Abstract
Purpose
This paper is focused on the role of ChatGPT an artificial intelligence (AI) language model in the area of sports trauma. Sports trauma represents some significant concerns due to its prevalence and impacts. The objective of this study is to present an overview of the literature on how ChatGPT handles information about sports trauma, considering both its strengths and limitations.
Methods
A review method is used in this study. Well-known online databases such as PubMed, ScienceDirect, Springer and Google Scholar were searched for the relevant studies. In addition, ChatGPT application was accessed to provide the concise information on the research topic.
Results
Search strategy resulted in 30 articles on the topic. Among them only seven studies revealed the potential applications of ChatGPT in sports. The other five studies presented the current status on ChatGPT and sports trauma. The results show that ChatGPT generates information on several types of sports trauma that align with the published literature. However, some limitations of ChatGPT are identified such as its tendency to provide general information about sprains and lack of updated statistics on sports trauma. This study also identified some serious concerns such ethical considerations, data privacy and security regarding the ChatGPT application in sports industry.
Conclusion
Despite having some limitations, the ChatGPT application has potential to be used in healthcare, and particularly in sports trauma. The implications of this study guide scholars for the development of enhanced AI systems, which are tailored to redress the challenges of sports trauma.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
1 Introduction
Trauma is one of the major causes of injuries and deaths among individuals up to 44 years old [1], encompasses various forms of injuries or physical damages, including sports trauma. Sports trauma can be defined as physical damages or injuries, which occur due to athletic activities participating in sports. These physical damages range from severe fractures to the minor sprains and strains, soft tissue injuries or dislocations and accidents occurring during activities in sports [2]. Various parts of body are affected by sports trauma, including ligaments, bones, tendons, muscles and joints. Several factors involve in occurrence of sports trauma such as conditioning or inappropriate warm-up, direct impact, repetitive motions, overuse, and improper techniques. The nature and intensity of sports make athletes more vulnerable to the various types of injuries [3].
Artificial intelligence (AI)-based applications are used for motion capturing in the sports field. Convolutional neural networks (CNNs) as marker-less motion capturing systems have shown better results [4]. Since sports injuries can have negative impacts on team performance, AI-based systems have been successfully used for assessing and predicting sports injuries [5]. AI techniques analyze patterns from sensors' kinematic and positional data of athletes to enhance players' performance [6]. Cardiovascular and respiratory conditions can be investigated, and physicians may find it helpful in recommending medicine for athletes.
Recently, a large language model ChatGPT has been released by Open AI, a research laboratory located in San Francisco. ChatGPT can process and respond to the text-based inquiries in a humanistic fashion [7]. ChatGPT is rapidly being incorporated with the various areas of research. Since its release, several papers have been published in most reputed journals. In this paper, we take into account a few articles published on ChatGPT and its applications in sports trauma. The online AI application, ChatGPT, has been used for analyzing the quality and readability of information about shoulder stabilization surgery [8]. This study has assisted younger internet users in avoiding unnecessary shoulder surgery. A recent study highlights the use of ChatGPT in sports medicine for image diagnosis, exercise prescription, and sports nutrition [9]. This application serves as an assistant, potentially reducing the need for sports physicians.
Prior to our study, a number of surveys were conducted to examine the role of AI in sports. A survey article primary deals with the AI approaches used for different sports injuries and other risks [10]. Another review article [11] was aimed to examine the role of machine learning to predict and prevent sports injuries. Based on the existing literature and knowledge on the injury risk factors, a review article was aimed to assess the current AI applications [12]. However, these studies do not focus on ChatGPT applications in sports injuries. To bridge this gap, this study is undertaken to review the literature on the ChatGPT applications in sports trauma. Can the ChatGPT application provide us with sufficient information on sports trauma or injuries?
Overall this paper contributes to the literature as follows:
-
This paper presents an overview of the recently published works on sports trauma.
-
This paper compares the information on sports trauma provided by ChatGPT with the existing literature.
The remainder of the paper is organized as follows:
Section 2 outlines the review methodology employed in this study. Section 3 offers an overview of the current status of ChatGPT applications, including their strengths, weaknesses, and potential applications in sports trauma. Section 4 provides a summary of the key points discussed in this study.
2 Methods
A comprehensive literature search was conducted using PubMed, ScienceDirect, Springer, and Google Scholar databases. Keywords such as “ChatGPT and Sports Trauma” were utilized on these databases to collect relevant articles. Various types of articles including research studies, letters to the editor, comments, and clinical trials were considered for this study.
Below, we provide the inclusion and exclusion criteria for studies in this review article.
2.1 Inclusion criteria
-
Studies discussing various types of sports trauma.
-
Studies discussing the potential applications of ChatGPT in sports.
-
Studies discussing strength and weaknesses of using ChatGPT in sports trauma.
-
Studies published in English.
2.2 Exclusion criteria
-
Studies published in languages other than English were excluded.
-
Studies discussing sports trauma without ChatGPT applications were excluded.
-
Grey literature on the topic was excluded.
Based on the aforementioned inclusion and exclusion criteria, the titles and abstracts of the extracted 45 articles were screened for this review study. Subsequently, full-length articles that did not meet the inclusion criteria were examined. Following this, results were extracted and reviewed by two colleague authors for further assessment and correction. A total of 30 articles were selected and reviewed in this study.
3 Results and discussion
This section presents results and their discussion.
3.1 Current status on ChatGPT and sports trauma
Critics of ChatGPT claim that ChatGPT generates text, which is almost identical to the existing literature, and can be used to manipulate the results from the previously published studies. However, they also state that the text generated by ChatGPT can mislead researchers or readers [13]. This claim made by researcher is somewhat valid for reviewers who cannot distinguish contents generated by ChatGPT and human being. However, we disagree with their next claim about inaccuracy and bias by ChatGPT. From a technical standpoint, if unbalanced data is used to train the data, we may encounter biasness in the text generated by ChatGPT. This claim is consistent with findings that ChatGPT application has potential for biased recommendations in sports [14]. Overall, ChatGPT does not show bias to any of its users. It provides answers based on the text used as input and does not take into account the identity of users utilizing the ChatGPT application. To validate this point, we asked ChatGPT to reveal common examples of sports trauma. We received the answer below:
“Common examples of sports trauma include sprained ankles, torn ligaments, concussions, muscle strains, fractures, and dislocations. These injuries can result from contact sports, repetitive motions, overuse, or accidents during athletic activities, requiring proper medical attention and rehabilitation.”
We aimed to assess the accuracy of the provided examples of sports trauma. To this inquiry, we obtained six types of sports trauma. Upon examining the literature on the sports trauma, this paper presents an analysis of published works to identify data related to various types of sports-related injuries.
Table 1 shows us data on sports trauma types from ChatGPT and published works. Although a large body of literature is focused on sports trauma and its types, we randomly chose three articles that show discussion on the sports trauma and its types. Overall, eight sports trauma types qualified for this research work. ChatGPT seems to have maximum information on the mentioned injuries, except contusions and wrestler ear injury. Study by Elmagd [15] covers all the injuries mentioned, while Nalliah et al. in [16] focused on sprains, strains, fractures and contusions. Aleman and Meyers [17] presented information on strains, fractures, dislocation, overuse injuries, and wrestler ear injury but missed concussions or contusions.
3.2 ChatGPT pros and cons for sprains
Moreover, we demonstrate how ChatGPT can explain the occurrence, symptoms, treatment, rehabilitation, and physical therapies associated with sprains. Our aim was to identify the strengths and limitations of ChatGPT's application in the context of sprains. The sprains are common ligament injuries, which occur due to tearing or stretching of ligaments. These ligaments are bends of connective tissues, which involve in stabilizing joints. Most common type of sprains are ankle sprains. Besides this ChatGPT’s information, we find that ankle sprain is one of the common musculoskeletal injuries and ranges between 15 to 20% in sports injuries [18]. When compared to the literature, it is known that ChatGPT provides very basic and general information about ankle sprains such as its symptoms, initial treatment, rehabilitation exercises, and physical therapies. Literature is largely focused on ankle sprains and their treatment strategies. Rest, ice, compression and elevation (RICE) therapy is mainly discussed in the literature [19, 20]. ChatGPT recommends that RICE therapy must be applied immediately when an injury occurs. RICE therapy must be continued for the first 48–72 h. This information is consistent with the previous study [21]. However, ChatGPT failed to provide an appropriate source of this information.
We were interested to seek some recent information about ankle sprain in sports. We subsequently posed the question to ChatGPT, requesting recent information on ankle sprains in sports.
“Recent research underscores ankle sprains' prevalence in sports, emphasizing early diagnosis, proper treatment, and comprehensive rehabilitation for improved outcomes.”
However, the response we received was largely consistent with the previously discussed information. It is important to note that the training data for OpenAI's application was last updated in September 2021, and therefore, it lacks information published after that date, particularly in the field of health.
Moreover, the literature suggests that the accuracy of ChatGPT is still questionable, as the AI application could generate passing grades [22]. Therefore, data generated by ChatGPT in sports and medicine fields needs to be tested on a large amount of information for accurate performance. Furthermore, ChatGPT application is used to calculate the sample size for a sports medicine study. It showed 25% correct results in calculating the accurate sample size [23]. However, it improved its results when the question was asked again. Therefore, ChatGPT must be used cautiously when utilized in future works. ChatGPT application may have potential problems and disadvantages in the field of research (sports medicine), as contents generated by ChatGPT are considered plagiarized since authors did not write them themselves [13].
The management aspect of sports has been highlighted in a study. In response to short questions from authors, ChatGPT provided quality, accurate, and complete answers [24]. This indicates the better use of ChatGPT applications in sports management in higher education classrooms. This helps us understand how ChatGPT can supplement and support sports management classes. In the event of sports management, content creation is a time-consuming task [25]. However, the launch of ChatGPT and other generative tools such as Dall-E2 can alleviate the time faculty spend on content creation regarding events in sports management.
In the following section, we summarize the studies on sports trauma regarding ChatGPT.
3.3 Potential applications of ChatGPT in sports
Other studies [22, 24, 26, 27] present that ChatGPT can give us prompt and accurate answers for inquiries about sports topics (Table 2). One of the main features as apparent in these studies is the coherency in writing on different topics. ChatGPT has strong feature of writing coherent answers because of its tendency to provide connected ideas in an academic writing. Other studies by Cheng et al. [9, 28] and He et al. [29] primarily focus on sports medicine, providing support for surgeons dealing with joint arthroplasty and spinal issues in sports. Despite of these information, literature has limited data on the role of ChatGPT in some specific areas. For example, there is limited published data on the application of ChatGPT in the field of physical medicine and rehabilitation (PM&R) [30]. Other than these limitations, ChatGPT is not efficient in considering the ethics, and gender equality in sports. Security and privacy are fundamental potential risks, which are associated with the surgical tasks in sports industry.
4 Conclusion
In summary, this paper examines the literature on the sports trauma in relation to the ChatGPT application. The main focus of the paper is on the bias and accuracy of information presented by ChatGPT. While ChatGPT may confuse reviewers during the editorial process of an article, it does not display bias towards its users. The paper identifies various types of sports trauma, which have been well documented in the literature and ChatGPT application. ChatGPT is trained on the literature but fails in providing the exact information about information sources. This paper also finds that ChatGPT provides only general information about sprains and lacks up-to-date statistics on sports trauma. To overcome these limitations, future research can be conducted to explore ChatGPT's capabilities in sports and other related research areas.
Data availability
All data used in this article are referenced.
References
Eun JC, et al. Vascular injury is associated with increased mortality in winter sports trauma. Ann Vasc Surg. 2015;29(1):109–13.
Clarsen B, Myklebust G, Bahr R. Development and validation of a new method for the registration of overuse injuries in sports injury epidemiology: the Oslo Sports Trauma Research Centre (OSTRC) overuse injury questionnaire. Br J Sports Med. 2013;47(8):495–502.
Pardiwala DN, et al. Badminton injuries in elite athletes: a review of epidemiology and biomechanics. Indian J Orthop. 2020;54(3):237–45.
Palucci Vieira LH, et al. Automatic markerless motion detector method against traditional digitisation for 3-dimensional movement kinematic analysis of ball kicking in soccer field context. Int J Environ Res Public Health. 2022;19(3):1179.
Kakavas G, et al. Artificial intelligence: a tool for sports trauma prediction. Injury. 2020;51:S63–5.
Chidambaram S, et al. Using artificial intelligence-enhanced sensing and wearable technology in sports medicine and performance optimisation. Sensors. 2022;22(18):6920.
Gupta R, et al. Application of ChatGPT in cosmetic plastic surgery: ally or antagonist. Aesth Surg J. 2023;2023:sjad042.
Hurley ET, et al. Evaluation high-quality of information from ChatGPT (artificial intelligence—large language model) artificial intelligence on shoulder stabilization surgery. Arthrosco J Arthrosc Related Surge. 2023;2023:1.
Cheng K, et al. Artificial intelligence in sports medicine: Could GPT-4 make human doctors obsolete? Ann Biomed Eng. 2023;2032:1–5.
Claudino JG, et al. Current approaches to the use of artificial intelligence for injury risk assessment and performance prediction in team sports: a systematic review. Sports Med Open. 2019;5:1–12.
Van Eetvelde H, et al. Machine learning methods in sport injury prediction and prevention: a systematic review. J Exp Orthop. 2021;8:1–15.
Sigurdson H, Chan JH. Machine learning applications to sports injury: a review. icSPORTS. 2021;2021:157–68.
Dahmen J, et al. Artificial intelligence bot ChatGPT in medical research: the potential game changer as a double-edged sword. Knee Surg Sports Traumatol Arthrosc. 2023;31(4):1187–9.
Bahrini A, et al. ChatGPT: applications, opportunities, and threats. In: 2023 systems and information engineering design symposium (SIEDS). IEEE; 2023.
Abou Elmagd M. Common sports injuries. Int J Phys Educ Sports Health. 2016;3(5):142–8.
Nalliah RP, et al. Epidemiology of hospital-based emergency department visits due to sports injuries. Pediatr Emerg Care. 2014;30(8):511–5.
Aleman KB, Meyers MC. Mountain biking injuries in children and adolescents. Sports Med. 2010;40:77–90.
Petersen W, et al. Treatment of acute ankle ligament injuries: a systematic review. Arch Orthop Trauma Surg. 2013;133:1129–41.
Van Den Bekerom MP, et al. What is the evidence for rest, ice, compression, and elevation therapy in the treatment of ankle sprains in adults? J Athl Train. 2012;47(4):435–43.
Halabchi F, Hassabi M. Acute ankle sprain in athletes: clinical aspects and algorithmic approach. World J Orthop. 2020;11(12):534.
Kristiani RB. The effect of cold compress on pain in muscle injury after collection of loads in the JM fitness center, Kapas Madya Village, Kenjeran Subdistrict, Surabaya. In: International conference of Kerta Cendekia Nursing Academy; 2019.
Szabo A. ChatGPT is a breakthrough in science and education but fails a test in sports and exercise psychology. Baltic J Sport Health Sci. 2023;1(128):25–40.
Methnani J, et al. ChatGPT for sample-size calculation in sports medicine and exercise sciences: a cautionary note. Int J Sports Physiol Perform. 2023;1(aop):1–5.
Keiper MC, et al. Artificial intelligence in sport management education: playing the AI game with ChatGPT. J Hosp Leis Sport Tour Educ. 2023;33:100456.
Keiper MC. ChatGPT in practice: Increasing event planning efficiency through artificial intelligence. J Hosp Leis Sport Tour Educ. 2023;33:100454.
Ollivier M, et al. A deeper dive into ChatGPT: history, use and future perspectives for orthopaedic research. Knee Surg Sports Traumatol Arthrosc. 2023;31(4):1190–2.
Anderson N, et al. AI did not write this manuscript, or did it? Can we trick the AI text detector into generated texts? The potential future of ChatGPT and AI in Sports & Exercise Medicine manuscript generation. BMJ Spec J. 2023;2023:e001568.
Cheng K, et al. The potential of GPT-4 as an AI-powered virtual assistant for surgeons specialized in joint arthroplasty. Ann Biomed Eng. 2023;2023:1–5.
He Y, et al. Will ChatGPT/GPT-4 be a lighthouse to guide spinal surgeons? Ann Biomed Eng. 2023;2023:1–4.
Peng S, et al. AI-ChatGPT/GPT-4: an booster for the development of physical medicine and rehabilitation in the new era! Ann Biomed Eng. 2023;2023:1–5.
Acknowledgements
During the preparation of this work the author(s) used ChatGPT in order to extract some information. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
Funding
The author received no funding for the research, authorship, and/or publication of this article.
Author information
Authors and Affiliations
Contributions
Author MH conducted the primary research activities for this submission. MH conceived the research idea, collected and analyzed the data. However, authors BM and SI assisted in revising the article. They both contributed to editing and reviewed the article.
Corresponding author
Ethics declarations
Competing interests
No benefits in any form have been or will be received from a commercial party related directly or indirectly to the subject of this manuscript.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Hasnain, M., Mehboob, B. & Imran, S. The role of ChatGPT in sports trauma: a mini review on strengths and limits of open AI application. Discov Artif Intell 3, 40 (2023). https://doi.org/10.1007/s44163-023-00093-1
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s44163-023-00093-1