Conducting Literature Reviews in Science

Over the last few years, I’ve worked closely with students at all levels, and one issue comes up time and again. Many are asked to write a literature review without being given any real structure or strategy. They are told to read widely, but not how to do it effectively. This five-stage approach has helped even undergraduate students produce literature reviews that could easily hold their own at doctoral level. It has been tested in my teaching, research supervision, and academic writing workshops. Here is a brief overview: 1. Decide on the type of review Are you writing a narrative review, a systematic review, a scoping review, or something else? The type you choose will depend on the aims/objectives of your review 2. Develop the search strategy A well-defined search strategy is essential. That includes having a clear aim, selecting appropriate search terms, setting limits on publication date or geography, and knowing when to include or exclude studies. 3. Select your information sources Good reviews draw from a range of sources. This can include search engines like Google Scholar, databases like PubMed, Scopus and increasingly, AI tools. Each has its own strengths. 4. Extract your data Structure matters here. Using a consistent extraction form ensures reliability. Depending on your review type, critical appraisal may also be part of this step. 5. Synthesise your results This is where the review becomes more than a summary. Whether through a narrative synthesis or a meta-analysis, your job is to identify trends, highlight gaps, and offer insight. Two principles sit at the heart of the method: 1. Every decision must be justified. 2. Every step must be documented. This will be the focus of my next workshop in September. It is designed for those who are serious about producing high-quality reviews with confidence and clarity. Full details will be shared there soon. Save. Repost ♻️

I tested over 100 research tools with my PhD students. Only 20 made the cut. I started keeping a list around year 8 of supervising. A student would tell me something had genuinely helped them. I would test it myself. Either it stayed on the list or it did not. 18 years later, the list is still 20. Here they are. 1) Literature Search Semantic Scholar, Lens.org, Connected Papers, Scopus free access Semantic Scholar is the one I push hardest. You can trace citations forward and backward in ways Google Scholar simply cannot. If Google Scholar is your only search tool right now, this is the first thing to change. 2) Reference Management Zotero, Mendeley, Paperpile If you are not using Zotero already, download it today. Every student I supervise uses it from month one. None have ever asked to switch away from it. Paperpile has no free version but it has a 30-day trial and a 50% academic discount after that, which brings it to around $5 a month. Worth it if you write a lot. 3) Writing and Grammar Hemingway Editor, Inkwell.net, WordCounter Hemingway shows you when your writing is more complex than it needs to be. Useful for chapters that still feel heavy after you have already edited them twice. Inkwell.net is newer but genuinely good for academic tone and clarity checks. 4) Data Analysis R, ATLAS.ti free trial, MAXQDA free trial, 5) AI Research Assistants Consensus, Elicit, Research Rabbit These three are the main AI tools I recommend for literature work right now. They cite real sources. They do not make references up. That matters more than any other feature on the list. 6) Productivity Notion, Toggl Track, Focusmate, Cold Turkey Focusmate pairs you with a real person for a 50-minute working session over video. No chat, no distraction. Just two people getting their work done at the same time. Several of my students swear by it for thesis writing days. My personal top 3? Semantic Scholar for searching. Zotero for managing references. Consensus for quick scoping when a student is new to a field and needs to map the territory fast. Start there. Add the rest when you need them. One more thing. For most students I work with, the tools are not actually the gap. The gap is knowing how to use them together in the right order. That is what most PhD programmes never teach. Which tools would you add to this list? Save this toolkit. Repost for your PhD network. #PhDTips --- If your toolkit gaps are not tools but structure and strategy, my 1:1 mentoring programme is built for working professionals doing PhDs and DBAs. Fill in the discovery form at www.phdtoprof.com

Your Literature Review is Sabotaging Your Success. 80% of doctoral students make this critical mistake—and it's keeping them stuck in endless revision cycles. Most students approach their lit review like this: "Smith (2020) found X. Jones (2021) found Y. Brown (2022) found Z." Then they're confused when their committee says it "lacks synthesis" or "reads like a book report." Here's the problem: You're cataloging individual studies instead of revealing what the field has collectively learned. The Game-Changing Shift: Stop writing WHAT studies found. Start writing what the FIELD knows. Your committee doesn't want a grocery list of findings. They want to see you thinking like a scholar who can identify patterns, gaps, and emerging themes across bodies of research. Compare These Approaches: ❌ The Grocery List (What Most Students Do): "Johnson (2020) studied social media and found negative effects on mental health. Williams (2021) also studied social media and found mixed results. Davis (2022) found positive effects in their sample." ✅ The Synthesis (What Committees Want): "The relationship between social media use and mental health depends on three key factors that emerged across 15 studies: type of use (passive vs. active), duration of use, and individual vulnerability factors (Johnson, 2020; Williams, 2021; Davis, 2022)." See the difference? The second example: -Identifies patterns across studies -Creates new knowledge from existing research -Shows YOU thinking, not just reporting -Demonstrates scholarly maturity How to Make This Shift: Instead of asking: "What did this study find?"  Ask: "What do these studies collectively tell us?" Look for: -Patterns across findings -Contradictions that reveal important variables -Gaps where knowledge is missing -Emerging themes that connect different studies Your lit review should read like a story about what the field has learned, not a bibliography with commentary. The Real Impact: -When you master synthesis, you: -Get faster committee approval -Demonstrate readiness for original research -Show you understand your field deeply -Set up your methodology naturally -Position yourself as a emerging scholar, not just a student Remember: Your committee has read these studies. They don't need you to summarize them. They need you to synthesize them into new understanding. Struggling with your literature review? The difference between reporting and synthesizing is often what separates students who finish from those who don't. What's your biggest challenge with literature reviews? Share in the comments—let's help each other level up. 👇 #PhDLife #DoctoralStudent #LiteratureReview #AcademicWriting #PhD #DissertationHelp #GradSchool #AcademicSuccess #ScholarlyWriting

Literature Review Guidelines: Do's and Don'ts DO: Demonstrate a thoughtful synthesis of relevant material about your key constructs. Aim to integrate and analyse the existing literature coherently and comprehensively, focusing on the aspects directly related to your research aim and objectives. DO NOT: ➜ Merely summarise sources without adding insightful analysis or synthesis. Instead, try to provide a coherent and integrated grasp of the body of information already known in your subject. ADDITIONALLY, MAKE SURE THAT YOU: ➜ Describe the gap in the literature that your topic highlights.   ➜ Show the state of current knowledge by presenting a clear picture of the current state of understanding in your research area. This means highlighting the most recent and significant contributions. This will demonstrate your awareness of the existing literature and its implications for your own work.   ➜ Emphasise themes and conflicts. To do this, summarise the current state of knowledge thoroughly and identify major themes, patterns, and disagreements in the literature. You can present a nuanced opinion by displaying opposing arguments or unsolved disputes.   ➜ Evaluate the literature by engaging in a critical analysis of the sources you include. Assess the strengths and limitations of the studies, the methodologies employed, and the credibility of the arguments. This evaluation will demonstrate your ability to assess the quality and reliability of the literature. ➜ Use your voice by ensuring your literature review accurately represents your viewpoint and distinctive contribution to the topic. While maintaining objectivity is crucial, your review should include your interpretations and ideas. Using your own voice can help people recognise your literature review as a unique contribution.   By following these recommendations, you can actually create a literature review showing your understanding of the field's body of knowledge and offering a valuable synthesis and critical assessment of the literature relevant to your study. Make no mistake, this is a tough piece of work. I wish you good luck and follow #thedalemethod. #highereducation #postgraduate

PhD Students / Researchers - How to Do Your Literature Review 10x Faster Using AI in 2024. A solid literature review takes at least 2-3 months. Using tools, you can reduce this time by 50%. 1. Elicit: Use Elicit to find research papers quickly. It not only shows me papers but also gives summaries that help me decide which ones are important. This saved me hours of reading. 2. Scite: Scite shows how papers are cited—whether other researchers support or disagree with the findings. It helped me focus on trustworthy papers and skip those that aren’t useful. 3. Litmaps: Litmaps creates a visual map of how different papers are connected. This makes it super easy to find the key studies in my field and stay on top of new research. 4. Consensus: This tool gives me direct answers from research papers. Instead of reading through everything, I get straight to the answers I need, helping me make decisions faster. 5. Connected Papers: When I’m exploring a new topic, Connected Papers helps me see how studies are linked. It has introduced me to papers I would’ve never found otherwise. 6. Zotero + ChatGPT: Zotero keeps my papers organized, and ChatGPT helps me summarize them. This combo speeds up my note-taking process, letting me focus on understanding the research rather than just collecting it. 7. ResearchRabbit: Research Rabbit has learned what topics I’m interested in and suggests papers that are relevant. It’s like having an AI research assistant bringing me papers I didn’t know I needed. 8. Scholarcy: Long papers used to drain my time, but Scholarcy summarizes them for me. Now, I only focus on the important sections, saving me from reading unnecessary details. 9. Paperpile: Paperpile has made organizing and citing papers so much easier. It works with Google Docs, so I can add citations without breaking my writing flow. 10. Rayyan: Rayyan is perfect for systematic reviews. It uses AI to help me tag and sort papers, making the whole process faster and more organized. P.S: Have you used any AI tools for your research? Let me know in the comments. #PhDLife #AcademicResearch #LiteratureReview #AIForResearch 

PhD Students - How to conduct a solid literature review? Here are the steps you can follow to conduct a literature review. 𝟏. 𝐒𝐩𝐞𝐜𝐢𝐟𝐲 𝐭𝐡𝐞 𝐧𝐞𝐞𝐝 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐫𝐞𝐯𝐢𝐞𝐰: Why you are conducting the review? Most of the PhD students conduct literature review at the start of their PhD. The aim here is to identify the research gap that they can fill in their PhD. There can be other reasons for literature review too. 𝟐. 𝐃𝐞𝐟𝐢𝐧𝐞 𝐭𝐡𝐞 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬: In consultation with your advisor, you will specify the broader research topic for your PhD. Then, you will specify the initial set of research questions for the literature review. Mostly the questions are of the style that what are the key challenges and solutions in a particular domain. 𝟑. 𝐂𝐨𝐧𝐝𝐮𝐜𝐭 𝐚 𝐩𝐢𝐥𝐨𝐭 𝐬𝐭𝐮𝐝𝐲: Once you specify the initial research questions, then you will manually identify around 10 primary studies relevant to your topic. Based on these 10 papers, check whether you can answer the initial set of questions. If not, try to modify your questions accordingly. 𝟒. 𝐃𝐞𝐬𝐢𝐠𝐧 𝐭𝐡𝐞 𝐬𝐞𝐚𝐫𝐜𝐡 𝐬𝐭𝐫𝐢𝐧𝐠: Define a search string based on your research questions that can retrieve relevant papers from well-known databases such as IEEE, ACM, Google Scholar, etc. You can verify the search string by making sure that it returns the already known 10 relevant papers. 𝟓. 𝐃𝐞𝐟𝐢𝐧𝐞 𝐢𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧 𝐚𝐧𝐝 𝐞𝐱𝐜𝐥𝐮𝐬𝐢𝐨𝐧 𝐜𝐫𝐢𝐭𝐞𝐫𝐢𝐚: The search string will return a larger number of papers. All of these will not be relevant to your literature review. So, you will define inclusion and exclusion criteria to help you guide in the selection process. You can include study quality assessment in this step. 𝟔. 𝐒𝐞𝐥𝐞𝐜𝐭 𝐭𝐡𝐞 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐬𝐭𝐮𝐝𝐢𝐞𝐬: Using the inclusion and exclusion criteria, select the most suitable studies that can answer your research questions. You can do this selection based on reading paper title, paper abstract, or the whole paper. 𝟕. 𝐒𝐭𝐚𝐫𝐭 𝐞𝐱𝐭𝐫𝐚𝐜𝐭𝐢𝐧𝐠 𝐭𝐡𝐞 𝐝𝐚𝐭𝐚 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐩𝐚𝐩𝐞𝐫𝐬: Once the study selection is complete, design a form that you will use for data extraction. This form determines what items you will extract from the papers. Start reading each paper and extract items as per the designed data extraction form. 𝟖. 𝐀𝐧𝐚𝐥𝐲𝐳𝐢𝐧𝐠 𝐚𝐧𝐝 𝐫𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠 𝐭𝐡𝐞 𝐝𝐚𝐭𝐚: Once data is extracted from all the papers, you will analyze the data using various techniques (e.g., thematic analysis) to answer the research questions. Alongside the analysis, you can also report the data in form of a report or secondary study. Anything to be added? #phd #research #literature #review

Thinking of doing a Systematic Review? Read this first 👇 If you’re starting your research journey, you’ve probably heard that a systematic review is a “high-level” form of evidence synthesis. True, but it’s also one of the most misunderstood research designs among beginners. So, follow these guidelines: 1. Start with a crystal-clear question Use the PICO or SPIDER framework depending on your field. Your question isn’t just academic—it’s your GPS for the entire review. If your question is fuzzy, your review will wander. 2. Write and register your protocol Before you start searching, write your plan: What databases will you search? What inclusion/exclusion criteria? How will you assess quality? Then, register it on PROSPERO or OSF. (Why? It adds transparency and protects your effort from being duplicated.) 3. Search like a detective, not a tourist Don’t rely on just PubMed or Google Scholar! Use multiple databases (e.g., Scopus, Web of Science, Cochrane Library) and include grey literature (theses, reports, conference papers). Work with a librarian if possible — they’re gold for refining your strategy. 4. Screen with discipline Systematic = consistent. Use tools like Rayyan, Covidence, or EndNote to screen titles and abstracts. Always have two reviewers independently screen to reduce bias. 5. Assess quality, don’t just summarize Every study has strengths and flaws. Use tools like JBI, CASP, or Cochrane Risk of Bias checklists. This helps you weigh evidence, not just count it. 6. Synthesize with sense Quantitative? → Go for meta-analysis (if studies are similar). Qualitative? → Try thematic synthesis. Either way, tell a story — what do these studies collectively say? 7. Report transparently Follow PRISMA guidelines. Include your flow diagram, search strategy, and reasons for exclusions. It’s not just paperwork — it’s what makes your review trustworthy. PS: What’s one challenge you’ve faced while doing (or planning) a systematic review? Share in the comments. REPOST to help others.

Literature reviews: Some love them. Some hate them. Everyone has to do them. But what makes a good review article? 5 years ago, I wrote a post for LSE Impact Blog that made it into the TOP10 of the year (https://lnkd.in/dW8U2eg). I was fascinated by the “evidence maps” of the health sciences. One click and you know everything about all treatments for a condition. Should the social sciences not have the same? After analyzing 1400+ articles since the 1980s--charting the past, present and future of reviews--Tim Hannigan, Andre Spicer, and I say: no. https://lnkd.in/ewtxbj6U    But we see much room for improvement. What principles do we recommend? 1. 𝗜𝘁’𝘀 𝘁𝗵𝗲 𝗽𝘂𝗿𝗽𝗼𝘀𝗲, 𝘀𝘁𝘂𝗽𝗶𝗱: We are too fixated on HOW to do a literature review. We forget WHY a review is needed and WHERE it takes a field. 2. 𝗨𝗽 𝘆𝗼𝘂𝗿 𝗴𝗮𝗺𝗲: Unlike in other disciplines, there is little use of technology and collaboration in management, and we are slow. We recommend technologically infused and collective review practices to become faster, more relevant and more impactful. 3. 𝗕𝗲 𝗿𝗲𝗳𝗹𝗲𝘅𝗶𝘃𝗲: Generative AI will soon make descriptive reviews redundant. Find a better edge to your review. Think of it as engaging in abstract art when photography challenged the use of naturalistic paintings. 4. 𝗕𝗲𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺𝗮𝘁𝗶𝗰 𝗺𝗶𝗴𝗵𝘁 𝗻𝗼𝘁 𝗯𝗲 𝘁𝗵𝗮𝘁 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁: Unlike in the health sciences--where missing a rare side effect can literally be fatal--the social sciences benefit from “varieties of review” that reject following one idealized approach, such as systematic reviewing. 5. 𝗜𝘁’𝘀 𝗻𝗼𝘁 𝗲𝗶𝘁𝗵𝗲𝗿-𝗼𝗿. 𝗜𝘁 𝗱𝗲𝗽𝗲𝗻𝗱𝘀: A review should not be critical or integrative by default. Instead, your choice should depend on the state of the field. We call this doing “reviews with attitudes.” 6. 𝗦𝘁𝗼𝗽 𝗱𝗼𝗶𝗻𝗴 𝗿𝗲𝘃𝗶𝗲𝘄𝘀 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝘆𝗼𝘂 𝘀𝗲𝗲 𝗮 𝗴𝗮𝗽: Reviewing is a social process. Engage in the “knowledge work” of reviews to develop the field's “knowledge infrastructure.” We find 10 different review purposes that deviate from how reviews have previously been classified. We develop a “directional space” that should help authors in the future. Thanks to AOM's Annals for the space to develop an extensive analysis and provocative agenda. Especially Marya Hill-Popper Besharov for her collaborative guidance during a long process! Also the current and former EICs Matthew Cronin Elizabeth George Carrie Leana for supporting it, and Stacey Victor for keeping it going. Thanks to Sven Kunisch Nuno Oliveira Xavier Castañer Michael Lounsbury Dev (P. Devereaux) Jennings Renate E. Meyer for great comments. We hope this piece will be of use to researchers. ESCP Business School Academy of Management #reviewing #literaturereviews #research #science #management #reflexivity #ESCP

A systematic review without the right tools is academic self-sabotage. Here are selected tools to get you started Most students/early researchers are using the wrong tools for their systematic review. If your workflow is weak, the process becomes 10x harder. Here’s the stack to get started with: 🔎 Literature discovery ———- → R Discovery → SciSpace → Research Rabbit → Litmaps → Connected Papers → Elicit → Semantic AI ➤ Bohrium ➤ Consensus ➤ AnswerThis (YC F25) Remember these are not replacement for your traditional reproducible search strategies —————- 📚 Reference management → Zotero → EndNote → Mendeley ➤ Refworks ———- 📊 Screening & data management → Rayyan → Covidence → Excel → REDCap ————— 📈 Meta-analysis → R → Stata → RevMan → Python ——— ⚖️ Bias & quality assessment → RobotReviewer → Abstrackr ——- The research process is already hard. Don’t make it harder by ignoring tools to streamline your workflows. Save this. Share with your research group. And upgrade your workflow before your deadline upgrades your stress. 😁

Most medical writers are still using ChatGPT for everything. Meanwhile, they're missing specialized AI tools that actually understand scientific literature. Here are 3 tools that changed my literature review process completely: 📌 Consensus AI This one searches through 200+ million research papers and gives you instant answers backed by actual studies. It even shows you if there's scientific consensus on your question or if researchers are still debating it. 📌 Elicit Think of it as your research assistant that reads papers for you. It extracts key findings, methodology, and results into clean tables. I used to spend hours reviewing papers. Now? It happens in minutes. 📌 Scite AI This tool shows you how papers have been cited – and whether those citations support or contradict the findings. Amazing for checking if that 2019 study you're referencing has been debunked or validated since. ChatGPT is good for drafting and brainstorming. But these tools are built specifically for scientific literature. They understand study design, citation context, and research methodology in ways general AI doesn't. I still fact-check everything (always will). Always have to! But my literature reviews take significantly less time now. P.S. I also used Open Evidence before. However, it's no longer available in India. You can still use VPN and use it. But I just find these 3 more user friendly now. Have you used any of these before? #medicalwriting #medicalcopywriting #medcomms #healthcomms #medicalcommunication #healthcommunication #scientificwriting #freelance #freelancemedicalwriting #medicomarketing #mbbs #neetpg #usmle #nonclinical #pharma #biotech #medicaldevices