Study designs are fundamental frameworks that guide the planning, execution, and interpretation of research studies in the health sciences. In epidemiology and pharmacy practice, they help investigate disease causes, evaluate therapeutic interventions, assess drug-related problems, measure health outcomes, and inform evidence-based clinical decision-making. The choice of study design shapes data quality, validity, cost, ethical feasibility, and strength of conclusions. Broadly, study designs are classified into observational and experimental (interventional) studies, each serving distinct scientific purposes. Importance of Study Designs Appropriate study design allows researchers to: Identify causes and risk factors of diseases Understand disease distribution and determinants Develop and evaluate preventive and therapeutic strategies Establish association or causation between exposure and outcome Provide clinical and public health recommendations Support pharmacovigilance and drug safety monitoring Generate new scientific hypotheses and evidence for clinical practice Epidemiology underpins these designs, defined as the study of the distribution and determinants of health-related events in populations and the application of this knowledge to control health problems. ✅ OBSERVATIONAL STUDIES In observational research, the investigator does not manipulate exposure but monitors events naturally. These studies are essential when experimentation is unethical or impractical. They are of two types: descriptive and analytical. 1. Descriptive Studies These studies focus on describing health events without determining causality. They answer Who, Where, and When regarding disease occurrence. Descriptive studies are often hypothesis-generating for future analytical research. Types Case Reports In-depth narrative of a single patient’s symptoms, diagnosis, treatment, and outcome Useful for reporting novel diseases, unusual ADRs, drug interactions, rare presentations Method includes patient history, clinical findings, diagnosis, treatment, follow-up, and conclusion Case Series Collection of multiple similar cases Helps identify patterns, risk factors, treatment outcomes, or ADR clusters Uses systematic data collection, ethical consent, diagnostic work-up, treatment protocols, and outcome tracking Cross-Sectional (Prevalence) Studies Snapshot of exposure and disease at one point in time Measures prevalence; useful for public health planning Cannot infer causality but useful to identify burden and associations Purpose Describe unusual clinical conditions Document medication-related problems Identify new adverse drug reactions Provide real-world clinical insights 2. Analytical Studies These investigate associations between exposure and outcome and answer Why and How diseases occur. a) Case-Control Studies Retrospective design comparing individuals with disease (cases) vs without disease (controls) Looks back to evaluate exposure

1. STUDY DESIGNS
Study designs refers to the plan or structure of a research study, outlining the methods and
procedures used to collect and analyse data.
It encompasses decisions about the research question, participant selection, data collection
methods and statistical analysis.
Epidemiology is the study of the distribution and determinants of health-related states or
events in populations and the application of this study to control health problems.
It helps in:
• Identifying the cause of diseases
• Understanding disease patterns
• Developing preventive and control strategies
• Evaluating the effectiveness of health programs and interventions
TYPES OF STUDIES
Epidemiological studies are broadly classified into Observational and Experimental studies.
A. OBSERVATIONAL STUDIES
In these studies, the investigator observes the natural course of events without manipulating the
study environment.
1. Descriptive Studies
• Aim: To describe the occurrence and distribution of disease.
• Focus: “Who, Where, and When” of disease.
• Example: Case reports, case series, cross-sectional surveys.
Types:
• Case Report: A detailed report of a single patient.
• Case Series: Description of several cases with similar features.
• Cross-Sectional Study (Prevalence Study): Measures disease and exposure at a single
point in time.
Use: Identify health problems and generate hypotheses.

2. 2. Analytical Studies
These studies analyze the relationship between exposure (risk factor) and disease (outcome).
They answer “Why and How” a disease occurs.
Types:
a) Case-Control Study
• Compares people with the disease (cases) and without the disease (controls).
• Looks back to find prior exposure.
• Measure used: Odds Ratio (OR)
Advantages: Quick, inexpensive, good for rare diseases.
Limitations: Recall bias, cannot measure incidence.
b) Cohort Study (Follow-up Study)
• Starts with a disease-free population and classifies them based on exposure.
• Followed over time to see who develops the disease.
• Measure used: Relative Risk (RR) or Incidence Rate Ratio
Advantages: Measures incidence, establishes temporal relationship.
Limitations: Time-consuming, expensive, loss to follow-up.
c) Cross-sectional Study (Repeated)
• Observes both exposure and disease at the same time.
• Used to measure prevalence.
B. EXPERIMENTAL STUDIES
• Also called Interventional studies.
• The investigator actively manipulates exposure (e.g., giving a vaccine or drug).
Types:
1. Randomized Controlled Trial (RCT) – Subjects randomly assigned to intervention or
control groups.
2. Field Trial – Conducted among healthy people to prevent disease (e.g., vaccine trials).
3. Community Trial – Entire communities receive intervention (e.g., fluoridation of water)

3. Case Study
A case study is a structured and detailed analysis of an individual patient’s clinical condition,
A case study is a qualitative observational research method that involves in-depth
investigation of a single patient or clinical scenario.
The main purposes of case studies in clinical medicine and pharmacy include:
• To report rare or complex medical conditions
• To identify and analyze drug-related problems (DRPs)
• To document adverse drug reactions (ADRs) and drug interactions
• To assess rationale of drug therapy and therapeutic modifications
• To highlight the pharmacist’s role in patient care
• To contribute new knowledge to clinical science and improve patient-centered care
Methodology / Steps in Case Study Preparation
1. Case Identification and Selection
• Select an unusual, clinically significant, or educationally relevant case
(e.g., rare disease, unexpected treatment response, unique ADR).
• Case must contribute new knowledge or raise academic interest.
• Ensure patient safety, ethical consideration, and scientific value.
Selection criteria
• Novelty or rarity
• Significant therapeutic challenge
• Potential to add learning value
2. Ethical Considerations & Patient Consent
• Protect patient privacy and confidentiality
• Remove identifying information (name, address, ID)
• Obtain written informed consent for publishing clinical data and images
• Ethical committee approval may be required if identifiable data use
3. Comprehensive History Taking
Include complete patient profile:
Parameter Details
Demographics Age, gender, occupation

4. Parameter Details
Present illness Symptoms, duration, progression
Past history Previous illnesses, hospitalizations
Family history Genetic or hereditary disorders
Drug history Current & past medications, allergies
Social habits Smoking, alcohol, diet, stress, exercise
Lifestyle & psychosocial factors Socioeconomic status, support system
History helps establish etiology, risk factors, and differential diagnosis.
4. Clinical Examination
• Record general and systemic examination findings
• Vital signs (BP, HR, RR, Temp)
• Organ-specific evaluation (CNS, CVS, respiratory, GI, renal, endocrine, etc.)
• Objective and reproducible findings strengthen clinical interpretation
5. Diagnostic Work-up
• Laboratory investigations (CBC, RFT, LFT, electrolytes etc.)
• Imaging (X-Ray, CT, MRI, Ultrasound)
• Specialized diagnostic tests
• Use standard guidelines (WHO/ICD/DSM) to confirm diagnosis
• Present differential diagnosis and rationale for ruling out other conditions
6. Treatment and Intervention Documentation
• Describe complete pharmacotherapy plan
o Drug name, dose, frequency, route, duration
o Monitoring parameters
o Justification for drug selection
• Include non-pharmacological measures, surgical interventions, supportive care
• Note treatment modifications, patient compliance, and response
7. Follow-Up and Outcome Evaluation
• Monitor patient progress regularly
• Record improvement, side effects, complications, relapse, long-term outcome
• Follow-up helps determine treatment effectiveness and prognosis
8. Discussion & Literature Correlation
• Compare findings with published literature and guidelines
• Highlight:

5. o What makes the case unique
o Pharmacist’s role in treatment optimization
o Pathophysiological basis of condition
• Provide clinical reasoning and evidence-based analysis
9. Conclusion & Key Takeaways
• Brief summary of clinical message
• Lessons learned & therapeutic implications
• Recommendations for practice or future research
• Emphasize importance of individualized patient-centered care

6. Case Report
A case report is a structured clinical document that describes the diagnosis, treatment, and
follow-up of an individual patient. It highlights rare conditions, unusual presentations,
unexpected treatment responses, or novel drug-related problems. The methodology ensures that
the case is documented scientifically, ethically, and accurately for academic and clinical value.
Case report methodology
1. Case Identification
• Select a clinically relevant or unique patient case.
• Examples: rare disease, unusual symptom, new drug reaction, unexpected therapeutic
outcome.
• Case must have scientific significance and contribute new learning.
2. Ethical Considerations & Patient Consent
• Obtain written informed consent from the patient or legal guardian.
• Maintain confidentiality by masking personal identifiers (name, ID, address).
• Ethical committee approval may be required if identifiable data or images are used.
3. Patient History Collection
Record comprehensive history including:
• Demographics (age, gender, occupation)
• Presenting complaints and onset
• Past medical/surgical history
• Drug and allergy history
• Family and social history (alcohol, smoking, lifestyle)
• Psychosocial and occupational background
A detailed history helps understand etiological links and differential diagnosis.
4. Clinical Examination
• Perform and document general and systemic examination.
• Include vital signs (BP, HR, Temp, RR) and disease-specific findings.
• Record objective observations to support diagnosis
5. Diagnostic Investigations
• Conduct and present relevant laboratory and imaging tests.
• Apply standard diagnostic criteria (e.g., WHO, ICD).

7. • List differential diagnoses and show evidence for ruling them out.
6. Therapeutic Intervention
• Describe all treatment measures:
o Drug therapy (name, dose, route, duration)
o Non-pharmacological therapy and diet advice
o Surgical/Procedural interventions if any
• Provide rationale for therapy and changes made during treatment.
• Note patient adherence and response to treatment.
7. Follow-Up & Outcome
• Monitor patient progress over a defined period.
• Document improvements, complications, relapse, or prognosis.
• Follow-up adds credibility and clinical relevance to the case.
8. Discussion
• Compare findings with existing literature and guidelines.
• Highlight what makes the case unique.
• Explain possible pathophysiology, clinical lessons, and pharmacist/clinician role.
• Discuss alternative management options and evidence-based reasoning.
9. Conclusion
• Summarize the key clinical message and learning points.
• Emphasize importance for clinical practice, patient safety, or future research.
• State recommendations for healthcare practice if applicable.
10. References
• Cite relevant journal articles, clinical guidelines, textbooks, and case reports.
• Use standard citation style (Vancouver/APA).

8. Case Series
A case series is a descriptive observational study that involves systematic reporting of multiple
patients with a similar medical condition, clinical presentation, exposure, or treatment outcome.
Methodology of Case Series
1. Case Identification and Selection
• Identify multiple patients with:
o Similar disease or symptoms
o Similar drug reaction or exposure
o Same clinical condition or treatment protocol
• Select cases with clinical relevance and novelty
• Define inclusion and exclusion criteria
• Ensure cases are representative and not arbitrarily chosen
Example: All patients presenting with an unusual adverse drug reaction to a new antibiotic.
2. Study Objectives and Research Questions
Clearly define:
• Study purpose (e.g., identify pattern, describe ADR profile)
• Research question(s)
• Clinical significance of the case series
Example: To document rare hepatic toxicity associated with Drug X in diabetic patients.
3. Ethical Clearance and Patient Consent
• Obtain ethical committee approval if required
• Secure written informed consent from all patients (or their guardians)
• Ensure confidentiality and anonymity
• Remove personal identifiers (name, ID, contact details)
Ethics compliance is mandatory to protect patient rights and privacy.
4. Data Collection
Collect standardized data for all patients, such as:
Category Examples
Demographics Age, gender, occupation

9. Category Examples
Clinical presentation Symptoms, duration, severity
Medical history Comorbidities, past illness
Drug history Medications, allergies
Diagnostic findings Labs, imaging, special tests
Treatment details Drug doses, interventions
Outcome Recovery, complication, mortality
Ensure uniformity in data collection to maintain scientific consistency.
5. Clinical Examination & Work-up
• Perform physical and systemic examination
• Document vitals, organ-specific findings, severity grading
• Use standard diagnostic criteria (WHO, ICD, DSM etc.)
• Include baseline and follow-up assessments
6. Diagnostic Investigations
• Relevant laboratory tests and imaging
• Special diagnostic procedures if required
• Rule out differential diagnoses systematically
This ensures accuracy and prevents misclassification of cases.
7. Treatment & Intervention Documentation
• Document therapeutic regimens
• Specify:
o Medication names, dose, route, duration
o Surgical or supportive treatment
o Lifestyle or non-drug therapy
• Note treatment variations if any
• Record patient compliance and follow-up therapy adjustments
8. Follow-Up and Outcomes
• Monitor each case for:
o Improvement or deterioration
o Adverse events or complications
o Relapse or long-term outcomes
• Follow-up may be days, weeks, or months depending on condition
• Use standardized outcome measures/scales where possible

10. 9. Data Analysis & Interpretation
• Summarize patient findings in tables, charts, or flow diagrams
• Identify:
o Common patterns or trends
o Unique observations
o Response similarities or variations
• Perform descriptive statistics (mean, median, frequency, rates)
• No hypothesis testing or causal inference is done (non-comparative study)
10. Literature Review & Discussion
• Compare findings with previous published literature
• Highlight similarities, differences, and novel insights
• Discuss possible mechanisms, clinical implications, and challenges
• Acknowledge limitations (bias, small sample, lack of control group)
• Suggest future research directions
11. Conclusion
• Summarize the clinical significance
• Highlight lessons for practice and pharmacovigilance
• Provide recommendations for healthcare providers
12. References & Documentation
• Cite relevant journal articles and clinical guidelines
• Use proper scientific referencing style (Vancouver/APA)

11. Case-Control Studies
A case-control study is an analytical, observational study design used to investigate the causes
of diseases or outcomes by comparing individuals with a particular condition (cases) to
individuals without the condition (controls). It is especially useful for studying rare diseases,
long-latency conditions, or newly emerging diseases.
Methodology of Case-Control Studies
1. Define the Research Problem and Objectives
• Identify the disease/outcome and suspected risk factors.
• Frame a clear research question or hypothesis.
Example: Is smoking associated with lung cancer?
2. Case Definition and Selection
• Establish a strict diagnostic criteria for identifying cases.
• Cases are individuals who already have the disease/outcome of interest.
• Cases may be selected from:
o Hospitals/clinics
o Registries/databases
o Community/population surveys
Important:
• Ensure cases are newly diagnosed (incident) or already existing (prevalent), as specified
in study design.
• Avoid misclassification bias by confirming diagnosis with standardized tools/guidelines.
3. Control Definition and Selection
• Controls are individuals without the disease/outcome being studied.
• Controls should come from the same population as cases to ensure comparability.
• Sources of controls:
o Community controls
o Hospital/outpatient controls
o Registry-based or population-based controls
Requirements for controls:
• Must be at risk of developing the disease
• Must not have the disease currently
• Should resemble cases in baseline characteristics except the exposure

12. 4. Matching Cases and Controls
Matching is done to remove confounding variables.
Types of matching:
Type Meaning
Individual matching Each case is matched to one or more controls (e.g., by age/sex)
Group matching Controls selected to match distribution of cases
Matching variables may include age, gender, race, socioeconomic status, etc.
Avoid over-matching, which may mask true associations.
5. Sample Size Determination
• Based on expected exposure frequency, effect size (odds ratio), significance level, and
power.
• Case-control studies often use a 1:1 or 1:2 ratio, but may go up to 1:4 to increase power.
6. Data Collection on Exposure and Risk Factors
Use standardized tools:
• Interviews / structured questionnaires
• Medical and pharmacy records
• Laboratory investigations or biomarker data
• Past treatment history, lifestyle information, occupational exposure
Record potential confounders like smoking, alcohol use, family history, BMI, comorbidities.
Minimize recall bias by using validated questionnaires and medical records.
7. Measurement of Exposure
Exposure refers to risk factors or drug/treatment exposure prior to disease onset.
Examples:
• Smoking before lung cancer diagnosis
• Oral contraceptive use before thrombosis
• NSAID use before peptic ulcer
Exposure assessment must be:

13. • Accurate
• Objective
• Time-relevant (pre-disease exposure)
8. Data Analysis
• Calculate Odds Ratio (OR) = measure of association in case-control studies
OR > 1 → risk factor; OR < 1 → protective factor
• Adjust for confounders using:
o Logistic regression
o Stratification (e.g., Mantel-Haenszel method)
o Multivariate analysis
9. Addressing Bias and Confounding
Common biases in case-control studies:
Bias Meaning
Selection bias Improper selection of cases or controls
Recall bias Cases recall exposures better than controls
Observer bias Interviewer influences responses
Prevention strategies:
• Clear selection criteria
• Blinding interviewers
• Using medical records instead of memory
• Proper matching and statistical adjustment
10. Ethical Considerations
• Obtain ethics committee approval
• Informed consent from participants
• Maintain confidentiality of patient data
• Avoid harm or psychological distress
11. Interpretation and Reporting Results
• Compare findings with existing literature
12. Conclusion
• Summarize key associations and implications
• Highlight limitations (biases, recall errors, confounders)
• Suggest further cohort studies or RCTs to confirm causality

14. Cross-Sectional Studies
A cross-sectional study is an observational research design in which data are collected at a
single point in time from a defined population. It measures the prevalence of disease, health
conditions, behaviors, exposures, or risk factors .
Methodology of Cross-Sectional Studies
1. Define the Research Problem & Objectives
Clearly identify:
• What health outcome/exposure is being studied
• Why the study is important
• Specific, measurable objectives
Example Objective:
To estimate the prevalence of hypertension among adults aged 30–60 years.
2. Study Population & Setting
• Define target population (e.g., adults, students, diabetic patients)
• Specify study setting (e.g., hospital, community, pharmacy)
• Ensure the population is representative of the group being studied
3. Sampling Strategy
Select appropriate sampling method to avoid selection bias:
Sampling Type Examples
Probability Simple random, systematic, stratified sampling
Non-probability Convenience, quota, purposive sampling
Important: Probability sampling provides more generalizable results.
4. Sample Size Determination
Sample size is calculated based on:
• Expected prevalence
• Margin of error
• Confidence level (usually 95%)
• Population size

15. 5. Inclusion & Exclusion Criteria
Specify criteria to ensure appropriate participant selection.
Inclusion Example: Adults 30–60 years attending OPD
Exclusion Example: Patients with temporary illness, pregnant women, unwilling participants
6. Ethical Approval and Consent
• Obtain Institutional Ethics Committee approval
• Take informed consent from participants
• Maintain confidentiality and anonymity
Ethical compliance is mandatory for human research.
7. Data Collection Tools
Select appropriate methods:
Method Examples
Questionnaires Standardized, validated, self-administered
Interviews Face-to-face, telephone, structured interview
Clinical measurements BP, BMI, blood tests
Records review Medical/pharmacy records
Use validated instruments to improve reliability.
8. Data Collection Procedure
• Train data collectors if needed
• Collect data at one point in time
• Ensure uniform procedure for all participants
• Avoid leading questions & observer bias
• Ensure privacy during interviews/examinations
9. Variables to Be Measured
Identify dependent and independent variables.
Variable Type Examples
Outcome (dependent) Presence of disease, symptom score
Exposure (independent) Smoking, lifestyle, drug use

16. Variable Type Examples
Confounders Age, gender, socioeconomic status
10. Data Management and Quality Control
• Use coding sheets, data entry software (SPSS, Excel, R)
• Perform data verification and cleaning
• Ensure quality control through pilot testing
11. Data Analysis
Use descriptive and analytical statistics:
Analysis Purpose
Frequency/Percentage Prevalence estimates
Mean/SD Continuous variables
Chi-square Test Association between categorical variables
Logistic Regression Adjust for confounding variables
12. Interpretation of Findings
• Compare results with previous studies/guidelines
• Discuss significance and public health implications
• Highlight patterns or associations found
13. Limitations
• Does not determine cause-effect relationship
• Risk of response bias or recall bias
• Temporal ambiguity (exposure vs outcome timing)
• Poor for rare diseases
14. Conclusion
Summarize key findings:
• Prevalence of the disease/exposure
• Major associations
• Implications for healthcare and future research
Provide recommendations (e.g., screening, awareness programs, further cohort studies).

17. Advantages
• Quick, inexpensive, easy to conduct
• Useful for prevalence studies
• Generates hypotheses
• Good for public health planning
Limitations
• Cannot establish causality
• Subject to confounding and bias
• Not suitable for rare diseases or rare exposures

18. Cohort Studies
A cohort study is an observational, analytical, longitudinal study in which a group of
individuals (cohort) is followed over a period to determine the incidence of a disease or outcome.
Cohort studies help establish temporal association between exposure and outcome, making
them valuable for studying risk factors and natural history of diseases.
Steps / Methodology of Cohort Study
1. Define the Research Problem & Objectives
• Clearly state the health outcome (disease/event) and exposure of interest.
• Formulate research question and hypotheses.
Example:
Does long-term cigarette smoking increase the risk of lung cancer among adults?
2. Select Study Population (Cohort Selection)
Two types:
Population-based cohort — general community population
Exposure-based cohort — selected based on exposure from specific groups (e.g., factory
workers exposed to chemicals)
Inclusion & Exclusion criteria must be defined to ensure the cohort is initially free from
outcome at baseline.
3. Classification of Participants Based on Exposure
Participants are divided into groups according to exposure:
Group Description
Exposed cohort Individuals who have the risk factor
Unexposed cohort Individuals without the risk factor
Exposure status should be measured accurately using validated tools (questionnaires, medical
records, lab tests, environmental measurements).

19. 4. Baseline Assessment
At the beginning (baseline), collect data on:
• Demographics — age, sex, socioeconomic status
• Exposure level — dose, duration, frequency
• Lifestyle factors — diet, smoking, alcohol, exercise
• Medical history
• Co-morbidities and confounders
Data collection methods:
• Interviews / questionnaires
• Medical records
• Laboratory tests
• Physical examination
Baseline ensures equal disease-free status at start.
5. Follow-Up
• Participants are followed over time to observe who develops the outcome.
• Prospective cohort: follow participants into future
• Retrospective cohort: use historical records and follow to a future point
Follow-up methods:
• Periodic interviews / questionnaires
• Hospital / clinic follow-up
• Telephone / email contact
• Use of registries / death records
Important: Prevent loss to follow-up to avoid bias.
6. Outcome Assessment
Determine who develops the disease/ outcome during follow-up.
Methods:
• Clinical examination
• Laboratory diagnostic tests
• Hospital records
• Death certificates (for mortality studies)
Ensure standardized outcome assessment to avoid misclassification bias.

20. 7. Data Analysis
Calculate Incidence Rates:
• Incidence among exposed
• Incidence among unexposed
8. Interpretation of Results
Interpret based on RR:
RR Value Interpretation
=1 No association
>1 Exposure increases risk (risk factor)
<1 Exposure decreases risk (protective factor)
Strengths
• Establishes temporal relationship
• Directly measures incidence
• Useful for studying multiple outcomes
• Good for rare exposures
Limitations
• Time-consuming (long follow-up periods)
• Expensive
• Loss to follow-up possible
• Not efficient for rare diseases
• Potential for confounding
Applications
• Studying causes of chronic diseases (cancer, CVD)
• Occupational exposure studies
• Natural history of diseases
• Pharmaco-epidemiology (drug safety studies)

21. Interventional (Experimental) Studies
Interventional studies, also known as experimental studies or clinical trials, are systematic
research investigations in which researchers actively administer an intervention to evaluate its
effect on health outcomes.
Examples of interventional studies include:
• Drug efficacy studies
• Vaccine trials
• Surgical technique evaluations
• Lifestyle modification studies (diet/exercise programs)
Methodology
1. Formulating Research Question & Objectives
The study begins by clearly defining:
• The health problem to be studied
• The intervention to be tested
• The primary outcome (main effect being measured)
• Secondary outcomes (additional effects)
Example:
“To evaluate whether Drug A reduces systolic blood pressure more effectively than standard
therapy in hypertensive patients.”
Clear objectives help in:
• Selecting appropriate study design
• Determining sample size
• Choosing outcome measures
2. Choosing Study Design
The appropriate interventional design is selected depending on research aim, feasibility, and
ethical considerations.
Design Type Description Example
RCT (Randomised
Controlled Trial)
Participants randomly assigned to
groups
Drug vs placebo
Non-randomized trial Allocation not random Educational intervention

22. Design Type Description Example
Crossover trial
Participants receive both treatments at
different times
Drug A → washout →
Drug B
Factorial design
Tests multiple interventions
simultaneously
Aspirin + Vitamin E
Cluster trial
Groups randomized instead of
individuals
School-based
vaccination
Quasi-experimental
No randomization but an intervention
occurs
Policy implementation
study
Choice depends on ethical feasibility, resources, and nature of intervention.
3. Ethical Approval & Informed Consent
Ethical clearance from Institutional Ethics Committee (IEC/IRB) is compulsory to protect
subjects' rights and welfare.
Key ethical responsibilities:
• Register trial (e.g., CTRI in India)
• Informed consent explaining risks, benefits, confidentiality, right to withdraw
• Maintain privacy and patient dignity
• Monitor adverse events
• Implement safety stopping rules if harm observed
Ethics ensures compliance with Good Clinical Practice (GCP).
4. Defining Study Population & Eligibility
Eligibility criteria specify who can participate.
Inclusion criteria:
Essential characteristics required (e.g., adults with stage-1 hypertension)
Exclusion criteria:
Conditions that may increase risk or interfere with study (e.g., pregnancy, kidney failure)
A well-defined population ensures:
• Homogeneity
• Generalizability
• Safety
Recruitment methods: hospital OPD, community programs, advertisements, electronic health
records.

23. 5. Sample Size Determination
Adequate sample size ensures statistical power and reliability.
Based on:
• Expected effect size
• Significance level (α = 0.05)
• Power (80–90%)
• Variability in population
• Drop-out rate
Sample size prevents:
• Type I error (false positive)
• Type II error (false negative)
Underpowered studies may give misleading results.
6. Randomization
Randomization assigns participants to treatment or control groups by chance, eliminating
selection bias.
Purpose:
• Ensures comparability
• Distributes confounders equally
• Enhances validity
Types of Randomization:
Type Explanation
Simple Like coin toss or computer program
Block Maintains equal group size throughout trial
Stratified Ensures equal distribution of key variables (age, sex)
Cluster Randomizes groups (schools, villages)
Crossover Each participant receives both treatments sequentially
Randomization protects study from conscious or unconscious assignment bias.

24. 7. Blinding (Masking)
Blinding prevents participants and research staff from knowing treatment allocation to reduce
bias.
Type Who is Blind Benefit
Single blind Participant Avoids placebo effect
Double
blind
Participant + investigator Reduces performance & observer bias
Triple blind
Participant + investigator +
analyst
Prevents data analysis bias
Open-label No blinding
Used when blinding impossible (e.g.,
surgery)
Placebo or double-dummy technique used to maintain blinding.
8. Intervention Administration
Protocol defines:
• Dose, schedule, route
• Duration of treatment
• Handling and storage of study drugs
• Monitoring adherence and side effects
Control group receives:
• Placebo, OR
• Standard therapy (active control)
Standardization prevents variability in treatment delivery.
8. Follow-Up & Outcome Assessment
Participants monitored over specified time to measure effect and safety.
Data collected via:
• Clinical evaluation
• Laboratory tests
• Questionnaires/scales
• Medical imaging
• Adverse event reporting
Consistency in follow-up prevents bias and missing data.

25. 10. Data Collection & Management
Data recorded using:
• Case Record Forms (CRFs)
• Electronic Data Capture tools
• Validated clinical scales
Important principles:
• Accuracy, Confidentiality
• Data audit trails, Compliance with GCP guidelines
11. Statistical Analysis
Statistical methods applied based on study type and outcome measures.
Advanced models if required:
• Regression analysis
• Survival analysis (Kaplan-Meier, Cox model)
13. Interpretation of Findings
Interpret in context of:
• Statistical significance
• Clinical relevance
• Study limitations
• Comparison with previous research
Results should explain whether the intervention is beneficial, neutral, or harmful.
14. Reporting & Publication
Trial reported using CONSORT Guidelines, including Flow diagram
• Baseline characteristics, Intervention details, Adverse events, Statistical analysis plan
Results submitted to journals, regulatory agencies, and clinical trial registries.