bims-librar 2024-07-07 papers

bims-librar

Biomed News

on Biomedical librarianship

Issue of 2024–07–07
fourteen papers selected by
Thomas Krichel, Open Library Society

The Evolution of Library Workplaces and Workflows via Generative AI.
Creating and validating a scholarly knowledge graph using natural language processing and microtask crowdsourcing.
OpenChemIE: An Information Extraction Toolkit for Chemistry Literature.
European Health Information Portal: a one-stop shop for health information.
Exploring and retrieving sequence and metadata for species across the tree of life with NCBI Datasets.
Implementation and evaluation of an additional GPT-4-based reviewer in PRISMA-based medical systematic literature reviews.
Chatbots as Patient Education Resources for Aesthetic Facial Plastic Surgery: Evaluation of ChatGPT and Google Bard Responses.
Evaluation of Online AI-Generated Foot and Ankle Surgery Information.
Accuracy, readability, and quality of websites about metastatic renal cell carcinoma treatment.
Assessing readability of online patient educational material on concussion and return to play.
YouTube as a possible learning platform for patients and their family caregivers for gastrostomy tube feeding: A cross-sectional study.
YouTube™ Videos as a Source of Information on Necrotizing Gingivitis: A Content-Quality Analysis.
"Does My Kid Have an Ear Infection?" An Analysis of Pediatric Acute Otitis Media Videos on TikTok.
Human papilloma virus (HPV)-related information acquisition and seeking behavior among infected women: A single center cross-sectional survey in Shanghai, China.

Coll Res Libr. 2023 Nov;84(6): 836-842

The Evolution of Library Workplaces and Workflows via Generative AI.

Mohammad Hosseini, Kristi Holmes.

DOI: https://doi.org/10.5860/crl.84.6.836
Int J Digit Libr. 2024 ;25(2): 273-285

Creating and validating a scholarly knowledge graph using natural language processing and microtask crowdsourcing.

Allard Oelen, Markus Stocker, Sören Auer.

  Due to the growing number of scholarly publications, finding relevant articles becomes increasingly difficult. Scholarly knowledge graphs can be used to organize the scholarly knowledge presented within those publications and represent them in machine-readable formats. Natural language processing (NLP) provides scalable methods to automatically extract knowledge from articles and populate scholarly knowledge graphs. However, NLP extraction is generally not sufficiently accurate and, thus, fails to generate high granularity quality data. In this work, we present TinyGenius, a methodology to validate NLP-extracted scholarly knowledge statements using microtasks performed with crowdsourcing. TinyGenius is employed to populate a paper-centric knowledge graph, using five distinct NLP methods. We extend our previous work of the TinyGenius methodology in various ways. Specifically, we discuss the NLP tasks in more detail and include an explanation of the data model. Moreover, we present a user evaluation where participants validate the generated NLP statements. The results indicate that employing microtasks for statement validation is a promising approach despite the varying participant agreement for different microtasks.

Keywords:  Crowdsourcing microtasks; Knowledge graph validation; Scholarly knowledge graphs; User interface evaluation

DOI:  https://doi.org/10.1007/s00799-023-00360-7
J Chem Inf Model. 2024 Jul 01.

OpenChemIE: An Information Extraction Toolkit for Chemistry Literature.

Vincent Fan, Yujie Qian, Alex Wang, Amber Wang, Connor W Coley, Regina Barzilay.

Information extraction from chemistry literature is vital for constructing up-to-date reaction databases for data-driven chemistry. Complete extraction requires combining information across text, tables, and figures, whereas prior work has mainly investigated extracting reactions from single modalities. In this paper, we present OpenChemIE to address this complex challenge and enable the extraction of reaction data at the document level. OpenChemIE approaches the problem in two steps: extracting relevant information from individual modalities and then integrating the results to obtain a final list of reactions. For the first step, we employ specialized neural models that each address a specific task for chemistry information extraction, such as parsing molecules or reactions from text or figures. We then integrate the information from these modules using chemistry-informed algorithms, allowing for the extraction of fine-grained reaction data from reaction condition and substrate scope investigations. Our machine learning models attain state-of-the-art performance when evaluated individually, and we meticulously annotate a challenging dataset of reaction schemes with R-groups to evaluate our pipeline as a whole, achieving an F1 score of 69.5%. Additionally, the reaction extraction results of OpenChemIE attain an accuracy score of 64.3% when directly compared against the Reaxys chemical database. OpenChemIE is most suited for information extraction on organic chemistry literature, where molecules are generally depicted as planar graphs or written in text and can be consolidated into a SMILES format. We provide OpenChemIE freely to the public as an open-source package, as well as through a web interface.

DOI: https://doi.org/10.1021/acs.jcim.4c00572
Eur J Public Health. 2024 Jul 01. 34(Supplement_1): i29-i34

European Health Information Portal: a one-stop shop for health information.

Population Health Information Research Infrastructure and the Health Information Portal

BACKGROUND: Timely and high-quality population-level health information is needed to support evidence-informed decision-making, for planning and evaluation of prevention, care and cure activities as well as for research to generate new knowledge. FAIR (Findable, Accessible, Interoperable and Reusable) principles are one of the key elements supporting health research and making it more cost-effective through the reuse of already existing data. Currently, health data are in many countries dispersed and difficult to find and access.
METHODS: Two EU Public Health Programmes co-funded Joint Actions, Information for Action (InfAct) and Population Health Information Research Infrastructure (PHIRI) have established a European Health Information Portal, a web-based service, to facilitate better findability, access, interoperability and reuse of existing health information.
RESULTS: The European Health Information Portal (www.healthinformationportal.eu) has been established including sections on National Nodes, data sources, publications, health information projects within countries and across Europe, research networks and research infrastructures, ethical and legal issues for health information exchange and use, capacity-building activities in all areas of population health and a dedicated COVID-19 section.
CONCLUSIONS: The European Health Information Portal, being a central place for a wide range of population health information from EU Member States, is an information source for researchers, policy-makers and other relevant stakeholders. It is important to ensure the sustainability of the portal, especially in light of the European Health Data Space (EHDS) Regulation proposal and its requirements regarding the secondary use of health data.

DOI: https://doi.org/10.1093/eurpub/ckad172
Sci Data. 2024 Jul 05. 11(1): 732

Exploring and retrieving sequence and metadata for species across the tree of life with NCBI Datasets.

Nuala A O'Leary, Eric Cox, J Bradley Holmes, W Ray Anderson, Robert Falk, Vichet Hem, Mirian T N Tsuchiya, Gregory D Schuler, Xuan Zhang, John Torcivia, Anne Ketter, Laurie Breen, Jonathan Cothran, Hena Bajwa, Jovany Tinne, Peter A Meric, Wratko Hlavina, Valerie A Schneider.

To explore complex biological questions, it is often necessary to access various data types from public data repositories. As the volume and complexity of biological sequence data grow, public repositories face significant challenges in ensuring that the data is easily discoverable and usable by the biological research community. To address these challenges, the National Center for Biotechnology Information (NCBI) has created NCBI Datasets. This resource provides straightforward, comprehensive, and scalable access to biological sequences, annotations, and metadata for a wide range of taxa. Following the FAIR (Findable, Accessible, Interoperable, and Reusable) data management principles, NCBI Datasets offers user-friendly web interfaces, command-line tools, and documented APIs, empowering researchers to access NCBI data seamlessly. The data is delivered as packages of sequences and metadata, thus facilitating improved data retrieval, sharing, and usability in research. Moreover, this data delivery method fosters effective data attribution and promotes its further reuse. This paper outlines the current scope of data accessible through NCBI Datasets and explains various options for exploring and downloading the data.

DOI: https://doi.org/10.1038/s41597-024-03571-y
Int J Med Inform. 2024 Jun 26. pii: S1386-5056(24)00194-1. [Epub ahead of print]189 105531

Implementation and evaluation of an additional GPT-4-based reviewer in PRISMA-based medical systematic literature reviews.

Assaf Landschaft, Dario Antweiler, Sina Mackay, Sabine Kugler, Stefan Rüping, Stefan Wrobel, Timm Höres, Hector Allende-Cid.

   BACKGROUND: PRISMA-based literature reviews require meticulous scrutiny of extensive textual data by multiple reviewers, which is associated with considerable human effort.
OBJECTIVE: To evaluate feasibility and reliability of using GPT-4 API as a complementary reviewer in systematic literature reviews based on the PRISMA framework.
METHODOLOGY: A systematic literature review on the role of natural language processing and Large Language Models (LLMs) in automatic patient-trial matching was conducted using human reviewers and an AI-based reviewer (GPT-4 API). A RAG methodology with LangChain integration was used to process full-text articles. Agreement levels between two human reviewers and GPT-4 API for abstract screening and between a single reviewer and GPT-4 API for full-text parameter extraction were evaluated.
RESULTS: An almost perfect GPT-human reviewer agreement in the abstract screening process (Cohen's kappa > 0.9) and a lower agreement in the full-text parameter extraction were observed.
CONCLUSION: As GPT-4 has performed on a par with human reviewers in abstract screening, we conclude that GPT-4 has an exciting potential of being used as a main screening tool for systematic literature reviews, replacing at least one of the human reviewers.

Keywords:  AI-based reviewer; GPT-4 API; PRISMA; Systematic literature review

DOI:  https://doi.org/10.1016/j.ijmedinf.2024.105531
Facial Plast Surg Aesthet Med. 2024 Jul 01.

Chatbots as Patient Education Resources for Aesthetic Facial Plastic Surgery: Evaluation of ChatGPT and Google Bard Responses.

Neha Garg, Daniel J Campbell, Angela Yang, Adam McCann, Annie E Moroco, Leonard E Estephan, William J Palmer, Howard Krein, Ryan Heffelfinger.

Background: ChatGPT and Google Bard™ are popular artificial intelligence chatbots with utility for patients, including those undergoing aesthetic facial plastic surgery. Objective: To compare the accuracy and readability of chatbot-generated responses to patient education questions regarding aesthetic facial plastic surgery using a response accuracy scale and readability testing. Method: ChatGPT and Google Bard™ were asked 28 identical questions using four prompts: none, patient friendly, eighth-grade level, and references. Accuracy was assessed using Global Quality Scale (range: 1-5). Flesch-Kincaid grade level was calculated, and chatbot-provided references were analyzed for veracity. Results: Although 59.8% of responses were good quality (Global Quality Scale ≥4), ChatGPT generated more accurate responses than Google Bard™ on patient-friendly prompting (p < 0.001). Google Bard™ responses were of a significantly lower grade level than ChatGPT for all prompts (p < 0.05). Despite eighth-grade prompting, response grade level for both chatbots was high: ChatGPT (10.5 ± 1.8) and Google Bard™ (9.6 ± 1.3). Prompting for references yielded 108/108 of chatbot-generated references. Forty-one (38.0%) citations were legitimate. Twenty (18.5%) provided accurately reported information from the reference. Conclusion: Although ChatGPT produced more accurate responses and at a higher education level than Google Bard™, both chatbots provided responses above recommended grade levels for patients and failed to provide accurate references.

DOI: https://doi.org/10.1089/fpsam.2023.0368
J Foot Ankle Surg. 2024 Jul 03. pii: S1067-2516(24)00143-1. [Epub ahead of print]

Evaluation of Online AI-Generated Foot and Ankle Surgery Information.

Dominick Casciato, Sara Mateen, Steven Cooperman, Danielle Pesavento, Roberto A Brandao.

  As a natural progression from educational pamphlets to the worldwide web, and now artificial intelligence (AI), OpenAI chatbots provide a simple way of obtaining pathology-specific patient information, however, little is known concerning the readability and quality of foot and ankle surgery information. This investigation compares such information using the commercially available OpenAI ChatGPT Chatbot and FootCareMD®. A list of common foot and ankle pathologies from FootCareMD® were queried and compared with similar results using ChatGPT. From both resources, the Flesch Reading Ease Score (FRES) and Flesch-Kincaid Grade Level (FKGL) scores were calculated for each condition. Qualitative analysis of each query was performed using the JAMA Benchmark Criteria Score and the DISCERN Score.The overall ChatGPT and FootCareMD® FRES scores were 31.12±7.86 and 55.18±7.27, respectively (p<0.0001). The overall ChatGPT and FootCareMD® FKGL scores were 13.79±1.22 and 9.60±1.24 respectively (p<0.0001), except for the pilon fracture FKGL scores (p=0.09). The average JAMA Benchmark for all information obtained through ChatGPT and FootCareMD® were 0±0 and 1.95±0.15 (p < 0.001), respectively. The DISCERN Score for all information obtained through ChatGPT and FootCareMD® were 52.53±5.39 and 66.93±4.57 (p < 0.001), respectively. AI-assisted queries concerning common foot and ankle pathologies are written at a higher grade level and with less reliability and accuracy compared to similar information available on FootCareMD®. With the ease of use and increase in AI technology, consideration should be given to the nature and quality of information being shared with respect to the diagnosis and treatment of foot and ankle conditions. LEVEL OF EVIDENCE: IV.

Keywords:  Artificial Intelligence; ChatGPT; Machine Learning; Natural Language Model; Patient Education

DOI:  https://doi.org/10.1053/j.jfas.2024.06.009
Urol Oncol. 2024 Jul 01. pii: S1078-1439(24)00527-1. [Epub ahead of print]

Accuracy, readability, and quality of websites about metastatic renal cell carcinoma treatment.

Nonna Shakhnazaryan, Liam Gima-Lange, Arpita Desai, Kelly Fitzgerald, Daniel H Kwon.

   OBJECTIVES: Patients with metastatic renal cell carcinoma (mRCC) face complex treatment decisions and frequently turn to the Internet for treatment information. The content of patient educational websites about mRCC treatment has not been evaluated. This study evaluated the accuracy, readability, and quality of websites about the treatment of mRCC.
METHODS: A total of 2,700 Internet queries were performed. Across 3 Internet search engines, 25 links of 36 permutations of mRCC keywords and their synonyms were screened for eligibility. Eligible websites were English-language websites containing information about mRCC treatments. Sponsored, social media, provider-facing, and news websites were excluded. Accuracy of eligible websites was evaluated in 2 domains: (1) Completeness by calculating the percentage of mRCC facts included in websites using an investigator-created checklist based on the NCI's RCC Treatment (PDQ®)-patient version, and (2) Correctness by identifying incorrect statements that were inconsistent with guidelines. Websites containing ≥60% of checklist items had a "passing" completeness score. Incorrect statements were tallied and qualitatively categorized. Readability was evaluated using the Fry and SMOG formulae, which calculate reading grade levels. Quality was evaluated using validated instruments that appraise health information quality: QUEST (scored 0-28), which focuses on online information, and DISCERN (scored 16-80), which focuses on treatment choices.
RESULTS: Thirty-nine websites were analyzed. Mean completeness score was 30% (range 0%-69%); only 2 (5%) websites had a passing score. Twelve (31%) websites had ≥1 incorrect statement, such as listing homeopathy or hormone therapy as mRCC treatment options, or including outdated statements. Mean readability levels were 11th and 12th grades for the Fry and SMOG methods, respectively. No website had a reading level lower than 9th grade. Mean QUEST score was 19 (range 9-28); authorship, complementarity, and currency items had the lowest scores. Mean DISCERN score was 56 (range 42-76), with 7 (18%) websites rated "excellent", 22 (56%) rated "good", and 10 (26%) rated fair.
CONCLUSIONS: Many websites about mRCC treatment have incomplete, inaccurate, and unreadable information. Quality is highly variable. Efforts to improve accuracy, readability, and quality are needed to ensure that patients with mRCC can make well-informed treatment decisions and avoid harm from misinformation.

Keywords:  Consumer Health Education; Health Communication; Internet; Kidney Neoplasms; Patient Education; Renal Cell Carcinoma

DOI:  https://doi.org/10.1016/j.urolonc.2024.06.015
Neurosurg Focus. 2024 Jul;57(1): E6

Assessing readability of online patient educational material on concussion and return to play.

Joanna M Roy, Stefan T Prvulovic, Shubhang Bhalla, Caroline Casella, Sina Zoghi, Aryan Gajjar, Christian A Bowers.

   OBJECTIVE: Concussions are self-limited forms of mild traumatic brain injury (TBI). Gradual return to play (RTP) is crucial to minimizing the risk of second impact syndrome. Online patient educational materials (OPEM) are often used to guide decision-making. Previous literature has reported that grade-level readability of OPEM is higher than recommended by the American Medical Association and the National Institutes of Health. The authors evaluated the readability of OPEM on concussion and RTP.
METHODS: An online search engine was used to identify websites providing OPEM on concussion and RTP. Text specific to concussion and RTP was extracted from each website and readability was assessed using the following six standardized indices: Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level, Gunning Fog Index, Coleman-Liau Index, Simple Measure of Gobbledygook Index, and Automated Readability Index. One-way ANOVA and Tukey's post hoc test were used to compare readability across sources of information.
RESULTS: There were 59 concussion and RTP articles, and readability levels exceeded the recommended 6th grade level, irrespective of the source of information. Academic institutions published OPEM at simpler readability levels (higher FRE scores). Private organizations published OPEM at more complex (higher) grade-level readability levels in comparison with academic and nonprofit institutions (p < 0.05).
CONCLUSIONS: The readability of OPEM on RTP after concussions exceeds the literacy of the average American. There is a critical need to modify the concussion and RTP OPEM to improve comprehension by a broad audience.

Keywords:  American Medical Association; concussion; readability; return to play

DOI:  https://doi.org/10.3171/2024.4.FOCUS24128
Nutr Clin Pract. 2024 Jul 03.

YouTube as a possible learning platform for patients and their family caregivers for gastrostomy tube feeding: A cross-sectional study.

Hyeon Sik Chu, Hanyi Lee.

   BACKGROUND: Many patients and family caregivers have informational needs, especially regarding gastrostomy care and home gastrostomy tube feeding. YouTube is a potential accessible option for educational resources concerning these topics.
METHODS: This study aimed to explore the educational quality and content of informational YouTube videos. We used "gastrostomy," "G-tube," "enteral feeding," and "enteral nutrition," as search keywords on YouTube on October 3, 2021. A total of 229 videos were evaluated using the global quality scale (GQS) and modified DISCERN scoring system. Variables extracted from the videos included general features, video parameters, and content themes.
RESULTS: The GQS and modified DISCERN scores were 3.31 ± 0.90 and 2.63 ± 1.23, respectively. There were educational quality and differences among videos uploaded by various agencies. Frequent video content themes included "cleaning and dressing a gastrostomy tube," "bolus method," and "replacing a balloon-type of gastrostomy tube."
CONCLUSION: Results showed that YouTube can be a supplemental educational resource for people requiring gastrostomy care and for their caregivers. However, given the open-access nature of YouTube, healthcare professionals' guidance is needed for video selection. Healthcare professionals should know and use specific, reliable resources to effectively guide and educate patients with gastrostomy and their caregivers, enhancing their self-management skills and knowledge.

Keywords:  YouTube; education; gastrostomy; homecare; web

DOI:  https://doi.org/10.1002/ncp.11186
Cureus. 2024 Jun;16(6): e61485

YouTube™ Videos as a Source of Information on Necrotizing Gingivitis: A Content-Quality Analysis.

Şeyma Çardakcı Bahar, Oğuz Koca.

  Background This study aims to evaluate the quality, reliability, and content of the information provided in YouTube™ videos on necrotizing gingivitis (NG), demonstrate the effectiveness of the videos for patients, and help dentists use this platform as a resource to properly guide their patients. Methodology This cross-sectional study was conducted by two experienced periodontologists. They began the study by searching for YouTube™ videos using the keywords "necrotizing gingivitis" and "trench mouth." Descriptive parameters such as the source of upload, country of origin, duration, upload date, number of likes, dislikes, views, and comments were evaluated. After this initial evaluation, the viewing rate and interaction index were calculated. Videos were categorized into high content (HC) and low content (LC) based on a 7-point scale. The quality of video content was assessed using the Global Quality Scale (GQS) and the Video Information and Quality Index (VIQI). The data were analyzed using various statistical tests, with a significance level set at p<0.05. Results Initially, 148 videos were screened, and 50 videos on NG that met the inclusion criteria were included in the study. Out of the 50 videos, 28 (56%) were uploaded by healthcare professionals. Overall, 68% of videos (n=34) were classified as HC and 32% (n=16) as LC. The most common topic was clinical symptoms and signs of NG, with 86% (n=43), while NG prevention was the least common topic, with 26% (n=13). Statistically significant differences were found between video duration, time since upload, and VIQI scores according to TCS scores (p<0.05). Video duration and VIQI scores were higher for HC videos compared to LC videos. The time since upload for LC videos was higher than for HC videos. Positive correlations were observed between TCS scores, video duration, and VIQI, as well as between GQS scores, video duration, viewing rate, and VIQI. Conclusions The majority of NG videos on YouTube™ are useful and comprehensive, but their number is insufficient. Poor-quality and inadequate videos may mislead practitioners and patients. However, this also presents an opportunity for healthcare professionals to leverage YouTube™ as an educational tool. Periodontologists should upload more comprehensive videos and play a more active role in providing high-quality information.

Keywords:  content analysis; dentistry; e-health; necrotizing gingivitis; youtube

DOI:  https://doi.org/10.7759/cureus.61485
Laryngoscope. 2024 Jul 04.

"Does My Kid Have an Ear Infection?" An Analysis of Pediatric Acute Otitis Media Videos on TikTok.

Rose Dimitroyannis, Stella Cho, Sharanya Thodupunoori, David Fenton, Rachel Nordgren, Christopher R Roxbury, Andrea Shogan.

   INTRODUCTION: With the rise of social media, online platforms have become a common way to access healthcare information. This study examines the quality of pediatric acute otitis media (AOM) videos on TikTok, a popular short-form video social media platform.
METHODS: A TikTok search was conducted between 8/18 and 8/19/2023 using pediatric AOM hashtags: #pediatric acute otitis media management, #kid ear infections remedy, #child ear infections treatment, and #kid ear infection. Data collected include number of views/shares per day, uploader type (nonmedical influencer, lay individual, and medical professional), and content categories. The Patient Education Materials Assessment Tool for Audiovisual Material (PEMAT-AV) and DISCERN questionnaire measured understandability, actionability, and quality of videos. Multivariable linear regression models were used (significance set at ≤0.05).
RESULTS: Of 166 videos, 38.6% (64) of uploaders were medical professionals, and 32.5% (54) were nonmedical influencers. Nonmedical influencer videos were viewed and shared significantly more than those by medical professionals (p < 0.05). Controlling for covariates, physicians were more likely to produce more beneficial and higher quality videos as compared with nonmedical influencers (β = 2.4 and 1.3, p < 0.01, respectively). However, physicians did not have significantly different ratings for understandability compared with nonmedical influencers (β = 0.45, p > 0.05).
DISCUSSION: AOM content on TikTok is often geared toward caretakers of symptomatic children. Although physician-created AOM content was significantly higher quality, these videos reached a statistically smaller audience than those from nonmedical influencers. Addressing misinformation on social media platforms requires physicians to reach larger audiences by producing more actionable and understandable content.
LEVEL OF EVIDENCE: NA Laryngoscope, 2024.

Keywords:  acute otitis media; healthcare education; public health; social media

DOI:  https://doi.org/10.1002/lary.31617
Glob Health Med. 2024 Jun 30. 6(3): 212-217

Human papilloma virus (HPV)-related information acquisition and seeking behavior among infected women: A single center cross-sectional survey in Shanghai, China.

Xiehua Yuan, Linlin Lu, Ruhe Jiang, Yue Yu, Jing Zhou, Ling Wang, Yan Du.

  Lacking of adequate knowledge is an obstacle to effective prevention of cervical cancer, yet factors that affect the information acquisition and seeking behavior as well as the information communication process are not well studied. We assessed information acquisition and seeking behavior, as well as perceived barriers of doctor-patient communication regarding human papilloma virus (HPV)-related information of infected women. Among 437 participants, 405 (93%) expressed demands for HPV-related information, while only a small proportion (100/437, 22.9%) actively sought information and felt obstacles comprehending. Web-based channels were most frequently utilized and medical personnel were the most trusted information source. Patients' satisfaction was significantly correlated with doctor's patience (r = 0.581, p < 0.001) and emotional caring (r = 0.555, p < 0.001). Compared to patients not actively seeking information, those actively seeking information were more likely to be single (p = 0.005), had higher education (p = 0.009) and monthly individual-level income (p = 0.023), and was more likely to undergo regular cervical cancer screening (p = 0.003), and were already or willing to be vaccinated (p = 0.008). The actively seeking information group also achieved higher scores in HPV knowledge test (p = 0.007). Public health interventions targeting HPV-infected women using specifically designed educational materials may influence information seeking behavior, increase HPV literacy and knowledge, which could potentially increase HPV vaccine uptake and cervical cancer screening rate.

Keywords:  HPV infection; cervical cancer; health communication; information acquisition; prevention

DOI:  https://doi.org/10.35772/ghm.2023.01100