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Cross-sectional
data from different sources collected at the same time
longitudinal
data collected from the same sources over a period of time
Cross-sectional
Advantages:
1. Less time-consuming and less costly than prospective studies
2. They often serves as the starting-point in prospective cohort studies for screening-out already existing conditions
3. The design allows the measurement of risk, although the estimate is not precise
Cross-sectional
Disadvantages:
1. It does not enable the direct estimation of risk
2. Prone to bias from selective survival
3. Often difficult to establish temporal sequence of exposure and the disease - since data is taken at one point in time
Cohort
Sampling Population:
Population without the disease
Case Control
Sampling Population:
1. Population with the disease (cases)
2. Population without the disease (controls)
Cross-sectional
Sampling Population:
- Population with both disease and exposure status unknown at the start of the study
Cohort
Temporal Sequence:
- can be prospective or retrospective
Case Control
Temporal Sequence:
retrospective
Cross-sectional
Temporal Sequence:
Current and/or retrospective
Cohort
use: Compares incidence rates in exposed and unexposed
Case Control
use: Compares prevalence of exposure among cases and controls
Cross-sectional
use: Describes association between exposure and disease
Cohort
Measure of disease frequency: Incidence of disease among exposed and unexposed groups
Case Control
Measure of disease frequency: Cannot be computed
Cross-sectional
Measure of disease frequency: Prevalence of disease among exposed and exposed
Cohort
Measure of association between disease and exposure:
- Relative risk
- Attributable risk
Case Control
Measure of association between disease and exposure:
- Odds ratio (estimate of relative risk)
Cross-sectional
Measure of association between disease and exposure:
- Prevalence ration (inexact estimate of relative risk)
- Odds ratio
Experiments
- Provide the best evidence for testing any hypothesis or to investigate possible cause-effect relationship
- Resemble cohort studies in that they require follow-up of subjects to determine outcome
Experiments
- used to test for evidences
- involves action, manipulation or intervention on the part of the investigator
Experiments
important to have a good protocol to make sure that you can control all confounding variables that might be occurring in research and might affect results of your study
Experiments
Main Characteristics:
- Pre and post-treatment measurements made
- Presence of a control group
- Random selection of subjects from reference population
Experiments
Main Characteristics:
- Random assignment of subjects and treatment to groups
- High degree of control over extraneous variables to ensure the interventions made is the cause of the outcome
Randomization
one of the hurdles as you have to ensure homogenous subject as different characteristics may result to confounding variable
Hawthorne effect
- Observed factory workers are not well lit and cannot clearly see and do work and proposes to make it well lit which led to the result of increased performance of factory workers
- situation when you know you are being observed you try to do things properly
John Henry Effect
- Threat to internal validity
- One group may view it is a competition with the other group and works harder under normal circumstances
- Normally applied to control group taking on the experimental group
Surveillance Bias
esults when one population is more likely to have the disease or condition detected than another because or increased testing, screening or surveillance in general
Pretest and posttest
Are needed:
- To enable the measurement of change resulting from the treatment
- Change is often used as indicator of effectiveness
Control group
is needed:
- To determine whether or not change occurs even in the absence of the treatment or intervention
Solomon Four Group
Applied where they have two types of interventions and each experiment group has a control group
Quasi-Experimental Design
- allocation of subjects to experimental and control groups is NOT done at random
- Out of control, manipulation and randomization, randomization is not achieved
Quasi-Experimental Design
Common Variations:
- 1 pre test and multiple post tests
- More than one type of intervention that are related is being studied
1 pre test and multiple post tests
- Used when it is sustained or long-term and not the immediate effect of the intervention which the researcher is interested in
- Check for the sustained effect at different point in times
More than one type of intervention that are related is being studied
- Used when the effect of more than one treatment or intervention is being studied
- One experimental group per treatment/intervention
- One group receiving more than one treatment raises an ethical strike as there are no known side effects and can destroy the data as prior exposure to prior treatment results to learnings or bias
Pre-clinical studies
Experiments done prior to testing drugs in humans for purposes of:
- Isolating and characterizing active compounded
- Testing of absorption, distribution, metabolism, excretion and toxicological properties (ADME/tox)
Pre-clinical studies
Experiments done prior to testing drugs in humans for purposes of:
- Pharmacology and toxicology in animals
- Establishing no observable adverse effect levels to determine dosage to be used for initial phase 1 clinical trial of the dry
Pre-clinical studies
- are conducted with animals first before humans
- Not acceptable to do it to humans first as side effects are not known and may do more harm
IACUC (institutional animal care and use committee for live vertebrate animals)
counterpart of ethics research board for animals
Clinical Trials
Experimental designs used by clinicians and epidemiologists to evaluate drugs, medical devices and clinical or health care procedures
Clinical Trials
Most common form: randomized, controlled, double blind
Phase 1 Clinical Trial
- Perform initial human testing in a small group of healthy volunteers (20-100)
- Major goal to determine if drug is safe in humans
Phase 2 Clinical Trial
- Test in a small group of patients (100-500)
- Objective is to determine possible short-term side effects and risks associated with the drug; if it works according to expected mechanism
Phase 3 Clinical Trial
Test in a large group of patients (1000-5000) to show safety and efficacy
Phase 4 Clinical Trial
Post-marketing surveillance of drug to determine long-term safety and reassess effectiveness, acceptability and continued use under normal field settings
Variables
- measurable and quantifiable
- can be determined by using a tool or through experimentation
Relational Statements
- how one variable is linked or related to the other
- will help researchers how to go about with the study, from hypothesis development, then the collection of your data, to the identification of a data analysis method, until reaching the results of the study
Experimental Research
- Manipulation is done to the independent variable and to check if such manipulation has an effect to the dependent variable
- Cause and effect
Non-Experimental Research
- Simply to describe variables or check if one variable is correlated with the other without manipulating it through inferential statistics/analysis
- Association of one variable to another
Experimental Group
to whom you are going to give the treatment or intervention
Control Group
- to whom you are going to withhold the treatment or intervention
- basis for comparison
Debriefing
- must be done after implementation of data collection in a study where blinding or masking is implemented
- includes disclosing information that the informant belongs to the controlled/experimental group
