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Article

Exploring Lexical Bundles in the Move Structure of English Medical Research Abstracts: A Focus on Vocabulary Levels

1
Department of Foreign Languages, Faculty of Medicine, Osaka Medical and Pharmaceutical University, Takatsuki 569-8686, Japan
2
Department of Regenerative Science, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama 700-8558, Japan
*
Author to whom correspondence should be addressed.
Languages 2024, 9(9), 281; https://doi.org/10.3390/languages9090281
Submission received: 1 May 2024 / Revised: 5 August 2024 / Accepted: 18 August 2024 / Published: 23 August 2024

Abstract

:
Research article abstracts, the second most-read part of research papers after titles, generally follow disciplinary conventions, which are often manifested in their language use. This study analyzed lexical bundles or multi-word sequences in move texts of a one-million-word corpus of English-language medical research article abstracts, with particular attention to vocabulary levels. The most frequent lexical bundles, such as “the primary end point was”, often occurred once per text and predominantly took part in realizing a move. The coverage of the first thousand New General Service List was 63.6% for the entire corpus but was around 80% for bundles in Move 3, describing principal results, and those in Move 4, evaluating the results. Many of the sequences were research-oriented bundles, used to express research contexts. The bundles were made up of relatively accessible word items, but the sequences occurred to realize highly specific research contexts. The findings suggest that becoming familiar with the bundle may need increasing awareness of disciplinary conventions such as guideline adherences and statistical procedures. This study may offer insights on the need for learners to familiarize themselves with these bundles.

1. Introduction

In an era where information floods every aspect of academic and professional life, understanding the conventions of academic writing genres, including textual and vocabulary features, is essential (Swales 1990; Bhatia 2019; Coxhead 2020). Over the past 50 years, the academic landscape has undergone unprecedented changes, marked by a substantial increase in the number of academic papers (Hyland and Jiang 2019). This rapid growth leads to a need for learners, especially medical students, to become proficient in reading and writing research article abstracts because of the specialized nature of their disciplinary texts (Coxhead 2016; Dang 2020; Simpson 2022; Tang and Liu 2019).
Functioning as an academic, especially in English, entails engaging in a sophisticated activity framework of communication practices, particularly when constructing and disseminating scientific claims (Belcher 2016). In this system, language plays a pivotal role in forging consensus and persuading the target discourse community, a group of individuals with shared goals (Swales 1990). Academic discourse is navigated through genre texts, which are types of spoken or written texts used for specific communicative purposes (Hyon 2018, p. 3).
Written communication can be distinguished by differences in audience, purposes, content, form, style, and context (Robinson et al. 2008). Academic written language is known to be differ from academic spoken language, particularly from a vocabulary perspective (Dang et al. 2017; Coxhead and Dang 2019). Students, particularly those learning English as an additional language (EAL) need to learn the genres and conventions commonly used by community members (Brooks et al. 2023; Samraj 2016; Flowerdew 2000). This mastery is the focus of English for academic purposes (EAP) research. EAP research has two main pillars: analyzing genre-specific texts to identify communicative functions and structures (Samraj 2016), and vocabulary studies (Coxhead 2016). Both aim to aid learners’ academic development (Hyland 2016).
EAP research often involves constructing corpora to facilitate these analyses (Handford 2010). One of the central pillars of this research is genre analysis (Swales 1990). The other main pillar of EAP research, vocabulary studies, also employs corpus linguistics techniques (Nation 2005). As Storch et al. (2016) indicated, approaches to EAP are influenced by various factors, including differences in higher education systems across countries. Therefore, research-based instruction integrating multiple approaches is recommended (Hyland 2016; Storch et al. 2016). In this context, linking vocabulary quantification with rhetorical moves has been attempted by several studies (Cortes 2013; Mizumoto et al. 2017; Qi and Pan 2020; Casal and Kessler 2020). These studies illustrate the importance of combining move analysis and vocabulary studies to shed light on the features of disciplinary texts. However, to our knowledge, studies examining the vocabulary levels of word items in lexical bundles within the moves of abstracts have been scarce. Therefore, this study aimed to examine lexical bundles across moves in disciplinary research article abstracts with a focus on the vocabulary levels.

2. Literature Review

2.1. Move Analysis

As a key element of genre analysis framework, move analysis is “a text analytical method developed by Swales in 1981” (Moreno and Swales 2018, p. 40). Moves, as defined by Swales (2004, pp. 228–29), are “discoursal or rhetorical units performing coherent communicative functions in texts”, exhibiting variability in length and other features. The “revised Create a Research Space (CARS) model” (Swales 1990, p. 140), preceded by “a 4-Move Schema” (Swales 1981, p. 15), provides an analytical approach to understanding the structure of research article introductions. Swales (2004) refined the CARS model to include distinct move structures: “Move 1 Establishing a territory”, “Move 2 Establishing a niche”, and “Move 3 Presenting the present work” (pp. 230–32). These moves, denoting their communicative purposes, can be segmented into “Steps” (Swales 2004, p. 230) that realize “functional components” (Tankó 2017, p. 43). The move analysis approach has been applied extensively to examine research articles as a whole (Kanoksilapatham 2005; Maswana et al. 2015; Mizumoto et al. 2017; Nwogu 1997; Stoller and Robinson 2013) and abstracts (Hyland 2000; Kanoksilapatham 2009; Pho 2008; Salager-Meyer 1991, 1992; Tankó 2017) in various disciplines, including medicine.

2.2. Vocabulary Studies

Teaching common words in specific contexts helps learners effectively improve their vocabulary (Nation 2001). In support of learners, various word lists have been developed from collections of specialized texts (Browne 2013; Coxhead 2000; Coxhead and Hirsh 2007; Fraser 2007; Tang and Liu 2019; Wang et al. 2008). An early example is Thorndike’s word book for instructors (Thorndike 1921), which was later updated by Thorndike and Lorge (1944). The General Service List (GSL; West 1953) was subsequently compiled after extensive international discussions before and after World War II (Gilner 2011). Developed from a five-million-word corpus, the GSL is tailored for ESL/EFL learners and is organized into two groups of word families (Coxhead 2000). The GSL has frequently been used as a basis for developing other word lists, including the Academic Word List (AWL) of 570 word families prepared by Coxhead (2000).
Many studies utilize the GSL and AWL to develop specialized word lists. Coxhead and Hirsh (2007) created “the pilot science corpus” (p. 70) from textbooks and discipline-specific reading materials to compile a word list covering items not included in the GSL or AWL. Fraser (2007) quantified the vocabulary required by pharmacology students and compiled the Pharmacology Word List (PWL) from international pharmacology journal articles. Wang et al. (2008) investigated key medical vocabulary to support curriculum design and learning objectives and created a Medical Academic Word List (MAWL). To support medical students, Quero and Coxhead (2018) also compiled word type lists based on their medical corpora, which included texts from medical textbooks. These studies are just a few examples of the many that have used the GSL and AWL to examine the features of their corpora.
While the original GSL has been a foundational tool in language learning over 50 years, it has faced some criticism in recent time (Green and Lambert 2018). The approach of utilizing word families in the GSL and AWL has been the subject of some debate among researchers (Gardner and Davies 2014). In response to these discussions, the New General Service List (NGSL), developed by Browne and his colleagues (Browne 2013), was designed as a modern update of the original GSL. Consisting of 2801 high-frequency words with a clearer definition of a “word” and a higher coverage of general English (Dang and Webb 2016), the NGSL is viewed by some researchers as more suitable for EAL learners (Mizumoto et al. 2021). It has been suggested that EAL undergraduates may find the NGSL to offer a slightly easier learning curve, potentially making it more appropriate for learners compared to the GSL (Culligan 2019). Subsequently, the New Academic Word List (NAWL), consisting of 963 words, was developed to align with the NGSL along with other specific purpose word lists targeting mid-frequency range vocabulary. It is reported that the NGSL and the NAWL combined offer an average of 92% coverage of academic texts and lectures (Browne 2021, p. 4). These updates reflect ongoing efforts to improve vocabulary learning tools for English language learners.

2.3. Lexical Bundles

In vocabulary studies that support learning academic texts, research on multiword units, often referred to as ”lexical bundles”, is also significant (Nation 2022, p. 454). Corpus-based studies have identified these lexical bundles (Samraj 2016). The term lexical bundles is defined as “sequences of word forms” (Biber et al. 1999, p. 990) that occur frequently across texts, characterizing a genre or discipline. This concept has gained prominence in corpus linguistics research (Biber et al. 1999; Cortes 2004, 2013; Hyland 2008a). Lexical bundles have been studied extensively for helping learners develop a repertoire that is sensitive to disciplinary norms (Hyland 2012, p. 17).
A study by Cortes (2013) associated the identification of lexical bundles and rhetorical analysis of moves and steps in research article introductions. This approach has contributed to revealing essential relationships between forms and functions (Gray et al. 2020, p. 139), showing the values of prefabricated word sequences (Biber et al. 2004, p. 376) within the linguistic contexts that constitute “communicative events” (Swales 1990, p. 9).
Following Cortes (2013), several scholars have observed move-specific bundles (Mizumoto et al. 2017; Omidian et al. 2018; Qi and Pan 2020). Mizumoto et al. (2017) observed 25 moves across 1000 research articles as a whole in applied linguistics, identifying frequently occurring lexical bundles in each move. Omidian et al. (2018) identified lexical bundles in each move in research article abstracts from six disciplines such as mechanical engineering, physics, and applied linguistics. Their study has shown a marked difference in the frequency of bundles across disciplines, suggesting that researchers from different fields prioritize different aspects when presenting their work in academic abstracts (Omidian et al. 2018, p. 12). Qi and Pan (2020) performed move analysis according to Hanidar’s (2016) four-move structure and extracted lexical bundles, suggesting the role of lexical bundles in achieving the communicative goals of rhetorical sections.
These bundles, also known as “multi-word sequences” (Biber et al. 2004, p. 373; Mizumoto 2015, p. 30) or “recurrent word combination” (Chen and Baker 2010, p. 31), and synonymous with “n-grams” (Mizumoto 2015, p. 31; Stubbs and Barth 2003, p. 61), play a crucial role in the structure of discourse. These bundles often encapsulate shorter sequences, such as three-word bundles, within their four-word structures (Cortes 2004, p. 401; Hyland 2008a, p. 6). Although Stubbs and Barth (2003) question the status of n-grams as linguistic units and refer to them as “chains of word-forms” (p. 62), they acknowledge that these recurring sequences typify specific text genres. Traditionally, studies have focused on the prevalence of four-grams in academic writing, with phrases like “as a result of” and “in the context of” serving as organizers of specific texts (Cortes 2013, p. 34).
Hyland (2008a, p. 6) has shown that frequency counts “drop dramatically” when quantitating five-grams compared to four-grams, stating that “many four and five word strings” share three-grams. Cortes (2024, pp. 120–21) discusses “potential overlaps” such as the five-gram “as a result of the” extending beyond shorter sequences like “as a result”. Furthermore, Hyland and Jiang (2019, p. 110) have demonstrated that longer strings, such as the five-gram “at the beginning of the” which extend beyond the four-gram “the beginning of the” may offer deeper insights into the pedagogical applications of lexical bundles. Golparvar and Barabadi (2020, p. 6) analyzed “phrase frames” (p-frames; Cortes 2024, p. 105) in the discussion section of research articles and suggested that five-word p-frames could often be “more specific to a particular genre” compared to four-word p-frames. The most frequently occurring five-word p-frame was “are * likely to withdraw”, with fillers such as “less” and “more”, while the leading four-word p-frame was “the * of technology”, with fillers such as “use” and “adoption”. Liu and Chen (2022) have shown that five-word and six-word p-frames in university lectures reveal knowledge-disseminating and content-oriented features. Casal and Kessler (2020), who studied frequent p-frames in grant applications, demonstrated a strong association between the writers’ use of five-word p-frames and their rhetorical intentions. Using a bundle-driven approach, Li et al. (2020) found that five-word bundles contributed to identifying moves of PhD abstracts. These findings indicate that extended sequences such as five-grams may be useful for genre-specific language use and potentially provide linguistic patterns beneficial for learners.

2.4. Medical Research Abstracts

Abstracts are the most-read texts in a research paper, second only to titles, and serve as a vital standalone tool of communication (Hyland 2000). Scientists increasingly rely on abstracts as “short, concise, complete, and accurate sources of information” (Salager-Meyer et al. 2014, p. 222). Research paper abstracts act as “advance indicators of the content and structure of the following text” (Swales 1990, p. 179) and encapsulate the key findings of the research (Huckin and Olsen 1983, p. 359).
Structured abstracts have become the norm in medical literature, largely because of long-standing endorsements by journal editors, such as those from the International Committee of Medical Journal Editors (ICMJE) since 1993 (Salager-Meyer et al. 2014, p. 223). Salager-Meyer (1991) noted that among 77 medical research article abstracts, half were deemed “poorly structured” in adherence to “the Introduction, the Methods, the Results, and the Discussion (IMRAD) pattern” (p. 528). While Anderson and Maclean (1997) examined “unstructured abstracts” (p. 2) of medical article abstracts and identified a five-move structure, including an optional background, along with the purpose, method, results, and conclusion, Hanidar (2016), analyzing abstracts from various disciplines including medicine, advocated for a four-move structure, comprising “Move 1: Creating a research space, ” “Move 2: Describing research procedure”, “Move 3: Summarizing principal results”, and “Move 4: Evaluating results”. This four-move approach aligns with our corpus texts structured according to the journal’s guidelines. The studies of structured abstracts, notably by James Hartley, highlights the benefits of structured texts over traditional formats (Hartley 1993, p. 90). Hartley (1999, 2003) argued that structured abstracts, already used in medicine, could be “appropriate for applied ergonomics” (1999, p. 535) and could be “introduced into psychology journals” (2003, p. 366). His extensive work on structured abstracts was comprehensively reviewed by Zhang and Liu (2011), who have underscored “the advantages of structured abstracts over traditional ones” (p. 575).
In medical research publications, articles are often categorized by study design and must meet the requirements of specific reporting standards (Millar et al. 2019; Stosic 2022). High-quality reporting is facilitated by over 616 standardized reporting guidelines from the EQUATOR Network (2024), up from around 400 different sets (Millar et al. 2019, p. 150). Failure to adopt the guidelines may cause a manuscript to be regarded as inferior in quality by the ICMJE (Millar et al. 2019, p. 141). The ICMJE (2024) aims to enhance the quality and transparency of medical reporting. Their recommendations are broadly “accepted by biomedical journals” (Luo and Hyland 2019, p. 39) and play a crucial role (Millar et al. 2012, p. 393) in shaping the research writing standards. These initiatives appear to accelerate the standardization of research writing (Swales 2017, p. 249).
While there are no specific guidelines on language use (Stosic 2022), medical abstract conventions have been studied from the perspective of linguistic features. Salager-Meyer (1992) analyzed 84 medical abstracts and revealed the choice of verb tense and modality associated with rhetorical functions. Abdollahpour and Gholami (2018) gathered 1800 medical article abstracts from various journals. They identified four-word lexical bundles and classified them into general and technical groups by two qualified raters (Abdollahpour and Gholami 2018). Nam et al. (2016), who aimed to reformat unstructured abstracts into the IMRAD format, have found that linguistic features such as a five-word sequence “aim of this study was” would improve the effectiveness of abstract sentence classification. These studies have contributed to understanding the textual features of medical research article abstracts.

2.5. Application of Move Analysis and Vocabulary Research

Most recent studies have integrated move analysis and vocabulary research to envisage academic writing instruction (Casal and Kessler 2020; Li et al. 2020; Qi and Pan 2020). As a practical application, Mizumoto et al. (2017) developed an academic writing support tool called the “Academic Word Suggestion Machine (AWSuM)”. AWSuM integrates move analysis with lexical bundle analysis. John Morley’s (2023) “The Academic Phrasebank” serves as a general resource for academic writers. It offers examples of phraseological components organized according to the main sections of a research paper or dissertation. This integrated approach is particularly beneficial for EAL learners. For instance, first-year medical students are shown to have difficulties in reading medical research abstracts (Shimizu 2019). It was pointed out that the boundary of methods and results sections is hard to identify when the learners face sentences like “Of the 19,114 persons who were enrolled in the trial, 9525 were assigned to receive aspirin and 9589 to receive placebo” (Shimizu 2019, p. 85). These findings echo Tardy and Jwa’s (2016) observations about the challenges of learning academic writing within a discipline, suggesting the importance of integrating genre and vocabulary research for future instructional practices.

3. The Current Study

The purpose of this study was to investigate the vocabulary levels of medical research article abstracts, especially lexical bundles across moves in disciplinary research article abstracts. This study identified lexical bundles across moves of research article abstracts and used the New General Service List (NGSL; Browne 2013) for examining the vocabulary levels of word items in the move texts and lexical bundles across moves. Our study poses the following research questions:
  • Research Question 1: Which lexical bundles occur most frequently in specific moves within medical research abstracts?
  • Research Question 2: What are the language features of lexical bundles across moves in medical research abstracts, such as the coverage of the NGSL, forms, and functions?

4. Data and Methods

4.1. Corpus

The data used in this study contain abstracts from the original research articles published in the years 2002–2020 in The New England Journal of Medicine (Table 1). These abstracts were selected for their “representativity, reputation, and accessibility”, according to Nwogu’s (1997, p. 121) criteria. The journal’s articles are also valued for providing regional students with essential insights into evaluating medical literature (Ogawa 2014) and understanding the practical use of language in medical writing (Jego 2012). Additionally, the journal provides official translations in the local language (Nankodo 2024).1
Each article was segmented into individual sentences. Drawing on the studies by Cortes (2013, p. 36), who identified lexical bundles in research article introductions and mapped them to specific rhetorical moves, and Mizumoto et al. (2017, p. 902), who concentrated on extracting “move-specific lexical bundles”, we segmented our corpus by sections (moves). For move identification, we adopted the methodology of Qi and Pan (2020), dividing our corpus texts “based on their own headings” (p. 112)—Background, Methods, Results, and Conclusions—to create subcorpora “Move 1: Creating a research space”, “Move 2: Describing research procedure”, “Move 3: Summarizing principal results”, and “Move 4: Evaluating results” according to Hanidar (2016, p. 14). This four-move approach aligns with our corpus texts structured according to the journal’s guidelines (The New England Journal of Medicine 2024).
The abstract texts had 1,148,583 words, as determined using AntConc (Version 4.2.4; Anthony 2023).2 The number of words in each text was quantitated using CasualConc (Version 3.0.8; Imao 2024) and was visualized using Google Colaboratory’s Python environment (Version 3.10.12). The average word count of the abstracts was 303 words, with a standard deviation of 44 words. The distribution of abstract word counts showed that 50% of the texts fell between 273 and 332 words, with a median value of 299 words (Figure 1). These findings indicate a relatively consistent length across the corpus texts.
The most frequent words in the medical research abstract corpus included many function words, with the and of ranked the first and second (Table 2). The top 100 words accounted for over 51% of the texts (Table 3). These findings suggest that a limited set of words were quite frequently used for presenting research information. Furthermore, frequent instances of these function words and the scarcity of specialized terms suggest that studies on diverse topics were reported using similar basic vocabulary.
For the analysis with the NGSL (Version 1.01, Browne 2013) and NAWL (Version 1.01, Browne et al. 2013), we used a corpus tool, CasualConc (Imao 2024). The NGSL comprises a total of 2801 words. Separate lists categorizing the top 1000 words by frequency (first NGSL), the next 1000 words (second NGSL), and the remaining 801 words (third NGSL) were available from the AntWordProfiler website (Anthony 2024) as a resource for vocabulary profiling. In addition, a supplementary list of 174 basic words, which were not included in the aforementioned three lists, and the NAWL, consisting of 963 words, were also downloaded from the same site. By combining these five lists cumulatively, the following four stopword lists were created and imported into CasualConc for coverage analysis.
  • First NGSL + Supplement
  • First NGSL + Second NGSL + Supplement
  • First NGSL + Second NGSL + Third NGSL + Supplement
  • First NGSL + Second NGSL + Third NGSL + NAWL + Supplement
Using the stopword function of CasualConc, the word items in the lists were applied to automatically remove the target items in the preparatory step (Sarica and Luo 2021). To determine the covered word count, the word count after removal was subtracted from the total word count of the texts using Microsoft Excel (Version 2406). This procedure was repeated using the aforementioned stopword lists one by one, and the results were visualized using Python 3.10.12 in the Google Colaboratory environment (Figure 2).
The first 1000 words plus the supplementary 172 words covered 63.6% of the entire corpus, 71.1% with the first 2000 words, and 75.6% with the addition of the remaining 801 words. The NAWL yielded an additional 5.1% coverage, reaching a total coverage of 80.7%.
The comparison with previous studies showed that while the NGSL and NAWL provided greater coverage in other texts, they did not cover as much of our medical research article abstract corpus. The 2801 high-frequency words from the NGSL provided between 95% and 97% overall text coverage of English reading passages of Japan’s national university entrance examination from 2015 to 2019 (MacDonald 2019, p. 22). The NGSL and NAWL combined to provide an average coverage of 84.8% of a 7.8-million-word civil engineering research article corpus (Gilmore and Millar 2018). In contrast, the coverage of our medical research abstract corpus was lower, indicating its highly specialized vocabulary level.

4.2. Data Processing

Hyland and Jiang (2019, p. 111), following Cortes (2015, p. 205), argued that while bundle frequencies are often standardized per 10,000 words, this normalization may result in higher instances of bundles in smaller corpora. This potentially raises the frequency of word combinations that are not usually common enough to surpass the threshold. Consequently, phrases that are infrequently used might still be classified as lexical bundles after normalization (Hyland and Jiang 2019, p. 111). To mitigate this issue, we adopted multi-step approach to bundle identification, drawing on methodologies mainly from Cortes (2004), Hyland (2008a), Hyland and Jiang (2019), and Lake and Cortes (2020). Our initial step was to ensure that each abstract in our corpus had broadly similar word count in English and quantitated the abstracts (Figure 1).
Recent studies have shown that five-word bundles are likely to realize rhetorical intentions (Casal and Kessler 2020) and represent a particular genre (Golparvar and Barabadi 2020). Nam et al. (2016) studied several linguistic features for classifying unstructured abstract sentences into the IMRAD format. They found that n-grams produced the best results. However, increasing the value of “n” in n-grams did not necessarily improve classification performance. Better results were obtained with sequences such as five-grams and six-grams (Nam et al. 2016). Therefore, the present study focused on identifying five-word bundles. Initially, following the criteria for five-word p-frames set by Casal and Kessler (2020), five-word bundles appearing in at least five different texts with a raw frequency of five were identified. This was achieved with the N-Gram function of AntConc (Version 4.2.4, Anthony 2023). This process revealed 433 bundles in Move 1, 1901 in Move 2, 3349 in Move 3, and 840 in Move 4. Given the size of the move corpora (Table 1), we followed the idea of Bestgen (2020) to avoid the potential bias of smaller corpora yielding more bundles by using higher frequency thresholds. For further analysis, a threshold of appearing in at least five different texts with a raw frequency of 10 was applied.
We followed the approach of Hyland and Jiang (2019, p. 109), which involved manually removing bundles containing text-dependent noun phrases, such as “the United States”. However, we retained phrases such as “the primary end point”. This is because primary end points serve as key measures of study outcomes, as noted by Qi and Pan (2020, p. 115), and because of the substantial instructional value of items conforming to disciplinary requirements (Salager-Meyer et al. 2014; Luo and Hyland 2019; Millar et al. 2019). This strategy aimed at extracting bundles while preserving “the observation of language in use” (Sinclair 1991, p. 39) as much as possible. In this process, we followed Durrant’s (2017, p. 170) study for the exclusion of “punctuation and numerals”. We utilized AntConc’s feature for automatically omitting punctuation and digits (Viana and O’Boyle 2022, p. 119). Then, we manually excluded “overlapping word sequences” (Chen and Baker 2010, p. 33) with reference to the procedure outlined by Qi and Pan (2020, p. 113). This was done by placing the extracted bundles on spreadsheets (Microsoft Excel) and examining AntConc’s concordance lines. For example, the bundle “did not reduce the rate” showed 13 times in Move 4; all instances were from the six-word string “did not reduce the rate of”. The five-word string “not reduce the rate of” occurred 15 times, including two instances of a six-word sequence, “does not reduce the rate of” (Figure 3). Therefore, the bundle “not reduce the rate of” was listed.
The structures of the bundles were examined with reference to Biber et al. (1999, pp. 1014–24). We also referred to the procedure by Hyland (2008a, p. 10) and examples by Qi and Pan (2020, pp. 125–28). Biber et al. (1999) presented taxonomies for lexical bundles in academic prose, providing example bundles embedded in sentences. Hyland (2008a), citing Biber et al. (1999), also gave example bundles in sentences. By comparing our identified bundles to those examples, we classified our bundles accordingly. Bundles that did not fall into the categories based on the examples, such as “than in the group that”, were labeled as others.
The functions of the bundles were analyzed based on Hyland’s (2008a) classification. Hyland (2008a, p. 13) explained that research-oriented bundles “help writers to structure their activities and experiences of the real world”. Accordingly, our observation included both less specific items such as “with a use of the” and highly specific combinations such as “hazard ratio confidence interval ci” in this category. Text-oriented bundles are “concerned with the organisation of the text and its meaning as a message or argument”, and participant-oriented bundles are “focused on the writer or reader of the text” (Hyland 2008a, pp. 13–14). Based on these definitions, bundles such as “associated with an increase in” were differentiated from research-oriented sequences such as “associated with an increased risk” in classification.

5. Results

5.1. Lexical Bundles in Move Texts

5.1.1. Frequencies

We found a total of 1286 five-word lexical bundles in medical research abstracts: 71 in Move 1, 305 in Move 2, 848 in Move 3, and 62 in Move 4. The most frequently occurring bundles are shown in Table 4, Table 5, Table 6 and Table 7, and all 1286 bundles are shown in Table A1 in Appendix A. The most frequent five-word bundle “the efficacy and safety of” appeared 98 times in Move 1 with a range of 96; “the primary end point was” in Move 2 occurred 708 times in 705 texts. The bundle “confidence interval ci to p” occurred 681 times in 681 texts in Move 3. The original sequence was “confidence interval [CI], n# to n#; P<n#” as shown in an example sentence below, after the exclusion of punctuation and digits (Durrant 2017, p. 170; Viana and O’Boyle 2022, p. 119). In Move 4, the most frequently occurring bundle “associated with an increased risk” appeared 59 times in 56 texts. These instances indicate that many high-frequency sequences were used only once per abstract. The raw frequency and range values suggest a consistent use of bundles across the corpus texts.
1.
In total, 457 patients (22.8%) in the surgery group and 539 patients (26.4%) in the control group died (hazard ratio, 0.77; 95% confidence interval [CI], 0.68 to 0.87; p < 0.001).
While the top bundle in Move 1 did not exceed a raw frequency of 100 (Table 4), the bundle “the primary end point was” in Move 2 was notably prevalent and was found 708 times in 705 texts (Table 5). The prevalence of this bundle indicates common practices in the disciplinary research where the sequence is used to define main variable or parameter to be measured. The combination reflects a highly technical aspect, setting the stage for the methodological framework although the individual lexical items—“the”, “primary”, “end”, “point”, and “was”—have been found to be accessible from a vocabulary perspective (Asano and Fujieda 2024). For instance, the following example illustrates the essential role of such lexical bundles in presenting the main parameters of a study in a succinct manner:
2.
The primary end point was histologic improvement in the 10-mg group as compared with the placebo group.
The bundle “confidence interval ci to p” also occurred as high as 681 times in 681 texts in Move 3, as represented by the fragment “95% confidence interval [CI], 0.68 to 0.87; p < 0.001” in the abovementioned example sentence. This indicates a noticeably consistent appearance in statistical contexts. The abbreviation “CI” indicates multiple occurrences of the term “confidence interval” within the text. The consistent appearance of the five-word bundle “confidence interval ci to p” across various texts suggests its routine use in statistical analyses within medical research. This bundle helps in presenting critical statistical information in a uniform manner, which facilitates clear and comparable interpretations of study results. For instance, the text uses this bundle to report the statistical measures of effect and significance, such as the confidence interval and a p-value. The text illustrates the bundle’s role in showing quantitative aspects of the study findings. This uniform application of statistical terminology ensures that the findings are communicated in a precise and standardized format that can be easily understood and evaluated by others in the scientific community. In Move 4, high-frequency bundles contained word items related to discussing changes or statistical results, such as “associated with an increased risk” and “there was no significant difference”, as described later in Section 5.1.3. Structure and Functions of Lexical Bundles.
Figure 4 shows the frequency of the leading bundles in each move. This indicates that the individual bundles have unique roles in the texts, as shown by Nam et al. (2016). For example, Panel A in Figure 4 shows that “the efficacy and safety of” occurred most often in Move 1. Example concordance lines indicated that the bundle took the technical part of the sentence for realizing study objectives.
3.
We assessed the efficacy and safety of a paclitaxel-coated balloon in this setting.
Panel B in Figure 4 indicates that the instances of “the primary end point was” were dominant in Move 2. The bundle “confidence interval ci to p” only occurred in Move 3 (Panel C), indicating its essential function for presenting statistical findings. The sequence “associated with an increased risk” was rather exceptional as it was common in Moves 3 and 4 and also occurred in Move 1. However, the instances in these moves were below 60; therefore, the bundle may have been used only when the bundle fitted appropriately in realizing the authors’ intentions. The findings suggest that these combinations may have pedagogical value. Becoming aware of where these bundles typically appear and their function within the abstracts could greatly enhance learners’ familiarity with disciplinary research article abstracts.

5.1.2. The NSGL Coverage of the Bundles

The coverage of the first thousand NGSL varied across the moves (Figure 5). The word list covered up to 83.9% of the word items in bundles occurred in Move 4, followed by 76.4% in Move 3, 66.7% in Move 2, and 54.6% in Move 1. These variations are explicitly depicted in Figure 6. This figure shows the percentages of word items in each five-word bundle covered by the word list. For instance, a five-word bundle was classified as 100% when all five individual word items were covered by the word list. It was marked as 80% when four out of the five word items were covered. When none of the word items were covered by the word list, the bundle was marked as 0%.
In Move 4, about a half of the bundles consisted of words in the first NGSL only, such as “with an increased risk of”, “did not result in a”, and “was not associated with a”. The coverage of the word list was 40% or greater in all the bundles in Move 4. These bundles were often used for discussing the changes or statistical results.
On the other hand, 15.5% of the bundles in Move 1 contained no word items covered by the word list, such as “hepatitis c virus hcv infection” (Table 8). Additionally, 14.1% of the sequences had only one word item covered by the word list, such as the fourth most frequently occurring bundle “low density lipoprotein ldl cholesterol” (Table 4). These combinations were used to introduce the research area as described in the following Section 5.1.3.
Move 3 also had many bundles comprised of words covered by the word list, but they were different from the bundles in Move 4 in that most of the bundles in Move 3 were used to accurately report results with numerals, such as “percent confidence interval to p”, “of the patients in the”, and “than in the placebo group” (Table 6). Although each word item was rather accessible, the bundles appeared to convey information specific to the research (Table 9).
Similar tendencies were seen in Move 2, where many frequent bundles, such as “the primary end point was” and “we randomly assigned patients with”, were embedded in the context of research as shown in the next section. There were 31 instances of the first-person pronoun, and they were generally used to build research-oriented bundles. Here again, while the individual word items seemed accessible, the combined use of the words tended to reflect the disciplinary conventions.

5.1.3. Structure and Functions of Lexical Bundles

The texts showed that main structures of bundles were noun phrases, similar to the findings in academic written discourse such as those by Biber et al. (1999), Hyland (2008a), and Golparvar and Barabadi (2020). Noun phrases most often occurred in Move 1 (Table 10). Many were used for presenting disciplinary content words like “low-density lipoprotein (LDL) cholesterol” and “chronic obstructive pulmonary disease (COPD)” for setting the scene:
4.
Non–small-cell lung cancer with sensitive mutations of the epidermal growth factor receptor (EGFR) is highly responsive to EGFR tyrosine kinase inhibitors such as gefitinib, but little is known about how its efficacy and safety profile compares with that of standard chemotherapy.
On the other hand, of-phrase fragments such as “a significantly lower rate of” appeared frequently in expressing the conclusions (Move 4). Most sequences were part of descriptions used to indicate comparisons:
5.
In children with chronic hepatitis B, 52 weeks of treatment with lamivudine was associated with a significantly higher rate of virologic response than was placebo.
The results (Move 3) made by far the most use of bundles beginning with a prepositional phrase. Such items included “of the patients in the”, “in the medical therapy group”, and “as compared with the placebo”. These were most likely used to describe classifications and comparisons:
6.
At 3 years, the criterion for the primary end point was met by 5% of the patients in the medical-therapy group, as compared with 38% of those in the gastric-bypass group (p < 0.001) and 24% of those in the sleeve-gastrectomy group (p = 0.01).
Verb phrases were most used for describing methods (Move 2). These included passive bundles preceded by “patients”, such as “patients were randomly assigned to”, and constructions with the presence of the first-person pronoun, such as “we evaluated the efficacy of”. The following is an example with the first-person pronoun:
7.
We conducted a double-blind, randomized, placebo-controlled trial of intravenous remdesivir in adults who were hospitalized with COVID-19 and had evidence of lower respiratory tract infection.
There were very few usages of the anticipatory it structure among five-word bundles. The only sequence we found was “it is not known whether” in Move 1:
8.
It is not known whether infants conceived with use of intracytoplasmic sperm injection or in vitro fertilization have a higher risk of birth defects than infants conceived naturally.
Many sequences were research-oriented bundles (Table 11). These bundles were used to introduce the research area in Move 1, such as “coronary artery bypass grafting cabg”. The specific word combinations were used and defined to engage readers and direct their focus to the research areas early in the abstracts.
9.
Some studies suggest that combination antiretroviral therapy in pregnant women with human immunodeficiency virus type 1 (HIV-1) infection increases the risk of premature birth and other adverse outcomes of pregnancy.
Almost all bundles were shown to describe study-related matters in Move 2. They were used to describe “location—indicating time/place” (Hyland 2008a, p. 13) such as “at the time of the”, procedure such as “we randomly assigned to a”, and quantification such as “a scale from to with”. These bundles functioned to contextualize the research processes.
10.
Each videotape was rated in various domains of technical skill on a scale of 1 to 5 (with higher scores indicating more advanced skill) by at least 10 peer surgeons who were unaware of the identity of the operating surgeon.
Although the results section (Move 3) was also predominantly composed of research-oriented bundles, it showed a few participant-oriented bundles like “were more likely to be”. Such bundles were accompanied by specific numbers, or values, and results of statistical analyses. The sequences helped to support the summarized data to describe major findings.
11.
According to univariate analysis, patients with S. marcescens bacteremia stayed in the surgical intensive care unit longer than controls (13.5 vs. 4.0 days, p < 0.001), were more likely to have received fentanyl in the surgical intensive care unit (odds ratio, 31; p < 0.001), and were more likely to have been exposed to two particular respiratory therapists (odds ratios, 13.1 and 5.1; p < 0.001 for both comparisons).
Move 4 showed outstanding differences in that it had various text-oriented bundles. They were related to changes seen in the studies in relation to certain interventions, such as “associated with an increase in” or indicating statistical results, such as “no significant difference in the”. These bundles helped briefly discuss and conclude the study findings in abstract texts.
12.
Knowledge of the fetal oxygen saturation is not associated with a reduction in the rate of cesarean delivery or with improvement in the condition of the newborn.
The instances of “participant-oriented bundles” (Hyland 2008a, p. 14) were fewer than expected, indicating a preference for diverse word combinations to construct participant-oriented discourse. Specifically, the bundle “may reduce the risk of” and “may increase the risk of”, which incorporate the modal “may”, were extracted only in Moves 1 and 4, with more frequent occurrences in Move 1. The bundles such as “more likely to have” and “more likely to be” were found in Moves 3 and 4. These bundles were consistently paired with quantifiers like “more” or “less”, likely reflecting the authors’ intention to contextualize and interpret their results within comparative frameworks.
Despite the simplicity of the individual lexical items such as prepositions, pronouns, and verbs like “know”, their combination into bundles plays significant roles in structuring academically contextualized sequences. This synergy illustrates how domain-specific language is formulated from simple components to convey complex ideas, which is crucial for precise communication in scientific contexts.

6. Discussion

Our main purpose in this study was to examine the lexical bundles across moves in the research article abstracts with a focus on the vocabulary levels. We aimed to address the two research questions. Our findings on the most frequently occurring five-word bundles in each move revealed many sequences similar to the 185 bundles extracted by Qi and Pan (2020) but showed a substantial difference in numbers. We identified 1286 five-word lexical bundles in total; about two-thirds of them occurred in Move 3, one-quarter in Move 2, and the remaining bundles were in either Move 1 or Move 4.
Our findings on the structures and functions of bundles support studies by Biber et al. (1999) and Hyland (2008a), which showed that the main structures of bundles are noun phrases, with the majority of sequences being research-oriented bundles. We have extended these studies by examining the coverage of the first thousand NGSL for bundles in each move. We found fluctuations in the coverage of the first thousand NGSL among bundles in different moves.
Although the word list covered around 80% of the word items in the bundles in Move 3 and Move 4, differences were seen in the forms and functions of the bundles in these moves. In Move 3, noun-phrase bundles accounted for about 50%, and many sequences were used to summarize research findings, describing essential data and presenting statistical information. In Move 4, however, about one-third of the bundles were verb phrases, and text-oriented bundles comprised 40%. The bundles in Move 2 were made up of word items in which the coverage of the word list was slightly lower than in the Move 3 bundles and were predominantly research-oriented. The first-person pronoun used in the Move 2 bundles was mainly part of research-oriented sequences. These pronouns were used to describe the researchers’ adherence to disciplinary requirements (Hyland 2008a). Although many five-word lexical bundles were built with basic word items, the combined sequences often realized the contexts of research. Becoming familiar with these bundles may require learners to raise their awareness of the contextual knowledge of formal and rhetorical features of the genre texts (Tardy 2009). These findings may have implications for teaching specific lexical bundles in educational settings especially for novice learners such as undergraduate medical students.
Our study has several limitations. One is that we identified lexical bundles primarily based on frequency information. Nation (2001) argued that items with higher frequency are used more often and thus have educational value. Biber et al. (2004) suggested that examination of frequently occurring bundles can reveal the real-world use of multi-word sequences. However, there are counterarguments. Flowerdew (2012), citing Widdowson (1991) and Cook (1998), pointed out “the danger of equating frequency with pedagogic relevance” (p. 191). This is pertinent because Simpson-Vlach and Ellis (2010) argued that “sequences such as ‘on the other hand’ and ‘at the same time’ are more psycholinguistically salient than sequences such as ‘to do with the’, or ‘I think it was’” (p. 490). They created an academic formula list by taking into consideration the psycholinguistic salience in addition to frequency count.
A notable finding from Graetz (1982) is that there is a high correlation between the disciplines in which abstracts appear in journals and lecturers’ reliance on abstracts, along with their belief that students should be taught how to read abstracts (p. 26). This perspective is supported by Nation (2022), who emphasized that the characteristics and usage of language items should substantially influence teaching and learning strategies (p. 435). However, our study primarily focused on analyzing the features of lexical bundles in abstract texts, without exploring into classroom applications.
In one of our prior studies, we used a seven-year segment of our corpus to develop the Medical English Education Support System (MEESUS), which was implemented in language courses at a university (Asano et al. 2022a). The complexity of contextual meanings of lexical items in disciplinary discourse has been pointed out, such as the term “clinical” in “clinical trials” and “a clinical decision” (Coxhead 2016, p. 179). To tackle this difficulty, around 100 first-year “genre students” (Hyland 2008a, p. 20), with an average TOEFL ITP score of 475.04, engaged with the MEESUS in our previous study (Asano et al. 2022a). They used its concordance tool to explore language items and reported their insights on terms like “mean” for an average and “case” for a subject, gaining awareness of their their usage in the academic contexts.
In another study, fourth-year medical students, averaging a TOEFL ITP score of 455.9, used disciplinary “guidelines” (Millar et al. 2019, p. 150) to examine and summarize research abstracts (Asano et al. 2022b). Despite different thoughts about “learner-directed corpus projects” (Ballance and Coxhead 2022, p. 412), such activities have been shown to enhance linguistic “awareness” and “tolerance”, preparing learners for real-world applications (Cook 2010, pp. 117–18). Simpson-Vlach and Ellis (2010) suggested that “organization of constructions according to academic needs and purposes is essential” in transforming language resources into effective tools for pedagogy (p. 510).
In the future, it will be necessary to expand upon these prior works by conducting classroom activities. Such activities may include observing lexical bundles and raising learners’ awareness of the form and function of the sequences in context.
Many studies have shown the linguistic features of lexical items in disciplinary texts (Biber et al. 1999; Cortes 2004, 2013; Hyland 2008a, 2008b; Mizumoto et al. 2017; Omidian et al. 2018; Qi and Pan 2020; Li et al. 2020). These studies have aimed to address the challenges faced by “novice and seasoned scientists” (Kanoksilapatham 2005, p. 288). This includes the notion that becoming proficient in a language requires an awareness of the preferred word sequences used by experts (Hyland 2008b, p. 44). Our study found similar results regarding five-word lexical bundles in the moves of research article abstracts (Biber et al. 1999; Hyland 2008a). Our examination revealed that although the bundles identified in our texts consisted of relatively accessible individual vocabulary items, their combined sequences reflected the context of research and adherence to the required academic conventions. Several difficulties in learning multiword items have been pointed out (Boers 2020). Becoming familiar with these patterns could assist students in “learning productive chunks of language” (Reppen and Olson 2020, p. 177). In helping learners succeed in their learning contexts (Tribble 2017), the findings in this study suggest that raising awareness of specific lexical bundles can be beneficial for aiding students in joining their disciplinary communities.

Author Contributions

Conceptualization, M.A. and M.F.; text processing and corpus compilation K.H.; analyses, M.A., K.H. and M.F.; writing—original draft preparation, M.A., K.H. and M.F.; funding acquisition, M.A. and M.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Grants-in-Aid for Scientific Research awarded by the Japan Society for the Promotion of Science (JSPS) grant numbers 23K02800 and 18K02966. The APC was funded by the Author Voucher discount code (0736e63e42811a20).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data from our corpus are currently not accessible to the public. However, data used in this study can be provided upon request to the corresponding author.

Acknowledgments

We would like to express our gratitude to the two anonymous reviewers for their insightful comments. We also thank the academic editors of Languages for their generous assistance throughout the review process. The authors are especially grateful to Junichiro Taki, a fourth-year medical student at Osaka Medical and Pharmaceutical University, for his invaluable assistance in data processing and corpus compilation. Any remaining errors are our responsibility.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

All lexical bundles identified are listed by move in the order of frequency (Table A1). The abbreviations are as follows: Freq stands for frequency, 1st N for the coverage of the first NGSL, NP for noun phrase, VP for verb phrase, PP or prepositional phrase, Ant it for anticipatory it structure, Res for research-oriented, Text for text-oriented, and Participant for participant-oriented bundles.
Table A1. All lexical bundles identified by move, frequency, first NGSL coverage, structure, and function.
Table A1. All lexical bundles identified by move, frequency, first NGSL coverage, structure, and function.
MoveBundlesFreqRange1st NStructureFunction
1the efficacy and safety of989660NPRes
1non small cell lung cancer474740NPRes
1the safety and efficacy of454560NPRes
1low density lipoprotein ldl cholesterol424220NPRes
1with an increased risk of4241100PPRes
1human immunodeficiency virus type hiv4040100NPRes
1associated with an increased risk403940VPRes
1in patients with type diabetes373280PPRes
1chronic obstructive pulmonary disease copd313120NPRes
1coronary artery bypass grafting cabg31310NPRes
1it is not known whether3131100Ant itText
1small cell lung cancer nsclc303040NPRes
1human immunodeficiency virus hiv infection282820NPRes
1we tested the hypothesis that272780VPRes
1little is known about the2626100VPParticipant
1out of hospital cardiac arrest232160NPRes
1are at high risk for2222100VPRes
1human epidermal growth factor receptor222260NPRes
1we conducted a study to222280VPRes
1years of age or older2120100NPRes
1we sought to determine whether2020100VPRes
1hepatitis c virus hcv infection19190NPRes
1of human immunodeficiency virus hiv191940PPRes
1influenza a h n virus181820NPRes
1high density lipoprotein hdl cholesterol171720NPRes
1is a major cause of1717100VPParticipant
1the human immunodeficiency virus hiv171740NPRes
1acute respiratory distress syndrome ards16160NPRes
1hepatitis c virus hcv genotype16160NPRes
1in patients with atrial fibrillation161560PPRes
1to reduce the risk of1616100PPRes
1we conducted a randomized trial161640VPRes
1are at increased risk for1515100VPRes
1has been shown to reduce1515100VPText
1proprotein convertase subtilisin kexin type151520NPRes
1transcatheter aortic valve replacement tavr15150NPRes
1we evaluated the effect of151580VPRes
1with hepatitis c virus hcv151520PPRes
1epidermal growth factor receptor egfr141440NPRes
1has been shown to be1413100VPText
1may reduce the risk of1414100VPParticipant
1we evaluated the efficacy of141460VPRes
1we evaluated the safety and141460VPRes
1with human immunodeficiency virus hiv141440PPRes
1diffuse large b cell lymphoma13940NPRes
1st segment elevation myocardial infarction13130NPRes
1the treatment of patients with1313100NPRes
1allogeneic hematopoietic stem cell transplantation121220NPRes
1angiotensin converting enzyme ace inhibitors12120NPRes
1in patients with heart failure121280PPRes
1primary percutaneous coronary intervention pci12120NPRes
1the most common cause of1212100NPParticipant
1we assessed the efficacy and121260VPRes
1cardiovascular events in patients with111080NPRes
1continuous positive airway pressure cpap111140NPRes
1cystic fibrosis transmembrane conductance regulator11110NPRes
1has not been well studied1111100VPParticipant
1methicillin resistant staphylococcus aureus mrsa11110NPRes
1patients with chronic kidney disease11960NPRes
1patients with relapsed or refractory111060NPRes
1patients with type diabetes mellitus111160NPRes
1severe acute respiratory syndrome coronavirus11110NPRes
1the long term effects of1111100NPRes
1the risk of cardiovascular events111180NPRes
1we examined the effect of111180VPRes
1with acute myeloid leukemia aml111120PPRes
1data are lacking on the1010100VPParticipant
1graft versus host disease gvhd101020NPRes
1mutations in the gene encoding101040NPRes
1of death from any cause1010100PPRes
1patients with severe aortic stenosis101040NPRes
2the primary end point was70870580VPRes
2at a dose of mg32525260PPRes
2we randomly assigned patients with29429460VPRes
2were randomly assigned to receive28527860VPRes
2primary end point was the27827780VPRes
2per kilogram of body weight21121180PPRes
2the primary outcome was the19019060VPRes
2in a ratio to receive18317880PPRes
2randomly assigned in a ratio15114740VPRes
2patients were randomly assigned to14914860VPRes
2randomized double blind placebo controlled13413420NPRes
2assigned in a ratio to12712360VPRes
2to with higher scores indicating125105100PPRes
2years of age or older125121100NPRes
2were randomly assigned in a12412060VPRes
2double blind placebo controlled trial12012020NPRes
2was a composite of death938880VPRes
2the primary outcome was a909060VPRes
2outcome was a composite of797760VPRes
2we randomly assigned patients to797960VPRes
2per square meter of body757560PPRes
2we conducted a randomized double727240VPRes
2the primary efficacy end point717060NPRes
2we randomly assigned patients who707060VPRes
2secondary end points included the535380VPRes
2with the use of a5352100PPRes
2with the use of the5350100PPRes
2the efficacy and safety of525160NPRes
2scores range from to with5142100NPRes
2of death from any cause5047100PPRes
2reverse transcriptase polymerase chain reaction50500NPRes
2with higher scores indicating more4543100PPRes
2a total of patients with4444100NPRes
2between the ages of and4443100PPRes
2to years of age with4443100PPRes
2the primary end points were434380VPRes
2we conducted a double blind434340VPRes
2in this randomized double blind414140PPRes
2mg per deciliter mmol per402940NPRes
2the primary outcome measure was393960VPRes
2to years of age who3939100PPRes
2we conducted a multicenter randomized383840VPRes
2double blind placebo controlled phase373720NPRes
2of death from cardiovascular causes373380PPRes
2the primary efficacy outcome was373740VPRes
2a double blind placebo controlled343340NPRes
2change from baseline in the343180NPRes
2the primary outcome was death343460VPRes
2was death from any cause3434100VPRes
2were to years of age3433100VPRes
2were randomly assigned to undergo333340VPRes
2ml per minute per m312380NPRes
2this double blind placebo controlled313140NPRes
2at a dose of µg302460PPRes
2forced expiratory volume in second303060NPRes
2in a randomized double blind303040PPRes
2on the basis of the2929100PPText
2outcome was the rate of292780VPRes
2were years of age or2929100VPRes
2assessed with the use of282780VPRes
2end point was the percentage282880VPRes
2the presence or absence of282860NPText
2we randomly assigned patients in282860VPRes
2assigned to receive mg of272660VPRes
2or death from cardiovascular causes262480NPRes
2the primary safety end point262460NPRes
2trial we assigned patients with262660VPRes
2double blind randomized placebo controlled252520NPRes
2mg per day or placebo252460NPRes
2nonfatal myocardial infarction nonfatal stroke25240NPRes
2double blind trial we randomly242420NPRes
2placebo controlled trial we randomly242440NPRes
2on the modified rankin scale232040PPRes
2to receive either mg of232380VPRes
2a total of patients were2222100NPRes
2end point was death from2222100VPRes
2placebo controlled phase trial we222240NPRes
2the change from baseline to222180NPRes
2the two primary end points222280NPRes
2we conducted a randomized trial222240VPRes
2weight in kilograms divided by222260NPRes
2divided by the square of212160VPRes
2patients with moderate to severe212160NPRes
2performed with the use of2121100VPRes
2randomized double blind trial we212120NPRes
2secondary end points included overall212160NPRes
2the patients were randomly assigned212160VPRes
2was a sustained virologic response212160VPRes
2weeks after the end of2121100NPRes
2assigned patients with type diabetes202060VPRes
2at a dose of or201780PPRes
2composite of death myocardial infarction201940NPRes
2end point was a sustained202080VPRes
2health related quality of life2020100NPRes
2in the score on the2018100PPRes
2nonfatal myocardial infarction or nonfatal202020NPRes
2out of hospital cardiac arrest201860NPRes
2we randomly assigned adults with202060VPRes
2children to months of age1919100NPRes
2end points were overall survival191960VPRes
2free survival and overall survival191940NPRes
2in the intention to treat191880PPRes
2on a scale of to191780PPRes
2or placebo in addition to191980NPRes
2outcome was the composite of191860VPRes
2to mg per deciliter to191660PPRes
2a time to event analysis1815100NPRes
2at a dose of to181680PPRes
2double blind phase trial we181820NPRes
2ejection fraction of or less181860NPRes
2randomly assigned to one of181860VPRes
2the primary composite end point181860NPRes
2was the composite of death181780VPRes
2after the end of treatment1717100PPRes
2at the end of the1716100PPRes
2end point was the composite171580VPRes
2hours after the onset of171780NPRes
2in this phase trial we171760PPRes
2investigator assessed progression free survival171720NPRes
2mg per kilogram every weeks171060NPRes
2non small cell lung cancer171640NPRes
2patients were assigned to receive171580VPRes
2progression free survival and overall171740NPRes
2we conducted a retrospective cohort171740VPRes
2were randomly assigned to a171760VPRes
2a left ventricular ejection fraction161620NPRes
2a scale from to with161580NPRes
2key secondary end point was161680VPRes
2mg twice daily or placebo161540NPRes
2or death from any cause1616100NPRes
2randomization was stratified according to161660VPRes
2randomized placebo controlled double blind161620NPRes
2secondary end points were the161680VPRes
2the between group difference in1614100NPText
2the coprimary end points were161680VPRes
2the median follow up was161680VPRes
2the primary end point of161680NPRes
2the safety and efficacy of161660NPRes
2the time to the first1614100NPRes
2to with lower scores indicating1614100PPRes
2we conducted an open label161660VPRes
2we enrolled patients who had161680VPRes
2who had not previously received161680VPRes
2a composite of death myocardial151560NPRes
2according to the intention to151580PPRes
2analyzed with the use of151380VPRes
2during the period from through1514100PPRes
2end points were progression free151580VPRes
2every weeks for up to1514100NPRes
2in this multicenter double blind151540PPRes
2of to mg per deciliter151360PPRes
2open label phase trial we151540NPRes
2the composite of death from151580NPRes
2the percentage of patients with151380NPRes
2the primary safety outcome was151540VPRes
2a composite of cardiovascular death141260NPRes
2after the end of therapy141480PPRes
2as compared with placebo in141480PPRes
2at the time of the1413100PPRes
2death myocardial infarction or stroke141440NPRes
2free survival as assessed by141460NPRes
2in a ratio to undergo141460PPRes
2mg per kilogram per day141160NPRes
2or hospitalization for heart failure141460NPRes
2patients who had a response1413100NPRes
2to years of age and1414100PPRes
2was the percentage of patients141480VPRes
2we conducted a randomized controlled141460VPRes
2we randomly assigned women with141460VPRes
2a composite of death or131380PPRes
2and randomly assigned them to131360VPRes
2bmi the weight in kilograms131360NPRes
2boundary of the confidence interval131340NPRes
2end point was disease free1313100VPRes
2end point was the first139100VPRes
2in a double blind fashion131340PPRes
2in this double blind phase131340PPRes
2key secondary end points were131380VPRes
2of body surface area and131380PPRes
2patients with hcv genotype infection131040NPRes
2patients with relapsed or refractory131360NPRes
2placebo for weeks the primary131260NPRes
2point was investigator assessed progression131340VPRes
2primary end point was disease131380VPRes
2primary end point was survival131360VPRes
2psoriasis area and severity index131340NPRes
2randomized trial we assigned patients131340NPRes
2sustained virologic response at weeks131360NPRes
2time to event analysis was1312100NPRes
2to years of age to1312100PPRes
2trial to evaluate the efficacy131340NPRes
2we performed a randomized double131360VPRes
2were followed for up to1313100VPRes
2who did not have a1313100VPRes
2years of age or younger1313100NPRes
2a dose of either mg121160NPRes
2aspirin at a dose of121160NPRes
2at a daily dose of121180PPRes
2at a dose of iu121060PPRes
2between and years of age1212100PPRes
2body mass index bmi the121240NPRes
2determined with the use of1212100VPRes
2end point was the annualized121280VPRes
2estimated with the use of1212100VPRes
2evaluated with the use of121280VPRes
2for a median of years121280PPRes
2in this double blind trial121240PPRes
2measured with the use of1212100VPRes
2mg once daily or placebo121260NPRes
2of patients who had a1212100PPRes
2on the basis of a1212100PPText
2real time polymerase chain reaction121240NPRes
2secondary end point was the121280VPRes
2st segment elevation myocardial infarction12120NPRes
2than years of age who1212100PPRes
2the percentage of patients who121180PPRes
2the primary composite outcome was121240VPRes
2the primary objective was to121260VPRes
2the primary outcome was day121260VPRes
2the primary outcome was survival121240VPRes
2the primary outcomes were the121260VPRes
2the secondary end points were121280VPRes
2to years of age in1211100PPRes
2trial in which patients with121280NPRes
2was the time to the1211100VPRes
2we evaluated the effect of121280VPRes
2we evaluated the efficacy of121260VPRes
2we performed a multicenter randomized121260VPRes
2were at high risk for1212100VPRes
2were randomly assigned to the121260VPRes
2with a by factorial design121280PPRes
2a by factorial design we111180NPRes
2a noninferiority margin of percentage111140NPRes
2an estimated glomerular filtration rate111160NPRes
2an intention to treat basis111180NPRes
2assessed in a time to11880VPRes
2assigned to one of three111180VPRes
2controlled trial involving patients with111180PPRes
2death from coronary heart disease111080PPRes
2disease patients were randomly assigned111160VPRes
2dose of mg every weeks111160NPRes
2dose of to mg per111060NPRes
2factorial design we randomly assigned111140NPRes
2from no symptoms to death111180PPRes
2in the intensive care unit111180PPRes
2in this double blind randomized111140PPRes
2of less than mm hg11760PPRes
2of the confidence interval for111160PPRes
2open label randomized controlled trial111140NPRes
2patients at high risk for1111100NPRes
2patients were stratified according to111180VPRes
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3duration of progression free survival131240NPRes
3for a median of months131380PPRes
3free survival was months and131280VPRes
3group absolute difference percentage points131060NPRes
3group and days in the1313100NPRes
3group in the mg group13880NPRes
3group risk difference percentage points131080NPRes
3hazard ratio for death or131160NPRes
3hazard ratio was ci to131240VPRes
3in of the patients receiving1310100PPRes
3in of those who received138100PPRes
3in the combined therapy group13560PPRes
3in the conventional therapy group13860PPRes
3in the group receiving the138100PPRes
3in the mg tofacitinib group13560PPRes
3in the standard treatment group135100PPRes
3observed in of the patients131380VPRes
3of log copies per milliliter13940PPRes
3of patients who had a1312100PPRes
3of serious adverse events was131380VPRes
3of the composite end point131080PPRes
3of the patients who had1313100PPRes
3of the primary outcome was131360VPRes
3patients in the aspirin group13880NPRes
3percentage of patients who were131180NPRes
3placebo p for both comparisons131140NPRes
3risk ratio ci to p131240NPRes
3significantly more patients in the131280NPRes
3survival hazard ratio for death131240NPRes
3survival was months and months13980VPRes
3that in the placebo group131280NPRes
3the area under the curve131180NPRes
3the rate of grade or131080NPRes
3the two groups were similar1313100VPText
3venous thromboembolism occurred in of131160VPRes
3was also associated with a1313100VPText
3was cells per cubic millimeter131360VPRes
3was ci to and the131180VPRes
3was more frequent in the131280VPRes
3was observed in of the131380VPRes
3were more likely to be1313100VPParticipant
3with a reduced risk of1310100PPRes
3adjusted hazard ratio for death12740NPRes
3among the patients who were1211100VPRes
3and p for the comparison12860NPRes
3and percentage points ci to12960NPRes
3and serious adverse events were121280VPRes
3and the hazard ratio for121260NPRes
3and were more likely to1212100VPParticipant
3ci to and in the121080NPRes
3ci to hazard ratio for121140NPRes
3ci to p and death121060NPRes
3ci to p for both121260NPRes
3difference percent percent confidence interval12960NPRes
3during the follow up period1212100PPRes
3end point of death from1211100NPRes
3end point was in the1210100VPRes
3from any cause ci to121280PPRes
3group p and in the121280NPRes
3had a higher rate of1212100VPText
3had occurred in of patients1210100VPRes
3in the control group percent129100PPRes
3in the ldl cholesterol level121060PPRes
3in the placebo group died121180PPRes
3in the placebo group with121180PPRes
3in the proportion of patients121180PPRes
3not associated with an increased1212100VPText
3occurred in participants in the121280VPRes
3of follow up was years1212100VPRes
3of in the control group1211100PPRes
3of the children in the128100PPRes
3of the infants in the12680PPRes
3of the patients in group125100PPRes
3other adverse events were similar121280VPRes
3outcome event occurred in of121180VPRes
3patients in the surgery group12980NPRes
3patients vs. patients hazard ratio12940NPRes
3patients who did not have1212100NPRes
3percentage points ci to for12660NPRes
3rate of overall survival was121260NPRes
3response rate was in the1212100VPRes
3risk of death from any1211100NPRes
3serious adverse events in the121280NPRes
3the median follow up period121280NPRes
3the placebo group had a121180VPRes
3the placebo group vs. p121240NPRes
3the primary end point of121280NPRes
3the risk of death was1211100VPRes
3there was a trend toward121280VPText
3to p as was the121280PPRes
3vs hazard ratio for death121140PPRes
3vs in the control group12980PPRes
3was in the placebo group12980VPRes
3year in the placebo group121080NPRes
3a higher percentage of patients111080NPRes
3a percent increase in the115100NPRes
3a relative reduction of in111160NPRes
3a significantly increased risk of111080NPRes
3a total of children were1111100VPRes
3among patients who did not119100PPText
3among patients who had a119100PPText
3among patients years of age118100PPRes
3and ci to for the11980NPRes
3as compared with with placebo511980PPRes
3at the end of treatment119100PPRes
3between group difference percentage points111080PPRes
3between the two study groups1111100PPRes
3death hazard ratio ci to111140NPRes
3did not differ significantly in111160VPText
3event occurred in of patients1110100VPRes
3group and months ci to11980NPRes
3group had died relative risk11980VPRes
3groups in the rates of1111100NPRes
3had an increased risk of1111100VPRes
3had no significant effect on1111100VPText
3hazard ratio for disease recurrence11940NPRes
3in the active treatment group11580PPRes
3in the apixaban group and11680PPRes
3in the control group adjusted11980PPRes
3in the hypothermia group and11780PPRes
3in the paclitaxel stent group11560PPRes
3in the placebo group incidence11860PPRes
3in the t pr group11580PPRes
3in the watchful waiting group11680PPRes
3liter percent confidence interval to11640NPRes
3mean change from baseline in111080NPRes
3mg per deciliter in the11560NPRes
3no significant differences among the1111100NPText
3no significant differences were observed111180VPText
3occurred in and of patients119100VPRes
3occurred in patients who received1110100VPRes
3occurred in percent of the1111100VPRes
3of grade or higher occurred111180PPRes
3of less than mg per11780PPRes
3patients had at least one1111100VPRes
3patients in the apixaban group11680NPRes
3patients in the pci group11680NPRes
3patients who did not receive119100NPRes
3percent confidence interval to or111060NPRes
3percent vs. percent p or111160NPRes
3placebo hazard ratio confidence interval11110NPRes
3progression free survival rate was111060VPRes
3rate of serious adverse events111180NPRes
3rate of the primary outcome111160NPRes
3reported in of patients in1111100VPRes
3risk of death from cardiovascular111180NPRes
3the end of the study1111100NPRes
3the most frequent adverse events111160NPRes
3the patients randomly assigned to11860NPRes
3the placebo group p and111160NPRes
3the primary composite end point111160NPRes
3the rate of freedom from11980NPRes
3the rates of the primary111180NPRes
3to hazard ratio ci to11740PPRes
3was associated with a percent1110100VPText
3was more common in the1111100VPText
3were ci to ci to111160VPRes
3were lost to follow up1110100VPRes
3were randomly assigned to a111160VPRes
3who did not have a1111100VPRes
3who received at least one119100VPRes
3who received placebo p for11760VPRes
3women in the placebo group11980NPRes
3years confidence interval ci to111140NPRes
3a glycated hemoglobin level of10760NPRes
3a significant increase in the109100NPRes
3a significantly lower risk of10980NPRes
3a total of cases of1010100NPRes
3a total of infants were101080VPRes
3a total of participants in101080NPRes
3an increase in the risk109100NPRes
3and events per person years109100NPRes
3and in the group receiving106100PPRes
3and of participants in the10780NPRes
3and percent in the group109100NPRes
3and percent respectively in the10680NPRes
3as compared with percent among1010100PPRes
3as compared with placebo p10760PPRes
3at months the rate of1010100PPRes
3at to years of age107100PPRes
3at years the rate of1010100PPRes
3bleeding occurred in of patients101080VPRes
3by the end of the1010100PPRes
3ci to among patients with10880NPRes
3ci to in the per10780NPRes
3ci to p and for10860NPRes
3confidence interval ci to not101040NPRes
3control group than in the108100NPRes
3data and safety monitoring committee101040NPRes
3days of patients in the108100NPRes
3death from any cause occurred1010100VPRes
3developed in of the patients1010100VPRes
3developed in patients in the1010100VPRes
3died as compared with of109100VPRes
3differences in the rate of109100NPRes
3for progression or death ci10860PPRes
3for the comparison between the10680PPText
3free survival and overall survival10940NPRes
3free survival hazard ratio for101040NPRes
3free survival was in the10980VPRes
3from any cause occurred in1010100PPRes
3group and in the medical101080NPRes
3group and in the surgery10980NPRes
3group in the intention to101080NPRes
3group of patients vs. of101080NPRes
3group rate ratio ci to101060NPRes
3had a lower risk of1010100VPRes
3had received a median of101080VPRes
3hazard ratios for death from10860NPRes
3in the budesonide formoterol group10560PPRes
3in the group that underwent10680PPRes
3in the placebo group adjusted10560PPRes
3in the rate of the1010100PPRes
3in the rates of death1010100PPRes
3in the surgery group p10860PPRes
3in the two groups were1010100PPRes
3in the two groups with1010100PPRes
3increase in the incidence of10880NPRes
3increased by a factor of109100VPRes
3increased from in to in109100VPText
3independent data and safety monitoring101040NPRes
3intention to treat analysis of101080NPRes
3intervention group as compared with10880NPRes
3kaplan meier estimates of the101060NPRes
3level of mg per deciliter10760NPRes
3major bleeding occurred in of101080VPRes
3mg group as compared with10680NPRes
3occurred in patients and patients109100VPRes
3of the patients had a1010100PPRes
3of the patients in each1010100PPRes
3older than years of age1010100OthRes
3outcomes did not differ significantly101040VPRes
3patients in the enoxaparin group10780NPRes
3patients in the respective groups101080NPRes
3percent confidence interval to with10660NPRes
3percent in the group given105100NPRes
3progression free survival in the101060NPRes
3progression or death in the101080NPRes
3rate of disease free survival10980NPRes
3reduction in the number of10880NPRes
3risk of death hazard ratio101060NPRes
3significant between group differences were1010100VPRes
3standard therapy group hazard ratio10640NPRes
3surgery group and in the10880NPRes
3survival was similar in the101080VPRes
3sustained virologic response at weeks10560NPRes
3than among those receiving placebo101080OthRes
3than in the group that1010100OthRes
3than with placebo vs. p10840OthRes
3the between group difference in109100NPRes
3the control group p and10980NPRes
3the control group vs. p10960NPRes
3the group that received the107100NPRes
3the mg group and the10580NPRes
3the most common grade or101080NPRes
3the patients who had a1010100NPRes
3the patients who were enrolled101080NPRes
3the placebo group and respectively10960NPRes
3the rate of death was1010100VPRes
3the relative risk of death10980NPRes
3the results were similar in1010100VPText
3the subgroup of patients with101080NPRes
3the two groups did not1010100VPText
3those who received placebo p10860NPRes
3treatment group than in the108100NPRes
3vs p as was the101060PPRes
3was days interquartile range to101080VPRes
3was reported in of patients109100VPRes
3was similar to that of1010100VPText
3were enrolled in the study101080VPRes
3were included in the analyses1010100VPRes
3were similar with respect to1010100VPText
3women to years of age105100NPRes
3women were randomly assigned to101060VPRes
4associated with an increased risk5956100VPRes
4with an increased risk of5855100PPRes
4did not result in a3838100VPText
4at a dose of mg312760PPRes
4was associated with an increased3030100VPRes
4of death from any cause2724100PPRes
4there was no significant difference2727100VPText
4than among those who received2626100OthRes
4out of hospital cardiac arrest232260NPRes
4was associated with a higher2323100VPRes
4did not differ significantly between222260VPText
4was not associated with a2222100VPText
4did not significantly reduce the212180VPText
4a significantly lower rate of202080NPText
4years of age or older2018100NPRes
4is associated with an increased1919100VPText
4reduction in the rate of191980NPText
4was associated with a lower1918100VPText
4non small cell lung cancer181840NPRes
4rates of sustained virologic response181860NPRes
4in a lower incidence of171780PPText
4the rate of death from1717100NPRes
4was associated with a significantly171780VPText
4a significantly lower risk of161680NPRes
4associated with a reduction in151580VPText
4lower among those who received1515100OthRes
4not reduce the rate of1515100VPText
4patients with moderate to severe151560NPRes
4resulted in a significantly lower151580VPText
4and was associated with a1414100VPText
4composite end point of death141480NPRes
4free survival among patients with141480NPRes
4in patients with type diabetes141480PPRes
4in the rate of death1413100PPRes
4of death from cardiovascular causes141480PPRes
4patients with relapsed or refractory141460NPRes
4than those who received placebo141480OthRes
4an increased risk of death1313100NPRes
4free survival and overall survival131340NPRes
4in patients with atrial fibrillation131360PPRes
4not reduce the risk of1313100VPRes
4patients with hcv genotype infection131240NPRes
4a significantly higher rate of121280NPText
4associated with an increase in1212100VPText
4longer progression free survival than121260NPRes
4with a lower rate of1212100PPText
4with a lower risk of1211100PPRes
4among patients with type diabetes111180NPRes
4had no significant effect on1111100VPRes
4in a lower rate of1110100PPText
4in this trial involving patients111180PPRes
4increase in the rate of1110100NPText
4overall survival among patients with111160NPRes
4than in the placebo group111180OthRes
4was associated with a significant1111100VPText
4increase in the risk of108100NPRes
4no significant difference in the1010100NPText
4patients with acute ischemic stroke101040NPRes
4patients with chronic kidney disease101060NPRes
4the rate of the composite101080NPRes
4the risk of death from109100NPRes
4with a higher rate of109100PPText

Notes

1
Although translations can sometimes be criticized for not perfectly reflecting “the content” of the original source texts or texts originally written in the target language (Rees 2022, p. 395), the Japanese translations of the journal’s abstracts, shown in the regional edition of the journal as well as on the website of the licensed publisher (Nankodo 2024), are noted for accurately reflecting the original texts. Noto (2015) specifically highlighted their effectiveness in conveying essential information to the domestic disciplinary readers, ensuring that critical medical insights remain accessible and reliable.
2
When measured in the Google Colaboratory’s Python environment, the English-language abstract texts comprised 1,201,780 words. However, using AntConc for quantification, the count was 1,209,851 words with punctuation included and 1,148,583 words without punctuation. For the purposes of this study, we adopt the more conservative word count of 1,148,583, excluding punctuation, to describe the size of our corpus.
3
The bundle “a total of of the” was extracted from fragments such as “a total of 444 of the 490 children” because punctuation and numerals were excluded when extracting bundles, following the methodology of a previous study (Durrant 2017, p. 170).
4
The bundle “a total of of patients” was extracted from fragments such as “a total of 128 of 212 patients”.
5
The bundle “as compared with with placebo” was extracted from fragments such as “as compared with 44% with placebo”.

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Figure 1. Distribution of the word count of individual abstracts.
Figure 1. Distribution of the word count of individual abstracts.
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Figure 2. Cumulative coverage of the NGSL and NAWL over the abstract corpus.
Figure 2. Cumulative coverage of the NGSL and NAWL over the abstract corpus.
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Figure 3. Example screen of AntConc showing “not reduce the rate of” as the node word with 13 instances of “did” and 2 instances of “does” at L1 or one word to the left (order by frequency of L1).
Figure 3. Example screen of AntConc showing “not reduce the rate of” as the node word with 13 instances of “did” and 2 instances of “does” at L1 or one word to the left (order by frequency of L1).
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Figure 4. Frequency of move-specific most frequent five-word bundles. (A): the efficacy and safety of; (B): the primary end point was; (C): confidence interval ci to p; (D): associated with an increased risk.
Figure 4. Frequency of move-specific most frequent five-word bundles. (A): the efficacy and safety of; (B): the primary end point was; (C): confidence interval ci to p; (D): associated with an increased risk.
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Figure 5. The first thousand NGSL coverage of word items in lexical bundles by move.
Figure 5. The first thousand NGSL coverage of word items in lexical bundles by move.
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Figure 6. Percentages of word items in each five-word bundle covered by the first thousand NGSL across moves. From the bottom, bars in dark gray represent 100%, those in blue gray represent 80%, those in dim gray represent 60%, those in silver represent 40%, those in light gray represent 20%, and those in black represent 0%.
Figure 6. Percentages of word items in each five-word bundle covered by the first thousand NGSL across moves. From the bottom, bars in dark gray represent 100%, those in blue gray represent 80%, those in dim gray represent 60%, those in silver represent 40%, those in light gray represent 20%, and those in black represent 0%.
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Table 1. Corpus of research article abstracts.
Table 1. Corpus of research article abstracts.
 DescriptionData
Years2002–2020
Type of textsResearch article abstracts
Number of texts3983
Mean length of texts303
Total number of words (tokens)1,148,583
Total word types22,950
NGSL and NAWL coverage
 First NGSL63.6%
 First and second NGSL71.1%
 First, second, and third NGSL75.6%
 First, second, third NGSL, and NAWL80.7%
Move tokens
 Move 1162,558
 Move 2317,349
 Move 3497,215
 Move 4171,461
Move word types
 Move 111,897
 Move 213,631
 Move 314,229
 Move 412,169
Table 2. List of the most frequent words in the abstract corpus.
Table 2. List of the most frequent words in the abstract corpus.
RankWordFreq per Mil *RankWordFreq per Mil *
1the52,87526that4026
2of46,18627among3982
3in33,59428than3944
4and29,72129placebo3852
5to22,60130an3674
6with20,87031treatment3428
7a17,65832after3372
8patients14,35733is3192
9was11,98234on3148
10for10,86835years3135
11were10,86636disease3131
12or961137not3042
13group949338ratio3001
14p673939therapy2936
15at641040primary2772
16we584641mg2721
17by543742associated2714
18from508243rate2699
19had491344interval2619
20who480145months2585
21as445146death2581
22ci407347confidence2492
23percent403848number2470
24risk403149assigned2468
25per403050compared2420
* Freq per mil stands for frequency per million words.
Table 3. Cumulative coverage of the top 100 words in the abstract corpus.
Table 3. Cumulative coverage of the top 100 words in the abstract corpus.
RankCoverageRankCoverage
1026.1%6044.8%
2033.0%7046.7%
3037.0%8048.4%
4040.1%9049.9%
5042.7%10051.4%
Table 4. Most frequent five-word lexical bundles in Move 1.
Table 4. Most frequent five-word lexical bundles in Move 1.
RankFive-Word Lexical BundleFreqRange
1the efficacy and safety of9896
2non small cell lung cancer4747
3the safety and efficacy of4545
4low density lipoprotein ldl cholesterol4242
4with an increased risk of4241
6human immunodeficiency virus type hiv4040
6associated with an increased risk of4039
7in patients with type diabetes3732
8chronic obstructive pulmonary disease copd3131
8coronary artery bypass grafting cabg3131
8it is not known whether3131
Table 5. Most frequent five-word lexical bundles in Move 2.
Table 5. Most frequent five-word lexical bundles in Move 2.
RankFive-Word Lexical BundleFreqRange
1the primary end point was708705
2at a dose of mg325252
3we randomly assigned patients with294294
4were randomly assigned to receive285278
5primary end point was the278277
6per kilogram of body weight211211
7the primary outcome was the190190
8in a ratio to receive183178
9randomly assigned in a ratio151147
10patients were randomly assigned to149148
Table 6. Most frequent five-word lexical bundles in Move 3.
Table 6. Most frequent five-word lexical bundles in Move 3.
RankFive-Word Lexical BundleFreqRange
1confidence interval ci to p681681
2hazard ratio ci to p421272
3percent confidence interval to p310155
4of the patients in the291192
5hazard ratio confidence interval ci230230
6in of patients in the225149
7than in the placebo group221173
8similar in the two groups208193
9in the placebo group p185138
10a total of patients were180180
10and in the placebo group180138
Table 7. Most frequent five-word lexical bundles in Move 4.
Table 7. Most frequent five-word lexical bundles in Move 4.
RankFive-Word Lexical BundleFreqRange
1associated with an increased risk5956
2with an increased risk of5855
3did not result in a3838
4at a dose of mg3127
5was associated with an increased3030
6of death from any cause2724
6there was no significant difference2727
8than among those who received2626
9out of hospital cardiac arrest2322
9was associated with a higher2323
Table 8. Concordance lines with the node word of “hepatitis C virus (HCV) infection” in Move 1.
Table 8. Concordance lines with the node word of “hepatitis C virus (HCV) infection” in Move 1.
chronichepatitis C virus (HCV) infection is a cause of major complications
chronichepatitis C virus (HCV) infection is more prevalent among
therapy for chronic hepatitis C virus (HCV) infection is effective in less than 50% of
in patients with chronic hepatitis C virus (HCV) infection. We compared the efficacy and
for patients with chronic hepatitis C virus (HCV) infection. We evaluated daclatasvir (an
ribavirin for chronic hepatitis C virus (HCV) infection. However, these regimens have
Patients with chronic hepatitis C virus (HCV) infection who have not had a response to
response to therapy for hepatitis C virus (HCV) infection, and limited data suggest that
facilitate treatment for hepatitis C virus (HCV) infection in patients with thrombocytopenia
standard treatment forhepatitis C virus (HCV) infection is interferon, which is administered
Table 9. Concordance lines with the node word of “of the patients in the” in Move 3.
Table 9. Concordance lines with the node word of “of the patients in the” in Move 3.
centers: 6.7 percent of the patients in the angioplasty group reached the primary
was reached in 8.5 percent of the patients in the angioplasty group, as compared with
performed in 12.0 percent of the patients in the paclitaxel-stent group and 6.4
angiography in 16.5 percent of the patients in the paclitaxel-stent group and 6.9
group and 18 percent of the patients in the placebo group reported
severity index in 4 percent of the patients in the placebo group, as compared with
group and 6.4 percent of the patients in the sirolimus-stent group (p = 0.13).
Only 42 percent of the patients in the intraperitoneal-therapy group
Overall, 12 percent of the patients in the lamivudine group and 18 percent
index in 25 percent of the patients in the low-dose group, 44 percent of
Table 10. Principal structures of bundles across moves (%).
Table 10. Principal structures of bundles across moves (%).
StructureMove 1Move 2Move 3Move 4
NP-based57.739.048.141.9
 Noun phrase15.55.92.43.2
 Noun phrase + of9.97.913.316.1
 Noun phrase + other32.425.232.422.4
PP-based14.120.725.621.0
 Prepositional phrase + of2.87.25.712.9
 Other prepositional phrase11.313.419.98.1
VP-based26.839.324.930.6
 Passive verb4.23.92.712.9
 Pronoun/noun + verb11.311.15.40.0
 Pronoun/noun + be2.813.87.71.6
 Verb + noun/prep. phrase5.66.25.216.1
 Copula be + noun/adjective phrase1.43.03.90.0
 to-clause fragment1.41.30.00.0
Others0.01.01.46.5
Anticipatory it structure1.40.00.00.0
Totals100.0100.0100.0100.0
Table 11. Distribution of bundle functions by move (%).
Table 11. Distribution of bundle functions by move (%).
FunctionMove 1Move 2Move 3Move 4
Research-oriented87.398.791.362.9
Text-oriented4.21.38.437.1
Participant-oriented8.50.00.40.0
Totals100.0100.0100.0100.0
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Asano, M.; Hirosuna, K.; Fujieda, M. Exploring Lexical Bundles in the Move Structure of English Medical Research Abstracts: A Focus on Vocabulary Levels. Languages 2024, 9, 281. https://doi.org/10.3390/languages9090281

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Asano M, Hirosuna K, Fujieda M. Exploring Lexical Bundles in the Move Structure of English Medical Research Abstracts: A Focus on Vocabulary Levels. Languages. 2024; 9(9):281. https://doi.org/10.3390/languages9090281

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Asano, Motoko, Kensuke Hirosuna, and Miho Fujieda. 2024. "Exploring Lexical Bundles in the Move Structure of English Medical Research Abstracts: A Focus on Vocabulary Levels" Languages 9, no. 9: 281. https://doi.org/10.3390/languages9090281

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