1. An Introduction to Critical
Appraisal
Laura Wilkes
Trust Librarian
West Suffolk Foundation Trust
Laura.Wilkes@wsh.nhs.uk
Last updated May 2012

2. Learning Outcomes
 By the end of this session you will:
o Understand what Critical Appraisal is
o Be aware of some of the different types of research
o Be able to interpret basic statistics within a research paper
o Gain experience in critically appraising a research paper

3. Evidence Based Practice
 “"Evidence-based medicine is
the conscientious, explicit
and judicious use of current
best evidence in making
decisions about the care of
individual patients.”
Sackett, 1996

4. Hierarchy of Evidence

5. Types of Research
 Systematic Reviews
 A literature review focused on a single question which tries to
identify, appraise, select and synthesize all high quality research
relevant to that question.
 Combines results of several RCTs or other types of evidence
 Systematic reviews follow a clear sequence of steps:
 Defining an appropriate question
 Searching the literature – published and unpublished, English & non-
English
 Assessing the studies – involves 2 independent reviewers
 Combining the results & producing a “bottom-line”
 Placing the findings into context
 Advantages
 Limits bias
 Good quality evidence
 Added power by synthesising individual study results

6. Types of Research
 Experimental:
 Randomised Controlled Trials (RCTs)
 Randomly assign individuals to an intervention group or a
control group in order to measure the effectiveness of an
intervention.
 Gold standard for treatment evaluations
 However, some studies are not suitable for RCTs

7. Types of Research
 Observational Studies
 Cohort Studies
 A non-experimental study design
 Follows a group of people (a cohort), and then looks at how
events differ among people within the group.
 Follow up period can be years or decades
 Prospective cohort studies (which track participants
forward in time) are more reliable than retrospective
cohort studies
 Can be expensive to conduct

8. Types of Research
 Observational
 Case-Control Study
 Examines a group of people who have experienced an
event (usually an adverse event) and a group of people who
have not experienced the same event, and looks at what
risk factors both groups have been exposed to
 Retrospective, therefore prone to recall bias, but quick &
involve small numbers
 Primary method of studying new or unusual outcomes
 Case-Series
 Analysis of series of people with the disease
 there is no comparison group

9. Critical Appraisal
 The process of systematically weighing up the quality
and relevance of research to see how useful it is in
decision making
 It is the balanced assessment of benefits and strengths
of research against its flaws and weaknesses
 Increases the effectiveness of your reading
 It can help you make informed decisions
 Is a skill that needs to be practised

10. How do I Appraise?
• You don’t need to be a statistics expert
• Ready-made checklists help you focus on the most
important aspects of the article
 Different checklists available for different types of
research (RCTs, systematic reviews, case-control
studies, etc).
 Checklist for Qualitative research
 Available free from CASP
http://www.casp-uk.net

11. Critical Appraisal
 Critical appraisal of any study design must assess:
Validity
 Were sound scientific methods used?
 Chance / Bias / Confounding Factors
 Results
 What are the results and how are they expressed?
 Relevance
 Are the findings generalisable – can they be applied to
settings / situations outside the research study? Do these
results apply to my local context?

12. Potential Errors of Research
 Chance
 A random error appearing to cause an association between an
intervention and an outcome. Probability of a random error is
estimated using statistics (p values & confidence intervals)
 Bias
 The deviation of results from the truth due to systematic
error in the research methodology
 Selection bias – when two groups being studied differ
systematically in some way
 Observer bias – where there are systematic differences in the
way groups are treated or in how information is collected
 Confounding Factors
 An error of interpretation
 Where part of the observed relationship between two variables
is due to the action of a third variable
 Known confounders: e.g. age, gender, smoking, etc.

13. Critical Appraisal of an RCT
 Screening questions:
 1. Did the study ask a clearly focused research question?
 Patient / Intervention / Outcome
 Is it relevant to you?
 2. Did the authors use an appropriate research method?
 Is an RCT the most appropriate?
 If the answer to these questions is “YES” you can carry
on with the rest of the checklist!

14. RCT Appraisal Checklist continued
 Detailed Questions:
 3. Were participants appropriately allocated to groups?
 Sample:
 Is it representative of the target population (the population to which the
results will be applied)
 Convenience sampling?
 Exclusion / Inclusion criteria – do you agree?
 If too selective results may not be generalisable
 Bias?
 Are the groups balanced?
 Important that groups are similar at the beginning of a trial so there is more
chance of differences at the end being due to the intervention
 Look at the Baseline Characteristics Table
 Was group allocation truly random?
 Bias can occur if patients, carers, or researchers can influence allocation

15. Randomisation
 Randomisation ensures individuals have an equal chance of being
allocated to any Group
 Potential confounding factors will be equally distributed
between groups
 Successful randomisation requires that group allocation cannot be
predicted in advance – allocation concealment avoids bias
 Allocation concealment ensures all those involved in the trial are
unable to predict the allocation of the next participant until that
participant is enrolled. Methods include telephone randomisation,
or using consecutive sealed opaque envelopes.
 A good study should indicate who generated the randomisation
sequence, the method used, and how concealment was achieved
& monitored

16. Randomisation Methods: Computer
Generated Sequence
E.g.:
4,8,3,2,7,2,6,6,3,4,2,1,6,2,0,…….
Two Groups (criterion: even-odd):
AABABAAABAABAAA
Three Groups:
(criterion:{1,2,3}~A, {4,5,6}~B, {7,8,9}~C; ignore 0’s)
BCAACABBABAABA……

17. Permuted Block Randomisation
 Used for small studies to maintain reasonably good
balance among groups
With a block size of 4 for two groups (A,B), there are 6
possible permutations and they can be coded as:
1=AABB, 2=ABAB, 3=ABBA, 4=BAAB, 5=BABA, 6=BBAA
Each number in the random number sequence in turn
selects the next block, determining the next four
participant allocations (ignoring numbers 0,7,8 and 9).
e.g., The sequence 67126814…. will produce BBAA AABB
ABAB BBAA AABB BAAB.

18. Stratified Block Randomisation
 A set of permuted blocks is generated for each
combination of prognostic factors
 E.g. age group, severity of condition, and treatment
centre.
 Stratification means having separate block
randomisation schemes for each combination of
characteristics („stratum‟)
 For example, in a study where you expect treatment
effect to differ with age and sex you may have four
strata: male over 65, male under 65, female over 65
and female under 65

19. Questions continued
 4. Were participants, staff and study personnel “blind” to
participants study group?
 Withholding information about the assigned interventions from people
involved in the trial who may be influenced by this knowledge
 Eliminates error through bias
 Is blinding always possible?
 Different levels of Blinding
 Single- blind Trial
 Either the researcher or the subject is blind to the allocation
 Double-blind Trial
 Both researcher and subject are blinded
 Triple-blind Trial
 Subject, researcher and analyst

20.  5. Were all the participants who entered the trial accounted
for at its conclusion?
 Loss to follow up?
 A common cause of missing data, especially in long-term studies
 How important are the losses?
 5% probably OK but >20% poses threat to validity
 Losses equally distributed?
 Intention to treat analysis?
 Analysing people at the end of the trial, in the groups to which they
were randomised, even if they did not receive the intended
intervention
 Maintains randomisation
 Prevents bias caused by loss of participants
 6. Were all the participants in all groups followed up and data
collected the same way?
 Were groups treated equally?
 Followed over the same time period / received same attention
 Bias?
 Differences in the way data collected, measurements taken etc.
 if individuals know which group they have been allocated to

21.  7. Did the study have enough participants to
minimise the play of chance?
 Before calculating the sample size, a clinically
significant treatment effect is estimated
 POWER Calculation: calculates how large the sample
should be in order to have a high chance of detecting a
true difference between the groups.
 Avoids a type I (false positive) or type II (false negative)
error
 Calculated before the study begins
 Look for 80% - 90% power –probability of finding a
significant difference with a given sample size
 Sample size increases when a small treatment effect is
expected & with higher power.

22. Are the Results Significant?
 8. How are the results presented and what is the
main result?
 What sort of data have they got & have they used
appropriate statistical tests?
 Are the results expressed in terms of likely harm or
benefit?
 Relative Risk
 Numbers Needed to Treat
 How meaningful is the result?

23. Event Rates
Number of people experiencing an event as a proportion of the
number of people in the population
• Form the basis of other calculations
 Control Event Rate (CER)
 Experimental Event Rate (EER)
Emerg Med J 2008 25: 26-29:
Proportion with recurrent headache (whole sample)
 CER = 12/31 = 39%
 EER = 8/30 = 27%

24. Risk of benefit and harm
 Relative Risk (RR) = compares the risk in 2 different groups
of people
 tells us how many times more likely it is that an event will
occur in the treatment group relative to the control group
 EER / CER
 Relative Risk of 1 means the risk is the same in each group
 <1 = treatment reduces risk of event
 >1 = treatment increases risk of event
27/39 = 0.69 = treatment reduces risk of event
Risk of headache is 0.69 times lower in the treatment group
than in the control group.

25. Risk continued
 Absolute risk reduction (ARR)
 Difference in risk between experimental and
control groups
 Risk of Event in Control Group – Risk of Event
in intervention group
 ARR=0 Treatment has no effect
 ARR positive – Treatment is beneficial
 ARR negative – Treatment is harmful
 39% - 27% = 12%
 Dexamethasone reduces the absolute risk of
recurrent headache by 12%

26. Relative Risk Reduction (RRR)
 tells us the reduction in the rate of the outcome in the
treatment group relative to that in the control group
 ARR / CER Or 1 – RR
 0.12 / 0.39 = 0.31 = 31%
 1-0.69 = 0.31 = 31%
 Dexamethasone reduces the risk of recurrent headache
by 31% relative to that occurring in the control group.

27. Absolute Risk Reduction & Relative
Risk Reduction
Results of hypothetical trial of a new drug for
myocardial infarction

28. Compare with Low Risk Patients
 Later studied in a lower risk population:
 10% mortality rate at 30 days among
untreated
 7.5% mortality among treated
 Absolute Risk Reduction is therefore 2.5%
 10% - 7.5% = 2.5%
 Relative Risk Reduction is 25%
 2.5 / 10 = 0.25 = 25%
 Relative Risk Reduction is often more
impressive than Absolute Risk Reduction
 The lower the event rate the smaller the
absolute risk reduction

29. Odds Ratio
 Odds = number of
Headache
headache
No
events / number of non Odds
events
 Odds Ratio = odds in
treatment group / odds
in control group Treatment 8/31 8 23 0.35
 If odds is greater than 1
then the event
(outcome) is more likely Placebo 12/3 12 20 0.6
to happen than not. 2
Odds Ratio = 35/60 = 0.59
Odds of recurrent headache almost 50% less in the
treatment group

30. Numbers Needed to Treat
 Measures the impact of a treatment or intervention
 States how many patients need to be treated in order to
prevent an event which would otherwise occur.
 NNT = 10 means that 10 patients need to be treated to
prevent one adverse outcome
 The closer to 1 the better
 Calculation:
 1 / ARR (if ARR expressed as a proportion)
 100/ARR (if ARR expressed as a %)
 100/12 = 8

31. Results
 9. How precise are the results?
 P Values
 P=Probability
 A p-value is a measure of statistical significance which tells
us the probability of an event occurring due to chance
alone
 P values only from 0 to 1
 If P Value is very small (e.g. P<0.001) the result is unlikely
to be due to chance (1 in 1000)
 Generally, look for P<0.05 (1 in 20)

32. P - values
In simple terms, probability (p-value) can only take values
between 0 and 1:
0|-----------------------|--------------------|1
Impossible…....... Absolutely certain…
If p=0.001 the likelihood of a result happening by chance is extremely
low: 1 in 1000
If p=0.05 it is fairly unlikely that the result happened by chance 1 in 20
If p=0.5 it is fairly likely that the result happened by chance 1 in 2
If p=0.75 it is very likely that the result happened by chance 3 in 4

33. Confidence Intervals
 An alternative way of assessing the effects of
chance
 The result of the trial is a “point estimate” – if
you ran the trial again you will get a different
result
 The Confidence Interval gives the range in which
you think the real answer
 The 95% CI is the range in which we are 95%
certain that the true population value lies
 Look at how wide the interval is, and the values
at each end
 E.g. RR = 0.69 95% CI 0.33 to 1.45

34. Forest Plot – Simple Example
The shorter the
Line of No Effect
Confidence Interval (CI)
Individual sample the more confident we
size
can be that the results
Combined
Results are true
Best Estimate
If the CI crosses the line
of no effect, then the
Confidence Interval results of that study are
not statistically significant
Line of No Effect =
1 for Relative Risk or
Odds Ratio
Favours Treatment Favours Control 0 for Mean results

36. Relevance
 10. Were all important outcomes considered so the
results can be applied?
 Does your local setting / population differ from that in the
research in ways that would produce different results?
 Can you provide the same treatment in your local setting?
 Does any benefit reported outweigh any harm?
 Should policy or practice change as a result of this
research?

37. Is there a Systematic Review on the subject?
…… Check the Cochrane Library
No Cochrane Reviews, but 2 “Other Reviews” – Systematic
Reviews but not produced by the Cochrane Collaboration.

39. Conclusion
 Critical Appraisal is part of Evidence Based Healthcare
 It takes practice
 Use CASP checklists
 Depth of Appraisal is your choice
 Only you can assess usefulness

40. Useful websites
 www.healthknowledge.org.uk/interactive-
learning/finding-and-appraising-the-evidence
 www.thennt.com/
 www.casp-uk.net/
 www.wikipedia.org very good for a basic guide to
statistics in critical appraisal. Search for critical
appraisal.