Research Methods in Public Health
Expert-defined terms from the Postgraduate Certificate in Public Health course at London School of Planning and Management. Free to read, free to share, paired with a professional course.
Research Methods in Public Health Glossary #
Research Methods in Public Health Glossary
1 #
Cluster Sampling
Cluster sampling is a sampling technique where the population is divided into cl… #
This method is often used in public health research when it is difficult or impractical to sample individuals directly.
Example #
In a study on the prevalence of obesity in schools, researchers may use cluster sampling by randomly selecting a few schools from each district to participate in the study.
Challenges #
One challenge of cluster sampling is that it may lead to increased variability compared to simple random sampling, as individuals within the same cluster may be more similar to each other.
2 #
Confounding Variables
Confounding variables are extraneous factors that may affect the relationship be… #
These variables can lead to erroneous conclusions if not properly controlled for in the research design.
Example #
In a study investigating the relationship between smoking and lung cancer, age could be a confounding variable as older individuals are more likely to develop lung cancer and also more likely to be long-term smokers.
Challenges #
Identifying and controlling for all potential confounding variables can be challenging, especially in observational studies where random assignment is not possible.
3 #
Descriptive Statistics
Descriptive statistics are numerical summaries of data that provide information… #
These statistics help researchers to understand the characteristics of their data.
Example #
A public health researcher may use descriptive statistics to summarize the heights of individuals in a population by calculating the average height, the range of heights, and the most common height.
Challenges #
Descriptive statistics can be sensitive to outliers, which may skew the results and misrepresent the overall characteristics of the data.
4 #
Experimental Design
Experimental design refers to the plan or strategy that researchers use to condu… #
It involves the selection of participants, manipulation of variables, and control of extraneous factors to ensure valid results.
Example #
In a study evaluating the effectiveness of a new drug on lowering blood pressure, researchers may use an experimental design where participants are randomly assigned to either receive the drug or a placebo.
Challenges #
Designing a rigorous experiment requires careful consideration of ethical concerns, practical constraints, and potential biases that could impact the validity of the results.
5 #
Incidence Rate
The incidence rate is a measure of the frequency at which new cases of a disease… #
It is often expressed as the number of new cases per unit of population at risk.
Example #
Public health officials may calculate the incidence rate of COVID-19 in a community by dividing the number of new cases reported in a month by the total population at risk during that period.
Challenges #
Calculating accurate incidence rates relies on timely and complete reporting of new cases, which can be challenging in situations where data collection is inconsistent or incomplete.
6 #
Qualitative Research
Qualitative research is a method of inquiry that focuses on understanding human… #
It aims to explore complex phenomena in depth.
Example #
A qualitative study on the impact of stigma on mental health may involve conducting interviews with individuals who have experienced mental illness to understand their perspectives and coping strategies.
Challenges #
Qualitative research relies on subjective interpretation and may lack generalizability, making it important to carefully consider the context and limitations of the findings.
7 #
Reliability
Reliability refers to the consistency and stability of measurements or results o… #
A reliable measure produces similar results when repeated under the same conditions, indicating that it is free from random error.
Example #
A reliable blood pressure monitor will provide consistent readings each time it is used, allowing healthcare providers to track changes in a patient's blood pressure accurately.
Challenges #
Ensuring reliability in research requires careful attention to measurement protocols, instrument calibration, and the minimization of sources of error that could affect the results.
8 #
Sample Size
Sample size refers to the number of participants or observations included in a s… #
Determining an appropriate sample size is essential for ensuring the statistical power of a study and the generalizability of the results.
Example #
A researcher conducting a survey on vaccination attitudes may calculate the sample size needed to detect a significant difference in opinions between different age groups with a specified level of confidence.
Challenges #
Determining the optimal sample size involves balancing practical considerations such as time, resources, and participant availability with statistical considerations to avoid underpowered studies.
9 #
Surveillance
Surveillance is the systematic collection, analysis, and interpretation of healt… #
It plays a crucial role in disease control and prevention.
Example #
Public health agencies use surveillance systems to track the spread of infectious diseases, monitor vaccine coverage rates, and identify emerging health threats in the community.
Challenges #
Maintaining effective surveillance systems requires ongoing investment in infrastructure, resources, and workforce capacity to ensure timely and accurate data collection and analysis.
10 #
Validity
Validity refers to the extent to which a study measures what it claims to measur… #
A valid study produces results that are accurate and meaningful.
Example #
A study assessing the effectiveness of a smoking cessation program is considered valid if it accurately reflects the program's impact on participants' smoking behavior and can be applied to other similar populations.
Challenges #
Ensuring validity requires careful attention to study design, measurement tools, sampling methods, and the control of bias to minimize threats to the validity of the results.
11 #
Quantitative Research
Quantitative research is a method of inquiry that focuses on collecting and anal… #
It uses statistical techniques to draw conclusions based on empirical evidence.
Example #
A quantitative study on the association between physical activity and cardiovascular health may use objective measures such as heart rate monitors and activity trackers to quantify participants' exercise levels.
Challenges #
Quantitative research requires careful attention to data quality, measurement precision, and statistical assumptions to ensure the validity and reliability of the findings.
12 #
Random Sampling
Random sampling is a sampling technique where each member of the population has… #
It helps to ensure that the sample is representative of the population and reduce bias.
Example #
In a study on hand hygiene practices in healthcare settings, researchers may use random sampling to select a sample of healthcare workers from a list of all staff members to participate in the study.
Challenges #
Implementing random sampling may be challenging in practice due to logistical constraints, incomplete sampling frames, and the need to ensure adequate sample size for analysis.
13 #
Systematic Review
A systematic review is a type of research synthesis that involves a comprehensiv… #
It aims to minimize bias and provide a rigorous overview of the literature.
Example #
A systematic review on the effectiveness of handwashing in reducing healthcare-associated infections would involve searching for, selecting, and critically appraising all relevant studies to provide a comprehensive summary of the evidence.
Challenges #
Conducting a systematic review requires expertise in research methodology, access to a wide range of databases, and the ability to critically evaluate and synthesize diverse sources of evidence.
14 #
Triangulation
Triangulation is a research strategy that involves using multiple methods, data… #
Triangulation is a research strategy that involves using multiple methods, data sources, or researchers to investigate a research question from different perspectives and increase the reliability and validity of the findings.
Example #
A public health study on the impact of air pollution on respiratory health may use a combination of environmental monitoring data, health surveys, and focus group discussions to triangulate the results.
Challenges #
Triangulation requires careful integration of different sources of data, consideration of potential biases, and the ability to synthesize diverse findings to draw meaningful conclusions.
15 #
Variable
A variable is a characteristic or attribute that can take on different values an… #
Variables are essential for measuring and analyzing relationships in research.
Example #
In a study on the impact of diet on weight loss, variables such as diet type (low-carb, low-fat) and weight change (in pounds) would be considered to examine the relationship between diet and weight.
Challenges #
Selecting and defining variables requires careful consideration of their relevance to the research question, measurement properties, and potential sources of variability that could impact the results.