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. 2024 Feb 23;103(8):e37272. doi: 10.1097/MD.0000000000037272

Emerging trends and patterns in healthcare-seeking behavior: A systematic review

Limin Li a, Li Fu a, Hui Li a, Tong Liu a, Jiangjie Sun a,b*,✉
PMCID: PMC11309724  PMID: 38394511

Abstract

Objectives:

The study of healthcare-seeking behavior is essential for optimizing resource allocation and improving healthcare services. Its complexity and diversity have made it a prominent research area. Understanding factors influencing healthcare-seeking decisions allows targeted interventions and policy development to address barriers and ensure equitable access to quality healthcare for diverse populations. Such research plays a vital role in enhancing healthcare outcomes and overall population health.

Methods:

The study utilized a systematic quantitative literature review approach, employing the Web of Science (WOS) Core Collection and PubMed databases as data sources. Additionally, bibliometric tools such as CiteSpace and VOSviewer were employed for analysis and visualization of the literature.

Results:

A comprehensive statistical analysis and visualization were performed on the annual publication volume, publication countries, journals, keywords, and keyword co-occurrence patterns up until 2023. Through this analysis, a framework was established, identifying the determinants and fundamental elements of healthcare-seeking behavior. These findings contribute to the advancement of research in this field and inform future studies and interventions aimed at improving healthcare-seeking behavior.

Conclusions:

Based on the aforementioned literature review and framework, several conclusions were drawn. The determinants that facilitate healthcare-seeking behavior include improving health education awareness, enhancing healthcare resources, reducing costs, and ensuring system soundness. Additionally, providing social environment support was found to be crucial. Furthermore, the fundamental elements of healthcare-seeking behavior were identified as healthcare demand, healthcare choices, and the process of diagnosis and treatment. These findings provide valuable insights for developing interventions and policies to promote optimal healthcare-seeking behavior.

Keywords: fundamental elements, healthcare-seeking behavior, systematic literature review, trends

1. Introduction

Medical sociologists regard healthcare-seeking behavior as a social behavior of individuals pursuing health, and the social relationship between individuals and doctors starts from the beginning of illness to the end of medical treatment.[1,2] The study of healthcare-seeking behavior can date back to the 1950s when the rise of medical sociology began. Medical Behavior initial research mainly focuses on the decision-making process of medical behavior, mainly in psychology and sociology research,[3,4] with time, medical behavior research content and research methods are also developing, involving clinical medicine,[5,6] economics,[7,8] public health,[9–11] and other disciplines, research content mainly involves the influencing factors of medical behavior,[12] different groups[13] or disease types[14,15] public medical characteristics, etc. The deep integration of Internet technology and the medical industry is an important direction for the development of the medical industry, and hospitals are moving towards interconnection, sharing, mobile, collaboration, and wisdom. The development of Internet medical treatment has promoted a change in traditional public healthcare-seeking behavior. In recent years, a large number of documents have been conducted on Internet medical treatment, online medical treatment,[16–19] and other aspects. There are still some gaps in the research hotspot and evolution trend of healthcare-seeking behavior in the English database, and no systematic quantitative literature review has been conducted to quantitatively evaluate the research on healthcare-seeking behavior. Our study comprehensively integrates a vast body of literature, analyzing key determinants of healthcare-seeking behavior, including socioeconomic factors, cultural backgrounds, gender disparities, health beliefs, and attitudes. We also emphasize the role of healthcare institutions and discuss factors influencing patient satisfaction and healthcare experiences. By understanding the driving factors and barriers of healthcare-seeking behavior, we can develop more effective health policies and interventions to improve the quality and accessibility of healthcare services.

2. Methods

2.1. Data sources

The literature used in this paper is derived from the Web of Science (WOS) core collection database and the Pub Med database. The WOS core data set was searched with (TS = (Medical-seeking behavior) OR TS = (Willingness to seek medical treatment)), article * or review * was refined, and the search period was before May 2023. The search results showed 160 related documents, and the literature samples were exported in RIS format. Using “Medical-seeking behavior or Willingness to seek medical treatment” as the search term, the search period was before May 2023, and the search results showed 251 related documents, and the literature samples were exported in Pub Med format. The exported documents (411) were imported into EndNote X9.3.3 for data cleaning, 87 duplicate documents were removed, and the related documents (324) were exported into RIS format. Figure 1 illustrates the collection process of literature data related to the topic of healthcare-seeking behavior. This work did not require ethical approval because it did not involve any human or animal research.

Figure 1.

Figure 1.

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The collection process of literature data related to the healthcare-seeking behavior theme.

2.2. Research methodology

Bibliometric analysis is used in a growing number of literature review papers in the social sciences and management fields, to quantify and map studies and to identify research gaps.[20] Bibliometric analysis is used as a set of analytical methods and procedures to identify lead authors and pioneering work, as well as to identify and map new research trends.[21] This study application CiteSpace 6.2.R2 software and VOSviewer 1.6.19 software in the field of annual publications, countries, journals, and keywords such as frequency statistical analysis, build keywords co-occurrence network and visual knowledge map, through the keywords and the detection of dynamic word mapping analysis reveals different topic evolution process, summarizes the existing research, research hotspot, and development trend, analysis the shortcomings in the field of medical behavior, aims to provide a reference for researchers further research, to better understand the public changes in crowd doctor-seeking behavior.

3. Results

3.1. Descriptive analysis

3.1.1. Annual publication volume and trend.

The number of publications in a field is an external indicator of the field. From the annual change in the number of publications, we can observe and grasp the development trends of the field. We tracked the evolution of publications on the topic of healthcare-seeking behavior as of May 2023. The cumulative time distribution of the medical-seeking behavior study is shown in Figure 2. The increasing number of published studies on healthcare-seeking behavior, particularly in recent times, reflects the growing academic awareness and interest in this topic.

Figure 2.

Figure 2.

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Cumulative time distribution of trend studies on medical behavior.

3.1.2. Geography of scientific production.

In terms of the geographical distribution of scientific achievements (as shown in Table 1), the United States has the highest number of publications, with 82 documents, followed by China (34), Australia (6), and the United Kingdom (5). This may reflect the attention and investment of these countries in the field of healthcare and medical research over the past few decades.

Table 1.

Leading countries in healthcare-seeking behavior (top 6).

Country N. Publications
USA 82
China 34
Australia 6
England 5
Canada 3
Japan 3
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3.1.3. Scientific outputs by journal.

Academic journals serve as important platforms for showcasing research achievements. Thomson Reuters defines Impact Factor (IF) as a measure of a journal influence, representing the number of citations received by articles published in that particular journal in a specific year.[22] It is an important tool for assessing the quality of research outcomes. Table 2 and Table 3 present the top 5 journals in terms of publication volume in Pub Med and WOS respectively, with a primary focus on the field of healthcare. Examples include “BMC Health Services Research” and “ACADEMIC MEDICINE.”

Table 2.

Number of research articles on healthcare-seeking behavior in PubMed TOP5 journals and number of articles.

Sequence Journal name Number of publications Impact factor JCR quartile in category
1 BMC Health Services Research 5 3.647 Q3
2 International Journal of Environmental Research and Public Health 4 4.614 Q1
3 Plos One 4 3.752 Q2
4 BMJ Open 3 7.09 Q1
5 Journal of Community Health 3 4.37 Q2
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Table 3.

Number of research articles on healthcare-seeking behavior in WOS TOP5 journals and number of articles.

Sequence Journal name Number of publications Impact factor JCR quartile in category
1 BMJ Open 5 7.09 Q1
2 Academic Medicine 3 7.84 Q1
3 Bioethics 3 2.512 Q2
4 International Journal of Environmental Research and Public Health 3 4.614 Q1
5 Medical Decision Making 3 2.749 Q3
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WOS = Web of Science.

3.2. Quantitative analysis

3.2.1. Citation analysis.

Total citation frequency is a crucial indicator for assessing the quality and significance of an article. Analyzing citation frequency helps identify the most influential papers in a research field.[23] Highly cited articles represent recognition within the academic community and have a significant impact on the development of the field. Table 4 presents the top 10 most cited articles in the field of healthcare-seeking behavior.

Table 4.

The cited TOP10 articles in the field of healthcare-seeking behavior.

Sequence Title of article Journal name Author Citations
1 How patients’ trust relates to their involvement in medical care Journal of Family Practice Trachtenberg (2005) 148
2 How the relationship between attitudes toward mental health treatment and service use differs by age, gender, ethnicity/race and education Social Psychiatry and Psychiatric Epidemiology Gonzalez (2011) 94
3 Pattern of medical waste management: existing scenario in Dhaka City, Bangladesh BMC Public Health Hassan (2008) 77
4 Internet Hospitals Help Prevent and Control the Epidemic of COVID-19 in China: Multicenter User Profiling Study Journal of Medical Internet Research Gong (2020) 76
5 Decision-making about seeking medical advice in an internet sample of women trying to get pregnant Human Reproduction Bunting (2007) 75
6 Animal models in urological disease and sexual dysfunction British Journal of Pharmacology McMurray (2006) 73
7 Misconceptions and the Acceptance of Evidence-based Nonsurgical Interventions for Knee Osteoarthritis. A Qualitative Study Clinical Orthopaedics and Related Research Bunzli (2019) 68
8 A comparison of the direct costs and cost effectiveness of serotonin reuptake inhibitors and associated adverse drug reactions
CNS drugs		 Sullivan (2004) 66
9 Negative Attitudes Toward Help Seeking for Mental Illness in 2 Population-Based Surveys From the United States and Canada Canadian Journal of Psychiatry-Revue Canadienne De Psychiatrie Jagdeo (2009) 65
10 Surrogate Decision Makers’ Responses to Physicians’ Predictions of Medical Futility
CHEST		 Zier
(2009)		 65
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3.2.2. Keywords co-occurrence analysis.

Keyword analysis helps us gain a deeper understanding of research preferences and focuses within a specific field. By using CiteSpace and VOSviewer software to visualize keywords extracted from the WOS and Pub Med datasets, we can obtain the results shown in Figures 3 and 4. From these figures, we can observe several high-frequency keywords, such as “middle-aged,” “surveys and questionnaires,” “cross-sectional studies,” “young adult,” “general & and internal medicine,” and “public health.” These keywords appear frequently in the literature. It can be inferred that research on healthcare-seeking behavior primarily employs survey questionnaires and cross-sectional studies as research methods. The research content predominantly focuses on public health and healthcare quality. The target population of these studies is mainly middle-aged and young adult individuals.

Figure 3.

Figure 3.

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builds a visual atlas based on CiteSpace extraction keywords.

Figure 4.

Figure 4.

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builds a visual atlas based on VOSviewer extraction keywords.

3.2.3. Tracking central keywords.

Through temporal and spatial burst analysis of core keywords related to healthcare-seeking behavior in the literature, it is possible to accurately identify research hotspots and temporal-spatial evolution patterns in the field.[24] Figures 5 and 6 depict the dynamic development of keywords in the healthcare-seeking behavior field in recent years. Here is an academic description of these figures:

Figure 5.

Figure 5.

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A spatiotemporal emergent analysis of the keywords.

Figure 6.

Figure 6.

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Dynamic co-word map for central keywords detection.

During the period from 2010 to 2012, “attitude to health” and “attitude of health personnel” emerged as key keywords in the field of healthcare-seeking behavior. This indicates that public attitudes play a dominant role in research on healthcare-seeking behavior.

From 2012 to 2014, “young adult” became a key keyword in this field, indicating a focus on healthcare-seeking behavior among the young adult population.

From 2014 to 2016, “surveys and questionnaires” and “qualitative research” emerged as dominant keywords. This suggests that research methods primarily focused on survey questionnaires and qualitative studies.

During the period from 2016 to 2018, the frequency of keywords such as “prevalence” and “health care science & and service” gradually increased in the literature. This period likely emphasized research on healthcare-seeking behavior prevalence and healthcare science and services.

Since 2018, relevant literature in this field has primarily revolved around “public health,” “mental health,” “infant,” and “general & and internal medicine.” This indicates a recent research focus on public health, mental health, infants, and general internal medicine within the field of healthcare-seeking behavior.

These keyword-tracking analysis results provide valuable information on the dynamic changes in research hotspots within the field. They enable researchers to gain a deeper understanding of the development trends and key areas of focus in the field of healthcare-seeking behavior.

4. A framework of healthcare-seeking behavior

Through a comprehensive review of relevant literature, we categorize healthcare-seeking behavior into 2 aspects: Antecedents of promoting medical treatment, and The basic elements of medical treatment. Our article presents a comprehensive framework (as shown in Fig. 7) to enhance understanding of the fundamental elements and processes in healthcare-seeking behavior. This framework not only facilitates the scientific conduct of healthcare activities but also improves the efficiency and effectiveness of healthcare delivery, ultimately better serving the health needs of the population. By aiding clinicians in comprehending patients’ healthcare needs more deeply, it plays a crucial role in fostering strong doctor-patient relationships and enhancing the overall effectiveness of clinical diagnostics and treatment practices.

Figure 7.

Figure 7.

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The framework of antecedents-basic elements of healthcare-seeking behavior.

The first aspect, facilitating factors for seeking healthcare, encompasses factors that encourage individuals to seek medical services. These factors include personal factors such as the perceived need for medical services, personal beliefs and attitudes towards healthcare, and awareness of available healthcare services. Social factors, such as social support networks, cultural norms, and socioeconomic status, also play a crucial role in promoting healthcare-seeking behavior. Additionally, healthcare system factors, including accessibility, affordability, and quality of healthcare services, influence individuals’ decisions to seek medical care.

The second aspect, essential elements of healthcare-seeking, refers to the key components involved in the process of seeking medical services. This includes recognizing symptoms or health problems, seeking information about available medical options, selecting healthcare providers, making appointments or visiting healthcare facilities, receiving appropriate diagnosis and treatment, and engaging in follow-up medical actions. Each element influences the entire healthcare-seeking behavior and affects the outcomes of the healthcare process.

By adopting this framework, researchers and healthcare professionals can gain a better understanding of the multifaceted nature of healthcare-seeking behavior and design interventions and strategies to improve accessibility, utilization, and effectiveness of healthcare. Furthermore, policymakers can utilize this framework to identify gaps and barriers in healthcare service delivery and implement effective policy measures to address these issues.

4.1. Factors promoting healthcare seeking

When delving into the factors that promote healthcare seeking, several aspects need to be considered, including raising the awareness of health education, improvement in healthcare resources, cost reduction and a sound system, and social environment support.

4.1.1. Raise the awareness of health education.

The improvement in health education and awareness plays a crucial role in promoting public understanding of their health issues and how to maintain good health. In a study by Otiashvili[4] that involved in-depth interviews with 55 substance-using women and 34 healthcare providers, it was revealed that low self-esteem, coupled with significant familial and societal stigma in the Orthodox society of Georgia, hindered women from seeking medication or medical help. Therefore, there is an urgent need to educate the public, including policymakers and healthcare providers. Lee[25] suggested that situational learning and health knowledge engagement have a positive impact on health communication. Negative framing effects and engagement with health knowledge also influence patients’ willingness to seek medical help. Furthermore, situational learning and engagement with health knowledge impact the willingness to seek medical help through communication factors. Egube[26] recommended healthcare providers offer more health education to pregnant women regarding neonatal jaundice during antenatal care visits. Torres[27] demonstrated through a randomized clinical trial that physician-led information dissemination activities effectively increased COVID-19 knowledge, information-seeking behavior, and self-reported protective behaviors among different population groups. Large-scale implementation studies are needed to confirm clinical significance.

4.1.2. Improvement in healthcare resources.

Improvement and accessibility of healthcare resources constitute a comprehensive issue. Challenges such as the supply-demand imbalance of healthcare resources, unequal distribution of healthcare resources, and insufficient quality of medical practitioners need to be addressed. Zhang,[28] through a cross-sectional survey conducted in Wuhan, found that the goal of community health services, namely, “treating minor illnesses in the community and treating severe diseases in hospitals,” has not been fully achieved. Porteous[29] in an experiment exploring the public preference for attributes of community pharmacies, highlighted that the attributes of community pharmacies and their staff may influence people decisions on where to seek treatment and advice for minor ailments. Gong,[16] in their study on the role of internet hospitals in the prevention and control of COVID-19 in China, found that internet hospitals can serve various types of consultation needs during epidemic outbreaks.

4.1.3. Cost reduction and a sound system.

The high cost of medical care is a significant factor influencing people healthcare-seeking behaviors. Particularly for individuals in impoverished areas, medical expenses can become an overwhelming burden. Stephen[30] discussed whether uterine transplantation technology should be subsidized by the government. Danis,[31] in exploring the public and physicians’ attitudes toward insurance coverage and out-of-pocket costs, found that the trust relationship between patients and healthcare providers may be more beneficial in facilitating discussions on healthcare costs than specific discussion strategies. Won,[32] through a discrete choice experiment investigating cancer patients’ preferences for different types of healthcare payment, can help develop patient-centered healthcare models. Li,[33] in a modeling study on the applicability and cost-effectiveness of the Systolic Blood Pressure Intervention Trial (SPRINT) in the Chinese population, concluded that SPRINT has the potential to prevent cardiovascular disease events, generate gains in quality-adjusted life years, and is cost-effective at commonly accepted thresholds.

4.1.4. Social environment support.

Aspects such as culture, beliefs, socio-economic status, family, and social support have an impact on healthcare-seeking behaviors. Chandra[3] found that racial/ethnic disparities in knowledge about depression treatment still exist but are more pronounced among parents than adolescents. Conversations between parents who have more knowledge about depression treatment and adolescents are associated with greater knowledge and a higher willingness to seek treatment for depression. Moyehodie[34] revealed that both individual and community-level factors are important predictors of community-based health insurance enrollment in families. Park[35] emphasized the importance of considering shared cultural beliefs and stigma within ethnic communities when addressing mental health issues and promoting the use of mental health services. Given the mistrust in the biomedical model of depression and family shame, fostering mental health literacy among elderly immigrants may be beneficial.

4.2. Essential elements of healthcare

When exploring the essential elements of healthcare in-depth, several aspects need to be taken into consideration: healthcare demand, healthcare choice, and healthcare diagnosis and treatment. Through understanding and analyzing these fundamental elements of healthcare, it is possible to gain better insights into the various stages of the healthcare process, improve the efficiency and effectiveness of healthcare, and better serve the healthcare needs of the population.

4.2.1. Healthcare demand.

Healthcare demand arises when individuals experience physical or psychological discomfort and seek medical attention. This demand can motivate individuals to proactively seek healthcare, but it can also be influenced by other factors that may delay or hinder the process. In a study by Dardas,[36] school-based interventions were shown to meet the critical service needs of adolescents with depression and other mental health issues. Utilizing school nurses and counselors can address the mental health concerns of this vulnerable group. Nakagawa[37] found that most young people tend to opt for early decompressive craniectomy following a large-scale ischemic stroke. Interestingly, Moritz[17] discovered a paradox where individuals with depression are least motivated to seek face-to-face treatment when they need help the most. Chen[38] revealed that aging, lack of health insurance, and a lack of annual eye exams are barriers for cataract patients seeking cataract surgery.

4.2.2. Healthcare choice.

Healthcare choice refers to the decision-making process individuals go through when selecting from multiple healthcare options, including the type of medical services, healthcare institutions, and healthcare providers. People healthcare choices can be influenced by various factors, such as the severity of the illness, personal preferences, geographical location, reputation of healthcare institutions, and coverage provided by healthcare insurance. Accessibility to healthcare facilities is crucial for the elderly, as highlighted by Li.[39] It is important to consider elderly individuals with lower levels of education, those who cannot travel independently, and those residing far from city centers when planning future healthcare facilities. Liu[40] found a significant decrease in the willingness rate for initial visits to primary healthcare services compared to the policy recommendations proposed by the Chinese State Council. Hence, the government should develop strategies to promote the implementation of a tiered diagnosis and treatment system.

4.2.3. Healthcare diagnosis and treatment.

A reliable healthcare diagnosis and effective treatment contribute to improving the quality and safety of medical services, thereby boosting people confidence and motivation to seek treatment at hospitals. In a study by Zooro[41] examining whether patients would consider telemedicine as a means of seeking pelvic floor physical therapy care, it was concluded that providing patients with face-to-face visits or mixed alternative options may be the best choice to enhance treatment adherence, especially when considering access to care. Plummer,[42] in a qualitative case study on factors influencing pain communication during pediatric hematopoietic stem cell transplantation, emphasized the need for child-centered approaches to support children in expressing their pain experiences and overcoming the complexities and limitations of the clinical environment. Todd[43] highlighted the necessity of establishing strategies that discourage the use of certain prescriptions for patients with life-limiting illnesses. These strategies should aim to establish patient expectations, consider the timing of discussions about discontinuing treatment, and encourage the involvement of other stakeholders in the decision-making process. Bunzli[5] pointed out that common misconceptions about knee osteoarthritis seem to impact patients’ acceptance of non-surgical, evidence-based treatments such as exercise and weight loss.

5. Discussion, conclusion, and future research

Building upon the systematic quantitative literature review, several research directions have been identified. Table 5 explains these research directions and presents unresolved issues in the field of healthcare behavior. The table offers a preliminary list of key research gaps and questions, but it is not comprehensive. Considering that the field of healthcare behavior research is still in its early stages, there are still research gaps and unresolved issues.

Table 5.

Research directions on healthcare-seeking behavior.

Research directions Research questions

Antecedents of promoting healthcare-seeking behavior		 Q1: There are still uncertainties regarding the mechanisms for cultivating health consciousness. How can we further explore methods to cultivate health consciousness?
Q2: How can we promote medical technology innovation, and how do the outcomes of medical technology innovation contribute to the improvement and optimization of healthcare resource allocation?
Q3: How can we optimize healthcare measures for the elderly in a highly developed healthcare informatization context? Is it possible to establish a healthcare insurance system tailored to the needs of the elderly?
Q4: How do different cultural backgrounds or social support influence individuals’ healthcare willingness and behavior?
The basic elements of healthcare-seeking behavior Q5: How can we measure the impact of digital technologies on healthcare demand, and how can we enhance the quality and accessibility of digital healthcare services?
Q6: How to improve the transparency and openness of healthcare service information, as well as enhance individuals’ decision-making abilities and safeguard their rights in healthcare choices.?
Q7: How can we gain a deeper understanding of the impact of individual differences on the diagnosis and treatment of diseases, and how can we offer more personalized healthcare services?
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Regarding the factors influencing healthcare utilization, we have conducted research and exploration in the following areas: raising awareness of health education, improvement in healthcare resources, cost reduction and a sound system, and social environment support. Firstly, the theory of knowledge, beliefs, and actions is one of the most commonly used models to explain the influence and changes in individuals’ health behaviors based on their health knowledge and beliefs. This model helps individuals change their health beliefs, establish a health knowledge system, and foster positive health beliefs.[44] By enhancing health education and awareness, we can influence people healthcare-seeking behaviors at the conscious level. For instance, Lee[45] explored the impact of health knowledge engagement on health communication by collecting and analyzing data from patients who used online doctor blogs or engaged in discussions with doctors about medical information on the blogs. Although there is a considerable amount of research on the impact of health education and awareness on relevant health outcomes, as well as practical experiences and theoretical studies in this area, there is relatively less research on the cultivation of health education and health knowledge. Future research should focus on improving the mechanisms for cultivating health awareness, exploring effective ways to disseminate health information, and designing and evaluating health education strategies and interventions to promote changes in individual health behaviors. Additionally, research should address the influence of individuals’ health knowledge and beliefs on healthcare choices and medical behaviors, while leveraging digital technologies to enhance individuals’ health knowledge and decision-making abilities. Therefore, an important direction for future research is:

(Q1) There are still uncertainties regarding the mechanisms for cultivating health consciousness. How can we further explore methods to cultivate health consciousness?

Secondly, with the development of technology, treatment methods, and healthcare facilities in the medical field are constantly being updated. The widespread availability and improvement of medical resources greatly enhance the accessibility of healthcare for individuals[46,47] and influence their willingness to seek medical treatment.[19,28] For example, van Veen aimed to determine the readiness for using mobile healthcare technology in underserved communities and found a great potential and willingness to use mobile healthcare technology in medical triage. Currently, research on medical resources mainly focuses on resource allocation, individuals’ willingness to seek medical treatment, and convenience aspects, while there is less research on the innovation aspect of medical technology. Future research should focus on promoting innovation in medical technology and explore in depth how medical technology innovation can facilitate the allocation of healthcare resources. This will help improve the quality and efficiency of healthcare services and enhance people healthcare experiences. Therefore, an important direction for future research is:

(Q2) How can we promote medical technology innovation, and how do the outcomes of medical technology innovation contribute to the improvement and optimization of healthcare resource allocation?

Thirdly, establishing a sound healthcare system and gradually promoting the universalization of medical insurance, along with providing appropriate subsidies for patients, are important means to facilitate healthcare seeking. The increasingly improved healthcare system reduces the economic burden of illness for individuals[8,48,49] and also contributes to the sustainable development of the healthcare system to some extent.[50,51] Future research should focus on how to optimize healthcare security measures for the elderly and establish a suitable healthcare insurance system for them in the context of highly developed medical informatics. This will provide the elderly with more comprehensive and sustainable healthcare security, promoting their health and well-being. It is also an important measure to address the challenges of population aging and contributes to the advancement of social health. Therefore, an important direction for future research is:

(Q3) How can we optimize healthcare measures for the elderly in a highly developed healthcare informatization context? Is it possible to establish a healthcare insurance system tailored to the needs of the elderly?

Fourthly, the influence of social and cultural backgrounds and interpersonal relationships on healthcare-seeking behavior is multifaceted, involving factors such as personal beliefs, values, social influence, and resource support. The social and cultural backgrounds of different countries or regions to some extent facilitate or hinder people seeking healthcare,[4,13,52] and the beliefs of different groups significantly impact individuals’ healthcare behavior or willingness to seek healthcare.[53,54] For example, Dube,[55] in analyzing HIV cure-related research on treatment interruptions, added considerations for race, ethnicity, gender, and gender diversity, aiming to derive a triadic perspective on the social and ethical impacts of analytical treatment interruptions (ATIs) in underrepresented populations and partner protection strategies during ATIs. Different cultural backgrounds and social customs have significant influences on healthcare-seeking behavior and health beliefs. There is extensive research on healthcare-seeking behavior in different sociocultural backgrounds in foreign countries. However, in domestic research, there is relatively less exploration of healthcare-seeking behavior and health beliefs in different cultural backgrounds. Future research should focus on the attitudes, values, and interactions with the healthcare system among different cultural groups. Studies can examine the influence of cultural differences on healthcare decision-making, doctor-patient relationships, disease diagnosis, treatment choices, and other aspects, thus guiding the development of healthcare policies and services tailored to different cultural backgrounds. Therefore, an important research direction for the future is:

(Q4) How do different cultural backgrounds or social support influence individuals’ healthcare willingness and behavior?

Regarding the fundamental elements of healthcare-seeking, we have conducted research and exploration in the following aspects: healthcare demand, healthcare choice, and healthcare diagnosis and treatment. Firstly, healthcare demand refers to the willingness and ability of individuals or society to seek medical services for a certain health issue, closely related to individual health status and the effectiveness, efficiency, and fairness of the healthcare system. Individual health status is a crucial factor in generating healthcare demand among the public,[56,57] where the more severe the individual health problem or the more noticeable the symptoms, the more urgent the healthcare demand. Economic status often acts as a barrier to the transformation of healthcare demand into healthcare utilization,[58] as financial difficulties may prevent individuals from affording medical expenses or lead to delayed healthcare-seeking. Additionally, the effectiveness, fairness, and rationality of the healthcare system also influence people healthcare demand,[59] as an efficient, equitable, and trustworthy healthcare system can encourage individuals to actively seek medical services. With the rapid development of digital technology, healthcare demand is gradually undergoing a digital transformation. Digital technology is increasingly applied in the field of healthcare, such as electronic medical records, telemedicine, and health mobile applications, among others. The introduction of these technologies provides patients with more convenient and efficient ways of seeking healthcare, enhancing the accessibility and quality of healthcare services. Future research needs to focus on the impact of digital technology on healthcare demand and explore how to further improve the quality and accessibility of digital healthcare services. Therefore, an important research direction for the future is:

(Q5) How can we measure the impact of digital technologies on healthcare demand, and how can we enhance the quality and accessibility of digital healthcare services?

Secondly, healthcare choice refers to the decision-making process individuals undertake when faced with multiple healthcare options. Patients need to consider various factors such as the professionalism of healthcare institutions, geographic location, and the qualifications and experience of doctors. During the healthcare choice process, individuals often face information asymmetry, where healthcare service providers possess more information than individuals, leaving them with insufficient information to make informed decisions.[60] To improve the transparency and accessibility of healthcare service information, several key research directions deserve exploration. Firstly, it is necessary to develop and promote applicable information technology tools and platforms that provide relevant information about healthcare services. Secondly, the construction of healthcare service evaluation and regulatory systems should be strengthened to ensure quality and safety. Furthermore, the protection of healthcare consumers’ rights should be enhanced to promote fair competition and information disclosure, safeguarding individuals’ rights to be informed and to choose during healthcare selection. In summary, to enhance individuals’ decision-making capabilities and safeguard their rights in healthcare choices, future research should focus on improving the transparency and accessibility of healthcare service information. Therefore, an important research direction for the future is:

(Q6) How to improve the transparency and openness of healthcare service information, as well as enhance individuals’ decision-making abilities and safeguard their rights in healthcare choices?

Thirdly, healthcare diagnosis and treatment are crucial steps in achieving a cure or alleviating the symptoms of a disease. With the continuous advancement of medical technology, there is increasing research focus on providing personalized diagnostic and treatment plans for each individual.[61–63] In this research field, it is necessary to delve into the sources of individual differences, such as genetic inheritance, environmental factors, and lifestyle, and their impact on disease progression and treatment response. Additionally, efforts should be made to strengthen data collection and sharing, establish collaborative research networks across institutions and countries to expand sample sizes, and increase the reliability of studies. To provide more personalized healthcare services, the development and application of clinical decision support systems should be enhanced. Furthermore, techniques such as artificial intelligence and machine learning can be employed to analyze and mine large amounts of clinical data, uncover patterns and correlations hidden within the data, and provide support for individualized diagnosis and treatment. Therefore, an important research direction for the future is:

(Q7) How can we gain a deeper understanding of the impact of individual differences on the diagnosis and treatment of diseases, and how can we offer more personalized healthcare services?

6. Limitations

The use of the WOS and Pub Med databases for a quantitative literature review of healthcare behaviors, along with analysis and visualization using tools like VOSviewer and CiteSpace, can provide researchers with a comprehensive understanding and insights into the field. However, this approach also has certain limitations.

Firstly, although the WOS and Pub Med databases are widely used literature databases, their coverage is still limited. These databases mainly cover English literature, and there may be relatively fewer inclusions of literature in other languages or specific regions. This could lead to some bias in the research on healthcare behaviors, and may not fully reflect the latest developments in the field.

Secondly, tools like VOSviewer and CiteSpace primarily rely on the analysis of author keywords, co-citation relationships, and other content when analyzing and visualizing literature. This method to some extent depends on the accuracy of the keywords provided by authors and the correctness of citation relationships. Inconsistent use of keywords or errors in citation relationships in the literature may have an impact on the analysis results.

For future improvements, the following directions can be considered: Diversification of databases: In addition to WOS and Pub Med, other databases such as Google Scholar, Scopus, and specialized databases in other languages and regions can be utilized to expand the coverage of literature. This can provide a more comprehensive research perspective. Enhancement of algorithms and techniques: Continuous improvement of algorithms and techniques in tools like VOSviewer and CiteSpace can enhance the efficiency and accuracy of analysis and visualization. For example, the introduction of machine learning and natural language processing methods can assist in identifying and processing keywords and citation relationships in the literature. Integration with other data sources: In addition to literature data, other data sources such as academic conference papers, patent data, clinical data, etc, can be combined to obtain more dimensions and in-depth information on healthcare behaviors. These data sources can provide more practical and applicable information, thereby better supporting research on healthcare behaviors. Integration of multiple research methods: Combining quantitative literature reviews with qualitative research methods can provide a more comprehensive understanding of healthcare behaviors. Qualitative research methods such as in-depth interviews, focus group discussions, etc, can provide in-depth insights into specific details, dynamic changes, and influencing factors of healthcare behaviors. By integrating qualitative and quantitative research, a more comprehensive and multi-dimensional picture of healthcare behaviors can be obtained. Analyzing from different research perspectives: In quantitative literature reviews, different research perspectives and frameworks such as sociology, psychology, economics, etc, can be adapted to analyze healthcare behaviors. This can facilitate a better understanding of the multiple dimensions of healthcare behaviors, such as individual behaviors, social influences, economic effects, etc. Focus on emerging areas and trends: With the continuous development of medical technology and information and communication technology, emerging areas such as telemedicine, mobile health, etc, have significant impacts on healthcare behaviors. Future quantitative literature reviews can focus on these emerging areas and explore their applications and influences in healthcare behavior research.

Author contributions

Conceptualization: Min Li Li, Jiangjie Sun.

Data curation: Min Li Li, Tong Liu, Hui Li.

Methodology: Min Li Li, Tong Liu, Hui Li.

Writing – original draft: Min Li Li, Li Fu, Tong Liu, Hui Li, Jiangjie Sun.

Writing – review & editing: Min Li Li, Li Fu, Tong Liu, Hui Li, Jiangjie Sun.

Abbreviation:

WOS
Web of Science

This work was supported in part by the National Natural Science Foundation of China (No.72374005), the NSF Center for Basic Science Project (No.72188101), the Natural Science Foundation for the Higher Education Institutions of Anhui Province of China (No. 2023AH050561 and No. KJ2021A0266), and Cultivation Programme for Young and Middle-aged Excellent Teachers in Anhui Province (YQZD2023021).

The authors have no conflicts of interest to disclose.

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

This work did not require ethical approval because it did not involve any human or animal research.

How to cite this article: Li L, Fu L, Li H, Liu T, Sun J. Emerging trends and patterns in healthcare-seeking behavior: A systematic review. Medicine 2024;103:8(e37272).

Contributor Information

Limin Li, Email: lihui@stu.ahmu.edu.cn.

Li Fu, Email: fuli@stu.ahmu.edu.cn.

Hui Li, Email: lihui@stu.ahmu.edu.cn.

Tong Liu, Email: liutong@stu.ahmu.edu.cn.

References

  • [1].Fox NJ. Health sociology from post-structuralism to the new materialisms. Health (London). 2016;20:62–74. [DOI] [PubMed] [Google Scholar]
  • [2].Macdonald J. A sociological approach to health determinants. Aust N Z J Public Health. 2015;39:596–96. [Google Scholar]
  • [3].Chandra A, Scott MM, Jaycox LH, et al. Racial/ethnic differences in teen and parent perspectives toward depression treatment. J Adolesc Health. 2009;44:546–53. [DOI] [PubMed] [Google Scholar]
  • [4].Otiashvili D, Kirtadze I, O’Grady KE, et al. Access to treatment for substance-using women in the Republic of Georgia: socio-cultural and structural barriers. Int J Drug Policy. 2013;24:566–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5].Bunzli S, O’Brien P, Ayton D, et al. Misconceptions and the acceptance of evidence-based nonsurgical interventions for knee osteoarthritis. A qualitative study. Clin Orthop Relat Res. 2019;477:1975–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [6].Evans J, Horn K, Cowan D, et al. Development of a clinical pathway for screening and integrated care of eating disorders in a rural substance use treatment setting. Int J Ment Health Nurs. 2020;29:878–87. [DOI] [PubMed] [Google Scholar]
  • [7].Miller PJ, Balu S, Buchner D, et al. Willingness to pay to prevent chemotherapy induced nausea and vomiting among patients with breast, lung, or colorectal cancer. J Med Econ. 2013;16:1179–89. [DOI] [PubMed] [Google Scholar]
  • [8].Yu W, Liu X, Zhao F, et al. Control of unreasonable growth of medical expenses in public hospitals in Shanghai, China: a multi-agent system model. BMC Health Serv Res. 2020;20:490. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [9].Bailey KS, Brown HE, Lekic V, et al. Helicobacter pylori treatment knowledge, access and barriers: a cross-sectional study. Helicobacter. 2023;28:e12954. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [10].Jiang M, Feng L, Wang W, et al. Knowledge, attitudes, and practices towards influenza among Chinese adults during the epidemic of COVID-19: a cross-sectional online survey. Hum Vaccin Immunother. 2021;17:1412–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [11].Connolly D, Davies E, Lynskey M, et al. Comparing intentions to reduce substance use and willingness to seek help among transgender and cisgender participants from the Global Drug Survey. J Subst Abuse Treat. 2020;112:86–91. [DOI] [PubMed] [Google Scholar]
  • [12].Li Z, Gao Y, Yu L, et al. Analysis of the elderly’s preferences for choosing medical service facilities from the perspective of accessibility: a case study of tertiary general hospitals in Hefei, China. Int J Environ Res Public Health. 2022;19:9432. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [13].Hailstone J, Mukadam N, Owen T, et al. The development of attitudes of people from ethnic minorities to help-seeking for dementia (APEND): a questionnaire to measure attitudes to help-seeking for dementia in people from South Asian backgrounds in the UK. Int J Geriatr Psychiatry. 2017;32:288–96. [DOI] [PubMed] [Google Scholar]
  • [14].Wong WC, Yilin W. A qualitative study on HIV risk behaviors and medical needs of sex workers in a China/Myanmar border town. AIDS Patient Care STDS. 2003;17:417–22. [DOI] [PubMed] [Google Scholar]
  • [15].Wang JH, Wang LW, Liang SY, et al. Relationship between prescribed opioids, pain management satisfaction, and pain intensity in oncology outpatients. Support Care Cancer. 2022;30:3233–40. [DOI] [PubMed] [Google Scholar]
  • [16].Gong K, Xu Z, Cai Z, et al. Internet hospitals help prevent and control the epidemic of COVID-19 in China: multicenter user profiling study. J Med Internet Res. 2020;22:e18908. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [17].Moritz S, Schröder J, Meyer B, et al. The more it is needed, the less it is wanted: attitudes toward face-to-face intervention among depressed patients undergoing online treatment. Depress Anxiety. 2013;30:157–67. [DOI] [PubMed] [Google Scholar]
  • [18].Nielsen AC, Rotger-Griful S, Kanstrup AM, et al. User-innovated eHealth solutions for service delivery to older persons with hearing impairment. Am J Audiol. 2018;27(3s):403–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [19].van Veen T, Binz S, Muminovic M, et al. Potential of mobile health technology to reduce health disparities in underserved communities. West J Emerg Med. 2019;20:799–802. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [20].Mariani MM, Machado I, Nambisan S. Types of innovation and artificial intelligence: a systematic quantitative literature review and research agenda. J Bus Res. 2023;155:113364. [Google Scholar]
  • [21].Donthu N, Kumar S, Mukherjee D, et al. How to conduct a bibliometric analysis: an overview and guidelines. J Bus Res. 2021;133:285–96. [Google Scholar]
  • [22].Mabillard V, Demartines N, Joliat GR. How can reasoned transparency enhance co-creation in healthcare and remedy the pitfalls of digitization in doctor-patient relationships? Int J Health Policy Manag. 2021;11:1986–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [23].Hu Y, Yu Z, Cheng X, et al. A bibliometric analysis and visualization of medical data mining research. Medicine (Baltim). 2020;99:e20338. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [24].Liang YD, Li Y, Zhao J, et al. Study of acupuncture for low back pain in recent 20 years: a bibliometric analysis via CiteSpace. J Pain Res. 2017;10:951–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [25].Lee YC, Wu WL. The effects of situated learning and health knowledge involvement on health communications. Reprod Health. 2014;11:93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [26].Egube BA, Ofili AN, Isara AR, et al. Neonatal jaundice and its management: Knowledge, attitude, and practice among expectant mothers attending antenatal clinic at University of Benin Teaching Hospital, Benin City, Nigeria. Niger J Clin Pract. 2013;16:188–94. [DOI] [PubMed] [Google Scholar]
  • [27].Torres C, Ogbu-Nwobodo L, Alsan M, et al. Effect of physician-delivered COVID-19 public health messages and messages acknowledging racial inequity on black and white adults’ knowledge, beliefs, and practices related to COVID-19 a randomized clinical trial. JAMA Netw Open. 2021;4:13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [28].Zhang P, Zhao L, Liang J, et al. Societal determination of usefulness and utilization wishes of community health services: a population-based survey in Wuhan city, China. Health Policy Plan. 2015;30:1243–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [29].Porteous T, Ryan M, Bond C, et al. Managing minor ailments; the public’s preferences for attributes of community pharmacies. A discrete choice experiment. PLoS One. 2016;11:15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [30].Wilkinson S, Williams NJ. Should uterus transplants be publicly funded? J Med Ethics. 2016;42:559–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [31].Danis M, Sommers R, Logan J, et al. Exploring public attitudes towards approaches to discussing costs in the clinical encounter. J Gen Intern Med. 2014;29:223–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [32].Wong SF, Norman R, Dunning TL, et al. A discrete choice experiment to examine the preferences of patients with cancer and their willingness to pay for different types of health care appointments. J Natl Compr Cancer Netw. 2016;14:311–9. [DOI] [PubMed] [Google Scholar]
  • [33].Li C, Chen KY, Cornelius V, et al. Applicability and cost-effectiveness of the Systolic Blood Pressure Intervention Trial (SPRINT) in the Chinese population: a cost-effectiveness modeling study. PLoS Med. 2021;18:14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [34].Moyehodie YA, Mulugeta SS, Yilema SA. The effects of individual and community-level factors on community-based health insurance enrollment of households in Ethiopia. PLoS One. 2022;17:14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [35].Park NS, Jang Y, Chiriboga DA. Willingness to use mental health counseling and antidepressants in older Korean Americans: the role of beliefs and stigma about depression. Ethn Health. 2018;23:97–110.27764962 [Google Scholar]
  • [36].Dardas LA, Silva SG, van de Water B, et al. Psychosocial correlates of Jordanian adolescents’ help-seeking intentions for depression: findings from a nationally representative school survey. J Sch Nurs. 2019;35:117–27. [DOI] [PubMed] [Google Scholar]
  • [37].Nakagawa K, Bianchi MT, Nakagawa SS, et al. Aggressive care after a massive stroke in young patients: is that what they want? Neurocrit Care. 2010;13:118–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [38].Chen XF, Chen CL, Yuan RD, et al. Reasons for the delay of surgical treatment among patients with age-related cataracts in urban Chongqing, China. Sci Res Essays. 2010;5:3095–99. [Google Scholar]
  • [39].Li Z, Gao YY, Yu L, et al. Analysis of the elderly’s preferences for choosing medical service facilities from the perspective of accessibility: a case study of tertiary general hospitals in Hefei, China. Int J Environ Res Public Health. 2022;19:23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [40].Liu C, Qiu L, Wang HM. Willingness rate of the first visit to primary healthcare services and the associated factors in China: a meta-analysis. Aust J Prim Health. 2022;28:459–68. [DOI] [PubMed] [Google Scholar]
  • [41].Zoorob D, Yunghans S, Methenitis A, et al. Patient receptivity to integration of telehealth in pelvic floor physical therapy regimens. Urogynecology (Phila). 2023;29:281–6. [DOI] [PubMed] [Google Scholar]
  • [42].Plummer K, McCarthy M, Newall F, et al. The influence of contextual factors on children’s communication of pain during pediatric haematopoietic stem cell transplantation: a qualitative case study. J Pediatr Nurs. 2022;64:e119–29. [DOI] [PubMed] [Google Scholar]
  • [43].Todd A, Holmes H, Pearson S, et al. “I don’t think I’d be frightened if the statins went”: a phenomenological qualitative study exploring medicines use in palliative care patients, carers and healthcare professionals. BMC Palliat Care. 2016;15:13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [44].Chang SJ, Choi S, Kim S-A, et al. Intervention strategies based on information-motivation-behavioral skills model for health behavior change: a systematic review. Asian Nurs Res. 2014;8:172–81. [Google Scholar]
  • [45].Lee YC, Wu WL. The effects of situated learning and health knowledge involvement on health communications. Reprod Health. 2014;11:6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [46].Zhao J, Wang LY, Guo KM. Impact of smart health systems on the behavior of older adults under community healthcare. Front Public Health. 2022;10:13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [47].Lavergne JA, Kennedy ML. Telepsychiatry and medical students: a promising mental health treatment for medical student use both personally and professionally. Curr Psychiatry Rep. 2021;23:31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [48].Holzinger A, Floris F, Schomerus G, et al. Gender differences in public beliefs and attitudes about mental disorder in western countries: a systematic review of population studies. Epidemiol Psychiatr Sci. 2012;21:73–85. [DOI] [PubMed] [Google Scholar]
  • [49].Oyekale AS, Adeyeye A. Rural households’ awareness and willingness to pay for National Health Insurance Scheme (NHIS) in Ilesha West Local Government Area, Osun State Nigeria: a recursive bivariate probit approach. Life Sci J. 2012;9:2086–93. [Google Scholar]
  • [50].Feng X, Feng W, Shen P, et al. The effect of the integrated delivery system on managing hypertension in rural areas of China. Ann Palliat Med. 2021;10:434–42. [DOI] [PubMed] [Google Scholar]
  • [51].Gao Y, Guo Y, Deng J. Effects of and prospects for the hierarchical medical policy in Beijing, China. Healthcare (Basel). 2023;11:1067. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [52].Steelfisher GK, Blendon RJ, Brulé AS, et al. Public response to an anthrax attack: a multiethnic perspective. Biosecur Bioterror. 2012;10:401–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [53].Lubman DI, Cheetham A, Jorm AF, et al. Australian adolescents’ beliefs and help-seeking intentions towards peers experiencing symptoms of depression and alcohol misuse. BMC Public Health. 2017;17:658. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [54].Ioannou CI, Altenmuller E. Approaches to and treatment strategies for playing-related pain problems among czech instrumental music students. Med Probl Perform Artists. 2015;30:135–42. [DOI] [PubMed] [Google Scholar]
  • [55].Dube K, Kanazawa J, Campbell C, et al. Considerations for increasing racial, ethnic, gender, and sexual diversity in HIV cure-related research with analytical treatment interruptions: a qualitative inquiry. Aids Res Hum Retroviruses. 2022;38:50–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [56].Hazewinkel MH, Sprangers MAG, Taminiau-Bloem EF, et al. Reasons for not seeking medical help for severe pelvic floor symptoms: a qualitative study in survivors of gynaecological cancer. BJOG. 2010;117:39–46. [DOI] [PubMed] [Google Scholar]
  • [57].Bewtra M, Kilambi V, Fairchild AO, et al. Patient preferences for surgical versus medical therapy for ulcerative colitis. Inflamm Bowel Dis. 2014;20:103–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [58].Ting SFY, Chien KCW, Ramzi NH, et al. Personality traits and annual income determine the willingness to pay for a single tooth implant. Healthcare. 2021;9:11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [59].Jones JL. Perspectives on the therapeutic potential of MDMA: a nation-wide exploratory survey among substance users. Front Psychiatry. 2023;14:9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [60].Xu Y, He W. More information = less aggression? Impact of information asymmetry on Chinese patients’ aggression. Front Public Health. 2019;7:118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [61].Gafson A, Craner MJ, Matthews PM. Personalised medicine for multiple sclerosis care. Mult Scler. 2017;23:362–9. [DOI] [PubMed] [Google Scholar]
  • [62].Spence W. Personalising prostate radiotherapy in the era of precision medicine: a review. J Med Imaging Radiat Sci. 2018;49:376–82. [DOI] [PubMed] [Google Scholar]
  • [63].Strack S, Millon T. Personalized psychotherapy: a treatment approach based on Theodore Millon’s integrated model of clinical science. J Pers. 2013;81:528–41. [DOI] [PubMed] [Google Scholar]

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