Current trends in pain management: A bibliometric analysis for the 1980-to-2023 period.

In this study, we presented a bibliometric analysis of 10,566 articles on the topic of PM, which has shown an exponential growth trend in recent years. This article provides an important bibliometric analysis that will help us understand the current approaches to PM and future research directions. In recent years, starting in 2020, trending research topics have shifted towards e-health, telemedicine, virtual reality, digital health, mental health, peripheral nerve blocks, erector spinae plane blocks, quadratus lumborum blocks, opioid use disorder, buprenorphine, musculoskeletal pain, COVID-19, cervicalgia, and interprofessional collaboration. In recent years, telehealth, e-health, mobile health, and virtual reality applications have started to play a more significant role in PM. These technologies can facilitate communication between patients and experts and assist patients in monitoring and managing their pain. Since every patient’s experience of pain is different, the importance of personalized treatment plans has also increased in recent years. Furthermore, peripheral nerve blocks have become 1 of the most frequently researched topics in recent years. Peripheral nerve blocks involve the direct application of local anesthetic drugs to nerves, resulting in minimal systemic effects (e.g., some complications associated with general anesthesia). Advances in imaging technologies have recently contributed to the more precise and safer administration of peripheral nerve blocks. This approach encourages collaboration among healthcare professionals from various specialties, including anesthesiologists, surgeons, rheumatologists, and pain specialists. We have identified research leadership not only in Western countries with major economies (USA, Canada, Australia, and European countries) but also in China, India, and Turkey in the field of PM. While there are significant international collaborations globally, we believe that increasing international collaborations in developing countries is essential.

Pain is a sensory and emotional experience that typically arises from causes such as tissue damage, illness, or stimulation of the nervous system. It is a highly complex phenomenon consisting of both sensory and emotional components. Pain can serve as a warning sign indicating potential harm or the presence of an issue within the body. [ 1 ] Pain is a universal experience that affects human health and can be associated with various etiologies. Therefore, the effective management of pain represents a significant area in clinical medicine. [ 2 ] Pain management (PM) represents an approach in which pain is addressed from a multidisciplinary perspective, and individualized treatment plans are developed. [ 3 ] This approach encompasses a multidisciplinary approach involving the perception, assessment, treatment, and control of pain. Consequently, PM plays a crucial role among various healthcare disciplines, including physical therapy, neurology, anesthesiology, psychology, and others, working on different types and causes of pain. PM aims to reduce and control the severity of pain, manage its duration, improve the quality of life, and restore the functionality of patients. This approach encompasses a broad field of research, application, and learning to enhance patients’ quality of life and minimize the adverse effects of pain. [ 3 , 4 ] PM addresses both acute and chronic pain conditions and encompasses pharmacological and non-pharmacological approaches. These approaches may include pharmacotherapy (drug treatment), non-pharmacological treatments (physical therapy, psychotherapy, acupuncture, massage, etc), rehabilitation, surgical interventions, and other interventions. Additionally, PM takes into account psychosocial factors that influence the patient’s pain experience and considers the patient’s specific needs. [ 5 , 6 ] PM can be applied to different pain conditions, such as acute pain (e.g., post-surgical pain) and chronic pain (e.g., rheumatoid arthritis, cancer pain). Furthermore, PM aims to address the physical, emotional, and social dimensions through which the patient suffers due to pain. [ 1 , 6 ] Bibliometric analysis is a research field that examines the quantitative and qualitative characteristics of scientific literature and conducts these investigations using data analytics and statistical methods. [ 7 , 8 ] This type of analysis is used for the examination and evaluation of text-based sources such as academic publications, journal articles, conference papers, theses, and other scientific documents. [ 9 ] Bibliometric analysis is an important research method used to understand the development of scientific research fields, publication trends, citation relationships, and the structure of scientific communities. [ 10 ] It provides valuable insights to researchers, scientific communities, and decision-makers, helping them guide and plan scientific knowledge more effectively. [ 11 ] This type of analysis plays a significant role in the enhancement of scientific discoveries and research strategies. [ 12 ] The primary objectives of bibliometric analyses include Examining Publication Trends, Citation Analyses, Research Network Analyses, Data Mining and Discoveries. Publication Trends analysis evaluates academic trends by examining how publications are distributed and how they change over time within specific topics, disciplines, or research areas. [ 7 – 13 ] The aim of this study was to monitor the advancement of the PM research field, demonstrate global productivity, identify the most highly cited studies, delineate collaborations between research areas and countries, and uncover new research topics and intriguing trends.

Conceptualization: Emre Demir, Guvenc Dogan, Murat Kiraz, Arzu Akdağli Ekici, Selçuk Kayir, Musa Ekici, Gülçin Aydoğdu, Tuba Kayir. Data curation: Emre Demir, Gülçin Aydoğdu. Formal analysis: Emre Demir, Guvenc Dogan, Murat Kiraz, Arzu Akdağli Ekici, Selçuk Kayir, Musa Ekici, Gülçin Aydoğdu, Gül Doğan, Tuba Kayir. Investigation: Emre Demir, Guvenc Dogan, Murat Kiraz, Arzu Akdağli Ekici, Selçuk Kayir, Musa Ekici, Gülçin Aydoğdu, Gül Doğan, Tuba Kayir. Methodology: Emre Demir, Guvenc Dogan, Murat Kiraz, Arzu Akdağli Ekici, Selçuk Kayir, Musa Ekici, Gülçin Aydoğdu, Gül Doğan, Tuba Kayir. Resources: Emre Demir. Software: Emre Demir, Guvenc Dogan, Murat Kiraz, Arzu Akdağli Ekici, Selçuk Kayir, Musa Ekici, Gülçin Aydoğdu, Gül Doğan, Tuba Kayir. Supervision: Emre Demir, Guvenc Dogan, Murat Kiraz, Arzu Akdağli Ekici, Selçuk Kayir, Musa Ekici. Validation: Emre Demir. Visualization: Emre Demir, Guvenc Dogan, Murat Kiraz, Arzu Akdağli Ekici, Selçuk Kayir, Musa Ekici, Gülçin Aydoğdu, Gül Doğan, Tuba Kayir. Writing – original draft: Emre Demir, Guvenc Dogan, Murat Kiraz, Arzu Akdağli Ekici, Selçuk Kayir, Musa Ekici, Gülçin Aydoğdu, Gül Doğan, Tuba Kayir. Writing – review & editing: Emre Demir, Guvenc Dogan, Murat Kiraz, Arzu Akdağli Ekici, Selçuk Kayir, Musa Ekici, Gülçin Aydoğdu, Gül Doğan, Tuba Kayir.

To access scientific studies on the subject of PM, the Web of Science (WoS) database (Clarivate Analytics, Philadelphia) was used. Since publications prior to 1980 are not indexed in WoS, the starting year was set as 1980, and all studies indexed in WoS between 1980 and 2023 were accessed. Bibliometric analyses included only original articles, excluding other types of publications. Specifically, studies indexed in the research fields of Veterinary Sciences, Agriculture, and Zoology were excluded. The approach employed for conducting the search in this study was as follows: [(Title = (pain management) NOT (Veterinary Sciences AND Agriculture AND Zoology] AND [Document Type = (Article) AND Publication time: 1980 to 2023) (Access to articles was performed on August 1, 2023). This search method provided access to all articles containing the terms “pain management” (management of pain, management of cancer pain, management of chronic pain, management of acute pain, etc) in their titles. Basic statistical analyses were performed using the SPSS software (Version: 22.0, SPSS Inc., Chicago, Licence: Hitit University). In order to forecast the trajectory of articles in the field of PM for the next 5 years, we utilized the Smoothing Forecaster in Microsoft Office Excel. Seasonal adjustment was incorporated into the prediction model to anticipate the article trends. Exponential smoothing is a method used to forecast time series data. In this method, there is a greater emphasis on the recent observations. In other words, more importance is given to the data from closer time periods. The world map, displaying the intensity of colors to depict countries’ contributions to the literature on PM, was generated utilizing the website www.paintmaps.com . [ 14 ] Bibliometric analyses were performed using the biblioshiny interface in bibliometrix library ( http://www.bibliometrix.org/ ), which is an R Studio-Tool for science mapping, and VOSviewer open access bibliometric software (Version 1.6.19, Leiden University). [ 15 , 16 ] Bibliometrix and VOSviewer software packages are more commonly used in the literature to visualize and construct bibliometric networks, and they have some relative advantages and differences compared to each other. Therefore, in our study, both packages were used for bibliometric analyses and network visualizations. Bibliometric networks can encompass countries, institutions, researchers, journals, keywords, and can be constructed based on citation, co-citation, or co-authorship relationships. [ 12 , 13 ] Co-occurrence analysis of keywords, also known as co-word analysis, is a bibliometric technique used to map research domains. In the field of bibliometrics, co-occurrence analysis is applied to explore potential associations between 2 terms that appear within the same publication. This analytical method investigates the simultaneous presence of pairs of items (keywords) within a document, aiming to uncover relationships among the terms found in textual content. Co-word analysis is closely related to co-citation analysis, with the former focusing on keywords within documents and the latter on citations. Co-citation analysis offers a means to chart the structural landscape of a research field by identifying documents that are jointly cited. [ 7 , 9 ] Reference Publication Year Spectroscopy (RPYS) is a bibliometric method that can be used to analyze the historical origins and development of research fields. This method maps the distribution of publication years of cited references. This analysis can be useful in understanding which years received the most attention in a field or subject and how this interest has changed over time (i.e., when the literature has concentrated in specific periods). [ 15 , 17 ] WordCloud analysis is used to create a visual representation of the frequency of a word or term within a text. The purpose of using WordCloud is to examine the most frequently used terms in articles published on a particular topic. In summary, Word Cloud is a system that reveals words in visual form by highlighting the frequency of occurrence of relevant words in articles. [ 17 ] Conceptual structure analysis is employed to understand the research landscape referred to as the “research front,” and to identify the most important and current topics. This analysis helps determine the conceptual structure of publications related to a specific topic, revealing its main themes, subthemes, and relationships. Factor analysis, which is used as a subanalysis of conceptual structure analysis, examines the relationships and structures among numerous variables in a dataset, reducing these variables into smaller and meaningful groups or factors. [ 15 ] Thematic evolution analysis can be used to track developments and changes in a research domain. Researchers can observe the emergence of new topics and the evolution of existing ones over time by examining the conceptual structure of publications related to a specific topic. Themes in thematic evolution are interpreted according to the quarter in which they are placed in the thematic maps obtained for the examined periods: top right quadrant: motor themes; bottom right quadrant: basic themes; bottom left quadrant: emerging or declining themes; and top left quadrant: highly specialized/niche themes. [ 15 , 17 ] In factor analysis, the MCA method is used to visualize and analyze relationships between different categorical variables. It is particularly useful for understanding relationships among numerous categorical variables. MCA aims to represent multiple categorical variables with fewer components. Thus, MCA enables the reduction of the data set’s dimensionality, resulting in a simpler and more comprehensible structure. [ 15 , 17 ]

As a result of the literature review, a total of 20,080 publications on the subject of PM were found in the WoS database between 1980 and 2023. Publications tagged under the research areas of Veterinary Sciences, Agriculture, and Zoology were excluded, and as a result, the remaining 19,734 publications were considered. The distribution of these publications was as follows: Articles (10,566, 53.5%), Review Articles (3096, 15.6%), Meeting Abstracts (2825, 14.3%), Letters (934, 4.7%), Proceedings Papers (618, 3.1%), and the remaining in other publication types (Editorial Materials, Book Chapters, Book Reviews, News Items, Notes, Books, Discussions, Software Reviews, Bibliographies, etc). Bibliometric analyses were conducted using a subset of 10,566 articles from the total of 19,734 publications. Of these articles, 94.2% (n = 9948) were published in English, while the rest were published in other languages (German, French, Spanish, Korean, Turkish, Italian, Polish, Portuguese, etc). Furthermore, 76.3% (n = 8066) of the articles were indexed in SCI-Expanded, 24.8% (n = 2617) in the Social Sciences Citation Index (SSCI), and 17.2% (n = 1820) in the Emerging Sources Citation Index (ESCI) (note that a single article can be indexed in both SCI-Expanded and SSCI simultaneously). The line graph in Figure 1 illustrates the distribution of the number of articles published on the PM over the years. Since the year 2023 is not yet complete, it was not included in the forecasting model. In addition, the predicted values obtained by performing Exponential Smoothing with seasonal adjustment to determine the number of articles that could be published in a 5-year period from 2023 to 2027 are also presented in Figure 1 . The model with the highest R 2 value (99%) was obtained with the exponential model. According to the exponential model findings, it is estimated that there will be 823 articles (confidence interval, CI: %: 762–884) published on PM in 2023 and 1031 articles (CI%: 948–1113) in 2027 (Fig. 1 ). A line graph depicting the change in the number of articles published on pain management over the years and the estimated article trend for the years 2023 to 2027. The research domains that featured a substantial volume of articles related to PM (240 or more articles) included: Anesthesiology (1697, 16.1%), Medicine General Internal (1631, 15.4%), Clinical Neurology (1493, 14.1%), Nursing (1177, 11.1%), Health Care Sciences Services (773, 7.3%), Surgery (685, 6.5%), Rehabilitation (622, 5.8%), Orthopedics (602, 5.6%), Pharmacology Pharmacy (515, 4.8%), Oncology (471, 4.4%), Pediatrics (456, 4.316), Neurosciences (399, 3.7%), Public Environmental Occupational Health (327, 3%), Emergency Medicine (308, 2.9%), Medicine Research Experimental (286, 2.7%), and Obstetrics Gynecology (245, 2.3%) (note that an article can be tagged in multiple research areas). In all 10,566 articles on the subject of PM, a total of 11,948 different keywords were used. Out of these keywords, 128 were co-occurrences used in more than 30 different articles, as presented in Table 1 . Furthermore, the top 50 Author keywords used in articles over time, along with their co-occurrence counts, are depicted in Figure 2 A (to optimize the figure, the top 3 most frequently used keywords, namely pain, PM, and chronic pain, were not included within the figure). The cumulative trend of the top 10 most frequently used keywords over time is shown in Figure 2 B. The 128 most frequently used keywords in published articles on pain management. NU = Number of uses (co-occurrences). (A) A graphic showing the top 50 keywords most commonly used in articles from the past to the present. (B) A line graph illustrating the cumulative frequency of usage over time for the top 10 most frequently used keywords in articles. Trend keyword analysis using the Biblioshiny application was conducted in 3 different time periods. The findings of trend keyword analysis from 1980 to 2004 are presented in Figure 3 A, from 2005 to 2013 in Figure 3 B, and from 2014 to 2023 in Figure 4 . The usage frequencies and yearly distribution of 5 trend keywords for each year are visualized in the figures. (A) A graphic depicting the findings of trend keyword analysis from 1980 to 2004. (B) A graphic depicting the findings of trend keyword analysis from 2005 to 2013. Footnote: Lines represent the usage trend of keywords over the years, and circle sizes indicate the frequency of usage. A graphic depicting the findings of trend keyword analysis from 2014 to 2023. Footnote: Lines represent the usage trend of keywords over the years, and circle sizes indicate the frequency of usage. The network visualization map generated through cluster analysis using the VOSviewer package is presented in Figure 5 A. Based on the Cluster analysis findings for 128 keywords used in at least 30 different articles (co-occurrences = 30), 8 distinct clusters were identified. Additionally, a trend network visualization map for the period 1980 to 2023, aiming to determine historical and current research trends, is provided in Figure 5 B. The Keyword Heatmap generated using the VOSviewer package is displayed in Figure 5 C, and the WordCloud visualization obtained using the Biblioshiny package with Keyword Plus is shown in Figure 5 D. (A) A network visualization map illustrating the results of cluster analysis. Footnote: Keywords with the same colors belong to the same clusters. As the number of keywords used in articles increases, the size of the circle also increases. In general, the closer 2 terms are to each other, the stronger their relationship. (B) A network visualization map showing past and current trends on pain management. Footnote: In the legend at the bottom right corner of the figure, as the relevance of topics increases, the colors transition from blue to red (blue–green–yellow–red). The blue color indicates that a term was published in previous years, while the red color indicates that a term was published in later years. (C) The Keyword Heatmap. Footnote: The transition from blue to red indicates an increase in the importance of keywords. (D) WordCloud visualization obtained with Keyword Plus. A factor analysis was conducted using author keywords to determine the conceptual structure of the PM subject. The findings of the factor analysis, performed using Multiple Correspondence Analysis, are presented in Figure 6 . A conceptual structure map displaying the findings of factor analysis conducted using Multiple Correspondence Analysis. Footnote: The origin of the map represents the average position of all column profiles and therefore represents the center of the research area (indicating common and widely shared topics). To determine the conceptual structure of the PM subject using author keywords, thematic evolution analysis was conducted. Thematic evolution for the defined periods of 1980 to 2004, 2005 to 2013, and 2014 to 2023 based on publication trends is presented in Figure 7 A, and thematic maps for each period are shown in Figure 7 B. (A) Thematic Evolution Maps for the Periods 1980 to 2004, 2005 to 2013, and 2014 to 2023. (B) Thematic Maps for the Periods 1980 to 2004, 2005 to 2013, and 2014 to 2023. Footnote: Thematic maps obtained for the examined periods: (1) top right quadrant: motor themes; (2) bottom right quadrant: basic themes; (3) bottom left quadrant: emerging or declining themes; (4) top left quadrant: highly specialized/niche themes. The top 20 most productive countries contributing to the literature on PM in descending order are the United States of America (Number of articles: 4021), United Kingdom (791), Canada (602), Australia (456), China (394), Germany (388), France (295), Italy (273), India (269), Turkey (229), Spain (184), Korea (159), Iran (156), Sweden (126), Japan (117), Netherlands (116), Switzerland (93), Norway (91), Brazil (82), and Denmark (80). A color density map illustrating the distribution of article counts by country is presented in Figure 8 A. The top 20 countries with the highest total citation counts are as follows: USA (total citations: 95,018, Average citation: 23.6), United Kingdom (18,339, 23.2), Canada (14,728, 24.5), Australia (9596, 21), Germany (5966, 15.4), Italy (4603, 16.9), China (3973, 10.1), France (3648, 12.4), Netherlands (3183, 27.4), Sweden (2703, 21.5), Turkey (2522, 11), Spain (1900, 10.3), India (1865, 6.9), Ireland (1739, 22), Norway (1571, 17.3), Denmark (1379, 17.2), Korea (1332, 8.4), Switzerland (1323, 14.2), Iran (1242, 8), and Finland (1227, 20.4). (A) A world map depicting the distribution of article numbers by countries. (B) A graph showing the proportion of corresponding authors’ countries for the top 20 most productive countries compared to the total. Footnote: SCP: Single Country Publication, MCP: Multiple Countries Publication; MCP specifies the number of documents with at least 1 coauthor from a different country for each country. MCP measures the level of international collaboration for a given country. (C) Country collaboration map. International collaboration analysis among countries was conducted using Biblioshiny, and, the Biblioshiny corresponding author’s countries for the top 20 most prolific countries, taking into account the corresponding author numbers, are shown in Figure 8 B. The top 15 countries with the highest Multiple Countries Publication (MCP) scores are as follows: USA = 256, Canada = 145, United Kingdom = 135, Australia = 86, Germany = 71, China = 57, Italy = 43, Netherlands = 40, Norway = 37, Switzerland = 34, France = 29, Denmark = 29, Ireland = 29, Spain = 26, and Sweden = 25. Additionally, the biblioshiny Country collaboration map is presented in Figure 8 C. According to VOSviewer scores for international collaboration, the top 15 countries with the highest scores are as follows: USA = 1038, England in UK = 843, Germany = 536, Canada = 489, Australia = 443, Italy = 428, Netherlands = 355, Belgium = 339, Spain = 316, France = 309, Switzerland = 307, Sweden = 245, Denmark = 237, Austria = 206, and China = 190. A total of 10,566 articles related to PM were published across 2457 different scientific journals. Notably, the journals that had the most substantial impact on the literature, each with more than 50 articles, included Pain Management Nursing (n = 215), Pain Medicine (n = 200), Journal of Pain and Symptom Management (n = 196), Clinical Journal of Pain (n = 122), Pain (n = 117), Journal of Pain Research (n = 108), Anesthesia and Analgesia (n = 89), European Journal of Pain (n = 78), Schmerz (n = 69), Pain Physician (n = 67), Pain Research & Management (n = 65), Journal of Pain (n = 64), BMJ Open (n = 60), Spine (n = 56), Journal of Clinical Nursing (n = 54), Pain Practice (n = 54), British Journal of Pain (n = 53), Journal of Advanced Nursing (n = 53), and Supportive Care in Cancer (n = 53). The top 50 scientific journals in PM, based on their h-index, along with their g, and m-index values, total citation counts, article counts, average citation counts per article, and publication start years, are presented in Table 2 . The 50 most influential scientific journals according to the h-index on pain management. AC = average citation per document, NA = number of articles, PY = publication year, TC = total citations. The most active authors in PM (with 20 or more articles published) were, in order, Miaskowski C. (Number of articles: 47, h-index: 25, total citations: 2759), Meissner W. (NA: 44, h: 14, TC: 884), Kerns RD. (NA: 32, h: 15, TC: 1028), Bruera E. (NA: 26, h: 13, TC: 776), Bhatnagar S. (NA: 22, h: 5, TC: 124), Kaye AD. (NA: 21, h: 11, TC: 722), Bair MJ. (NA: 20, h: 14, TC: 944), and Bennett MI (NA: 20, h: 8, TC: 296). Among the 10,566 articles published in PM, the top 30 articles with the highest total citation counts, along with their titles, authors, journal names, publication years, total citation counts, and average citation counts per year, are shared in Table 3 . The first 30 high-impact articles based on the total number of citations on pain management. AC = average citations per year, PY = publication year, TC = total citations. Among the 10,566 articles published in PM, a total of 213,495 publications were cited in the reference sections. Among these studies, the 7 most impactful studies with more than 180 co-citations each were, in order, Cleeland (1994, Co-Citation: CC = 235), Melzack (1965, CC = 216), Cleeland (1994, CC = 208), Breivik (2006, CC = 200), Chou (2016, CC = 194), and Apfelbaum (2003, CC = 193). [ 4 , 18 – 23 ] Additionally, reference spectroscopy obtained using all the cited publications in the articles is presented in Figure 9 . A line graph illustrating the findings of Reference Publication Year Spectroscopy (RPYS).

An examination of the article distribution in the field of PM from 1980 to 2022 reveals 3 distinct publication trends: 1980 to 2004, 2005 to 2013, and 2014 to 2022. Between 1980 and 2004, an average of 78 articles (min–max: 18–156) were published. The year 2005 marked the onset of an increasing trend in the number of articles, with an average of 302 articles (min–max: 205–396) being published during 2005 to 2013. Subsequently, in 2014, another surge in article publications began, resulting in an average of 605 articles (min–max: 453–774) during the period from 2014 to 2022. Evaluating the 5-year forecast for 2023 and beyond, it becomes evident that the productivity of PM articles is expected to continue its exponential growth. When evaluating the findings of the keyword analysis conducted in the field of PM, it can be observed that the most studied topics from the past to the present, aside from the main headings of pain and PM, are chronic pain, opioids, analgesia/analgesics, cancer pain, postoperative pain, low back pain, opioid, cancer, acute pain, and self-management. Other frequently used keywords can be seen in the tables and figures. When examining the cumulative totals of these topics from the past to the present, it was determined that the prevalent topics in PM are chronic pain, opioids, analgesia/analgesics, cancer pain, postoperative pain, and low back pain. When evaluating the findings of keyword analysis conducted in 3 different time periods to determine trending topics, the following observations were made: Up until the early 2000s, common topics in PM included acute pain, physician education, rhizotomy, hostility, AIDS, chiropractic manipulation, and outcome measures. Starting in the year 2000, topics such as postoperative pain, chronic pain, nurse education, epidural analgesia, and cognitive-behavioral approaches gained prominence. From 2000 to 2005, areas of research interest included ergonomics, nurses’ knowledge, postoperative analgesia, reflex sympathetic dystrophy, nursing documentation, nonsteroidal anti-inflammatory drugs, and ethics, which were frequently studied over extended periods. Between 2005 and 2013, topics such as anticonvulsants, subcutaneous treatments, acute low back pain, palliative treatment, spinal cord interventions, opioid rotation, beliefs, decision making, pharmacology, home care, pain relief, opiates, epidural methods, morphine, and pediatric PM were the focus of extensive research. From 2014 to 2019, notable research areas included bupivacaine, cancer pain, pain assessment, neuropathic pain, rehabilitation, low back pain, postoperative pain, analgesia, nurses’ education, quality of life, pediatrics, chronic pain, and physiotherapy. In recent years, starting in 2020, trending research topics have shifted towards e-health, telemedicine, virtual reality, digital health, mental health, peripheral nerve blocks, erector spinae plane blocks, quadratus lumborum blocks, opioid use disorder, buprenorphine, musculoskeletal pain, COVID-19, cervicalgia, and interprofessional collaboration. When conducting trend keyword analysis without segmenting by time periods (with a threshold of a minimum of 30 occurrences of a keyword), it was observed that in the earlier years, topics like morphine, fentanyl, cancer pain, and chiropractic were frequently researched, while in recent years, topics such as telemedicine, e-health, m-health, virtual reality, primary health care, musculoskeletal pain, nerve blocks, opioid use disorder, multimodal analgesia, and total knee arthroplasty have gained more significant research attention. In the analysis of cluster findings, we identified 7 clusters of keywords representing significant areas of interest in PM according to the network map. These focal points, in order of cluster sizes, were as follows: the red cluster encompassed topics related to analgesia, opioids, postoperative, and acute pain; the green cluster focused on chronic pain, low back pain, self-management, exercise, rehabilitation, physiotherapy, telemedicine, and e-health; the blue cluster was associated with topics concerning the emergency department, children, chest pain, and abdominal pain; the yellow cluster revolved around cancer pain, palliative care, pain assessment, pain measurement, and nurses’ education and knowledge; the purple cluster addressed opioid use disorder (specifically buprenorphine and methadone); the turquoise cluster delved into pelvic pain, endometriosis, and laparoscopy; and the orange cluster centered on neuropathic pain, neuromodulation, spinal cord stimulation, and quality of life, while the brown cluster related to acupuncture and sickle cell disease. Additionally, through keyword co-occurrence analysis, the evolution of research hotspots was determined. In the field of PM, we can identify primary hotspots as chronic pain, opioids, analgesia, and postoperative pain, while secondary hotspots include low back pain, cancer pain, acute pain, the emergency department, abdominal pain, self-management, neuropathic pain, palliative care, and pain assessment. Furthermore, when evaluating the Word Cloud analysis visualization conducted using keyword plus terms, which are added to publications to express broader topics or related fields and provide a broader context for the content of the publication instead of author keywords, it was observed that the main topics in PM research encompass analgesia, postoperative pain, prevalence, low back pain, care, double-blind, efficacy, surgery, children, quality of life, morphine, therapy, and outcomes. When evaluating the findings of factor analysis, it was determined that in the central factor, which occupies a central position, the key topics included analgesia, opioids, postoperative pain, acute pain, cancer pain, and chronic pain. Apart from these central topics, the 3 subfactors were identified as follows: low back pain, neck pain, exercise, rehabilitation, and physiotherapy (red factor); nurses, nursing (green factor); and postoperative, depression, anxiety (turquoise factor). When evaluating the thematic evolution visualization conducted during 3 separate publication trend periods, it can be noted that there have been no significant changes in the topics, but in recent years, the concepts of “opioid” and “neuropathic pain” have become more prominent. Additionally, the visuals generated through thematic evolution analysis are crucial in displaying basic, emerging or declining, niche, and motor themes for each of the 3 periods. Researchers can gain detailed insights into the rising and falling topics for each period from these visuals. In the current period (2015–2023), when evaluating the themes, it will be observed that the fundamental themes are opioid, analgesia, and cancer, while emerging or declining themes include chest pain, motor themes encompass chronic pain, low back pain, self-management, multimodal analgesia, nerve block, and total knee arthroplasty, and niche themes represent pelvic pain, endometriosis, and laparoscopy. It should be noted that motor themes represent the main and predominant research topics in a field, often found in numerous studies, while niche themes denote narrower or more specific subjects, typically centered around a particular subtopic or specialized area of interest, and are generally newer and emerging research topics compared to motor themes. When examining the productivity of countries in the field of PM, it was observed that out of the top 20 countries contributing the most to the literature, 16 were developed countries, while only 4 (China, India, Turkey, Iran) were developing countries. These developing countries, however, had substantial economies. In the literature, various bibliometric studies in different fields have identified a significant correlation between a country’s economic size and its research productivity. When exploring the collaborative authorship network among countries, it was generally found that global collaborations were widespread. Upon evaluating the findings of inter-country collaboration analysis, the top 5 countries contributing the most to international collaboration in PM were determined to be the USA, Canada, United Kingdom, Australia, and Germany, followed by European countries and China. In the results section presenting the ranking of active journals contributing the most to PM literature and the most effective journals according to their h-index, these findings have been provided. We recommend these journals to researchers preparing publications in this field. Additionally, when assessing the average citations per document for journals after publication, the most effective journals were found to be the Journal of Clinical Oncology (Average citation per document, AC: 129.3), Anesthesiology (110.7), Pediatrics (87), Pain (72.8), Spine (69.8), Journal of Pain (64.4), Cancer (61), Journal of the American Geriatrics Society (57.8), Journal of General Internal Medicine (57.1), and Clinical Orthopaedics and Related Research (50.1). For researchers who prioritize greater impact for their articles after publication, we recommend considering these journals. When analyzed based on the total number of citations received, the most cited study was identified as Barr et al.’s (2013) work titled “Clinical practice guidelines for the management of pain, agitation, and delirium in adult patients in the intensive care unit,” published in Critical Care Medicine. [ 24 ] The second most influential study was Woolf and Mannion (1999) article titled “Neuropathic pain: etiology, symptoms, mechanisms, and management,” published in The Lancet. [ 25 ] The third most influential study was Chou et al.’s (2016) guideline on the management of postoperative pain published in the Journal of Pain. [ 4 ] When evaluated based on the average citations per year, the most influential study was also Barr et al.’s (2013) article. [ 24 ] The second most influential study was Chou et al.’s (2016) article. [ 4 ] The third most influential study was Devlin et al.’s (2018) clinical practice guidelines in the field of PM. [ 26 ] The importance of average citations per year lies in its ability to adjust for the advantage that older documents have more time to accumulate citations compared to newer documents. Regarding the co-citation numbers, which represent the citations shared by all analyzed articles, the most influential works were Cleeland (1994), Melzack (1965), Cleeland (1994), Breivik (2006), Chou (2016), and Apfelbaum (2003). [ 4 , 18 – 23 ] We recommend these studies as essential readings for researchers interested in this field. According to the historical development analysis conducted using RPYS analysis, it can be stated that interest in the field of PM began to increase after 1981, with a more significant growth observed after 1991. The interest continued to rise with a steeper slope, and the highest surge in interest was seen from 1997 to 2010, reaching its peak in 2010. As a result of our literature review, we did not come across a comprehensive bibliometric study on the general field of PM. Damar et al. (2018) conducted a bibliometric analysis specifically on research related to PM in nursing. [ 27 ] Chen et al. (2021) focused solely on the bibliometric analysis of research on PM in osteoarthritis. [ 28 ] Mei et al. (2023) performed a bibliometric analysis exclusively on research related to musculoskeletal PM. [ 29 ] Chen et al. (2023) and Zhai et al. (2023) conducted bibliometric analyses only on research related to post-cesarean section PM. [ 30 , 31 ] Liao et al. (2023) exclusively conducted a bibliometric analysis of research on neonatal PM. [ 32 ] In our study, we analyzed 10,566 articles, and we can claim that it is superior to other studies in terms of both scope and a broader time period as well as the scope of bibliometric analyses. As a limitation of this research, it could be argued that we only preferred the WoS database for our literature search. However, it has been emphasized in many studies that PubMed database is not preferred for bibliometric analyses as it does not allow citation and co-citation analyses. [ 7 – 9 ] Additionally, it is noted that Scopus database indexes some lower impact journals. [ 10 , 11 ] The WoS database indexes articles published in higher impact journals (mostly SCI-expanded) compared to other databases. [ 12 , 13 ]