The Latest in Global Science

Leveraging Social Media as a Tool for Education

21 May 2026

NetworkingThe Latest in Global Science

Leveraging Social Media as a Tool for Education

Social media has become very normal in our day-to-day lives. It has become intuitive to many of us, especially younger generations who grew up with it. Most students in higher education are already online and consuming all kinds of (mis)information. And people are finding and sharing scientific research on social media more than ever. Today, scholars are using academic and non-academic social media as venues for public education. Additionally, they are bringing social media into their classrooms. This article explores how social media can be leveraged as a teaching tool. Taking a medium that students in higher education are already using makes the process more relevant to their lives. Social media and popular education Social media has a significant influence on the world today. Increased use of virtual platforms has seen scientific information circulating more quickly. Making academic work more transferable to a mainstream audience is important. In particular, using social media helps to further the reach and impact of scientific ideas to more mainstream audiences. The sheer amount of information posted online means it can be hard to figure out what is real or not. Providing more mainstream scientific content can reach social media users as a form of popular education. This encourages critical thinking and combats disinformation. Online platforms like SciProfiles offer a space for scholars to promote their work and build community. Some also seek to build a bigger online presence to extend the reach of their work and diversify their audience. Scholars can use their social media accounts to share their research as a forum for popular education. For instance, you could adapt slides or resources from your teaching and research program for social media. There are also drawbacks to having a public presence (privacy concerns, increased scrutiny, copyright limitations). You’re under no obligation to join any particular site(s). Pick those that best suit your needs and goals. For instance, using a more limited or invite-only platform can mean a more private and safer space. Social media as a teaching tool for the classroom In addition to your public academic presence, social media can be used in a more contained way as part of the classroom. It is a valuable tool to build skills related to research, collaboration, and critical thinking. Studies show that integrating social media into education has positive impacts on students. By using it in the curriculum, different aspects of coursework can include the use of social media. Most courses do have an online component. In these cases, students are automatically enrolled in a course-specific webpage. However, these are often limited in functionality and not necessarily user-friendly. So, a social media site might provide a more engaging space for student discussion. Accessing relevant educational content online and sharing their own ideas creates a mini community for your students. It can be a useful and fun way to meet students where they are at. Ways to incorporate social media into your course There are many different ways to include social media as part of your course. It can be time-limited and used for a certain assignment. Or, it can be used throughout the semester for general discussion. A few suggestions are included here: Create an online venue (for example, a course-specific hashtag, a specific post for discussion, or within a private Facebook group) for students to post and comment on each other’s work. Having students create their own educational content (a short video, a slide show, etc.) to share on social media. They can use research studies from coursework. This can help target different learning styles and a more lay audience. Getting students to research and engage with relevant scholars and scientific communities. This can build gaps in knowledge and help them to understand the broader academic landscape. Using SciProfiles Finally, for those working with graduate students or in a professional educational setting, SciProfiles can be the venue for this kind of education. It is members-only, free to sign up, and brings with it plenty of relevant information. SciProfiles offers a semi-private forum focused specifically on scientific research. Participants can discuss and engage with posted content as part of their coursework. Depending on your discipline and context, many of the students or group members may already have a SciProfiles account. (Or, for those who aren’t, it’s easy to register.) Leveraging social media in this way increases scientific literacy by tailoring it for different audiences. It can also enhance and expand research and teaching practices. And, in turn, this engagement empowers students to use the tools available to them in responsible ways.
Zoë GrossZoë Gross
Zoë Gross

921

Utility and Limitations of AI as Academic Tools

17 December 2025

The Latest in Global Science

Utility and Limitations of AI as Academic Tools

While AI can dramatically accelerate workflows and improve efficiency, its effectiveness depends on the quality of input and access to accurate, reliable data, supported by stringent human oversight. High-quality outputs require well-defined objectives, carefully curated datasets, and continuous validation to avoid bias or misinformation. Despite its expanding role in research, healthcare, and education, AI remains a tool—powerful, but not infallible—capable of augmenting rather than replacing human expertise. Critical thinking, ethical judgment, and academic rigor remain irreplaceable, ensuring that AI complements rather than compromises scholarly integrity. When integrated responsibly, with adherence to scholarly values and professional ethics, AI holds transformative potential, particularly for academics and healthcare professionals seeking to enhance productivity, expand knowledge, and improve decision-making. Utility of AI platforms AI-driven platforms enhance manuscript writing by refining grammar, coherence, and structure, and by identifying redundancies and logical flaws. However, relying on AI to write manuscripts is poor practice; instead, authors should use it to support and refine their work. Integrated citation tools also streamline referencing and cross-verification, saving time and improving academic precision. AI as augmenter, not replacer AI excels in pattern recognition and test selection, enabling rapid analysis of vast, complex datasets to identify trends and guide diagnostic reasoning. However, AI lacks empathy, moral judgment, and clinical intuition—virtues essential to patient-centered care. A recent study reported that while GPT-4 alone demonstrated significantly higher diagnostic accuracy than clinicians using conventional tools, physicians who were assisted by GPT-4 performed no better than those relying solely on traditional resources. This finding underscores a critical barrier: without proper training and integration into workflows, AI’s strengths may not translate effectively into improved outcomes. To harness its full potential, AI must be introduced as a supplement to, not a replacement for, human expertise—preserving the indispensable judgment and relational nuances that clinicians bring to healing. Using AI in academia AI offers tremendous potential in healthcare research, serving as a powerful ally in bridging theoretical knowledge with real-world clinical application. It enhances diagnostics, improves precision in treatment planning, and accelerates the pace of discovery by sifting through complex datasets far more rapidly than humans can. AI-driven insights—from predicting recovery outcomes to optimizing investigation pathways—can transform patient care when wielded thoughtfully. However, this technological promise comes with critical caveats. The surge in AI-powered tools—from literature-review systems to diagnostic algorithms—demands rigorous oversight and methodological soundness. As the literature emphasizes, AI should augment, not replace, human expertise. Ethical concerns such as bias, lack of transparency, and hallucinated outputs highlight the necessity for researchers and practitioners to approach AI with both enthusiasm and caution. By marrying AI capabilities with critical human judgement, the medical and academic communities can harness its benefits responsibly—to improve outcomes, foster innovation, and uphold integrity. Limitations and responsibilities of AI use Despite these advantages, AI is not a panacea. Its outputs are entirely dependent on the quality of input data, model training, and prompt specificity. As with computers, often it is summarized by the adage: “garbage in, garbage out”—the integrity and usefulness of AI-generated content hinge predominantly on human oversight. Without critical engagement, there is a risk of reinforcing bias, misinterpretation, or spreading misinformation. Researchers and academics must therefore remain actively involved in evaluating AI outputs, applying domain expertise, and ensuring alignment with ethical standards. AI should be seen as a co-pilot—not an autopilot—for research. Generative AI for optimizing healthcare and reducing costs Generative AI and advanced analytics transform healthcare by tackling rising costs, inefficiencies, fragmented data, polypharmacy, and inconsistent outcomes. Predictive analytics, real-time monitoring, and automated decision support enable earlier diagnoses, optimized treatments, and fewer unnecessary interventions, yielding savings and improved outcomes. This shift replaces reactive care with proactive, personalized, data-driven precision. Technology will strengthen decision-making and empower care teams to act faster using evidence-based insights, while patients receive focused, coordinated care. Policy reforms should advance preventive care by promoting health education, ensuring access to disease prevention resources, affordable, nutritious foods, consistent physical activity, and routine screenings. Implementing these measures should substantially reduce costs. Strategic investments in AI-driven technologies, machine learning analytics, and shifting care from hospitals to community-based programs will improve population health, expand access, cut costs, and build a resilient, future-ready healthcare infrastructure. Within five years, integrating cybernetic systems with generative AI could transform delivery, diagnostics, treatments, and follow-up care at far lower cost. This integration will enable real-time monitoring, predictive analytics, and early detection of health issues, facilitating timely interventions and personalized care that prevent disease progression and improve long-term outcomes. Ethical and epistemological boundaries AI cannot replicate the intellectual depth, moral reasoning, or contextual understanding that define rigorous scholarship. Critical thinking, creativity, and ethical judgment remain irreplaceably human qualities. AI lacks the capacity for intuition, empathy, and the kind of deep domain knowledge that emerges from years of focused study and experience. Academic institutions and publishers must also address ethical concerns around plagiarism, authorship, data privacy, and algorithmic transparency. Establishing guidelines for responsible AI use in academia is essential to ensure trustworthiness and academic integrity. Embracing AI as a complementary tool Academics must approach AI with both curiosity, enthusiasm, and caution—embracing it as a tool to augment their intellectual endeavors, not replace them. When used responsibly, AI can significantly enhance the efficiency, precision, and depth of scholarly output in a short time. Researchers who learn to use AI tools effectively and recognize their limits from the beginning can produce more impactful, high-quality work that benefits science and society. AI can be used effectively for Pattern Recognition – Detecting trends in symptoms, diagnostics, and outcomes, Medical Imaging – Enhancing accuracy in X-rays, MRIs, and CT scans, Virtual Assistance – Supporting clinicians and patients with real-time guidance, and Patient Data Analysis – Streamlining records, predicting risks, and personalizing care. Synergy between human and machine intelligence The future of academic inquiry lies in a synergistic relationship between human intellect and machine intelligence. AI’s potential to accelerate research is enormous—but it must be guided by scholarly discipline, ethical reflection, and human oversight. By integrating AI thoughtfully and strategically into the academic process, we can expand the frontiers of knowledge while preserving the rigor and values that define scholarship. AI technologies are transforming how researchers conduct, analyze, and present academic work. Tools like generative AI enhance productivity by automating literature reviews, improving manuscript quality, and revealing novel connections across disciplines. However, their utility depends on thoughtful, ethical, and skilled use by researchers. AI cannot replicate human intellect, contextual understanding, or moral reasoning. For meaningful and credible outcomes, academics must apply AI critically and judiciously. The future of scholarship and advances lies in synergizing AI’s computational power with human creativity and wisdom—elevating both the quality and impact of academic research for the greater good. Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Sunil J. WimalawansaSunil J. Wimalawansa
Sunil J. Wimalawansa

2944

Harnessing AI for Academic Research and Scholarly Writing: Emerging Tools and Trends

16 December 2025

The Latest in Global Science

Harnessing AI for Academic Research and Scholarly Writing: Emerging Tools and Trends

Artificial Intelligence (AI) is revolutionizing academic research and essential scholarly writing. It helps to streamline key tasks across the research cycle. This process includes literature review and data analysis, writing, and citation management. Generative AI, in particular, enables cross-disciplinary exploration and the rapid synthesis of vast knowledge bases, enhancing hypothesis generation and trend identification. AI’s transformative role in academia Artificial Intelligence (AI) is transforming academic research and scholarly writing by significantly amplifying the quality, speed, and breadth of intellectual exploration. Rather than simply surfing the internet and using AI-generated text as a shortcut for transcription, or being dependent on AI for primary writings, researchers should develop his/her drafts and engage deliberately and critically with AI. AI-generated content can include errors, outdated information, or biases, so it is vital to corroborate its outputs against trusted sources, research archives, and maintain vigilance in interpretation. At every stage of the research process—whether it is crafting hypotheses, reviewing literature, conducting statistical and data analyses, or drafting manuscripts—AI is becoming an indispensable tool. When used judiciously with common sense, it can streamline workflows, surface novel insights, and elevate the precision of scholarly output. However, its effectiveness rests on the researcher’s ability to blend AI’s capabilities with sound methodology, rigorous fact-checking, and editorial judgment. People should form concepts and hypotheses, while AI assists in research. Academic researchers across disciplines are beginning to recognize that integrating AI into the research cycle can yield more profound insights, foster innovation, and reduce workload—when used thoughtfully. Supporting the research lifecycle AI technologies now help at virtually every stage of the process, irrespective of the type of research. Natural language processing (NLP) algorithms and large language models, or LLMs (like ChatGPT and Copilot), can help researchers to formulate more meaningful research questions, refine arguments, and organize thoughts. Tools like semantic search engines, citation managers, and content summarizers help streamline literature reviews by rapidly identifying relevant publications, extracting key themes, and organizing references. These are becoming more advanced. Accelerating interdisciplinary discovery Generative AI supports interdisciplinary exploration by scanning massive repositories of scholarly literature and revealing patterns, relationships, and knowledge gaps that might otherwise go unnoticed. These tools can generate new research questions or hypotheses by connecting seemingly unrelated domains. For example, AI can suggest how a method in computational linguistics might be applied to biological data analysis or link behavioral economics to environmental policy. Interdisciplinary collaborations One of the most profound impacts of AI is its facilitation of interdisciplinary collaboration. By swiftly processing and synthesizing information from disparate fields, AI enables scholars to uncover novel connections and propose innovative solutions to complex questions. This technology empowers teams to break down traditional academic silos, fostering dialogue between disciplines such as medicine, engineering, social sciences, and the humanities. Computational tools can discern emerging trends and knowledge gaps, helping researchers focus their efforts more strategically and encouraging fresh perspectives. Enhancing academic writing and communication AI-based writing assistants improve the clarity, tone, and technical quality of academic writing. These tools provide feedback on sentence structure, eliminate verbosity, improve readability, and ensure consistent formatting. For non-native English speakers, AI offers real-time language translation and grammatical correction, making academic publishing more inclusive and globally accessible. Besides, AI also supports visual communication by generating graphs, data visualizations, and graphical abstracts, allowing researchers to communicate findings more effectively. AI developments in medicine AI already demonstrates superior diagnostic power in complex, image-driven cases and delivers faster, more cost-effective diagnostics. Shortly, the combination of AI and physicians—when workflows are optimized—can yield the best outcomes, with AI supporting rapid triage and test selection. At the same time, doctors serve as validators, communicators, and caregivers. The physician’s evolving role will be to integrate AI insights with human nuance, ensuring that technology enhances rather than replaces clinical judgment. Current barriers include workflow integration, trust, and regulatory challenges, while the future demands improved user experience, targeted training, rigorous clinical trials, and robust ethical oversight. Capabilities of AI to transform academic and healthcare AI’s capacity to integrate and analyze large-scale data offers a transformative opportunity for uncovering patterns and connections that remain hidden in vast datasets. By concurrently querying multiple databases, AI dramatically reduces the time needed to extract pertinent information—soaring beyond the limitations of manual review. This expedited access not only accelerates the pace of discovery but also enables dynamic, data-driven hypothesis testing across fields, highlighting the importance of methodological rigor at every stage of research. Moreover, AI tools are increasingly indispensable in conducting meta-analyses, systematic reviews, and evidence mapping—cornerstones of evidence-based research. For instance, AI systems like “Elicit” can assist with repeatable and reliable systematic reviews, while platforms such as “Paperguide” automate key workflows from search to statistical synthesis. “Elicit” is an AI research assistant that helps users find relevant academic papers, generate literature reviews, and structure research questions using natural language queries. “Paperguide” streamlines the writing process by offering AI-powered support for manuscript organization, clarity improvements, and journal-specific formatting guidance. AI tools like these would make the content more tangible and helpful for a researcher, but writers should not depend on them. Emerging innovations—like explainable AI frameworks that adhere to PRISMA guidelines—offer even faster, transparent review processes, shrinking timelines from months to days. These advancements not only foster innovation but also elevate collaboration, enabling researchers to pivot from information gathering to analysis and insight generation with unprecedented efficiency. AI developments in patient care AI already demonstrates superior diagnostic power in complex, data and image-driven cases and delivers faster, more cost-effective diagnostics. Shortly, the combination of AI and physicians—when workflows are optimized—can yield the best outcomes, with AI supporting rapid triage, compiling and summarizing patients’ electronic medical records, as well as the selection (prompt) of the most optimal and cost-effective investigations. At the same time, doctors serve as validators, communicators, and caregivers. The physician’s evolving role will be to integrate AI insights with human nuance, ensuring that technology enhances rather than replaces clinical judgment. Current barriers include workflow integration, trust, and regulatory challenges, while the future demands improved user experience, targeted training, rigorous clinical trials, and robust ethical oversight. Potentials of AI in healthcare AI holds transformative promises in healthcare by effectively bridging theoretical knowledge and clinical practice. When applied judiciously, it elevates understanding from foundational principles to advanced applications in patient care. AI-driven tools can inspire innovation, sharpen diagnostics, forecast recovery paths, guide cost-effective investigations, and optimize treatment plans. However, it is essential not to lose sight of the trajectory of findings and data—and to apply common sense when interpreting conclusions. Presently, the application of this prudent, contextual judgment remains noticeably lacking. When applied wisely, it enhances understanding from foundational principles to advanced clinical applications. AI can drive innovation, improve diagnostics, predict recovery paths, guide cost-effective investigations, and optimize treatment strategies. However, one should not lose the path of common sense in validating and understanding data, and apply commensurate judgment in interpretations and conclusions. To realize AI’s full potential, academics and healthcare professionals must approach its adoption with open-mindedness, holistic perspectives, and a sense of responsibility. Only by pairing technological capability with sound methodology and critical oversight can AI meaningfully enhance medicine rather than merely augmenting its pitfalls. AI can greatly enhance research and collaboration, but its impact relies on human guidance, rigorous methodology, and critical judgment. In the next blog, we will discuss the limitations and responsibilities of using AI. Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Sunil J. WimalawansaSunil J. Wimalawansa
Sunil J. Wimalawansa

3241

Why Traditional Publishing Continues to Flourish

13 November 2025

The Latest in Global Science

Why Traditional Publishing Continues to Flourish

A consistent record of academic publishing is a crucial part of being a successful scholar. In order to accomplish this, authors can be strategic and take into consideration the best publishing model to pursue. Traditional academic publishing continues to flourish even as options are expanded. In order to help you make an informed decision, this article will explore the continued success of the traditional publishing process. It will consider: What is traditional publishing exactly? Why do scholars continue to choose traditional models for their work? We will also explain how traditional publishing offers both advantages and disadvantages versus open access academic publishing. What is traditional publishing? The academic publishing landscape has been significantly altered by cultural shifts towards inclusivity, diversity, and accessibility. This has resulted in widespread adoption of open access publishing as part of the broader open science movement. Even though the advent of open access models, the traditional publishing process continues to flourish. This model involves a closed access subscription publishing-based model of peer-reviewed academic work. An important aspect of traditional publishing is that readers do not pay a fee. The responsibility for paying to access paywalled research falls to the individual or their affiliated institution. In general, the traditional publishing process is made up of several different steps. These include doing research, preparing a manuscript, submission to a journal, peer review, revisions, copy edits, and final publication. Journals using this model produce high-quality publications through a lengthy and rigorous process. Advantages of traditional publishing Now that we have a sense of what traditional publishing is, what are the key benefits of choosing this model? Getting your academic work published requires consistent work, dedication, and patience. What and where you publish can have a significant impact on your career advancement. There are different aspects of the traditional publishing model that are discipline- or journal-specific. But a few key factors keep traditional publishing as a top choice for scholars. Historically, traditional publications have been more likely to be highly ranked, have a high impact factor, and have a strong reputation. Many of the most well-regarded and prestigious journals in the relevant field(s) publish under traditional models. This is in large part due to these journals maintaining the highest ethical standards and quality control practices. Rigorous peer review and an established readership and wide reach for their publications are also key. In addition, subscription publishing journals do not require authors to pay an article processing charge (APC) to publish. This means that scholars don’t have to be funded or pay out of pocket in order to have a chance to share their work. Limitations of traditional publishing While there are many advantages to the traditional publishing process, there are also some disadvantages to consider. One disadvantage is that this process typically follows a much longer timeline than open access publishing. Rather than taking months, it can take years to move through peer review and revisions to final publication and distribution. An important limitation that remains is the financial barriers associated with a subscription publishing-based system. This is because, while subscription publishing doesn’t charge authors to publish, they do charge for access. For those affiliated with an institution that covers the subscription cost, being able to read and share academic work is easy. But paying for each article individually from journals can quickly become very costly, and is completely prohibitive for many. Economic status and institutional affiliation (or lack thereof) limit who can actually access, use, and share scientific research. This has significant consequences globally, with various marginalized communities unable to fully participate in academic discourse. This only widens the research and publication gaps due to a lack of community-driven programs. The academic publishing landscape has been significantly altered by cultural shifts towards inclusivity, diversity, and accessibility. This has resulted in widespread adoption of open access publishing as part of the broader open science movement. Balancing your publishing program Both traditional and open access models offer advantages to authors, readers, and academia more broadly. As you do your research, keep in mind things like high impact factor, reputation, accessibility and reach, and readership. There may be times when certain advantages or disadvantages matter more than others. For example, if you are doing research that is particularly timely or cutting-edge, you may want to try to publish as quickly and widely as possible. In this instance, publishing open access may be the best option to disseminate your research findings within academia and to the public. At other times, as scholars are looking toward tenure or promotion opportunities, pursuing academic publication with a subscription publishing-based journal, particularly one with a high impact factor and a notable reputation in your field, may be a better option. As the academic publishing world continues to open up, there are plenty of options to pursue for publication. If you keep working hard and demonstrating your commitment to the work, you can build a strong and impactful publishing portfolio. Last updated on: July 25, 2026
Zoë GrossZoë Gross
Zoë Gross

1261

Boosting Research Visibility with Academic Video Abstracts

25 September 2025

The Latest in Global Science

Boosting Research Visibility with Academic Video Abstracts

Academic spaces are a place of constant evolution, and one such evolution was the creation of video abstracts. A relatively new part of academic publishing, here we’ll address what a video abstract is and why you’d want one for your research. What is a video abstract? As scholarly communication moves toward digital, open access, and multimedia formats, traditional text-based dissemination is being complemented by more dynamic and accessible methods. A video abstract is a concise, visually engaging multimedia presentation that summarizes the core findings of a scholarly article. By combining narration with visuals such as animations, infographics, real-world footage, or data visualizations, it makes complex research easier to understand for both academic and non-specialist audiences. Video abstracts are often shared through multiple channels, including academic publishers’ platforms (e.g., MDPI, Elsevier, Springer Nature), where they appear alongside the original article, as well as open access repositories, academic networks like ResearchGate, video platforms such as YouTube, and social media channels including LinkedIn and X. Read the paper that this video abstract is based on here Why create a video abstract? In the evolving landscape of scholarly communication, video abstracts are becoming an essential tool for increasing research visibility, enhancing impact, and improving discoverability in a competitive research environment. Enhancing views Research consistently shows that video abstracts can significantly improve visibility. A 2014 study in the Journal of Librarianship and Scholarly Communication found that although only 5% of articles included a video abstract, 25–30% of the most-read articles featured one. More recently, a 2023 Scientometrics study reported a 35% increase in article views for papers with video abstracts, even after controlling for other factors. Boosting citations Research indicates that video abstracts can significantly increase citation rates. A 2009 study published in Scientometrics found that articles accompanied by video abstracts received 20% more citations than those without. This statistically significant increase highlights the role of video abstracts in enhancing a work’s academic reach. Amplifying altmetrics scores Video abstracts can also enhance attention beyond scholarly circles. The Scientometrics study showed that articles with video abstracts have been shown to achieve a 25% higher Altmetric Attention Score (AAS), a metric that reflects attention across X , blogs, news outlets, and other digital media. A well-produced video abstract can: Demonstrate experiments or fieldwork visually Clarify theoretical concepts with illustrations or examples Present tools, equipment, or datasets used in the study Highlight simulations or animations that reinforce findings Engage audiences in a more informal and memorable way Therefore, video abstracts support scholars when used in academic presentations, lectures, and instructional settings. In an era where research is increasingly evaluated by both scholarly impact and public relevance, video abstracts offer a compelling tool to bridge the gap between academia and broader societal engagement. Which publishers encourage video abstracts? Publishers encourage researchers to create and share video abstracts by offering comprehensive support and showcasing their measurable impact. Some publishers integrate video abstract submission options into manuscript submission systems, provide detailed guidelines and templates, and occasionally collaborate with third-party platforms to assist with production. Most leading academic publishers now support or encourage the use of video abstracts as part of their publishing strategy, recognizing their value in enhancing research visibility and engagement. Publishers such as MDPI, Elsevier, Wiley, ACS Publications, Cell Press, Taylor & Francis, and IOP Science offer dedicated platforms or guidelines for submitting video content alongside written articles. The video abstract “How Do Sex Hormones Control Behavior?” has received over 1.9 million views on YouTube, and the related article has been cited more than 290 times, reflecting both its broad public impact and substantial academic influence. How to produce a good video abstract A video abstract is a short, engaging video summary that condenses key elements of a study. Keep It Brief: Aim for under 5 minutes. Focus on the research question, methodology, key findings, and implications. Write a Clear and Engaging Script: Ensure clarity and accessibility. Avoid jargon, keeping the language simple and engaging for a broad audience. Use Visuals: Use professional video editing software and animation tools to present charts, graphs, and animations that simplify complex data and highlight key points. Ensure Quality Audio and Video: Record in a quiet environment with a good microphone. Proper lighting enhances professionalism. Adopt a Conversational Tone: Speak naturally to engage viewers, avoiding reading directly from the script. However, creating video abstracts remains a significant challenge for most researchers. As such, many are turning to commercial services for assistance. Some video services offer one-stop solutions, helping researchers produce polished video abstracts. Sample video abstract Flavonoid-Based Nanoparticles for Osteoarthritis and Rheumatoid Arthritis This review has shed light on the potential of flavonoids and flavonoid-based nanoparticles as promising avenues for the management of osteoarthritis and rheumatoid arthritis. The video abstract was produced by MDPI’s Encyclopedia Academic Video Service. It has helped broaden its reach, garnering significant attention with 24 academic citations, 5.8k article views, and 3.4k video views. MDPI Academic Video Service The MDPI Academic Video Service is dedicated to helping researchers communicate their work through engaging visual media. The services was officially launched in April 2025. It offers comprehensive support, including one-on-one video assistance, scriptwriting and editing. Not only that, but also high-quality animations, voice actor or AI voiceovers, multiple revision rounds, custom infographics, and social media promotion. This service includes the production of Video Abstracts, Short Takes, and Scholar Interviews. These are designed to complement traditional academic publications and enhance the reach of research. Encyclopedia has collaborated with more than 40 SCI-indexed journals. Nutrients, Foods, Sustainability, Cancers, Entropy, Remote Sensing, Nanomaterials, Animals, and Encyclopediaare some examples. These collaborations aim to support the dissemination of research findings, facilitate viewer engagement, and contribute to broader scholarly communication efforts. For more information about video abstracts or assistance with video production, feel free to contact office@encyclopedia.pub.
SciProfiles OfficialSciProfiles Official
SciProfiles Official

1878

AI in My Research: Practical Lessons Every Academic Should Know

29 August 2025

The Latest in Global Science

AI in My Research: Practical Lessons Every Academic Should Know

Enhancing Efficiency Without Replacing Expertise Here, I share practical lessons from my research, where Artificial Intelligence (AI) has become an essential productivity tool. AI enhances efficiency, improves data-driven decision-making, and simplifies the management of complex technical workflows. In research areas like energy systems, hydrogen economy, and decarbonization, AI has become indispensable in supporting design optimization, techno-economic assessments, and policy-related studies. The Growing Role of AI in Technical Research Research demands in engineering and sustainability are increasing. The volume of data, the complexity of multidisciplinary systems, and the expectation for actionable and impactful results make it clear that traditional methods, while foundational, require intelligent support. AI has emerged as a practical solution to address these demands by assisting researchers in managing large datasets, improving analytical workflows, and enhancing research efficiency. To me, it feels like AI is no longer a luxury or an optional add-on. For researchers working in technical fields, it is becoming an essential tool that supports rigorous analysis and process optimization. AI allows people to focus on high-level problem-solving while automating data-heavy and repetitive processes. AI as a Technical Enabler in Modeling, Design, and Analysis In my research, AI functions as a supportive tool that enhances technical workflows, particularly in design optimization, data management, and analytical assessments. In a recent carbon capture project, an AI-driven data generation framework boosted the accuracy of solvent screening for rotating packed beds from 40% to over 92%, reducing the time and cost needed to identify optimal candidates and accelerating deployment of advanced CO₂ capture systems. However, the core scientific thinking, critical analysis, and decision-making remain entirely driven by human expertise. AI assists in improving efficiency, but intellectual leadership and scientific rigor always come from the researcher. Optimizing Design Configurations and Scenario Assessments Design optimization tasks often involve multiple design variables, complex trade-offs, and scenario evaluations. AI supports these workflows by organizing variable sets and assisting in identifying efficient configurations within defined technical boundaries. For example, in one liquefied natural gas (LNG) study, an AI-based surrogate model paired with advanced optimization algorithms cut the computational time of process design by over 90 percent, while maintaining near-perfect accuracy in predicting energy use. This approach not only sped up decision-making but also revealed operating conditions that could meaningfully lower greenhouse gas emissions. AI helps in managing optimization parameters and providing structured comparisons of alternative configurations. However, the final selection of the optimal design, assessment of trade-offs, and alignment with project objectives are determined through in-depth analysis by the researcher. Enhancing Data Handling and Techno-Economic Evaluations Techno-economic studies demand managing extensive technical and economic data, modeling various policy scenarios, and evaluating the financial viability of technologies. AI assists in organizing datasets, automating trend analysis, and visualizing results for better clarity. In my research, AI-driven analytics streamline the handling of complex datasets, helping structure the evaluation process more efficiently. However, the interpretation of economic impacts, policy implications, and formulation of strategic conclusions is a process that depends entirely on the researcher’s expertise and critical assessment. Streamlining Documentation and Review Processes Research documentation, reporting, and preparation of policy briefs require meticulous attention to detail. AI tools assist in managing references, ensuring formatting consistency, and organizing large documents efficiently. These tools help reduce the time spent on routine documentation tasks, allowing me to dedicate more focus to in-depth content development and technical analysis. However, the creation of research content, the development of arguments, and the final quality review remain the responsibility of the researcher. Supporting Communication and Ethical Compliance Communicating research findings effectively, whether in academic publications, policy discussions, or industry engagements, requires clarity, accuracy, and contextual understanding. AI tools support by organizing supporting materials, managing citations, and preparing visual summaries. However, crafting the message, ensuring factual precision, and maintaining ethical standards in communication are tasks that require human oversight and intellectual responsibility. AI organizes information, but the integrity and depth of communication are led by the researcher. Key Lessons and Guidance for Researchers AI enhances workflow efficiency in data handling, optimization processes, and analytical documentation, but does not influence the intellectual direction of research. The researcher’s expertise, critical thinking, and domain knowledge are central to every decision-making and analysis process. AI assists in managing technical tasks, allowing researchers to focus on addressing complex challenges and delivering meaningful research outcomes. How to maximize benefits To maximize the benefits of AI while maintaining academic rigor and scientific leadership, researchers should consider the following practical guidelines: Apply AI tools to streamline data-heavy workflows, such as managing datasets and organizing scenario comparisons. Use AI to assist in optimizing workflow efficiency, but retain full ownership of analysis and conclusions. Collaborate with AI experts to adapt tools effectively for specific research applications. Engage in interdisciplinary collaborations where AI applications intersect with engineering, data science, and policy research to develop comprehensive, real-world solutions to complex energy and sustainability challenges. Maintain a clear distinction between AI-assisted processes and core research activities that require human expertise. Continuously evaluate AI’s role as a productivity enhancer, ensuring that academic rigor and research integrity are never compromised. Stay informed about advancements in AI methodologies relevant to your research domain to leverage emerging tools that can further enhance analytical efficiency. Document AI-assisted methodologies in your research publications to demonstrate transparency, reproducibility, and the thoughtful integration of AI into technical workflows. The Future of AI in Research Excellence AI will continue to play an important role in improving research workflows, especially in technical disciplines that involve complex data structures, design optimization, and techno-economic evaluations. It will enhance research capacity and streamline analytical processes. However, AI will not replace the human expertise and scientific judgment necessary for high-quality research. Institutions that integrate AI strategically will benefit from improved efficiency, but the leadership in innovation and research excellence will always remain with the researchers. Conclusion It is important to recognize that AI cannot replace researchers and scientists. The formulation of research ideas, critical evaluations, analytical reasoning, and strategic conclusions will always require human intellect, domain expertise, and scientific judgment. AI assists in improving workflows, but it does not possess the creativity, contextual understanding, or scientific rigor needed to drive research innovation. AI is a powerful productivity tool, but it is the researcher who defines the direction, ensures the quality, and leads the journey from data to impactful outcomes. By embracing AI with a clear understanding of its role as a supportive enabler, researchers can amplify their capabilities, enhance their efficiency, and maintain the integrity and depth that define academic and scientific excellence. Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Muhammad Abdul QyyumMuhammad Abdul Qyyum
Muhammad Abdul Qyyum

2754

What is Open Access Publishing?

10 July 2025

The Latest in Global Science

What is Open Access Publishing?

Scholars have more options than ever when it comes to how they would like to publish their work, open access publishing is one of those options. In addition this, traditional publishing models exist. The growth of open access academic publishing, however, has become widely accepted across disciplines globally. Here we explain what open access publishing is and how it differs from traditional publishing models. The advantages and disadvantages of each are considered. It will also provide an overview of how OA benefits the work of scholars and academia more broadly. What is open access publishing? Over the past 25 years, open access (OA) publishing has been consistently growing, accelerating scientific communication and knowledge dissemination. OA makes scientific research more accessible to a wider readership by being published in online journals that are free to access. Open access, under the broader open science movement, aims to reduce financial or other barriers to publishing, reading, and reusing emerging research. The more author- and reader-friendly copyright and licensing regulations enable scholars to more easily share and use each other’s work. One of the most significant differences between the two models is the use of article processing charges (APCs). This requires authors, or their institution, to cover the cost of each publication. This replaces the paywall that exists with subscription-based journals. Open access versus traditional publishing So, why publish open access? How does open access compare to traditional publishing models? A big part of why OA publications are easier to access and distribute is that they are all published online. The acceleration of scholarly communications has helped to streamline various aspects of the publication process, including peer review and timelines to release. Historically, subscription-based journals put out hard copies, which by nature are more difficult to disseminate on a practical level. Many of these journals continue to produce printed copies, which are often in addition to the paywalled online version. Key factors to consider A good strategy for scholars is to pursue both open access and traditional subscription-based publications, depending on the specific context and situation. In order to make the best decision, there are various factors to keep in mind: Cost to publish Open access research is published with a required article processing charge (APC). Either the author or a sponsoring institution can pay the fee. Publication timeline The traditional publishing process has markedly longer timelines than open access academic publishing. Each journal has its own regulations, but, in general, OA takes weeks or months to publish, rather than the often years-long process of traditional publishing. Availability, sharing, and reuse Most open access journals aim to publish articles as quickly and widely as they can. In most cases, finalized papers are freely available to share and reuse upon publication. Authors can also post a preprint on an online repository before this, and then update it to the new version. Licensing and copyright Under most OA models, authors retain the copyright and licensing rights. If restrictions do exist, they are usually temporary or removed under an open license copyright. Types of OA The aim of open access academic publishing is to make publications as freely and easily accessible as possible to as many people as possible. The open science movement As you move through different parts of your career, certain forms of publishing might offer more benefits than others. This might include pursuing various forms of OA in line with your personal and professional goals. The types of open access are represented through a coded system, as briefly explored below. Gold Currently, gold OA is the standard for a lot of academic open access journals, including across MDPI’s catalogue of hundreds of publications. Under this model, an APC is paid, and the author retains full copyright over their work. Once the published article is released by the journal, it is immediately and permanently available to be used and reused for free. Green Scholars can upload their own work on an online depository with green OA, known as self-archiving. Authors can upload a preprint version of their work for the use of readers before updating it with the finalized peer-reviewed publication. The finalized publication is not made available right away, and the copyright is retained by the publisher. Hybrid This type offers a mixture of open and closed access. Some journal articles are available to those with a subscription, and some are made open access if an APC has been paid by the author or affiliated institution. Diamond or platinum Articles under this model are typically published fully OA, without requiring the author or the reader to pay a fee. This open access research is typically made possible by external funding from public or private institutions. Bronze These articles are not typically available for reuse, but they are free to read on the publisher’s official page. Black This includes making available unauthorized digital copies of closed access literature. This often involves the uploading and sharing of PDF versions of paywalled research. Gratis This type includes free online access to read, but not reuse, scientific research papers. Libre With this model, readers have free online access to read academic work, with some reuse rights. Ultimately, open access academic publishing has helped scholars to increase the reach and impact of their work. The opening up of academic research to more authors and readers has diversified engagement with scientific conversations. This continues to create more possibilities for collaborative and community-driven knowledge, which further the principles of open science. Last updated on: July 25, 2026
Zoë GrossZoë Gross
Zoë Gross

2153

Embracing AI in Research: Opportunities, Ethics, and Evolving Practice

14 April 2025

The Latest in Global Science

Embracing AI in Research: Opportunities, Ethics, and Evolving Practice

Artificial Intelligence (AI) is quickly changing the research landscape—changing how we generate and process data, collaborate, and envision the future of academic practice. The rise of generative AI tools such as ChatGPT, Bard, and Claude has opened new possibilities for literature synthesis, hypothesis generation, academic brainstorming, research summarization, and educational support. These tools assist researchers in navigating complex content, structuring arguments, and exploring novel ideas in the early stages of research development. Complementing these are AI-powered research discovery platforms like Research Rabbit, Connected Papers, and Litmaps, which facilitate dynamic literature mapping, enabling users to visualize scholarly networks and uncover relevant studies more intuitively. As a researcher in digital health and rehabilitation technologies, I’ve seen firsthand how these innovations can act as catalysts for academic inquiry—while also raising critical questions about ethics, integrity, and the responsible use of AI in research. From tool to thought partner AI tools today go far beyond automation. Natural Language Processing models like ChatGPT can assist with summarizing the literature, organizing arguments, refining writing, and even sparking new research ideas. For early-career researchers, these capabilities offer valuable support during the most time-intensive stages of academic work. In a recent crossover randomized controlled trial, published in 2024, my colleagues and I examined the usability and effectiveness of ChatGPT among health sciences students, particularly in chronic disease education. Students valued the tool’s accessibility and responsiveness, especially for tasks like initial drafting and exploring alternative phrasing. However, our findings also reinforced a key message for those just beginning their research careers: AI can complement, but not replace, critical thinking, academic judgment, or complex subject knowledge. Although it can streamline tasks and provide structure, the researcher’s comprehension and context give academic work depth and originality. For those navigating how to use AI thoughtfully in research, I have published a set of practical tips on the ethical and responsible use of AI, including in the Guidelines for Equitable Use of Artificial Intelligence developed as part of our protocol study on ChatGPT in health sciences education (Veras et al., 2023). These suggestions are intended to support, not substitute, the curiosity, creativity, and critical rigour that define strong academic practice. Ethics, bias, and digital equity As researchers begin integrating AI into their academic work, thinking beyond efficiency and convenience is essential. AI is powerful, but it’s not neutral. The outputs we get are only as good as the data and design behind our tools. That means it’s up to us to stay curious, critical, and intentional in applying them. One of the most important habits to develop is learning to question and validate AI-generated content. Whether you’re using an AI tool to draft a summary, brainstorm research questions, or format citations, always ask: Where did this information come from? Is it accurate? Whose perspective might be missing? At the same time, AI can potentially support more significant equity in research. AI tools can be a valuable resource for researchers without access to paid reference managers. For example, ChatGPT and similar models can help generate and format citations in APA, MLA, or Chicago style. This offers a solution for meeting journal requirements when conventional reference tools are unavailable. How is it useful? This is particularly useful for those working in low- and middle-income countries (LMICs) or institutions with limited resources. AI-powered platforms such as Connected Papers, Research Rabbit, and Litmaps help researchers discover and visualize related work without needing costly subscriptions. Similarly, AI translation tools make it easier to engage with global research, expand access to the non-English literature, and contribute to international scholarly conversations. Still, the promise of AI depends on how it is used. Tools must be applied thoughtfully, with attention to diverse data sources, inclusive perspectives, and ethical standards. AI should amplify researchers’ voices, not erase them. It should be a means to bridge knowledge gaps, not widen them. AI won’t solve every problem for researchers navigating structural barriers. Be it limited infrastructure, funding, or mentorship, when used responsibly, it can help reduce inequities, broaden access, and empower more people to participate fully in academic life. Supporting, not replacing, academic practice For researchers, AI offers both opportunity and complexity. AI can enhance academic work, but ultimately, our values, methods, and critical reflections define its impact. While AI can accelerate tasks such as drafting, summarizing, or identifying connections across the literature, human insight ensures these tools are applied meaningfully and ethically. Responsible use requires active engagement, verifying sources, contextualizing outputs, and making thoughtful decisions about where and how AI is used in research. We are only beginning to understand AI’s long-term implications in research and education. What is clear, however, is that responsible integration, grounded in transparency, ethics, and equity, is essential. Researchers must move beyond simply adopting AI tools and instead focus on using them intentionally and reflectively. This means asking not only what AI can do but also why and how we should use it. It also means fostering a culture of openness, shared learning, and critical dialogue around these technologies. Empowering the future of research Although the world may not yet be fully prepared for the rapid evolution of AI in research, the academic community is uniquely positioned to lead with care and foresight. With curiosity, caution, and an intense commitment to equity, we can ensure that AI becomes not just a tool for efficiency but a force for a meaningful, inclusive, and responsible scholarship. As we prepare the next generation of scholars and practitioners, we must equip them with access to AI tools and the critical awareness to use them wisely and reflectively. I hope that continued dialogue and collaborative research, such as our recent trial on ChatGPT in health education, will help ensure that AI becomes a tool that empowers, rather than eclipses, human ingenuity. Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Mirella VerasMirella Veras
Mirella Veras

3912

How Does a Reviewer Provide Qualified Review Reports and Help the Authors Improve their Manuscripts?

10 February 2025

The Latest in Global Science

How Does a Reviewer Provide Qualified Review Reports and Help the Authors Improve their Manuscripts?

1. Introduction The invitation to share my insights and experiences as a peer reviewer on the SciProfiles blog challenged me. In 2020, I was invited to review a manuscript submitted to an international academic journal. I received the invitation enthusiastically and tried to write a good review report In 2022, I was invited to be a Reviewer Board Member of the MDPI journal Antibiotics, and a few weeks later, I was asked to participate in a webinar during peer reviewer week. Since then, I have decided to do my best as a reviewer, and my activity has significantly increased in the last 3 years. As a reward for my efforts, I received the Antibiotics Outstanding Reviewer Award in 2023 and 2024. My awareness has continuously increased with time, and my aim of providing high-quality review reports persists. I have reviewed over 135 papers in MDPI journals; my Web of Science Researcher profile records 237 peer-reviews of 161 manuscripts. They have an average of 392 words per review report, which is higher than the academic average (361). My experience continues to increase—I recently became a Section Board Member of another MDPI journal (Current Issues in Molecular Biology)—and, proportionally, I aim to improve the quality of my afferent activities. The peer reviewer skills I have developed are very helpful when I am invited to make an editorial decision. 2. Background A recent study analyzed the quality of 313 reviewer reports (within an average length of between 406.57 and 631.31 words) in a requested time range of 14-203 days. The results showed that the difference in quality between the shorter and longer reviews was not considerable [1]. The study demonstrates that efficient and high-quality peer review can be achieved without extensive time or lengthy reports. Reviewers’ age is also a significant predictor of review quality [2]. The increasing rate of manuscript submissions in various academic journals requires numerous reviewers to be available for the peer-review process. The most well-known academic journal platforms have experimented with implementing artificial intelligence (AI) in the peer-review process to efficiently address these challenges [3]. Despite AI’s minimal time requirements to produce a review report (2.5 ± 1.8 min) compared to humans (7.5 ± 2.8 weeks), human re-viewers achieved higher scores in Clarity of Feedback, Depth of Analysis, Literature Engagement, and Overall Quality. How, then, does a reviewer provide suitable review reports and help authors improve their manuscripts? Each academic journal has instructions for reviewers and describes the essential aspects point by point, but the reviewers’ understanding, motivation, and attitudes are essential to the peer-reviewing process. 3. Responsibility Understanding the reviewer’s key role as a link between editors, authors, and readers underlines a key aspect of the willingness to provide a high-quality review report. This involves the following objectives. 3.1. Ensuring the Quality Control of Manuscripts For editors: Peer reviewers assess a manuscript’s quality, validity, and significance. This helps editors make informed decisions about whether to accept, reject, or request revisions for a submission. For authors: Reviewers offer constructive feedback, highlighting strengths and weaknesses in the research, methodology, and writing. This helps authors improve their work before publication, increasing its impact and credibility. For readers: Peer reviewers act as a filter, ensuring that published research meets rigorous quality standards. This gives readers confidence in the information’s reliability and trustworthiness. 3.2. Maintaining Academic Integrity For editors: Reviewers help identify potential issues, such as plagiarism, data fabrication, or ethical concerns, safeguarding the publication’s integrity. For authors: Reviewers encourage authors to adhere to high ethical standards in their research and reporting. For readers: Peer reviewers ensure that published research is original, properly conducted, and free from significant flaws. 3.3. Promoting Scholarly Communication For editors: Reviewers often provide context and perspective on a study’s contribution to the field. These aspects help editors decide whether the manuscript fits the journal’s scope and direction. For authors: Peer review can be a valuable learning experience, exposing authors to different viewpoints and approaches within their field. For readers: Peer review ensures that published research is relevant and timely and contributes to the ongoing dialogue within a specific study area. 4. Empathy Many reviewers are concomitantly in the positions mentioned above: readers, authors, and editors. When they receive an invitation to review a manuscript, they should be aware of the trust that is put in them, the immense impact of their report on the authors, and their duty to provide valuable, well-written, and helpful articles to potential readers. They should also realize how lucky they are to be invited to contribute, develop their abilities, and gain experience and credibility in the academic world. Springer journals make the following request of reviewers: “Before you submit your report, please take a moment to read it and put yourself in the place of the authors. How would you feel if you received this report? Would you find the tone courteous and professional?” Indeed, empathy is an essential condition for effective peer review. It fosters a positive environment, enhances the quality of reviews, and promotes fairness and objectivity. By approaching the review process with empathy, reviewers can play a vital role in helping authors improve their work and further advance knowledge in their field. 4.1. Fostering a Positive and Respectful Environment Understanding the author’s perspective Reviewers should remember that authors have put significant time and effort into their work. Approaching the review with empathy means recognizing the authors’ investment and providing feedback respectfully and encouragingly, even when pointing out flaws. Constructive criticism Empathetic reviewers focus on providing constructive criticism that helps authors improve their work. This means framing feedback in a specific, actionable way and avoiding personal attacks or harsh language. Open communication Empathy encourages open communication between reviewers and authors. When reviewers are empathetic, authors are more likely to be receptive to feedback and engage in a productive dialogue about their work. 4.2. Enhancing the Quality of Reviews Thoughtful feedback Empathetic reviewers are more likely to provide thoughtful and insightful feedback. They consider the authors’ goals and the broader context of the research, offering relevant and helpful suggestions. Balanced perspective Empathy helps reviewers strike a balance between identifying weaknesses and acknowledging strengths, providing authors with a more comprehensive and balanced assessment of their work. Clear and specific language Empathetic reviewers communicate their feedback using clear and specific language. This avoids ambiguity and helps authors understand precisely what needs improvement. 4.3. Promoting Fairness and Objectivity Minimizing bias Empathy can help reviewers mitigate their own biases and preconceptions. By trying to understand the author’s perspective, reviewers can provide a more objective and fair assessment of the work. Focusing on the science Empathy encourages reviewers to focus on the science itself rather than being influenced by factors such as the author’s reputation or affiliation. 4.3.1. Challenges and Considerations Maintaining objectivity While empathy is essential, reviewers must maintain objectivity and assess the work honestly. It is a delicate balance to strike. Time constraints Reviewers often have limited time, making providing detailed and empathetic feedback challenging. 5. Other Essential Qualities 5.1. Expertise and Knowledge Subject matter expertise A strong peer reviewer possesses deep knowledge and understanding of the subject matter relevant to the work being reviewed. This expertise allows them to accurately assess the methodology, results, and conclusions. Awareness of current research They should stay updated with the latest research, trends, and debates in the field. This ensures that the review considers the work’s contribution in the context of existing knowledge. 5.2. Objectivity and Impartiality Unbiased evaluation A good reviewer evaluates the work objectively, setting aside personal biases, preferences, or any potential conflicts of interest. Focus on merit They should focus on the work’s scientific merit, rigor, and significance rather than the author’s reputation or affiliation. 5.3. Constructive Feedback 5.3.1. Clear and Specific Comments Strong reviewers provide clear, specific, and actionable feedback. Instead of vague statements, they point out specific strengths and weaknesses with supporting evidence and examples. Balance of Positivity and Negativity: They should offer a balanced assessment, highlighting the positive aspects and areas for improvement. This helps authors understand their work’s strengths and where they can improve. 5.3.2. Respectful and Professional Tone Reviewers should communicate feedback respectfully, constructively, and professionally, even when pointing out significant flaws. They should avoid personal attacks or harsh language. 5.3.3. Thoroughness and Attention to Detail Careful reading and analysis Reviewers should thoroughly read and analyze the work, focusing on methodology, data analysis, interpretation, and presentation. Identification of errors and inconsistencies They can identify errors, inconsistencies, or gaps in the research, providing valuable input for improvement. 5.3.4. Communication Skills Clarity and conciseness Reviewers should express their feedback clearly, concisely, and logically. This ensures that authors understand the comments provided and can easily incorporate them. Well-organized review They should structure their review in a well-organized manner, making it easy for authors and editors to navigate and understand the feedback. 5.4. Ethical Conduct Confidentiality Reviewers should maintain privacy and never share the reviewed work with others without permission. Integrity They should conduct the review process with integrity, avoiding plagiarism or the misappropriation of ideas. 5.5. Timeliness and Efficiency Meeting deadlines Reviewers should adhere to deadlines and submit their reviews on time. This is vital for maintaining the review process’s efficiency. Respecting others’ time Reviewers should understand that authors and editors rely on their feedback and strive to complete reviews promptly. 6. Observations Delays are a significant source of frustration for authors and editors. However, many reviewers have overwhelming administrative, teaching, work, and research commitments that take precedence over reviews. Sometimes, a scholar has concomitantly 3-4 pending review invitations. Additionally, urgent matters may arise, such as a revised version review or an editor’s decision, and their priorities change in favor of the latter. The last few months have been the first time I was overwhelmed and delayed a few review reports. I communicated this to the Managing Editor and was grateful for their kind and understanding response: “We look forward to receiving your report at a time that is convenient for you.” References 1. Cabezas Del Fierro, P.; Sabaj Meruane, O.; Varas Espinoza, G.; González Herrera, V. Peering into Peer Review: Good Quality Reviews of Research Articles Require Neither Writing Too Much nor Taking Too Long. Transinformacao 2018, 30, doi:10.1590/2318-08892018000200006. 2. Evans, A.T.; Mcnutt, R.A.; Fletcher, S.W.; Fletcher, R.H. The Characteristics of Peer Reviewers Who Produce Good-Quality Reviews. J Gen Intern Med 1993, 8, doi:10.1007/BF02599618. 3. Gatrell, C.; Muzio, D.; Post, C.; Wickert, C. Here, There and Everywhere: On the Responsible Use of Artificial Intelligence (AI) in Management Research and the Peer-Review Process. Journal of Management Studies 2024, 61. Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Violeta PopoviciVioleta Popovici
Violeta Popovici

3475

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