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Psychometric properties of the health literacy instrument in Brazil (HLS-EU-BR47)

Health literacy (HL) is a key component of health promotion and sustainability and contributes to well-being. Despite its global relevance, HL is an under-researched topic in South America but is now debuting ...

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Factors influencing smoking cessation attempts and success in Iranian male adults: national survey data

Smoking cessation is a dynamic process that often involves a series of unsuccessful quit attempts before long-term abstinence is achieved. To implement interventions that lead to long-term abstinence, it will ...

Barriers and facilitators to uptake and use of oral pre-exposure prophylaxis in pregnant and postpartum women: a qualitative meta-synthesis

Acute HIV infection during pregnancy and in the postpartum period increases the risk of vertical transmission. The World Health Organization (WHO) has recommended preexposure prophylaxis for pregnant and postp...

Unpacking the impact of COVID-19 on child immunization: evidence from Ghana

With the onset of the COVID-19 pandemic, governments implemented social distancing regulations to limit the spread of the disease. Some health experts warned that these measures could negatively affect access ...

Exploring community needs in combating aedes mosquitoes and dengue fever: a study with urban community in the recurrent hotspot area

Aedes mosquitoes are the main vector of dengue infection, a global health threat affecting millions of people annually. Conventional prevention and control methods against dengue outbreaks have only achieved m...

Geographic inequalities and determinants of anaemia among preeclamptic women: a cross-sectional sample-based study in Bangladesh

Anaemia among preeclamptic (PE) women is a major undefined health issue in Bangladesh. This study explored the risk factors associated with anaemia and mapped the regional influences to understand the geograph...

People affected by cancer and their carers from gender and sexually diverse communities: their experiences and the role of smartphone applications

People living with cancer, or carers who are from lesbian, gay, bisexual, transgender, queer, intersex or asexual (LGBTQIA+) communities experience unique information and support needs. Accessible technology-b...

Self-inflicted ingestion of harmful chemicals in adolescents and adults: risk factors and characteristics

Injury due to ingestion of harmful chemicals has become an area of concern globally. In South Africa, paraffin has been widely implicated in multiple health outcomes, including severe ingestion injuries. A spe...

Exploring online reproductive health promotion in Canada: a focus on behavioral and environmental influences from a sex and gender perspective

Reproductive health promotion can enable early mitigation of behavioral and environmental risk factors associated with adverse pregnancy outcomes, while optimizing health of women + (all genders that can gesta...

Cognitive performance trends among European older adults: exploring variations across cohorts, gender, and educational levels (2007–2017)

This study explores recent cohort trends in cognitive performance among older Europeans from 2007 to 2017, addressing three key questions: (1) Did cognitive performance improve universally and across the perfo...

Estimating helmet wearing rates via a scalable, low-cost algorithm: a novel integration of deep learning and google street view

Wearing a helmet reduces the risk of head injuries substantially in the event of a motorcycle crash. Countries around the world are committed to promoting helmet use, but the progress has been slow and uneven....

Relationship of urinary glyphosate concentrations with glycosylated hemoglobin and diabetes in US adults: a cross-sectional study

Glyphosate is a commonly used herbicide worldwide and is purportedly associated with multiple health effects. Research assessing the association of glyphosate concentrations with glycosylated hemoglobin (HbA1c...

Excess mortality during the COVID-19 pandemic in low-and lower-middle-income countries: a systematic review and meta-analysis

Although the COVID-19 pandemic claimed a great deal of lives, it is still unclear how it affected mortality in low- and lower-middle-income countries (LLMICs). This review summarized the available literature o...

Impact of the 2008 economic crisis on the burden of hepatitis B and C diseases in Southern European countries

The economic crisis that began in 2008 has severely affected Southern (Greece, Italy, Portugal, Spain) Western European (SWE) countries of Western Europe (WE) and may have affected ongoing efforts to eliminate...

Spatiotemporal epidemiology of substance-related accidental acute toxicity deaths in Canada from 2016 to 2017

In Canada, substance-related accidental acute toxicity deaths (AATDs) continue to rise at the national and sub-national levels. However, it is unknown if, where, when, and to what degree AATDs cluster in space...

The effect of educational intervention based on health belief model on colorectal cancer screening behaviors

Colorectal cancer is the second most prevalent cause of death from malignancies globally. The present study was conducted targeting the influence of an educational intervention based on the health belief model...

Burden of drug use disorders in the United States from 1990 to 2021 and its projection until 2035: results from the GBD study

Drug use disorders (DUDs) have emerged as one of the most significant public health crises, exerting a substantial influence on both community health and socio-economic progress. The United States (US) also su...

Community led health promotion to counter stigma and increase trust amongst priority populations: lessons from the 2022–2023 UK mpox outbreak

Stigma, lack of trust in authorities, and poor knowledge can prevent health-seeking behaviour, worsen physical and mental health, and undermine efforts to control transmission during disease outbreaks. These f...

Association of the American Heart Association’s new “Life’s Essential 8” with all-cause mortality in patients with chronic kidney disease: a cohort study from the NHANES 2009–2016

People with chronic kidney disease (CKD) are more likely to die prematurely, and this increased risk of death is primarily attributable to deaths from cardiovascular disease (CVD). We aim to investigate the re...

Maternal depressive symptom trajectories and associations with child feeding

Responsive feeding, when caregivers attend to children’s signals of hunger and satiation and respond in an emotionally supportive and developmentally appropriate way, is associated with the development of heal...

Neonatal mortality and associated factors among newborns in Mogadishu, Somalia: a multicenter hospital-based cross-sectional study

Neonatal mortality is a significant public health problem in Sub-Saharan Africa, particularly in Somalia, where limited data exists about this. Mogadishu, the densely populated capital, faces a high rate of ne...

Thriving from work questionnaire: German translation and validation

The Thriving from Work questionnaire is a comprehensive indicator of positive well-being for employees, applicable in both research and practical contexts. Current discussions underline the crucial impact that...

Working mechanisms of the use and acceptability of ecological momentary interventions: a realist evaluation of a guided self-help ecological momentary intervention targeting self-esteem

Technology improves accessibility of psychological interventions for youth. An ecological momentary intervention (EMI) is a digital intervention geared toward intervening in daily life to enhance the generaliz...

The impact of temperature, humidity and closing school on the mumps epidemic: a case study in the mainland of China

To control resurging infectious diseases like mumps, it is necessary to resort to effective control and preventive measures. These measures include increasing vaccine coverage, providing the community with adv...

Only 9% of mothers have eight and more ANC visit in 14 sub-saharan African countries; evidence from the most recent DHS 2018–2023: a multilevel analysis

The world health organization’s global health observatory defines maternal mortality as annual number of female deaths, regardless of the period or location of the pregnancy, from any cause related to or cause...

Parental reports of hospital- and community-based follow-up services, self-efficacy, and symptoms of depression a few months after discharge of a prematurely born child

Many parents report the transition from hospital to home as challenging after the birth of a preterm-born child. This study investigates parental perceptions of community-based follow-up services after hospita...

Modifiable factors influencing attention performance in healthy children: insights from a comprehensive school nutrition study

There is inconclusive evidence for the effects of various leisure activities on attention performance in children. The literature reports inconsistent associations between activities such as physical activiti...

Psychometric assessment of the Runyankole-translated Marlowe-Crowne Social Desirability Scale among persons with HIV in Uganda

Social desirability can negatively affect the validity of self-reported measures, including underreporting of stigmatized behaviors like alcohol consumption. The Marlowe-Crowne Social Desirability Scale (SDS) ...

An international perspective on young stroke incidence and risk factors: a scoping review

Stroke among younger age groups is increasing globally. While there is a focus on research conducted on people under 65 years who have had a stroke, there is a paucity of data on the incidence and risk factors...

Effect of sexual health education on sexual function and satisfaction of menopausal migrant women: an application of the theory of planned behavior

This study investigated the effect of an intervention based on the theory of planned behavior on sexual function and satisfaction of migrant women during menopause in Iran.

The association between screen time exposure and myopia in children and adolescents: a meta-analysis

This study aimed to systematically review epidemiological evidence on associations between screen time exposure and myopia in children and adolescents, and to quantitatively evaluate summary effect estimates f...

U-shaped relationship between non-high-density lipoprotein cholesterol and cognitive impairment in Chinese middle-aged and elderly: a cross-sectional study

The relationship between blood lipids and cognitive function has long been a subject of interest, and the association between serum non-high-density lipoprotein cholesterol (non-HDL-C) levels and cognitive imp...

The impact of telecom industry employees’ stress perception on job burnout: moderated mediation model

The rapid development of the telecommunications industry in the post-COVID-19 era has brought tremendous pressure to employees making them a high-risk group for job burnout. However, prior research paid less a...

Do health literacy, physical health and past rehabilitation utilization explain educational differences in the subjective need for medical rehabilitation? Results of the lidA cohort study

Medical rehabilitation can be helpful for maintaining workers’ health and work ability. Its contribution to longer working lives is of high economic relevance in aging populations. In Germany, individuals must...

How predictive of future healthcare utilisation and mortality is data-driven population segmentation based on healthcare utilisation and chronic condition comorbidity?

In recent years data-driven population segmentation using cluster analyses of mainly health care utilisation data has been used as a proxy of future health care need. Chronic conditions patterns tended to be e...

Factors associated with hookworm and Schistosoma mansoni infections among school-aged children in Mayuge district, Uganda

Hookworm infection and schistosomiasis are two of sub-Saharan Africa's most common neglected tropical diseases. An annual mass drug administration (MDA) program against schistosomiasis and soil-transmitted hel...

Translation and adaptation of the person-centered maternity care scale to a Persian-speaking population: a confirmatory factor analysis

Recognized as the most exhaustive multidimensional evaluation of women's person-centered experiences during childbirth, the Person-Centered Maternity Care (PCMC) Scale offers domain-specific insights into face...

Barriers and facilitators to uptake and persistence on prep among key populations in Southern Province, Zambia: a thematic analysis

Especially in high HIV prevalence contexts, such as Zambia, effective biomedical prevention tools are needed for priority populations (PPs), including key populations (KPs), who are at higher risk. HIV pre-exp...

The association of female reproductive factors with history of cardiovascular disease: a large cross-sectional study

This study aimed to explore the association of female reproductive factors (age at first birth (AFB), age at last birth (ALB), number of pregnancies, and live births) with history of cardiovascular disease (CVD).

Vaping cessation support recommendations from adolescents who vape: a qualitative study

Youth vaping is a serious public health concern, being more prevalent than any other tobacco use. To inform cessation interventions, we explored what adolescents perceive as their reasons for quitting and stra...

New Orleans school meal programs during the COVID-19 pandemic: challenges and innovations identified through qualitative interviews

School meal programs are critical to reducing childhood food insecurity. This study identified challenges and innovations in school meal service in a disaggregated charter school system during COVID-19 in New ...

The Childbearing sense of coherence scale (CSOC-scale): development and validation

the salutogenic theory is essential to explain an individual’s ability to maintain health during the perinatal period. While previous studies mainly focused on the perspectives from a family-level orientation ...

Social support as perceived, provided and needed by family-members of migrants with type 2 diabetes – a qualitative study

Social support provided by a family member has been found to have a buffering effect on distress and is associated with better diabetes self-care. This study explores the meaning of social support, as describe...

Correction to: Examining psychosocial pathways to explain the link between breastfeeding practices and child behaviour in a longitudinal cohort

The original article was published in BMC Public Health 2024 24 :675

Attitudes toward an HPV vaccine for condyloma acuminata and willingness to undergo vaccination among STD clinic attendees in China: Focus on STI prevention with HPV vaccine

Condyloma acuminata (CA) is a common, and recurrent sexually transmitted disease (STD) that greatly contributes to direct health care costs and has a substantial psychosocial impact. Human papillomavirus (HPV)...

Identifying emerging hot spots of road traffic injury severity using spatiotemporal methods: longitudinal analyses on major roads in Ghana from 2005 to 2020

Although road traffic injuries and deaths have decreased globally, there is substantial national and sub-national heterogeneity, particularly in low- and middle-income countries (LMICs). Ghana is one of few co...

Childcare needs as a barrier to healthcare among women in a safety-net health system

Childcare needs are an understudied social determinant of health. The effect of childcare needs on access to healthcare must be understood to inform health system interventions and policy reform. This study so...

Impact of health literacy, social support, and socioeconomic position on the serum uric acid level in asymptomatic hyperuricaemia patients in China: a structural equation model

Hyperuricaemia (HUA) poses a significant public health challenge on a global scale. It is mostly asymptomatic hyperuricemia (AHU) with unsatisfactory recognition and control rates. The role of health literacy ...

Roles of caregiver-child interaction on the association of socioeconomic status with early childhood development: a population-based study in rural China

Socioeconomic status (SES) has been previously associated with children’s early development, health, and nutrition; however, evidence about the potential role of caregiver-child interaction in such association...

Taking emic and etic to the family level: interlinking parents’ and children’s COVID-19 views and experiences in Germany

COVID-19 impacted families globally, restricting movement, and changing daily routines and family dynamics. In order to explore and contrast children’s and parents’ experiences and perceptions of life during C...

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Research topics and trends in medical education by social network analysis

Affiliations.

• 1 Biomedical Knowledge Engineering Laboratory, Seoul National University, Seoul, Republic of Korea.
• 2 National Center of Excellence in Software, Chungnam National University, Daejeon, Republic of Korea.
• 3 Center for Innovative in Dental Education, Seoul National University, Seoul, Republic of Korea.
• 4 College of Nursing, Keimyung University, 1095 Dalgubeol-daero, Dalseo-Gu, Daegu, 42601, Republic of Korea. [email protected].
• PMID: 30249248
• PMCID: PMC6154904
• DOI: 10.1186/s12909-018-1323-y

Background: As studies analyzing the networks and relational structures of research topics in academic fields emerge, studies that apply methods of network and relationship analysis, such as social network analysis (SNA), are drawing more attention. The purpose of this study is to explore the interaction of medical education subjects in the framework of complex systems theory using SNA and to analyze the trends in medical education.

Methods: The authors extracted keywords using Medical Subject Headings terms from 9,379 research articles (162,866 keywords) published in 1963-2015 in PubMed. They generated an occurrence frequency matrix, calculated relatedness using Weighted Jaccard Similarity, and analyzed and visualized the networks with Gephi software.

Results: Newly emerging topics by period units were identified as historical trends, and 20 global-level topic clusters were obtained through network analysis. A time-series analysis led to the definition of five historical periods: the waking phase (1963-1975), the birth phase (1976-1990), the growth phase (1991-1996), the maturity phase (1997-2005), and the expansion phase (2006-2015).

Conclusions: The study analyzed the trends in medical education research using SNA and analyzed their meaning using complex systems theory. During the 53-year period studied, medical education research has been subdivided and has expanded, improved, and changed along with shifts in society's needs. By analyzing the trends in medical education using the conceptual framework of complex systems theory, the research team determined that medical education is forming a sense of the voluntary order within the field of medicine by interacting with social studies, philosophy, etc., and establishing legitimacy and originality.

Keywords: Complex systems theory; Medical education; Research topics; Research trends; Social network analysis.

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Research topics and trends in medical education by social network analysis

1 Biomedical Knowledge Engineering Laboratory, Seoul National University, Seoul, Republic of Korea

2 National Center of Excellence in Software, Chungnam National University, Daejeon, Republic of Korea

Hong Gee Kim

3 Center for Innovative in Dental Education, Seoul National University, Seoul, Republic of Korea

Soo-Kyoung Lee

4 College of Nursing, Keimyung University, 1095 Dalgubeol-daero, Dalseo-Gu, Daegu, 42601 Republic of Korea

Associated Data

The datasets used in this study are stored at the College of Nursing, Keimyung University and the Center for Innovative Dental Education Korea. They are available from the corresponding author on reasonable request.

As studies analyzing the networks and relational structures of research topics in academic fields emerge, studies that apply methods of network and relationship analysis, such as social network analysis (SNA), are drawing more attention. The purpose of this study is to explore the interaction of medical education subjects in the framework of complex systems theory using SNA and to analyze the trends in medical education.

The authors extracted keywords using Medical Subject Headings terms from 9,379 research articles (162,866 keywords) published in 1963–2015 in PubMed. They generated an occurrence frequency matrix, calculated relatedness using Weighted Jaccard Similarity, and analyzed and visualized the networks with Gephi software.

Newly emerging topics by period units were identified as historical trends, and 20 global-level topic clusters were obtained through network analysis. A time-series analysis led to the definition of five historical periods: the waking phase (1963–1975), the birth phase (1976–1990), the growth phase (1991–1996), the maturity phase (1997–2005), and the expansion phase (2006–2015).

Conclusions

The study analyzed the trends in medical education research using SNA and analyzed their meaning using complex systems theory. During the 53-year period studied, medical education research has been subdivided and has expanded, improved, and changed along with shifts in society’s needs. By analyzing the trends in medical education using the conceptual framework of complex systems theory, the research team determined that medical education is forming a sense of the voluntary order within the field of medicine by interacting with social studies, philosophy, etc., and establishing legitimacy and originality.

Electronic supplementary material

The online version of this article (10.1186/s12909-018-1323-y) contains supplementary material, which is available to authorized users.

An ancient scholar, Aristotle, established the basis of predicate logic, which divides knowledge into the smallest units and expresses it by linking them together (Sung-ho H: Structure and emergence analyses of knowledge network based on the social network analysis (SNA) methods: Focused on chungcheong strategic industries, unpublished) [ 1 ]. Recent studies have begun to use social network analysis as a means to analyze the trends of studies and understand the knowledge systems of each field by analyzing previously researched results. Generally, the purpose of research trend analysis in a particular academic field is to comprehend the current state of research by examining the existing results and to present future research directions [ 2 ].

Research trend analysis has been conducted for articles published in representative journals in medical education (ME), and its results serve as fundamental measures for securing academic identity [ 3 , 4 ]. Analysis is being conducted from multiple angles to confirm this identity from a holistic perspective, and research methods analyzing the relationship through the application of SNA in research trend analysis are steadily increasing in the social studies field.

The study of trends in medical education analyzes the entire academic field or the subject of a particular academic field. There are studies taking quantitative approaches such as those analyzing the frequency of medical training in medical education [ 4 – 8 ]. Other examples include studies that a) focused on the main subjects studied in medical education by analyzing common research topics in medical education from six journals [ 4 ], b) analyzed the co-topics occurring frequently in ME articles and the differences among journals’ publication of co-topics [ 9 ], c) focused on top-cited articles identified by keyword search [ 10 ], and d) focused on network analysis of the researchers in medical education [ 11 ]. In addition, analysis of unit subjects in specific academic fields, such as an analysis of the trends in research topics including a study on the geographical distribution of researchers whose works have published in major journals of medical education [ 12 ] and a study on the social relationships of medical students and the dispersion of their attitudes [ 13 ], have been conducted steadily each year.

These studies are meaningful in that they analyze the trends of medical education subjects from a macro perspective or study specific research topics from a micro perspective, thus enabling the analysis of the trends in medical education and its knowledge system. However, this method requires the collection and analysis of vast amounts of data, demanding considerable time and manpower for interpretation. In addition, it is highly likely that researchers rely on the knowledge, experience, and insight of experts during analysis [ 14 , 15 ]. In addition, the analysis has to be conducted by sorting the impactful keywords based on frequency [ 9 , 11 ] or citation factors [ 10 ] or through keyword analysis by topics [ 4 ]. However, such methods are limited in their ability to identify historical changes in the relationships between specific topics. SNA is a commonly accepted method for quantitatively and visually obtaining the overall structures of network connections.

As studies analyzing the networks and relational structures of research topics in academic fields emerge, studies that apply methods of network and relationship analysis, such as SNA, are drawing more attention [ 16 ]. General methods of analyzing research trends include using co-word analysis on keywords extracted from databases [ 10 , 11 ], co-citation analysis using the citation information of articles [ 12 ]. And there have also been studies on topics network analysis [ 13 , 16 – 18 ].

SNA is an actively utilized method that recognizes and interprets complex phenomena under micro units as an issue of order [ 17 ]. Exploring the interactions and qualitative changes in research topics in medical education according to the framework of complex systems theory will provide new answers regarding the knowledge network of medical education. Unlike previous quantitative studies on the issues in medical education, this paper aims to identify the phases of medical education distinguished by changing topics and explore the topics that emerge during the phases.

Therefore, the study utilizes SNA to investigate the interaction patterns among the issues in medical education by applying the framework of complex systems theory [ 18 ] and realistically contemplating the abstract knowledge network of medical education.

In order to grasp the features of research trends in the field of medical education, the study extracted social-network keywords connected to terms from the title and abstract of available articles in Medline. Mesh terms were used during the process of retrieving articles from Pubmed, and the keyword extraction was conducted through text analysis. The information used for the analysis in this paper includes the title, abstract, and publication year of the paper. Since MeSH terms are not attached to all of the papers to be analyzed in this study, the authors extracted the keywords using the TextRank algorithm from the text consisting of the title and abstract. The TextRank algorithm is advantageous in that it provides high performance without being influenced by the linguistic characteristics of the text to be analyzed (Mihalcea R, Tarau P: TextRank - bringing order into texts. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, unpublished). A more detailed analysis was conducted by collecting the articles for analysis. This analysis included 1) category-setting through analysis of keyword similarity, 2) performing content analysis on the keywords, 3) analyzing the resulting network, and 4) conducting a trend analysis.

In June 2015, we searched PubMed for articles indexed under the “medical” major topic whose titles or abstracts included the term “medical education.” Our query terms included related terms such as “medical learner,” “medical teacher,” “medical teaching,” “medical training,” “medical learning,” and “medical education.” In this stage, two researchers reviewed and evaluated the list of keywords. For all of the papers, the extracted keywords with the use of the TextRank Algorithm underwent a refining process by two researchers. During the refining process, in order to refine the keywords, we looked at the whole list, checked and summarized the thesaurus, exception list, and defined words that needed refinement, and conducted a re-analysis of keywords. For instance, the research team deleted numbers or keywords such as “the”, “% +/”, “% <”, “% ci -0/3”, “(99 m) tc” which make it difficult to draw out the meaning of a keyword before data analysis. They also considered singular and plural keywords, such as “cardiac problem” and “cardiac problems,” as synonyms. Moreover, abbreviations were normalized by controlling them with a list of synonyms.

Then, as the first stage in the data analysis, the team generated a frequency matrix sized 3,030X53 that consisted of the yearly frequency of all the terms and the year of publication of each article. Next, to sort out the terms, the team calculated the weighted value of the terms by applying the Term Frequency–Inverse Document Frequency (TF–IDF) formula used in the field of information search [ 19 ]. The weighted value W t,D was calculated using the formula below.

The tf(t,D) refers to the adjusted value of the sum of the frequencies of t of terms used in data collection using yearly frequency, and N from log Y y ∈ Y : t appears in y refers to the yearly range 53 {y∈Y: t appears in y}.

TF–IDF is a weighted value used in text mining, and it indicates how many times a certain word appears in a given document. The higher the value of TF-IDF, the greater its importance; this also means that the word appears often. Therefore, the value multiplies DF (Document Frequency) with IDF (Inverse Document Frequency), a reciprocal number. Since this value increases with the frequency of a specific word and decreases with the number of documents containing the word out of the total number of documents, it filters the words that appear often in most documents [ 20 ].

In order to quantitatively calculate the relationship between MeSH terms, the research team calculated the Weighted Jaccard Similarity [ 20 ].

That is, the relationship between the terms and t was calculated with the formula below, using the yearly frequency information from the frequency matrix.

Relatedness ( S ,  T ) = ∑ y mina S y T y ∑ y maxa S y T y .

Distributional Hypothesis [ 21 ] is the result of a study showing that when two words are used in the same context, these two words tend to have a similar meaning, and we assumed that there is a higher correlation between the two words if two keywords were used many times in the same year compared to the case where they were not. The science mapping principle dictates that the more related two elements are, the closer to each other they are positioned in a map [ 22 ]. This study based on the approach of distribution hypothesis and the science mapping principle for the correlation between words, the frequency value of each word’s annual appearance was used. The calculation method used in this study is a Weighted Jaccard similarity that used the appearance frequency of keywords. When using a Weighted Jaccard similarity, if two words are used together with high frequency in multiple years, they return a high similarity value.

Clustering of keywords was calculated using the Markov Cluster(MCL) Algorithm [ 23 ], which is widely applied to weight graphs in the computer science field, after constructing a graph with the keyword as the node of the graph and the similarity between the keywords as the weight of the edge between the nodes.

The MCL algorithm is a simple yet useful algorithm that is used for sequence data clustering in the biotechnology field which can be expressed as a weight graph. Therefore, it can be understood that the keywords with a high frequency of simultaneous appearance are used in the same context and have a higher correlation than other words in the same year. That is to say, they return a high similarity value.

Data analysis and interpretation

In order to analyze the process of change in research topics in the medical education field, the study used the Frequency Matrix and the Weighted Jaccard Similarity and marked the times at which clear changes occurred, such as when new keywords rapidly emerged or diminished, using yearly similarities as cut-off points. The entire data collection process was separated into five phases based on the emergence of keywords, and each phase was analyzed using SNA. In order to conduct the network analysis, the input file for Gephi, a tool used in network analysis, was generated by calculating the relevance of terms for each phase using the methods mentioned above and representing the values as the relevance between nodes. The size of each node was expressed as the authority score obtained by the HITS (Hypertext Induced Topic Selection) algorithm of Gephi [ 24 ]. The authority score enabled the extraction of main research topics by using the mutual information between the nodes that comprised the network. Here, the authority score refers to the frequency of the reception of links [ 25 ].

The study used PubMed articles that were available for electronic search using MeSH terms in October 2015. From 1963, the year of the first publication related to medical education, to 2015, a total of 9,379 articles (with 162,866 keywords) on medical education were published in PubMed, with a slow increase over time and a rapid increase since the 2000s.

Category-setting through analysis of keyword similarity

Figure  1 shows the results of the analysis of keywords by year, arranged in three-year sections. In the graph, points at which similarity begins to increase after decreasing indicate a great increase in change in keywords; these were set as phase cut-off points.

Phase-setting by similarity

On the basis of the similarity analysis by year, phase 1 was set to range from 1963 to 1975; phase 2 from 1976 to 1990; phase 3 from 1991 to 1996; phase 4 from 1997 to 2005; and phase 5 from 2006 to 2015. The next subsection characterizes these phases by keyword (and the keywords by phase).

Content analysis in the key words

Figure  2 shows increases and decreases in the top 20 keywords newly appearing in each phase. Keywords newly emerging as research topics were as follows for each phase: From phase 1 to 2, “Internship and Residency,” “Medical Staff, Hospital,” and “Psychiatry;” from phase 2 to 3, “Problem-Based Learning,” “Program Development,” and “Health Care Reform;” from phase 3 to 4, “Internet,” “Evidence-Based Medicine,” and “Education, Distance;” and from phase 4 to 5, “Young Adult,” “Quality Improvement,” “General Practice,” “Patient Safety,” “Cultural Competency,” and “Self-Efficacy.”

Top20 new keywords for each phase

Analysis of the resulting network

To systematically understand research trends and changes in knowledge structure in medical education over time, this study analyzed connections between keywords using social network analysis.

Figure  3 shows a schematization of the network resulting from extraction of keywords with high connectivity and high weighted value for each phase. In all, 20 clusters were schematized.

Topic clusters in medical education

Topics in cluster 1, the largest group (comprising 19 nodes), are as follows: “Education, Medical, Graduate,” “Questionnaires,” “Clinical Competence,” and “Internship and Residency.” Cluster 2 is made up of eight nodes, under the following topics: “Middle Aged,” “Data Collection,” “Accreditation,” and “Problem-Based Learning.” Cluster 3 has seven nodes, under the following topics: “Communication,” “Career Choice,” and “Computer-Assisted Instruction.” Topics in cluster 4 are gathered around “Computer Simulation,” “Leadership,” and “User–Computer Interface.” In cluster 5, “Competency-Based Education” and “Professional Competence” are the topics, and cluster 6 mainly deals with “Adolescents,” “Fellowships and Scholarships,” and “Interview as Topic.”

Trend-watching: All five phases

Figure  4 shows the SNA over all five phases, with detailed topic networks for each phase given in the Additional files  1 , 2 , 3 , 4 and 5 : Figures S1–S5. Phase 1 (1963–1975) showed lower connectedness among research topics compared to other phases, due to the difference in scale of article publication. Central keywords included “Education, Medical, Undergraduate,” “Curriculum,” “Male,” “Female,” and “Adult.” On the basis of these keywords, a subnetwork emerged, continuing up to phase 5. In phase 2 (1976–1990), connections between central keywords grew tighter, and new keywords appeared, including “Professional Competence,” “Attitude of Health Personnel,” and “Peer Review.” In phase 3 (1991–1996), connections among keywords such as “Clinical Competency,” “Educational Measurement,” and “Physician–Patient Relations” were enhanced. In phase 4 (1997–2005), the association of keywords with high connectedness became dual, and connections among keywords such as “Data Collection,” “Problem-Based Learning,” and “Health Knowledge, Attitudes, Practice” were enhanced. In phase 5 (2006–2015), the number and connectedness of keywords increased, and new keywords, such as “Computer-Assisted Instruction,” “Personal Staffing and Scheduling,” “User–Computer Interface,” “Professional Competency,” “Accreditation,” “Program Evaluation,” and “Educational Measurement,” appeared.

SNA of each historical phase of medical education

The study realistically contemplated the abstract knowledge network of medical education by identifying the network trends in medical education research topics through the use of SNA and investigating the use patterns in interactions by time. The study contains articles from the year when PubMed made it possible to electronically search for MeSH term in medical education articles, and coincidentally, this is consistent with Norman’s suggestion that a new generation of medical education has emerged [ 25 ].

The study identified five phases based on the changes in time indicated by clear differences in keyword similarities and identified newly derived keywords and networks in each phase. The clustering was conducted by deriving the keywords with high similarity using the appearance frequency values ​​of the two keywords and constructing a weighted graph based on the similarity between the keywords. This can be observed by clustering the sequences of the main keywords overall.

When the trend of the newly emerged keywords from five phases was analyzed, the keywords with the highest increase rates in all the phases, such as “Education,” “Medical,” “Humans,” “Curriculum,” “Continuing Medical Education,” and “Internship and Residency,” were similar to the keywords from a previous study by Lee K. [ 9 ]. Such repetition of research topics, as noted in the study by Eva K. W., probably occurs because studies in medical education are mostly observational [ 26 ].

In a similar study, Lee K. also analyzed the historical trends in medical publications in the field of medical education [ 9 ]. Even though the general trend appears similar, it did not distinguish the semantic unit that grasps the variations in the emergence of new keywords. Therefore, the study is meaningful in that it distinguishes between the phases by analyzing the interactions between medical education keywords using the complex systems framework.

Research in medical education has mostly been dominated by a positivist approach [ 26 ], and the emergence of new keywords with time represents the extent of the efforts being made to reflect social needs using the educational paradigm [ 27 ]. When the contents of topics that increased in a certain period or had newly emerged were analyzed, the first phase was characterized by important keywords being continuously mentioned in medical education, and new keywords such as “competency” or “accreditation” began to appear in the second phase. This could be due to the fact that the authentication program was formally declared in 1975 in order to improve the quality of medical education [ 28 ]. Considering that the top-cited articles in medical education began to contain reviews and research on competency since then, the studies seem to have been accumulated from this time [ 10 ]. Keywords that emerged in the third phase, such as “problem-based learning” and “computer communication networks” imply an increased interest in new education methods [ 4 ]. Keywords such as “competency-based assessments” and “outcome-based education,” which emerged in the fourth phase, represent the extension of research topics during the time period in which medical education became a topic of conversation [ 28 ]. Finally, the fifth phase is characterized by the emergence of keywords such as “quality improvement,” “patient safety,” “cultural competency,” and “self-efficacy,” which confirms that more research reflecting the trend is being conducted and realistic demands of medical education are being made. This period is also marked by increased interest in medical education and emphasis on the importance of evaluation, and thus, qualitative analysis and program evaluation were among the most important research topics (Fligstein N: Theoretical perspectives in medical education: past experience and future possibilities, unpublished). It appears that interest in quality improvement increased as social requirements for doctors gradually influenced educational institutions [ 27 , 29 , 30 ]. Therefore, various educational programs should be developed and evaluated with a focus on the effectiveness of medical education [ 31 – 34 ].

After exploring the keywords used in medical education research using SNA from a macro perspective, the research team analyzed the research trends of each phase by historical flow. When a network is considered to be one ecosystem, it corresponds with the principle of complex systems, and from the perspective of interpreting the flow of the network, the complex systems logic is presented as a new alternative [ 35 ]. Recently, there have been a number of discussions on the need to explore the nature of knowledge networks using complex systems theory [ 17 ].

The study was able to identify the process of improving the academic field in medical education by analyzing keywords in separate phases. This effort can be considered as a method of knowledge formation clearly distinguished from those used in previous studies. An emergency refers to a disorderly situation that arises as a result of complex network structures and patterns, and the system of such an emergency can be referred to as a complex system [ 18 ]. Unlike the analysis of keyword emergence, the flow of the phases studied by SNA is quite similar to the changing trend in human societies or networks [ 36 ]. This implies that the research topics in medical education resemble the emergence phenomena, as used in the complex phenomena. In other words, when examining the timely flow of keywords related to medical education, it can be noted that the newly emerged keywords form a network by interacting with each other. This, like the coevolution phenomena presented by complex systems theory, shows a similar phenomenon in which keywords evolve as they interact. As such, it seems like the trend in topics by phases derived through medical education keyword analysis is a part of the change process suggested by complex systems theory. At the same time, a cycle in which new research topics emerge, interact, and evolve should be formed [ 30 , 37 ].

As the research team examined the research trends by phase, the features of each phase could be analyzed on the basis of complex systems theory: the waking phase (1963–1975), the birth phase (1976–1990), the growth phase (1991–1996), the maturity phase (1997–2005), and the expansion phase (2006–2015). And each name contained one the following meanings. The first period (1963–1975) is when keywords that served as central nodes for all the phases, such as “Education, Medical, Undergraduate” “Curriculum,” “Male,” “Female,” and “Adult,” appeared. This period forms the backbone of research in medical education, and shows the networks of basic levels. The second phase (1976–1990) is the period of the birth of medical education. The major keywords in the first phase focused on the subjects; however, the second phase is characterized by a focus on the keywords of properties, such as “Professional Competence,” “Attitudes of Health Personnel,” and “Peer Review.” In order for the subjects of medical education research to connect and be studied, it seems like the keywords representing the properties or characteristics should emerge and connect the subjects and foster the research. The third phase (1991–1996) was a period of growth for medical education, which is marked by the emergence of keywords in research methodology such as “Educational Measurement,” “Evaluation as Topic,” and “Questionnaire.” It appears that various methodologies have been tried in order to achieve qualitative improvement in subjects and properties. Ultimately, this seems to reflect the purpose of solving various problems in medical education, and it has been confirmed that suggested alternatives influenced and improved the academic field of medical education. The fourth phase (1997–2005) was a period of maturity, when keywords such as “Health Knowledge, Attitudes, and Practice,” “Ethics and Medicine,” and “Physician-Patient Relations” emerged. These keywords reflect an increasing interest in selecting physician candidates with high morality, with an emphasis on ethical responsibilities in medical education. At the same time, the trend represents the extension of research topics from analysis of general education to quality management [ 27 ]. From this perspective, various educational keywords in performance and competency are being connected in this phase. This trend could imply that the influence of general citizens’ requirements of physicians could have had effects on the education sector as well. The fifth phase (2006–2015) was a period of expansion, and major keywords such as “Computer Assisted Instruction,” “Personal Staffing and Scheduling,” “User-Computer Interface,” “Professional Competency,” “Accreditation,” and “Program Evaluation” emerged. Unlike other keywords, medical education keywords have larger network connectivity from the fifth phase, forming true network structures. While the first three phases are marked by the emergence of new keywords, the fourth phase is characterized by network formation. The fifth phase is called the period of expansion because networks are becoming highly concentrated and forming new networks.

However, the study has some limitations. First of all, since it is a quantitative study using SNA, it focused on terms related to medical education in Medline without taking into consideration the articles published in medical education journals such as JAMA(Journal of the American Medical Association), BMJ(British Medical Journal), JAMA internal medicine, etc. Thus, compared to the studies conducted by Rotgans JI, Wolf E Hautz et al., and Tutarel O, some articles are not reflected in this study [ 4 , 11 , 12 ]. Secondly, as in many other studies, the research team could only search for articles published in English. Thirdly, co-word analysis, co-citation analysis, and bibliographic coupling are among the most commonly used content analysis methods in the field of bibliometrics [ 38 ]. Co-word analysis used in this study is a method of analyzing a pattern in which a pair of terms (phrases) used in text in a specific field are analyzed at the same time to reveal the knowledge structure of the field. In this paper, the corelation between two words is used by frequency of use of words in common by year using the approach of distribution hypothesis. However, in order to better comply with the context-based distribution hypothesis, a new method is needed to calculate semantic relations between two words in the future. Fourthly, since this is a quantitative study, there is a need for interdisciplinary research focusing on issues in sociology, economics, or ecology. At the same time, future studies could focus on the establishment of new theories from current effectiveness verification studies. Lastly, a great amount of time and manpower was required for data collection, classification, and interpretation, because of which the study could not implement additional keyword analysis within the last one year. This calls for the development of a new research methodology that can readily analyze recent trends through SNA.

As this shows, medical education research has focused not only on medical knowledge and practice (content) but also on research topics related to education theory as a social science (pedagogy) [ 31 , 39 ]. Hence, for the development of medical education, a relevant community of work in related social science fields is also needed, and this work, from all disciplines, needs to be pursued in an integrated, interdisciplinary fashion, with fields and studies reflecting each other’s requirements and assumptions. In this way, a new and unique kind of medical education will develop, which will be crucial for the future of the field.

The study reinterpreted the changes in medical education using the complex systems theory, a mechanism in which various factors influence each other and collide into an order while forming a causal relationship. This confirmed that a unique legitimacy of medical education is being formed. Research in medical education is continuously improving and keeping pace with numerous social changes. Therefore, as educational and sociological theories integrate in the field of medicine, the medical education sector is expected to achieve independent development in the future.

Additional files

Figure S1. SNA of each historical phase1(1963–1975) of medical education (TIF 1645 kb)

Figure S2. SNA of each historical phase2(1976–1990) of medical education (TIF 2932 kb)

Figure S3. SNA of each historical phase3(1991–1996) of medical education. (TIF 3844 kb)

Figure S4. SNA of each historical phase4(1997–2005) of medical education. (TIF 3575 kb)

Figure S5. SNA of each historical phase5(2006–2015) of medical education. (TIF 2378 kb)

This research was supported by the Office of Research Affairs of the Seoul National University Fundation (No. 860–20140058) and by a National Research Foundation of Korea (NRF) grant funded by the Korean Ministry of Science, ICT and Future Planning (No. NRF-2015R1C1A1A01055753).

Availability of data and materials

Abbreviations.

Authors’ contributions

YJ substantial contributed to the conception or design of the work or the acquisition, analysis, or interpretation of data for the work. SN contributed to the design of the work and analze big data for the work. HK contributed to the approval of the version to be published. JL contributed to the interpretation of data and drafting the work or revising it critically for importatnt intellectual content. SL contributed to the agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work. All authors read and approved the final manuscript.

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Not applicable.

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Competing interests.

The authors declare that they have no competing interests.

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Young A Ji, Email: rk.ca.uns@ijay .

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AHP indicates allied health professional; CM, care manager; SW, social worker.

Box plots illustrate the distribution of daily secure messages sent and read per user, grouped by unique user-role labels. Boxes represent the IQR with the median marked by a horizontal line. AHP indicates allied health professional; APP, advanced practice professional; CM, care manager; SW, social worker.

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• A Window Into Inpatient Health Care Delivery Through Secure Message Logs JAMA Network Open Invited Commentary December 26, 2023 Lisa S. Rotenstein, MD, MBA, MSc; Srijan Sen, MD, PhD

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Small W , Iturrate E , Austrian J , Genes N. Electronic Health Record Messaging Patterns of Health Care Professionals in Inpatient Medicine. JAMA Netw Open. 2023;6(12):e2349136. doi:10.1001/jamanetworkopen.2023.49136

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Electronic Health Record Messaging Patterns of Health Care Professionals in Inpatient Medicine

• 1 New York University Grossman School of Medicine, New York, New York
• Invited Commentary A Window Into Inpatient Health Care Delivery Through Secure Message Logs Lisa S. Rotenstein, MD, MBA, MSc; Srijan Sen, MD, PhD JAMA Network Open

Miscommunication and teamwork failures are leading causes of sentinel events 1 and cost US hospitals an estimated $12 billion in 2010. 2 Information technology facilitates communication among health care professionals (HCPs). The US Centers for Medicaid & Medicare Services states that HCPs should only text patient information using secure messaging applications. 3 Messaging is reported to improve patient emergency department length of stay. 4 However, messaging has unintended patient safety consequences, such as increased interruptions for HCPs. 5 Implementors of messaging technologies must appreciate interprofessional communication patterns, potential misuse, and consequences for patient care.

Since 2017, our large urban academic medical center has provided secure messaging access via desktop computers and smartphones. Patients can be linked to conversations comprising 2 or more HCPs in Epic Secure Chat, facilitating care decisions. To better understand use patterns among HCPs and relative consequences for their daily work, this study characterizes a mature electronic health record–based secure messaging network used in the care of internal medicine inpatients.

The New York University Grossman School of Medicine Institutional Review Board approved this cross-sectional study and waived informed consent. The STROBE reporting guideline was followed. We extracted Epic Secure Chat metadata, including user details and time stamps, associated with internal medicine service inpatients (excluding intensive care unit [ICU] transfers) at 4 hospitals from January 25, 2021, to January 25, 2022. Roles were categorized as medicine and nonmedicine attendings, house staff, advanced practice professionals (eg, nurse practitioners and physician assistants), nurses, technicians, and social workers, care managers, or allied health professionals. User-level analysis included only HCPs who participated in at least 100 messages during the study period. Demographic information was limited for age and sex and was unavailable for race and ethnicity. Data analysis was performed on October 30, 2023, using Python, version 3.9.16 (GCC).

This study included 14 329 participants. Over 12 months, 15.1 million messages were sent to 2.3 users each over 108 000 inpatient encounters (33.7 daily messages/encounter). There were 5.1 million messages sent about internal medicine inpatients to 2.5 users each during 22 900 encounters (35.9 daily messages/hospitalization). Approximately 69.1% of messages were sent between 8 am and 6 pm ( Figure 1 ), and weekday volume was 36.3% higher. Most messages (75.9%) yielded responses within 5 minutes.

Nurses sent the largest proportion of messages (27.7%), followed by medicine house staff (13.5%) and social workers, care managers, and allied health professionals (12.6%). However, temporal variation existed, with medical clinicians sending the most daytime messages ( Figure 1 ). Per user, medicine practitioners had the largest daily messaging burden ( Figure 2 ). Whereas most medicine house staff (77.0%) received more than 45 daily messages, medicine attendings generally sent fewer messages but received up to 250 daily messages.

These findings suggest that messaging patterns differ by role, with medicine providers sending and receiving 2.8 and 3.1 times the average daily messaging volume as the other groups, respectively. Unlike the other groups, nursing did not exhibit diurnal messaging patterns and represented the largest contributor among roles despite lower per-user messaging. Future studies should evaluate consequences of messaging on individual and team performance, identify harmful patterns, and analyze message content to contextualize important events (eg, ICU transfers).

Institutional policies on storing messages limited our ability to analyze their content, which is critical to further interpreting inpatient communication patterns. Generalizability of these findings may be limited to academic medical centers with years of messaging experience.

Although secure messaging use has surged, concerns exist regarding its contributions to HCP interruptions 5 and burnout analogous to in-basket messaging for outpatient HCPs. 6 We cannot yet comment on adaptive messaging behaviors but emphasize that Epic Secure Chat should not be used for urgent and emergent issues; this should ease expectations of fast responses and promote HCP concentration. Characterizing messaging patterns in the inpatient setting represents a first step in facilitating benchmarking and, ultimately, strategic interventions to enhance the HCP digital experience, preserving the technology’s benefits while mitigating its disruptions.

Accepted for Publication: November 7, 2023.

Published: December 26, 2023. doi:10.1001/jamanetworkopen.2023.49136

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Small W et al. JAMA Network Open .

Corresponding Author: William Small, MD, MBA, New York University Grossman School of Medicine, 405 E 14th St, Apt 12D, New York, NY 10009 ( [email protected] ).

Author Contributions: Dr Small had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Small, Iturrate, Genes.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Small, Genes.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Small, Iturrate.

Administrative, technical, or material support: Small, Iturrate.

Supervision: All authors.

Conflict of Interest Disclosures: None reported.

Data Sharing Statement: See the Supplement .

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Xylitol is prothrombotic and associated with cardiovascular risk

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Marco Witkowski, Ina Nemet, Xinmin S Li, Jennifer Wilcox, Marc Ferrell, Hassan Alamri, Nilaksh Gupta, Zeneng Wang, Wai Hong Wilson Tang, Stanley L Hazen, Xylitol is prothrombotic and associated with cardiovascular risk, European Heart Journal , 2024;, ehae244, https://doi.org/10.1093/eurheartj/ehae244

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The pathways and metabolites that contribute to residual cardiovascular disease risks are unclear. Low-calorie sweeteners are widely used sugar substitutes in processed foods with presumed health benefits. Many low-calorie sweeteners are sugar alcohols that also are produced endogenously, albeit at levels over 1000-fold lower than observed following consumption as a sugar substitute.

Untargeted metabolomics studies were performed on overnight fasting plasma samples in a discovery cohort ( n = 1157) of sequential stable subjects undergoing elective diagnostic cardiac evaluations; subsequent stable isotope dilution liquid chromatography tandem mass spectrometry (LC-MS/MS) analyses were performed on an independent, non-overlapping validation cohort ( n = 2149). Complementary isolated human platelet, platelet-rich plasma, whole blood, and animal model studies examined the effect of xylitol on platelet responsiveness and thrombus formation in vivo . Finally, an intervention study was performed to assess the effects of xylitol consumption on platelet function in healthy volunteers ( n = 10).

In initial untargeted metabolomics studies (discovery cohort), circulating levels of a polyol tentatively assigned as xylitol were associated with incident (3-year) major adverse cardiovascular event (MACE) risk. Subsequent stable isotope dilution LC-MS/MS analyses (validation cohort) specific for xylitol (and not its structural isomers) confirmed its association with incident MACE risk [third vs. first tertile adjusted hazard ratio (95% confidence interval), 1.57 (1.12–2.21), P < .01]. Complementary mechanistic studies showed xylitol-enhanced multiple indices of platelet reactivity and in vivo thrombosis formation at levels observed in fasting plasma. In interventional studies, consumption of a xylitol-sweetened drink markedly raised plasma levels and enhanced multiple functional measures of platelet responsiveness in all subjects.

Xylitol is associated with incident MACE risk. Moreover, xylitol both enhanced platelet reactivity and thrombosis potential in vivo . Further studies examining the cardiovascular safety of xylitol are warranted.

Role of the artificial sweetener xylitol in cardiovascular event risk. In initial untargeted metabolomics studies (discovery cohort) and subsequent stable isotope dilution liquid chromatography tandem mass spectrometry (LC-MS/MS) studies (validation cohort), fasting levels of xylitol are associated with incident major adverse cardiovascular events (MACE). Using human whole blood, platelet-rich plasma, and washed platelets, xylitol enhances multiple indices of platelet reactivity in vitro . Xylitol also was shown to enhance thrombosis formation in a murine arterial injury model in vivo . In human intervention studies, when subjects ingested a typical dietary amount of xylitol in an artificially sweetened food, multiple functional measures of platelet responsiveness were significantly increased. Xylitol is both clinically associated with cardiovascular event risks and mechanistically linked to enhanced platelet responsiveness and thrombosis potential in vivo . ADP, adenosine diphosphate; MI, myocardial infarction.

• cardiovascular diseases
• blood platelets
• sugar alcohols
• sweetening agents
• whole blood

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