Research Methods Orientation Guide

ORIENTATION TO
RESEARCH METHODS

COVERAGE
• WRITING A RESEARCH PROPOSAL
• REVIEW OF RESEARCH DESIGNS
• PROBLEM FORMULATION AND DISSECTION
• IDENTIFICATION OF VARIABLES
• OBJECTIVE SETTING
• HYPOTHESIS FORMULATION
• BIAS AND CONFOUNDERS
• REVIEW OF MEDICAL LITERATURE

COVERAGE
• SELECTION OF STUDY POPULATION
• SAMPLING TECHNIQUES; SAMPLE SIZE CALCULATION
• DATA COLLECTION, SOURCES, AND METHODS
• INSTRUMENT DEVELOPMENT
• DATA PRESENTATION
• RESEARCH DESIGN FRAMEWORK
• DATA ANALYSIS - DESCRIPTIVE STATISTICS
• DATA ANALYSIS - INFERENTIAL STATISTICS

RESEARCH
• “A SYSTEMATIC INVESTIGATION, INCLUDING RESEARCH DEVELOPMENT,
TESTING AND EVALUATION, DESIGNED TO DEVELOP OR CONTRIBUTE TO
GENERALIZABLE KNOWLEDGE”
• A BROAD DEFINITION THAT MAY INCLUDE BIOMEDICAL RESEARCH,
EPIDEMIOLOGICAL STUDIES, AND HEALTH SERVICES RESEARCH, AS WELL
AS STUDIES OF BEHAVIORAL, SOCIAL, AND ECONOMIC FACTORS THAT
AFFECT HEALTH.

IMPORTANCE OF RESEARCH
• IT CAN PROVIDE IMPORTANT INFORMATION ABOUT:
• DISEASE TRENDS AND RISK FACTORS
• OUTCOMES OF TREATMENT OR PUBLIC HEALTH INTERVENTIONS
• FUNCTIONAL ABILITIES
• PATTERNS OF CARE
• HEALTH CARE COSTS AND USE

• IT CAN LEAD TO SIGNIFICANT DISCOVERIES
• DEVELOPMENT OF NEW THERAPIES
• IMPROVEMENT IN HEALTH CARE AND PUBLIC HEALTH

• MEDICAL RESEARCH CAN HAVE AN ENORMOUS IMPACT ON
HUMAN HEALTH AND LONGEVITY
• IT LEADS TO INDIVIDUAL BENEFITS OF IMPROVED HEALTH
• THE RESULTING INCREASED PRODUCTIVITY OF THE POPULATION
CONTRIBUTES GREATLY TO THE NATIONAL ECONOMY

• SCIENCE TODAY IS CHANGING RAPIDLY AND BECOMING MORE
COMPLEX, SO NO SINGLE RESEARCHER OR SINGLE SITE CAN BRING ALL
THE EXPERTISE TO DEVELOP AND VALIDATE MEDICAL INNOVATIONS OR
TO ENSURE THEIR SAFETY.
• THUS, EFFICIENT SHARING OF INFORMATION BETWEEN INSTITUTIONS
HAS BECOME EVEN MORE IMPORTANT THAN IN PREVIOUS ERAS, WHEN
THERE WERE FEWER NEW THERAPIES INTRODUCED.

STAGES OF THE RESEARCH PROCESS
1. IDENTIFYING THE PROBLEM
2. REVIEWING LITERATURE
3. SETTING RESEARCH QUESTIONS, OBJECTIVES, AND HYPOTHESES
4. CHOOSING THE STUDY DESIGN
5. DECIDING ON THE SAMPLE DESIGN
6. COLLECTING DATA
7. PROCESSING AND ANALYZING DATA
8. WRITING THE REPORT

(1) IDENTIFYING THE RESEARCH PROBLEM
• THE FIRST AND FOREMOST TASK IN THE ENTIRE PROCESS OF SCIENTIFIC RESEARCH IS TO
IDENTIFY A RESEARCH PROBLEM.
• A WELL-IDENTIFIED PROBLEM WILL LEAD THE RESEARCHER TO ACCOMPLISH ALL-IMPORTANT
PHASES OF THE RESEARCH PROCESS, STARTING FROM SETTING OBJECTIVES TO THE SELECTION
OF THE RESEARCH METHODOLOGY.

• WE HAVE COUNTLESS PROBLEMS AROUND US, BUT ALL THAT WE ENCOUNTER DO NOT
QUALIFY AS RESEARCH PROBLEMS, AND THUS, THESE DO NOT NEED TO BE RESEARCHED.
• KEEPING THIS POINT IN VIEW, WE MUST DRAW A LINE BETWEEN A RESEARCH PROBLEM AND A
NON-RESEARCH PROBLEM.

• RESEARCHABLE PROBLEMS ARE THOSE WHO HAVE A POSSIBILITY OF
THOROUGH VERIFICATION INVESTIGATION, WHICH CAN BE EFFECTED
THROUGH THE ANALYSIS AND COLLECTION OF DATA, WHILE THE NON-
RESEARCH PROBLEMS DO NOT NEED TO GO THROUGH THESE PROCESSES.

(2) REVIEWING THE LITERATURE
• A REVIEW OF RELEVANT LITERATURE IS AN INTEGRAL PART OF THE RESEARCH
PROCESS. IT ENABLES THE RESEARCHER TO FORMULATE HIS PROBLEM IN TERMS
OF THE SPECIFIC ASPECTS OF THE GENERAL AREA OF HIS INTEREST THAT HAS
NOT BEEN SO FAR RESEARCHED.

(2) REVIEWING THE LITERATURE
• SUCH A REVIEW, NOT ONLY PROVIDES HIM EXPOSURE TO A LARGER BODY OF
KNOWLEDGE BUT ALSO EQUIPS HIM WITH ENHANCED KNOWLEDGE TO
EFFICIENTLY FOLLOW THE RESEARCH PROCESS.
• THROUGH A PROPER REVIEW OF THE LITERATURE, THE RESEARCHER MAY
DEVELOP THE COHERENCE BETWEEN THE RESULTS OF HIS STUDY AND THOSE
OF THE OTHERS.

(3) SETTING THE RESEARCH QUESTION, OBJECTIVES,
AND HYPOTHESES
• AFTER DISCOVERING AND DEFINING THE RESEARCH PROBLEM, RESEARCHERS
SHOULD MAKE A FORMAL STATEMENT OF THE PROBLEM LEADING TO
RESEARCH OBJECTIVES.

(3) SETTING THE RESEARCH QUESTION, OBJECTIVES,
AND HYPOTHESES
• AN OBJECTIVE WILL PRECISELY SAY WHAT SHOULD BE RESEARCHED, TO DELINEATE
THE TYPE OF INFORMATION THAT SHOULD BE COLLECTED AND PROVIDE A
FRAMEWORK FOR THE SCOPE OF THE STUDY. THE BEST EXPRESSION OF A RESEARCH
OBJECTIVE IS A WELL-FORMULATED, TESTABLE RESEARCH HYPOTHESIS.
• A HYPOTHESIS IS AN UNPROVEN STATEMENT OR PROPOSITION THAT CAN BE
REFUTED OR SUPPORTED BY EMPIRICAL DATA. HYPOTHETICAL STATEMENTS ASSERT A
POSSIBLE ANSWER TO A RESEARCH QUESTION.

(4) CHOOSING THE STUDY DESIGN
• THE RESEARCH DESIGN IS THE BLUEPRINT OR FRAMEWORK FOR FULFILLING
OBJECTIVES AND ANSWERING RESEARCH QUESTIONS.
• IT IS A MASTER PLAN SPECIFYING THE METHODS AND PROCEDURES FOR
COLLECTING, PROCESSING, AND ANALYZING THE COLLECTED DATA.

(4) CHOOSING THE STUDY DESIGN
• THE TYPE OF RESEARCH DESIGN TO BE CHOSEN DEPENDS PRIMARILY ON FOUR
FACTORS:
• THE TYPE OF PROBLEM
• THE OBJECTIVES OF THE STUDY
• THE EXISTING STATE OF KNOWLEDGE ABOUT THE PROBLEM THAT IS BEING
STUDIED
• THE RESOURCES ARE AVAILABLE FOR THE STUDY

(5) DECIDING ON THE SAMPLE DESIGN
• SAMPLING IS AN IMPORTANT AND SEPARATE STEP IN THE RESEARCH PROCESS. THE
BASIC IDEA OF SAMPLING IS THAT IT INVOLVES ANY PROCEDURE THAT USES A
RELATIVELY SMALL NUMBER OF ITEMS OR PORTIONS (CALLED A SAMPLE) OF A
UNIVERSE (CALLED POPULATION) TO CONCLUDE THE WHOLE POPULATION.
• IT CONTRASTS WITH THE PROCESS OF COMPLETE ENUMERATION, IN WHICH EVERY
MEMBER OF THE POPULATION IS INCLUDED. SUCH A COMPLETE ENUMERATION IS
REFERRED TO AS CENSUS.

• A POPULATION IS THE TOTAL COLLECTION OF ELEMENTS ABOUT WHICH WE WISH TO
MAKE SOME INFERENCE OR GENERALIZATION.
• A SAMPLE IS A PART OF THE POPULATION, CAREFULLY SELECTED TO REPRESENT THAT
POPULATION. IF CERTAIN STATISTICAL PROCEDURES ARE FOLLOWED IN SELECTING
THE SAMPLE, IT SHOULD HAVE THE SAME CHARACTERISTICS AS THE POPULATION AS A
WHOLE. THESE PROCEDURES ARE EMBEDDED IN THE SAMPLE DESIGN.

• SAMPLE DESIGN REFERS TO THE METHODS TO BE FOLLOWED IN SELECTING A
SAMPLE FROM THE POPULATION AND THE ESTIMATING TECHNIQUE, VIS-A-VIS
FORMULA FOR COMPUTING THE SAMPLE STATISTICS.

(6) COLLECTING DATA
• THE GATHERING OF DATA MAY RANGE FROM SIMPLE
OBSERVATION TO A LARGE-SCALE SURVEY IN ANY DEFINED
POPULATION. THERE ARE MANY WAYS TO COLLECT DATA.

(6) COLLECTING DATA
• THE APPROACH SELECTED DEPENDS ON THE OBJECTIVES OF THE STUDY,
THE RESEARCH DESIGN, AND THE AVAILABILITY OF TIME, MONEY, AND
PERSONNEL.
• WITH THE VARIATION IN THE TYPE OF DATA (QUALITATIVE OR
QUANTITATIVE) TO BE COLLECTED, THE METHOD OF DATA COLLECTION
ALSO VARIES.

(7) PROCESSING AND ANALYZING DATA
• DATA PROCESSING GENERALLY BEGINS WITH THE EDITING AND
CODING OF DATA. DATA ARE EDITED TO ENSURE CONSISTENCY
ACROSS RESPONDENTS AND TO LOCATE OMISSIONS, IF ANY.

• BECAUSE IT IS IMPRACTICAL TO PLACE RAW DATA INTO A REPORT,
ALPHANUMERIC CODES ARE USED TO REDUCE THE RESPONSES TO A
MORE MANAGEABLE FORM FOR STORAGE AND FUTURE PROCESSING.
• THIS CODING PROCESS FACILITATES PROCESSING THE DATA. THE
COMPUTER OFFERS AN EXCELLENT OPPORTUNITY IN DATA EDITING AND
CODING PROCESSES.

• DATA ANALYSIS USUALLY INVOLVES REDUCING ACCUMULATED DATA TO A
MANAGEABLE SIZE, DEVELOPING SUMMARIES, SEARCHING FOR PATTERNS, AND
APPLYING STATISTICAL TECHNIQUES FOR UNDERSTANDING AND INTERPRETING
THE FINDINGS IN THE LIGHT OF THE RESEARCH QUESTIONS.
• FURTHER, THE RESEARCHER, BASED ON HIS ANALYSIS, DETERMINES IF HIS FINDINGS
ARE CONSISTENT WITH THE FORMULATED HYPOTHESES AND THEORIES.

• THE TECHNIQUES TO BE USED IN ANALYZING DATA MAY RANGE FROM SIMPLE
GRAPHICAL TECHNIQUE TO VERY COMPLEX MULTIVARIATE ANALYSIS DEPENDING
ON THE OBJECTIVES OF THE STUDY, RESEARCH DESIGN EMPLOYED, AND THE
NATURE OF DATA COLLECTED.
• AS IN THE CASE OF METHODS OF DATA COLLECTION, AN ANALYTICAL TECHNIQUE
APPROPRIATE IN ONE SITUATION MAY NOT BE APPROPRIATE FOR ANOTHER.

(8) WRITING THE REPORT
• THE ENTIRE TASK OF A RESEARCH STUDY IS ACCUMULATED IN A
DOCUMENT CALLED A PROPOSAL.
• A RESEARCH PROPOSAL IS A WORK PLAN, PROSPECTUS, OUTLINE,
AN OFFER, A STATEMENT OF INTENT OR COMMITMENT FROM AN
INDIVIDUAL RESEARCHER OR AN ORGANIZATION.

• THE PROPOSAL WILL BE PREPARED TO KEEP IN VIEW THE SEQUENCE PRESENTED IN THE RESEARCH
PROCESS. THE PROPOSAL TELLS US WHAT, HOW, WHERE, AND TO WHOM IT WILL BE DONE.
• IT MUST ALSO SHOW THE BENEFIT OF DOING IT. IT ALWAYS INCLUDES AN EXPLANATION OF THE
PURPOSE OF THE STUDY (THE RESEARCH OBJECTIVES) OR A DEFINITION OF THE PROBLEM.
• IT SYSTEMATICALLY OUTLINES THE PARTICULAR RESEARCH METHODOLOGY AND DETAILS THE
PROCEDURES THAT WILL BE UTILIZED AT EACH STAGE OF THE RESEARCH PROCESS.

• THE END GOAL OF A SCIENTIFIC STUDY IS TO INTERPRET THE RESULTS AND
DRAW CONCLUSIONS.
• TO THIS END, IT IS NECESSARY TO PREPARE A REPORT AND TRANSMIT THE
FINDINGS AND RECOMMENDATIONS TO ADMINISTRATORS, POLICYMAKERS,
AND PROGRAM MANAGERS FOR THE INTENDED PURPOSE OF MAKING A
DECISION.

• AT A BARE MINIMUM, A RESEARCH REPORT SHOULD CONTAIN SECTIONS ON:
• AN EXECUTIVE SUMMARY;
• BACKGROUND OF THE PROBLEM;
• LITERATURE REVIEW;
• METHODOLOGY;
• FINDINGS;
• DISCUSSION;
• CONCLUSIONS AND
• RECOMMENDATIONS.

• THE RESULTS OF THE STUDY CAN ALSO BE DISSEMINATED THROUGH PEER-
REVIEWED JOURNALS PUBLISHED BY ACADEMIC INSTITUTIONS AND REPUTED
PUBLISHERS BOTH AT HOME AND ABROAD.
• THESE JOURNALS HAVE THEIR FORMAT AND EDITORIAL POLICIES. THE
CONTRIBUTORS CAN SUBMIT THEIR MANUSCRIPTS ADHERING TO THE POLICIES
AND FORMAT FOR POSSIBLE PUBLICATIONS OF THEIR PAPERS.

• MANY INTERESTING STUDIES HAVE BEEN CONDUCTED BY THE RESEARCHERS
WITHOUT HAVING ANY EFFECT IN ACTUAL SETTINGS. IDEALLY, THE
CONCLUDING STEP OF A SCIENTIFIC STUDY IS TO PLAN FOR ITS UTILIZATION
IN THE REAL WORLD.

• ALTHOUGH RESEARCHERS ARE OFTEN NOT THEMSELVES IN A POSITION TO
IMPLEMENT A PLAN FOR UTILIZING RESEARCH FINDINGS, THEY CAN
CONTRIBUTE TO THE PROCESS BY INCLUDING IN THEIR RESEARCH REPORTS A
FEW RECOMMENDATIONS REGARDING HOW THE RESULTS OF THE STUDY
COULD BE UTILIZED FOR POLICY FORMULATION AND PROGRAM
INTERVENTION.

RESEARCH PROCESS
The research process often begins with a very broad
idea for a topic you’d like to know more about. You
do some preliminary research to identify a problem.
After refining your research questions, you can lay
out the foundations of your research design, leading
to a proposal that outlines your ideas and plans.

[1] CHOOSE YOUR TOPIC
First you have to come up with some ideas.
Your research topic can start out very broad. Think
about the general area or field you’re interested in
– it’s often a good idea to choose a topic that you
already know a bit about.

Do some reading to begin narrowing down your
topic.
Look for the top journals in your field and skim
through some recent issues. If an article interests
you, check the reference list to find other relevant
sources.

As you read, take notes and try to identify
problems, questions, debates, contradictions and
gaps. Your aim is to narrow down from a broad area
of interest to a specific niche.

Make sure to consider the practicalities: the
requirements of your program, the amount of time
you have to complete the research, and how
difficult it will be to access sources and data on the
topic.

It’s important that your topic is interesting to you,
but you’ll also have to make sure it’s academically,
socially or practically relevant.

Academic relevance means that the research can fill a
gap in knowledge or contribute to a scholarly debate in
your field.
Social relevance means that the research can advance
our understanding of society and inform social change.
Practical relevance means that the research can be
applied to solve concrete problems or improve real-life
processes.

The easiest way to make sure your research is
relevant is to choose a topic that is clearly
connected to current issues or debates, either in
society at large or in your academic discipline.
The relevance must be clearly stated when you
define your research problem.

[2] IDENTIFY A PROBLEM
So you’ve settled on a topic and found a niche – but
what exactly will your research investigate, and
why does it matter?
To give your project focus and purpose, you have to
define a research problem.

The problem might be a practical issue.
Alternatively, you might choose to investigate a
theoretical problem.
To put the problem in context and set your
objectives, you can write a problem statement.
This describes who the problem affects, why
research is needed, and how your research project
will contribute to solving it.

A research problem is a specific issue, difficulty,
contradiction, or gap in knowledge that you will
aim to address in your research. You might look for
practical problems aimed at contributing to change,
or theoretical problems aimed at expanding
knowledge.

As you discuss and read about your topic, look for
under-explored aspects and areas of concern,
conflict or controversy. Your goal is to find a gap
that your research project can fill.

If you are doing practical research, you can identify a
problem by reading reports, following up on previous
research, and talking to people who work in the
relevant field or organization.
Theoretical research focuses on expanding knowledge
and understanding rather than directly contributing to
change. You can identify a research problem by reading
recent research, theory and debates on your topic to
find a gap in what is currently known about it.

Theoretical problems often have practical
consequences, but they are not focused on solving
an immediate issue in a specific place (though you
might take a case study approach to the research).

[3] Formulate Research Questions
Next, based on the problem statement, you need to
write one or more research questions. These target
exactly what you want to find out. They might focus
on describing, comparing, evaluating, or explaining
the research problem.

[3] Formulate Research Questions
A strong research question should be specific
enough that you can answer it thoroughly using
appropriate qualitative or quantitative research
methods. It should also be complex enough to
require in-depth investigation, analysis, and
argument.

[4] Set Objectives
In general, research objectives describe what
we expect to achieve by a project. Research objectives
are clear, concise, declarative statements which
provide direction to the investigation or the study.
Research objectives describe concisely what the
research is trying to achieve. They summarize the
accomplishments a researcher wishes to achieve
through the project and provides direction to the study.

[4] Set Objectives
Research objectives are usually expressed in lay terms
and are directed as much to the client as to the
researcher. Research objectives may be linked with a
hypothesis or used as a statement of purpose in a study
that does not have a hypothesis.
Even if the nature of the research has not been clear to
the layperson from the hypotheses, he should be able
to understand the research from the objectives.

[4] Set Objectives
Research objectives should be closely related to the
statement of the problem and summarize what the
researcher hopes will be achieved by the study.
The objectives focus on the ways to measure the
variables under study.

[4] Set Objectives
The general objective of the study states what the
researcher expects to achieve in general terms.
The specific objectives break down the general
objective into smaller, logically connected parts
that systematically address the various aspects of
the problem. The specific objectives should specify
exactly what will be done in each phase of the
study, how, where, when and for what purpose.

[4] Set Objectives
A good objective must be SMART:
Specific
Measurable
Attainable
Realistic
Time Bound

[5] Formulate Hypothesis
A research hypothesis is a statement of
expectation or prediction that will be tested by the
research.
The hypothesis is a statement of the specific
relationship the researcher expects to find from
examination of the variables.

A hypothesis states the predictions about what the
research will find.
It is a tentative answer to the research question
that has not yet been tested. For some research
projects, several hypotheses might be needed to
address different aspects of the research question.

The hypothesis must be testable – it must be verifiable and
falsifiable. Researchers must be able to test whether a
hypothesis is true or false.
To be considered testable:
▪ There must be a possibility to prove that the hypothesis is
true.
▪ There must be a possibility to prove that the hypothesis is
false.
▪ The results of the hypothesis must be reproducible.

The hypothesis must state an expected relationship
between variables.
The independent and dependent variables to be
studied must be identified, and the hypothesis must
state the nature of the relationship that exists
between the variables.

The hypothesis must be consistent with the existing
body of knowledge.
A hypothesis is not just a guess — it should be based
on existing theories and knowledge.

The hypothesis must be parsimonious – that is stated in
a simple and concise statement. It is better to be
concise than to be longwinded.
It is also better to have several simple hypotheses than
one complicated hypothesis.
However, be careful not to make the hypothesis to
specific nor too general.

Do not include references to specific measures in
the hypothesis.
Do not refer to specific statistical procedures that
will be used in the analysis.

[6] Create Research Design
The research design is a practical framework for
answering your research questions. It involves
making decisions about the type of data you need,
the methods you’ll use to collect and analyze it,
and the location and timescale of your research.

There are often many possible paths you can take to
answering your questions. The decisions you make
will partly be based on your priorities.

You need to decide whether you will use primary or
secondary data and qualitative or quantitative
methods.
You also need to determine the specific tools,
procedures, and materials you’ll use to collect and
analyze your data, as well as your criteria for
selecting participants or sources.

[7] Write Research Proposal
The proposal outlines the context, relevance,
purpose, and plan of your research.
As well as outlining the background, problem
statement, and research questions, the proposal
should also include a literature review that shows
how your project will fit into existing work on the
topic. The research design section describes your
approach and explains exactly what you will do.

Epidemiological Studies
All epidemiological studies can be divided into
observational and experimental studies.
Observational studies observe and measure the
effects on disease rates of exposures of interest (as
they occur in the population). They are further
subdivided in Descriptive and Analytical studies.

The image shows the tree of possible designs,
branching into subgroups of study designs by
whether the studies are descriptive or analytic and
by whether the analytic studies are experimental or
observational.

The first distinction is whether the study is analytic
or non-analytic.
A non-analytic or descriptive study does not try to
quantify the relationship but tries to give us a
picture of what is happening in a population, e.g.,
the prevalence, incidence, or experience of a
group.

Descriptive studies include case reports, case-
series, qualitative studies and surveys (cross-
sectional) studies, which measure the frequency of
several factors, and hence the size of the problem.

An analytic study attempts to quantify the
relationship between two factors, that is, the effect
of an intervention (I) or exposure (E) on an outcome
(O).
To quantify the effect we will need to know the rate
of outcomes in a comparison (C) group as well as
the intervention or exposed group.

Whether the researcher actively changes a factor
or imposes uses an intervention determines whether
the study is considered to be observational (passive
involvement of researcher), or experimental (active
involvement of researcher).

In experimental studies, the researcher manipulates
the exposure, that is he or she allocates subjects to
the intervention or exposure group.

Experimental studies, or randomised controlled
trials (RCTs), are similar to experiments in other
areas of science. That is, subjects are allocated to
two or more groups to receive an intervention or
exposure and then followed up under carefully
controlled conditions.

Such studies controlled trials, particularly if
randomised and blinded, have the potential to
control for most of the biases that can occur in
scientific studies but whether this actually occurs
depends on the quality of the study design and
implementation.

In analytic observational studies, the researcher
simply measures the exposure or treatments of the
groups. Analytical observational studies include
case-control studies, cohort studies and some
population (cross-sectional) studies. These studies
all include matched groups of subjects and assess of
associations between exposures and outcomes.

Observational studies investigate and record
exposures (such as interventions or risk factors) and
observe outcomes (such as disease) as they occur.
Such studies may be purely descriptive or more
analytical.

Studies can incorporate several design elements.
For example, the control arm of a randomised trial
may also be used as a cohort study; and the
baseline measures of a cohort study may be used as
a cross-sectional study.

Problem Formulation and Dissection,
Objective Setting
and Identificationof Variables

References
• Designing Clinical Research 3rd Edition by Hulley S., Cummings S.
et.al.
• Introduction to Health Research in the Health Sciences-5th Ed. By
Polgar S, Thomas S 2010
• Clinical Epidemiology: The Essentials, 5th Ed. Fletcher R., Fletcher
S.
• Painless Evidence Based Medicine by Dans AL., Dans LF., Silvestre
A., 2008
• World Health Organization, Health Research Methodology, 2nd
Edition

Objectives
• Discuss the different parts of a research
• Formulate a relevant research question and topic
• Discuss the different types of research variables

Parts of Research
• Introduction
• Statement of the problem
• Hypothesis
• Objectives
• Theoretical/Conceptual Framework
• Assumptions
• Scope and limitations
• Definition of terms

plus
• Abstract
• Title Page
• Dedication
• Acknowledgement
• Table of Contents
• List of Tables and Figures
• Reference/ Bibliography
• Appendices

Research Topicand Problem
•Research topic
•A general area of study or issue
•Research problem
•The more specific question

1.Does it really interest me?
2.Can it be answered with scientific inquiry?
3.Do I have the resources?
4.Are there irresolvable ethical problems?
5.Is it theoretically or practically important?
6.FINER
Important Questions about the Research Problem

FINER
FEASIBLE
• adequate number of subjects
• adequate technical expertise
• affordable in time and money
• manageable in scope
INTERESTING - to the investigator
NOVEL
• confirms or refutes previous
findings
• extends previous findings
• provides new findings
ETHICAL
RELEVANT
• to scientific knowledge
• to clinical and health policy
• to future research directions

Stating the Research Problem
•Format in stating a research question
•Population
•Intervention/Maneuver/ Exposure
•Control
•Outcome of interest
•Methods

Basic Guidelines for Clear Writing
1. State the problem clearly and completely
2. Express thought fully with least words possible
3. Keep the sentence short
4. Look critically at each thought. Do the words say exactly what
you want them to say? Read carefully phrase by phrase. Throw
out superfluous (more than is needed and wanted) and unnecessary
words
5. Avoid foggy and generalized statement
6. Edit! Edit! Edit!

Research Objectives
• Objectives guide the investigator during the process of
formulating research questions and hypothesis
• They will also help in the prioritization process
• They will enable the reader or consumer of the work to
judge whether the investigator had achieved these
objectives or not

The research objectives should be:
1. closely related to the research question
2. covering all aspects of the problem
3. very specific
4. ordered in a logical sequence
5. stated in action verbs that could be evaluated e.g. to
describe, to identify, to measure, to compare, etc.
6. achievable, taking into consideration the available
resources and time
7. mutually exclusive, with no repetitions or overlaps

Action Verbs to Avoid
• … to know …
• … to understand …
• … to really understand …
• … to fully appreciate …
• … to internalize …
• … to grasp the significance of …
• … to have an awareness of …

Research Objectives
•Properly formulated, specific objectives will
facilitate the development of your research
methodology and will help to orient the collection,
analysis, interpretation and utilization of data

Formulation of Research Objectives
• General Objectives
• Specific Objectives

The General Objective
• states what researchers expect to achieve by the study in
general terms.
• advisable to break down a general objective into smaller,
logically connected parts. These are normally referred
to as specific objectives.

The Specific Objectives
• should systematically address the various aspects
(dimensions) of the general objective.
• should specify what you will do in your study, where
and for what purpose.

Research Variables
Typesof Variables
1. Independent (Treated or Manipulated)
2. Dependent (Response or Effect)
3. Confounding (Intervening, extraneous)
4. Background Variables (Demographics)

Independent Variable
• variable that causes the change in the dependent variable
• input or the stimulus
• explain the variation in the event of interest
• this is the cause or the treatment
• what the researcher manipulates
• may have more than one independent variable

Dependent Variable
• Variable that measures what is being
explained
• the “Outcome” or the “Effect”

Confounding Variables
• Variables that are not included in the research or held
constant, but would have a probable impact on the
outcome on the outcome of the research

Typesof Confounding
• Extraneous – any variable other than the IV that could
cause a change in the DV
• Intervening – variables that arise during the course of
research and can be difficult to control which can alter the
results of the research

Intervening Variables
• Extraneous variables are all those that are not
of direct interest to the researcher but that
could affect the variables measured

Hypothesis Formulationand
Errorsin Research (Biasand Confounding)

References
• Designing Clinical Research 3rd Edition by Hulley S., Cummings S.
et.al.
• Introduction to Health Research in the Health Sciences-5th Ed. By
Polgar S, Thomas S 2010
• Clinical Epidemiology: The Essentials, 5th Ed. Fletcher R., Fletcher S.
• Painless Evidence Based Medicine by Dans AL., Dans LF., Silvestre A.,
2008
• World Health Organization, Health Research Methodology, 2nd
Edition

Objectives
• Discuss the different types of hypothesis
• Identify the different errors in research

Research Hypothesis
• a tentative explanation for certain behaviors, phenomena or events,
which have occurred or will occur
• Shrewd or intelligent guess about a phenomenon or event that can
happen (Webster)

Hypothesis
• a statement that describes the relationship between two or more
variables allowing for the relationship to be tested empirically
• Research Hypothesis
• states the true expectation of results
• prediction of the outcome of the study
• Statistical Hypothesis
• states no difference between groups
• way to test the research hypothesis

Simple Versus Complex Hypotheses
Simple hypothesis
expresses a predicted
relationship between one
independent variable and one
dependent variable
Complex hypothesis
states a predicted relationship
between two or more
independent variables and/or two
or more dependent variables

Directional vs. Non-directional Hypotheses
Directional hypothesis
Predicts the direction or
outcome of a relationship
Non-directional hypothesis
Predicts the existence of a
relationship, not its direction

HYPOTHESES: Examples
•Research hypothesis:
If, then - If age is a factor in total blood cholesterol then
the nurse should observe clear differences between the
blood pressure results from the older and younger groups

Statistical hypothesis
Null hypothesis
• H0 : There is no difference
between the two groups.
Alternative hypothesis
• H1: There is a difference
between the two groups

Guidelines
• in experimental investigation, the hypothesis should be
explicit
• in descriptive and historical, it may not be explicitly
expressed
• the hypothesis is stated in the “null” form
• it is formulated from the research question

Hypothesis Formulation and Errorsin Research
All analytic studies must begin with a clearly formulated
hypothesis
The hypothesis must be quantitative and specific
• it must predict a relationship of a specific size

• A poor example:
“Babies who are breast-fed have less illness than babies who are
bottle-fed”
Which illnesses? How is feeding type defined? How large a
difference in risk?
• A better example:
“Babies who are exclusively breast-fed for three months or more will
have a reduction in the incidence of hospital admissions for
gastroenteritis of at least 30% over the first year of life”

Only specific prediction allows one to draw legitimate conclusions from
a study which tests a hypothesis
But even with the best formulated hypothesis, two types of errors can
occur
• Type 1 - observing a difference when in truth there is none
• Type 2 - failing to observe a difference when there is one

These errors are generally produced by one or more of the
following:
1. Random Error
2. Random Misclassification
3. Bias
4. Confounding

1. Random Error
• deviation of results and inferences from the truth, occurring
only as a result of the operation of chance
• can produce Type 1 or Type 2 errors

Exampleof Random Error
• By chance, there are more episodes of gastroenteritis in the bottle-
fed group in the study sample, producing a Type 1 error (when in truth,
breastfeeding is not protective against gastroenteritis)
• or, also by chance, no difference in risk was found, producing a Type
2 error (when in truth, breastfeeding is protective against gastroenteritis)

2. Random (Non-differential) Misclassification
• Random error applied to the measurement of an exposure
or outcome
• Errors in classification can only produce type 2 errors,
except if applied to a confounder or to an exposure
gradient

Exampleof Random Misclassification
• Lack of good information on feeding history results in some
breast-feeding mothers being randomly classified as bottle-
feeding, and vice-versa
• If this happens, the study finding underestimates the true
relative risk (RR), whichever feeding modality is associated
with higher disease incidence, producing a Type 2 error

3. Bias
• Systematic, non-random deviation of results and inferences
from the truth, or processes leading to such deviation
• Any trend in the collection, analysis, interpretation,
publication or review of data that can lead to conclusions
which are systematically different from the truth (Dictionary of
Epidemiology, 3rd ed.)

Exampleof Bias
• The medical records of bottle-fed babies only are less
complete (perhaps bottle fed babies go to the doctor less often)
than those of breast-fed babies, and thus record fewer
episodes of gastro-enteritis in them only
• This is called “bias” because the observation itself is in error

4. Confounding
• A problem resulting from the fact that one feature of study subjects
has not been separated from a second feature, and has thus been
confounded with it, producing a spurious result
• The spuriousness arises from the effect of the first feature being
mistakenly attributed to the second feature
• Confounding can produce either a Type 1 or a Type 2 error, but we
usually focus on Type 1 errors

Exposure Outcome
Third variable
Confounding
• To be a confounding factor, two conditions must be met ...
1. be associated with exposure without being the
consequence of exposure
2. be associated with outcome independently of exposure (not
an intermediary)

Coffee Coronary Heart Disease
Smoking
Confounding
• Smoking is correlated with coffee drinking and a
risk factor even for those who do not drink coffee

Example of Confounding
• The mothers of breast-fed babies are of higher social class, and the
babies thus have better hygiene, less crowding and perhaps other
factors that protect against gastroenteritis
• Crowding and hygiene are truly protective against gastroenteritis,
but we mistakenly attribute their effects to breast feeding
• This is called confounding because the observation is correct, but its
explanation is wrong

Key Principlein Biasand Confounding
• The factor that creates the bias, or the confounding
variable, must be associated with both the independent
and dependent variables (i.e. with the exposure and the disease)
• Association of the bias or confounder with just one of the
two variables is not enough to produce a spurious result

in the example just given …
the BIAS, namely incomplete chart recording, has to be associated with
feeding type (the independent variable) and also with recording of
gastroenteritis (the dependent variable) to produce the false result
the CONFOUNDING VARIABLE (or CONFOUNDER) better hygiene, has to
be associated with feeding type and also with gastroenteritis to
produce the spurious result

• were the bias or the confounder associated with just the
independent variable or just the dependent variable, they would not
produce bias or confounding
This gives a useful rule …
• If you can show that a potential confounder is NOT associated with
either one of the two variables under study (exposure or outcome),
confounding can be ruled out

Biasand Confounding:the difference
• Bias creates an association that is not true
• Confounding describes an association that is true, but
potentially misleading

Protection against Random Error
and Random Misclassification
• Random error can work to falsely produce an association
(Type 1 Error) or falsely not produce an association (Type 2
Error)
• We protect ourselves against random misclassification
producing a Type 2 error by choosing the most precise and
accurate measures of exposure and outcome

Protectionagainst Type 1 Errors
• We protect our study against random type 1 errors by establishing
that the result must be unlikely to have occurred by chance (e.g. p <
0.05)
• p-values are established entirely to protect against type 1 errors due
to chance, and do not guarantee protection against type 1 errors
due to bias or confounding
• This is the reason we say statistics demonstrate association but not
causation

Protectionagainst Type 2 Errors
We protect our study against random Type 2 errors by
• providing adequate sample size, and
• hypothesizing large differences
The larger the sample size, the easier it will be to detect a true
difference, and the largest differences will be the easiest to detect
(imagine how hard it would be to detect a 1% increase in the risk of gastroenteritis
with bottle-feeding)

Two (2) Waysto Increase Power
The sample size needed to detect a significant difference is called the
power of a study
1. Choosing the most precise and accurate measures of exposure and
outcome has the effect of increasing the power of our study, because
of variances of the outcome measures, which enter into statistical
testing, are decreased
2. Having an adequate-sized sample of study subjects

Research Methods Orientation Guide

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