a good literature review would not

How to do a systematic review: 5 steps that will save you days (if not weeks!)

• October 5, 2020

Systematic review is the gold-standard of medical evidence if it’s done properly. But not all health researchers know how to do a systematic review, so I see the same mistakes being made over and over again.

I’m here to show you how to do it properly so that you can avoid those mistakes and save yourself oodles of time!

I’ll kick off with some background, take you through 5 vital steps, and then finish with a list of handy resources.

(I’ll also confess the biggest systematic review mistake that I’ve ever made as a reminder that we all start somewhere when we’re learning!)

Why you should do a systematic review

Before we dig into the juicy details of doing a systematic literature review, let’s get pumped up about why we want to do one in the first place.

Systematic reviews are the best medical evidence…

You might have seen this evidence hierarchy before because it’s well known. The higher up the triangle you go, the more trustworthy the evidence is.

See that point at the top? We’re aiming for that.

Systematic reviews are at the top because they are:

• Objective (not opinion based)
• Comprehensive (include all research on a topic)
• Precise (answer a specific question)
• Reproducible (if you did the exact same thing again then you should get the same result)

…and they’re great for career development…

Give yourself a career boost by publishing your own research. It establishes you as an expert and gives you wider reach, deeper knowledge and extra skills.

It’s also really interesting to research something you feel passionate about!

Literature reviews are an ideal starting point. They’re low cost and don’t need participant recruitment, a big team, or regulatory approval.

Plus they can often be published in high impact journals because they’re the crème de la crème of evidence.

…but only if they’re done right

If you don’t know what you’re doing, it’s easy not to hit the objective, comprehensive, precise and reproducible parts of a systematic review or spend much longer than needed getting there.

So we’re going to go over 5 of the most important steps (which also happen to be the most common mistakes that I see!).

Step 1. Plan like a boss

Here’s an often-repeated life lesson from my Dad…

“Failing to prepare is preparing to fail”

Dad said this a lot in my teens when I hadn’t got my school stuff ready the night before. It probably explains why I’m now super organized.

So how will failing to prepare affect your review?

It will take you soooo much longer to do your review if you don’t plan it well upfront. You’ll repeat steps and retrieve papers and data that you then don’t use.

Worst case scenario is you’ll have to bin everything and start from scratch. I’ve seen this happen more than once and it usually ends in tears and frustration.

We can avoid this by putting together a solid plan before you start

It’s best practice to write a review protocol.

A protocol is really helpful for keeping you on track and making sure you and your collaborators all have the same understanding of what’s happening.

Most journals now also want to see your protocol when you submit your review for publication.

Check out the PRISMA website  for useful information on how to write a systematic review protocol.

You’ll need to include these steps in your protocol

These are the steps you’ll work through to complete your review and what to cover in your protocol.

Step 2. Nail your research question

Us medical statisticians love you to drill down on exactly what your research question is.

That’s because being crystal clear on that will make your research easier to do and easier for other people to understand.

So it massively increases your impact.

This blog post walks you through how to write your research question.

PICO is a tool to make your research question is clear

This stands for:

P – Population or Patient

I – Intervention or Exposure

C – Comparison

O – Outcome you would like to measure

Finding it hard to choose only one research question?

For a systematic review, it’s often best to stick with one research question, but it’s okay to have a few. I usually recommend keeping it to 3 at most.

If you have more than one then always choose one as the primary research question. The others will then be secondary research questions.

It’s best to have as much overlap as you can in the PICO for each question. For example, only change the outcome between questions. Otherwise you’ll have to run multiple searches and screenings.

Step 3. Get the experts in

You can technically do an end-to-end evidence review by yourself.

But you’ll end up with a better review if you involve other people.

Here’s my run down of who to get involved and when.

If it’s not your area of clinical expertise then you’ll want to involve a clinician who knows the subject area well.

They’ll help to refine your research question and give you the background knowledge you need to plan your search criteria.

Clinical librarians are invaluable in helping you to write your search terms.

They’ll help you with general search strategy approaches, like Boolean operators and wild cards. They’ll also be able to help with alternative words, phrases and spellings for your search terms.

If you’re associated with a hospital or university then there’s likely to be a librarian who specializes in literature reviews.

If you don’t have access to a clinical librarian then get in touch as I can support you with this.

Statistician

If you’re doing a review of quantitative data (numbers-based) then you’re going to need to summarise and synthesise the data you find.

You can do this yourself if it’s a straightforward meta-analysis or a statistician can do it for you (picture me jumping up and down with my hand up saying “Pick me! Pick me!”)

Either way, it’s always a good idea to involve a statistician at the protocol writing stage.

We can help you avoid collecting data you don’t need and make sure you collect the data you do need. Then you won’t have to go back and re-do your data extraction whilst your search is getting out of date.

Qualitative researcher

If you’re doing a qualitative review (words-based) instead and you’re not experienced with qualitative analysis then it’s a good idea to bring an expert in here too.

Like a statistician, they’ll be able to help you with the planning, conduct and analysis stages.

Second (and third) reviewer

To hit the gold standard of systematic review, you’ll need 2 reviewers to independently screen articles for inclusion. Any articles where you disagree can then be discussed and agreed between you, or a third reviewer can make the decision.

You’ll then go through the same process of independent review and agreement for the data extraction.

Second reviewer not got time for all of that? They could instead do a quality control of your search and data extraction where they check what you’ve done. Again, you can discuss disagreements or go to a third reviewer.

Step 4. Avoid screening twice by recording everything as you go

I promised to tell you the biggest mistake that i made.

That way, you can avoid doing your literature search twice like I did with my first review.

Once you know, it’s obvious.

So I feel embarrassed confessing this but we’re friends now right.

And I know others have made the same mistake.

Let’s start with the end…

Checklists help you to write a better paper

When you publish a research paper, use a checklist to make sure you include everything you need.

The PRISMA checklist is the best one for systematic reviews.

I’d recommend using it in the planning stage as well to make sure you’re covering everything that you’re going to need to report on later. It’s no coincidence that PRISMA have tools for both protocol writing and reporting.

The PRISMA statement also has a flow chart

The flow chart shows each stage of your literature review, such as how many initial articles you found from each source, how many were excluded at the title/abstract screening stage (first pass), how many were excluded at the full paper screening stage (second pass), and more.

Can you guess what my mistake was yet?

That’s right. I didn’t track those screening stages so I had no way of completing the PRISMA flow chart.

I had to do ALL of the searching again.

This is such a simple mistake to avoid with some basic data management. Save each step of your search as you go.

You don’t need a fancy tool for this. Excel or a reference management software, like EndNote, work well. And keep a note of any inclusion/exclusion decisions you make because you’ll need to summarise them in your paper too.

Step 5. Do your data extraction the right way

You’ve ran your searches, retrieved the papers and decided which ones are eligible. Now we’ve got to get the relevant data out of the paper so it can be analysed.

This is called data extraction

You can extract straight into Excel or onto a paper copy of your data extraction form and then type that into Excel. I find it easiest to extract onto paper first, but try both and go with whichever works best for you.

There are 3 types of information you’ll need to extract

• Basic information about the paper (author, data, study type, location etc)
• Data needed for your planned analysis
• Information for quality/risk of bias assessment

I’m focusing on quantitative data because I’m a statistics lady.

A lot of this also applies to qualitative data, but please check with a qualitative expert before you start extracting to save yourself headaches down the line!

Data extraction is a big topic

So here I’m going to focus on common mistakes.

Mistake 1… The gigantic spreadsheet

The point is to extract relevant data. Not to re-arrange the contents of the paper into your spreadsheet. Re-visit your research question and consult with your statistician to check what you actually need. Otherwise you might spend hours extracting data that is never used.

Mistake 2… Missing information

The opposite of this is where you don’t extract vital information and have to go back to the paper to pull it out. Broken record shout out: Your statistician can help with this!

Mistake 3… Forgot to pilot the data extraction form

Once you’ve written your data extraction form, use it with 2 or 3 papers to see how well it works. You’re looking to see how logical the flow is, whether you’re able to capture all the information you need, and whether it’s clear what should be extracted.

Then go back and revise your data extraction form based on how you got on. Use your revised data extraction form for all of the data extraction, including the papers you piloted.

Mistake 4… The un-analysable spreadsheet

I might have made that word up?! But the concept is real. It’s a spreadsheet that’s such a mess, you have to spend days tidying it up before you can do anything with it. I’ve got a blog post  on how to avoid that.

Super useful resources

Here’s a quick recap of the things we’ve talked about that you should do to avoid common mistakes when doing a systematic review…

• Write a protocol before you start
• Write down a super clear research question using PICO
• Get expert help in where you need it
• Record details of your screening process as you go
• Make sure you extract all of the data that you need (and avoid data you don’t need) into a well-thought out spreadsheet

There’s lots out there to help you

Here’s a list of some of my favourite resources.

Planning – PRISMA Protocol , PICO , PROSPERO

Searching – Cochrane Library , PubMed , Google Scholar , Embase

Storing – EndNote Web

Retrieving – DeepDyve , Core

Appraising – Cochrane Collaboration’s tool for assessing risk of bias (there are lots of different tools out there so find one that meets your needs)

Reporting – PRISMA Checklist

I’d love to work with you on your systematic review

If you need a systematic review completing as a standalone project or a Clinical Evaluation Report then get in touch to chat through the options.

© 2022 Danielle Bodicoat | All Rights Reserved | Website by Wild Coast Design

📧 [email protected] 

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A Good Leader Will Always Make a Good Manager

A good leader will always make a good manager - literature review example.

• Subject: Management
• Type: Literature review
• Level: College
• Pages: 8 (2000 words)
• Downloads: 0

Extract of sample "A Good Leader Will Always Make a Good Manager"

The paper "A Good Leader Will Always Make a Good Manager" is an outstanding example of a management literature review. This report critically evaluates the statement that “a good leader will always make a good manager”. According to various studies, a good leader is able to manage organizations in the right manner by encouraging increased production and innovation while observing the interests of his employees. This report evaluates how a good leader will always be a good manager in a business organization setting.

Introduction

Normally, organizations refer to their executives and members of boards as the leadership team. However, not all managers or members of the board are leaders though they all influence employees and direct work. Leaders carry out their functions differently as compared to managers hence managers do not always qualify to be leaders.

Leadership is the ability to influence a group of individuals in order to achieve a common goal. On the other hand, management can be defined as the science of planning, organizing, directing, staffing and controlling with the aim of meeting organizational goals and objectives. The statement that a good leader will always make a good manager is true. The qualities of good leadership if possessed by a manager of a business organization will lead to good planning, organizing, directing, staffing and controlling thus leading to the success of an organization according to Kotelnikov (2001).

Effective Thinking by a Good Leader

According to Fenton (1990), a good leader thinks radically and is more emotional thus being able to consider the interests of all stakeholders especially employees while making decisions. Moreover, good leaders make their decisions based on facts but not chauvinism and as a result, they have a preference for innovation. Good leaders usually develop goals for their organizations and ensure that they are attainable and well understood by all internal and external stakeholders. In a business organization, setting goals is one of the major factors that determine success in the market.

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Change management scenario, traits of a good leader, management of self-managed teams, characteristic differences between a manager and a leader, applied management science - making good strategic decisions, manager as a position of authority vs leader as a person with special traits.

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