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Development of a self-management behavior assessment scale for liver cancer patients from ethnic minorities

BMC Health Services Research volume 25, Article number: 315 (2025) Cite this article

Abstract

Background

Liver cancer poses significant health challenges worldwide, particularly for ethnic minority populations, who often face barriers such as cultural differences, limited health literacy, and inadequate access to healthcare, contributing to poorer self-management and treatment outcomes. Existing self-management tools do not adequately address the unique needs of ethnic minority liver cancer patients, necessitating the development of a culturally tailored assessment scale.

Methods

Grounded in the Health Belief Model, this study developed a self-management behavior assessment scale specifically for ethnic minority liver cancer patients. The scale was constructed using a comprehensive literature review, semi-structured qualitative interviews with 11 ethnic minority liver cancer patients, and two rounds of expert consultation via the Delphi method. The initial item pool was refined through expert input to ensure relevance and cultural sensitivity.

Results

Through literature review and semi-structured qualitative interviews with 11 ethnic minority liver cancer patients, four key dimensions were identified: health behavior management, disease perception and cognition, psychological and emotional regulation, and information acquisition and decision-making participation. These dimensions and items were further refined through two rounds of expert consultation using the Delphi method, ensuring the scale’s cultural relevance and content validity. As a result, a self-management behavior assessment scale was developed, consisting of four dimensions and 31 items tailored to the specific needs of ethnic minority liver cancer patients.

Conclusion

This newly developed scale provides a culturally sensitive tool to assess self-management behaviors in ethnic minority liver cancer patients. It has the potential to enhance patient care by identifying culturally specific barriers to effective self-management. Further research is needed to validate the scale’s reliability and applicability in broader patient populations.

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Introduction

Liver cancer is one of the leading causes of cancer-related morbidity and mortality globally. Its incidence continues to rise, particularly in developing countries [1, 2]. As indicated by data from the Global Cancer Report, liver cancer has become the third leading cause of cancer-related mortality worldwide in 2022 [3]. The majority of patients with liver cancer are diagnosed at an advanced stage, with an average life expectancy typically ranging from 6 to 12 months [4]. Even among patients who receive treatment at an early stage, the 5-year survival rate is below 50% to 70% [5]. Consequently, enhancing the quality of life and improving treatment outcomes for patients represent critical challenges in current management. Self-management is the process by which patients actively participate in the management of their health and treatment, encompassing behaviors aimed at maintaining physical health, adhering to medical advice, managing symptoms and side effects, and regulating psychological well-being. Studies have indicated that self-management behaviors play a significant role in prolonging the quality of life and increasing survival rates among patients [6, 7]. Ethnic minorities are defined in this paper as non-Han groups within China known for their distinctive cultures, languages, and traditional practices. Patient engagement in self-management is critical for recovery and long-term prognosis in liver cancer treatment [8]. However, many patients, especially those from ethnic minorities, encounter significant challenges due to cultural differences, limited awareness of effective disease management strategies, and a lack of knowledge about their condition [9, 10], which directly impacts their treatment adherence and physical and mental health [11]. These challenges are compounded by traditional beliefs about health and illness that may influence treatment decisions, leading to reduced treatment adherence and negative impacts on physical and mental health [12,13,14,15].

For instance, cultural practices pertaining to diet, traditional medicine, and health-seeking behaviors may serve as impediments to the effective self-management of health conditions. Ethnic minority patients may demonstrate a preference for traditional remedies over evidence-based treatments or may experience limitations in access to culturally appropriate health education [16], further complicating their ability to manage their illness. Such disparities are of critical importance, as they have been shown to contribute to increased incidence of complications during treatment, elevated psychological burdens, and reduced survival rates [17]. Therefore, the improvement of patient self-management capabilities represents a crucial element in the optimization of individual health outcomes and the reduction of healthcare expenditures [18].

Despite the crucial relevance of self-management in the rehabilitation of liver cancer patients, existing self-management scales, such as Self-Management Behavior Scale (SMBS) [19], Patient Activation Measure (PAM) [20], and Self-Care of Chronic Conditions Inventory II (SCCII) [21], have been widely applied in research on chronic diseases and general health behaviors. However, these scales are designed more for general assessment and lack attention to cultural sensitivity and disease-specific dimensions in self-management behaviors among liver cancer patients, especially among ethnic minority groups [22, 23]. Consequently, they fail to adequately account for the distinctive cultural and social backgrounds of ethnic minority patients. In these cases, there is a distinct absence of scales designed to systematically assess self-management behaviors. Furthermore, this may result in healthcare providers failing to take into account culturally specific factors that influence health behaviors. Accordingly, there is an urgent requirement for the development of a self-management behavior assessment scale that is tailored for ethnic minority liver cancer patients, which not only considers the distinctive health beliefs and practices of these communities, but also takes account of the psychological burdens associated with prolonged treatment [24,25,26]. This study aims to develop a self-management behavioral assessment scale for ethnic minority liver cancer patients (SMS-EMLC), therefore filling a critical gap in the literature and enhancing clinical nursing practice for this underserved population.

Materials and methods

Theoretical basis for the development of SMS-EMLC

In this study, the Health Belief Model (HBM) was employed as the theoretical framework for SMS-EMLC. The model was initially proposed by psychologists Rosenstock in the 1950s [27] to explain and predict the formation of individual health behaviors and the factors influencing them [28, 29]. The core dimensions of the model include perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, and cues to action, all of which shape an individual's decision to engage in preventive or therapeutic health behaviors. In recent years, the HBM has been widely used in health behavior research, providing theoretical guidance for self-management and health behavior interventions across various diseases [29,30,31]. For instance, the Health Belief Model Scale for Diabetic Patients, developed by Asiye Kartal, incorporates the dimensions of the HBM and effectively assesses patients' perceptions and behavioral choices about the disease, demonstrating strong reliability and validity [32].

This study, based on the HBM theoretical framework, combines literature review with semi-structured interviews to extract and integrate core dimensions of self-management behaviors into four key dimensions: health behavior management, disease cognition and perception, psychological and emotional management, and information acquisition and decision-making participation, and refine scale-specific items, which are further optimized in content and sequence through subsequent Delphi method expert consultations.

Literature research methodology

A comprehensive search was conducted across six databases (CNKI, VIP, Wan Fang, PubMed, Web of Science, Embase) using a multifaceted search strategy. This approach involved utilizing both subject terms and free words, as illustrated in Table 1 with PubMed as an example. The remaining databases were tailored according to the established principles of library searches. The temporal scope of the search extended from the inception of the library to September 2024. To ensure a complete search of the literature, the search did not include qualifiers for ethnic minorities. The group engaged in repeated discussions regarding the preliminary formulation of the scale entry pool in relation to the search results. During the literature screening process, two independent researchers were used to initially screen the literature by titles and abstracts, followed by full-text screening for documents that met the criteria. Disputes over the screening of documents were resolved through discussion or by involving a third-party expert to ensure the consistency of the screening results. In the data extraction phase, the two researchers independently extracted key information from the literature and recorded it using a standardized template to ensure the completeness and consistency of the information. Finally, all screened and extracted data were subjected to thematic analysis and synthesized into the construction of the scale items.

Table 1 Search strategy
Full size table

Qualitative research

This study employed qualitative interviews to conduct in-depth interviews with ethnic minority liver cancer patients with diverse characteristics. The objective was to gain in-depth insights into the self-management behaviors of ethnic minority liver cancer patients with diverse characteristics and the obstacles they encounter.

Inclusion criteria:

  1. i.

    Patients aged 18 years or older, diagnosed with liver cancer;

  2. ii.

    Patients from ethnic minorities;

  3. iii.

    Patients with basic Chinese communication skills;

  4. iv.

    Patients who have received or are receiving treatment;

  5. v.

    Patients who voluntarily participate in the study.

Exclusion Criteria:

  1. i.

    Patients with a combination of severe cognitive and psychiatric disorders;

  2. ii.

    Patients in an extremely critical stage of illness;

  3. iii.

    Patients who refuse to participate or withdraw.

The interview questions were designed based on the core dimensions of the HBM, covering aspects such as perceived severity, perceived susceptibility, perceived barriers and benefits, self-efficacy, and cues to action. Researchers used plain language during the interview process and confirmed the patients' understanding of the questions in real-time, ensuring that patients could respond accurately. The interviews were conducted in a quiet and private setting, and the objective and scope of the study were elucidated to the patients in advance. During the interview process, recordings are made on the principle of informed consent from the patient. Two researchers take on different roles: one focuses on communicating with the patient, ensuring that questions are asked clearly and are easy to understand; the other is responsible for recording the patient's body movements, facial expressions, and other non-verbal information to help better understand the patient's emotional responses and attitudes. The duration of the interview was limited to 30 min. Following the interview, the data was processed by the research team within 24 h using Nvivo 20. Thematic analysis was applied, and the data was coded by two independent researchers. The data was analyzed with strict adherence to the principle of data saturation to ensure that the information from the interviews is representative of self-management for the majority of ethnic minority liver cancer patients [33].

Expert Delphi method

The preliminary draft of the SMS-EMLC outlines the structure of the expert correspondence questionnaire. It comprises five sections: (a)An introductory section, which provides a description of the purpose and significance of the study. (b)A section on the background of the experts who responded to the questionnaire. This includes their names, genders, ages, academic qualifications, titles, years of experience, and fields of work. (c) The main of the questionnaire comprises the dimensions of the questionnaire, the specific items, the importance of the items, the inclusion indicators, the modifications of the items and the additional items. The importance of the items is rated on a 5-point Likert scale, with 'no' being scored 1, 'rarely' scored 2, 'sometimes' scored 3, 'often' scored 4 and 'always' scored 5. (d) Questionnaire on experts' familiarity with entries and basis for judgement. The Delphi method was conducted via email, and the information provided by experts is kept strictly confidential.

Criteria for inclusion of experts:

  1. i.

    Professional background in the field of liver cancer diagnosis and treatment, nursing, psychology or health management;

  2. ii.

    Minority background or at least 5 years working with minorities;

  3. iii.

    Bachelor degree or above;

  4. iv.

    Voluntary and able to actively co-operate in completing 2 rounds of correspondence.

Technology roadmap

The detailed flowchart is shown in Fig. 1.

Fig. 1
figure 1

The detailed flowchart

Full size image

Statistical analyses

The statistical analysis was conducted using SPSS 26 and Excel 2022. Descriptive statistics, including frequencies and percentages, were used to summarize the characteristics of interview subjects and experts. Four indicators were used to evaluate the entries, namely the degree of expert positivity, the degree of expert authority, the degree of expert opinion concentration, and the degree of expert opinion coordination. The screening criteria for scale entries were as follows: mean score > 4, coefficient of variation < 0.25, percentage of experts choosing 4 or 5 points > 80% [34], and exclusion of items with lower scores or significant disagreement based on statistical analysis.

Results

Qualitative study

General information about the interviewees

In this study, semi-structured interviews were conducted with ethnic minority liver cancer inpatients at a tertiary cancer hospital in Chengdu between August and September 2024, and data saturation was reached after 11 interviews. The demographic characteristics of these 11 patients are shown in Table 2.

Table 2 General information about the interviewees (n = 11)
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Qualitative research: the collation and analysis of results

Following the analysis of the interview data, four key dimensions were identified and refined: health behavior management, disease perception and cognition, psychological and emotional management and information acquisition and decision-making participation. Qualitative interviews revealed many specific needs of ethnic minority patients, such as the impact of traditional dietary habits on health management, the role of ethnic traditional activities in emotional regulation, and the contradiction between traditional medical beliefs and modern treatment advice. These findings were integrated into the scale items, making them more culturally adaptable and specific. These details are further elaborated in Table 3.

Table 3 Thematic extraction table of interview results for ethnic minority liver cancer patients (n = 11)
Full size table

The Delphi method of expert enquiry

General information on experts

Two rounds of expert correspondence were conducted in this study, and 13 experts participated, met the standard [35, 36]. The demographic information of the experts is provided in Table 4.

Table 4 General information about the experts (n = 13)
Full size table

Level of expert engagement

The return rate of questionnaires and the rate of expert input were used to assess expert engagement. In the first round of correspondence, 14 questionnaires were distributed, with 13 returned, resulting in a response rate of 92.8%. Nine experts provided feedback, giving an input rate of 69.2%. In the second round, 13 questionnaires were distributed, with 12 returned, yielding a response rate of 92.3%. Seven experts provided feedback, leading to an input rate of 58.3%. These figures indicate a relatively high level of expert engagement [37].

Level of expert authority

The coefficient of expert authority was used to indicate the degree of expert authority. The coefficient of familiarity of the experts in the first round of expert correspondence was 0.846, the coefficient of the basis of judgement was 0.976, the academic level was 0.876, and the coefficient of expert authority was 0.900. The coefficient of familiarity of the experts in the second round of expert correspondence was 0.867, the coefficient of the basis of judgement was 0.983, the academic level was 0.858 and the coefficient of expert authority was 0.903, which was a high level of expert authority [38].

Expert opinion consensus

The mean importance scores and ratios of 4 and 5 were used to measure the consensus of expert opinions. In Round 1, the mean importance scores for the scale dimensions ranged from 4.53 to 5.00, with 100% of scores between 4 and 5. For the scale items, mean importance scores ranged from 2.07 to 5.00, with 8% to 100% of scores between 4 and 5. In Round 2, the mean importance scores for the scale dimensions ranged from 4.58 to 5.00, with 100% of scores between 4 and 5, while the mean scores for the scale items ranged from 3.25 to 5.00, with 17% to 100% of scores between 4 and 5.

Level of expert opinion coordination

Kendall's Coefficient of Concordance (Kendall's W) and the coefficient of variation were used to assess the coordination of expert opinions. In Round 1, the coefficient of variation for the scale dimensions ranged from 0.00 to 0.11, with a Kendall's W value of 0.401 (P < 0.001). For the scale items, the coefficient of variation ranged from 0.00 to 0.11, with a Kendall's W value of 0.478 (P < 0.001). In Round 2, the coefficient of variation for the scale dimensions ranged from 0.00 to 0.11, with a Kendall's W value of 0.354 (P < 0.005). For the scale items, the coefficient of variation ranged from 0.00 to 0.19, with a Kendall's W value of 0.492 (P < 0.001).

Results of the first round of expert consultation

Based on the results from the first round of expert correspondence, the preliminary scale entries were adjusted and optimized. By combining the coefficient of variation and the expert selection rate, items with a mean score greater than 4 and a coefficient of variation less than 0.25 were selected for the second round of correspondence. Check supplementary material (Supplementary Table 1) for specific changes.

Discussion

The development of a self-management behavior scale specifically for ethnic minority liver cancer patients addresses a significant gap in both clinical practice and research. This study not only highlights the unique challenges faced by ethnic minority populations in managing liver cancer but also provides a culturally tailored tool to assess and enhance self-management behaviors. The scale’s integration of culturally specific elements, such as traditional health beliefs, national dietary practices, and decision-making dynamics, ensures its relevance and utility in improving healthcare delivery for underserved populations.

Implications for clinical practice and remote healthcare settings

In remote regions where ethnic minority populations often reside, access to comprehensive healthcare services is constrained by a number of factors, including geographical isolation, socioeconomic circumstances and healthcare resource limitations [39, 40]. The SMS-EMLC can be utilized as a valuable instrument by healthcare professionals to ascertain patients' particular requirements, even in the absence of substantial in-person interaction. The utilization of this scale permits local healthcare workers and community volunteers to conduct assessments during home visits or through telemedicine platforms [41,42,43], thereby facilitating continuous monitoring and support for liver cancer patients.

The feasibility of telehealth interventions is growing in remote regions as mobile network coverage expands [44]. The integration of the SMS-EMLC into telehealth platforms would facilitate patient and caregiver self-reporting of behaviors such as symptom management, adherence to dietary recommendations and emotional regulation. Remote healthcare providers enable to use this data to provide timely advice and interventions, thereby overcoming the limitations imposed by distance and limited healthcare infrastructure [45]. This approach not only empowers patients, but also facilitates improved access to personalized healthcare that is culturally and practically relevant to their lives.

Cultural sensitivity and tailored interventions

One of the most significant attributes of the SMS-EMLC is its cultural sensitivity [46], which acknowledges and addresses the distinctive health beliefs, customary practices, and social dynamics of ethnic minority liver cancer patients. For many ethnic minority groups, cultural beliefs regarding illness, traditional healing methods and dietary customs exert a considerable influence on their approach to disease management [47]. Without a culturally sensitive approach, healthcare interventions may fail to resonate with these patients, leading to lower adherence to treatment plans and poorer health outcomes.

By incorporating these culturally distinctive elements, the scale enables healthcare professionals to develop interventions that resonate with the patient's worldview, thereby enhancing the relevance and acceptability of care. This is of particular significance for ethnic minorities, for whom traditional medicine and culturally informed practices are often a primary focus, superseding conventional medical advice [16]. For instance, patients diagnosed with liver cancer from specific ethnic groups may opt for herbal remedies or adhere to particular dietary traditions that are thought to facilitate recovery. The scale enables healthcare professionals to identify such practices and collaborate with patients to achieve a balance between traditional beliefs and modern medical treatments, thereby enhancing adherence and improving outcomes.

Furthermore, developing a self-management scale specifically for this population is critical, as generalized scales often overlook the nuances of cultural differences. Ethnic minorities encounter specific obstacles to healthcare, including linguistic challenges, skepticism towards healthcare institutions, and a shortage of culturally sensitive care. A scale tailored to their specific needs ensures that these barriers are identified and addressed in a structured manner, facilitating more effective self-management strategies that resonate with their cultural context.

Improving patient engagement and self-efficacy

The empowerment of patients to assume an active role in their healthcare is a crucial element in the management of chronic diseases such as liver cancer. The scale emphasizes psychological and emotional management, focuses on decision-making participation, and has the potential to enhance patients' confidence and self-efficacy. For ethnic minority patients, who may already encounter numerous obstacles to accessing healthcare, fostering a sense of control over their own health is of particular importance. Such empowerment can help to mitigate feelings of helplessness or mistrust in the healthcare system, which are common among underserved populations [48].

Moreover, the scale's use in clinical practice can inform the development of health education programs that address the specific barriers to self-management faced by ethnic minority populations [49]. These programs can be designed to accommodate cultural preferences and literacy levels, ensuring that health information is accessible and actionable. In remote regions, this can make a significant difference in reducing healthcare disparities and improving patient outcomes [50, 51].

By identifying specific areas where patients lack confidence, such as managing symptoms, adhering to dietary recommendations, or balancing traditional and modern treatment methods, healthcare providers can offer targeted support. This not only enhances adherence but also furnishes patients with the competencies they require to assume control of their health in culturally congruent manners. Furthermore, insights derived from the scale can inform the development of health education programs that are tailored to the specific needs of ethnic minority patients [52], thereby ensuring that health information is both accessible and relevant to their cultural context.

Limitations and future research

A notable limitation of this study is that the newly developed SMS-EMLC has yet to undergo comprehensive reliability and validity testing. Although the scale was developed through qualitative research and expert consultations, it has yet to be empirically tested with larger or more diverse populations to establish its psychometric properties. Accordingly, further studies are required to assess the scale's internal consistency, test–retest reliability, and construct validity. Furthermore, it is recommended that future studies examine the scale's applicability to other populations. As this scale was developed with a specific focus on ethnic minority groups in China, it is essential to evaluate its suitability for application to liver cancer patients from other ethnic and racial backgrounds.

Conclusion

This study utilized the Health Belief Model to guide the development of a self-management behavior scale for liver cancer patients. Through a combination of literature review, qualitative interviews, and expert consultations, a four-dimension, 31-item scale specifically designed for ethnic minority liver cancer patients was constructed. While the scale demonstrates scientific rigor, reliability, and clinical applicability, further testing is required to refine its reliability and validity.

Data availability

The datasets used during the current study are available from the corresponding author on reasonable request.

Abbreviations

SMS-EMLC:

Self-management behavioral assessment scale for ethnic minority liver cancer patients

HBM:

Health Belief Model

SMBS:

Self-Management Behavior Scale

PAM:

Patient Activation Measure

SCCII:

Self-Care of Chronic Conditions Inventory II

References

  1. 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. Ca Cancer J Clin. 2024;74:229–63.

    Article  PubMed  Google Scholar 

  2. Shao S-Y, Hu Q-D, Wang M, Zhao X-Y, Wu W-T, Huang J-M, et al. Impact of national Human Development Index on liver cancer outcomes: Transition from 2008 to 2018. World J Gastroenterol. 2019;25:4749–63.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Deo SVS, Sharma J, Kumar S. GLOBOCAN 2020 Report on Global Cancer Burden: Challenges and Opportunities for Surgical Oncologists. Ann Surg Oncol. 2022;29:6497–500.

    Article  CAS  PubMed  Google Scholar 

  4. Yilma M, Houhong XuR, Saxena V, Muzzin M, Tucker L-Y, Lee J, et al. Survival Outcomes Among Patients With Hepatocellular Carcinoma in a Large Integrated US Health System. JAMA Netw Open. 2024;7: e2435066.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Sarveazad A, Agah S, Babahajian A, Amini N, Bahardoust M. Predictors of 5 year survival rate in hepatocellular carcinoma patients. J Res Med Sci. 2019;24:86.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Guo L, Li L, Lu Y, Li T, Chen L, Jiang L, et al. Effects of empowerment education on the self-management and self-efficacy of liver transplant patients: a randomized controlled trial. BMC Nurs. 2023;22:146.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Huang Y, Li S, Lu X, Chen W, Zhang Y. The Effect of Self-Management on Patients with Chronic Diseases: A Systematic Review and Meta-Analysis. Healthcare. 2024;12:2151.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Hanlon P, Daines L, Campbell C, McKinstry B, Weller D, Pinnock H. Telehealth Interventions to Support Self-Management of Long-Term Conditions: A Systematic Metareview of Diabetes, Heart Failure, Asthma, Chronic Obstructive Pulmonary Disease, and Cancer. J Med Internet Res. 2017;19: e172.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Zeng H, Yan PP, Tang GX, Liu Q, Liu FF, Zhou HM, et al. Diabetes knowledge and needs among prediabetic patients with different levels of self-management. J Cent South Univ (Med Sci). 2019;44:679–84.

    Google Scholar 

  10. Wu LX, Zhang Y, Meng LX, Liu L, Zhao T. Self-management status and influencing factors among elderly patients with comorbidities. Chin Gen Pract. 2024;27:2565–6.

    Google Scholar 

  11. Wang YX, Lin QL, Gan BH. Evaluation of the application effect of “Internet+” health coach technology in postoperative breast cancer patients. Chin Nurs Manag. 2023;23:1078–83.

    Google Scholar 

  12. Van Der Hout A, Van Uden-Kraan CF, Holtmaat K, Jansen F, Lissenberg-Witte BI, Nieuwenhuijzen GAP, et al. Role of eHealth application Oncokompas in supporting self-management of symptoms and health-related quality of life in cancer survivors: a randomised, controlled trial. Lancet Oncol. 2020;21:80–94.

    Article  PubMed  Google Scholar 

  13. Li R, Liang N, Bu F, Hesketh T. The Effectiveness of Self-Management of Hypertension in Adults Using Mobile Health: Systematic Review and Meta-Analysis. JMIR Mhealth Uhealth. 2020;8: e17776.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Borries TM, Dunbar A, Bhukhen A, Rismany J, Kilham J, Feinn R, et al. The impact of telemedicine on patient self-management processes and clinical outcomes for patients with Types I or II Diabetes Mellitus in the United States: A scoping review. Diabetes Metab Syndr. 2019;13:1353–7.

    Article  PubMed  Google Scholar 

  15. Jiang Y, Sun X, Jiang M, Min H, Wang J, Fu X, et al. Impact of a mobile health intervention based on multi-theory model of health behavior change on self-management in patients with differentiated thyroid cancer: protocol for a randomized controlled trial. Front Public Health. 2024;12:1327442.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Yu RF, Chen GH, Chen XY, Lai JQ, Huang Q, Yang LH, et al. Survey on the current status and development needs of evidence-based capacity in ethnic minority medicine. J Tradit Chin Med. 2024;65:1559–64.

    Google Scholar 

  17. Tan AJ, Tran C, Aliyev N, Rochling F, Sempokuya T. Survival Difference of Colorectal Adenocarcinoma Among Racial and Ethnic Minority Groups: A SEER Database Study. Hawaii J Health Soc Welf. 2024;83:279–85.

    PubMed  PubMed Central  Google Scholar 

  18. Sahely A, Sintler C, Soundy A, Rosewilliam S. Feasibility of a self-management intervention to improve mobility in the community after stroke (SIMS): A mixed-methods pilot study. PLoS ONE. 2024;19: e0286611.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Liang Z, Shi Y, Zhang Y, Zhang H, Zhuo Y, Lv N, et al. Influencing factors of self-management behavior among Chinese patients with chronic disease: A cross-sectional study. Public Health Nurs (Boston Mass). 2024. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/phn.13482.

  20. Hibbard JH, Stockard J, Mahoney ER, Tusler M. Development of the patient activation measure (PAM): conceptualizing and measuring activation in patients and consumers. Health Serv Res. 2004;39(4 Pt 1):1005–26.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Wu VX, Dong Y, Tan PC, Gan P, Zhang D, Chi Y, et al. Development of a community-based e-health program for older adults with chronic diseases: Pilot pre-post study. JMIR aging. 2022;5: e33118.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Chen Y, Lu M, Jia L. Psychometric properties of self-reported measures of self-management for chronic heart failure patients: a systematic review. Eur J Cardiovasc Nurs. 2023;22:758–64.

    Article  PubMed  Google Scholar 

  23. Eyles JP, Hunter DJ, Meneses SRF, Collins NJ, Dobson F, Lucas BR, et al. Instruments assessing attitudes toward or capability regarding self-management of osteoarthritis: a systematic review of measurement properties. Osteoarthritis Cartilage. 2017;25:1210–22.

    Article  CAS  PubMed  Google Scholar 

  24. Yu WH, Chi JJ, An R, Liang WN, Zhang XR, Tang JJ, et al. Research progress on self-management of young cancer patients. Nurs Res. 2022;36:4238–42.

    Google Scholar 

  25. Bond SM, Schumacher K, Dietrich MS, Wells N, Militsakh O, Murphy BA. Initial psychometric testing of the Head and Neck Cancer Patient Self-Management Inventory (HNC-PSMI). Eur J Oncol Nurs. 2020;47: 101751.

    Article  PubMed  Google Scholar 

  26. Wang W, Ding Y, Lu Q, Qi J, Zhang S. The development of a behaviour questionnaire for stoma self-management for persons with bladder cancer and an ileal conduit. J Adv Nurs. 2021;77:1085–95.

    Article  PubMed  Google Scholar 

  27. Rosenstock IM, Strecher VJ, Becker MH. Social learning theory and the Health Belief Model. Health Educ Q. 1988;15:175–83.

    Article  CAS  PubMed  Google Scholar 

  28. Ka C, Lk H. The relationship between the health belief model and compliance of persons with diabetes mellitus. Diabetes Care. 1980;3:594.

    Article  Google Scholar 

  29. Knight RA, Hay DA. The relevance of the health belief model to Australian smokers. Soc Sci Med. 1982;1989(28):1311–4.

    Google Scholar 

  30. Zhao YC, Zhao M, Song S. Online Health Information Seeking Among Patients With Chronic Conditions: Integrating the Health Belief Model and Social Support Theory. J Med Internet Res. 2022;24: e42447.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Khalil MIM, Ashour A, Shaala RS, Allam RM, Abdelaziz TM, Mousa EFS. Effect of health belief model-based educational intervention on prostate cancer prevention; knowledge, practices, and intentions. BMC Cancer. 2024;24:289.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Kartal A, Ozsoy SA. Validity and reliability study of the Turkish version of Health Belief Model Scale in diabetic patients. Int J Nurs Stud. 2007;44:1447–58.

    Article  PubMed  Google Scholar 

  33. Moore A, Leena N. An exploration of the emotional response among nurses in Bermuda, during the Covid-19 pandemic. PLoS ONE. 2024;19: e0279792.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Liao Q, Gui JY. Application progress of the Delphi method in nursing. Nurs Res. 2015;29:269–71.

    Google Scholar 

  35. Li YY, Chen WJ. Current application of the Delphi method in nursing management. Nurs Res. 2018;32:3339–41.

    Google Scholar 

  36. Ren Y, Li DD, Pan C, Shen S. Current application of the Delphi method in clinical pharmacy. Chin J Hosp Pharm Eval Anal. 2019;19:1525–7.

    Google Scholar 

  37. Qu JL, Zhu YX, Qu B. Application of the Delphi method in medical education research. Chin J Med Educ. 2019;39:227–30.

    Google Scholar 

  38. Wang XY, Wei N, Wang L. Construction of a scientific research integrity evaluation system for medical students from the perspective of scientific research education. Chin Med Educ Technol. 2022;36:617–23.

    Google Scholar 

  39. Liang B, Huang L, Chen Z, Hao B, Li C. Regional differences, dynamic evolution, and influencing factors of high-quality medical resources in China’s ethnic minority areas. Front Public Health. 2024;12:1436244.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Xu XM, Long Y, Zhang HF, Peng YH, Ma SS, Zhao L, et al. Awareness of core knowledge on chronic diseases and its influencing factors among Han and ethnic minority residents in Asbestos County. Mod Prev Med. 2024;51:1872–7.

    Google Scholar 

  41. Long H, Bartlett YK, Farmer AJ, French DP. Identifying Brief Message Content for Interventions Delivered via Mobile Devices to Improve Medication Adherence in People With Type 2 Diabetes Mellitus: A Rapid Systematic Review. J Med Internet Res. 2019;21: e10421.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Huang J, Han Y, Wei J, Liu X, Du Y, Yang L, et al. The effectiveness of the Internet-based self-management program for cancer-related fatigue patients: a systematic review and meta-analysis. Clin Rehabil. 2020;34:287–98.

    Article  PubMed  Google Scholar 

  43. Devan H, Farmery D, Peebles L, Grainger R. Evaluation of Self-Management Support Functions in Apps for People With Persistent Pain: Systematic Review. JMIR Mhealth Uhealth. 2019;7: e13080.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Chairuengjitjaras P, Nimmanterdwong Z, Petchlorlian A, Praditpornsilpa K, Tangkijvanich P. Exploring the Feasibility and Acceptability of a Telehealth Platform for Older Adults with Noncommunicable Diseases and Chronic Viral Hepatitis. Telemed J E Health. 2024. https://doiorg.publicaciones.saludcastillayleon.es/10.1089/tmj.2024.0289.

    Article  PubMed  Google Scholar 

  45. Pavlou M, Flavell CA, Gourtani FM, Nikitas C, Kikidis D, Bibas A, et al. Feasibility and acceptability of the HOLObalance telerehabilitation system compared with standard care for older adults at risk of falls: the HOLOBalance assessor blinded pilot randomised controlled study. Age Ageing. 2024;53:afae214.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Gomez Cardona L, Yang M, Seon Q, Karia M, Velupillai G, Noel V, et al. The methods of improving cultural sensitivity of depression scales for use among global indigenous populations: a systematic scoping review. Glob Ment Health (Cambridge, England). 2023;10:e83.

    Article  PubMed Central  Google Scholar 

  47. Yuan W, Fei X, Yuxin Z, Enhui Z, Jianqin Z, Yuxin HU, et al. Relationship between ethnic minority speciality diets and cardiovascular disease: based on the cohort study of natural populations living in ethnic minority aggregation areas in the southwest region. Chin Gen Pract. 2025;28:688.

  48. Sepulveda R, Chong J, Shegog R, Martin K, Begley C, Addy R, et al. Experiences of using the MINDSET Self-Management mobile health app among Hispanic Patients: Results of a qualitative study. Epilepsy Behav. 2024;153: 109702.

    Article  PubMed  Google Scholar 

  49. Holden CE, Wagland R, Harle A, Wheelwright S. The experiences and decision making of patients with incurable cancer and health literacy difficulties. PLoS ONE. 2024;19: e0309104.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Tian CY, Wong EL-Y, Qiu H, Zhao S, Wang K, Cheung AW-L, et al. Patient experience and satisfaction with shared decision-making: A cross-sectional study among outpatients. Patient Educ Couns. 2024;129:108410.

  51. B W, L B-F, M A, D L, As L. Shared decision making between community therapists and Latinx caregivers during evidence-based practice delivery in publicly-funded children’s mental health services. Patient education and counseling. 2023;115.

  52. Qin XX, Ma RL, Guo H, Zhang XH, Remina, Cao BY, et al. Evaluation of the effect of health education intervention on gallstones in rural Uyghur residents of the Xinjiang Production and Construction Corps. Chin J Public Health. 2023;39:86–91.

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Acknowledgements

The authors would like to express their sincere gratitude to all the participants involved in this study for their valuable time and insights. We also extend our thanks to the experts who contributed through the Delphi consultation process. Special thanks go to the research teams at the University of Electronic Science and Technology of China and Sichuan Cancer Hospital for their support throughout the study. This research was made possible by the funding from the Science and Technology Department of Sichuan Province (grant number 23KPZP0101). Finally, we appreciate the assistance provided by our colleagues and institutions in facilitating this research.

Funding

This work was supported by the Science and Technology Department of Sichuan Province (23KPZP0101), Sichuan.

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Author notes

  1. Beijia Liu and Jun Chen share first authorship.

Authors and Affiliations

  1. Department of Comprehensive Ward, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China

    Beijia Liu, Xue Zhao, Qian Gui & Ying Lin

  2. Department of Radiation Oncology, Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China

    Jun Chen, Bingrong He, Lijuan Feng & Yin Zhang

  3. Department of Hepatopancreatobiliary Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China

    Lixia Zhang & Meiling Liu

  4. Department of Nursing, The First People’s Hospital of Liangshan Yi Autonomous Prefecture, Xichang, China

    Anyun Yu

  5. Department of Comprehensive Ward, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China

    Xiaoli Tang

  6. Department of Radiation Oncology, Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China

    Guiyu Huang

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  1. Beijia Liu
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Contributions

BL and JC: Conceptualization, data collation, study design and manuscript writing. XZ, YL and QG: Literature review and data extraction. BH, LF and YZ: Semi-structured interviews and collation of qualitative research findings. AY, ML and LZ: Collation of expert correspondence and overall quality control (QC). XT and GH: Manuscript writing, overall QC and reviewing.

Corresponding authors

Correspondence to Xiaoli Tang or Guiyu Huang.

Ethics declarations

Ethics approval and consent to participate

This study has been approved by the Institutional Review Board of Sichuan Cancer Hospital (Ethical Approval Number: SCCHEC-02–2024-217). The study complied with local legal and institutional requirements. All patients signed an informed consent form when they participated in the study.

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Not applicable.

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The authors declare no competing interests.

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Liu, B., Chen, J., Zhao, X. et al. Development of a self-management behavior assessment scale for liver cancer patients from ethnic minorities. BMC Health Serv Res 25, 315 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12913-025-12272-0

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12913-025-12272-0

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BMC Health Services Research

ISSN: 1472-6963

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