chronic diseases, where interventions targeting attitudes—such as counseling and peer support—have been shown to significantly enhance adherence to preventive and treatment practices.20,21 The SEM fit indices (TLI and CFI > 0.80) are interpreted as acceptable given the model complexity, although stricter thresholds (≥0.90) are typically recommended, this discrepancy is acknowledged as a limitation.

Significant differences in KAP scores were observed across demographic and clinical variables, shedding light on factors influencing health behaviors in this population. Higher education levels were consistently associated with better knowledge and attitudes, as reflected in both the descriptive and multivariate analyses. For instance, participants with an associate degree or higher had markedly higher knowledge scores, a finding consistent with prior research that links higher education to greater health literacy and better access to health-related resources.22,23 Similarly, urban residents outperformed rural residents in both knowledge and practices, reflecting disparities in access to healthcare services and information. These results echo findings from other studies highlighting the urban-rural divide in health behaviors and outcomes,24,25 underscoring the urgent need for targeted interventions in underserved rural areas. Clinical factors such as a diagnosis of hepatitis B and liver cancer duration also significantly influenced knowledge, with those diagnosed with hepatitis B (OR = 1.530, P = 0.018) and those diagnosed with liver cancer for 1–3 years (OR = 1.690, P = 0.024) exhibiting higher scores. These findings suggest that direct exposure to healthcare systems and disease-specific information plays a key role in improving knowledge, although such benefits may not extend equally to attitudes and practices without additional support.

The distribution of responses in the knowledge dimension revealed specific areas of concern. Participants showed poor understanding of key concepts, such as the relative harm of “big three positive” versus “small three positive” hepatitis B statuses and the limitations of liver function tests. These gaps mirror findings in other studies that identified similar misconceptions as barriers to early diagnosis and treatment adherence.26,27 The attitude dimension also revealed notable challenges, including significant proportions of participants who reported anxiety, stigma, or embarrassment about their diagnosis. Such emotional barriers have been shown to hinder open communication and reduce engagement with healthcare services.28,29 In terms of practices, cost emerged as a significant barrier, with many participants forgoing treatments due to financial constraints. This finding aligns with evidence from other settings where high out-of-pocket expenses for liver cancer treatments were associated with lower adherence to medical recommendations.30,31 Interestingly, non-disclosure of income was positively associated with better practice scores in this study. This unexpected finding may reflect privacy concerns or cultural attitudes toward discussing finances, rather than a true socioeconomic effect. Such associations warrant further qualitative research to clarify underlying motivations.

These findings highlight several areas for intervention. Targeted educational programs should focus on addressing the most misunderstood aspects of hepatitis B and liver cancer, using culturally tailored approaches to reach both urban and rural populations. Community-based health promotion campaigns, delivered through local health workers and community leaders, could help bridge the urban-rural divide. Financial assistance mechanisms, such as expanded health insurance coverage and subsidies for screening and treatment, are critical to reducing cost barriers, particularly for lower-income groups. Psychological support services should be integrated into routine care to address anxiety and stigma, with peer support groups and counseling services playing a pivotal role in fostering positive attitudes. Interventions addressing substance use, including alcohol and smoking cessation programs, could further improve adherence to preventive and treatment practices. It should be noted that the observed negative association between alcohol consumption and practice scores should not be overinterpreted as causal. Rather, it may reflect broader lifestyle patterns or comorbid risk factors, and should be considered cautiously when informing intervention strategies. For family members, tailored workshops emphasizing their role in supporting patients and promoting regular follow-ups should be developed to strengthen family involvement. Ongoing monitoring and feedback systems, potentially leveraging digital tools such as mobile health apps, could provide patients and families with real-time reminders and educational resources, ensuring sustained improvements in health behaviors.32,33 Recent research among high-risk populations in China confirms that liver cancer screening practices remain low despite relatively positive attitudes, indicating that knowledge deficits are a persistent barrier.10 Moreover, trend analyses show that although age-standardized rates of liver cancer incidence and mortality have declined over time, the absolute numbers and burden remain high, particularly among males and rural populations, suggesting that socioeconomic and structural factors still exert a strong influence.34

This study has several limitations. First, as a cross-sectional survey, it cannot establish causal relationships between knowledge, attitudes, and practices, nor can it assess changes over time. Second, the study relied on self-reported data, which may be subject to social desirability bias, potentially overestimating positive attitudes and practices. Third, the study employed purposive sampling, relying on cooperative hospitals and personal networks for recruitment. This approach may limit the generalizability of the findings, as the participating hospitals could be relatively resource-rich or urban. Nevertheless, purposive sampling was deemed appropriate to ensure feasibility and secure multicenter participation across hepatobiliary surgery departments. Fourth, patients unaware of their diagnosis were excluded, whereas their family members were allowed to participate. This created a partial asymmetry in the dataset, as some family responses may reflect caregiving dynamics without corresponding patient data. However, this approach was ethically necessary to avoid breaching patient confidentiality. Analytically, family member data were treated as an independent but complementary perspective, and subgroup analyses of patients and family members were conducted separately to reduce potential bias from this asymmetry. Finally, the sampling was limited to hospitals in central and western China, which may affect the generalizability of the findings to other regions or healthcare settings. These limitations should be considered when interpreting the results.

Conclusions

In conclusion, liver cancer patients and their family members demonstrated inadequate knowledge but relatively positive attitudes and proactive practices regarding hepatitis B and liver cancer in hospitals in central and western China. This apparent knowledge–practice gap may reflect cultural norms, family involvement, or the influence of large-scale public health campaigns, suggesting that behavior change does not always require comprehensive understanding. Nevertheless, enhancing knowledge remains crucial, as it can consolidate positive attitudes and further reinforce sustainable practices. Targeted educational interventions should therefore be implemented in clinical and community settings to strengthen health literacy and reduce misconceptions, ultimately supporting more effective disease management and prevention. In particular, future interventions should be tailored to address urban–rural disparities and to actively involve family members in supporting patients with liver cancer. These findings also provide practical implications for policymakers and clinicians, including integrating health literacy promotion into routine care, prioritizing caregiver education, and designing programs that link counseling with affordable access to screening and treatment.

Data Sharing Statement

All data generated or analyzed during this study are included in this published article.

Ethics Approval and Consent to Participate

The study was approved by Ethic Committee of the First Affiliated Hospital of Army Medical University[(A) KY2023025]. All participants were informed about the study protocol and provided written informed consent to participate in the study. I confirm that all methods were performed in accordance with the relevant guidelines. All procedures were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.

Acknowledgments

Qingsong Deng, Ying Chen, and Minglian He are co-first authors for this study. We would like to express our gratitude to Jie Lin, Chao Xie, Jiwei Li, and Rui Zhao for their participation in some of the questionnaire surveys and collection work.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

The study was supported by National Natural Science Foundation of China (NO. 82073348). The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.

Disclosure

The authors declare that they have no competing interests in this work.

References

1. Razavi-Shearer D, Gamkrelidze I, Nguyen MH. Global prevalence, treatment, and prevention of hepatitis B virus infection in 2016: a modelling study. Lancet Gastroenterol Hepatol. 2018;3(6):383–403. doi:10.1016/s2468-1253(18)30056-6

2. Cooke GS, Andrieux-Meyer I, Applegate TL, et al. Accelerating the elimination of viral hepatitis: a lancet gastroenterology & hepatology commission. Lancet Gastroenterol Hepatol. 2019;4(2):135–184. doi:10.1016/s2468-1253(18)30270-x

3. Weinbaum CM, Williams I, Mast EE, et al. Recommendations for identification and public health management of persons with chronic hepatitis B virus infection. MMWR Recomm Rep. 2008;57(Rr–8):1–20.

4. World Health Organization. Hepatitis B fact sheet. WHO Newsroom. 2025. Available from: https://www.who.int/news-room/fact-sheets/detail/hepatitis-b. Accessed November07, 2025.

5. Wang FS, Fan JG, Zhang Z, Gao B, Wang HY. The global burden of liver disease: the major impact of China. Hepatology. 2014;60(6):2099–2108. doi:10.1002/hep.27406

6. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67(1):7–30. doi:10.3322/caac.21387

7. Han X, He L, Li S, Zhu Y. Trends in liver cancer rehabilitation needs, disease burden, and attributable risk factors in China, 1990–2021. Sci Rep. 2025;15(1):15682. doi:10.1038/s41598-025-00317-7

8. Kim S, Lee K, Kim S. Knowledge, attitude, confidence, and educational needs of palliative care in nurses caring for non-cancer patients: a cross-sectional, descriptive study. BMC Palliat Care. 2020;19(1):105. doi:10.1186/s12904-020-00581-6

9. Tan CK, Goh GB, Youn J, Yu JC, Singh S. Public awareness and knowledge of liver health and diseases in Singapore. J Gastroenterol Hepatol. 2021;36(8):2292–2302. doi:10.1111/jgh.15496

10. Feng G-H, Liu M, Chen Y-S, et al. Knowledge, attitudes, and practices of liver cancer screening among high-risk populations in China. BMC Public Health. 2025;25(1):2346. doi:10.1186/s12889-025-23582-7

11. Qin Y, Tang C, Li J, Gong J. Liver cancer in China: the analysis of mortality and burden of disease trends from 2008 to 2021. BMC Cancer. 2024;24(1):594. doi:10.1186/s12885-024-12334-2

12. Adjei VY, Mensah GI, Parry-Hanson Kunadu A, Tano-Debrah K, Ayi I, Addo KK. Microbial safety of beef along beef value chains in the ashaiman municipality of Ghana. Front Vet Sci. 2022;9:813422. doi:10.3389/fvets.2022.813422

13. Charan J, Biswas T. How to calculate sample size for different study designs in medical research? Indian J Psychol Med. 2013;35(2):121–126. doi:10.4103/0253-7176.116232

14. Abouzid MR, Kamel I, Elkhawas I, Rezk A, Esteghamati S, Nwaukwa CC. Health disparities in cardiac critical care: understanding inequities, barriers, and pathways toward equitable access and enhanced outcomes. Cureus. 2024;16(7):e64151. doi:10.7759/cureus.64151

15. Id El Haj N, Adnane M, Ziati J, El Kettani C, Haoudar A. Complex management of a migrating inhaled metallic foreign body in a child: a multidisciplinary success. Cureus. 2024;16(9):e70023. doi:10.7759/cureus.70023

16. Razavi-Shearer D, Gamkrelidze I, Pan C. Global prevalence, cascade of care, and prophylaxis coverage of hepatitis B in 2022: a modelling study. Lancet Gastroenterol Hepatol. 2023;8(10):879–907. doi:10.1016/s2468-1253(23)00197-8

17. Veronese P, Dodi I, Esposito S, Indolfi G. Prevention of vertical transmission of hepatitis B virus infection. World J Gastroenterol. 2021;27(26):4182–4193. doi:10.3748/wjg.v27.i26.4182

18. Ross A, Touchton-Leonard K, Perez A, Wehrlen L, Kazmi N, Gibbons S. Factors that influence health-promoting self-care in registered nurses: barriers and facilitators. ANS Adv Nurs Sci. 2019;42(4):358–373. doi:10.1097/ans.0000000000000274

19. Voorheis P, Bhuiya AR, Kuluski K, Pham Q, Petch J. Making sense of theories, models, and frameworks in digital health behavior change design: qualitative descriptive study. J Med Internet Res. 2023;25:e45095. doi:10.2196/45095

20. Collado-Mateo D, Lavín-Pérez AM, Peñacoba C, et al. Key factors associated with adherence to physical exercise in patients with chronic diseases and older adults: an umbrella review. Int J Environ Res Public Health. 2021;18(4):2023. doi:10.3390/ijerph18042023

21. Ho LLK, Li WHC, Cheung AT. Helping patients with chronic diseases quit smoking by understanding their risk perception, behaviour, and smoking-related attitudes. PLoS One. 2023;18(4):e0284690. doi:10.1371/journal.pone.0284690

22. Diogo PG, Pereira VH, Papa F, van der Vleuten C, Durning SJ, Sousa N. Semantic competence and prototypical verbalizations are associated with higher OSCE and global medical degree scores: a multi-theory pilot study on year 6 medical student verbalizations. Diagnosis. 2023;10(3):249–256. doi:10.1515/dx-2021-0048

23. Mutaru AM, Balegha AN, Kunsu R, Gbeti C. Knowledge and determinants of infection prevention and control compliance among nurses in Yendi municipality, Ghana. PLoS One. 2022;17(7):e0270508. doi:10.1371/journal.pone.0270508

24. Peterson L, Morgan ZJ, Andrilla CHA, et al. Academic achievement and competency in rural and urban family medicine residents. Fam Med. 2023;55(3):152–161. doi:10.22454/FamMed.2023.656489

25. Xu N, Zhang Y, Zhang X, et al. Knowledge, attitudes, and practices of urban residents toward COVID-19 in Shaanxi during the post-lockdown period. Front Public Health. 2021;9:659797. doi:10.3389/fpubh.2021.659797

26. Fanning GC, Zoulim F, Hou J, Bertoletti A. Therapeutic strategies for hepatitis B virus infection: towards a cure. Nat Rev Drug Discov. 2019;18(11):827–844. doi:10.1038/s41573-019-0037-0

27. Ogunnaike M, Das S, Raut SS, et al. Chronic hepatitis B infection: new approaches towards cure. Biomolecules. 2023;13(8):1208. doi:10.3390/biom13081208

28. Freeland C, Farrell S, Kumar P, et al. Common concerns, barriers to care, and the lived experience of individuals with hepatitis B: a qualitative study. BMC Public Health. 2021;21(1):1004. doi:10.1186/s12889-021-11093-0

29. Freeland C, Qureshi A, Wallace J, et al. Hepatitis B discrimination: global responses requiring global data. BMC Public Health. 2024;24(1):1575. doi:10.1186/s12889-024-18918-8

30. Bhat SA, Ahanger IA, Kazim SN. Forthcoming developments in models to study the hepatitis B virus replication cycle, pathogenesis, and pharmacological advancements. ACS Omega. 2023;8(16):14273–14289. doi:10.1021/acsomega.2c07154

31. Upala P, Apidechkul T, Tamornpark R, Chomchoei C, Yeemard F. Seroprevalence and factors associated with hepatitis B infection among the hill tribe adult population in Thailand: a cross-sectional study. BMC Infect Dis. 2020;20(1):494. doi:10.1186/s12879-020-05221-1

32. Kosasih M, Sendaydiego X, Bednarke K, et al. Prevalence and susceptibility to hepatitis B virus and the need for community health education in Milwaukee’s Hmong community. J Racial Ethn Health Disparities. 2022;9(5):1873–1881. doi:10.1007/s40615-021-01124-2

33. Liu Z, Lin C, Mao X, et al. Changing prevalence of chronic hepatitis B virus infection in China between 1973 and 2021: a systematic literature review and meta-analysis of 3740 studies and 231 million people. Gut. 2023;72(12):2354–2363. doi:10.1136/gutjnl-2023-330691

34. Zhan Z, Chen B, Huang R, et al. Long-term trends and future projections of liver cancer burden in China from 1990 to 2030. Sci Rep. 2025;15(1):13120. doi:10.1038/s41598-025-96615-1