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CAREER FEATURE
04 December 2020
Correction 09 December 2020

How to write a superb literature review

Andy Tay is a freelance writer based in Singapore.

You can also search for this author in PubMed Google Scholar

Literature reviews are important resources for scientists. They provide historical context for a field while offering opinions on its future trajectory. Creating them can provide inspiration for one’s own research, as well as some practice in writing. But few scientists are trained in how to write a review — or in what constitutes an excellent one. Even picking the appropriate software to use can be an involved decision (see ‘Tools and techniques’). So Nature asked editors and working scientists with well-cited reviews for their tips.

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doi: https://doi.org/10.1038/d41586-020-03422-x

Interviews have been edited for length and clarity.

Updates & Corrections

Correction 09 December 2020 : An earlier version of the tables in this article included some incorrect details about the programs Zotero, Endnote and Manubot. These have now been corrected.

Hsing, I.-M., Xu, Y. & Zhao, W. Electroanalysis 19 , 755–768 (2007).

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Ledesma, H. A. et al. Nature Nanotechnol. 14 , 645–657 (2019).

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Brahlek, M., Koirala, N., Bansal, N. & Oh, S. Solid State Commun. 215–216 , 54–62 (2015).

Choi, Y. & Lee, S. Y. Nature Rev. Chem . https://doi.org/10.1038/s41570-020-00221-w (2020).

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How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

Search for relevant literature
Evaluate sources
Identify themes, debates, and gaps
Outline the structure
Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

Instantly correct all language mistakes in your text

Upload your document to correct all your mistakes in minutes

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

Quick Run-through
Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

Demonstrate your familiarity with the topic and its scholarly context
Develop a theoretical framework and methodology for your research
Position your work in relation to other researchers and theorists
Show how your research addresses a gap or contributes to a debate
Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

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See an example

Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
Body image, self-perception, self-esteem, mental health
Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

Your university’s library catalogue
Google Scholar
Project Muse (humanities and social sciences)
Medline (life sciences and biomedicine)
EconLit (economics)
Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

What question or problem is the author addressing?
What are the key concepts and how are they defined?
What are the key theories, models, and methods?
Does the research use established frameworks or take an innovative approach?
What are the results and conclusions of the study?
How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

Don't submit your assignments before you do this

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To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
Themes: what questions or concepts recur across the literature?
Debates, conflicts and contradictions: where do sources disagree?
Pivotal publications: are there any influential theories or studies that changed the direction of the field?
Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

Most research has focused on young women.
There is an increasing interest in the visual aspects of social media.
But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

Look at what results have emerged in qualitative versus quantitative research
Discuss how the topic has been approached by empirical versus theoretical scholarship
Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
Critically evaluate: mention the strengths and weaknesses of your sources
Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

Open Google Slides Download PowerPoint

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Sampling methods
Simple random sampling
Stratified sampling
Cluster sampling
Likert scales
Reproducibility

Statistics

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Statistical power
Probability distribution
Effect size
Poisson distribution

Research bias

Optimism bias
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Hawthorne effect
Anchoring bias
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A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

To familiarize yourself with the current state of knowledge on your topic
To ensure that you’re not just repeating what others have already done
To identify gaps in knowledge and unresolved problems that your research can address
To develop your theoretical framework and methodology
To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other academic texts , with an introduction , a main body, and a conclusion .

An annotated bibliography is a list of source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a paper .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, September 11). How to Write a Literature Review | Guide, Examples, & Templates. Scribbr. Retrieved September 3, 2024, from https://www.scribbr.com/dissertation/literature-review/

Is this article helpful?

Shona McCombes

Other students also liked, what is a theoretical framework | guide to organizing, what is a research methodology | steps & tips, how to write a research proposal | examples & templates, "i thought ai proofreading was useless but..".

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Literature Reviews for Medical Sciences

Introduction

Headings and subheadings

For this section, structuring a literature review as a standalone assignment will be covered (not as part of a research paper). To understand content and structure of literature reviews that are part of research papers, please look at the section Body .

All structure and citation guidelines on this guide will be in adherence to APA format.

Reminders for APA Style Formatting:

Accepted fonts: Arial, Calibri, Times New Roman (12-point)
Double spaced
1" margins
Running header and page number on every page

Basic Structure

This will be the very first page of your literature review. This will present your title and credentials for your readers.

Basic information on the topic and scope of the paper.

Introduces the reader to topic and structure of the paper.

Body Paragraph

Main focus of the paper. Discussion and analysis of resources.

Summarize your findings.

Reference List

Full bibliographic list of sources used in the paper.

Not all literature reviews will require every element listed here. Please check the assignment requirements to understand what content you will need to include for your assignment. Any questions should be directed to your professor.

<< Previous: Home
Next: Title page >>
Last Updated: Aug 21, 2024 9:59 AM
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How to Conduct a Literature Review (Health Sciences and Beyond)

What is a literature review, traditional (narrative) literature review, integrative literature review, systematic reviews, meta-analysis, scoping review.

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Systematic Reviews by Roy Brown Last Updated Oct 17, 2023 915 views this year
Write a Literature Review by John Glover Last Updated Jul 26, 2024 4616 views this year

A literature review provides an overview of what's been written about a specific topic. There are many different types of literature reviews. They vary in terms of comprehensiveness, types of study included, and purpose.

The other pages in this guide will cover some basic steps to consider when conducting a traditional health sciences literature review. See below for a quick look at some of the more popular types of literature reviews.

For additional information on a variety of review methods, the following article provides an excellent overview.

Grant MJ, Booth A. A typology of reviews: an analysis of 14 review types and associated methodologies. Health Info Libr J. 2009 Jun;26(2):91-108. doi: 10.1111/j.1471-1842.2009.00848.x. Review. PubMed PMID: 19490148.

A traditional (narrative) literature review provides a quick overview of current studies. It helps explain why your study is important in the context of the literature, and can also help you identify areas that need further research. The rest of this guide will cover some basic steps to consider when conducting a traditional literature review. Click on the right thumbnail to see an excerpt from this type of literature review.

Integrative reviews "synthesize findings from different approaches, like experimental and non-experimental studies" ( ). They may or may not be systematic reviews. Click on the right thumbnail to see an excerpt from this type of literature review.

Systematic reviews synthesize high quality empirical information to answer a given research question ( ). Conducting a systematic review involves following rigorous, predefined protocols that "minimise bias and ensure transparency" ( ). See our for more information on what they are and how to conduct one. Click on the right thumbnail to see an excerpt from this type of literature review.

Meta-analyses are "the statistical integration of separate studies" ( ). They involve identifying similar studies and pooling their data to obtain a more accurate estimate of true effect size. A systematic review can include a meta-analysis. Click on the right thumbnail to see an excerpt from this type of literature review.

A scoping review involves a broad research question that explores the current evidence base ( ). It can help inform areas that are appropriate for a systematic review. Click on the right thumbnail to see an excerpt from this type of literature review.

Next: Developing a Research Question >>
Last Updated: Mar 15, 2024 12:22 PM
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Types of Literature Reviews
How to Write a Literature Review
How to Write the Introduction to a Research Article
The Pandora's Box of Evidence Synthesis and the case for a living Evidence Synthesis Taxonomy | BMJ Evidence-Based Medicine, 2023
Meeting the review family: exploring review types and associated information retrieval requirements | Health Information and Libraries Journal, 2019
A typology of reviews: an analysis of 14 review types and associated methodologies | Health Information and Libraries Journal, 2009
Conceptual recommendations for selecting the most appropriate knowledge synthesis method to answer research questions related to complex evidence | Journal of Clinical Epidemiology, 2016
Methods for knowledge synthesis: an overview | Heart & Lung: The Journal of Critical Care, 2014
Not sure what type of review to conduct? Brief descriptions of each type plus tools to help you decide

Ten simple rules for writing a literature review | PLoS Computational Biology, 2013
The Purpose, Process, and Methods of Writing a Literature Review | AORN Journal. 2016
Why, When, Who, What, How, and Where for Trainees Writing Literature Review Articles. | Annals of Biomed Engineering, 2019
So You Want to Write a Narrative Review Article? | Journal of Cardiothoracic and Anesthesia, 2021
An Introduction to Writing Narrative and Systematic Reviews - Tasks, Tips and Traps for Aspiring Authors | Heart, Lung, and Circulation, 2018

The Literature Review: A Foundation for High-Quality Medical Education Research | Journal of Graduate Medical Education, 2016
Writing an effective literature review : Part I: Mapping the gap | Perspectives on Medical Education, 2018
Writing an effective literature review : Part II: Citation technique | Perspectives on Medical Education, 2018

Types of Reviews

Label

Description

Appraisal

Synthesis

Analysis

Critical Review

Aims to demonstrate writer has extensively researched literature and critically evaluated its quality. Goes beyond mere description to include degree of analysis and conceptual innovation. Typically results in hypothesis or model

Seeks to identify most significant items in the field

No formal quality assessment. Attempts to evaluate according to contribution

Typically narrative, perhaps conceptual or chronological

Significant component: seeks to identify conceptual contribution to embody existing or derive new theory

Literature Review

Generic term: published materials that provide examination of recent or current literature. Can cover wide range of subjects at various levels of completeness and comprehensiveness. May include research findings

May or may not include comprehensive searching

May or may not include quality assessment

Typically narrative

Analysis may be chronological, conceptual, thematic, etc.

Mapping review/ systematic map

Map out and categorize existing literature from which to commission further reviews and/or primary research by identifying gaps in research literature

Completeness of searching determined by time/scope constraints

No formal quality assessment

May be graphical and tabular

Characterizes quantity and quality of literature, perhaps by study design and other key features. May identify need for primary or secondary research

Meta-analysis

Technique that statistically combines the results of quantitative studies to provide a more precise effect of the results

Aims for exhaustive, comprehensive searching. May use funnel plot to assess completeness

Quality assessment may determine inclusion/exclusion and/or sensitivity analyses

Graphical and tabular with narrative commentary

Numerical analysis of measures of effect assuming absence of heterogeneity

Mixed studies review/mixed methods review

Refers to any combination of methods where one significant component is a literature review (usually systematic). Within a review context it refers to a combination of review approaches for example combining quantitative with qualitative research or outcome with process studies

Requires either very sensitive search to retrieve all studies or separately conceived quantitative and qualitative strategies

Requires either a generic appraisal instrument or separate appraisal processes with corresponding checklists

Typically both components will be presented as narrative and in tables. May also employ graphical means of integrating quantitative and qualitative studies

Analysis may characterise both literatures and look for correlations between characteristics or use gap analysis to identify aspects absent in one literature but missing in the other

Overview

Generic term: summary of the [medical] literature that attempts to survey the literature and describe its characteristics

May or may not include comprehensive searching (depends whether systematic overview or not)

May or may not include quality assessment (depends whether systematic overview or not)

Synthesis depends on whether systematic or not. Typically narrative but may include tabular features

Analysis may be chronological, conceptual, thematic, etc.

Qualitative systematic review/qualitative evidence synthesis

Method for integrating or comparing the findings from qualitative studies. It looks for ‘themes’ or ‘constructs’ that lie in or across individual qualitative studies

May employ selective or purposive sampling

Quality assessment typically used to mediate messages not for inclusion/exclusion

Qualitative, narrative synthesis

Thematic analysis, may include conceptual models

Rapid review

Assessment of what is already known about a policy or practice issue, by using systematic review methods to search and critically appraise existing research

Completeness of searching determined by time constraints

Time-limited formal quality assessment

Typically narrative and tabular

Quantities of literature and overall quality/direction of effect of literature

Scoping review

Preliminary assessment of potential size and scope of available research literature. Aims to identify nature and extent of research evidence (usually including ongoing research)

Completeness of searching determined by time/scope constraints. May include research in progress

No formal quality assessment

Typically tabular with some narrative commentary

Characterizes quantity and quality of literature, perhaps by study design and other key features. Attempts to specify a viable review

State-of-the-art review

Tend to address more current matters in contrast to other combined retrospective and current approaches. May offer new perspectives on issue or point out area for further research

Aims for comprehensive searching of current literature

No formal quality assessment

Typically narrative, may have tabular accompaniment

Current state of knowledge and priorities for future investigation and research

Systematic review

Seeks to systematically search for, appraise and synthesis research evidence, often adhering to guidelines on the conduct of a review

Aims for exhaustive, comprehensive searching

Quality assessment may determine inclusion/exclusion

Typically narrative with tabular accompaniment

What is known; recommendations for practice. What remains unknown; uncertainty around findings, recommendations for future research

Systematic search and review

Combines strengths of critical review with a comprehensive search process. Typically addresses broad questions to produce ‘best evidence synthesis’

Aims for exhaustive, comprehensive searching

May or may not include quality assessment

Minimal narrative, tabular summary of studies

What is known; recommendations for practice. Limitations

Systematized review

Attempt to include elements of systematic review process while stopping short of systematic review. Typically conducted as postgraduate student assignment

May or may not include comprehensive searching

May or may not include quality assessment

Typically narrative with tabular accompaniment

Reproduced from Grant MJ, Booth A. A typology of reviews: an analysis of 14 review types and associated methodologies . Health Info Libr J. 2009 Jun;26(2):91-108. doi: 10.1111/j.1471-1842.2009.00848.x

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The literature review is the qualitative summary of evidence on a topic using informal or subjective methods to collect and interpret studies.The literature review can inform a particular research project or can result in a review article publication.

Aaron L. Writing a literature review article. Radiol Technol. 2008 Nov-Dec; 80(12): 185-6.
Gasparyan AY, Ayvazyan L, Blackmore H, Kitas GD. Writing a narrative biomedical review: considerations for authors, peer reviewers, and editors. Rheumatol Int. 2011 Nov; 31(11): 1409-17.
Matharu GS, Buckley CD. Performing a literature review: a necessary skill for any doctor. Student BMJ. 2012; 20:e404. Requires FREE site registration
Literature Reviews The Writing Center at University of North Carolina at Chapel Hill has created a succinct handout that explains what a literature review is and offer insights into the form and construction of a literature review in the humanities, social sciences, and sciences.
Review Articles (Health Sciences) Guide Identifies the difference between a systematic review and a literature review. Connects to tools for research, writing, and publishing.

Systematic Approaches to a Successful Literature Review by Andrew Booth; Diana Papaioannou; Anthea Sutton Call Number: Norris Medical Library, Upper Level, LB 1047.3 B725s 2012
Documenting your search This resource provides guidance on how to document and save database search strategies.
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Literature reviews take time. here is some general information to know before you start. .

VIDEO -- This video is a great overview of the entire process. (2020; North Carolina State University Libraries) --The transcript is included --This is for everyone; ignore the mention of "graduate students" --9.5 minutes, and every second is important
OVERVIEW -- Read this page from Purdue's OWL. It's not long, and gives some tips to fill in what you just learned from the video.
NOT A RESEARCH ARTICLE -- A literature review follows a different style, format, and structure from a research article.

Reports on the work of others.

Reports on original research.

To examine and evaluate previous literature.

To test a hypothesis and/or make an argument.

May include a short literature review to introduce the subject.

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1 Institute of Biomedical Research, College of Medical and Dental Sciences, School of Immunity and Infection, University of Birmingham, UK

A necessary skill for any doctor

What causes disease, which drug is best, does this patient need surgery, and what is the prognosis? Although experience helps in answering these questions, ultimately they are best answered by evidence based medicine. But how do you assess the evidence? As a medical student, and throughout your career as a doctor, critical appraisal of published literature is an important skill to develop and refine. At medical school you will repeatedly appraise published literature and write literature reviews. These activities are commonly part of a special study module, research project for an intercalated degree, or another type of essay based assignment.

Formulating a question

Literature reviews are most commonly performed to help answer a particular question. While you are at medical school, there will usually be some choice regarding the area you are going to review.

Once you have identified a subject area for review, the next step is to formulate a specific research question. This is arguably the most important step because a clear question needs to be defined from the outset, which you aim to answer by doing the review. The clearer the question, the more likely it is that the answer will be clear too. It is important to have discussions with your supervisor when formulating a research question as his or her input will be invaluable. The research question must be objective and concise because it is easier to search through the evidence with a clear question. The question also needs to be feasible. What is the point in having a question for which no published evidence exists? Your supervisor’s input will ensure you are not trying to answer an unrealistic question. Finally, is the research question clinically important? There are many research questions that may be answered, but not all of them will …

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Critical Appraisal Resources
What are Literature Reviews?
Conducting & Reporting Systematic Reviews
Finding Systematic Reviews
Tutorials & Tools for Literature Reviews
Finding Full Text

What are Systematic Reviews? (3 minutes, 24 second YouTube Video)

Systematic Literature Reviews: Steps & Resources

These steps for conducting a systematic literature review are listed below .

Also see subpages for more information about:

The different types of literature reviews, including systematic reviews and other evidence synthesis methods
Tools & Tutorials

Literature Review & Systematic Review Steps

Develop a Focused Question
Scope the Literature (Initial Search)
Refine & Expand the Search
Limit the Results
Download Citations
Abstract & Analyze
Create Flow Diagram
Synthesize & Report Results

1. Develop a Focused Question

Consider the PICO Format: Population/Problem, Intervention, Comparison, Outcome

Focus on defining the Population or Problem and Intervention (don't narrow by Comparison or Outcome just yet!)

"What are the effects of the Pilates method for patients with low back pain?"

Tools & Additional Resources:

PICO Question Help
Stillwell, Susan B., DNP, RN, CNE; Fineout-Overholt, Ellen, PhD, RN, FNAP, FAAN; Melnyk, Bernadette Mazurek, PhD, RN, CPNP/PMHNP, FNAP, FAAN; Williamson, Kathleen M., PhD, RN Evidence-Based Practice, Step by Step: Asking the Clinical Question, AJN The American Journal of Nursing : March 2010 - Volume 110 - Issue 3 - p 58-61 doi: 10.1097/01.NAJ.0000368959.11129.79

2. Scope the Literature

A "scoping search" investigates the breadth and/or depth of the initial question or may identify a gap in the literature.

Eligible studies may be located by searching in:

Background sources (books, point-of-care tools)
Article databases
Trial registries
Grey literature
Cited references
Reference lists

When searching, if possible, translate terms to controlled vocabulary of the database. Use text word searching when necessary.

Use Boolean operators to connect search terms:

Combine separate concepts with AND (resulting in a narrower search)
Connecting synonyms with OR (resulting in an expanded search)

Search: pilates AND ("low back pain" OR backache )

Video Tutorials - Translating PICO Questions into Search Queries

Translate Your PICO Into a Search in PubMed (YouTube, Carrie Price, 5:11)
Translate Your PICO Into a Search in CINAHL (YouTube, Carrie Price, 4:56)

3. Refine & Expand Your Search

Expand your search strategy with synonymous search terms harvested from:

database thesauri
reference lists
relevant studies

Example:

(pilates OR exercise movement techniques) AND ("low back pain" OR backache* OR sciatica OR lumbago OR spondylosis)

As you develop a final, reproducible strategy for each database, save your strategies in a:

a personal database account (e.g., MyNCBI for PubMed)
Log in with your NYU credentials
Open and "Make a Copy" to create your own tracker for your literature search strategies

4. Limit Your Results

Use database filters to limit your results based on your defined inclusion/exclusion criteria. In addition to relying on the databases' categorical filters, you may also need to manually screen results.

Limit to Article type, e.g.,: "randomized controlled trial" OR multicenter study
Limit by publication years, age groups, language, etc.

NOTE: Many databases allow you to filter to "Full Text Only". This filter is not recommended . It excludes articles if their full text is not available in that particular database (CINAHL, PubMed, etc), but if the article is relevant, it is important that you are able to read its title and abstract, regardless of 'full text' status. The full text is likely to be accessible through another source (a different database, or Interlibrary Loan).

Filters in PubMed
CINAHL Advanced Searching Tutorial

5. Download Citations

Selected citations and/or entire sets of search results can be downloaded from the database into a citation management tool. If you are conducting a systematic review that will require reporting according to PRISMA standards, a citation manager can help you keep track of the number of articles that came from each database, as well as the number of duplicate records.

In Zotero, you can create a Collection for the combined results set, and sub-collections for the results from each database you search. You can then use Zotero's 'Duplicate Items" function to find and merge duplicate records.

File structure of a Zotero library, showing a combined pooled set, and sub folders representing results from individual databases.

Citation Managers - General Guide

6. Abstract and Analyze

Migrate citations to data collection/extraction tool
Screen Title/Abstracts for inclusion/exclusion
Screen and appraise full text for relevance, methods,
Resolve disagreements by consensus

Covidence is a web-based tool that enables you to work with a team to screen titles/abstracts and full text for inclusion in your review, as well as extract data from the included studies.

Screenshot of the Covidence interface, showing Title and abstract screening phase.

Covidence Support
Critical Appraisal Tools
Data Extraction Tools

7. Create Flow Diagram

The PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) flow diagram is a visual representation of the flow of records through different phases of a systematic review. It depicts the number of records identified, included and excluded. It is best used in conjunction with the PRISMA checklist .

Example PRISMA diagram showing number of records identified, duplicates removed, and records excluded.

Example from: Stotz, S. A., McNealy, K., Begay, R. L., DeSanto, K., Manson, S. M., & Moore, K. R. (2021). Multi-level diabetes prevention and treatment interventions for Native people in the USA and Canada: A scoping review. Current Diabetes Reports, 2 (11), 46. https://doi.org/10.1007/s11892-021-01414-3

PRISMA Flow Diagram Generator (ShinyApp.io, Haddaway et al. )
PRISMA Diagram Templates (Word and PDF)
Make a copy of the file to fill out the template
Image can be downloaded as PDF, PNG, JPG, or SVG
Covidence generates a PRISMA diagram that is automatically updated as records move through the review phases

8. Synthesize & Report Results

There are a number of reporting guideline available to guide the synthesis and reporting of results in systematic literature reviews.

It is common to organize findings in a matrix, also known as a Table of Evidence (ToE).

Example of a review matrix, using Microsoft Excel, showing the results of a systematic literature review.

Reporting Guidelines for Systematic Reviews
Download a sample template of a health sciences review matrix (GoogleSheets)

Steps modified from:

Cook, D. A., & West, C. P. (2012). Conducting systematic reviews in medical education: a stepwise approach. Medical Education , 46 (10), 943–952.

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Writing in the Health Sciences: Research and Lit Reviews

Research and Lit Reviews
Tables and Figures
Citation Management
Further Reference

What Is a Literature Review?

In simple terms, a literature review investigates the available information on a certain topic. It may be only a knowledge survey with an intentional focus. However, it is often a well-organized examination of the existing research which evaluates each resource in a systematic way. Often a lit review will involve a series of inclusion/exclusion criteria or an assessment rubric which examines the research in-depth. Below are some interesting sources to consider.

The Writing Center's Literature Reviews - UNC-Chapel Hill's writing center explains some of the key criteria involved in doing a literature review.

Literature Review vs. Systematic Review - This recent article details the difference between a literature review and a systematic review. Though the two share similar attributes, key differences are identified here.

Literature Review Steps

1. Identify a research question. For example: "Does the use of warfarin in elderly patients recovering from myocardial infarction help prevent stroke?"

2. Consider which databases might provide information for your topic. Often PubMed or CINAHL will cover a wide spectrum of biomedical issues. However, other databases and grey literature sources may specialize in certain disciplines. Embase is generally comprehensive but also specializes in pharmacological interventions.

3. Select the major subjects or ideas from your question. Focus in on the particular concepts involved in your research. Then brainstorm synonyms and related terminology for these topics.

4. Look for the preferred indexing terms for each concept in your question. This is especially important with databases such as PubMed, CINAHL, or Scopus where headings within the MeSH database or under the Emtree umbrella are present. For example, the above question's keywords such as " warfarin " or "myocardial infarction" can involve related terminology or subject headings such as "anti-coagulants" or "cardiovascular disease."

5. Build your search using boolean operators. Combine the synonyms in your database using boolean operators such as AND or OR. Sometimes it is necessary to research parts of a question rather than the whole. So you might link searches for things like the preventive effects of anti-coagulants with stroke or embolism, then AND these results with the therapy for patients with cardiovascular disease.

6. Filter and save your search results from the first database (do this for all databases). This may be a short list because of your topic's limitations, but it should be no longer than 15 articles for an initial search. Make sure your list is saved or archived and presents you with what's needed to access the full text.

7. Use the same process with the next databases on your list. But pay attention to how certain major headings may alter the terminology. "Stroke" may have a suggested term of "embolism" or even "cerebrovascular incident" depending on the database.

8. Read through the material for inclusion/exclusion . Based on your project's criteria and objective, consider which studies or reviews deserve to be included and which should be discarded. Make sure the information you have permits you to go forward.

9. Write the literature review. Begin by summarizing why your research is important and explain why your approach will help fill gaps in current knowledge. Then incorporate how the information you've selected will help you to do this. You do not need to write about all of the included research you've chosen, only the most pe rtinent.

10. Select the most relevant literature for inclusion in the body of your report. Choose the articles and data sets that are most particularly relevant to your experimental approach. Consider how you might arrange these sources in the body of your draft.

Library Books

Call #: WZ 345 G192h 2011

ISBN #: 9780763771867

This book details a practical, step-by-step method for conducting a literature review in the health sciences. Aiming to synthesize the information while also analyzing it, the Matrix Indexing System enables users to establish a structured process for tracking, organizing and integrating the knowledge within a collection.

Key Research Databases

PubMed - The premier medical database for review articles in medicine, nursing, healthcare, other related biomedical disciplines. PubMed contains over 20 million citations and can be navigated through multiple database capabilities and searching strategies.

CINAHL Ultimate - Offers comprehensive coverage of health science literature. CINAHL is particularly useful for those researching the allied disciplines of nursing, medicine, and pharmaceutical sciences.

Scopus - Database with over 12 million abstracts and citations which include peer-reviewed titles from international and Open Access journals. Also includes interactive bibliometrics and researcher profiling.

Embase - Elsevier's fully interoperable database of both Medline and Emtree-indexed articles. Embase also specializes in pharmacologic interventions.

Cochrane - Selected evidence-based medicine resources from the Cochrane Collaboration that includes peer-reviewed systematic reviews and randomized controlled trials. Access this database through OVID with TTUHSC Libraries.

DARE - Literally the Datatase of Abstracts of Reviews of Effectiveness, this collection of systematic reviews and other evidence-based research contains critical assessments from a wide variety of medical journals.

TRIP - This TRIP database is structured according to the level of evidence for its EBM content. It allows users to quickly and easily locate high-quality, accredited medical literature for clinical and research purposes.

Web of Science - Contains bibliographic articles and data from a wide variety of publications in the life sciences and other fields. Also, see this link for conducting a lit review exclusively within Web of Science.

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Literature review

Literature reviews are a way of identifying what is already known about a research area and what the gaps are. To do a literature review, you will need to identify relevant literature, often through searching academic databases, and then review existing literature. Most often, you will do the literature review at the beginning of your research project, but it is iterative, so you may choose to change the literature review as you move through your project.

Searching the literature

The University of Melbourne Library has some resources about searching the literature. Leonie spoke about how she met with a librarian about searching the literature. You may also want to meet face-to-face with a librarian or attend a class at the library to learn more about literature searching. When you search the literature, you may find journal articles, reports, books and other materials.

Filing, categorising and managing literature

In order to manage the literature you have identified through searches, you may choose to use a reference manager. The University of Melbourne has access to RefWorks and Endnote. Further information about accessing this software is available through the University of Melbourne Library .

Writing a literature review

The purpose of the literature review is to identify what is already known about a particular research area and critically analyse prior studies. It will also help you to identify any gaps in the research and situate your research in what is already known about a particular topic.

Aveyard, H. (2010). Doing a literature review in health and social care: A practical guide . London, UK: McGraw-Hill Education. Retrieved from Proquest https://ebookcentral.proquest.com/lib/unimelb/detail.action?docID=771406
Reeves, S., Koppel, I., Barr, H., Freeth, D., Hammick, M. (2002). Twelve tips for undertaking a systematic review. Medical Teacher . 24(4), 358-363 .
Grant, M.J. and Booth, A. (2009). A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information & Libraries Journal .
Jesson, J., & Lacey, F. (2006). How to do (or not to do) a critical literature review. Pharmacy Education , 6(2), 139-148 .
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Systematic Review
Open access
Published: 02 September 2024

Common data quality elements for health information systems: a systematic review

Hossein Ghalavand 1 ,
Saied Shirshahi 2 ,
Alireza Rahimi 2 ,
Zarrin Zarrinabadi 1 &
Fatemeh Amani 3

BMC Medical Informatics and Decision Making volume 24 , Article number: 243 ( 2024 ) Cite this article

Metrics details

Data quality in health information systems has a complex structure and consists of several dimensions. This research conducted for identify Common data quality elements for health information systems.

A literature review was conducted and search strategies run in Web of Knowledge, Science Direct, Emerald, PubMed, Scopus and Google Scholar search engine as an additional source for tracing references. We found 760 papers, excluded 314 duplicates, 339 on abstract review and 167 on full-text review; leaving 58 papers for critical appraisal.

Current review shown that 14 criteria are categorized as the main dimensions for data quality for health information system include: Accuracy, Consistency, Security, Timeliness, Completeness, Reliability, Accessibility, Objectivity, Relevancy, Understandability, Navigation, Reputation, Efficiency and Value- added. Accuracy, Completeness, and Timeliness, were the three most-used dimensions in literature.

Conclusions

At present, there is a lack of uniformity and potential applicability in the dimensions employed to evaluate the data quality of health information system. Typically, different approaches (qualitative, quantitative and mixed methods) were utilized to evaluate data quality for health information system in the publications that were reviewed. Consequently, due to the inconsistency in defining dimensions and assessing methods, it became imperative to categorize the dimensions of data quality into a limited set of primary dimensions.

Peer Review reports

Appropriate planning in the health sector relies on the existence of accurate data and the quality of the data must be continuously controlled. The World Health Organization has tried to ensure the quality of health data by providing a toolkit. This toolkit supports countries to assess and improve the quality of health data [ 1 , 2 ].

The existence of accurate, complete, and timely data plays an important role in health care management [ 3 , 4 , 5 ]. Data quality is often only considered a component of the effectiveness of health information systems, and hiding the value of data quality in other parts of the health field can lead to incorrect decision-making [ 6 , 7 , 8 , 9 ]. Previous studies have confirmed that data quality is a multidimensional concept. Data quality assessment requires familiarity with different subjective and objective criteria and both subjective perceptions of people and objective measurements of information must be addressed [ 10 , 11 ]. Qualitative evaluations of subjective data reflect the needs and experiences of stakeholders, and objective evaluations reflect the needs of managers and stakeholders [ 12 ].

Adverse effects on the quality of care, increasing costs, creating liability risks, and reducing the benefits of investing in health information systems can be identified as the negative effects of poor-quality data [ 13 , 14 , 15 , 16 ]. Defects in data quality can lead to incorrect diagnosis and intervention in health care [ 4 , 13 , 17 , 18 ]. The quality of healthcare depends on the existence of quality data, which ultimately leads to a significant impact on customer satisfaction [ 13 , 19 ].

Data quality in health information systems has a complex structure and consists of several dimensions and some critical factors performance such as environmental and organizational, technical and behavioral affected on data quality in health information system [ 20 , 21 , 22 ]. As we mentioned later, previous studies have sporadically reported some data quality elements in health information systems. There is no comprehensive agreement on its dimensions and there is no unique accepted definition of data quality among researchers for health information systems. However, there is still a lack of a review compiling and synthesizing all elements introduced in the literature. In this study, a more comprehensive understanding of the elements for quality of data in health information systems has been done using a systematic review method. The findings of this study can provide opportunities for health policy maker to become familiar with various data quality elements in health information. This systematic review specifically answered the following research questions:

1- What are the common data quality elements for health information systems?

2- What are the roles of common data quality elements to improve the performance of health information systems?

In this review, we used a systematic approach to retrieve the relevant research studies. Our reporting strategy follows the PRISMA guidelines [ 23 ].

Eligibility criteria

In this study the inclusion criteria were: (1) Data quality components were showcased within a health information system; (2) published from the year 2003 to 2024; (3) empirical studies that answered the research questions or tested the hypothesis and conducted on specific health system The exclusion criteria were: (1) Research that did not outline data quality dimensions in health management systems; (2) Content presented in a format other than a scientific article such as Conference papers, book sections, and …; (4) Methodologies deemed to be deficient in terms of quality; (5) Publication language not in English; and (7) The full text was unavailable.

Information sources

The literature search was conducted between September and October 2023, using the following five electronic scientific databases: Web of Knowledge, Science Direct, Emerald, PubMed, Scopus and Google Scholar search engine as an additional source for tracing references.

Search strategy

This study used a systematized review approach to identify common data quality elements for health information systems. The following keywords were used in the search strategy: Data quality, Health, clinic, Hospital, Medical, Information system. The keywords chosen were searched using various combinations and in the fields of title, abstract, subject, and keyword. We considered the search features in each database and used the Boolean operators (AND, OR) to combine and search selected keywords. An example of the search strategy was given in Table 1 .

Study selection

All the results were imported into EndNote reference management software. The duplicate and non-journal papers were removed. Next, the title and abstract of the remaining articles were screened to detect subject relevance with the research objectives. The selected articles were analyzed based on the inclusion and exclusion criteria. Finally, the reference lists of all identified articles were searched for additional studies. Two researchers undertook the screening of titles and abstracts obtained through the searches. A sample of just over 20% of articles was double screened in order to assess the level of agreement between the researchers. Disagreements were resolved through discussion or consultation with a third researcher.

Data collection process

Data extraction was completed independently by two assessors. The data were extracted from including four sections: bibliographic information, methodology, and the data quality elements investigated, and key findings. Each study was treated as a single unit of analysis and the relevant information in each study was extracted using a designated data extraction form.

Information was extracted from each included study (including first author, title, publication date, type of study, methodology, processes of knowledge management that were studied and selected results). We emphasize the results of selected papers that have reported elements for assessment data quality in health information systems.

Risk of bias in individual studies

In this study, we used the Joanna Briggs Institute (JBI) checklist [ 24 ] for quality assessment. The authors assessed the included studies with a further random examination by two independent reviewers. The results of the quality assessment were compared any disagreements between the reviewers were addressed through discussion or by involving a third reviewer.

Synthesis of results

In this review, by adopting similar identifies elements as broader themes, the results of the included studies were analyzed and categorized. Finally, the homogeneous data quality elements in health information systems were synthesized and described.

Risk of bias within studies

The JBI checklist was applied to all 58 studies; none were excluded based on quality assessment and all studies were rated as unclear or high risk of bias. In 16% of studies, we cannot find “statement locating the researcher culturally or theoretically” and in 37%, “influence of the researcher on the research” is not addressed.

The search for systematic reviews identified 734 references published between 2003 and 2024. Title and abstract review selected 167 references for full text review. In the analysis, it was found that 68 papers did not address research questions or test hypotheses, 32 papers lacked discussion on data quality dimensions in health management systems, and nine documents presented content in a format other than a scientific article.

Out of the 58 selected paper for final review, 42 were released between 2013 and 2024 [ 1 , 4 , 5 , 7 , 8 , 9 , 10 , 11 , 14 , 15 , 16 , 17 , 18 , 21 , 22 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 ]. Thirteen papers looked at information quality [ 7 , 11 , 14 , 27 , 28 , 29 , 31 , 37 , 52 , 54 , 55 , 56 ], five at content quality [ 7 , 15 , 21 , 43 , 50 ], and thirty-six at data quality [ 4 , 5 , 10 , 14 , 17 , 20 , 21 , 27 , 28 , 29 , 31 , 32 , 33 , 36 , 37 , 42 , 43 , 44 , 47 , 49 , 50 , 51 , 52 , 53 , 55 , 57 , 58 , 59 , 60 ]. None of the publications, however, made a distinction between “data” and “information,” or between “data quality” and “information quality.” As a result, “information quality” and “data quality” were used synonymously [ 21 ]. The search results and the study selection process are presented in Fig. 1 .

Flow diagram of study selection process

Evaluating the quality of the data was the primary goal of the reviewed studies [ 4 , 5 , 10 , 13 , 14 , 15 , 17 , 18 , 19 , 20 , 21 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 35 , 36 , 37 , 38 , 39 , 41 , 42 , 43 , 44 , 45 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 55 , 56 , 57 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 ].Two paper focused on information quality in health systems [ 11 , 52 ]. Methods for evaluating the quality of data were presented in eight publications [ 10 , 20 , 21 , 35 , 38 , 41 , 51 , 52 ], 19 publications tended to conduct on the health information [ 5 , 8 , 10 , 11 , 16 , 17 , 20 , 21 , 22 , 26 , 31 , 37 , 42 , 47 , 49 , 50 , 51 , 55 , 57 , 60 , 66 ] and eight paper focus on health or medical records as an information system in health context [ 13 , 19 , 25 , 38 , 44 , 45 , 64 , 67 ].

To describe data quality, the studies employed a total of 57 dimensions. The first data quality attribute for health information system that was most often used was accuracy [ 4 , 5 , 15 , 17 , 19 , 28 , 29 , 32 , 33 , 34 , 37 , 41 , 43 , 45 , 46 , 49 , 51 , 53 , 59 ], second is completeness [ 4 , 5 , 20 , 28 , 29 , 30 , 41 , 44 , 45 , 46 , 48 , 49 , 51 , 52 , 53 , 56 ], and third most-frequently criterion is timeliness [ 5 , 28 , 41 , 44 , 45 , 51 ]. Table 2 displays the common dimensions of data quality in health information systems that derived from existing literature.

Data accuracy measures the extent to which information accurately represents the objects or events. The accuracy of the information that is gathered, utilized, and stored is assessed through data accuracy. It is imperative for records to serve as a dependable source of information and to facilitate the generation of valuable insights through analysis. Maintaining high data accuracy guarantees that records and datasets meet the standards for reliability and trustworthiness, allowing for their use in decision-making and various applications [ 4 , 5 , 17 , 28 , 29 , 32 , 34 ]. Correctness, precision, free of error, validity, believability and integrity are common terms that use for describe data accuracy [ 21 ]. Data believability relates to whether the data is regarded as being true, real, and credible. Data believability is based on user’s perceptions [ 1 , 36 , 40 ].

Data consistency is the state in which all copies or instances of data are identical across various information systems. This uniformity is crucial in maintaining the accuracy, currency, and coherence of data across different platforms and applications. It is essential for instilling trust in users accessing the data. Implementing data validation rules, employing data standardization techniques, and utilizing data synchronization processes are some strategies to uphold data consistency. By ensuring data consistency, organizations can provide users with reliable information for making informed decisions, streamline operations, minimize errors, and enhance efficiency [ 9 , 45 , 48 , 51 , 52 , 65 ].

Data security is the practice of protecting information from corruption, theft, or unauthorized access throughout its life cycle. This involves safeguarding hardware, software, storage devices, and user devices, as well as implementing access controls, administrative controls, and organizational policies. By utilizing tools and technologies that enhance visibility of data usage, such as data masking, encryption, and redaction, organizations can ensure the security of their data. Moreover, data security assists organizations in streamlining auditing procedures and complying with data protection regulations, ultimately reducing the risk of cyber-attacks, human error, and insider threats [ 5 , 48 , 56 ]. Secure access, safe, confidentiality and privacy are common terms that use for describe data security [ 21 ].

Data timeliness denotes the currency and availability of data at the required time for its intended use. This is critical for enabling health organizations to make swift and accurate decisions based on the most up-to-date information. The timeliness of data has an impact on data quality as it determines the reliability and usefulness of information systems. Moreover, timely data can lead to cost savings as organizations can utilize real-time data to effectively manage inventories, optimize delivery routes, and coordinate with suppliers, thus reducing the risk of stock outs, minimizing delivery delays, and ensuring smooth operations [ 5 , 25 , 28 , 41 , 44 , 45 , 51 ].

Completeness of data refers to the extent to which information includes all necessary elements and observations for a specific purpose. This factor enhances the integrity and reliability of analyses, preventing gaps in understanding and supporting more robust decision-making processes. In a complete dataset, all variables relevant to the presentation of information should be present and fully populated with valid data values. Any missing, incorrect, or incomplete entries in the dataset can compromise the quality of analyses, interpretations, and decisions based on that data [ 4 , 5 , 9 , 28 , 29 , 30 , 41 , 44 , 45 , 52 ]. Coverage, comprehensiveness, appropriate amount, adequate, appropriate amount of data and integrity are common terms that use for describe data completeness [ 21 ]. The amount of data indicates the extent of data sets obtained for analysis and processing. In present-day information systems, these sets of data are frequently observed to be escalating in size, reaching capacities such as terabytes and petabytes [ 4 , 29 , 50 , 57 ].

Data reliability pertains to the uniformity of data across various records, programs, or platforms, as well as the credibility of the data source. Reliable data remains consistently accurate, while unreliable data may not always be valid, making it challenging to ascertain its accuracy. Consequently, organizations cannot depend on unreliable data for decision-making. Data reliability, also referred to as data observability, represents the trustworthiness of data and the insights derived from it for enabling sound decision-making. Reliability is characterized by two other fundamental elements of data quality include accuracy and consistency [ 9 , 49 , 53 , 57 , 59 , 65 ].

Data accessibility refers to the ease with which users can locate, retrieve, comprehend, and utilize data within an organization’s information systems. This is crucial in the modern digital landscape, where data is valuable for decision-making, strategic planning, and operational efficiency. Ensuring data accessibility involves creating an environment where data is available, understandable, and usable by individuals with varying levels of technical expertise. This approach is closely tied to data democratization, which aims to break down silos and make data available across different levels and departments of an organization. A well-implemented data accessibility strategy ensures that data is not locked away in isolated information systems but is integrated and accessible, contributing to a more informed and agile organizational structure. The ultimate goal is to empower users to leverage data in their daily tasks and decision-making processes, thus fostering a data-driven culture [ 4 , 26 , 29 , 33 , 50 , 57 ].

Data Objectivity refers to the extent to which data is free from personal biases, emotions, and subjective interpretations. Objective data is verifiable, reliable, and accurate, meaning that it can be verified independently by multiple parties. In other words, objective data is based on facts rather than opinions or judgments. In the context of information systems, data objectivity is crucial because it enables organizations to make informed decisions based on accurate and reliable information. Objective data helps to reduce errors, inconsistencies, and uncertainties, ensuring that business processes are efficient, effective, and compliant with regulatory requirements. Data objectivity in information systems is often hindered by biases in data collection, data quality issues, information overload, and lack of standardization. Biases may arise from human error, sampling errors, or deliberate data manipulation during the collection process. Inaccuracies, inconsistencies, and incompleteness resulting from poor data quality can compromise the objectivity of the information. The overwhelming amount of data available can make it challenging to differentiate between objective and subjective information. Inconsistencies in data representation and interpretation may occur due to the use of different systems or formats [ 36 , 41 , 44 , 45 , 46 ].

Data relevancy is an aspect of data quality that determines whether the data used or generated are relevant to add to the new target system and how usable it is for users [ 9 , 29 , 45 , 48 , 51 ]. Ease of operation, Usability, applicable, utility, Usefulness, Perceived usefulness and importance are common terms that use for describe data relevancy [ 21 ]. The concept of data usability revolves around a user’s ability to obtain meaningful information from various systems. When data is stored in text files that demand prolonged and intricate processing before it can be analyzed, its usability is limited. Conversely, data that is conveniently displayed on a performance dashboard for immediate interpretation is classified as highly usable [ 4 , 25 , 29 , 45 , 48 , 50 ]. The concept of data usefulness denotes the level at which data, post-analysis, aligns with the intended purpose within a given context for its user or consumer. In most cases, data usefulness is attained when all criteria related to data quality, such as dependability, thoroughness, uniformity, and others, are fulfilled [ 43 , 50 , 52 ].

Data Understandability refer to the level at which data exhibits qualities that facilitate understanding and analysis by users, and are presented in relevant languages, symbols, and measurements within a defined context of utilization [ 22 , 34 , 37 , 46 ]. Interpretability, ease of understanding, granularity and transparency are common terms that use for describe data understandability [ 21 ].

Data navigation refers to the process of searching, locating, and extracting relevant data from a vast pool of information to support decision-making, problem-solving, or analysis. It involves the utilization of different techniques and tools to navigate through extensive data, identify patterns, trends, and correlations, and present the information in a meaningful and actionable way. The success of data navigation is contingent upon several dimensions, including technical, domain knowledge, systems, methodological, and human dimensions. The technical dimension involves mastering programming languages like SQL and Python, utilizing data visualization software such as Tableau and Power BI, and implementing data mining techniques like machine learning algorithms. Domain knowledge dimension stresses the importance of expertise in specific fields. Information system dimension highlights the role of databases, data warehouses, cloud storage platforms, and other technologies in facilitating data navigation by storing, managing, and providing access to data. Methodological dimension focuses on statistical analysis, data mining techniques, and data visualization methods as key approaches to navigating data. Lastly, human dimension recognizes the significance of communication skills, collaboration, and critical thinking in the process of data navigation [ 4 , 50 , 65 , 68 ].

Data reputation is the evaluation of the trustworthiness, reliability, and credibility of data in an information system. It signifies the extent to which stakeholders, such as users, decision-makers, and other systems, perceive the data as accurate, reliable, and complete. Within an information system, data reputation plays a crucial role in decision-making, trust, system performance, and data sharing [ 42 , 60 , 61 ].

The concept of data efficiency revolves around an organization’s effectiveness in maximizing the value obtained from its data, while simultaneously minimizing the resources essential for processing, storing, and up keeping that data. Put simply, data efficiency focuses on streamlining the collection, storage, analysis, and utilization of data to meet objectives. When considering an information system, data efficiency can be examined from various angles, such as efficiency in data acquisition, storage, processing, analysis, visualization, security, retention, and archiving [ 7 , 28 , 29 , 48 ].

Data value-added pertains to the process of refining raw data into more useful, meaningful, and valuable information that can support decision-making, drive business outcomes, and create a competitive advantage. This process involves extracting insights, patterns, or trends from large datasets and presenting them in a manner that is easy to understand and act upon. By prioritizing these dimensions of data value-added within an information system, organizations can ensure that their data is transformed into valuable insights that support informed decision-making and drive business outcomes [ 5 , 22 , 25 , 45 ].

In a few papers, the concept of “fitness for use” was applied to data quality [ 6 , 55 , 69 ]. Two viewpoints can be used to characterize data quality: (1) the inherent quality of the data elements and set, and (2) how the set satisfies the needs of the user. The definition provided by the International Standards Organization best captures the accepted meaning of data quality, which is “the totality of features and characteristics of an entity that bears on its ability to satisfy stated and implied needs” [ 4 , 15 , 28 , 33 , 53 ].

Current review study identified 14 common dimensions for data quality in health information system. In related research data quality dimensions classified on four dimensions include: intrinsic (accuracy, objectivity, reputation), contextual timeliness, completeness, and relevancy), representational (representational format, understandability, consistency), and accessibility (accessibility, security) categories [ 53 , 60 , 69 , 70 , 71 ]. There exists a certain level of intersection between the aspects of data quality recognized in this review and those research in prior classifications of data quality.

Previous literature has often discussed intrinsic data quality in terms of the absence of defects, as indicated by various dimensions such as accuracy, perfection, freshness, and uniformity [ 72 ]. and “completeness, unambiguity, meaningless and correctness” [ 54 , 73 , 74 ]. The Canadian Institute for Health Information put forth a set of 69 quality criteria, organized into 24 quality characteristics, and further classified into 6 quality dimensions: accuracy, timeliness, comparability, usability, relevance, and privacy & security [ 58 , 71 ]. Research on data quality has primarily concentrated on recognizing general quality traits like accuracy, currency, completeness, correctness, consistency, and timeliness as fundamental aspects of data quality applicable across different fields. Nevertheless, existing reviews reveal a lack of consensus regarding the conceptual framework and definition of data quality [ 70 , 73 ]. However, our pervious review shows there is a lack of consensus conceptual framework and definition for data quality [ 1 , 71 ].

In this study, the three most-frequently used dimensions of data quality were accuracy, completeness and timeliness, respectively. This arrangement is somewhat different from previous literature in which the three most-frequently used dimensions were arranged in the order of completeness, accuracy, and timeliness, respectively [ 43 , 51 , 53 ]. Furthermore, the absence of a precise definition of the data quality dimensions led to complexities in evaluating them. The definitions of dimensions and their associated metrics were occasionally based on intuition, past experiences, or the underlying goals. These results indicate that data quality is a multi-faceted phenomenon. Likewise, other scholars argue that data quality is a multi-dimensional notion [ 5 , 28 , 38 , 52 , 61 ].

The Health Information Systems heavily rely on data, as they perform essential functions like generation, compilation, analysis, synthesis, communication, and data application to support decision-making. The literature frequently evaluates the dimensions of data quality, but there is currently a lack of consistency and potential generalizability in using these dimensions and methods to assess data quality in Health Information Systems. In this review of the literature, the data quality for health information system were examined and identified 14 common dimension include: Accuracy, Consistency, Security, Timeliness, Completeness, Reliability, Accessibility, Objectivity, Relevancy, Understandability, Navigation, Reputation, Efficiency and Value- added.

The quality of data in health information systems is indispensable for healthcare institutions to make well-informed decisions and provide patients with optimal care. Accurate and timely data assists healthcare organizations and professionals in identifying patterns, predicting outcomes, and enhancing patient results. Conversely, inadequate data quality in healthcare or other data-related issues can lead to inaccurate diagnoses, inappropriate treatments, and harm to patients. To ensure data quality in healthcare, organizations must prioritize investments in data governance, data management, and data analysis tools, while also maintaining a continuous process of monitoring and improving data quality in health information systems.

It is essential to have high-quality data in order to ensure the safe and dependable delivery of healthcare services. Health facility data plays a crucial role in monitoring performance. While various organizations may prioritize different aspects of data quality, it is important to acknowledge that no health data, regardless of its source, can be deemed flawless. All data are susceptible to various limitations related to data quality, including missing values, bias, measurement error, and human errors in data entry and computation. These limitations are associated with technical, behavioral, and organizational factors [ 75 ].

This study has limitations. Firstly, the number of articles with complete data was relatively small. Secondly, assessing the quality of some studies were difficult because the quality assessment criteria were not clearly identified. We have proposed four fundamental implications to inspire future research. Firstly, it is crucial for researchers to give equal attention to all dimensions of data quality, as these dimensions can have both direct and indirect effects on data quality outcomes. Secondly, researchers should aim to evaluate the existing data quality models and frameworks through a combination of mixed methods and case study designs. Thirdly, it is important to identify the underlying causes of data quality issues in health information systems. Lastly, efforts should be made to develop interventions that can effectively address and prevent data quality issues from occurring.

Data availability

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

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This study was supported by Abadan University of medical sciences, Research code: 1557.

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Hossein Ghalavand and Saied Shirshahi Conceived the study, prepared the analysis plan, conducted the analysis, and prepared the draft manuscript. Alireza Rahimi, Zarrin Zarrinabadi and Fatemeh Amani Conceived the study, prepared the analysis plan, performed the literature search, screening for study inclusion/exclusion, and risk of bias assessment, conducted the analysis, and prepared the draft manuscript. All authors contributed to the final version of the manuscript.

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Ghalavand, H., Shirshahi, S., Rahimi, A. et al. Common data quality elements for health information systems: a systematic review. BMC Med Inform Decis Mak 24 , 243 (2024). https://doi.org/10.1186/s12911-024-02644-7

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Click here to enlarge figure

Occupational	Non-Occupational

Questionnaire	Targeted Occupational Population	Evaluated Dimensions	Number of Items/ Languages Available	Details for Interpretation/ Scoring	Availability
Maslach Burnout Inventory [ , ]	Multiple	Three dimensions: Emotional exhaustion (EE) Depersonalization (DP) Low personal accomplishment (PA)	22 (MBI-HSS) 16 (MBI-GS)/EN and available translations for other languages	Low to high burnout evaluated for each dimension	Paid licence
Copenhagen Burnout Inventory [ , ]	Multiple	Three dimensions: Personal burnout Professional burnout Client-related burnout	19/EN, Danish	Low to severe burnout	Free
Oldenburg Burnout Inventory [ , ]	Multiple	Three dimensions: Physical exhaustion Mental exhaustion Disengagement from work	16/EN, (validated in China, Philippines, India, Brazil Portugal, Slovenia, Poland, Pakistan, Malays, Greece, Nigeria)	Low, moderate, or high; the higher the score, the higher the level of burnout	Free
Karasek Job Content Questionnaire [ ]	Multiple	Three dimensions: Decision latitude Psychological demands Social support	49/EN, validated in 30 countries (amongst them are the following: Belgium, Bulgaria, France, Iceland, Iran, Italy, Japan, Malaysia, Romania, Spain, Thailand, Venezuela)	Measures the high-demand/low-control/low-support model of job strain development	Paid licence
Burnout Assessment Tool with 2 sections BAT-C and BAT-S [ ]	Working and non-working population	BAT-C 4 dimensions: Exhaustion Mental distance Emotional impairment Cognitive impairment BAT-S 2 dimensions: Psychological component Psychosomatic component	Total 33 BAT-C 23 BAT-S 10/EN, Flemish, Dutch	No risk of burnout, at risk of burnout, very high risk of burnout, with statistical norms available for each dimension for the total level	Free
Burnout Clinical Subtypes Questionnaire [ ]	Multiple	The frenetic subtype with 3 subscales: Ambition Overload Involvement The underchallenged subtype with 3 subscales: Indifference Lack of development Boredom The worn-out subtype with 3 subscales: Lack of acknowledgement Neglect Lack of control	36/EN, Latvian	Differentiates types of burnout depending on the level of dedication at work	Free
Questionnaire for the Evaluation of Burnout Syndrome at Work [ ]	Multiple	Four dimensions: Enthusiasm for work Psychological exhaustion Indolence Guilt feeling	20/EN, Dutch, German, French, Italian, Brazilian Chinese, Brazilian, Finnish Hungarian, Japanese, Korean, Norwegian, Ukrainian, Polish, Portuguese, Romanian, Slovenian, Spanish, Turkish, Swedish, Russian, Greek, Latvian, Croatian, Lithuanian	Low scores on enthusiasm for work and high scores on psychological exhaustion, indolence, and guilt indicate high level of burnout	Paid licence
Brief Burnout Questionnaire Revised for Nursing Staff [ ]	Nurses	Burnout as a process with its antecedents and consequences	21/EN	Higher motivation at work implies lower levels of burnout	Free

Biomarker	Identification	Origin	Prediction/ Confirmation Value
Melatonin [ , , , , , , , ]	Blood, Saliva, Hair	Pineal gland	Confirmation
Cortisol [ , ]	Blood, Saliva, Hair	Hypothalamus	Confirmation
CRH—corticotropin-releasing hormone [ , ]	Blood	Hypothalamus	Prediction
DHEA—dehydroepiandrosterone [ , ]	Blood	Hypothalamus	Prediction
Thyroid hormones [ , ]	Blood, Hair	Hypothalamus	Prediction
ACTH—adrenocorticotropic hormone [ , , ]	Blood	Pituitary gland	Prediction
Prolactin [ , ]	Blood	Pituitary gland	Prediction
Serum S 100B [ ]	Blood	Astrocytes and oligodendrocytes	Prediction
BDNF—brain-derived neurotrophic factor [ , ]	Blood	Endoplasmic reticulum from dense core vesicle localized in hippocampus, basal forebrain, and cortex	Prediction
TNF-α—tumour necrosis factor alpha [ ]	Blood	Micro-inflammation	Prediction
IL—interleukin [ ]	Blood	Micro-inflammation	Prediction
CRP-C reactive protein [ ]	Blood	Micro-inflammation	Prediction

Protectors against Burnout
grit
resilience
psychological flexibility
social support
good employer–employee relationships
good infrastructure
presence of employee wellness or mental health service
work–life balance
institutional leadership
having a religious background or belief

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Ungur A-P, Bârsan M, Socaciu A-I, Râjnoveanu AG, Ionuț R, Goia L, Procopciuc LM. A Narrative Review of Burnout Syndrome in Medical Personnel. Diagnostics . 2024; 14(17):1971. https://doi.org/10.3390/diagnostics14171971

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Case report
Open access
Published: 06 September 2024

Dentatorubral-pallidoluysian atrophy: a case report and review of literature

Xin Chen 1 ,
Wenwen Xiang 1 ,
Lijun Xu 1 ,
Jiahao Zhao 1 ,
Qing Ke 1 , 2 ,
Zhipeng Liu 1 &

Journal of Medical Case Reports volume 18 , Article number: 429 ( 2024 ) Cite this article

Metrics details

Dentatorubral-pallidoluysian atrophy is a rare autosomal dominant neurodegenerative disease. It is a rare disease in the world. Therefore, sharing clinical encounters of this case can deepen global awareness and understanding of the disease.

Case presentation

The patient was a 34-year-old male of Han nationality who was unmarried. The patient was admitted owing to weakness of the left lower limb with walking instability for 2 months and aggravation for 1 month. There was no dizziness, headache, numbness of limbs, convulsions, nausea, vomiting, abdominal pain, ataxia, nausea, vomiting, or abdominal pain. No nausea, vomiting, diarrhea, abdominal distension, tinnitus, hearing loss, fever, cough, expectoration. Personal history: worked in Cambodia 5 years ago, worked in Dubai 3 years ago, engaged in computer work, smoking or drinking habits. The patient was unmarried. Family history: the mother had symptoms similar to walking unsteadily (undiagnosed). Positive signs include a wide-base gait with a rotatory nystagmus that jumps upward in both eyes. Bilateral finger-nose instability test was quasi-positive, rapid alternating test was negative, and eye closure tolerance test was positive. Tendon reflexes were active in both upper limbs and hyperreflexia in both lower limbs. Stability of the heel, knee, and tibia. Genetic testing showed that the number of repeats in the dentatorubral-pallidoluysian atrophy ATN1 gene was 18 and 62, and the (CAG)n repeat sequence in the ATN1 gene was abnormal, with a repeat number of 62, and the patient was a pathogenic variant. The patient was diagnosed with dentatorubral-pallidoluysian atrophy. Dentatorubral-pallidoluysian atrophy remains a progressive neurodegenerative disease with no effective treatment. At present, the proband is taking 5 mg of buspirone three times a day, which has been reported to improve the symptoms. The patient was followed up for 6 months after taking buspirone, and there was no significant improvement in the temporary symptoms. At present, there are few cases of dentatorubral-pallidoluysian atrophy, and the characteristics of nystagmus in this disease have not been proposed in the past. This case reported the unusual presentation of nystagmus.

Dentatorubral-pallidoluygur atrophy is a rare neurodegenerative disease with autosomal dominant inheritance. To the best of our knowledge, our present case report is the first case report of dentatorubral-pallidoluygur atrophy with specific nystagmus. We describe the special eye shake and its positive signs to increase dentatorubral-pallidoluysian atrophy clinical positive signs.

Peer Review reports

Introduction

Dentatorubral-pallidoluysian atrophy (DRPLA) is a rare autosomal dominantly inherited degenerative disorder of the nervous system in which cerebellar ataxia and epilepsy as well as dementia are more common. Spinocerebellar ataxia (SCA) is a group of inherited neurodegenerative disorders that are highly heterogeneous clinically and genetically; DRPLA is a type of SCA, and DRPLA is a type of polyglutamine-polyQ disorder. The DRPLA gene ATN1 is located on chromosome 12p13.31, and in the ATN1 gene, the abnormal amplification of the CAG repeat sequence leads to the development of DRPLA. Early genetic presentation occurs in DRPLA, and it has been reported in literature that DRPLA is more prone to paternal transmission [ 1 ]. This disease has been reported most frequently in Japan, followed by Portugal, Spain, South Korea, and Venezuela, and is quite rare in China; a literature search revealed more than 30 cases both at home and abroad [ 2 ]. The clinical features, imaging, ophthalmoplegia characteristics, and gene mutation characteristics of a patient with adult-onset DRPLA, in which ataxia was the first symptom, are reported and analyzed herein. DRPLA is an extremely rare neurological disease. As clinicians, we cannot miss any opportunity to learn. Therefore, we report a patient with DRPLA to deepen the diagnosis and understanding of this disease, and we are the first to report the characteristics of nystagmus in DRPLA.

The patient was a 34-year-old Han Chinese man who was unmarried. The patient was admitted owing to weakness of the left lower limb with walking instability for 2 months and aggravation for 1 month (first visit: 1 September 2023; no follow-up. The patient presented with left lower extremity weakness without any obvious triggers, occasional choking or coughing while drinking water, unsteady walking with involuntary rightward turning of the head, and aggravated symptoms of unsteady walking in September, with no dizziness, headache, numbness of the limbs, convulsion, nausea, vomiting, abdominal pain, or ataxia. There was no nausea, diarrhea, abdominal distension, tinnitus, hearing loss, fever, cough, or sputum. Personal history: history of work in Cambodia 5 years ago, history of work in Dubai 3 years ago, computer worker, smoking or alcohol habit, and unmarried; family history: mother has similar symptoms of unsteady walking (undiagnosed). There is no particular history of medical and social psychological diagnoses, and no relevant diagnosis and treatment measures have been given before.

Physical examination on admission: temperature: 36.5 ℃, pulse: 68 beats/minute, respiration: 18 breaths/minute, blood pressure: 124/85 mmHg. Cardiopulmonary physical examination revealed no obvious abnormalities in the abdomen. Physical examination of the nervous system showed clear consciousness, wide-base gait, no aphasia, normal comprehension, insight, memory, calculation, and orientation. The double palpebral fissures were large, without drooping eyelids. No visual defects were noted with hand coarse testing. Eye movements were full without gaze palsy, and nystagmus was observed with eyes jumping in rotation. The pupils were equal in size and round, 2.5 mm in diameter, sensitive to direct and indirect light reflex bilaterally, and accommodative reflex was present. Double flank pain touch was symmetric and normal, and the jaw reflex was not elicited. Bilateral frontal lines and nasolabial grooves were symmetric and deep, with no deviation at the tooth angle. Binaural hearing was coarse but normal. Sound was clear, the soft palate elevated bilaterally, the uvula was midline, and the gag reflex was symmetric. Bilateral head turning and shrugging were symmetrical and strong, with no atrophy of the sternocleidomastoid and trapezius muscles. The tongue was midline, with no muscle atrophy or beam fibrillation. Limb joint position sense, motion sense, and tuning fork vibration sense were normal. Grade 5 moderate limb muscle strength with muscle tension was observed. Muscle atrophy and hypertrophy were not seen. Bilateral finger-nose tests were unstable, rapid rotational movement was negative, and Romberg sign was positive. Tendon reflexes were active in both upper limbs and hyperreflexia in both lower limbs. Hoffmann sign, Rosolimo sign, and palmochin reflex were negative bilaterally. Babinski sign was negative bilaterally, and the neck was soft. Kirschner’s sign and Buchner’s sign were negative.

Routine blood sampling after admission was unremarkable.

Routine cerebrospinal fluid examination, biochemistry, bacterial smear examination, virus II, bacterial culture, and cerebrospinal fluid immunoglobulin G were not abnormal; anti-neuronal cell profile 16 tests were negative (cerebrospinal fluid, serum). Thiobarbituric acid tissue based assay (TBA) test (cerebrospinal fluid): no positive signals were detected; TBA test (serum): weakly positive signals were detected in the hippocampus area, coloring in neuronal cells, and the cerebellar area showed an abnormal signal, coloring within the Purkinje neuronal cells.

The 3-hour video electroencephalogram (EEG) monitoring suggested the following: abnormal EEG, abnormal epileptiform discharges, and diffuse.

Magnetic resonance suggested mild bilateral cerebellar atrophy with multiple abnormal signals in the brainstem and mild atrophy of the cervical spinal cord with multiple abnormal signals in the cerebral white matter (Fig. 1 ).

Magnetic resonance imaging of the head and cervical spine of the proband with dentatorubral-pallidoluysian atrophy (4 September 2023). A White matter lesions in bilateral cerebral hemispheres; B mild atrophy of the cervical spinal cord; C multiple contralateral abnormal signals in the brainstem; D abnormal “cross” signals in the dorsal pons; E widening of partial sulci in the cerebellar hemispheres and mild cerebellar atrophy

Electroconvulsive nystagmography revealed bilateral upward jumping with twisting nystagmus from the upper pole of the eyeball to the left ear (Fig. 2 ) (of nystagmus electricity figure video visible supplementary material video).

Abnormal results of electronystagmography in the proband

The genetic disease candidate gene panel + dynamic mutation gene test results were as follows: 18 and 62 DRPLA ATN1 gene repeats and abnormal amplification of the (CAG)n repeat sequence in the ATN1 gene with 62 repeats. The patient had a disease-causing mutation (Fig. 3 ). The patient was diagnosed with DRPLA.

Genetic disease candidate gene panel + dynamic mutation gene detection results for the proband

Therapy: idebenone at 30 mg three times a day and mecobalamin at 0.5 mg three times a day were given to the patient from the first day of hospitalization. The patient was hospitalized for a total of 9 days, during which oral medication was administered daily as prescribed. After discharge, the patient continued to take both drugs orally, and the dosage was consistent with that during hospitalization. The patient was followed up for 10 months after discharge. During our telephone follow-up, the patient reported that his walking symptoms had improved.

DRPLA is an extremely rare neurological disease. Compared with previous literature, we are unique in that we report the nystagmus features of DRPLA, which have not been reported in previous literature. The patient developed symptoms of ataxia at the age of 34 years with a specific nystagmus: bilateral saccadic nystagmus with the upper pole of the eyeball twisted toward the left ear. In addition, oral idebenone (30 mg three times a day) and mecobalamin (0.5 mg three times a day) for 10 months helped the patient to walk unsteadily. This has not been mentioned in previous literature.

DRPLA is a subtype of spinal cerebellar ataxia (SCA) that is similar to other polyglutamine disorders and is characterized by similar gene dynamics [ 3 ]. The causative gene of DRPLA is located in the 12p13.31 region, and the elongation of the polyglutamine chain (PloyQ) is associated with an abnormal amplification of the repetitive sequence of CAG. In PloyQ, there is a specific protein, the atrophin-1 protein, and when this protein accumulates within the neuron, causing cytotoxicity, the neuron then degenerates and dies [ 4 , 5 ]. DRPLA has been associated with the disruption of protein‒protein interactions, in which amplified polyQ bundles play a crucial role, and dysregulation of gene expression [ 6 ]. The main clinically characterized symptoms of DRPLA are ataxia and cognitive decline. A summary of Chinese cases revealed that DRPLA disease is extremely rare in the Chinese population [ 7 ], and the incidence and age of onset of the disease do not differ significantly by sex, but the clinical manifestations are characterized by different ages of onset of the disease [ 8 ]. In China, the typical clinical features of adult-type cases of DRPLA are ataxia, cognitive decline, and involuntary movements, whereas epilepsy and myoclonic seizures are more common in juvenile-type clinical cases. In this case, the patient was 34 years old, an adult, with ataxia and unsteady walking as the first symptom, accompanied by rapid involuntary head rotation to the right, and upward jumping rotational nystagmus in both eyes was observed on examination. On admission, the patient’s imaging suggested cerebellar atrophy and multiple abnormal signals in the brainstem; genetic testing confirmed that the number of repeats of the CAG sequence of the ATN1 gene in the preexisting patient was 18/62, which was consistent with the diagnosis of DRPLA.

A review of this case revealed that the clinical presentation characteristics of patients with adult-type DRPLA lacked specificity, and genetic testing was the basis for confirming the diagnosis, suggesting that although DRPLA is relatively rare in China, the detection of the number of CAG repeats in the ATN1 gene should not be ignored in addition to focusing on the characteristics of cerebellar atrophy in patients who are considered for investigating the etiology of ataxia. It is worth noting that previous studies did not mention nystagmus signs in patients with DRPLA, but the examination of the present patient revealed bilateral upward rotational nystagmus, suggesting that binocular upward rotational nystagmus may be a sign characteristic of DRPLA; therefore, the nystagmus signs of patients should also be considered when diagnosing patients with DRPLA.

DRPLA is a rare genetic neurodegenerative disease, its clinical features are extremely complex, and some patients’ clinical symptoms lack specificity, which makes it easy to miss and misdiagnose. To further understand this disease and improve its diagnosis and treatment, we reviewed the relevant literature both at home and abroad and summarized the basic status of this disease.

Clinical manifestations: DRPLA can occur at all ages, with 31 years as the average age and no significant difference in sex [ 9 ]. On the basis of the age of onset and clinical features, DRPLA is categorized into juvenile (< 20 years old), early adult (20–40 years old), and late adult (> 40 years old) subtypes, and the main manifestations of DRPLA in each age group are cerebellar ataxia and dementia [ 1 , 10 ]. The age of onset is 15–19 years, and juvenile patients with DRPLA usually present with epilepsy, myoclonus, and mental retardation, with epilepsy as the first symptom and rapid progression of the disease. Adult-onset DRPLA has an age of onset of approximately 38–43 years, with cerebellar ataxia, dementia, involuntary movements, and psychiatric abnormalities as common clinical manifestations and sometimes head tremors and vision problems [ 6 ]. Ataxia and cognitive decline are usually the first symptoms and need to be differentiated from other subtypes of SCA, as well as Huntington’s disease and spinal medullary myasthenia gravis [ 11 , 12 ]. Epilepsy is less common in patients with adult-onset DRPLA, but a few cases have been reported [ 13 ] (Table 1 );

Imaging: cranial magnetic resonance imaging (MRI) is an important test for diagnosing DRPLA, which commonly shows progressive atrophy of the brainstem and cerebellum and extensive cerebral white matter lesions on T2-weighted (T2W) or fluid–attenuated inversion recovery (FLAIR) sequences. Patient age and the number of CAG repeats are two independent factors affecting the severity of brainstem and cerebellar atrophy, and changes in the volume of the brainstem and cerebellum may be important indicators of disease progression. Cerebral white matter lesions, which are significant MRI features of DRPLA, are widely distributed in the cerebrum, brainstem, thalamus, and cerebellum in patients with DRPLA, and among them, cerebellar white matter lesions are a prominent feature of MRI in patients with DRPLA, especially at disease onset. Cerebellar white matter lesions are one of the prominent MRI features of DRPLA, especially in older patients [ 14 ], and have been reported in both juvenile and adult patients, with the adult type being the most common. The mechanism by which cerebellar white matter lesions occur in DRPLA has not yet been clarified, and several studies have shown that cerebellar white matter lesions in DRPLA are not related to ischemia-induced hypoperfusion; rather, they may originate from the disease process of DRPLA itself, which involves the accumulation of aberrant proteins resulting in the absence of axons or myelinated fibers. However, it is worth noting that the severity of cerebral white matter lesions did not significantly correlate with the duration of the disease or the number of CAG repeats in patients but was positively correlated with the age of the patients examined, suggesting that cerebral white matter lesions may not only be related to the disease itself but also be affected by other unknown factors, such as failure of the relevant compensatory mechanisms owing to aging, which needs to be further investigated [ 14 , 15 , 16 ].

Gene mutation: the ATN1 gene is located on chromosome 12p13.31 and encodes the atroph-1 protein, a transcriptional corepressor widely expressed in the central nervous system. There is an unstable CAG repeat queue in this gene, encoding polyglutamine, and DRPLA is the result of abnormal amplification of the CAG repeat queue. Currently, it is believed that the number of CAG repeats in normal individuals is usually 6–35, and individuals carrying 35–47 CAG repeats show incomplete outgrowth and usually have mild clinical manifestations, while those with more than 48 CAG repeats have a complete outgrowth phenotype. The number of CAG repeats is negatively correlated with age of onset and positively correlated with disease severity. The average number of CAG repeats in juvenile patients with DRPLA is 68 (range: 63–79), that in early adult patients with DRPLA is 64 (range: 63–69), and that in late adult patients DRPLA is 63 (range: 48–67) [ 4 , 9 , 17 ]. DRPLA is similar to other PolyQ disorders in that the phenomenon of early onset of genetic predisposition occurs in PolyQ disorders, with the age of onset advancing from generation to generation and with symptoms appearing earlier and earlier in the same lineage. The age of onset is advanced, and symptoms worsen from generation to generation, which may be related to the erratic amplification of the CAG repeat cohort, which is more pronounced in patrilineal transmission [ 1 , 9 , 18 ], but follow-up of the present prediagnostic patient did not have similar clinical manifestations among the families of the prediagnostic patient (follow-up of the prediagnostic patient’s parents, grandparents, and maternal grandparents).

Diagnosis and treatment: the clinical diagnosis of DRPLA mainly relies on clinical manifestations, imaging examinations, family history, and ethnic history. There are no standardized criteria. DRPLA should be considered a possible cause of disease when the patient’s relevant history and examinations meet the following criteria:

Clinical manifestations vary according to the age of onset, with patients under 20 years of age mainly presenting with epilepsy, myoclonus, and ataxia, while patients over 20 years of age mainly present with ataxia, athetosis, involuntary movements, cognitive decline, mental behavioral abnormalities, and so on;

Imaging shows atrophy of the brainstem and cerebellum and widely distributed cerebral white matter lesions in the cerebrum, cerebellum, brainstem, thalamus, and and other parts of the brain;

There is a family history of the disease, which is consistent with the characteristics of autosomal dominant inheritance, but there are also some DRPLA cases without a family history, and the absence of a family history does not exclude the diagnosis of DRPLA. Clinical patients suspected of having DRPLA should improve genetic testing, and DRPLA confirmation criteria for genetic testing for abnormal amplification of the ATN1 gene CAG repeat sequence, which is generally greater than 48 [ 7 , 9 ], should be met. DRPLA is still a progressive neurodegenerative disease, and there is no effective treatment [ 9 ]. Moreover, the progression of the disease cannot be stopped, and symptomatic treatment is still needed. This patient received 30 mg of idebenone orally three times a day during hospitalization. Mecobalamin was administered orally at 0.5 mg three times a day. The patient was hospitalized for a total of 9 days and received both drugs daily according to the prescribed dose. After discharge, the patient continued to take both drugs orally and regularly, with doses consistent with those during hospitalization. Patients were followed up for 10 months after discharge. During the follow-up, the patient reported that walking symptoms had improved.

In summary, we report a case of a patient with dentate nucleus red nucleus pallidus globus pallidus atrophicus who began with unsteady walking, with specific nystagmus double upturns accompanied by signs of nystagmus twisting of the upper pole of the eye toward the left ear. Through a literature review, we discussed in detail the clinical presentation and diagnostic criteria of patients with dentate nucleus red nucleus pallidus globus pallidus atrophicus and emphasized the patient’s specific nystagmus, cranial magnetic resonance, family history, and genetic testing for definitive diagnosis and early detection to improve quality of life. Additionally, we learned that the age of onset of DRPLA disease in the same family line advances from generation to generation, and symptoms worsen from generation to generation and are more pronounced in paternal transmission. However, following the present case of the preexisting patient, among the family, his mother had similar symptoms of unsteady walking, but owing to the complexity of the family environment of the preexisting patient, it was not possible to perform a genetic test on his mother.

Availability of data and materials

The datasets during the current study available from the corresponding author on reasonable request.

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Acknowledgements

We thank the reviewers for their valuable comments and suggestions.

Funding was acquired through Jiangxi Provincial Natural Science Foundation, award number: 20212BAB206046; the Recruitment Program of Experts of Jiangxi Province, award number: jxsp2023102164; The Science and technology plan of Jiangxi Health Committee, award number: 202210573; and National Natural Science Foundation incubation project of the Second Affiliated Hospital of Nanchang University, award number: 2021YNFY12007.

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Xin Chen, Wenwen Xiang, Lijun Xu, Jiahao Zhao, Ye Yu, Qing Ke, Zhipeng Liu & Li Gan

The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China

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XC reviewed the literature and wrote the initial manuscript drafts; WX, LX, JZ, YY, QK, ZL, and LG managed the patient, reviewed the literature, and completed the manuscript. Both authors read and approved the final manuscript.

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Correspondence to Li Gan .

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Given the patient’s extended residence in another province and the inconvenience of walking, telephone contact was maintained with the patient and his father, and the patient agreed to allow us to publish his case.

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Chen, X., Xiang, W., Xu, L. et al. Dentatorubral-pallidoluysian atrophy: a case report and review of literature. J Med Case Reports 18 , 429 (2024). https://doi.org/10.1186/s13256-024-04745-3

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Published : 06 September 2024

DOI : https://doi.org/10.1186/s13256-024-04745-3

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A systematic review collects secondary data, and is a synthesis of all available, relevant evidence which brings together all existing primary studies for review ( Cochrane 2016 ). A systematic review differs from other types of literature review in several major ways. It requires a transparent, reproducible methodology which indicates how studies were identified and the criteria upon which they were included or excluded. As well as synthesis of these studies' findings, there should be an element of evaluation and quality assessment. The systematic review methodology originated in medical and healthcare research, but it has now been adopted by other disciplines, such as engineering, education, economics and business studies. The processes and requirements for conducting a systematic review can seem arduous or time consuming, but with the use of appropriate tools and resources, and with thorough planning undertaken before beginning the review, researchers will be able to conduct their systematic reviews efficiently and smoothly.

This article provides an overview of the structure, form and content of systematic reviews, with a particular focus on the literature searching component. It will also discuss tools and resources – including those relating to reporting standards and critical appraisal of the articles included in the review – which will be of use to researchers conducting a systematic review.

Topic selection and planning

In recent years, there has been an explosion in the number of systematic reviews conducted and published ( Chalmers & Fox 2016 , Fontelo & Liu 2018 , Page et al 2015 ) – although a systematic review may be an inappropriate or unnecessary research methodology for answering many research questions. Systematic reviews can be inadvisable for a variety of reasons. It may be that the topic is too new and there are not enough relevant published papers to synthesise and analyse for a systematic review, or, conversely, that many other researchers have already published systematic reviews on the topic. However, if a scoping search appears to yield sufficient relevant studies for evidence synthesis, and indicates that no previous systematic reviews have been published (or that those previously published require an update or have methodological flaws), systematic reviews are likely to be appropriate.

Most systematic reviews take between six and 18 months to complete, and require a minimum of three authors to independently screen search results. Although many university modules require students to complete systematic reviews, due to this time and authorship requirement, it would be better to describe such student reviews as ‘reviews with systematic literature searches,’ as it is not possible to fulfil all the methodological requirements of a systematic review in a piece of work with a single author. Researchers without the available time or number of potential co-authors may prefer to adopt a different approach, such as narrative, scoping, or umbrella reviews. The systematic, transparent searching techniques outlined in this article can be adopted and adapted for use in other forms of literature review ( Grant & Booth 2009 ), for example, while the critical appraisal tools highlighted are appropriate for use in other contexts in which the reliability and applicability of medical research require evaluation.

Once it has been determined that a systematic review is the appropriate methodology for the research, and that there is sufficient time and resources to conduct it, researchers should then spend some time developing their review topic. It is appropriate at this point to do some scoping searches in relevant subject databases, first to ensure that the proposed review is unique, and meets a research need, and second to obtain a broad overview of the literature that exists, and which is likely to be included in the eventual systematic review. Based on this scoping work, the review topic may need to be refined or adapted, possibly to broaden or narrow it in focus. Once reviewers are satisfied with their chosen topic, the next step is to prepare a protocol which states transparently the methodology they intend to follow when conducting their review.

Creating a protocol

A protocol is a description of the proposed systematic review, including methods, the rationale for the review, and steps which will be taken to eliminate bias while conducting the review. Registering the protocol stakes a claim on the research, and it also means that researchers have done a significant portion of the work required before they formally begin the review, as they will have written the Methods section in draft form and planned what will be necessary to document and report by the time the protocol is finished.

Most protocols are registered with PROSPERO (2020), although it is also possible to upload your protocol on an institutional or subject repository, or publish the protocol in a journal. Guidance for creating a protocol can be found at PRISMA-P (The PRISMA Group et al 2015), or by working through the online training on protocols available at the Cochrane Library ( Cochrane Interactive Learning 2019 ).

Reporting standards and structure

PRISMA (the Preferred Reporting Items for Systematic Reviews and Meta-analyses) is 'an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses' ( Moher et al 2009 ). The PRISMA checklist is a useful guideline of content that should be reported and included in the final published version of the systematic review, and will help when in the planning stages as well. Most systematic reviews will be written up using the PRISMA checklist as their underlying structure, so familiarity with this checklist and the content required when reporting the findings of the systematic review should be established at the earliest planning stages of the research.

PRISMA-P (The PRISMA Group et al 2015) is the reporting guidelines for protocols. The EQUATOR Network lists reporting standards for multiple different types of study design ( EQUATOR Network 2020 ). Researchers can search for the right guideline for their type of study. Those undertaking a Cochrane review should select the correct Cochrane Handbook ( Cochrane Training 2020 ) for their review type.

Search strategy

The search strategy for systematic reviews is the main method of collecting the data which will underpin the review's findings. This means that the search must be sufficiently robust – both sensitive and specific – to capture all relevant articles. Ideally, multiple databases and other sources of information should be searched, using a consistent, predetermined search string. Generally, this will involve multiple synonyms for each theme of the review's topic, and a multifield search including freetext terms in (at minimum) the title and abstract, and the controlled vocabulary in the database thesaurus. These words are then combined with the Boolean operators AND, OR and NOT so that search results are both sensitive and specific.

Grey literature

It is likely that systematic reviews will need to include a search of grey literature as well as the peer-reviewed journal articles found through database searching. Grey literature includes unpublished theses, conference proceedings, government reports, unpublished trial data and more. Leaving grey literature out can run the risk of biasing the reviews results ( Goldacre 2011 ).

Searching grey literature can be challenging. Most sources of grey literature cannot be searched with complex Boolean operators and myriad synonymous keywords in the manner of a database. Likewise, the websites and other sources used to search for grey literature are unlikely to have a controlled vocabulary thesaurus. The Canadian Agency for Drugs and Technologies in Health (CADTH) tool is designed to help adapt complex systematic database search strategies for use when searching for grey literature ( CADTH 2009 ).

Snowballing, hand-searching and reference lists

Sometimes it may be appropriate to 'snowball' a search. This involves screening all the articles that cite included papers (the articles which meet the inclusion criteria after screening). Search for the titles of each included article in Web of Science or Scopus (or both), and any listed citing article which meets your inclusion criteria should also be included in the review.

Hand searching involves looking back through the tables of contents of key journals, conference proceedings, or lists of conference presentations relevant to the systematic review topic. Once key journals have been identified, reviewers should plan how many years back they will look – this will need to be done consistently across all journals that are hand-searched.

After reviewers have screened all the papers identified by the database and grey literature searches, and agreed on which will be included in the review, they should check through these articles' reference lists. Any articles in their reference lists which meet all inclusion criteria should also be included in the review.

Librarian co-authorship

There is some evidence that having a librarian co-author on a systematic review can improve the review's quality. A number of recent studies have indicated that librarian involvement improves the reproducibility of the literature searching ( Hameed et al 2020 , Koffel 2015 , Rethlefsen et al 2015 ). Reviews without librarian involvement often have problems with their search strategies – for example Boolean operators used incorrectly, inappropriate search syntax, or a lack of sufficient synonyms for each search term, meaning that relevant studies might be missed ( Golder et al 2008 , Li et al 2014 ). Unfortunately, in some instances, systematic reviews without librarian co-authors will still be published, even if their search strategies have significant methodological flaws ( Brasher & Giustini 2020 ). Librarian involvement will help ensure that the search strategy is robust, and that it is described accurately in the methodology to ensure that the systematic review is reproducible. Generally, if a librarian is developing the search terms, running the searches in databases and writing the search methods, they should be a co-author of the systematic review, whereas if the librarian supports researchers who then conduct the searches themselves, co-authorship is not necessary. This also aligns with the Vancouver recommendations on co-authorship ( International Committee of Medical Journal Editors 2019 ).

After database and grey literature searches are completed, and researchers have identified other papers through hand-searching, they will need to screen the titles and abstracts to determine if they meet the criteria for inclusion. These criteria should be pre-defined (ie: stated in the protocol before searches have begun). Inclusion criteria might relate to the following:

Date range of publication. Study design type. Whether a study focuses on the review's specific disease, condition, or patient population. Whether a study focuses mainly on the review's specific intervention. Whether a study focused on a certain country, region, or healthcare context (for example primary care, outpatient department, critical care unit, or similar).

This list is not exhaustive, and there are many other inclusion criteria to apply, depending on the scope of the topic of the systematic review. It is important that these criteria are stated clearly in the Methods section of both the protocol and systematic review, and that all co-authors understand them.

Generally, articles are screened against these criteria independently by at least two authors. Initially they should screen the titles and abstracts, and then move on to screening the full text for any articles which could not be judged as fulfilling (or not fulfilling) all inclusion criteria on the basis of the information in their titles and abstracts.

Referencing software such as Endnote, EndnoteWeb, Mendeley or Zotero can be used for screening, or reviewers may prefer to use systematic review screening software such as Covidence or Rayyan.

Critical appraisal tools

There are a number of tools and checklists available to help assess the quality of studies to be included in a review. Studies included in a systematic review should be assessed for their quality and reliability. While poor quality studies should not be excluded if they fulfil predefined inclusion criteria, the systematic review should make clear that all included studies have been assessed according to consistent principles of critical appraisal, and the results of that appraisal should be included in the review.

Most critical appraisal tools consist of different checklists to apply to different types of study design. If a systematic review includes multiple types of study design, it is advisable that researchers are consistent about which tools they use – it is preferable to use different checklists from a single source, rather than picking and choosing from a variety of sources.

If the systematic review is only including peer-reviewed, published journal articles, the checklists from either CASP (Critical Appraisal Skills Programme), Centre for Evidence-Based Medicine, SIGN (Scottish Intercollegiate Guidelines Network), or Joanna Briggs Institute will be appropriate ( Brice 2020 , Centre for Evidence-Based Medicine 2020 , Joanna Briggs Institute 2020 , SIGN 2020 ). Reviews which include grey literature should use a grey literature appraisal tool, such as AACODS ( Tyndall 2008 ). There are also risk of bias assessment tools, such as RoBiS for evaluating systematic reviews, and RoB 2 for evaluating randomized controlled trials ( Bristol Medical School 2020 , Sterne et al 2019 ).

One of the main advantages of systematic reviews is that they combine the analysis of the data from a number of primary studies. Most commonly, this is done through meta-analysis – the statistical combination of results from two or more studies. As outlined in the Cochrane Handbook, in interventional studies, a systematic review meta-analysis will seek to answer these three main questions:

What is the direction of effect? What is the size of effect? Is the effect consistent across [all included] studies? ( Higgins et al 2019 )

The researchers will then make a judgement as to the strength of evidence for the effect. If the systematic review is assessing the effectiveness of a variety of different interventions, it may not be possible to combine all studies for meta-analysis as the studies may be sufficiently different to make meta-analysis inappropriate. Researchers should ensure that when interpreting the results they consider the limitations and potential biases of included studies. When reporting the findings it is also usually necessary to consider applicability, and make recommendations – such as for a change in practice.

Systematic reviews – when an appropriate approach to the topic being researched – are a way to synthesize and evaluate the range of evidence available in multiple primary studies. Their methodology is complex, but if the correct reporting guidelines are followed, and researchers make use of tools, resources and the support of librarians and other information specialists, the process will be more straightforward. Planning is key: researchers should have a clear picture of what is involved, and what will need to be documented and reported in any resulting publications, and put measures in place to ensure that they capture all of this essential information.

No competing interests declared .

ORCID iD: Veronica Phillips https://orcid.org/0000-0002-4383-9434

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Ten Simple Rules for Writing a Literature Review
Ten Simple Rules for Writing a Literature Review - PMC
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Mapping the gap. The purpose of the literature review section of a manuscript is not to report what is known about your topic. The purpose is to identify what remains unknown—what academic writing scholar Janet Giltrow has called the 'knowledge deficit'—thus establishing the need for your research study [].In an earlier Writer's Craft instalment, the Problem-Gap-Hook heuristic was ...
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How to write a superb literature review
How to Write a Literature Review
Examples of literature reviews. Step 1 - Search for relevant literature. Step 2 - Evaluate and select sources. Step 3 - Identify themes, debates, and gaps. Step 4 - Outline your literature review's structure. Step 5 - Write your literature review.
How to structure a literature review
This will be the very first page of your literature review. This will present your title and credentials for your readers. Abstract. Basic information on the topic and scope of the paper. Introduction. Introduces the reader to topic and structure of the paper. Body Paragraph. Main focus of the paper. Discussion and analysis of resources. Conclusion
Writing a literature review
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How to Conduct a Literature Review (Health Sciences and Beyond)
The other pages in this guide will cover some basic steps to consider when conducting a traditional health sciences literature review. See below for a quick look at some of the more popular types of literature reviews. For additional information on a variety of review methods, the following article provides an excellent overview. Grant MJ, Booth A.
Literature Reviews
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Literature Review
The literature review is the qualitative summary of evidence on a topic using informal or subjective methods to collect and interpret studies.The literature review can inform a particular research project or can result in a review article publication. ... Norris Medical Library, Upper Level, LB 1047.3 B725s 2012. Documenting your search.
Writing an Effective Literature Review
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Chapter 9 Methods for Literature Reviews
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