Introduction

Every year, nations and regions globally are faced with many natural disasters and public health emergencies, which have a profound impact on human health (Berchtold et al., 2020; Goode et al., 2021). According to statistics, around 2 billion people globally were affected by natural disasters between 2008 and 2018 (Almukhlifi et al., 2021), and in 2019, the COVID-19 pandemic further captured global attention. In the process of emergency response and rescue, language barriers are one of the significant factors that affect rescue operations. In such situations, emergency language services become crucial for post-disaster relief efforts (Shao et al., 2018; Wang, 2021). Emergency language services refer to the provision of rapid language products, language technologies, or participation in language rescue operations for the prevention, monitoring, rapid response, and recovery of major natural disasters or public crisis events. These services include emergency translation of foreign languages, minority languages, dialects, and sign language for individuals with disabilities, the development of disaster language software, the dissemination of disaster information, and the management of disaster language resources for relief services. Additionally, they encompass the development of emergency language standards, emergency language training, language therapy, and rehabilitation, as well as language counseling and crisis intervention (Wang et al., 2020). In the context of disasters and other crises, emergency language services enable individuals to comprehend and communicate information about emergency preparedness and response systems, thereby enhancing personal safety and collectively mitigating risks faced by affected individuals (Markakis et al., 2017). Therefore, emergency language services are crucial in emergency situations.

At present, in terms of emergency language services, a comprehensive and clear representation of the scientific review literature is lacking. Traditional reviews in this area have mostly focused on enhancing the capabilities of emergency language services, such as the development of emergency language service systems and the training of personnel for emergency preparedness services. However, these studies have not sufficiently considered the complexity of communication during emergency response and rescue processes, and reliance solely on traditional on-site human translation proves inadequate to meet the efficiency requirements of emergency language services. Specifically, there is a scarcity of review studies that employ quantitative analysis methods to examine the complexities of emergency language services.

To address this gap, this paper employs bibliometric analysis and content analysis methods to analyze the collected effective literature related to the study of emergency language services. The analysis methods help to identify the development trends, research hotspots, and future directions of the field (Cheng, Zhang (2023)). This approach advances the research on emergency language services, providing guidance for its further development and for scholars conducting research in this field.

Specifically, the study mainly addresses the following key research questions.

RQ 1. What is the current state of emergency language services research, and what progress has been made in recent years?

RQ 2. What is the distribution of core authors, journals, and institutions involved in emergency language services research?

RQ 3. What are the hotspots of emergency language services research, and what are the prospects for the field in the future?

This paper makes a comprehensive analysis of the current research situation in the field of emergency language services, that is, a comprehensive review of the literature on emergency language services in recent decades, including bibliometric analysis and quantitative visualization research. Particularly, these research results provide guidance for constructing a framework combining the latest literature and highly cited content of emergency language services, and it promotes rapid and long-term development of emergency language services research.

The remaining sections of this paper are organized as follows. Section “Methods” explains the research design, including data sources, the screening process, and the main analysis methods (bibliometric analysis and content analysis). Section “Results” presents the results of trend analysis, impact analysis, and content analysis. Firstly, it analyzes the annual publication trends of the 3814 selected literature and identifies the key influential journals of publication. Then, it introduces the analysis of author influence, country and institution analysis, disciplinary analysis, keyword co-occurrence analysis, and keyword clustering analysis using bibliometric analysis and content analysis methods. The results of the bibliometric and content analysis are further discussed in Section “Discussion”. Finally, Section “Conclusions” presents the conclusions and outlines the limitations of this paper. The overall research design framework of this study is illustrated in Fig. 1. The process consists of three main steps: the first involves data collection and screening; the second applies bibliometric and content analysis; and the final step includes discussion and conclusions.

Fig. 1: Research design framework.
figure 1

The framework consists of three main research steps: data collection, bibliometric analysis, and discussion and conclusion. *n=number.

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Methods

Data source

In this paper, the literature used for the analysis of emergency language services research was retrieved from the core dataset of the Web of Science (WoS). WoS is one of the world’s leading science citation index databases and is widely recognized and used in academia (Wang et al., 2016). WoS includes high-quality articles on international research (Ciavolino et al., 2022), including journal articles related to emergency language services, and provides journal and article citations.

Data screening

To ensure the accuracy and representativeness of the selected literature, the inclusion criteria of the literature were established: (1) the literature source was the core dataset of WoS; (2) The publication period of the literature is from January 1, 1988–December 31, 2023; (3) The literature sources were SCI-EXPANDED, SSCI, ESCI, and A&HCI; (4) The language type of the document is English. Exclusion criteria: (1) The topic unrelated to emergency language services but only containing the keywords “emergency” and “language”; (2) Conference minutes, editorial materials and other non-academic articles. Finally, 3814 articles were obtained that were highly consistent with the research theme of this paper.

The data retrieval and cleaning process in the bibliometric analysis section is described as follows:

  1. 1.

    Using the advanced search method with the search condition “(Topic = emergency)” and “(Topic = language)”, a total of 5592 records were retrieved.

  2. 2.

    The literature retrieval type was set as “Article” or “Review article”, with the language filter set to English. The literature source categories included SCI-EXPANDED, SSCI, ESCI, and A&HCI. The retrieval period spanned from January 1, 1988, to December 31, 2023. Subsequently, book reviews, book chapters, conference proceedings, and other irrelevant materials were excluded, resulting in a final set of 4662 articles.

  3. 3.

    Further exclusions were made by reviewing and analyzing abstracts to eliminate articles unrelated to emergency language services. This included articles that only had keywords in the abstract without addressing research in the field, research papers not involving emergency language services in their descriptive topics, and data that was insufficient or findings that were unclear. In the end, a total of 848 papers were excluded, leaving 3814 papers for analysis.

Bibliometric analysis

In recent years, bibliometric research has witnessed rapid development, with its methods and tools increasingly applied in various scientific fields (Broitman and Davis, 2013). This study mainly focuses on bibliometric analysis, supplemented by content analysis. A total of 3814 literature articles on emergency language services published between January 1, 1988, and December 31, 2023, were analyzed from different perspectives. The first article retrieved from the WoS database on emergency language services was titled “Language Concordance as a Determinant of Compliance and Emergency Room Use in Patients with Asthma” (Manson, 1988). Therefore, it served as the starting point for data collection in this study.

Author influence analysis and national institution analysis were carried out after topic search and screening. This was done to identify authors with high influence and contributions in the research field of emergency language services, to pinpoint the hot research frontiers in this field, and to understand the situation of international cooperation. This analysis promotes cooperation and exchange between different national institutions and supports the international development of emergency language services research.

Various bibliometric cartographic analysis methods were applied to obtain answers to the research questions described in section “Introduction”. Each method of bibliometric cartographic analysis is designed for specific research purposes (Li et al., 2022). In this study, the following bibliometric network maps were created: keyword co-occurrence graph, cluster graph, and other types of tables and graphs to answer the research questions.

Content analysis

By employing content analysis, a more systematic and in-depth analysis was conducted on the disciplinary distribution, keywords co-occurrence, and clustering results related to emergency language services research. This helped identify different aspects and focal points of research in the field, providing guidance and direction for further research and practice. Content analysis and bibliometric analysis worked in tandem: bibliometric analysis identified pivotal articles and areas of focus, while content analysis delivered a detailed and objective portrayal of the research landscape of emergency language services.

Results

Publications output distribution

The distribution of publication output is a key indicator that provides insights into research activities related to a particular set of documents (Li et al., 2020). In this section, the main analysis is the trend in the number of publications and journal distribution of the 3814 articles.

Analysis of annual publication volume

Figure 2 illustrates the trend in the annual publication volume since 1988. It is evident that, although the overall trend indicates growth, the annual publication volume does not consistently increase. There were some temporary declines in certain years, such as 2001, 2007, and 2009. However, the number of articles has progressively increased in the field of emergency language services research, from only 1 article in 1988 to 488 articles in 2023. This indicates that in recent decades, there has been increasing attention from researchers in the field of emergency language services, and the prominence of emergency language services has been continually rising.

Fig. 2: Annual publication trends.
figure 2

Annual publication growth of research literature on emergency language services (1988-2023). Data points are represented by black diamonds (◆), with the number of publications per year indicated by blue numbers next to each data point. The three phases are demarcated by red dashed lines and labeled accordingly.

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It can be observed that the average annual publication counts for research on emergency language services from 1988 to 2023 is 109 articles, with a simple average annual growth rate of 30.92%, and a compound annual growth rate (CAGR) of approximately 14.64%. Based on the annual growth rate of the articles, this indicates a continuous upward trend: an initial exploratory period (1988–2003), a stable growth period (2004–2014), and a rapid growth period (2015–2023).

During the initial exploratory period from 1988 to 2003, an average of 15 articles related to emergency language services were published each year. Among them, the highest number of articles was published in 2002, with a total of 36 articles. In the stable growth period from 2004 to 2014, the publication count showed a steady increase with minor fluctuations, averaging 74 articles per year. After 2014, there was a significant increase in the number of publications, with a total of 2779 articles published in the following nine years, averaging 309 articles per year. This is approximately eight times the number of articles published during the initial exploratory period and the stable growth period. In 2022, there were 541 published articles, accounting for 14.18% of the total, reaching its peak.

Journal distribution

Figure 3 shows the top 20 journals in terms of publication quantity related to emergency language services. It can be seen that “Academic Emergency Medicine” leads the list with a total of 80 articles. Notably, “Academic Emergency Medicine” has published significantly more papers on emergency language services (n = 80) than other journals, such as “Pediatric Emergency Care” (n = 51), “Annals of Emergency Medicine” (n = 48), “BMJ Open” (n = 47), “American Journal of Emergency Medicine” (n = 44), “PLoS One” (n = 40), “International Journal of Environmental Research and Public Health” (n = 36), and “Journal of General Internal Medicine” (n = 34). Despite the relatively small overall number of publications, the number of papers published in “Academic Emergency Medicine” is nearly double that of any other journal. This indicates that, in terms of publication quantity, the journals ranking higher are more likely to attract the attention of researchers.

Fig. 3: Top 20 Journals.
figure 3

The top 20 journals in terms of publication quantity related to emergency language services are listed from top to bottom in descending order.

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Research power results

Author influence analysis

Research authors play a crucial role in reflecting the research capacity of an academic field and evaluating its development (Guo et al., 2021). Among the 3814 analyzed articles, there were a total of 17,026 authors, with an average of 4.46 authors per article. Given the large number of core authors, this study ranked the top 20 most prolific authors in descending order based on the number of publications, as shown in Table 1.

Table 1 Top 20 most productive authors in emergency language services research: 1988–2023.
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Table 1 reveals that, in terms of publication output, Lion, K. Casey from the University of Florida, and Topaz, Maxim from Columbia University in the United States have the highest number of publications on emergency language services research, with 13 articles each, which is significantly more than other scholars. Following closely is Camargo, Carlos A. from Massachusetts General Hospital in the United States, with 12 articles, maintaining a considerable lead over other contributors. Notably, 16 of the top 20 authors in this field are affiliated with American institutions, highlighting the significant emphasis placed by the United States and underscoring its influence in the global research landscape.

Country and institutional analysis

Analyzing the distribution of research on emergency language services across countries and institutions unveils the geographical landscape of such research, offering insights into its focus, strengths, and challenges globally. This information aids decision-makers in resource allocation and serves as a reference for international collaboration and knowledge sharing.

Table 2 presents the number and proportion of publications in the field of emergency language services research for the top 20 countries by publication count. At present, a total of 3814 articles were retrieved from 12,302 institutions studying emergency language services, covering 931 countries or regions. In terms of the number of publications and proportion, the top three countries are the United States, Canada, and the United Kingdom. Among them, the number of articles published in the United States is significantly higher than in other countries, accounting for 45.65%, which is 5.49 times and 5.58 times of Canada and the United Kingdom, ranking second and third, respectively. Therefore, the United States represents a major research force and a leading contributor to the development of the field of emergency language services research worldwide.

Figure 4 shows the collaboration institutions in emergency language services research. The size of the circle in Fig. 4 represents the number of publications by each institution in the field. The larger the circle, the more publications the institution has. Institutions such as the University of Washington, Harvard Medical School, and the University of California, San Francisco, are represented by the larger circles, signifying their significant contribution to research and publications in the field of emergency language services. These institutions demonstrate a high level of activity and influence. The top 20 institutions in the field of emergency language services, ranked by the number of publications, are listed in Table 3.

Table 2 The top 20 countries with the highest number of publications in the field of emergency language services.
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Fig. 4: Collaboration network of institutions.
figure 4

The collaboration network of institutions is visualized using CiteSpace, with nodes representing institutions.

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Table 3 Top 20 institutions in emergency language services.
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Table 3 provides basic information on the top 20 institutions in the field of emergency language services, ranked by the number of publications. It can be seen from this that the University of Washington, Harvard Medical School, and the University of California, San Francisco, have published the most papers. Additionally, centrality measures the importance of institutions in academic networks. Centrality was measured using a value between 0 and 1, with higher values indicating higher centrality in the academic network. The University of Washington and the University of California, San Francisco, are institutions with high centrality. These institutions hold significant research influence and occupy important positions in this field. These data reveal that institutions from the United States dominate in terms of article output and centrality in the field of emergency language services research.

Content analysis

Discipline analysis

In the WoS core database, each publication is classified into at least one thematic category, along with its research direction content, to indicate its research domain. This section analyzes the disciplinary knowledge and directional characteristics of 3814 retrieved literature to determine the main disciplinary directions involved in the research field of emergency language services. Considering the interdisciplinary nature, this article also explores the core disciplines in this field. Table 4 describes the Top 20 disciplinary direction rankings in emergency language services.

Table 4 Top 20 disciplinary direction rankings in emergency language services.
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The 3814 literature articles retrieved so far encompass a total of 194 disciplines related to emergency language services. The top 20 disciplinary directions reveal a broad range of disciplines that contribute to this interdisciplinary field (Table 4). Emergency Medicine leads the list with a significant frequency of 524, followed by Public Environmental Occupational Health, Medicine General Internal, and Health Care Sciences Services.

Highly cited topics, such as Nursing and Healthcare Policy, highlight the importance of these themes in the emergency language services domain. Themes like Trauma & Emergency Surgery, Health Literacy & Telemedicine, Knowledge Engineering and Representation, Language and Linguistics, and Education Educational Research, highlight the need for effective communication and technology integration in emergency settings.

The research directions show a similar trend, with Emergency Medicine, General Internal Medicine, and Public Environmental Occupational Health leading the way. Additionally, disciplines like Computer Science and Education Educational Research indicate the increasing relevance of technological solutions and training programs in enhancing emergency response capabilities.

In summary, based on the analysis of disciplinary categories, highly cited topics, and research directions, the disciplinary theoretical foundation of emergency language services mainly concentrates on emergency medicine, environmental science, public health and preventive medicine, computer science, educational science, and language and linguistics. This interdisciplinary approach underscores the complexity of providing effective language services in emergency scenarios and the need for collaboration across multiple fields. Besides, special attention should be given to theories that integrate computer science with other fields, as these theories play a crucial role in understanding emergency language services research.

Core keywords and co-occurrence analysis

Keywords provide information about the core content of an article (Liu et al., 2015). When two or more keywords appear together in the same paper, it is referred to as keyword co-occurrence (Fang et al., 2017). Keyword co-occurrence analysis can identify research hotspots and emerging frontiers in scientific knowledge domains (Liu et al., 2015). In a keyword co-occurrence graph, the size of the circles represents the total frequency of occurrence of keywords in the field of emergency language services research. The larger the circle, the more representative it is of research hotspots and directions in the field (Yang et al., 2020; Yu et al., 2020). Using CiteSpace software, keyword co-occurrence analysis was conducted on the text of the retrieved 3814 literature articles. The keyword co-occurrence network is shown in Fig. 5. The parameter settings are as follows:

  1. (1)

    year (s) per slice: 1 year;

  2. (2)

    Selection criteria: g-index (k = 10), LRF = 3.0, L/N = 10, LBY = 5, e = 1.0;

  3. (3)

    Pruning: Pathfinder;

  4. (4)

    Nodes Labeled: 1.0%.

Fig. 5: Co-occurrence keywords network.
figure 5

Co-occurrence network of keywords in the field of emergency language services (1988-2023). The network is visualized using CiteSpace. Each node represents a keyword, with the size of the node indicating the frequency of the keyword’s appearance.

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From Fig. 5, it can be observed that the circles containing the keywords “emergency department”, “natural language processing”, and “COVID-19 pandemic” are the largest, indicating their high frequency of occurrence. Therefore, the research hotspots in the field of emergency language services may be related to increased research in emergency medicine, natural language processing, and emergency services resulting from public health events like the COVID-19 pandemic.

To understand the co-occurrence of the keywords in Fig. 5, the core keywords were classified according to the three stages of emergency language service development. The top 20 keywords in each stage were listed in Table 5.

  1. (1)

    In the initial exploration stage from 1988 to 2003, “emergency department”, “communication”, “language”, “emergency medical services”, and “interpreters” were the top five keywords in terms of frequency. Among them, the “emergency department” has the highest frequency of occurrence, indicating that the emergency department was the core focus of research during this period. In addition, during this period, research on emergency language services also focused on communication issues in emergency situations, language barriers or cross-cultural communication barriers that may be encountered during communication, emergency pharmaceutical services, interpretation services, emergency management, and other aspects during emergency rescue.

  2. (2)

    During the steady growth period from 2004 to 2014, the keywords with high frequency were: “natural language processing”, “emergency medicine”, “systematic review”, “language barriers”, and “limited English proficiency”. During this period, researchers began to pay attention to the application of natural language processing technology to solve the problem of emergency language services. For example, Starlander et al. (2005) described the evaluation of an open-source medical speech translation system (MedSLT) for safety-critical applications with a view to eliminating the language barrier in emergency situations. St-Maurice, Kuo (2012) used natural language processing to analyze primary care data extracted from identification to identify inappropriate emergency room use. On the other hand, researchers are also working to overcome language barriers, focusing on public health and the harm caused by natural disasters and public health events to children or migrants with limited language skills.

  3. (3)

    During the period of rapid development from 2015 to 2023, high-frequency keywords such as “COVID-19 pandemic”, “machine learning”, “social media”, “emergency remote teaching” and “artificial intelligence” emerged. The keywords during this period covered multiple aspects of emergency language services research. Keywords such as “COVID-19 pandemic”, “emergency remote teaching”, “online learning”, “triage”, and “telemedicine” are highly likely to be related to the COVID-19 pandemic in public health in 2020. The COVID-19 pandemic has had a significant impact on research on emergency language services, and researchers have begun to pay attention to the evaluation and response of the COVID-19 pandemic to language service needs, language barriers, multilingual transmission, and cross-cultural communication.

Table 5 Different periods of literature co-occurring keywords (Partial excerpt).
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In the field of education, emergency remote teaching and online learning have been conducted. For example, Jiang et al. (2023) conducted a case study using a renowned Chinese language university to explore how Chinese university scholars responded to the challenges of emergency remote teaching during the pandemic. In the medical field, triage and prioritization are carried out during emergency situations, considering how to provide appropriate language support during the triage process to ensure the fair allocation of resources and timely provision of language services. For instance, a natural language processing system using nursing triage records was used to predict the quantity of emergency resources needed in the future (Sterling et al., 2020). Analysis of spoken expressions during simulated emergency call triage processes was also conducted (Morimura et al., 2005). Additionally, remote medical services are provided through technologies like video conferencing to offer cross-lingual medical consultations and support, addressing language barriers and promoting healthcare accessibility. For example, the usage of remote medical services by non-elderly patients with limited English proficiency during the COVID-19 pandemic was evaluated, along with its relationship to emergency department visits and hospital encounters (Chang et al., 2023). Remote medical methods under low bit-rate communication conditions have also been explored (Ruminski, 2008).

The keywords “social media” and “Twitter” may be related to the role of social media in the field of language services. Social media platforms and Twitter can be used to disseminate emergency information, provide multilingual support, promote community participation and communication. Keywords such as “refugees”, “pediatrics”, and “accident & emergency medicine” may be related to language service needs and practices specific to refugees, pediatric patients, and emergency medical settings. Through co-occurrence analysis of keywords, the focus of emergency language services research has changed in different periods. From a focus on emergency departments, communication, and language barriers during the exploration period, to a focus on natural language processing and language barriers in emergency medicine during the stable development period, and systematic reviews of previous research, to research on emergency language services, remote education and medical services, and the application of social media during the rapidly developing COVID-19 pandemic. This reflects the development trend and evolution of research focus in the field of emergency language services, while also revealing future research directions and challenges.

Literature co-word cluster analysis

This study employed co-occurrence cluster analysis to unveil intricate relationships between words in the literature, shedding light on the research content and patterns within current emergency language services research. By applying the co-occurrence clustering analysis method, many articles were successfully classified and organized based on their content, characteristics, and word co-occurrence. This approach has the potential to reveal nuanced topics and highlight potential connections within related literature, thus facilitating the identification of interdisciplinary research opportunities (Wang et al., 2016). By conducting an in-depth analysis of keyword frequencies, this paper successfully constructed multiple keyword co-occurrence networks. These networks vividly outlined the diverse landscape of emergency language services research. Figure 6 shows the co-word cluster network of emergency language services, generated using CiteSpace software. Notably, the analysis produced 10 distinct clusters, each offering valuable insights into specific facets of the emergency language services domain. The parameters are set as follows:

  1. (1)

    Slice Length = 1;

  2. (2)

    Selection criteria: g-index (k = 10), LRF = 3.0, L/N = 10, LBY = −1, e = 1.0;

  3. (3)

    Network: N = 429, E = 645 (Density= 0.007);

  4. (4)

    Pruning: Pathfinder;

  5. (5)

    Nodes labeled: 1.0%.

Fig. 6: Literature co-word cluster network.
figure 6

Nine large clusters of co-word in the field of emergency language services were generated by CiteSpace software. Each cluster is represented by a different color.

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Based on the parameters used, 15 clusters were identified. Figure 6 displays the top 10 of these clusters. From Fig. 6, it can be clearly observed that the symbiosis is visualized as a knowledge domain graph composed of ten keyword co-occurrence networks. Each of these networks is represented by a different color. To provide a clearer and more intuitive presentation of each cluster, Table 6 was created, which includes the labels, the number of keywords in each cluster, and some of the keywords contained in each cluster.

  1. (1)

    Cluster #0: emergency-medicine resident

Table 6 Overview of 10 clusters of emergency language services.
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This initial keyword cluster delves into the myriad challenges and complexities encountered by emergency medicine residents, specifically focusing on communication hurdles, language comprehension, and interactions with immigrant patients. The research within this cluster centers on resident physicians within the emergency medicine field, addressing various critical aspects:

  1. 1.

    Exploring communication challenges in emergency settings is urgent. This facet involves a thorough examination of the challenges and barriers that emergency medicine residents face in effectively communicating with patients. Noteworthy studies, such as those exploring emergency physicians’ awareness of language barriers within the emergency department environment (Hendry et al., 2012), contribute valuable insights into fostering improved communication strategies.

  2. 2.

    The exploration of health literacy levels is an important topic. Researchers within this cluster delve into how emergency medicine residents navigate patients’ health literacy levels. This includes investigating how emergency medicine residents address patients’ health literacy levels and potential obstacles in providing medical care, including issues related to patients’ understanding of diagnoses, treatment, and self-management abilities (Doty et al., 2022).

  3. 3.

    Addressing the unique challenges faced by emergency medicine residents when dealing with immigrant patients, including language barriers, cultural differences, and legal and policy-related issues, is necessary. For instance, assessing residents’ attitudes towards culturally competent care, their preparedness to provide quality care to diverse patient populations, as well as their experiences and educational environment regarding cross-cultural training (Betancourt et al., 2007). Additionally, exploring the approaches taken by emergency department physicians when facing unique barriers to accessing healthcare for undocumented residents (Samra et al., 2019).

The primary goal of these studies is to improve the communication skills of emergency medicine residents. Furthermore, they aim to foster a deeper understanding and trust between healthcare providers and patients, ultimately contributing to the delivery of enhanced medical services within emergency medicine settings.

  1. (2)

    Cluster #1: trial study design

This cluster primarily focuses on the application of experimental research designs in the field of emergency medicine. The research may involve evaluating health disparities among different populations (Cegala, Post (2006)) and understanding differences in health status, healthcare accessibility, or health outcomes among diverse populations to promote health equity and improve healthcare strategies targeting specific groups. It may also involve assessing the effectiveness of different medications, interventions, or acute asthma management approaches to study treatment methods and strategies for acute asthma (Press et al., 2012). Additionally, it may explore emergency department situations related to alcohol use (Vaca et al., 2020), such as examining the impact of alcohol-related incidents on emergency department visits, evaluating alcohol-related emergency interventions, or studying the health consequences of acute alcohol poisoning.

The main goal of this cluster is to advance the understanding of emergency medicine through robust experimental research designs. By assessing health disparities, differences in health status, and the efficacy of interventions, researchers contribute to the ongoing efforts to refine emergency medical practices and strategies. This cluster plays a pivotal role in shaping evidence-based approaches for diverse populations within emergency medicine contexts.

  1. (3)

    Cluster #2: review article

Cluster 2 is related to literature reviews, indicating that researchers at a certain stage focused on reviewing articles in the field of emergency language services. These reviews aimed to extract lessons learned and explore new research directions. The research within this cluster can be summarized into the following two aspects:

  1. 1.

    Clinical practices, diagnostic and treatment methods in the field of emergency medicine, and emergency medical systems and processes, are important research topics. For example, improving the analytical utility of clinical trial content by integrating data innovations to provide information for health disparity research (Cohen, Unangst (2018)). Systematically reviewing the differences in the usage of patient portals among vulnerable populations, with the aim of increasing the impact of interventions that promote portal use or predict factors associated with usage disparities (Grossman et al., 2019).

  2. 2.

    Emergency management in disaster situations, along with psychological well-being in emergency situations, deserves investigation. For example, Almukhlifi et al. (2021) conducted a comprehensive review of the literature on the perceived preparedness of emergency healthcare personnel for disaster management. The review revealed that most emergency healthcare workers appear to lack sufficient disaster preparedness, and past experiences and training have improved preparedness efforts. Future research should focus on interventions to enhance the preparedness of emergency healthcare workers for disasters. North, Pfefferbaum (2013) reviewed and summarized the evidence on how to best identify individuals in need of disaster mental health services and classify them into appropriate care. The aim is to provide a comprehensive understanding of the field of emergency medicine by synthesizing existing research and provide evidence for emergency medicine practice and policy-making.

This cluster, characterized by literature reviews, plays a crucial role in consolidating existing knowledge in emergency language services. By delving into clinical practices, diagnostics, treatment methods, and the broader spectrum of emergency management, researchers contribute to the synthesis of evidence. The outcomes of these reviews aid in informing and shaping the landscape of emergency medicine practices, paving the way for improved policies and strategic interventions.

  1. (4)

    Cluster #3: emergency call

Cluster 3 labeled “emergency call” is highly relevant to the field of emergency telephone services. The research on emergency language services within this cluster can include the following three points:

  1. 1.

    Analysis of emergency call data is a crucial theme. This involves examining the content and patterns of emergency calls to identify common issues, improve response protocols, and enhance emergency communication strategies. Researchers may investigate the relationship between emergency telephone services and patient mortality rates. For example, Cabrita et al., (2004) conducted a study on the impact of emergency medical service calls on the management of acute myocardial infarction. The study concluded that patients with symptoms of myocardial infarction underutilized emergency medical service calls and documented the beneficial effects of emergency medical service calls in reducing prehospital delays and increasing early reperfusion therapy.

  2. 2.

    Emergency telephone services provide medical support for non-healthy patients, such as those with dementia and heart failure. Research in this area includes Voss et al., (2018) qualitatively exploring the nursing experience of emergency medical services (EMS) nursing staff in dementia patients through focus groups and interviews, evaluating EMS staff’s views on dementia management. Jung et al. (2022) employed a descriptive qualitative approach to investigate 911 calls for EMS in cases of heart failure. Their findings suggest that interventions are needed to assist heart failure patients and their families in communicating more effectively during emergencies.

  3. 3.

    Emergency call response and quality assurance deserve significant attention. This includes investigating the effectiveness and efficiency of emergency call response systems, evaluating the quality of emergency services provided over the phone, and identifying areas for improvement in terms of language support and cultural sensitivity. For example, Penverne et al. (2019) reported on a strategy to reduce waiting time for emergency calls at dispatch centers. Through their research, they found that connecting dispatch centers can improve their performance, especially during periods of overload. This enables the prompt handling of emergency calls and appropriate dispatching of emergency medical services.

This cluster serves as a focal point for enriching the understanding of emergency language services within the realm of emergency telephone services. By dissecting emergency call data, addressing the medical support needs of non-healthy patients, and scrutinizing the efficiency of emergency call response systems, researchers contribute to the enhancement of emergency services, ultimately ensuring more effective and culturally sensitive outcomes.

  1. (5)

    Cluster #4: COVID-19 crisis

Cluster 4, denoted as the “COVID-19 Crisis”, is inherently tied to the challenges posed by the COVID-19 pandemic. During the COVID-19 crisis, researchers have explored the application of qualitative research methods in addressing the COVID-19 crisis. Qualitative research techniques mainly encompass the gathering and examination of data that is not expressed in numerical form, such as observations, interviews, and textual analysis. These methods aim to provide valuable insights into comprehending the COVID-19 crisis and evaluating response measures. Qualitative research in emergency language services can provide insights into various aspects of pandemic prevention and response measures (Wang et al., 2022), the involvement of social media in public health (Han et al., 2020), emergency online teaching (Adedoyin, Soykan (2023)), and remote medical services (Reza Safdari et al., 2021).

Furthermore, qualitative research provides researchers with an opportunity to gain an in-depth understanding of emergency language services. This includes exploring the experiences of participants such as translators, staff of translation service agencies, and service users, as well as examining service quality and effectiveness, the roles and practices of service providers, cultural and cross-cultural communication, and other aspects. Such research contributes to the improvement and optimization of emergency language service practices and policies to meet diverse language needs during emergency situations. When conducting qualitative research on emergency language services, methods such as focus group interviews and text analysis are commonly employed. For instance, the use of focus group interviews can facilitate discussions within a community to understand the importance of their surrounding environment, existing resources, and assistance. This engagement of the public helps in building resilient communities to minimize the impact of disasters (Nirupama, Maula (2013)). Regression text analysis, on the other hand, can be utilized to evaluate the quality and reliability of emergency language services and eliminate ambiguities in emergency response plans (Guo et al., 2020). These methods play a pivotal role in comprehending the diverse needs and challenges associated with emergency language services, ensuring accuracy, timeliness, and reliability in emergency situations. The insights garnered contribute not only to research advancements but also to the refinement of practices and policies in the broader landscape of emergency language services.

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    Cluster #5: pharmaceutical service

Cluster 5 is labeled “pharmaceutical service” and is highly relevant to pharmacy services in disaster and emergency situations. Additionally, researchers have also focused on the provision of pharmaceutical services within hospitals and issues related to healthcare inequalities. This may include studying the organization and management of pharmacy services within hospitals, the safety and efficiency of the pharmaceutical supply chain, and inequalities in accessing and utilizing pharmacy services among different populations. However, it is worth noting that the average year of research within this cluster is 1996, indicating that the studies related to pharmaceutical services in emergency language services are relatively earlier compared to other clusters.

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    Cluster #6: ethnic disparities

Cluster 6 is labeled “ethnic disparities”, and researchers focus on the differences among various ethnic groups in emergency language services, including variations in language needs, service access, and outcomes. Based on other keywords within the cluster, researchers also examine disparities among different ethnic groups in emergency language services related to stroke prevention, treatment, and rehabilitation, particularly in children. The aim is to improve the efficiency of treatment and rescue efforts and reduce the impact of diseases or disasters on physical health. For example, Flores, Ngui (2007) conducted a literature review to uncover several racial/ethnic disparities in pediatric patient safety and proposed a new conceptual model for understanding racial/ethnic disparities in patient safety. Lim et al. (2019) studied racial/ethnic disparities in the utilization of mental health services among Medicaid adults aged 21–64 in Hawaii. Hartford et al. (2022) explored differences in the treatment of pediatric migraines among different racial, ethnic, and language preference groups in the emergency department, highlighting another area where equity in emergency department patients must be improved.

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    Cluster #7: remote teaching

Cluster 7, denoted as “remote teaching”, primarily focuses on the realm of remote teaching in emergency situations, especially during the COVID-19 pandemic. Researchers within this cluster may concentrate on strategies for emergency remote teaching, online learning tools, teaching effectiveness, and the experiences of both students and teachers. For instance, Latif, Alhamad (2023) conducted a study by surveying 112 Arabic and English as a foreign language teachers and conducting semi-structured interviews with 14 teachers. The research investigated the experiences and reflective beliefs of Saudi university language teachers in emergency remote teaching, with specific attention to: a) the general educational challenges faced by teachers and how they overcome these challenges, b) the perceived difficulties of remote teaching and assessing the foreign language domain and their coping strategies, and c) a reflective evaluation of remote language teaching after three semesters. Wang et al. (2022) explored the positive emotions and language enjoyment of Chinese language learners in the context of emergency remote teaching (ERT) during the COVID-19 pandemic, adopting a positive psychology perspective. Knežević et al. (2022) surveyed the teaching practices and experiences of foreign language teachers during the “lockdown period” in 2020, as well as their self-assessment of their digital technology application skills in teaching. The results indicated a lack of pedagogical knowledge and skills among foreign language teachers in utilizing the mentioned tools in teaching. Consequently, the authors called for more attention to digital technology teaching issues in foreign language methodology courses.

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    Cluster #8: emergency department visit

Cluster 8 “emergency department visit”, combined with other keywords in the cluster, indicates that this cluster may focus on applying techniques such as natural language processing, machine learning, deep learning, and nursing informatics to process and analyze data related to emergency department visits. For example, Doan et al. (2016) attempted to create and test the performance of the Natural Language Processing (NLP) tool KD-NLP to identify emergency department (ED) patients who should be considered for diagnosis as Kawasaki disease Lee et al. (2019) provide an overview of machine learning related to clinical and operational scenarios in emergency medicine.

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    Cluster #9: systematic review

Cluster 9 centers on research involving systematic reviews and meta-analyses of specific topics or issues. Systematic review is a research method designed to systematically collect, evaluate, and synthesize existing literature to answer specific research questions. Meta-analysis, on the other hand, is a statistical analysis method within systematic reviews that involves the reanalysis and synthesis of existing statistical data from studies on a particular topic.

Through systematic review and meta-analysis, researchers can synthesize and analyze a large amount of research evidence on emergency language services, thereby obtaining more comprehensive and reliable conclusions and providing support for decision-making, policy formulation, and further research. For example, Iqbal et al. (2021) evaluate the evidence of clinical outcomes of digital alert systems in remote monitoring through system reviews and meta-analyses and call for trials of different alert protocols to understand the best alerts to guide future widespread implementation. This will further promote the development of emergency language services.

Discussion

This study conducted bibliometric and content analysis on 3814 items of literature retrieved from 1988 to 2023. Furthermore, it proposed several crucial research indicators, encompassing basic analyses of publication time and quantity, notable journals, primary research contributors (authors, countries, and institutions), disciplinary direction analysis, and co-occurrence clustering of keywords. Overall, the literature in the field of emergency language services research is constantly increasing, indicating that researchers’ interest in the field of emergency language services is gradually increasing.

Research trend

In addressing RQ 1: What is the current status of emergency language services research, and what progress has been made in recent years? Section “Publications output distribution” analyzes the current status and latest progress of research on emergency language services. The examination of published literature suggests a progressive rise in the number of research journals dedicated to emergency language services, indicating a growing trend toward diversification within the field. This phenomenon can be attributed to the fact that natural disasters and public health events impact countries worldwide to different extents, such as the Lushan earthquake in China in 2013 (Lu et al., 2014), the East Japan earthquake in 2011 (Onuma et al., 2017), the Christchurch earthquake in New Zealand and the Bangkok flood in Thailand (Noy, 2015), the novel coronavirus pandemic in 2019 (Wang et al., 2020) and the Ebola epidemic in West Africa in 2014–2016 (Agnihotri et al., 2021), Hurricane Katrina along the Gulf of Mexico in the United States (Kahn, Barondess (2008)), etc. Faced with numerous natural disasters and sudden public health emergencies, scholars from various countries have gradually enhanced the significance of research on emergency language services. Nevertheless, the multidisciplinary nature of emergency language services and the wide range of disciplines involved have contributed to a diverse trajectory of development. This emphasis on the advancement of emergency language services from various fields has fostered a diversified overall direction of progress.

Research power

Section “Research power results” analyzes the distribution of core authors and national institutions in emergency language service research, addressing RQ 2: What is the distribution of core authors, journals, and institutions involved in emergency language services research? An examination of research influence reveals that countries such as the United States, Canada, the United Kingdom, and Australia hold significant positions in publishing papers on emergency language services. Notably, the United States stands out with its dominant presence in terms of article output and centrality within the field. Institutions such as the University of Washington, Harvard Medical School, and the University of California, San Francisco, have a high research impact in the field of emergency language services. First, these countries have large populations, vast lands, and high rates of natural disasters and public health events. In this case, fast and accurate information transmission is crucial to ensure the safety of people’s lives and property. Modern technology provides a more powerful guarantee for emergency communication, effectively improves the efficiency of post-disaster emergency rescue work, and achieves good disaster reduction effects. These countries, owing to their robust economic and technological capabilities, as well as well-developed communication and information technology infrastructure, have shown a heightened focus on emergency management and response. Their ability to efficiently collect, process, and disseminate vast quantities of real-time emergency information enables them to effectively meet public demands and facilitate advancements in emergency language service research.

Research content

Section “Content analysis” mainly addresses RQ 3: What are the hotspots of emergency language services research, and what are the prospects for the field in the future? This part examines the multidisciplinary nature of emergency language services and explores the current research trends and focal areas within the field. By examining disciplinary categories, highly cited topics, and research directions, the disciplinary, theoretical bases of emergency language services mainly concentrate on emergency medicine, environmental science, public health and preventive medicine, computer science, educational science, and language and linguistics. However, the research focus varies across each field. The field of emergency medicine is more focused on optimizing the collaboration in emergency medicine research (Perry et al., 2021), language support in emergency medical facilities, medical translation, and interpretation services in emergency situations, etc. For example, it explores the application of mobile technology in medical interpretation (Ji, 2019). Environmental science mainly focuses on the language exchange of environmental information and risk communication in emergency events, language support for emergency environmental monitoring and data processing, etc. For example, in order to improve the efficiency of emergency rescue, the coal mine emergency rescue communication system based on a wireless mesh network and environmental monitoring subsystem is tested (Zhao, Yang (2018)). The research focuses on the field of public health and preventive healthcare science may include health information dissemination and education in emergency situations, multilingual emergency warning systems, and cross-cultural adaptation of emergency medical resources. The field of computer science primarily focuses on researching machine translation, such as evaluating two specific automatic translation techniques to assess their potential impact on improving communication in emergency situations (Turner et al., 2019), applying natural language processing, speech recognition, and intelligent language services. For example, the development of speech recognition technology in emergency calls (Valizada et al., 2021) provides online language support and emergency language services for medical translation services. The field of educational science focuses on training medical translators and interpreters, conducting cross-cultural communication, and education in emergency situations.

In terms of keyword clustering analysis, this paper elaborates on the three stages of emergency language service development to better understand its research progress. Firstly, during the exploration period, focus on emergency departments, communication, and language barriers. How should medical staff effectively communicate with patients in the emergency department when facing situations such as non-native language communication, hearing or speaking difficulties, or cultural differences between doctors and patients.

Secondly, during the stable development period, attention should be paid to natural language processing, language barriers in emergency medicine, and a systematic review of previous research. By conducting a systematic review of previous research, researchers can gain a comprehensive understanding of the current situation and development trends in the field of emergency language services, identify knowledge gaps and research challenges, and propose new research questions and directions to promote further development in the field of emergency language services. Moreover, with the continuous development of artificial intelligence (AI) technology, researchers have begun to combine some AI technologies, such as natural language processing technology, with emergency language services, to apply in emergency rescue and emergency medical care, to improve the efficiency and accuracy of language barrier handling, and make up for the shortcomings of human translation and interpretation.

Finally, during the rapid development period, attention should be paid to research on emergency language services, remote education, and medical services, as well as the application of social media during the COVID-19 pandemic. The outbreak of the COVID-19 epidemic has had a significant impact on the world. During COVID-19, emergency services such as distance learning and telemedicine developed rapidly. At the same time, social media plays an important role in information dissemination and crisis notification, multilingual support and translation services, and strengthening community cooperation. For example, Twitter is widely used in emergency situations to issue real-time emergency notifications and alerts. Many government agencies and emergency management departments use Twitter to release key information to the public, including disaster alerts, evacuation guidelines, safety tips, etc. This rapid and extensive dissemination of information helps people to promptly understand emergency situations and take appropriate action.

Emergency language services domain research shortcomings

To facilitate the disciplinary development of emergency language services research, this article presents a comprehensive synthesis of research findings and methodologies, with the goal of identifying the current limitations and shortcomings within the field.

Firstly, the analysis conducted in this paper highlights the interdisciplinary nature of emergency language services as a research field. Given the interdisciplinary nature of the subject matter, it is crucial to emphasize the comprehensive development process within this field. In the face of interdisciplinary content, it is needed to pay attention to its comprehensive development process. Currently, due to variations in disciplinary nature, there is often a tendency to overlook the holistic management of emergency information resources or the cross-disciplinary sharing of practical cases. For example, computer science can apply natural language processing technology to medical education (Chary et al., 2019), which can advance potential future work in the field of emergency medical education. However, the applicability of research results of these interdisciplinary theories in innovation still needs to be further increased.

Secondly, natural disasters and public health incidents often occur suddenly, and emergency rescue is extremely urgent. Therefore, the provision of emergency language services is also very urgent. Although current emergency translation technology and interpreters have made significant contributions to emergency language services, there are also significant limitations. For example, in remote areas lacking professional interpreters and basic communication facilities, hiring nonnonprofessional interpreters such as hospital employees and family members may bring great risks and cause serious medical accidents (Kletečka-Pulker et al., 2021). Therefore, it is necessary to further study the technological progress and practical application of emergency language services, and cultivate more professional interpreters.

Finally, the article focuses on the research focus of the three stages of emergency language services. At present, there are many applications of intelligent technologies related to emergency language services, such as natural language processing technology in emergency departments, the use of video interpretation systems during emergency rescue, and AI translation software. However, further exploration is needed to explore the differences, advantages, and disadvantages of various AI technologies in different application scenarios, and there is a lack of relevant literature. Besides, given the increasing use of AI in emergency language services, it is essential to consider the ethical implications of these technologies. Moral considerations arise, such as whether to use AI over live interpreters when cost-saving could compromise the quality of communication and patient care. The disparity in access to interpreters based on language prevalence raises equity concerns, particularly for less common languages like Karen. Rigorous testing is needed to validate the effectiveness of AI solutions for rare languages in real-world emergency scenarios to ensure they do not perpetuate disparities and meet ethical standards. Despite the challenges, the ongoing advancement of knowledge and technology will give rise to novel theories and technologies that can effectively address practical applications.

Prospects for emergency language services

To address the identified shortcomings, three targeted recommendations are proposed:

Firstly, emergency language services have interdisciplinary nature, therefore, it is necessary to strengthen cooperation and knowledge sharing between different disciplinary fields. Encourage experts in computer science, medicine, linguistics, and other fields to conduct collaborative research, promote the cross-application of technology and theory, and promote the comprehensive development of emergency language services.

Secondly, cultivate more professional interpreters and translation experts to meet the emergency needs of various situations. In addition, the efficiency and accuracy of emergency translation technology should be further improved to address translation errors caused by equipment issues.

Finally, it is necessary to explore the advantages and limitations of intelligent technology in different application scenarios, evaluate the applicability of different intelligent technologies in emergency language services, and select the most suitable technical solution based on specific circumstances. Simultaneously, active development of emergency language service technologies should be pursued, exploring the applications of technologies such as speech recognition, machine translation, and real-time video communication in emergency response.

Potential areas for future research on emergency language services

In outlining future research directions for emergency language services, this study identifies three key potential areas.

Firstly, the frequent occurrence of natural disasters has highlighted the increasing demand for emergency language services. At present, there are existing deficiencies in emergency rescue auxiliary equipment, and emerging technologies have the potential to provide essential assistance in addressing various challenges encountered during emergency rescue operations. As an example, within the healthcare domain, the application of AI algorithms and natural language processing techniques can play a critical role in identifying syncope patients within medical records of emergency departments (Dipaola et al., 2019). Further exploration by researchers is needed to determine how to effectively apply these state-of-the-art technologies to the field of emergency language services.

Secondly, it has been proven that social media platforms are effective in collecting information during emergencies caused by natural or man-made disasters (Khatoon et al., 2021). In the event of an emergency, emergency response managers need to respond quickly and handle the victim’s request for help. Citizens will use Internet social media to quickly disseminate information about the development of events, but for emergency response managers, it is difficult to select the most relevant information from a large number of data (Overbey et al., 2015). Therefore, it is crucial to study the application of straightforward natural language processing techniques to extract location information from social media networks and search for event-related messages. This research can greatly assist emergency response managers in making timely and accurate decisions (Nieuwenhuijse et al., 2016). For instance, by studying and comparing various machine learning models for the correlation classification of flood-related tweets, it becomes clear which machine learning-based method is most suitable for the correlation classification of flood-related tweets. This can assist emergency rescue personnel in identifying more effective disaster management information (Blomeier et al., 2024). In addition, text analysis techniques, machine learning (ML), and deep learning (DL) techniques can also be applied to automatically filter and analyze social media data in order to extract real-time information about key events and promote emergency response in crises (Khatoon et al., 2021).

Lastly, language models are assuming a progressively significant role in the domain of emergency language services. The current language models include acoustic and language models for automatic speech recognition, neural network language models, and multilingual speech recognition systems, which are widely used in medical emergencies and emergency rescue. For example, because of its advanced natural language processing capabilities, ChatGPT has become a tool that continues to evolve and advance in the ability to assist healthcare information. The study evaluated the accuracy of ChatGPT-3.5 and ChatGPT-4 models in solving queries related to CRRT alarm troubleshooting (Sheikh et al., 2024). Ungureanu et al. (2023) explore the use of automatic speech recognition models to enhance Romanian emergency services and reduce their response times. Future speech models will also have more breakthroughs and developments in the field of emergency language services.

Conclusions

This article conducts a comprehensive analysis of 3814 papers published between 1988 and 2023 on emergency language services using CiteSpace. The analysis aims to shed light on the research progress and future directions in this field. Analysis shows that there is an increasing number of published literature on emergency language services, and researchers are increasingly interested in researching emergency language services. The sources of disciplinary theory for emergency language services mainly concentrate on emergency medicine, environmental science, public health and preventive medicine, computer science, educational science, and language and linguistics. The findings of keyword clustering analysis demonstrate that current research in emergency language services leverages emerging technologies, such as natural language processing, language modeling, and machine learning. These technologies are utilized to expedite emergency response time and improve the quality of emergency services. In addition, there are also methods such as telemedicine and remote teaching to address emergency situations. Other cutting-edge areas include the adaptation and development of interdisciplinary methods for emergency language services, as well as the analysis of the important role of social media in the field of emergency language services.

Future research in emergency language services should focus on addressing pivotal issues related to research frameworks, fostering interdisciplinary and comprehensive development, and comprehending significant advancements in emerging technologies within the field. Of particular importance is the vast potential offered by social media and AI in supporting emergency language services.

This study provides a comprehensive analysis of the scope of emergency language services for research purposes. Nonetheless, it is important to acknowledge certain limitations. Specifically, this paper predominantly relies on the WoS core database and does not encompass other significant databases like Scopus and PubMed. In addition, this study is limited to the analysis of English papers and does not cover literature in other languages. Due to language limitations, this study may not be able to obtain or analyze relevant research results in other language contexts. Future research can consider expanding the language scope to include literature in more languages, to gain a more comprehensive understanding of the development and trends in the field of emergency language services.