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Systematic Reviews: Home

Created by Health Science Librarians

Sign up for a systematic review workshop or watch a recording Sign up for a consultation with a librarian about your systematic review New! Our Systematic Review Workbook Go to the scoping review guide

 

Launch Your Systematic Review with Free Summer Series

Interested in conducting a systematic review? The Health Sciences Library’s Systematic Review Lunchtime Summer Workshop Series will get you started in seven bite-sized sessions. Sign up for all of them, or just the ones you need.

This free virtual series will provide researchers in any discipline with the tools and resources to confidently navigate the systematic review process.

Who should attend?

This series is intended for individuals and research teams who are planning to conduct a systematic review or want more information about systematic reviews. No prior knowledge or experience with systematic reviews is required.

You must be a UNC-Chapel Hill or UNC Medical Center affiliate to register.

Do I have to be on campus?

No! All sessions will be hosted virtually via Zoom by librarians and systematic review experts from the Health Sciences Library.

What will be covered?

We’ve broken down the systematic review process from ideation through publication into seven one-hour lessons. Each lunchtime session is on Wednesday and runs from noon to 1 p.m.

  1. June 11 – Introduction to Systematic Review Methods
  2. June 18 – Project Management and Helpful Tools for Conducting Systematic Reviews
  3. June 25 – Literature Searching for Systematic Reviews
  4. July 9 – Introduction to Covidence
  5. July 16 – Predictive Artificial Intelligence and Automation Tools
  6. July 23 – Managing Data, Writing and Publishing your Review
  7. July 30 – Generative Artificial Intelligence Tools for Review Tasks

You will receive an email with a Zoom link for each session you register for.

How do I register?

Register by session at: go.unc.edu/SRW

What is a Systematic Review?

What is a Systematic Review?

A systematic review is a literature review that gathers all of the available evidence matching pre-specified eligibility criteria to answer a specific research question. It uses explicit, systematic methods, documented in a protocol, to minimize bias, provide reliable findings, and inform decision-making. ¹ 

 

There are many types of literature reviews.

Before beginning a systematic review, consider whether it is the best type of review for your question, goals, and resources. The table below compares a few different types of reviews to help you decide which is best for you. 

Comparing Systematic, Scoping, and Systematized Reviews
Systematic Review Scoping Review Systematized Review
Conducted for Publication Conducted for Publication Conducted for Assignment, Thesis, or (Possibly) Publication
Protocol Required Protocol Required No Protocol Required
Focused Research Question Broad Research Question Either
Focused Inclusion & Exclusion Criteria Broad Inclusion & Exclusion Criteria Either
Requires Large Team Requires Small Team Usually 1-2 People

For more information, see Covidence Academy's blog post comparing Systematic and Scoping Reviews.

A simplified process map

Systematic Reviews: A Simplified, Step-by-Step Process Map

Creative commons license applied to systematic reviews image requires that reusers give credit to the creator. It allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, for noncommercial purposes only.  Systematic Reviews: a Simplified, Step-by-Step Process © 2021 by Emily P. Jones & Michelle Cawley is licensed under CC BY-NC 4.0.

How can the library help?

The average systematic review takes 1,168 hours to complete.¹ 
A librarian can help you speed up the process.

Systematic reviews follow established guidelines and best practices to produce high-quality research. Librarian involvement in systematic reviews is based on two levels. In Tier 1, your research team can consult with the librarian as needed. The librarian will answer questions and give you recommendations for tools to use. In Tier 2, the librarian will be an active member of your research team and co-author on your review. Roles and expectations of librarians vary based on the level of involvement desired. Examples of these differences are outlined in the table below.

Roles and expectations of librarians based on level of involvement desired.
Tasks Tier 1: Consultative Tier 2: Research Partner / Co-author
Topic Development
Guidance on process and steps Yes Yes
Background searching for past and upcoming reviews Yes Yes
Development of Eligibility Criteria
Development and/or refinement of review topic Yes Yes
Assistance with refinement of PICO (population, intervention(s), comparator(s), and key questions Yes Yes
Guidance on study types to include Yes Yes
Protocol Creation and Registration
Guidance on protocol registration Yes Yes
Searching
Identification of databases for searches Yes Yes
Instruction in search techniques and methods Yes Yes
Training in citation management software use for managing and sharing results Yes Yes
Development and execution of searches No Yes
Downloading search results to citation management software and removing duplicates No Yes
Documentation of search strategies No Yes
Management of search results No Yes
Study Selection and Extraction
Guidance on methods Yes Yes
Guidance on data extraction, and management techniques and software Yes Yes
Writing and Publishing
Suggestions of journals to target for publication Yes Yes
Drafting of literature search description in "Methods" section No Yes
Creation of PRISMA diagram No Yes
Drafting of literature search appendix No Yes
Review other manuscript sections and final draft No Yes
Librarian contributions warrant co-authorship No Yes

How can AI and machine learning help?

Cochrane Webinar Series: Artificial Intelligence (AI) methods in evidence synthesis

Advancements in AI, automation, and language processing are increasingly influencing the creation and use of evidence syntheses. AI language models (e.g., ChatGPT, Claude) and automation tools (e.g., ASReview, Laser AI, DistillerSR) offer new possibilities for tasks like search strategy development, screening and data extraction, risk of bias assessment, and writing evidence syntheses. These tools can significantly speed up the process of producing or updating evidence syntheses, benefiting researchers and users alike. However, understanding the strengths and limitations of these technologies is critical to maintaining quality.

In this webinar series, Cochrane explores the role of AI in evidence synthesis, examines how it can complement traditional methods and provides a platform for experts to discuss the opportunities, challenges, and risks involved. This series targets those with foundational knowledge of systematic reviews who want to stay updated on AI developments in evidence synthesis.

This webinar series was developed in collaboration with Waldemar Siemens and Joerg Meerpohl, who are affiliated with Cochrane Germany and the Institute of Evidence in Medicine, Medical Center – University of Freiburg, Germany. The series is based on the Methods Forum 2024 by Cochrane Germany (cochrane.de/methodenforum-2024), organised by Waldemar Siemens and Joerg Meerpohl.

Webinar recordings and slides are available on the Cochrane Artificial Intelligence (AI) methods in evidence synthesis website.


  • (How) can AI-based automation tools assist with systematic searching? [January 2025] Presented by Dr. Maria-Inti Metzendorf & Irma Klerings
    View the recording.
  • Could large language models and/or AI-based automation tools assist the screening process? [February 2025] Presented by Dr. Siw Waffenschmidt
    View the recording.
  • Opportunities and challenges for data extraction with a large language model [March 2025] Presented by Prof. Gerald Gartlehner
    View the recording.
  • (How well) can large language models and AI-based automation tools assist in Risk of Bias Assessment? [April 2025] Presented by Dr. Angelika Eisele-Metzger
    View the recording.
  • How effectively do large language models and AI-based automation tools assist in writing and summarizing evidence syntheses? [Upcoming: May 7 2025] Presented by Dr. Riaz Qureshi
    Sign Up. View the recording.
  • Recommendations and guidance on responsible AI in evidence synthesis [Upcoming: June 3 2025]
    Presented by Ella Flemyng, Dr. Anna Noel-Storr, Prof. James Thomas, Prof. Gerald Gartlehner, Prof. Joerg Meerpohl, & Biljana Macura.
    Sign Up. View the recording.

How you can partner with the HSL

UNC Health Sciences Librarians partner on systematic reviews and can apply three different types of predictive AI based on the project's needs. You can find more information on each type on our How Does Predictive AI/ML Work? page.

Library guide

Publications by HSL Librarians

The following are systematic and scoping reviews co-authored by HSL librarians.

Only the most recent 15 results are listed. Click the website link at the bottom of the list to see all reviews co-authored by HSL librarians in PubMed

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Systematic reviews in non-health disciplines

Researchers conduct systematic reviews in a variety of disciplines.  If your focus is on a topic outside of the health sciences, you may want to also consult the resources below to learn how systematic reviews may vary in your field.  You can also contact a librarian for your discipline with questions.

Education

Environmental Topics

Social Sciences

Social Work

Software engineering

Sport, Exercise, & Nutrition

Resources for performing systematic reviews

Updating reviews