General Research and methodology (Unit-1)

GENERAL RESEARCH
METHODOLOGY
By:
Ms. Falguni Goel
Assistant Professor
MIET, Meerut

COVERED SYLLABUS
◦General Research Methodology: Research, objective,
requirements, practical difficulties, review of literature,
study design, types of studies, strategies to eliminate
errors/bias, controls, randomization, crossover design,
placebo, blinding techniques.

GENERAL RESEARCH METHODOLOGY
◦ Research
◦ Research comprises “creative and systematic work
undertaken to increase the stock of knowledge,
including knowledge of humans, culture and society,
and the use of this stock of knowledge to devise new
applications.”
OECD 2015
-- Frascati Manual 2015

Key Objectives of Research
◦ Exploration and Discovery: To uncover new phenomena, patterns, relationships, and principles in the
natural world and human society.
◦ Explanation and Understanding: To develop theories, models, and frameworks that explain observed
phenomena and provide insights into underlying mechanisms.
◦ Problem-Solving and Innovation: To identify and address practical problems, develop new
technologies, and create innovative solutions.
◦ Knowledge Generation and Dissemination: To contribute to the body of knowledge and share research
findings with the wider community.
◦ Decision Making and Policy Formulation: To inform evidence-based decision making and policy
formulation in various sectors.

REQUIREMENTS
◦ Clear and Well-Defined Research Questions: The research questions should be specific, focused, and achievable
within the scope of the study. They should guide the selection of research methods, data collection procedures,
and analysis techniques.
◦ Appropriate Research Design: The research design should be chosen carefully to address the research questions
effectively. Different research designs, such as quantitative, qualitative, or mixed-methods designs, serve different
purposes and require different approaches.
◦ Rigorous Data Collection Methods: Data collection methods should be reliable, valid, and unbiased. They should
be appropriate for the research questions and the target population.
◦ Systematic Data Analysis: Data analysis should be conducted in a systematic and transparent manner. Appropriate
statistical techniques or qualitative analysis methods should be used to extract meaningful insights from the data.

REQUIREMENTS
◦ Ethical Considerations: Ethical principles should be upheld throughout the research process. Informed consent,
confidentiality, and respect for participants' rights are paramount.
◦ Clear and Concise Reporting: Research findings should be reported in a clear, concise, and transparent manner.
The report should include a detailed description of the research methodology, data analysis, and interpretation of
findings.
◦ Validity and Generalizability: The research findings should be assessed for validity and generalizability. Validity
refers to the extent to which the findings accurately reflect the phenomenon being studied. Generalizability refers
to the extent to which the findings can be applied to a broader population.
◦ Peer Review and Dissemination: Research findings should be subjected to peer review by experts in the field to
ensure their rigor and credibility. Findings should be disseminated through publications, presentations, and other
means to contribute to the body of knowledge and inform practice.

TYPES OF RESEARCH
◦ Descriptive vs Analytical Research
◦ Descriptive research is concerned with describing and understanding the characteristics of a phenomenon
or population. It aims to gather information about what is happening, who is involved, and when, where,
and how it is happening. Descriptive research often involves collecting data through surveys, observations,
and interviews.
◦ Analytical research, on the other hand, goes beyond description to explain the reasons or causes behind
observed phenomena or relationships. It aims to identify patterns, correlations, and causal relationships
between variables. Analytical research often involves using statistical techniques to analyze data and test
hypotheses.

TYPES OF RESEARCH
◦ Quantitative vs Qualitative Research
◦ Quantitative research is concerned with collecting and analyzing numerical data to quantify relationships,
trends, and patterns. It often involves using surveys, experiments, and statistical techniques to measure
variables and test hypotheses. Quantitative research aims to provide generalizable findings that can be
applied to a broader population.
◦ Qualitative research, on the other hand, focuses on understanding the experiences, meanings, and
perspectives of individuals or groups. It often involves collecting data through interviews, observations,
and document analysis. Qualitative research aims to provide in-depth insights into individual or group
experiences and understandings.

TYPES OF RESEARCH
◦ Conceptual vs Empirical Research
◦ Conceptual research is concerned with developing and refining theories, models, and frameworks. It
involves using logic, reasoning, and critical thinking to analyze existing knowledge and develop new
conceptual frameworks. Conceptual research often involves literature reviews, theoretical discussions, and
case studies.
◦ Empirical research, on the other hand, is concerned with collecting and analyzing data to test hypotheses
and develop theories. It involves conducting experiments, surveys, observations, and other data collection
methods to gather empirical evidence. Empirical research often involves statistical analysis, hypothesis
testing, and model building.

Research Type Description Objectives Methods Examples
Descriptive Research Focuses on describing and
understanding the characteristics of a
phenomenon or population.
To gather information about the what,
who, when, where, and how of a
phenomenon.
Surveys, observations,
interviews
- Describing the demographics of a population -
Identifying the most common symptoms of a
disease - Understanding the prevalence of a
particular behavior
Analytical Research Aims to explain the reasons or causes
behind observed phenomena or
relationships.
To identify patterns, correlations, and
causal relationships between variables.
Statistical analysis,
hypothesis testing,
experiments
- Examining the relationship between smoking
and lung cancer - Determining the effectiveness
of a new drug therapy - Understanding the
factors that contribute to academic achievement
Applied Research Seeks to solve practical problems and
improve conditions in the real world.
To develop new technologies,
interventions, or solutions to address
specific problems.
Field studies, pilot studies,
clinical trials
- Developing a new vaccine for a disease -
Implementing a new educational program -
Designing a more efficient transportation system
Fundamental Research Driven by curiosity and the desire to
expand our knowledge and
understanding of the natural world or
human society.
To develop new theories, models, and
principles that explain fundamental
phenomena.
Literature reviews,
theoretical discussions,
case studies
- Understanding the origins of the universe -
Exploring the nature of consciousness -
Deciphering the genetic code
Quantitative Research Emphasizes the collection and
analysis of numerical data to quantify
relationships, trends, and patterns.
To provide generalizable findings that
can be applied to a broader population.
Surveys, experiments,
statistical analysis
- Analyzing the relationship between income and
education - Comparing the effectiveness of two
different teaching methods - Measuring the
impact of a new policy
Qualitative Research Focuses on understanding the
experiences, meanings, and
perspectives of individuals or groups.
To provide in-depth insights into
individual or group experiences and
understandings.
Interviews, observations,
document analysis
- Exploring the lived experiences of people with
disabilities - Understanding cultural beliefs and
practices - Analyzing historical documents
Conceptual Research Concerned with developing and
refining theories, models, and
frameworks.
To advance our understanding of a
phenomenon through logical reasoning
and analysis.
Literature reviews,
theoretical discussions,
case studies
- Developing a new theory of organizational
behavior - Refining a model of language
acquisition - Proposing a new framework for
understanding social inequality
Empirical Research Involves collecting and analyzing data
to test hypotheses and develop
theories.
To provide empirical evidence to support
or refute theoretical propositions.
Experiments, surveys,
observations, statistical
analysis
- Testing the effectiveness of a new drug therapy
- Examining the relationship between stress and
health - Evaluating the impact of a social
intervention

SIGNIFICANCE
◦ Enhance Rigor and Reliability: Research methodology promotes rigor by establishing clear guidelines and procedures for conducting
research. It ensures that research is conducted in a systematic, consistent, and replicable manner, minimizing biases and errors.
◦ Address Research Questions Effectively: Research methodology guides researchers in selecting appropriate research designs, data
collection methods, and analysis techniques that align with their research questions.
◦ Facilitate Interpretation and Generalizability: Research methodology provides a framework for interpreting research findings in the
context of existing knowledge and theoretical frameworks. It also helps researchers assess the generalizability of their findings,
determining the extent to which they can be applied to a broader population or context.
◦ Promote Ethical Conduct: Research methodology emphasizes the importance of ethical principles throughout the research process. It
guides researchers in obtaining informed consent, protecting confidentiality, and respecting the rights of participants.
◦ Enhance Credibility and Impact: Research methodology contributes to the credibility and impact of research studies. Rigorous and
ethical research methods enhance the trustworthiness of findings, increasing their likelihood of being accepted by the scientific
community and influencing practice or policy.

PRACTICAL PROBLEMS
◦ General research methodology is a broad framework that outlines the steps involved in conducting research. It can be
applied to a wide range of research projects, from small-scale studies to large-scale investigations. However, there are a
number of practical difficulties that researchers may encounter when using general research methodology. These
difficulties can range from logistical challenges to conceptual issues.
◦ Jones (2019) discusses the common practical difficulties that researchers encounter when using general research
methodology. The author identifies five key challenges: resource constraints, time constraints, access to data, ethical
considerations, and methodological challenges. Jones provides strategies for overcoming each of these challenges. For
example, the author suggests that researchers carefully plan their research projects to make the most of limited resources,
and that they seek funding opportunities to support their research. Jones also suggests that researchers collaborate with
other researchers to share resources and expertise.

PRACTICAL PROBLEMS
◦ Logistical Challenges
◦ Resource constraints: Research can be expensive, and researchers often have limited resources. This can
make it difficult to collect data, analyze results, and disseminate findings.
◦ Time constraints: Research projects can take a long time to complete. This can be a challenge for researchers
who are also teaching, working full-time, or have other commitments.
◦ Access to data: Researchers may have difficulty accessing the data they need. This can be due to privacy
concerns, data security measures, or the cost of data access.
◦ Ethical considerations: Researchers must carefully consider the ethical implications of their research. This
includes protecting the privacy of participants, avoiding harm, and obtaining informed consent.

PRACTICAL PROBLEMS
◦ Conceptual Issues
◦ Choosing a research method: There are a variety of research methods available, and each method has its
own strengths and weaknesses. Researchers must carefully choose the method that is best suited for their
research question and design.
◦ Measuring variables: Research variables must be clearly defined and measured in a way that is reliable
and valid. This can be difficult, especially for complex or abstract concepts.
◦ Analyzing data: Researchers must choose the appropriate data analysis techniques for their research
question and data type. This can be a complex and challenging task.
◦ Interpreting results: Research results must be interpreted carefully and with caution. Researchers must
consider the limitations of their study and avoid drawing unwarranted conclusions.

REVIEW OF LITERATURE
◦ A review of literature (ROL) is a
comprehensive summary and critical
analysis of existing research on a
particular topic. It's like a roadmap that
helps you navigate the vast landscape of
knowledge in your field and identify
where your own research fits in.

Types Of ROL
◦ Unveiling the Three Faces of ROL: Narrative, Systematic, and Meta-Analysis
◦ The review of literature (ROL) is a multifaceted tool, and choosing the right type depends
on your research goals. Let's delve into the three main types:
I. Narrative
II. Systematic and
III.Meta-analysis
Lets see how they each shine:

1. The Storyteller: Narrative Review
◦ Think of the narrative review as a captivating storyteller. It weaves together key findings from various studies, creating a
comprehensive picture of your topic. It highlights important themes, identifies controversies, and points out gaps in knowledge.
◦ Strengths:
◦ Flexibility: Can cover a broad topic without getting bogged down in methodology.
◦ Insightful: Offers a qualitative understanding of the field, highlighting major trends and debates.
◦ Efficient: Requires less time and resources compared to other types of ROL.
◦ Challenges:
◦ Subjectivity: Susceptible to author bias in selection and interpretation of studies.
◦ Limited scope: May not cover all relevant research due to its broader focus.
◦ Difficulty in assessing quality: Lacks a rigorous, replicable methodology.

2. The Detective: Systematic Review
◦ The systematic review plays detective, meticulously searching for and analyzing all relevant research on your topic. It uses
a pre-defined protocol to identify, select, appraise, and synthesize studies. This ensures transparency and minimizes bias.
◦ Strengths:
◦ Objectivity: Reduces bias through a rigorous and replicable methodology.
◦ Comprehensiveness: Aims to identify all relevant studies, providing a complete picture of the evidence.
◦ Quality assessment: Evaluates the methodological strengths and weaknesses of included studies.
◦ Challenges:
◦ Time-consuming: Requires significant effort to identify, assess, and synthesize studies.
◦ Limited flexibility: Less room for exploring complex themes or highlighting controversies.
◦ Statistical limitations: May not be suitable for combining quantitative data from diverse studies.

3. The Data Whisperer: Meta-Analysis
◦ The meta-analysis is the data whisperer, extracting quantitative information from various studies and statistically combining
them. This provides a powerful tool to summarize the overall effect of an intervention or phenomenon.
◦ Strengths:
◦ Quantitative synthesis: Provides a single, statistically robust estimate of the effect size.
◦ Increased precision: Combines data from multiple studies, leading to more reliable results.
◦ Hypothesis testing: Allows for stronger conclusions about the existence and magnitude of an effect.
◦ Challenges:
◦ Applicability: Requires studies to be sufficiently similar in design and outcome measures.
◦ Statistical complexities: Choosing appropriate statistical methods and interpreting results requires expertise.
◦ Publication bias: May underestimate true effect sizes due to unpublished negative results.

Choosing the Right Face
◦ The best type of ROL depends on your research question and goals.
A. For a broad overview and identification of key themes, a narrative
review is ideal.
B. For a comprehensive and unbiased assessment of the evidence, a
systematic review is the way to go.
C. To statistically quantify the overall effect of an intervention, a meta-
analysis is your weapon of choice.

STEPS OF ROL
◦ Define your scope: What is your specific research topic? What sub-topics are relevant? Narrowing your focus helps you stay
organized and avoid getting overwhelmed.
◦ Identify credible sources: Look for high-quality academic journals, books, conference proceedings, and other reliable sources
of information. Be wary of biased websites or Wikipedia rabbit holes!
◦ Take detailed notes: As you read, capture key points, findings, and limitations of each study. Use a consistent note-taking
system to stay organized and easily reference information later.
◦ Organize and analyze: Categorize your notes by theme, chronology, or any other system that makes sense for your topic.
This will help you identify patterns, trends, and connections between different studies.
◦ Synthesize and interpret: Don't just list studies one after another. Explain how they relate to each other, highlight key
findings, and identify areas of agreement or disagreement. This is where your critical thinking and analytical skills come into
play.

BENEFITS OF ROL
◦ Stronger research foundation: By building upon existing knowledge,
you're more likely to develop a well-defined research question,
choose appropriate methodologies, and interpret your results
accurately.
◦ Increased efficiency: A good ROL can save you time and effort by
helping you avoid reinventing the wheel. You can focus your energy
on addressing unanswered questions and making new contributions
to the field.
◦ Enhanced credibility: Demonstrating your awareness of previous
research shows reviewers and readers that you've done your
homework and are well-positioned to tackle your research question.

STUDY DESIGN
Study designs are the set of methods and procedures used to collect and analyze data in a study.
These are 2 types of study designs: descriptive studies and analytical studies.
Descriptive studies
Describes specific characteristics in a population of interest
Case report- we discuss our experience with the patient’s symptoms,
signs, diagnosis, and treatment
Case series- several patients with similar experiences are grouped.
Analytical Studies
An analytic study attempts to quantify the relationship between two factors.
Observational studies are studies that we conduct without any intervention or experiment.
In those studies, we purely observe the outcomes.
Experimental studies, we conduct experiments and interventions.

STUDY DESIGN – OBSERVATIONAL STUDY
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.
1. Cross-Sectional Survey A study that examines the relationship between diseases (or other health-related
characteristics) and other variables of interest as they exist in a defined population at one particular time (ie
exposure and outcomes are both measured at the same time). Best for quantifying the prevalence of a disease or
risk factor, and for quantifying the accuracy of a diagnostic test.
2. Cohort Study Data are obtained from groups who have been exposed, or not exposed, to the new technology or
factor of interest (eg from databases). No allocation of exposure is made by the researcher. Best for study the effect
of predictive risk factors on an outcome.
3. Case-Control Studies Patients with a certain outcome or disease and an appropriate group of controls without the
outcome or disease are selected (usually with careful consideration of appropriate choice of controls, matching, etc)
and then information is obtained on whether the subjects have been exposed to the factor under investigation.

STUDY DESIGN – EXPERIMENTAL STUDY
Experimental studies- The researcher manipulates the exposure, that is he or she allocates subjects to the
intervention or exposure group.
Randomised Controlled Trial
An experimental comparison study in which participants are allocated to treatment/intervention or
control/placebo groups using a random mechanism (see randomisation). Best for study the effect of an
intervention.
I. Crossover Design- A controlled trial where each study participant has both therapies, e.g, is
randomised to treatment A first, at the crossover point they then start treatment B. Only relevant if the
outcome is reversible with time, e.g, symptoms.
II. Parallel Design- A parallel study is a type of clinical study where two groups of treatments, A and B,
are given so that one group receives only A while another group receives only B.

STRATEGIES TO ELIMINATE ERROR/ BIAS
Bias is a personal and often unreasoned judgment for or against one side in a dispute.
Error in ROL is not try to read everything, be selective. Reading but not writing. Not keeping bibliographical
information. Incomplete referencing (paraphrases, summaries and direct quotes).
◦ Building a Fortress Against Error and Bias: Strategies in ROL
◦ The review of literature (ROL) is a powerful tool, but it's not immune to error and bias, which can distort
findings and mislead interpretations. Fortunately, we have strategies to build a fortress against these threats:
I. At the Gates: Design Strategies
II. Within the Walls: Analysis Strategies
III. Within the Walls: Analysis Strategies

1. At the Gates: Design Strategies
◦ Randomization: In intervention studies, randomly assigning participants to groups helps ensure equal
distribution of known and unknown confounders, minimizing their influence on outcomes.
◦ Restriction: Limiting your study to participants with specific characteristics (e.g., age range, disease stage) can
reduce variability and isolate the effect of interest.
◦ Matching: Pairing participants in different groups based on relevant characteristics helps control for potential
confounders, creating more comparable groups.

2. Within the Walls: Analysis Strategies
◦ Stratification: Analyzing data separately within subgroups defined by key characteristics (e.g., gender,
treatment type) allows you to identify potential effect modifiers and ensure generalizability.
◦ Standardization: Adjusting individual data points for confounding variables (e.g., age, socioeconomic status)
helps to create a "level playing field" and isolate the true effect of interest.

3. Guarding the Towers: Additional Techniques
◦ Blinding: Keeping participants and researchers unaware of group assignments minimizes bias in reporting
outcomes and data analysis.
◦ Double-blind: Both participants and researchers are blinded to group assignments, further reducing bias
and strengthening the study's objectivity.
◦ Preregistration: Clearly outlining your research question, methodology, and analysis plan before data
collection minimizes the risk of post-hoc bias and increases transparency.

RANDOMIZATION TECHNIQUE
◦ Randomization is a process of assigning patients by chance of groups that receives different treatments.
◦ No one can control or predict the results. It is used to get reliable answers to research questions.
◦ Its like flipping a coin in a football match to decide who will go first. In same way people are assigned
to investigational arm or to the control arm.
◦ Clinical trails are conducted to compare a standard drug to a investigational drug or if the standard drug
is not available then placebo drugs are taken.
◦ Placebo drugs is a dummy drug with no active ingredients (API).

RANDOMIZATION TECHNIQUE
◦ Selection for two groups is carried out via computer in a randomized way to select the investigational
and standard group.
◦ At the end the researchers compare to see which group has lower side effects and is more effective.
◦ Randomization prevents bias.
◦ Bias is effected in a research when a group of people’s choice affects the clinical trails results.
◦ If randomization was not taken in practice the investigator will be providing the standard drug to sicker
persons and the investigational drug to the more healthy volunteers then researchers will never know if
one drug works better or not.

SELECTION OF SUBJECTS
◦ Interactive Research Technology (IRT) is responsible for
I. Enroll patient in Clinical Trails.
II. Randomized Patient.
III. Manage study drug supply.

Types of Randomizations in Clinical
Trials
◦ Clinical trials rely heavily on randomization to eliminate bias and ensure the validity of their results. By assigning participants to treatment groups
randomly, researchers can control for confounding variables and attribute observed differences to the interventions being tested. However, not all
randomization methods are created equal. Here's a deeper dive into four common types and their unique strengths:
1) Simple Randomization: Imagine flipping a coin: heads for one treatment, tails for the other. That's the essence of simple randomization. Each
participant has an equal chance of being assigned to any group.
2) Block Randomization: Think of pre-shuffling a deck of cards with designated "drug" and "placebo" cards. Blocks of participants are assigned
together, ensuring roughly equal numbers in each group within each block.
3) Stratified Randomization: Imagine dividing a deck by suit before shuffling. Participants are first stratified by key characteristics (age, gender,
disease severity), then randomized within each stratum to ensure balanced group composition.
4) Dynamic Randomization: This is like playing blackjack with a twist: the dealer adjusts the bet size based on your hand. Randomization
probabilities shift based on accumulating data, aiming to achieve specific goals like balanced group sizes or optimal treatment allocation based on
response.

Simple Randomization
1) Simple Randomization: Imagine flipping a coin: heads for one treatment, tails for the other. That's the essence
of simple randomization. Each participant has an equal chance of being assigned to any group.

Block Randomization
2) Block Randomization: Think of pre-shuffling a deck of cards with designated “treatments (T)" and “Control (C)" cards.
Blocks of participants are assigned together, ensuring roughly equal numbers in each group within each block.

Stratified Randomization
3) Stratified Randomization: Imagine dividing a deck by suit before shuffling. Participants are first stratified by key
characteristics (age, gender, disease severity), then randomized within each stratum to ensure balanced group composition.

Dynamic Randomization
4) Dynamic Randomization: This is like playing blackjack with a twist: the dealer adjusts the bet size based on your hand.
Randomization probabilities shift based on accumulating data, aiming to achieve specific goals like balanced group sizes or
optimal treatment allocation based on response.

Randomization Type Description Example
Simple
Each participant has an equal chance of being
assigned to any treatment group.
A coin toss is used to assign participants
to either the drug or placebo group.
Block
Participants are assigned to treatment groups in
blocks of a fixed size, ensuring a roughly equal
number of participants in each group within
each block.
Participants are assigned in blocks of 4,
with 2 assigned to the drug and 2
assigned to the placebo in each block.
Stratified
Participants are first divided into subgroups
based on certain characteristics (e.g., age,
gender), and then randomization is performed
within each subgroup to ensure balance across
treatment groups.
Participants are stratified by age
(younger than 65, 65 or older) and then
randomized to drug or placebo within
each age group.
Dynamic
The probability of assignment to each
treatment group changes throughout the trial
based on accumulating data, aiming to balance
group sizes or achieve other specific goals.
The probability of assigning a participant
to the drug group increases if more
participants have recently been assigned
to the placebo group.

CROSS OVER DESIGN
Cross-over trials are a powerful research design where participants receive each treatment intervention in a randomized
order, with "washout" periods (time interval between two treatment) in a particular sequence (the order of treatment
administration). This allows for efficient comparisons while minimizing individual variability. Let's explore the specific
nuances of two, three, and four-point cross-over designs:

2-point cross-over
Participants receive each treatment twice, with washout periods between each exposure (e.g., AB-BA or
BA-AB sequences).

3-point cross-over
Participants receive each treatment three times, with washout periods in between (e.g., ABC-BCA-CAB).

4-point cross-over
Participants receive each treatment four times, with washout periods between each (e.g., ABCD-BCDA-
CDAB-DABC).

Placebo: The Power of Belief in
Medicine
A placebo is a seemingly inactive treatment, like a sugar pill or saline injection, given to a patient in a controlled experiment. It looks and
feels like the real medication but contains no active ingredients. Yet, surprisingly, placebos can still produce significant improvements in
patients' symptoms. This phenomenon, known as the placebo effect, reveals the profound influence of our minds on our bodies.
The exact mechanisms of the placebo effect are still being unraveled, but several key factors are likely at play:
Conditioning: If patients have previously experienced positive outcomes with a specific treatment, even a placebo that mimics that treatment
can trigger their body's natural healing mechanisms through conditioned responses.
Expectancy: When a patient believes they are receiving a helpful treatment, their expectation of improvement can trigger the release of
endorphins, dopamine, and other neurotransmitters that can alleviate pain and promote healing.
The doctor-patient relationship: Feeling cared for and listened to by a healthcare professional can induce positive emotions and trust, which
can in turn activate the brain's reward pathways and contribute to placebo effects.

Placebo: The Power of Belief in
Medicine
 The magnitude of the placebo effect can be astonishing. Studies have
shown that placebos can:
1) Reduce pain by 30-70% in various conditions like headaches, back
pain, and even irritable bowel syndrome.
2) Improve symptoms of depression and anxiety as effectively as some
antidepressants.
3) Boost the effectiveness of real medications when used in combination.

Blinding Technique
Blinding in experimental research is the process in which participants, data analysts, and data collectors are kept unaware of
the experiment or study. The objective is to limit biased interpretation of treatment. Binding is mainly carried out in an RCT
(randomized controlled trial).
It is usually used in clinical research to keep the patients in the dark as to whether they might require a placebo or not.
Placebo is something that might appear to be an active treatment to the participants but does not have any active treatment.
A control group is a trial condition not receiving the actual treatment and might serve as a baseline.
Many a time, the name of the treatment is also kept hidden. For instance, patients might have an idea that they are involved
in some trials for osteoporosis, but they will have zero information about the name of the brand in the trial. Boost the
effectiveness of real medications when used in combination.

IMPORTANCE OF Blinding
Technique
Researchers and data analysts performing specific experiments often expect a particular outcome from it, and intentionally or
otherwise, evaluate data in a way that goes well with the preferred hypothesis. It is most significant in subjective trials where
skewed outcomes are avoided with blinding.
For instance, blinding can be used in an experiment where pain relief is assessed. If the participants here are aware that they
are getting a drug, they will most likely report pain relief than those getting a placebo.
Some benefits associated with blinding in research are:
• Enhances the validity of results in a trial
• Ensures unbiased ascertainment of outcomes
• Makes better the reliability of research

Different Types of Blinding
TECHNIQUE
There are three types of blinding:
I. Single Blinded Trial
II. Double-Blinded Trial
III. Triple Blinded Trial

single-blinded trial
In a single-blinded trial, blinding or masking of any one group is ensured. Usually, the participant is blinded in a
single-blinded trial as they are the ones receiving treatment.
Example
Say you conduct an experiment where you compare two types of butter from two different brands, one with low
fats and the other with high fats. You chose a total of some 100 participants and told them to taste any one brand
of butter. As soon as they taste, they go through an online survey. Now you, as the researcher, know which brand
of butter contains how many calories and fats, but the participants do not. This is an example of a single-blinded
trial where only an individual or group of individuals know about the experiment. If this one is clear, let us move
on to the next type of blinding.

DOUBLE-blinded trial
In this type of trial, neither the participant knows about the treatment group they are assigned to nor are the
researchers interacting with them.
Example You want to find out whether females consuming high levels of caffeine are more energetic than the
rest. What you do here is randomly assign a few women to take a placebo pill and others to go with a caffeine
pill. Both the pills are coded and randomly numbered. You tell all the women in the room that they are given a
caffeine pill so that you can observe their interaction level in terms of energy.
We call this a double-blinded trial because neither you know who is in which group and nor do the participants.
Once you are done collecting the sample, you can check the codes on the pills to assess the final data. It is
imperative here that the researchers are also unaware of the complete information, which can later help them
calculate results without being biased.

TRIPLE-blinded trial
A triple-blinded trial is where neither the person governing the treatment nor the subject or the person measuring
or collecting data is told about the treatment. So, here three parties are blinded:
• The participant
• The researcher
• The data collector
Example You have just developed a new vaccine, say the COVID-19 vaccine, and want to test its effectiveness
on patients on Coronavirus. Now you make two groups; the first group is given a fake vaccine while the other is
given the actual one. You have no idea what is happening as a researcher and also have not told the data
collectors and participants about the whole deal. This is a triple-blinded trial where the third party does not also
have any clue about the experiment.

1. Describe briefly the different interventional study designs.
2. Explain different observational study designs.
3. What are case studies? Why are they conducted, explain them in detail.
4. How will you design a clinical study methodologically? Explain briefly.
5. Explain in detail the Clinical Trial Design. Classify its designs. Explain graphically the parallel and
crossover study designs.
6. Write notes on a) randomization, b) objectives c) direct and surrogate end point in Clinical study.
7. Discuss briefly about designing the methodology for clinical studies B) Describe how a sample size
is determined for simple comparative experiments.
8. Discuss briefly about determination of sample size for simple comparative experiments and for
confidence interval of specific width.
9. Discuss in detail about various clinical studies designs.
10. Describe various clinical study designs in detail? Write about the importance of Biostatistics?

REFERENCES
1) Merriam, S. B. (1985). The case study in educational research: A review of selected literature. The Journal
of Educational Thought (JET)/Revue de la Pensée Educative, 204-217.
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General Research and methodology (Unit-1)

General Research and methodology (Unit-1)

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