Anatomy and Physiology of Research

1. Introduction to Clinical Research
&
Concept of Scientific Inquiry
Tamer Hifnawy MD. Dr.PH
Associate Professor
Public Health & Community Medicine
Faculty of Medicine – BSU- Egypt
College of Dentistry Taibah University- KSA
Vice Dean For Quality, Development & International Affairs
Certified Trainer for International Research Ethics

2. What is research?
• Research is a systematic investigation
designed to discover or contribute to a
body of generalisable knowledge.

3. It is important at this point to draw the
line between “research” and
“practice”.

4. Anatomy of Research
What it’s made of?

5. Anatomy of Research:
What it’s made of?
• The structure of a research project is set out in its
Protocol “ The written plan of the study”
• Components of the Protocol:
1. Research Question
2. Background and significance
3. Design
4. Study Subjects
5. Variables
6. Statistical issues

6. Outline of the Study Protocol
Element Purpose
Research Question What question will the study address?
Background and significance Why are these question important?
Design:
•Time frame
•Epidemiological approach
How the study is structured?
Subjects
•Selection Criteria
•Sampling Design
Who are the subjects and how will they be selected?
Variables:
•Predictors variable
•Confounding Variables
•Outcome Variable
What measurement will be made
Statistical issues:
•Hypothesis
•Sample size
•Analytical approach
How large is the study and how will it be analyzed?

7. Research question
• The research question is the objective of the
study.
• The uncertainty of the investigator wants to
resolve.
• Often begin with a general concern that must
be narrowed to a concrete , reasonable issue.

8. Research question
Should people eat more fish?
• This is a good place to start, but the question must be
focused before planning efforts can begin.
• Often this involves breaking the question into more specific
components:
• How often do Saudis eat fish?
• Does eating fish lower the risk of cardiovascular diseases
• Do fish oil supplements have the same effect on CVD as
dietary fish?
• Which Fish oil supplements don’t make people smell like
fish?

9. Research question
• A good research question should pass the “So
What?” test.
• Getting the answer should contribute usefully
to our state of knowledge.
• The Acronym FINER denotes five essential
characteristics of a good research question:

10. Research question
FINER
• Feasible
• Interesting
• Novel
• Ethical
• Relevant

11. Background and Significance
• Set the proposed study in context and gives its
rationale
• What is know about the topic in hand?
• Why is the research question important?
• What kind of answers will the study provide?
• This section cites the previous researches that
are relevant ( including investigator own work)

12. Design
• The design of the study is a complex issue
• Could be Interventional or Non- Interventional
study (Observational Study).
• No one approach is always better than the
others, and each research question requires a
judgment about which design is the most
efficient way to get a satisfactory answer.

13. Design
• The Randomized Control trials (RCTs)is often held
up as the best design for establishing causality
and the effectiveness of the intervention.
• There are many situations for which an
observational study is a better choice or the only
feasible option.
• The relatively low cost of case control studies and
their suitability for rare outcomes make them
attractive for some questions.

14. Design
• A typical sequence for studying a topic begins
with observational studies of a type that is
often called descriptive.
• These studies explore the lay of the land:
– Describing distribution of a disease or a health
related problem in a population
– Usually followed by analytic studies that evaluate
the associations to permit inferences about cause
and effect relationship.

15. Study Subjects
• Inclusion criteria
• Exclusion Criteria
• How to recruit enough people
• Studying a random sample?

16. Variables
• In an analytical study the investigator studies the
associations among variables to predict outcomes
(Predictor variable) and (Outcome variable).
• Clinical trials examine the effect of an
intervention ( a special kind of predictor variable
that the investigator manipulate), this design
allow to observe the effect on the outcome
variable using randomization to control for the
influence of confounding variables (other
predictors of outcome)

17. What do we study in a medical
research?
• The outcome (Coronary Heart Disease).
• The primary exposure (risk factor) (Blood
Cholesterol).
• Other exposures that may influence the
outcome (Age, Sex).

18. Exposures and outcomes
The definition of both the “exposure” and
“outcome” depends on the question you
are asking
The primary exposure (s) is the one(s) included
in your hypothesis

19. Question 1: Does smoking increase the
risk of lung cancer?
Smoking Lung Cancer
exposure outcome

20. Question 2: Is consumption of aflatoxin
associated with increased risk of liver cancer?
Aflatoxin Liver Cancer
exposure outcome

21. Exposures and outcomes
Because you do not
know which
exposures are likely
to be risk factors for
the disease.
i.e. you do not know
which exposures are
“primary”
Because some exposures
may ‘get in the way’
when trying to sort out a
relationship between
primary exposure and
outcomes.
i.e. they may act as
confounding factors
You will need to measure more than one exposure

22. Exposure
Cholesterol level
Outcome
Coronary H.D.
Confounder
Age, Sex
Is exposure to High Cholesterol a risk factor for CHD?

23. Is caffeine consumption during pregnancy associated
with increased risk of low birth weight?
Caffeine during pregnancy Low birth weight
exposure outcome
Smoking during pregnancy
potential confounding factor

24. Exposures and outcomes
An outcome in one study could be the
exposure in another !
Low birth weight Hypertension
exposure outcome

25. Quiz
I am interested in finding out about the relationship
between cancer of the colon and diet.
Question: Which is the outcome ?
Answer: Depends on the research question.
• If question is: how does diet affect risk of developing
cancer colon ?
Outcome = cancer colon
• If question is: how does having cancer colon affect
diet?
Outcome = diet

26. Statistical Issues
• Sample size
• Specifying a hypothesis: 50 to 60 years old women with
CHD who take fish oil supplements will have a lower risk of myocardial
infarction than those who do not.
• Reasonable probability (P- value)
• Power

27. Statistical Issues
• Purely descriptive studies (What proportion of people
with CHD use fish oil supplements?)
• No statistical significance is required and this
do not require a hypothesis, instead, the
number of subject needed to produce a
narrow confidence intervals (CI)for means,
proportions or other descriptive statistics can
be calculated.

28. Physiology of Research
How it works?

29. Physiology of Research
How it works?
• The goal of clinical research is to draw
inferences from findings in the study about
the nature of the universe around.
• Two major sets of inferences are involved in
the interpreting a study.
• Internal validity
• External validity

30. Validity of a research
• Internal validity:
– The degree to which the investigator draws the
correct conclusion about what actually happened
in the study.
• External validity (Generalizability):
– The degree to which these conclusions can be
appropriately applied to people and events
outside the study.

31. Designing the study
• Consider the simple descriptive question:
What is the prevalence of regular use of fish oil
supplements among people with CHD?
• This question can not be answered with perfect
accuracy because it would be impossible to study
all patients with CHD; SO the investigator settles
for a related question that can be answered by
the study:
Among a sample of CHD patients seen in the investigators'
clinic and respond to a questionnaire what proportion
report taking fish oil supplements?

32. Implementing the study
• Sometimes we may get a wrong answer to a
study question because the way the sample
was actually drawn and the measurement
made, differed in important ways from the
way they were designed.
• The difference between the study plan and
the actual study can alter the answer to the
research question

33. Causal inference
• A special kind of validity problem arises in the
studies that examine the association between
a predictor and outcome variable in order to
draw a causal inference
IS smoking cause CHD?

34. The Errors of Research
• No Study is free of errors, and the goal is to
maximize the validity.
• Two main type of errors that interfere with
the research inferences:
– Random errors
– Systematic errors.

35. Random Errors
• A wrong result due to chance.
• Depends on the sample size.
• Can be minimized by increasing the sample
size.

36. Systematic Error
• Is a wrong result due to bias
• Bias: Source of variation that distort the study
findings in one direction.
• An example of a systematic measurement
error is the underestimation of the prevalence
of fish oil use due to lack of clarity in how the
question is phrased.

37. Summary
• The Anatomy of research is a set of tangible
elements that make up the study plan:
research question, its significance, study
design, study subjects and measurement
approach.
• The Physiology of research is how the study
works: internal and external validity, random
(chance) and systematic error (Bias)

38. Conceiving The
Research Question
Introduction to Clinical Research
&
Concept of Scientific Inquiry

39. Conceiving the Research question
• The research question is the uncertainty about
something in the population that the
investigator wants to resolve by making
measurements on the study subjects.

40. Origin of Research Question
• Mastering the literature
• Being alert to new ideas and techniques
– Attend conferences
• Keeping the imagination Roaming
– Careful observation of patients
– Teaching (during presentation and lecture preparation)
• Choosing a Mentor
– Experience

41. Characteristic of a Good Research
Question
• FINER Criteria for a Good Research Question.
–Feasible
–Interesting
–Novel
–Ethical
–Relevant

42. Feasible
• Adequate number of subjects
• Adequate technical expertise
• Affordable in time and money
• Manageable in scope. (You have to narrow the
scope and focus only on the most important goals)

43. Interesting
• It is wise to confirm that you are not the only
one who finds a questions interesting.
• Speak with mentors and outside experts
before devoting substantial energy to develop
plan or grant proposal that peers and funding
agencies may consider dull.

44. Novel
• Contribute to new information
• Reviewing literatures
Ethical
• Research Ethics Committee (REC)/ Institutional Review
Board (IRB)
• Following the international codes of Ethics.
• Autonomy/ Justice/ beneficence

45. Relevant
• Among the Characteristics of a good research
question, none is more important than its
relevance.
• A good way to decide about relevance is to
imagine the various outcome that are likely to
occur.
• Discuss with experts in the field.

46. HYPOTHESIS TESTING

47. HYPOTHESIS
• In statistics, is a claim or statement about
some population parameter (basically, a
good guess).
• The hypothesis may or may not be true
(there’s only one way to find out)….
• That’s what we are trying to figure out.

48. Research Hypothesis
o The research process begins with a
hypothesis about the relationship
between two occurrences. E.g.,
 People who smoke are more likely to get
lung cancer than people who do not
 Post-menopausal women treated with
Hormone replacement therapy (HRT) are less
likely to have MI than women who are not.

49. Research Hypothesis
• An assumed answer to the study question.
• The study has either to:
»Prove the hypothesis
»Disprove the hypothesis
• Research hypotheses depend on the current
state of knowledge and technology in a specific
field of study.

50. Research Hypothesis
o After formulation of the research hypothesis in
scientific methodology, the research hypothesis
is not tested directly.
o Instead we start with an assumption that there is
no difference or association between the
variables compared. This is called the null
hypothesis (H0 ).
o The null hypothesis is thus the contrary to the
research hypothesis (also termed alternative
hypothesis H1 ).

51. The NULL Hypothesis
• Null = Zero (in German language)
• No difference between compared groups (in
statistical science)

52. The NULL Hypothesis
• Assumes that the difference you observe is due
to chance (H0).
• When the significance test result shows that
(P≤ 0.05) this means:
1. The difference is significant
2. Reject the null hypothesis
3. Accept the alternative hypothesis (H1)
4. The observed difference is not due to chance
5. Find out what the difference signifies

53. Research Hypothesis
o In scientific methodology, even if a difference or
an association is found, it should be assumed
that it is due to chance, until it is proven, by
statistical analysis, that it is unlikely to be
explained by chance.
o The research hypothesis is accepted by exclusion
if the statistical test rejects the null hypothesis.

54. Difference
Observed Difference
Height Signifies;
 Age difference
 Sex difference
 Hormonal effect
 Nutritional effect
 Genetic effect
Is it normal biological variation (CHANCE)?

55. HYPOTHESIS TESTING AND
PROBABILITY
• Most statistical analyses in medicine involves
hypothesis testing, i.e. the probability, (P) that:
–The null hypothesis (H0) is A=B
–The alternative hypothesis (H1) is A B

56. HYPOTHESIS TESTING AND
PROBABILITY
• The P value:
–“the probability of obtaining the value of the
observed statistic (e.g. a difference between the
means of two groups, or a difference between
two proportions) or ones of more extreme
value, if the null hypothesis is true”.
–i.e. the probability that a difference or an
association as large as the one observed could
have occurred by chance alone.

57. P – VALUE
• So, we examine the probability of the observed
difference (and all the ones that are more extreme).
• If this probability P ≤ 0.05 (the Type I probability)
we conclude that the null hypothesis is false and it
should be rejected.
• So, a P value ≤ 0.05 leads to rejection of the null
hypothesis, while a P value > 0.05 indicates that
probability of type I error is high and we can not
reject the null hypothesis.

58. Poor
Man
500,000 $ 1000 $
1,000,000 $

59. Null hypothesis and alternative hypothesis
There is no difference between the means of two
compared groups (this shown difference would be
expected to occur by chance)
Null hypothesis
Alternative hypothesis
There is a difference between the means of the two
groups

60. Alpha error (Type I error):
• P value (traditionally levels of 0.05 are used
for statistical significance)
• It indicates the probability of rejecting the
statistical hypothesis tested when in fact,
that hypothesis is true.
ART

61. Beta error (Type II error):
• the probability that the test will accept the
hypothesis tested when in fact, it is false. It
measures the power of the test. =(1-B error)
• Power of the test: probability of rejecting the null
hypothesis when it is false.
BAF

62. EXAMPLE
It may be concluded on the basis of the results
that a new treatment is better when in fact it is
not better than the standard treatment
Type I error
Randomized control trial of drugs

63. On the other hand, a new treatment, that
is actually effective may be concluded to
be ineffective
Type II error

64. Type I error (P-value)
Level of significance
of the test

65. P < 0.05 ??
P<0.001
P>0.05
P<0.01P<0.05
P<0.0001

66. Type II error Power of the test

67. Remember:
• Be sure of the distribution of your data before doing
any statistical analysis to choose the right statistical
test.
P -value Statistical
significance