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3. Contents
• Introduction
• Research - defn. and types, scientific foundation
• Hypothesis – formulation, types
• Steps in conducting research
• Sampling techniques
• Data - types and measuring
• Study designs – descriptive, analytical, experimental
• Ethical issues
• Matching and Bias – types, prevention
• Evidence based hierarchy
• Metanalysis
• Conclusion
• References
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4. Introduction
Why do Research?
- To promote basic knowledge.
- To develop new treatment modalities.
- To inform the public
- For effective planning of available resources.
- For commercial success.
- For intellectual dependence.
- As a partial fulfillment to obtain Master’s
Degree
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5. • Research is a quest for knowledge through diligent search
or investigation or experimentation aimed at the discovery
and interpretation of new knowledge.
-Health research methodology, WHO.
• Research is a careful investigation or inquiry specially
through search for new facts in any branch of knowledge.
-Advanced learners dictionary.
• Research is a systematized effort to gain new knowledge
- Redman and Mory
DEFINITION OF RESEARCH
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6. RESEARCH METHODOLOGY
1. Is a way to systematically
solve the research problem
2. It may be understood as a
science of studying how
research is done
systematically
3. It not only involves research
methods but also extends to
consider the logic behind the
methods
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7. TYPES OF RESEARCH
All research can be broadly classified into
two types:
1. BASIC Vs APPLIED
2. OBSERVATIONAL Vs EXPERIMENTAL
3. QUALITATIVE Vs QUANTITATIVE
4. CONCEPTUAL Vs EMPIRICAL
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8. BASIC Vs APPLIED
• Basic research is also called fundamental research.
It is a search for knowledge without a defined goal
of utility or purpose.
• Applied research is problem oriented and it is
directed toward a defined and purposeful end. It
is done based on a perceived need and helps in
solving an existing problem.
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9. OBSERVATIONAL Vs EXPERIMENTAL
RESEARCH
• There are fundamentally two ways in
which research questions can be
answered:-
• We can observe what naturally happens in
the real world without interfering with it.
( OBSERVATIONAL)
OR
• We can manipulate some aspect of the
environment and observe its effects
( EXPERIMENTAL)
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10. • Qualitative research deals with
subjective aspects which are
qualitative or qualities by nature
which are difficult to quantify.
Eg: Motivation research.
• Quantitative research is based
on the measurement of quantity
or amount. It deals with
objective aspects.
Eg: Material science
research
QUALITATIVE Vs QUANTITATIVE
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11. CONCEPTUAL VS EMPIRICAL
CONCEPTUAL
Research is that related
to some abstract idea or
theory. It is generally
used by philosophers and
thinkers to develop new
concepts or Re-interpret
the existing ones
EMPIRICAL
Research is that in
which experience or
observation alone are
the tools of research.
It is data-based
research and it can be
further verified by
observation or
experimentation.
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12. SCIENTIFIC FOUNDATIONS OF RESEARCH
1) Order
2) Inference & chance
3) Maintenance of probability
4) Hypotheses
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13. ORDER
Research employs an
organized observation of
entities or events which
are classified or ordered
on the basis of common
properties & behaviors.
The commonality among
the observations help in
predictions which carry
to the ultimate become
laws.
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14. INFERENCE & CHANCE
Reasoning or inference is the force of advance in
research. There are two distinct approaches in the
development of inferences
DEDUCTIVE – It moves from the general to the
specific. Hence it does not allow for the element of
chance. It is not used much in health research.
INDUCTIVE – It moves from specific to the
general. There is extrapolation of results from a
sample to the target population. Health research
depends almost entirely upon inductive reasoning.
Hence chance must be fully accounted for.
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15. MAINTENANCE OF PROBABILITY
Maintaining a very high probability & eliminating the
chance occurrence is critical to ensure the validity
of a research.
Techniques used to maintain high probability are-
1. Representative sampling
2. Randomization in selection of study groups
3. Maintenance of comparison groups as controls
4. Blinding procedures
5. Statistical methods
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16. Hypothesis is defined as a presumption, supposition
or assumption derived either out of observation or
reflection.
Hypothesis are carefully constructed statements
generated from inferences & they use argument of
induction.
HYPOTHESIS
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17. METHODS OF GENERATING HYPOTHESIS
Mill’s canons of inductive reasoning are frequently
utilized in the forming of hypothesis. It involves
following methods-
1. The method of difference
2. The method of agreement
3. The method of concomitant variation
4. The method of analogy
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18. MILL’S CANONS OF INDUCTIVE
REASONING
1.Method of difference:
When the frequency of a disease is
markedly dissimilar under two circumstances
and if a factor can be identified in one
circumstance and not in the other, then this
factor either its presence or absence may be
the cause of the disease.
e.g.: Lung cancer and Smoking
Fluoride in water and Caries.
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19. 2. Method of agreement:
If a factor’s presence or absence is
common to number of circumstances that are
found to be associated with the disease then
that factor may be causally associated with
disease.
E.g.: Hepatitis A associated with patient
contact, crowding, poor sanitation etc.
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20. 3. Method of concomitant variation;
( Dose Response effect)
Eg. Decreasing level of Iodine, with increasing
expression of Goiter.
Increasing level of Radiation resulting
in increase in number of Leukemia cases.
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21. 4. Method of analogy
The distribution and frequency of a disease or
effect may be similar enough to that of some
other disease to suggest commonality in
cause.
Eg. Hepatitis B virus infection and cancer
of the liver.
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22. Formulation of hypothesis
• Should specify :
– The population
– Specific cause
– Expected outcome
– Dose response relationship
– Time response relationship
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23. EXAMPLE OF HYPOTHESIS
• E.g. ‘cigarette smoking causes lung
cancer’ – incomplete
• ‘the smoking of 30-40 cig/day causes
lung cancer in 10% of smokers after 20
yrs of exposure’
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24. I.
Directional hypothesis
Non directional hypothesis
II.
Research hypothesis
Null hypothesis
III.
Simple hypothesis
Complex hypothesis
TYPES OF HYPOTHESIS
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25. 1.Directional hypothesis
Is one that specifies not only the existence but the
expected direction of the relationship between
variables.
E.G -
Higher the anterior overjet higher the chances of
anterior teeth fracture.
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26. 2.Non directional hypothesis
Does not stipulate the direction of the relationship.
A. There is an association between the degree of
anterior overjet and anterior teeth fractures.
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27. 1.Research hypothesis (substantive or scientific hypotheses):
Are statements of actual expected relationships
between variables. Those which indicate researchers true
expectations.
Eg; Higher the daily intake of refined sugars higher
the DMFT score in children
2.Null hypothesis ( statistical hypothesis)
state that there is no relationship between the
independent variables and dependent variables.
Eg; there is no relationship between daily intake of
refined sugars and DMFT score in children
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28. 1.Simple hypothesis:
A hypothesis can predict the relationship
between a single independent variable and
a single dependent variable.
2.Complex hypothesis:
It can predict a relationship between two
or more independent variables or two or
more dependent variables.
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29. E) DATA COLLECTION by
1.Mere Observation
2.Intervention followed by observation
PROCEDURAL STEPS IN CONDUCTING RESEARCHPROCEDURAL STEPS IN CONDUCTING RESEARCH
A) CONCEPTUALIZING THE PROBLEM
Need
Background
Rationale
B) FORMULATING THE OBJECTIVES
Generating hypotheses
Testing hypotheses
C) DESIGNING THE APPROACH
Research design
Methods and materials
D) DEFINING THE POPULATION
Target population
Study population
F) ANALYSIS & INTERPRETATION
OF RESULTS
G) REPORTING OR
PUBLICATION OF THE STUDYwww.indiandentalacademy.com
30. Sampling
• Sampling is the process or technique of
selecting a sample of appropriate
characteristics and adequate size.
• The individuals, records, units or time are
considered to be elements in the sample.
• An element is the unit of observation or unit
about which information is collected and
which is the subject of analysis.
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31. Sampling
• The total of the elements of the population
under the survey is called “sampling frame”.
• The sample is drawn from this survey
population and is subset of the sampling
frame.
• The sampling frame may be used in toto for
sampling (simple random sampling) or
may be divided into sub-groups or strata
decided by age, sex, class (stratified
sampling);
or the frame may consist of areas or
clusters of big units containing smaller units
( cluster & multistage sampling).
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32. Advantages of Sampling:
1) Sampling reduces the cost of investigation, the time
required and the number of personnel involved.
2) Sampling is especially important when the tests used
are highly technical or detailed or must be
administered or interpreted by experts.
3) Sampling allows thorough investigation of the units of
observation.
4) It is obvious that a sample can be covered more
adequately and in more depth in a research project
than can a total population.
Therefore, Sampling is a more cost efficient way of
collecting data.
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33. Requisites for a Reliable Sample
1) Efficiency - Ability of the sample to yield the desired
information.
2) Representativeness - inferences drawn from the sample
can be generalized to that population with measurable
precision and confidence.
3) Measurability - The design of the sample should be such
that valid estimates of its variability can be made. In other
words, the investigator should be able to estimate the
extent to which the findings from the sample are likely to
differ from what we would have found had we studied the
entire parent population.
4) Size - A sample should be large enough to minimize sample
variability to allow estimates of the population
characteristics to be made with measurable precision.
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34. 5) Coverage - Adequate coverage of the sample is essential if
it is to remain representative. High rates of refusal,
unavailability, loss of follow up and other missing data can
render a sample unrepresentative of the parent population.
6) Goal Orientation - Sample selection and estimation
procedures should be oriented towards the study objectives
and research design and considerations.
7) Feasibility - The design should be simple enough to be
carried out in practice.
8) Economy and Cost Efficiency - The sample should therefore
yield the desired information within expected but tolerable
limits of sampling error for the lowest cost.
Requisites for a Reliable Sample
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36. Probability samples
Probability samples are those in which it is possible to ascertain the
probability that a unit of the population is included in the sample.
The common types of probability samples are :-
i) Simple Random Sampling -
It guarantees that each member of the population has an
equal chance of being included in the sample.
•The two common methods of random sampling are lottery and
tables of random numbers.
• The lottery method assigns numbers to the population; these
numbers are then thoroughly mixed and a sufficient number
drawn (without replacement) to provide the desired sample
size.
•Tables of random numbers are used after numbers (eg-
sequential counts) have been assigned to members of the
study population. www.indiandentalacademy.com
37. ii) Systematic Sampling-
The first unit is chosen at random and then other
units for the sample are chosen in a systematic way.
eg:- every other person or every fifth person.
iii) Stratified Random Sampling-
It is obtained by using the following procedure:-
The population to be sampled is divided into groups known as
strata, such that each group is homogeneous in its
characteristic.
A simple random sample is then drawn from each stratum. This
type of sampling is used when the population is
heterogeneous with regard to the characteristic under
study. Eg:- population divide into different age groups and
then samples are selected from the groups randomly.
This method ensures more representativeness, provides
greater accuracy and can concentrate on wider
geographical area. Care must be taken while dividing
the population into strata.www.indiandentalacademy.com
38. iv) Cluster Sampling-
It involves choosing groups of units or clusters at
random. All the units in each group, or samples of
them are then used in the study. Eg:- villages, wards,
school children. This method is simpler and involves
less time and cost, but gives a higher standard error.
v) Multistage Sampling-
The first step is to select the groups or clusters.
Then the sub samples are then taken in as many
subsequent stages as necessary to obtain the desired
sample size.
E.g.:- choice of states within countries --- 4
Choice of districts within states --- 4 and so on.
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39. vi) Multiphase Sampling-
It is used to take basic data from a large
sample and details from sub sample. This is
different from multistage sampling, in which
the same amount of information is obtained
for every unit.
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40. Non probability sampling
i) Accidental or incidental sampling – people who
have assembled in a common place with a common
interest or accidentally are surveyed
eg. Diabetes in football match
ii) Sequential Sampling-
Here a small sample is tested in order to answer
certain questions about the population. If the
questions are not answered, the number of subjects
or units in the sample is increased gradually until
conclusions may be drawn.
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41. iii) judgment sampling –
Sample selection is based on the judgment of
the person entrusted with the job
iv) Convenience sampling –
Selection is made from available source like
telephone directory, automobile registers,
cards, stock exchange directory etc.
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42. • Discrete:- They are called as attributes. They are
qualitative in nature e.g.: Race, Sex, Religion etc.
• Continuous:- They are also called variables. They are
quantitative in nature.
e.g.: Height, weight, RBC’ count etc.
TYPES OF DATA
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43. Four principal scales :
1.Nominal scale
2.Ordinal scale
3.Interval scale
4.Ratio scale
SCALES OF MEASUREMENT OF DATA
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44. 1. Nominal scale:- This scale
uses names or tags to
distinguish one measurement
from another. It does not
imply magnitude of individual
measurements.
Eg. Classification of sex,
Classification of religion.
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45. Ordinal scale:- it is like nominal scale but
there exists an implicit graded order
relationship among the categories.
Eg. Pain measured as:
Mild – 1
Moderate – 2
Severe – 3
or
Socio economic status measured as
Class I
Class II
Class III
Class IV
Stages of cancer as
I, II, IIIa, IIIb & IVwww.indiandentalacademy.com
46. • Interval scale:
A numerical unit of measurement is used in this scale.
The difference between any two measurements can be
clearly identified in terms of an interval between two
points of scale.
This scale has no true zero point
Eg. Measurement of body temperature in degrees of
Celsius.
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47. Ratio scale
• It is as same as interval
scale in every aspect
except that measurement
begins at a true or
absolute zero.
eg. Weight in Kgs,
Height in Mts.
There cannot be negative
measurements.
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48. EPIDEMIOLOGY
EPI = AMONG DEMOS = PEOPLE LOGOS = STUDY
DEFINITION OF EPIDEMIOLOGY
"Epidemiology is the study of the distribution and
determinants of health-related states or events in
specified populations and the application of this study to
the control of health problems."
(Last, 1988)
-WORLD HEALTH ORGANIZATION
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49. Classification of studies
•Descriptive study
•Analytical study
Cross sectional studyCross sectional study
Case control studyCase control study
Cohort- follow upCohort- follow up
Observational study Experimental study
•Randomised control trials/
clinical trials
• field trial/ community
intervention trial
•Community trial
All these study complement each other
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56. Timing
• Timing concerns whether the health
outcome of interest, and therefore all
study events, has already occurred before
the study actually began.
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60. Descriptive study
• Allows…formulation of hypothesis…
• 1st
phase of an investigation
They ask the question
– When…time dist
– Where…place dist
– Who… person dist
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61. • Procedure in descriptive study
– Defining population to be studied
– Defining disease under study
– Describing distribution by time, person n
place
– Measurement of disease
– Comparing with known indices
– Formulation of etiological hypothesis
Descriptive study
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62. • Def the population
– Age , sex, occupation, culture, characteristics
n similar information
– Population should be large enough
– Stable of migration
– No visitors n relative
Provide denominator for calculating rates,
measurement of frequency, distribution n
determination of disease
Descriptive study
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63. • Def the disease under study
– Precise and valid
– Operational defined…. Identified n measured
• Describing the disease
– Distribution…time, place , person
– Time trends or fluctuations
• Short term fluctuation
• Periodic fluctuation
• Long term fluctuation
Descriptive study
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64. – Place distribution – b/w countries
• Genetic Vs environment
• Role of diet
• Migration changes
• Geographic variations
– Person distribution – natural history
of disease.
Descriptive study
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65. • Measurement of disease :
– Mortality-
– Morbidity-
• incidence – longitudinal stud.
• prevalence - cross sectional stud.
– Disability
• Comparing with known indices
Descriptive study
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66. • Formulation of hypothesis
• Should specify :
– The population
– Specific cause
– Expected outcome
– Dose response relationship
– Time response relationship
• E.g. ‘cigarette smoking causes lung cancer’ –
incomplete
• ‘the smoking of 30-40 cig/day causes lung cancer
in 10% of smokers after 20 yrs of exposure’
Descriptive study
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67. • Uses :
– Data regarding magnitude of disease load
and types of disease problem
– Clues – disease Etiology and helps in
formulation of hypothesis
– Background data – P, O & E curative
services
– Describe variation in disease occurrence by
time, place and person
Descriptive study
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69. Analytical studies
• Second major type of study after descriptive
study.
• Interest – individual…instead of population
• Test a hypothesis
– Determine Statistical association
– Strength of association
• 2 types :
– Case control study
– Cohort study
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72. Case-control study design
Exposure Disease Observer
?
Choose groups with and without
disease, look back at what different
exposures they may have had
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73. Case control studies
• Attempt to make inference from
existing observations (retrospective)
• Compares patients with outcome/disease
with those without and attempts to
identify factors that influenced that
outcome (or caused that disease)
• Important concept: start with the
result (disease) and work backwards
for the cause
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75. Strengths of case-control design
• Best study when have rare disease or
outcome
• Relatively quick and inexpensive
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76. Weaknesses (potential biases)
• Selection (confounding) bias : controls must be as
similar to cases as possible without any
confounding factors
• Berkinsonian bias…rates of adm. to hospital
• Recall bias : cases may be able to remember
events better because of its significance or may
be prompted to remember by investigators
• Survival bias: dead people don’t make it into many
case-control studies; and if they are alive, they
don’t remember things very well
• Interviewer’s bias
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77. Ways to combat weakness
• Matching: for each case, find a control
that looks just like him/her in all other
possible ways except for the disease
(same age, race, economic class, etc.)
• Blinding: individual assessing exposures
should be blinded to whether the person
is a case or control
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78. Types of blinding
• Single blind trial – participant is not
aware whether he belongs to case or
control group.
• Double blind trail – neither doctor nor
participant
• Triple blind trial – participant, doctor
and the person analyzing data
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80. Cohort studies
• Studies whether exposure to a “risk factor”
is associated with a subsequent “outcome”
• Select two populations who seem the same
except for the hypothesized risk factor
• Follow them and see how many have the
outcome or disease
• Important concept: Start with the risk,
then look for the outcome
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81. • Consideration in assembling cohorts
– Free of disease
– Equally susceptible to disease
– Comparable groups
– Diagnostic n eligibility criteria must be
defined before hand
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83. Prospective Cohort study design
Exposure Observer Disease
?
Start with two groups of people who are
exposed and unexposed, follow them to see
who gets disease.
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84. Cohort Study Design (Retrospective/Historical)
Exposure Disease Observer
?
Start with two groups of people who are exposed
and unexposed, find out who got the disease.
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85. Prospective vs. Retrospective Cohort
• Prospective: start with exposed and
unexposed groups, wait for the outcome
• Retrospective: both exposure and
outcome have already happened, but
groups are still made based on exposed or
unexposed
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86. Strengths of cohort study
• Not only can you look at risk, you can
calculate how many people actually get the
disease (incidence rates)
• Since you enroll subjects before the
outcome, you can measure multiple
exposures without recall bias
• Best for rare exposures
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87. Some problems with cohorts
• Time consuming
• Large sample size required
• Expensive
• Attrition of study group
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88. 1.Selection of study subjects
• General population
• Select group…. Special exposure….
Degree or duration of exposure
2.Obtaining data on exposure
• Cohort members
• Review of records
• Medical examination/special tests
• Environmental surveys
Steps of Cohort study
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89. 3.Selection of comparisons group
• Internal comparisons… basis of degree /
levels of exposure
• External comparison with general population
• Periodic medical examination
• Reviewing physician n hospital records
• Surveillance of death record
• Mailed questionnaires, tele calls
4.Follow - up
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90. 5.Analysis
• Incidence rates of outcome among
exposed n unexposed
• Estimate of risk
• Risk estimate done in terms of-
– Relative risk … strength of association b/w
risk factor n disease
– Attributable risk
• In diff in incidence rates of disease b/w exposed
grp n non exposed
• Extent the disease under study can be
attributed to exposure
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91. Relative risk Vs. Attributable risk
• RR is imp in etiological enquires
• Increase in RR … inc cause n effect
association
• AR .. Impact of successful preventive or
public health programme on the problem
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93. Cross-Sectional Study
Advantages:
• Convenient and inexpensive
• Can consider several exposures and several
diseases
• Can generate hypotheses
• Usually represents the general population
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94. Cross-Sectional Study
Disadvantages:
• Cannot establish whether the exposure preceded
disease or disease influenced exposure
• Can identify only prevalent cases rather than
incident cases
• Possible bias since only survivors are available for
study
• May under-represent diseases with short duration
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96. Experimental studies
• Final / definitive step
• Direct intervention
Only Results from Experimental
Studies Can Demonstrate Cause
and Effect Relationships
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97. The investigator through randomization allocates subjects to
different categories of exposure.
BASIC IDEA
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99. 1. To promote “Scientific Proof” of
aetiological factors.
2. To provide a method of measuring
the effectiveness and efficiency of
health services.
Aims of experimental studies
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100. 1. ANIMAL EXPERIMENTS
2. HUMAN EXPERIMENTS
CLASSIFICATION OF EXPERIMENTS
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101. Animal studies are done for the following
purposes
a) Experimental reproduction of human
disease in animals to confirm aetiological
hypothesis.
b) To test the efficacy of various therapeutic
and preventive measures such as vaccines
and drugs.
c) To study the natural history of disease.
Animal experiments are done on carefully bred
animals in controlled environments.
PURPOSES OF ANIMAL STUDIES
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102. 1. Animals are bred in laboratories and
manipulated easily according to
wishes of the experimenter.
2. They multiply rapidly and enable
experimenter to carry out certain
experiments which are not possible
in human beings.
ADVANTAGES
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103. 1. All human diseases cannot be
reproduced in animals.
2. Results of animal studies cannot be
extrapolated to human beings.
LIMITATIONS
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104. 1. They are done on humans and very much
needed to investigate disease etiology.
2. They are also done to evaluate the preventive
and therapeutic measures.
eg. James Lind (1747) – Study done on Sailors
to reveal the association of lemons, oranges in
diet on scurvy among a group of Sailors.
Edward Jenners (1796) experimental work with
Cowpox to develop vaccine against Small pox.
3.Human studies should be carefully designed
because they involve logistic and ethical
implications
HUMAN EXPERIMENTS
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105. They are broadly divided into two types
1. Randomized Controlled Trials
2. Non Randomized Trials
CLASSIFICATION OF EXPERIMENTAL STUDIES
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106. RCT is considered as the gold standard
in epidemiology and perhaps the most
concrete evidence for establishing
association.
RANDOMIZED CONTROLLED TRIALS
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107. Types Of Randomized Controlled Trial
CLINICAL TRIAL
- concerned with evaluating therapeutic agents like
drugs.
PREVENTIVE TRIALS
- purported to prevent or eliminate diseases on an
experimental basis.
RISK FACTOR TRIALS
- A trial of risk factors in which the investigator
intervenes to interrupt the usual sequence in the
development of disease.
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108. 1. Drawing up a protocol
2. Selecting reference and experimental
Populations
3. Randomization
4. Manipulation or Intervention
5. Follow-up
6. Assessment of outcome
STEPS IN RCT DESIGN
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109. Select suitable population
(Reference or Target Population)
Select suitable sample
(Experimental or study population)
Those not eligible
Those who do not
wish to give consent
Make necessary exclusions
RANDOMIZE
Experimental group Control Group
Manipulation & Follow up
Assessment
DESIGN OF A RANDOMIZED CONTROLLED TRIAL
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110. 1. Concurrent Parallel Study
2. Cross-over type of Study
STUDY DESIGNS IN RCT’S
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111. Patients
Random Assignment Exposed to
specific
Treatment
Unexposed to
specific treatment
Observation
Compare
Outcome
Compare
Outcome
Exposed and
Unexposed
to treatment
CONCURRENT PARALLEL STUDY DESIGN
CROSS-OVER TYPE OF STUDY DESIGN
Time
Patients
Random Assignment
Exposed to
specific
Treatment
Unexposed to
specific treatment
Observation
Time
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112. 1. Researcher has ‘control’ over the
intervention (s).
2. Results are ensured.
3. Reliable and well-respected research
design
4. Individual factors can be identified.
ADVANTAGES OF EXPERIMENTAL RESEARCH DESIGNS
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113. 1. Problems in dealing with multiple
causation; isolating individual factors may
over-simplify complex issues.
2. Ethical issues.
3. Researcher bias and subjectivity in
research design, methods and analysis.
4. Hawthorne effect upon groups being
researched .
DISADVANTAGES OF EXPERIMENTAL RESEARCH
DESIGNS
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114. Ethical aspect
• All innovative scientific interventions, whether
diagnostic, prophylactic, or therapeutic should
ultimately be evaluated in human subjects
• The need for safeguards in human experimentation
cannot be overemphasized and several important
codes have been developed for protection of human
subjects
• Three underlying principles are
1. Beneficence, which requires that good should result,
harm should be avoided or that benefits should
justify the expected risk or harm
2. Respect for rights, including free choice of the
subject and protection for those of diminished
autonomy
3. Justice, which requires a equal distribution of
burden and benefits
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115. International Declarations:
• The first code was “ the Nuremberg
Code of 1947”
• This was followed by the “Declaration of
Helsinki” which was adopted by The
World Medical Association and the
W.H.O in 1975.
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116. HELSINKI GUIDELINES:
a) Biomedical research should follow scientific principles and
should be based on adequately performed laboratory and
animal experimentation.
b) The design of each procedure involving humans should be
clearly formulated in an experimental protocol.
c) the experiment should be conducted by scientifically
qualified persons under supervision of medical experts.
d) The right of the research subject to safeguard his/ her
integrity must always be respected.
e) The accuracy of the research results must be preserved.
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117. f) In any research on humans, each subject be informed
about the aim, methods, benefits and potential
hazards of the study.
g) When obtaining informed consent for research, a
doctor should be cautious if the subject is in a
dependant relationship to him/ her.
h) In case of legal competence, informed consent should
be obtained from the legal guardian.
i) Subjects should be informed that they are free to
abstain or to withdraw from participation at any time.
HELSINKI GUIDELINES:
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118. HIERARCHY OF EVIDENCE
SYSTEMATIC REVIEWS &
META ANALYSIS
RCTs
LONGITUDINAL COHORT STUDIES
CASE-CONTROL STUDIES
CROSS SECTIONAL STUDIES
CASE REPORTSwww.indiandentalacademy.com
119. Meta Analysis
• New concept in research
• Coined by Glass in 1976
“Metanalysis is nothing but combining the
results of several clinical studies on the
same subject to derive definitive
conclusions.”
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120. • Like a review article, begins with a
literature review identifying studies of
similar research question.
• Later it attempts to analyze
statistically the aggregate results to
derive a single integrated question
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121. Uses
• It scrutinizes studies to explain why
research results differ
• Identify new direction for research
• Useful in the research of rare diseases
• Decides on the best clinical approach to
the problem
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122. Conclusion
• Thus the study of research procedures and
methods is very important aspect of all post
graduate students and at the same time
provide guidelines on which our future
research would be based.
• It also shows us the procedures that need to
be followed while undertaking research and
also shows us, how the data or findings of our
study should be presented for correct
interpretation and for publication.
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123. References
• Health research methodology : a guide
for training in research methods
- World Health
Organization
• Preventive and social medicine
- K. Park
• Essentials of preventive and community
dentistry
- Soben Peter
• Methods of biostatistics
- T Bhaskara Rao
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