How to Read a Paper: The Basics of
Evidence-based Medicine by Trisha
Greenhalgh
Outstanding Text
How to Read a Paper is one of the bestselling texts on evidence-based
medicine, used by health care professionals and medical students
worldwide. Trisha Greenhalgh’s ability to explain the basics of evidence-
based medicine in an accessible and readable way means the book is an
ideal introduction for all, from first year students to experienced
practitioners.
This is a text that explains the meaning of critical appraisal and terms such
as numbers needed to treat, how to search the literature, evaluate the
different types of papers and put the conclusions to clinical use.
New features of the third edition include:

New discussion putting evidence-based medicine into the current context,
with more emphasis on patient perspectives
Increased coverage of qualitative research in evidence-based medicine
New information on literature sources and search mechanisms
Personal Review: How to Read a Paper: The Basics of
Evidence-based Medicine by Trisha Greenhalgh
This is a very readable and informative book on how to read and assess
medical research papers. The author touches on something broadly
applicable to almost any field, and that is how to exercise critical thinking,
how to ask the right questions, what logical traps to avoid. This is so
doctors don't get fooled by eager pharmaceuticals representatives; Also,
for patients to educate themselves in Bayesian statistics so they can
overcome their doctors flawed tests recommendations. This book will also
help researchers conduct their own experiment in integer ways to derive
informative results for society at large. It will also help policymakers not
being fooled by flawed research studies.
The author has been criticized for not often technically describing the
statistical tests she refers to. But, this was not the author's purpose. She
states right upfront in the preface, if you want to dig deep into the
technicalities get Clinical Epidemiology: A Basic Science for Clinical
Medicine. The author has conveyed something more important than
providing another treaty in statistical epidemiology. Frankly, if you are
interested in the various statistical tests, Wikipedia will do just fine. But,
what tests to use when and how are very important considerations she
addresses with much expertise. What analytical framework and
methodology to use in what research situation. How to judge if such
research conducted by others used inappropriate frameworks. Those are
tough issues often more difficult to handle proficiently than conducting
statistical tests.
She provides extensive information on related subjects. Her introduction
to Bayesian statistics in chapter seven is really clear. She explains the
likelihood ratio in the most straightforward way I have seen yet. Her
chapter on economic analysis is surprisingly insightful as she defines all
the different types of such analysis. Appendix I consists in a very rich set
of checklists for finding, appraising, and implementing [medical] evidence.
It is a good reference guide to the entire material within the book. Her
chapter on statistics for the non-statisticians is outstanding. She actually
teaches you a lot about statistics without going into the math. She even
uncovers several traps that many professional statisticians may fall into
especially when blinded by economic interests. Her discussion on
distinguishing causation from correlation or regression is well thought out.

In summary, this book offers a lot of valuable qualitative information to
better interpret quantitative research for both the layperson and the expert
alike.
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