Qingyun Wan†
Kai Liu
Shuting Luo- Department of Acupuncture and Rehabilitation, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
Objective: The number of citations to a paper represents the weight of that work in a particular area of interest. Several highly cited papers are listed in the bibliometric analysis. This study aimed to identify and analyze the 100 most cited papers in insomnia research that might appeal to researchers and clinicians.
Methods: We reviewed the Web of Science (WOS) Core Collection database to identify articles from 1985 to 24 March 2022. The R bibliometric package was used to further analyze citation counts, authors, year of publication, source journal, geographical origin, subject, article type, and level of evidence. Word co-occurrence in 100 articles was visualized using VOS viewer software.
Results: A total of 44,654 manuscripts were searched on the Web of Science. Between 2001 and 2021, the top 100 influential manuscripts were published, with a total citation frequency of 38,463. The top countries and institutions contributing to the field were the U.S. and Duke University. Morin C.M. was the most productive author, ranking first in citations. Sleep had the highest number of manuscripts published in the top 100 (n = 31), followed by Sleep Medicine Reviews (n = 9). The most cited manuscript (Bastien et al., Sleep Medicine, 2001; 3,384 citations) reported clinical validation of the Insomnia Severity Index (ISI) as a brief screening indicator for insomnia and as an outcome indicator for treatment studies. Co-occurrence analyses suggest that psychiatric disorders combined with insomnia and cognitive behavioral therapy remain future research trends.
Conclusion: This study provides a detailed list of the most cited articles on insomnia. The analysis provides researchers and clinicians with a detailed overview of the most cited papers on insomnia over the past two decades. Notably, COVID-19, anxiety, depression, CBT, and sleep microstructure are potential areas of focus for future research.
Introduction
Insomnia has been emerging with more public concerns over the past decades for affecting people’s health and well-being worldwide. The prevalence of insomnia disorder is approximately 10–20%, with approximately 50% having a chronic course (1). In America, 27.3% of adults reported insomnia 1 year, and the US annual loss of quality-adjusted life-years associated with insomnia (5.6 million) was significantly larger than that associated with any of the other 18 medical conditions assessed, including arthritis (4.94 million), depression (4.02 million), and hypertension (3.63 million) (2). The economic consequences of the disorder and the cost-effectiveness of insomnia treatments, in aggregate, exceeded $100 billion per year, with the majority being spent on indirect costs such as poorer workplace performance, increased health care utilization, and increased accident risk (3). Insomnia has been a public health issue and an extensive concern for medical practitioners. The number of insomnia-associated studies has gradually increased annually, of which 27,399 were published accumulatively in Web of Science (WoS) Core Collection from 1985 to 2021.
With a trend of research interest and explosive publication, it is worth identifying the most influential scientific achievements from an abundance of literature on insomnia related topics. So far, there is no perfect method for evaluating the scientific impact that a specific study has had on a scientific discipline, the number of citations of an article is a proxy to indicate the importance of the study (4). Bibliometric sciences offer both a statistical and quantitative analysis of published articles and provide a measure of their impact in a particular field of research. To date, no such analyses have been performed exploring the most influential works presented in the field of insomnia. In the present study, we aimed to analyze the top 100 most cited articles over the past decades in the field of insomnia with bibliometric citation analysis.
Methods
Identification of the top 100 cited articles
The Clarivate Analytics Web of Science Core Collection database was systematically searched on March 31, 2022. The search terms were “insomnia” and “disorders of initiating and maintaining Sleep,” with publication timespan (1985–2022). The publications were ranked by the number of citations, and these were reviewed to identify the top 100 papers with the most citations. Only original articles and reviews with full manuscripts that focused on insomnia as the main topic were included. Literature reviews that briefly summarized published studies were excluded; editorials and consensus statements were excluded. Two reviewers (SL and JJ) independently identified the top 100 papers according to the total citations of the papers, and any disagreement between the 2 reviewers was resolved by consensus involving a third reviewer (XM).
Analysis of the top 100 cited articles
Publications were stratified and systematically assessed according to publication year, country or institute, authors, and journal. Additionally, the frequencies of keywords extracted from the articles were assessed and then included in a network analysis of the development of insomnia.
All data were downloaded from the Web of Science and imported into the bibliometric package (Version 3.0.0) in R software (Version 4.1.3) (5), which converts and analyses automatically, including the distribution of countries/regions, years of publication, and authors. Publication quality by author was assessed based upon metrics that included the number of publications, citations in the research area, publication h-index value. The h-index is used to quantify an individual’s scientific research output and measure his citation impact (6).
Networks were constructed using VOS viewer v.1.6.18 (7) (Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands), which is commonly used to analyze and visualize relationships among authors, countries, co-citations, keywords, and the terms used in articles.
The Shapiro–Wilk test was applied to test the normality of the distribution of individual variables. We show the mean and standard deviation for data with a regularly distributed distribution and the median and range for data with a skewed distribution. The Tukey method was also employed for plotting the whiskers and outliers. The p-values from pairwise t-tests were adjusted according to either the Bonferroni post-hoc test or Mann–Whitney test to correct for the performance of multiple statistical analyses. All p-values were two-tailed, and a p-value of ≤0.05 was considered to indicate statistical significance. We used a one-way analysis of Kruskal–Wallis test for skewed data. The Mann–Kendall rank correlation was employed to test for correlations among non-parametric variables.
Results
Global trends of annual publication
A total of 44,654 eligible publications were listed in peer-reviewed journals on the ISI Web of Knowledge WoS Core on 31 March 2022. Manuscripts were screened according to inclusion and exclusion criteria and ranked according to citation frequency. The top 100 influential manuscripts were obtained. General information is detailed in Table 1.
Table 1. The top 100 most-cited articles in insomnia.
Over the course of 20 years, the total number of citations for the top 100 works of literature varied, but reached a peak in 2021 (Figure 1). The total citation frequency of the top 100 highly cited literature was 58,229 (ranging from 270 to 3,384), with a mean citation frequency of 582.29 and a median citation frequency of 427.5. To exclude the effect of year on citation volume, we analyzed the average annual citation rate of the 100 documents, the highest of which was “Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019” by Lai et al. (8) (average annual citation rate of 893.33; Table 1).
Figure 1. Global trends in publications on insomnia research.
Most articles on the list were published from 2005 to 2006 (n = 24), followed by articles published from 2020 (n = 9; Figure 2A). The number of citations was high for articles published between 2001 and 2012 (mean total citations = 3762) and decreased for articles published after 2012, but reached a peak in 20 years for articles published in 2020 (citations = 7852; Figure 2B). The total citation rate of an article was not related to the date of publication (r = 0.07108, p > 0.05, Mann–Kendall test; Figure 3A). However, the current citation rate of an article (as measured by the number of citations in 2021) suggests that articles published after 2011 are more likely to have been cited in recent years. This correlation was statistically significant (r = 0.5394, p < 0.0001, Mann–Kendall test: Figure 3B).
Figure 2. (A) The total number of publications for each type of article (clinical or review article) according to publication year. (B) The total number of citations publications for each type of article (clinical or review article) according to publication year. (C) Bar graph showing the number of citations (and standard deviation) for the 100 most-cited articles according to type of article (clinical research, review article). Box: lower linee= Box: lower linee number of= Box: lower linee number of citati= median value, white points = outliers. The Tukey method was used for plotting the whiskers and outliers. *Outlier.
Figure 3. (A) Overall citation rate since publication, and (B) current (2021 = last full year) citation rate for the 100 most-cited articles according to the publication date of the article.
Of the 100 articles, 50 were clinical research, 49 were review articles and 1 was basic research. Due to the small sample size of the basic research, we analyzed the number of citations for review articles and clinical research (Table 2) and found that the review articles did not vary significantly with respect to total citations per article compared to the clinical research articles [Mann–Whitney test, p = 0.08; clinical research: median = 397.5 (range = 275–3384); review articles: median = 531(range = 270–2126): Figure 2C].
Table 2. Citations for review articles and clinical research.
Distribution of countries and institutes
The global contribution of insomnia research was analyzed and represented by a blue-coded world map in the R software (Figure 4A). Of the 35 countries and territories identified for this study, the USA had the highest number of articles (n = 56), followed by Canada (n = 22), Germany (n = 11), Italy (n = 10) and the UK (n = 7) (Figure 4B). Studies from the USA were the most cited (24,423 citations), followed by Canada (11,832 citations), Germany (6,329 citations), China (5,587 citations) and the UK (3,097 citations) (Figure 4C).
Figure 4. Countries contributing to insomnia research. (A) World map showing the distribution of countries in this field. (B) Top 15 countries with the largest number of publications. (C) Total citations of related articles from different countries.
In the co-authorship analysis, a total of eight countries with more than five publications in the field were analyzed (Figure 5A). The five countries with the highest total connection intensity were the United States (total link strength = 19 times), Germany (17 times) and Canada (15 times). A total of 235 institutions are involved in this field. Laval University (38 articles) contributed the most publications, followed by Harvard University (11 articles), Stanford University (10 articles), University of Pittsburgh (10 articles), and Duke University (9 articles). We analyzed the co-authorship of 235 institutions with more than five publications. Eight institutional collaborations are shown (Figure 5B). The strongest institutions overall were Duke University (total link strength = 14 times).
Figure 5. Co-authorship analysis of countries and institutions. (A) Network map of co-authorship between countries with more than five publications. (B) Network map of co-authorship between institutions with more than five publications. The thickness of the lines indicates the strength of the relationship.
Analysis of author
Considering the number of publications, MORIN CM. is the most productive author, with 17 articles (Figure 6A) MORIN CM. was also the top-ranked author in terms of citations in this field (108 citations) (Figure 6B).
Figure 6. Analysis of authors. (A) Number of publications from different authors. (B) Total citations in the research filed from different authors. (C) Network map of co-authorship between authors with more than five publications. Size of the circles indicate the number of articles in the 100 most cited list, while the width of the curved line represents the link strength. The distance between two authors indicates approximate relatedness among the nodes.
We analyzed a total of 481 authors, 60 of whom were co-authors in more than two publications. Excluding 36 unrelated items, 24 authors were shown to have collaborated (Figure 6C). The author with the highest total linkage intensity was MORIN CM. (total link strength = 40 times).
Analysis of most cited journal
The 100 articles were published in 42 journals. Figure 7 shows the top ten h-index and cited journals that published related articles (Figures 7A, B). Of these 42 journals, the highest h-index was Sleep (h-index = 31), followed closely by Sleep Medicine Reviews (h-index = 9). Sleep was cited the most (928 times), followed by Sleep Medicine Reviews (193 times). In the co-citation analysis, we analyzed a total of 1,352 journals, and a total of 52 journals were cited more than 20 times (Figure 7C).
Figure 7. Analysis of journals. (A) Total citations in the research filed from different journals. (B) h-index of publications from different journals. (C) Network map of journals that were co-cited in more than 50 publications. The size of the circle represents the number of papers in the top 100 list.
Co-occurrence analysis of keywords
We analyzed a total of 33 keywords that were identified as appearing more than five times (Figure 8A). The colors in the overlay visualization shown in Figure 8B indicate the average year of publication of the identified keywords. The keywords which published after 2011 are colored more green or yellow. The density visualization shows the same identified keywords mapped by frequency of occurrence (Figure 8C).
Figure 8. Co-occurrence analysis of keywords. (A) Mapping of keywords of studies. (B) Distribution of keywords according to average publication year (blue: earlier, yellow: later). (C) Distribution of keywords according to the mean frequency of appearance. Keywords in yellow occurred with the highest frequency.
Citation and co-citation analyses
The citation analysis showed 94 pieces of literature with more than 50 citations (Figure 9A). As shown in Table 1, “Validation of the Insomnia Severity Index as an outcome measure for insomnia research” [Bastien et al. (8)] was cited 3,384 times, followed by “Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019” [Lai et al. (8)] with 2,680 citations and the third most cited is “Epidemiology of insomnia: what we know and what we still need to learn” [Ohayon (10)], with 2,126 citations.
Figure 9. (A) Network map of citation analysis of documents with more than 50 citations. (B) Network map of co-citation analysis of references with more than 10 citations. The size of the circle represents the number of papers in the top 100 list.
We analyzed 38 references that were co-cited more than 10 times in total (Figure 9B). The three most cited references were Ford de. (107) (1989, JAMA-J AM MED ASSOC; 33 citations), Ohayon (10) mm. (2002, sleep med rev; 30 citations), and Breslau (108) (1996, bio psychiat; 29 citations).
Discussion
General trends in insomnia research
Bibliometrics allows for quantitative analysis of a researcher’s individual achievements, or even a country’s or institution’s contribution and international impact in the field, through a statistical analysis of the total number of academic papers published in a clinical field and the total frequency of citations (109). In this study, we combined bibliometric analysis with network visualization to identify the initial 100 most influential manuscripts in the field of insomnia based on global citation frequency, highlighting the contributions that have led to significant advances in insomnia research and pointing to current trends in the field.
With the largest number of publications and citations, and the highest co-authorship analysis ranking by country, the United States is currently the world leader in insomnia research. These results suggest that the US is likely to have a major impact on the direction of research in the field and has the strongest collaboration globally. The citations of articles from Canada, Germany, Italy and the UK have also increased significantly over the last three decades. China has a small total number of publications, but ranks fourth in total citations; it ranks sixth in collaborations with other countries, indicating that China has an influential publication in the field of insomnia and actively maintains close collaborations with other countries. The Laval University Institute is the most productive, with 38% of the publications, while Duke University ranks first in the co-authorship analysis, indicating its close cooperation with other institutes.
Influential authors and studies in insomnia
Morin, C.M. has the largest number of publications and citations and also ranks first in co-authorship analysis conducted by authors. Of these top 100 highly cited publications, Morin C.M. has published 17 articles, 8 of which he is the first author. Dr. Morin is interested in the validation of assessment scale for insomnia. Utilizing scales to evaluate the therapeutic effects of insomnia is the most convenient and widely used method, and the reliability and validity analysis results are critical for the scale to be used as an outcome indicator. Dr. Morin examined psychometric indices of the Insomnia Severity Index to evaluate treatment response in a clinical sample (9), and validated the Dysfunctional beliefs and attitudes about sleep, providing a variety of indicators for the assessment of insomnia (10). Nevertheless, the original version of the ISI and the PSQI are the most commonly used, and the original version of the ISI remains the only validated scale that is highly recommended for all insomnia research protocols. Dr. Morin has also conducted extensive research on cognitive behavioral therapy for insomnia and its comorbidities (110, 111). His team’s current efforts continue to focus on evaluating the efficacy of cognitive behavioral therapy and optimizing the procedural approach (112, 113).
According to the literature citation analysis and reference co-citation analysis, the most frequently cited Bastien et al. (8) reported clinical validation of the Insomnia Severity Index Scale (ISI) as a brief screening indicator for insomnia and an outcome indicator for treatment studies, indicating that the ISI is a reliable and valid tool for quantifying perceived insomnia severity. The ISI is a brief self-report instrument designed to assess subjective symptoms and daytime status of insomnia and the extent to which insomnia causes worry or distress. The ISI has been continually validated and the study by Bastien et al. was the first formal psychometric analysis of the reliability and validity of the ISI. Further validation of the ISI using item response theory (IRT) analysis was reported by Morin et al. (114), obtaining evidence on internal consistency, item response patterns and convergent validity, yielding new evidence on optimal sensitivity and specificity indices for case finding and assessment of minimal important changes following treatment (12). A recent meta-analysis (115) reported on the construct validity of the Insomnia Severity Index (ISI), which showed that studies reporting validated factor analyses (CFA) had more reliable results than those reporting only exploratory factor analyses (EFA), and that two-factor solution were strong expressions of dimensionality and higher reliability indicators for the ISI compared to three-factor solutions.
Future outlook
Our co-occurrence network diagram, categorized by subject area or date of publication, shows current hotspots and future directions in insomnia research (Figures 8A–C). The keywords indicate that insomnia research involves a wide range of populations (elderly, adolescents), causal factors (quality of life, coronavirus), disorders (anxiety disorders, depression) and therapies (cognitive behavioral therapy, pharmacotherapy). The most recent keywords indicating future trends in the field are as follows:
COVID-19 and insomnia
The total number of citations in the insomnia-related literature rose significantly in 2021, reaching a peak in the last 20 years. This may be related to the outbreak of the Corona Virus Disease 2019 (COVID-19). The impact of the new coronavirus pneumonia outbreak has led to an increase in psychological disorders in the population and a climb in the prevalence of insomnia, with 36.7% of adults from 13 countries having clinical symptoms of insomnia and 17.4% meeting diagnostic criteria for insomnia (24, 114). Spielman identified negative life events and other stressors as triggers for the development of insomnia (116), with up to 37% of the population experiencing insomnia in the presence of stressful events (117). During the early stage of the COVID-19 pandemic, insomnia symptoms were mainly associated with acute psychological reactions due to the rapid spread of the disease and strict enforcement of restrictions, as well as poor sleep hygiene (118). During the late stage, insomnia symptoms are associated with economic stress associated with the COVID-19 pandemic (118) and the impairment of sleep patterns (119). Recent studies have shown that into the late stages, sleep is characterized by significant objective sleep fragmentation in the presence of adequate sleep duration (120), suggesting that the adverse effects of the initial pandemic outbreak on sleep will persist. Studies of insomnia during the COVID-19 pandemic highlight the importance of focusing not only on the primary diseases, but also on the psycho-psychological issues, particularly insomnia during global public health events.
Depression, anxiety, and insomnia
In our analysis of keywords, we found that “anxiety,” “depression,” and “mental disorders” were frequently mentioned in 100 documents as the second most frequently occurring keywords after “insomnia.” Studies have shown that there is a strong relationship between insomnia, depression and anxiety, with insomnia considered a risk factor for anxiety and depression (121), with those suffering from insomnia 9.82 times more likely to have clinically significant depression and 17.35 times more likely to have clinically significant anxiety compared to those without insomnia (38). Anxiety and depression are also considered risk factors for insomnia (122), suggesting that insomnia is bilaterally associated with psychiatric disorders such as anxiety and depression (41). In terms of biological mechanisms, polymorphisms and dysregulation of the serotonin, dopamine(DA), oxytocin (OXT) and genes may be associated with the development and maintenance of insomnia and mood disorders (123), while behavior and thoughts can in turn affect the activity of the serotonin, DA, OXT, and genes (124). In terms of brain function, sleep disturbances have been shown to disrupt the function of cortical neural circuits, including the amygdala, striatum, anterior cingulate cortex and prefrontal cortex (PFC) (125), which play a key role in the regulation of the affective system (126). In addition, there is growing evidence that insomnia disrupts brain functions associated with the reward system (127, 128), and that dysfunction of the reward system is associated with a variety of neuropsychiatric disorders (129), including depression, bipolar disorder (127, 128, 130) and others.
Subtypes of insomnia
Insomnia is a heterogeneous disorder (131), and identifying clinically relevant subtypes of insomnia disorders can help reduce heterogeneity, identify etiology, and personalize treatment (132). In Ohayon (10) proposed that epidemiological studies should focus on distinguishing different subtypes of insomnia. Typing by sleep stage symptoms, such as difficulty falling asleep (DIS), difficulty maintaining sleep (DMS), early awakening (EMA), or a combination of four subtypes (133); typing by insomnia episodes and duration, such as chronic insomnia, short-term insomnia (134); and typing by primary and secondary clinical features of insomnia, such as primary insomnia, secondary insomnia (135). Although these subtypes can differ in terms of stable sleep-related characteristics, reliability and validity are lacking and heterogeneity still prevails (136). It remains difficult to find consistent insomnia features in terms of cognition, mood, personality, life history, polysomnography, and sleep microstructure, and this inconsistency suggests that different subtypes of insomnia disorder have not been fully identified (137). For a long time, researchers have been working on different aspects of the subtypes of insomnia disorders, such as natural history of insomnia (94), subjective and objective sleep duration (74), sleep microstructure (138), non-insomnia characteristics (life history, affective and personality traits) (137), and clustering subtypes of insomnia (subtyping based on subjective sleep variables as well as age at onset of insomnia, the severity of anxiety and depressive symptoms) (139). Vgontzas et al. (74) proposed that insomnia with short objective sleep duration is the most biologically severe phenotype of the disorder and is associated with a higher risk for hypertension, diabetes, and other diseases. Also, it appears that insomnia with objective short sleep duration is a biological marker of genetic predisposition to chronic insomnia. In the future, the underlying genetic, neurobiological, and neuropsychological mechanisms of insomnia with objective short sleep duration could be further explored. In terms of polysomnography (140), brain imaging (141), and genetics (142), we can also examine the association of other sleep variables with other phenotypes of insomnia.
Cognitive behavioral therapy
Cognitive behavioral therapy (CBT) is the most widely researched form of psychotherapy, which leads to changes in emotional distress and problem behavior by altering therapeutic strategies that are maladaptive to poor cognition (14). CBT for insomnia (CBT-I) has long been shown to be more effective than control therapy (143). Cognitive behavioral therapy for insomnia (CBT-I) is now commonly recommended as a first-line treatment for chronic insomnia because of the potential for sustained benefit from psychotherapy without the risk of tolerance or adverse effects associated with pharmacological approaches (65). Recent evidence suggests that CBTI can also be used to treat acute insomnia caused by stress (144). Many elements of this treatment approach can be applied to stressful events such as the current COVID-19 pandemic and can be adapted to treat and prevent sleep problems resulting from confinement, increased stress and changes in circadian and daily activities (78). The development of technologies such as the Internet, big data and artificial intelligence has brought about a boom in digital medicine in the healthcare industry, enabling the digitization of CBT-I (145), and the effectiveness of digital cognitive behavioral therapy (dBT-I) for insomnia has been validated (146). In recent years, dBT-I has been widely used during the COVID-19 pandemic, and Liu et al’s (147) study provides an entry point for building a dBTI platform and a theoretical basis for clinical application.
Sleep microstructure
In recent years, sleep microstructure has gradually gained widespread attention, and a number of the 100 articles we examined have begun to focus on slow-wave sleep. Slow wave sleep (SWS) is a component of non-REM sleep that is important in neurophysiological processes like memory and cognition (148). According to the “active system consolidation hypothesis,” slow oscillations, in conjunction with sleep spindle waves, drive the repetitive reactivation of newly encoded memories during slow-wave sleep, facilitating their integration into long-term memory storage sites (149). A growing body of research confirms that auditory stimulation (150), transcranial direct current stimulation (151), and medication (152) are all effective in improving memory function by enhancing slow waves of sleep (153). Slow-wave sleep is not only used for memory enhancement, but has also been widely used to improve cognitive function in patients with mental illness (154, 155) and for sensory-motor recovery in stroke patients (156). Recent studies have shown that enhancing SWS in healthy individuals profoundly affects the connections between the endocrine and autonomic nervous systems (157), opening up a wide range of potential applications for enhancing SWS.
Strengths and limitations
To the best of our knowledge, this is the first bibliometric analysis of the Insomnia research trend. Using the R bibliometric package, we conducted a comprehensive survey of the literature to perform quantitative and qualitative analyses of the publication output and quality of studies from various authors. We also used a well-known scientometric software tool (VOSviewer) to build and visualize the bibliometric networks by analyzing co-authorship, co-citation, and co-occurrence. Nevertheless, our analyses have some limitations. Firstly, the search is primarily conducted in the WoS database. Although WoS is the most commonly used database in scientometrics, it is advisable to combine the results with those from other databases, such as PubMed and Scopus. Secondly, our search did not separate mechanistic studies from clinical studies, ignoring the research progress in mechanistic studies; however, this could also indicate that mechanistic studies in the field of sleep could be strengthened. Third, the keyword analysis results may have been influenced by incomplete keyword extraction. To better display the keywords, keywords that appeared more than five times in the network were shown. Fourthly, as this is a developing area of research, we may have overlooked the contribution of analyzing recently published studies because of their low citation frequency, despite some studies being published in high quality journals.
Conclusion
In conclusion, to our knowledge, this is the first bibliometric study to identify the 100 most cited papers in insomnia research. Our results suggest that the outbreak of the COVID-19 epidemic is strongly associated with the onset of insomnia and stimulates the researcher’s interest. The key words suggest “COVID-19;” “anxiety,” “depression,” “CBT,” and “sleep microstructure” are currently hot topics in the field of insomnia and will be future research trends in the field, indicating that the focus of research has shifted from insomnia epidemiology and scale validation to the study of co-morbidities and sleep microstructure of insomnia. Despite its limitations, citation analysis provides an important quantitative approach to research in the field of comparative science. The findings of this study may provide a valuable reference for researchers to guide and implement their scientific research interests in the field of insomnia.
Author contributions
QW, KL, and WW designed the study. QW and KL wrote and revised the draft manuscript and carried out data visualization and graphical interpretation. QW, KL, SL, JJ, and XW performed the literature search, retrieval, and data collection. WW provided the critical assistance or funding. All authors contributed and approved the final draft of the manuscript before submission.
Funding
This work was supported by the National Natural Science Foundation of China (grant number: 82274631) and Jiangsu Provincial Department of Science and Technology (grant number: BE2021751).
Acknowledgments
We acknowledge the support of the Team of the Insomnia Research Team of Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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Keywords: bibliometric analysis, citations, insomnia, trends, VOSviewer
Citation: Wan Q, Liu K, Wang X, Luo S, Yuan X, Wang C, Jiang J and Wu W (2023) The top 100 most cited papers in insomnia: A bibliometric analysis. Front. Psychiatry 13:1040807. doi: 10.3389/fpsyt.2022.1040807
Received: 09 September 2022; Accepted: 08 December 2022;
Published: 04 January 2023.
Edited by:
Mehmet Y. Agargün, Van Yüzüncü Yıl University, TurkeyReviewed by:
David Neubauer, Johns Hopkins Medicine, United StatesCélyne H. Bastien, Laval University, Canada
Copyright © 2023 Wan, Liu, Wang, Luo, Yuan, Wang, Jiang and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Wenzhong Wu, ✉ maerta_zhongacu@163.com
†These authors have contributed equally to this work and share first authorship