Singapore University Research Articles

Perceived challenges and opportunities for basic scientists transitioning to basic science educators in medical and health professions education

Basic science educators play a significant role in medical and health professions curricula, particularly in the biomedical science components. Although the shift from basic scientists to educators seems promising, no study has yet explored the transition process from the perspective of basic scientists themselves, especially in the early stages of their transition. An anonymous survey with voluntary participation was administered to all basic scientists in National University of Singapore (NUS) Yong Loo Lin School of Medicine. The survey aimed to identify the perceived challenges faced by basic scientists transitioning to basic science educators in medical and health professions education. This study consisted of Likert scale questions, followed by one multiple-choice question and two open-ended questions. Twenty-one basic scientists either postdoctoral fellows or instructors, completed the study. The study found that gaps in clinical content and experience, along with teaching pedagogy and training were among the major concerns for basic scientists aspiring to be basic science educators. These challenges and shortcomings could potentially be addressed by providing them with clinical shadowing opportunities, education mentorship and teaching training. Since most respondents lacked teaching experience, the results might differ if the majority had been involved in teaching within medical and health professions education. Nonetheless, it is important to understand and acknowledge the challenges and concerns experienced by basic scientists and examine how they can navigate them in the process of their transition to teaching medical and health professions. This also provides opportunities for personal reflection and development so that basic science educators will be more prepared for greater challenges and the ever-changing demands of contemporary medical and health professions education.

Tensions at the University and Living in Liminality: English Language Teachers Navigating through New Research Expectations

This study examined tensions affecting university English language teachers, and subsequently the liminal space they occupied. In this study, tensions arose because of the introduction and promotion of Scholarship of Teaching and Learning (SoTL) for conducting language pedagogical research. This move had inadvertently displaced existing research perspectives and approaches and compelled a reconfiguration of the teacher’s professional sense of self. There were four English language teachers involved in this study, all of whom were teaching different types of English courses for academic purposes in a public university in Singapore. Data for this study comprised reflections written by the participants, which were analyzed as case studies. Through the examination of tensions and liminality affecting the participants, it became apparent that distinct strategies and coping mechanisms were enacted. There were those who sought to distinguish existing research perspectives, and those who embarked on a productive journey to navigate through the new research requirement. All these constituted professional development for the participants in personalized ways. The examination of the case studies also indicated how top-down research endeavors may be challenged, especially in a field like English language education, given its long-standing and established research traditions. Yet, the circumstance which saw novel research approaches being introduced illustrate how the professional community of English language teachers in the higher education setting remain on the fringes of academia. Future studies should consider taking an ecological approach to examining tension to gain a more comprehensive understanding of English language teachers’ professional identity.

Frontiers of myopia research in the 21st century: A bibliometric analysis of the top 100 most influential articles in the field.

Myopia is the most common refractive error worldwide, contributing not only to visual impairment but also serving as a potential risk factor for various severe ocular diseases. Its impact on patients' quality of life and health is significant and imposes substantial socioeconomic burdens. In this study, we analyzed the top 100 most cited articles related to myopia published in the Web of Science Core Collection database from January 2000 to February 2024. Using data visualization tools CiteSpace, VOSviewer, and Scimago Graphica, we identified the most influential research papers and academic journals in the field of myopia. The top 100 most influential articles were published in 25 renowned journals across 30 countries, with Investigative Ophthalmology & Visual Science being the most prolific. Ophthalmology had the highest total citation frequency, while The Lancet had the highest average citation frequency. The United States and the National University of Singapore were the top countries and institutions with the most published papers. The 3 major research directions are Ophthalmology, Medicine, General & Internal, and Genetics & Heredity. The top 5 co-occurring keywords were refractive error, risk factors, prevalence, eye growth, and form-deprivation myopia. Cluster analysis results highlighted focal points such as retinal detachment, high myopia, and contrast sensitivity, indicating potential future research trends. Prospective research directions include investigating the pathogenesis of myopia, updating diagnostic technologies, and identifying risk genes for myopia and its complications.

A cross-sectional study on advance care planning documentation attitudes during national advance care planning week in a South-East Asian country

BackgroundThrough advocacy initiatives such as roadshows during “National ACP Week”, the Agency for Integrated Care (AIC) had increased advance care planning (ACP) engagement since 2011. Project Happy Apples (PHA), a community initiative project led by medical students from the National University of Singapore, also conducted a public exhibition to raise ACP awareness during this period. This study aimed to investigate and identify predictors of attitudes towards ACP documentation among ‘ACP Week’ respondents which may be used to formulate strategies to increase ACP documentation in Singapore.MethodsA cross-sectional study on ACP documentation attitudes of 262 respondents during local roadshows were conducted. Multiple logistic regression models were built to investigate the associations between demographic variables and attitudes toward ACP documentation.ResultsThe mean age was 43.5 years (SD = 17.4), 79 (30.15%) were males and 49 (18.7%) were healthcare professionals (HCP). 117 (44.66%) respondents had prior experience with serious illness and 116 (44.27%) had heard of ACP. Age was a significant predictor of readiness to sign official papers naming nominated healthcare spokesperson (NHS) (OR = 1.04, 95%CI: 1.02–1.07). Experience with serious illness was a significant predictor of readiness to discuss end-of-life (EOL) care with healthcare professionals (HCP) (OR = 3.65, 95%CI: 1.36–11.61). Being female was a significant predictor for readiness to speak to their nominated healthcare spokesperson about EOL care (OR = 7.33, 95%CI: 2.06–46.73). Subgroup analyses revealed that those aged 20–39 were less likely to speak to their healthcare professional about or sign official papers regarding EOL care. We also found that being a healthcare professional does not necessitate better or worse attitudes.ConclusionAdvocacy programs tailored to targeting respondents of different age groups and prior experience with serious illness may improve the efficacy of advocacy efforts.

Trends of machine learning for dental caries research in Southeast Asia: insights from a bibliometric analysis.

Dental caries is a common chronic oral disease, posing a serious public health issue. By analyzing large datasets, machine learning shows potential in addressing this problem. This study employs bibliometric analysis to explore emerging topics, collaborations, key authors, and research trends in Southeast Asia related to the application of machine learning in dental caries management. A comprehensive selection using the Scopus database to obtain relevant research, covering publications from inception to July 2024 was done. We employed the Bibliometric approaches, including co-authorship networks, yearly publishing trends, institutional and national partnerships, keyword co-occurrence analysis, and citation analysis, for the collected data. To explore the visualization and network analysis, we employed the tools such as VOSviewer and Bibliometrix in R package. The final bibliometric analysis included 246 papers. We found that Malaysia became the top contributor with 59 publications, followed by Indonesia (37) and Thailand (29). Malaysia had the highest Multiple Country Publications (MCP) ratio at 0.407. Top institutions including the Universiti Sains Malaysia led with 39 articles, followed by Chiang Mai University (36) and the National University of Singapore (30) became the leader. Co-authorship analysis using VOSviewer revealed six distinct clusters. A total of 1220 scholars contributed to these publications. The top 10 keywords, including 'human' and 'dental caries,' indicated research hotspots. We found growing evidence of machine learning applications to address dental caries in Southeast Asia. The bibliometric analysis highlights key authors, collaborative networks, and emerging topics, revealing research trends since 2014. This study underscores the importance of bibliometric analysis in tackling this public health issue.

Faculty’s attitudes towards inclusive education for university students with special educational needs (SENs) in Singapore

ABSTRACT This study seeks to examine faculty’s attitudes towards inclusive education for university students with special educational needs (SENs). A cross-sectional survey design was adopted. A total of 147 faculty (79 male, 53.7%) from six publicly funded universities in Singapore completed the survey, which consists of the researcher-developed Faculty Attitude toward Inclusive Education for Students with Special Educational Needs (FAISEN) scale. Results showed that faculty generally had positive attitudes towards inclusive education for university students with SENs. Faculty’s attitudes did not differ on major demographic variables, except their academic disciplines (i.e., STEM vs. non-STEM). Faculty also expressed a high level of training needs, especially on how to provide inclusive education for students with more invisible disabilities or difficulties. Faculty’s attitudes on the behavioral domain significantly and positively predicted their overall training needs. Implications for inclusive higher education, limitations, and directions for future research are also discussed.

The Effectiveness of a Digital Mental Fitness Program (Positive Intelligence) on Perceived Stress, Self-Compassion, and Ruminative Thinking of Occupational Therapy Undergraduate Students: Longitudinal Study.

Health care students often endure numerous stressors throughout their undergraduate education that can have lasting negative effects on their mental well-being. Positive Intelligence (PQ) is a digital mental fitness program designed to enhance self-mastery and help individuals reach their potential by strengthening various "mental muscles." This study aims to evaluate the effectiveness of a 6-week app-delivered PQ program in reducing perceived stress, increasing self-compassion, and decreasing rumination tendencies among health care undergraduates. We hypothesized that students would show reductions in perceived stress, increases in self-compassion, and decreases in rumination tendencies by the end of the PQ program, compared with their preprogram scores. We adopted an exploratory approach for the 5-month follow-up due to the limited research consensus on the sustained effects of app-based programs over varying periods. The PQ program includes weekly hour-long videos, weekly group meetings, and daily 15-minute app-guided practices. Participants were first-year students from the occupational therapy program at a university in Singapore. Participants completed surveys measuring self-compassion, perceived stress, and rumination levels before and after the PQ program, and again at a 5-month follow-up. Data were analyzed using repeated measures ANOVA to assess differences across the pretest, immediate posttest, and follow-up posttest. Out of 87 students enrolled in the study, the final sample consisted of 64 students (n=47, 73%, female; mean age 23 years, SD 5.06 years) with complete data. At the end of the 6 weeks, students exhibited significant increases in self-compassion (before the intervention: mean 3.07, SD 0.35; after the intervention: mean 3.34, SD 0.35; P<.001) and reductions in rumination tendencies (before the intervention: mean 3.57, SD 0.40; after the intervention: mean 3.27, SD 0.34; P<.001). However, no significant change in perceived stress levels was observed (before the intervention: 2.99, SD 0.14; after the intervention: mean 2.97, SD 0.16; P=.50). These effects were not influenced by the daily app-based practice of PQ exercises, and there were no sustained effects on self-compassion (mean 3.17, SD 0.27; P=.09) or rumination tendencies (mean 3.42, SD 0.38; P=.06) at the 5-month follow-up. Additionally, there was a significant increase in perceived stress at follow-up (mean 3.17, SD 0.21; P<.001) compared with pre- and postintervention levels. The PQ program did not directly alter stress perceptions but may have reframed students' automatic negative thought processes, increased their awareness of self-sabotaging behaviors, and enhanced their self-compassion while reducing ruminative thinking. These findings highlight the importance of self-awareness for students' well-being. Students can benefit from practices such as mindfulness and peer discussions to enhance self-compassion and reduce rumination. Educators trained in the PQ program can foster a supportive environment that encourages self-compassion, challenges negative self-talk, and helps students manage stress.

Trends of machine learning for dental caries research in Southeast Asia: insights from a bibliometric analysis

Background Dental caries is a common chronic oral disease, posing a serious public health issue. By analyzing large datasets, machine learning shows potential in addressing this problem. This study employs bibliometric analysis to explore emerging topics, collaborations, key authors, and research trends in Southeast Asia related to the application of machine learning in dental caries management. Methods A comprehensive selection using the Scopus database to obtain relevant research, covering publications from inception to July 2024 was done. We employed the Bibliometric approaches, including co-authorship networks, yearly publishing trends, institutional and national partnerships, keyword co-occurrence analysis, and citation analysis, for the collected data. To explore the visualization and network analysis, we employed the tools such as VOSviewer and Bibliometrix in R package. Results The final bibliometric analysis included 246 papers. We found that Malaysia became the top contributor with 59 publications, followed by Indonesia (37) and Thailand (29). Malaysia had the highest Multiple Country Publications (MCP) ratio at 0.407. Top institutions including the Universiti Sains Malaysia led with 39 articles, followed by Chiang Mai University (36) and the National University of Singapore (30) became the leader. Co-authorship analysis using VOSviewer revealed six distinct clusters. A total of 1220 scholars contributed to these publications. The top 10 keywords, including ‘human’ and ‘dental caries,’ indicated research hotspots. Conclusion We found growing evidence of machine learning applications to address dental caries in Southeast Asia. The bibliometric analysis highlights key authors, collaborative networks, and emerging topics, revealing research trends since 2014. This study underscores the importance of bibliometric analysis in tackling this public health issue.

Developing empathy in healthcare professions students: protocol of a mixed-methods non-controlled longitudinal intervention study.

Despite the necessary focus on clinical skills and knowledge during the tertiary education of healthcare professionals, the literature highlights the importance of developing psycho-social competencies. Empathy, a cognitive-behavioral attribute linked to various benefits for patients and healthcare professionals, is one such competency. Pedagogical approaches to successfully develop empathy in tertiary healthcare students are available. However, these approaches are often integrated piecemeal throughout the tertiary education journey. Research on a more empathy-focused curriculum is scarce. This manuscript describes the design of a study that aims to examine the effects of a more empathy-focused curriculum on empathy in tertiary healthcare profession students in Singapore. Freshmen dentistry, medicine, nursing, and pharmacy students enrolled in a novel curriculum with a strong empathy focus will be recruited for the study and followed for the program's extent. Mixed-methods data collection at various time points will be conducted. Quantitative data will be collected on cognitive-behavioral empathy, intentions to provide empathic care, and engagement in courses of the curriculum. Qualitative data on perceptions of patient care and empathy in relation to relevant courses of the curriculum will be collected to provide context for quantitative findings. Ethics approval was granted by the Departmental Ethics Review Committee of the Saw Swee Hock School of Public Health, National University of Singapore (Ethics ID: SSHSPH-214).

Digital twins for resource optimization in multi-purpose ports: A design approach for data-driven decision making

Abstract Multi-purpose ports’ ef/icient and sustainable operation relies on seamless coordination and decision-making among multiple organizations. This paper underscores the critical importance of forecasting resource and infrastructure utilization for informed operational, tactical, and strategic decision-making. The proposed approach draws on digital twin technology to enable collaborative decision-making by modeling complex port environments to enable shared situational awareness among stakeholders. Illustrated through a collaborative project involving the RISE Research Institutes of Sweden, National University of Singapore, Grieg Connect, Umeå University, Kvarken Ports Umeå, and INAB, we propose a digital twin design to empower the port as a decision-maker in multi-organizational settings to proactively plan and optimize its utilization of present and future resources.

First person – Mingkai Zhu

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Disease Models &amp; Mechanisms, helping researchers promote themselves alongside their papers. Mingkai Zhu is first author on ‘ Sex hormone receptors, calcium-binding protein and Yap1 signaling regulate sex-dependent liver cell proliferation following partial hepatectomy’, published in DMM. Mingkai conducted the research described in this article while a PhD student in Dr Dong Liu’s lab at Southern University of Science and Technology, Shenzhen, China and Dr Zhiyuan Gong's lab at National University of Singapore, Singapore. Mingkai is now a research fellow in the lab of Dr Wolfram Goessling at Massachusetts General Hospital, Boston, MA, USA, investigating regenerative medicine.

Systematic bibliometric and visualized analysis of research hotspots and trends on the application of artificial intelligence in glaucoma from 2013 to 2022.

To conduct a bibliometric analysis of research on artificial intelligence (AI) in the field of glaucoma to gain a comprehensive understanding of the current state of research and identify potential new directions for future studies. Relevant articles on the application of AI in the field of glaucoma from the Web of Science Core Collection were retrieved, covering the period from January 1, 2013, to December 31, 2022. In order to assess the contributions and co-occurrence relationships among different countries/regions, institutions, authors, and journals, CiteSpace and VOSviewer software were employed and the research hotspots and future trends within the field were identified. A total of 750 English articles published between 2013 and 2022 were collected, and the number of publications exhibited an overall increasing trend. The majority of the articles were from China, followed by the United States and India. National University of Singapore, Chinese Academy of Sciences, and Sun Yat-sen University made significant contributions to the published works. Weinreb RN and Fu HZ ranked first among authors and cited authors. American Journal of Ophthalmology is the most impactful academic journal in the field of AI application in glaucoma. The disciplinary scope of this field includes ophthalmology, computer science, mathematics, molecular biology, genetics, and other related disciplines. The clustering and identification of keyword nodes in the co-occurrence network reveal the evolving landscape of AI application in the field of glaucoma. Initially, the hot topics in this field were primarily "segmentation", "classification" and "diagnosis". However, in recent years, the focus has shifted to "deep learning", "convolutional neural network" and "artificial intelligence". With the rapid development of AI technology, scholars have shown increasing interest in its application in the field of glaucoma. Moreover, the application of AI in assisting treatment and predicting prognosis in glaucoma may become a future research hotspot. However, the reliability and interpretability of AI data remain pressing issues that require resolution.

Analysis and mapping of global research publications on migrant domestic workers

Recognizing the importance of evidence-based research in informing migration policies and empowering migrant domestic workers (MDWs), this study aims to provide a comprehensive analysis of MDW research patterns and trends. Using a descriptive cross-sectional study design, research articles on MDWs were retrieved from the Scopus database. The findings reveal a substantial increase in research output in recent years, with notable contributions from journals in the fields of social sciences and humanities. Key contributors include scholars from the United States, the United Kingdom, and institutions such as the National University of Singapore and the Chinese University of Hong Kong. Journals in the field of migration have prominent role in publishing research on MDWs. At the author level, Yeoh, B.S.A, at the National University of Singapore was the most prolific author. Academic activities were the main driver of research and that funding was suboptimal in this field. Highly cited articles focused on topics such as transnational motherhood, the international division of reproductive labor, and the negotiation of citizenship rights. Major research hotspots in the retrieved articles included mental health aspects, caregiving especially of the elderly, and struggles for legal rights. Specific nationalities, such as Filipina/o and Indonesian MDWs, have been the focus of numerous studies, shedding light on their narratives, challenges, and agency within transnational contexts. Overall, this study underscores the urgency of addressing the needs and rights of MDWs, advocate for human rights, and enhance understanding of occupational health and safety in the unique context of domestic work.

The people behind the papers - Jake Turley.

During wound healing, epithelial cells divide, migrate and change shape. However, it is unclear how much these different cell behaviours contribute to the closure of the wound. A new paper in Development applies deep learning models to analyse large imaging datasets from the Drosophila pupa and quantify the contributions of the different cell behaviours. To learn more about the story behind the paper, we caught up with first author Jake Turley. Jake was a PhD student in Bristol, UK, but is now a Research Fellow at the Mechanobiology Institute, National University of Singapore.

Self-discovery, storytelling and structuration in urban planning: pedagogical insights from Singapore

ABSTRACT This research unfolds the step-by-step pedagogical process the students of a graduate urban planning course at the National University of Singapore (NUS) recently experienced and through self-discovery and storytelling synthesized and reflected upon. This three-pronged process ultimately shows the relevancy of the structuration theory as an unintended consequence of identifying what is going on (the nature of urban problems detected), why (analysis) and how to fix them (synthesis and reflection) in selected case studies. While not part of the class experience, structuration helps show the recursive nature of these three themes, where neither agency nor the city (structure) alone accords primacy.

Reliability of ChatGPT in automated essay scoring for dental undergraduate examinations

BackgroundThis study aimed to answer the research question: How reliable is ChatGPT in automated essay scoring (AES) for oral and maxillofacial surgery (OMS) examinations for dental undergraduate students compared to human assessors?MethodsSixty-nine undergraduate dental students participated in a closed-book examination comprising two essays at the National University of Singapore. Using pre-created assessment rubrics, three assessors independently performed manual essay scoring, while one separate assessor performed AES using ChatGPT (GPT-4). Data analyses were performed using the intraclass correlation coefficient and Cronbach's α to evaluate the reliability and inter-rater agreement of the test scores among all assessors. The mean scores of manual versus automated scoring were evaluated for similarity and correlations.ResultsA strong correlation was observed for Question 1 (r = 0.752–0.848, p < 0.001) and a moderate correlation was observed between AES and all manual scorers for Question 2 (r = 0.527–0.571, p < 0.001). Intraclass correlation coefficients of 0.794–0.858 indicated excellent inter-rater agreement, and Cronbach’s α of 0.881–0.932 indicated high reliability. For Question 1, the mean AES scores were similar to those for manual scoring (p > 0.05), and there was a strong correlation between AES and manual scores (r = 0.829, p < 0.001). For Question 2, AES scores were significantly lower than manual scores (p < 0.001), and there was a moderate correlation between AES and manual scores (r = 0.599, p < 0.001).ConclusionThis study shows the potential of ChatGPT for essay marking. However, an appropriate rubric design is essential for optimal reliability. With further validation, the ChatGPT has the potential to aid students in self-assessment or large-scale marking automated processes.

How Does Artificial Intelligence Shape Audit Firms?

Does artificial intelligence (AI) displace auditors? We exploit the staggered hiring of AI employees at audit office locations across the United States as a proxy for the use of AI at local audit offices. The main findings are as follows. First, relative to audit offices that do not yet hire AI employees, those that do hire AI employees have a 4.3% increase in the number of auditor jobs, particularly among junior and midlevel auditors. Second, using AI is associated with an increased demand for soft skills (e.g., cognitive skills) in auditor jobs. Third, audit offices that use AI have more accurate going concern and internal control opinions. Semistructured interviews of 11 seasoned audit partners confirm that investment in AI is centralized at the national level, but the decision to deploy it often resides at the local audit office level. Notably, none of the partners believe that AI has replaced or will replace human auditors. Overall, our study—comprising both empirical and qualitative data—suggests that using AI does not replace auditors, but rather changes the skills required for these jobs and improves audit quality. This paper was accepted by Suraj Srinivasan, accounting. Funding: K. K. F. Law’s research is supported by the Start-Up Grant from Nanyang Technological University and the Ministry of Education (MOE), Singapore, under its Academic Research Fund Tier 1 [Grant RG128/20]. M. Shen’s research is supported by the Start-Up Grant from the National University of Singapore [Grant A-0003914-00-00] and the MOE under its Academic Research Fund Tier 1 [Grant A-8000098-00-00]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.04040 .

Examining bystander intervention for peer depression and sociodemographic correlates among university students in Singapore.

The Advancing Research To Eliminate Mental Illness Stigma (ARTEMIS) study evaluated the impact of an intervention developed and implemented in Singapore on attitudes towards depression in university students. We aimed to assess the likelihood of university students intervening when their peers suffer from depression, before and after the ARTEMIS intervention. 390 students were recruited from a university in Singapore. The ARTEMIS intervention comprised a lecture by a trained mental health professional, a sharing session by a person with lived experience of depression, and a question-and-answer segment with a panel. The Bystander Intervention Scale for Depression (BISD) was administered at baseline, post-intervention, and 3-month follow-up. BISD assessed four factors: acceptance of responsibility to intervene, knowledge on how to intervene, awareness of depression among peers, and vigilance towards possible symptoms of depression. Linear mixed models were conducted to investigate associations. Sociodemographic correlates were also examined. A favourable shift in all factors was observed at post-intervention, which weakened at 3-month follow-up. Having past experience in the mental health field (β=1.50) and older age (β=0.18) were significantly associated with knowledge on how to intervene. Having social contact with mental illness (SCMI) and past experience in the mental health field (PEMHF) were significantly associated with awareness of depression among peers (SCMI β=0.89, PEMHF β=0.43) and vigilance towards possible symptoms of depression (SCMI β=0.39, PEMHF β=0.61). The short-term results of the intervention appeared promising across all BISD factors; however, these results were not sustained after 3 months. Future research should include the impact of 'booster' interventions over time. Sociodemographic factors that were identified to be significant correlates should also be considered when planning for future interventions.

Do Investors Value Workforce Gender Diversity?

We examine whether investors value workforce gender diversity. Consistent with the view that investors believe workforce gender diversity can be valuable in major firms, we use event studies to demonstrate that U.S. technology firms and financial firms experience more positive stock price reactions when it is revealed that they have relatively higher (versus lower) workforce gender diversity numbers. For instance, we find that Google’s revelation of relatively low workforce gender diversity numbers triggered a negative stock price reaction, whereas eBay’s revelation of relatively high workforce gender diversity numbers triggered a positive stock price reaction. These stock price reactions are both economically and statistically significant; for example, we estimate that if a technology firm had revealed gender diversity numbers that were one standard deviation higher, its market valuation would have increased by $1.11 billion. Corroborating this plausibly causal field evidence, we also find positive investor reactions to workforce gender diversity in randomized experiments using Prolific participants with investing experience; these reactions seem to be underpinned by investors’ beliefs about potential upsides of diversity for the firm (e.g., reduced legal risks; increased creativity) but not by investors’ beliefs about potential downsides of diversity for the firm (e.g., increased conflict). Our findings highlight the importance of understanding investors’ intuitions or beliefs about major organizational phenomena such as workforce gender diversity. Our results also point toward a new type of business case for diversity, driven by investors: if major firms had more workforce gender diversity, investors may “reward” them with substantially higher valuations. Funding: This research is supported by NUS (National University of Singapore) Startup Grant WBS A-0003900-00-00 to D. P. Daniels.

Trends of machine learning for dental caries research in Southeast Asia: insights from a bibliometric analysis

Background Dental caries is a common chronic oral disease, posing a serious public health issue. By analyzing large datasets, machine learning shows potential in addressing this problem. This study employs bibliometric analysis to explore emerging topics, collaborations, key authors, and research trends in Southeast Asia related to the application of machine learning in dental caries management. Methods A comprehensive selection using the Scopus database to obtain relevant research, covering publications from inception to July 2024 was done. We employed the Bibliometric approaches, including co-authorship networks, yearly publishing trends, institutional and national partnerships, keyword co-occurrence analysis, and citation analysis, for the collected data. To explore the visualization and network analysis, we employed the tools such as VOSviewer and Bibliometrix in R package. Results The final bibliometric analysis included 246 papers. We found that Malaysia became the top contributor with 59 publications, followed by Indonesia (37) and Thailand (29). Malaysia had the highest Multiple Country Publications (MCP) ratio at 0.407. Top institutions including the Universiti Sains Malaysia led with 39 articles, followed by Chiang Mai University (36) and the National University of Singapore (30) became the leader. Co-authorship analysis using VOSviewer revealed six distinct clusters. A total of 1220 scholars contributed to these publications. The top 10 keywords, including ‘human’ and ‘dental caries,’ indicated research hotspots. Conclusion We found growing evidence of machine learning applications to address dental caries in Southeast Asia. The bibliometric analysis highlights key authors, collaborative networks, and emerging topics, revealing research trends since 2014. This study underscores the importance of bibliometric analysis in tackling this public health issue.