Research evolution and frontiers of shared decision-making in pediatrics: a bibliometric analysis based on CiteSpace

Introduction

Shared decision-making (SDM), as a patient-centered medical decision-making model, formulates diagnosis, treatment, or nursing plans jointly on the basis of full communication between health professionals and patients and their families, combining clinical evidence with patients’ personal preferences, values, and life goals (1). This model is especially significant in the field of pediatrics. It not only reflects respect for children’s rights but also advocates the family-centered nursing concept, which helps improve treatment compliance and satisfaction, optimize health outcomes, and facilitate the transition of children with chronic diseases to the adult healthcare system. The United Nations Convention on the Rights of the Child clearly grants children the right to participate in matters affecting their well-being, and international organizations such as the American Academy of Pediatrics also regard SDM as the core principle of family-centered care (2). Research indicates that SDM can mitigate conflicts in the decision-making process for children with chronic illnesses and enhance health outcomes for children with asthma (3). In recent years, research on pediatric SDM has been developed rapidly, covering multiple topics, including decisions on antibiotic use, care for children with complex diseases, decision-making experiences and preferences of children and parents, and the development of decision aids and their effectiveness evaluation (4,5). Currently, only systematic reviews and scoping reviews related to pediatric SDM have been published. While these reviews address particular research questions, implementation methods, and their outcomes, none offer a thorough summary of the available literature.

CiteSpace is a bibliometric modeling software that addresses the subjective biases often present in traditional narrative literature reviews. Utilizing a scientific drawing program, it visually analyzes structural dynamic patterns and trends within a specific field, enabling researchers to clearly identify the developmental trajectory of the discipline’s frontiers. This paper employs the bibliometric analysis tool CiteSpace V6.2.R3 to summarize the influential countries, institutions, journals, and authors in the field of pediatric SDM (6). Additionally, it analyzes the dynamic evolution and emerging topics related to pediatric SDM in the medical field, providing valuable insights for future research directions and researchers. We present this article in accordance with the BIBLIO reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-493/rc).

Methods

Research design and ethical considerations

This retrospective bibliometric analysis focuses on published articles and does not include any clinical trials involving human subjects. Therefore, this study does not require approval from the relevant ethics review committee.

Literature selection criteria

Inclusion criteria: (I) topic closely related to pediatric SDM; (II) limited to original research or critical articles; (III) literature published in English only.

Exclusion criteria: (I) conference abstracts, editorial materials, letters, news items, and withdrawn papers; (II) duplicate publications; (III) literature that are irrelevant to the research topic.

Data sources and search strategies

To ensure the rigor of the study and the timeliness of the data, we extracted the necessary publication data from the Web of Science Core Collection (WoSCC). The time range was limited from 1999, to April 2025, to avoid potential data bias that may arise from database updates. After screening, we obtained a total of 4,699 records, and 419 papers (8.91%) were included in the analysis, as illustrated in Figure 1. The search was conducted via the following link: https://webofscience.clarivate.cn/wos/woscc/summary/a27ac6a2-77b6-469a-986d-3c17b74673b0-0186295fcd/relevance/1. In constructing the retrieval strategy, we employed a topic retrieval method, utilizing Boolean logic operators to enhance both the comprehensiveness and accuracy of the search. The specific retrieval expression is as follows: TS=(“child*” OR “pediatr*” OR “paediatr*” OR “infant*” OR “adolescen*” OR “teen*” OR “minor*” OR “parent*” OR “caregiver*” OR “guardian*” OR “family member*” OR “pediatric patient*”) AND TS=(“shared decision making” OR “shared decision-making” OR “shared clinical decision making” OR “collaborative decision making” OR “patient-centered decision making” OR “joint decision making” OR “participatory decision making”).

Figure 1 Flow chart of document screening. This flowchart illustrates the screening process for publications retrieved from the Web of Science Core Collection (1999 to April 2025), resulting in 419 eligible papers (8.91% of the initial 4,699 records) included in the final analysis. WoSCC, Web of Science Core Collection.

Quality control

After the initial search, all documents were independently screened and evaluated by two researchers. If there was a disagreement between the two evaluators, they would first attempt to reach a consensus through discussion; if differences persisted, a third researcher would be invited to intervene and make a final judgment to ensure the objectivity of the literature evidence. By carefully examining the titles, abstracts, and full texts, the researchers eliminate duplicate and irrelevant documents, ensuring that the selected papers are closely related to the research topic. For documents presenting differing opinions, the research team will conduct group discussions to determine their inclusion. Following the screening process, the bibliographic information of all included documents will be exported in plain text format for subsequent analysis.

Data analysis

The included literatures were imported into CiteSpace6.2.R3 software. Set the time span from 1999 to April 2025, with each year as the time partition; Select country, institution, author and keywords as node types. G-index is adopted as the node screening method, and k=25, Top N =50, Top N% =10%. Choose pathfinder and pruning sliced networks as network clipping methods. The rest parameters are kept at the default settings, bibliometrics analysis is carried out, and the corresponding visual knowledge map is generated.

Results

Bibliometric analysis based on year of publication

Figure 2 illustrates the annual publication count of papers. The number of documents focusing on the application of SDM in pediatrics has gradually increased since only 2 papers were published in 1999. However, prior to 2011, the annual publication count did not exceed 10. The peak occurred in 2020, with a total of 50 papers published. Notably, from 2019 to 2024, the number of published articles exhibited significant fluctuations, reflecting shifts in research interests and priorities.

Figure 2 Annual trend chart of publications. This chart presents the annual number of pediatric SDM publications: 2 papers in 1999, <10 papers annually before 2011, a peak of 50 papers in 2020, and significant fluctuations in counts from 2019 to 2024. SDM, shared decision-making.

Bibliometric analysis based on countries and institutions

Globally, 32 countries and 283 institutions have published relevant articles on the topic of SDM in pediatrics. Table 1 provides a detailed overview of the top 10 countries and institutions that have contributed the most articles in this field, along with their respective article counts, proportions, and centrality scores. As indicated in Table 1, the United States leads the list with 249 related articles, followed by the United Kingdom (55 articles) and Canada (49 articles). The total number of papers from the top ten countries accounts for 90.63% of all publications, highlighting a significant imbalance in research and development in this area among different nations. Notably, the United States has a centrality score of 0.72, reflecting its substantial influence in academic circles; the United Kingdom ranks second with a centrality score of 0.44, indicating a strong academic presence as well. In terms of institutions, Cincinnati Children’s Hospital Medical Center (39 articles), Ohio University System (38 articles), and the University of Cincinnati (30 articles) occupy the top three positions. Figure 3 visually illustrates the distribution and collaborative networks of these contributing countries and institutions. These leading institutions are all located in the United States, further reinforcing the country’s dominant role in pediatric SDM practices, which aligns with the results of the national collinearity analysis.

Figure 3 Bibliometric analysis based on countries and institutions. This visualization displays the global distribution and collaborative networks of 32 countries/283 institutions in pediatric SDM research. Node features correspond to publication output/collaboration intensity, aligning with the U.S.’s dominant role (top country) and its leading institutions (per Table 1). SDM, shared decision-making.

Bibliometric analysis based on authors

Table 2 presents the top ten authors who have published the most articles in this research field. William B. Brinkman leads the list with 9 articles, followed by Ellen A. Lipstein with 8 articles. Imelda Coyne, Maria T. Britto, Emily F. Boss, Mary Catherine Beach, Jill Chorney tied for the third place, with 5 articles published. However, the centrality score of all these authors is 0, indicating that their influence in this field is relatively low. The cooperative network analysis conducted using CiteSpace software is illustrated in Figure 4. In the visual representation, the size of each circle is directly proportional to the number of articles published by the author, with different nodes representing different authors. A greater number of connections between nodes signify closer collaboration among authors (7). As shown in the figure, the collaboration among William B. Brinkman, Ellen A. Lipstein, Imelda Coyne is particularly strong.

Figure 4 Bibliometric analysis based on authors. This collaborative network map shows author connections in pediatric SDM research: node size reflects publication count, and link thickness indicates collaboration intensity. Strong collaboration is observed among William B. Brinkman, Ellen A. Lipstein, and Imelda Coyne. SDM, shared decision-making.

Bibliometric analysis based on journals and co-cited references

Table 3 presents the top 10 journals and their commonly cited references. Among these journals, Pediatrics shows the highest level of productivity, as it has published the largest number of relevant research studies, with a total of 282 papers. The most frequently cited reference is a study by scholars such as Boland et al. (5), which identifies key barriers to pediatric SDM, including parental knowledge gaps, emotional stress, staff time constraints, and inadequate training, as well as facilitators such as information support, medical staff training, and structured decision tools. In the future, research on pediatric SDM will likely focus on training medical staff, empowering parents, and optimizing systemic approaches, particularly in relation to SDM strategies across diverse cultural contexts and specific diseases. Through multi-level interventions, the effective implementation and advancement of pediatric SDM can be significantly enhanced.

Bibliometric analysis based on co-occurrence keywords

The analysis of the retrieved literature yielded a total of 453 keywords, 1,166 connections, and a density measure of 0.0114, as illustrated in Figure 5. The ten most frequently occurring keywords are “shared decision making” (n=218), “children” (n=102), “care” (n=89), “parents” (n=74), “communication” (n=52), “adolescent” (n=42), “participation” (n=40), “experience” (n=34), “decision making” (n=33), and “outcome” (n=30). Additionally, the purple circles representing the outer rings of the nodes indicate a relatively high level of node centrality within the co-occurrence network diagram. Notably, the centrality of “decision making” is the highest at 0.22, followed by “children” (0.16), “communication” (0.15), and “adolescent” (0.15), as detailed in Table 4.

Figure 5 Bibliometric analysis based on co-occurrence keywords. This network diagram depicts 453 keywords (1,166 connections; density =0.0114). Node size reflects frequency (top: “shared decision making”, n=218), and purple outer rings indicate centrality (highest: “decision making”, 0.22; per Table 4).

Clustering analysis of keyword

Keyword clustering is based on the inherent similarity among keywords, utilizing the log-likelihood ratio (LLR) ranking algorithm to generate cluster tags. This methodological approach allows for the segmentation of keywords into multiple network clusters, facilitating a more thorough examination of keyword co-occurrence. Within the CiteSpace framework, nodes that belong to the same cluster are either enclosed by convex hulls or defined by boundary lines, with clusters sequentially numbered starting from zero. Specifically, cluster #0 represents the largest cluster, followed by cluster #1 as the second largest, and this recursive numbering continues thereafter (8). The Q value associated with the clustering module serves as an indicator of the structural integrity of the network map; a Q value exceeding 0.3 indicates a statistically significant clustering structure. Additionally, the average contour S value reflects the clarity of the clustering, with S values greater than 0.5 indicating reasonable clustering and those exceeding 0.7 suggesting a high degree of clustering reliability. In the present study, the analyzed literature yielded 13 distinct clusters (Figure 6, Table 5), with a modular value of Q=0.4729 and a contour value of S=0.7811, thereby confirming the reliability and significance of the findings.

Figure 6 Clustering analysis of keywords. This map (via log-likelihood ratio algorithm) segments keywords into 13 clusters (enclosed by convex hulls/boundaries, numbered by size). It yields modularity Q=0.4729 (significant structure) and silhouette S=0.7811 (high reliability; per Table 5).

Bibliometric analysis based on citation burst keywords

Emergent words are defined as terms that experience a significant increase in frequency within a specific research domain over a designated time frame, thereby reflecting the dynamics at the forefront of that field (7). Figure 7 illustrates twelve keywords (γ=0.8) that exhibit notable citation surges from 1999 to April 2025. Among these, “mental health” (3.98), “perspective” (3.91), and “perceptions” (2.93) demonstrate particularly strong emergent intensity. The year indicated corresponds to the initial appearance of each keyword, with the red line representing the duration of the citation surge and the blue line denoting the time intervals. Notably, “decision making”, which reached its earliest citation peak in 1999, has been associated with ongoing research topics—including perspectives and sickle cell disease—that remain relevant today.

Figure 7 Distribution of the top 12 keywords with citation burst intensity during 1999–2025 (γ=0.8). This chart identifies 12 keywords with citation surges (e.g., “mental health”, intensity =3.98). Years denote first appearance; red lines = burst duration, blue lines = other intervals (e.g., “decision making” peaked in 1999 and remains relevant).

Discussion

General characteristics

From January 1, 1999, to April 2025, we collected 419 papers related to children’s SDM from the WoSCC. The growth trend of these publications has fluctuated significantly over time. A total of 32 countries have published relevant articles, with the United States contributing 249 papers, underscoring its dominant position in this field. The United Kingdom and Canada follow as the next two most prolific contributors, benefiting from abundant research resources and financial support. SDM is included in the Patient Protection and Affordable Care Act of the United States (9), the government of Saskatchewan in Canada has also set up an SDM working group, and Ottawa, Ontario has set up a patient decision-making auxiliary research group (10), and there are corresponding research funds in various ways to support the corresponding research, which provides the best conditions and guarantees for SDM research in pediatrics. The top ten countries except China are all developed countries, which shows that the developed countries lead the research in pediatric SDM, while the participation of low-and middle-income countries is low. At the same time, the number of papers published by the top 10 countries accounts for 90.63% of all papers, which also shows that the research development in this field is uneven among countries. At the same time, the distribution of institutions shown in Table 1 shows that scientific research institutions in universities occupy a dominant position in literature output, reflecting the core position of higher education institutions in this research field. From the geographical distribution of institutions, the three institutions with the highest contribution are all from the United States, which shows that American institutions have made great contributions to the field of children’s sharing decision-making. The results of this study show the consistency of contribution between institutions and national distribution. Therefore, in the future, we should strengthen cooperation and exchanges between countries, jointly explore effective support and service models, and jointly promote the development of global pediatric SDM.

Among the 419 articles retrieved, more than 500 authors participated in the writing. Among them, William B. Brinkman became the most prolific authors with 9 articles, and their research focused on the clinical practice optimization of the family-oriented SDM model in children with attention deficit hyperactivity disorder (ADHD), children with autism spectrum disorder (ASD), and children with sickle cell disease, and they devoted themselves to the research and development of auxiliary tools for pediatric SDM and its effect verification (11-13). It is worth noting that although the number of papers published by this scholar is leading, it is not the most frequently cited researcher-the most frequently cited document is a summary of the influencing factors of pediatric sharing decision-making by Boland et al. (5). This phenomenon shows that researchers pay more attention to the summary of experience and lessons in the implementation process than the specific application measures of the SDM model in children with specific diseases. This research tendency also reflects the deep thinking of the academic circles on the promotion path of SDM, that is, how to transform the theoretical framework into a replicable practice model, rather than being limited to the technical details of a single disease scene. However, according to the co-occurrence analysis of the authors in Figure 4, there is a contradiction between the current research ecology and the above theoretical demands. The top ten authors are mostly connected with internal cooperation, while other authors are sparsely connected with low node density, and the cooperative relationship in the display field is still in a fragmented state, and a multi-level cohesive research team has not yet been formed. This lack of cooperation frequency and intensity may restrict the experience integration and model promotion across diseases and regions. Therefore, scientific research institutions and scholars need to further promote the integration of resources and the construction of international cooperation networks to promote the all-round development of this research field.

Research themes and frontline trends

Keyword analysis and research trends

Keywords serve as a broad representation of the article’s theme, and the frequency of these keywords can indicate prevailing research directions within a specific field. By applying keyword co-occurrence and cluster analysis, this study identifies “decision making” and “decision aid” as the primary focal points of research within the domain of pediatric SDM. Existing literature suggests that interventions related to SDM for chronic and complex conditions, such as asthma (14), ADHD (15,16), autism (17), sickle cell disease (18), and pediatric intensive care (19), have emerged as significant trends in this area of research.

SDM involving children’s participation

Previous research indicates that the successful implementation of SDM necessitates the collaborative involvement of both parents and children. Traditionally, pediatric SDM has predominantly positioned parents as the primary decision-makers, guiding their children in the decision-making process. However, the study conducted by Coyne et al. (20) has provided novel insights, revealing that young cancer patients perceive participation as a means of acquiring information, articulating preferences, and negotiating treatment plans, which ultimately enhances treatment outcomes. This finding challenges conventional understandings and underscores the need for increased participation by children. Furthermore, it is essential to recognize that children’s involvement in SDM should not be viewed as a singular event but rather as an ongoing process throughout the entirety of their treatment. As children’s preferences may evolve in response to the progression of their illness, it is imperative that their voices are consistently heard in the decision-making process. Additionally, parental support emerges as a critical factor facilitating children’s engagement in SDM. Tailored interventions designed for families can significantly bolster parental encouragement of children’s active participation in this collaborative process (21).

Practical value of decision aid tools (DAs)

Numerous studies have confirmed that the application of DAs in pediatric SDM significantly enhances decision-making quality. A randomized controlled trial by Wysocki et al. (22) on adolescents with type 1 diabetes demonstrated that electronic DAs reduced family decision-making conflicts by 35% and increased parental satisfaction with the decision process to 82%. Another study on asthmatic children (23) revealed that multimedia DAs combined with SDM interventions enhanced parents’ depth of understanding of treatment plans by 40% and significantly mitigated medical resource waste due to decision-making hesitation. In pediatric oncology, structured information presentation via DAs improved parental acceptance of chemotherapy regimens by 27% while effectively alleviating physician-patient information asymmetry (24). Future research could focus on integrating DAs with intelligent interactive systems, optimizing the decision experience through interactive decision trees, risk visualization tools, and age-stratified virtual treatment simulation modules (e.g., gamified interfaces). This integration is expected to facilitate more efficient and high-quality decision-making processes in pediatric care (25,26).

Research prospects

The positive impact of children’s participation in SDM on chronic disease management has been validated across multiple dimensions. In adolescent asthma patients, SDM interventions incorporating hierarchical information sharing models significantly improve inhaler use compliance and reduce the risk of hospitalization due to acute exacerbations (25). In pediatric oncology, family involvement in treatment decisions has been shown to increase acceptance of chemotherapy regimens by 27% while significantly enhancing psychosocial adaptability scores (26). Notably, current research remains predominantly focused on single-disease populations or isolated intervention phases, lacking systematic evaluation of SDM’s comprehensive efficacy. Future investigations should prioritize multi-center collaborative studies to accumulate high-quality evidence, which will be critical for the standardized implementation of SDM across pediatric healthcare settings (27,28).

Limitations

First, this research only retrieved publications from the Web of Science database, which might have led to the omission of some significant research findings. Additionally, the keyword cleaning process and statistical metrics were self-designed, potentially constrained by professional knowledge and experience. In the future, we will further expand data sources and standardize keywords to enhance the overall quality of the paper and the accuracy of predictions.

Conclusions

This study systematically outlines the evolutionary trajectory of pediatric SDM research over the past 25 years through bibliometric analysis. It highlights the significance of three key research threads: parent-child collaborative participation mechanisms in decision-making, visual support for complex medical decisions via DAs, and innovative intervention practices in chronic and complex disease contexts. At the same time, it reveals that the current global research forces show a significant distribution imbalance among countries/regions and institutions. The cross-regional cooperation network has not yet formed a systematic collaborative framework, which to a certain extent restricts the cross-scenario transformation of research results and the accumulation of evidence. Future research should focus on strengthening transnational and cross-institutional research collaboration mechanisms, establishing multi-center joint research networks, and promoting standardized development of pediatric SDM in methodological innovation, tool development, and clinical translation.

Acknowledgments

The authors would like to express their gratitude to the Web of Science Core Collection (WoSCC) database for providing the bibliometric data essential to this study. We also acknowledge the developers of CiteSpace software for creating the tool that enabled the visual analysis of research trends in pediatric SDM. Additionally, we thank all peer reviewers and editorial staff for their valuable comments and guidance during the manuscript revision process.

Footnote

Reporting Checklist: The authors have completed the BIBLIO reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-493/rc

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-493/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-493/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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