The Scientific Method
Understand observation, research questions, hypothesis development, data collection, analysis, interpretation, and conclusion.
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Course Preview
Watch the Sample Video
Watch the introductory video to learn how the course makes research methodology, epidemiology, statistics, and critical appraisal practical and relevant to Occupational Medicine.
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Introduction
Course Overview
Evidence-based practice lies at the heart of modern Occupational Medicine. Occupational Health professionals are expected not only to understand scientific evidence but also to critically appraise research, interpret epidemiological data, evaluate workplace risks, and apply statistical findings to clinical and workplace decision making.
Whether assessing the health effects of workplace exposures, interpreting surveillance data, or reviewing published research, a sound understanding of research methods and statistics is essential for safe and effective Occupational Health practice.
This comprehensive 30 CPD hour course provides a practical and clinically relevant introduction to research methods, epidemiology, and statistics within Occupational Medicine.
Designed for Occupational Health physicians, nurses, trainees, and MFOM candidates, the programme develops the skills required to understand, interpret, and apply scientific evidence in workplace health settings.
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Research Foundations
Research Methodology
Research Questions
Learn how clear and focused research questions guide study design, population selection, outcomes, and analysis.
Hypothesis Testing
Understand null and alternative hypotheses and how statistical testing is used to evaluate research findings.
Research Ethics
Explore consent, confidentiality, participant welfare, ethical approval, scientific integrity, and responsible research conduct.
Data Collection
Understand sampling, measurement, questionnaires, clinical information, exposure data, and outcome assessment.
Evidence Translation
Apply research findings to clinical decisions, workplace interventions, guidelines, and Occupational Health policy.
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Population Health
Principles of Epidemiology
Epidemiology is the science of studying the distribution and determinants of health conditions within populations.
Within Occupational Medicine, epidemiological methods help identify patterns of work-related illness, investigate associations between workplace exposures and health outcomes, evaluate preventive measures, and support evidence-based workplace policy.
Descriptive Epidemiology
Describe disease patterns according to person, place, time, occupation, exposure, and workforce characteristics.
Analytical Epidemiology
Compare groups and investigate possible associations between workplace exposures and health outcomes.
Experimental Epidemiology
Evaluate interventions through controlled studies and assess their effects on health outcomes.
Occupational Epidemiology
Apply population methods to workers, workplace exposures, occupational diseases, and preventive programmes.
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Measuring Health Outcomes
Incidence, Prevalence and Measures of Risk
Incidence
Understand the occurrence of new cases within a population during a defined period.
Prevalence
Understand the proportion of a population affected by a condition at a particular time or over a period.
Risk
Evaluate the probability that an individual or group will develop a defined health outcome.
Rates
Interpret the frequency of health events in relation to population size and time at risk.
Relative Risk
Compare the risk of an outcome between exposed and unexposed groups.
Odds Ratios
Understand the relationship between exposure and outcome, particularly within case-control research.
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Evidence Generation
Common Research Study Designs
Learners will understand the purpose, structure, strengths, and limitations of the research designs commonly encountered in Occupational Medicine literature.
Cross-Sectional Studies
Examine exposure and health outcomes within a population at a defined point in time.
Case-Control Studies
Compare people with a health outcome to those without it and examine previous exposure.
Cohort Studies
Follow exposed and unexposed groups to compare the occurrence of future health outcomes.
Randomised Controlled Trials
Evaluate interventions using random allocation and comparison between treatment or prevention groups.
Systematic Reviews
Identify, assess, and synthesise relevant research using transparent and structured methods.
Meta-Analyses
Statistically combine findings from multiple studies to estimate an overall effect.
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Evidence Quality
Evidence Hierarchy and Critical Appraisal
Different study designs provide different levels and types of evidence. The most appropriate design depends on the research question, ethical considerations, feasibility, exposure, outcome, and population being studied.
Learners will develop a structured approach to evaluating research validity, relevance, methodology, analysis, results, limitations, and applicability to Occupational Health practice.
Is the Research Question Clear?
Identify the population, exposure or intervention, comparison group, and outcome being investigated.
Is the Study Design Appropriate?
Determine whether the selected design can answer the research question reliably.
Are the Methods Valid?
Review participant selection, exposure measurement, outcome assessment, follow-up, and data quality.
Are the Results Reliable?
Evaluate effect size, precision, statistical significance, bias, confounding, and consistency.
Can the Evidence Be Applied?
Consider relevance to the workforce, clinical setting, exposure, organisation, and intended intervention.
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Interpreting Evidence
Bias, Confounding and Causation
Selection Bias
Understand how participant selection or loss to follow-up may influence study findings.
Information Bias
Explore measurement error, recall bias, misclassification, and inaccurate exposure or outcome assessment.
Confounding
Identify additional factors that may distort the observed relationship between exposure and outcome.
Effect Modification
Understand how the effect of an exposure may differ across subgroups or circumstances.
Association and Causation
Distinguish statistical association from evidence that an exposure causes a health outcome.
Chance and Precision
Evaluate whether findings may be explained by random variation and how precisely effects have been estimated.
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Statistical Foundations
Understanding Data and Descriptive Statistics
✓ Categorical Data
✓ Continuous Data
✓ Ordinal Data
✓ Nominal Data
✓ Mean
✓ Median
✓ Mode
✓ Range
✓ Variance
✓ Standard Deviation
✓ Normal Distribution
✓ Data Presentation
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Evidence Interpretation
Confidence Intervals, p-Values and Hypothesis Testing
Probability
Understand chance, uncertainty, and the likelihood of observing particular results.
Confidence Intervals
Interpret the estimated range within which the true population effect may lie.
p-Values
Understand what p-values indicate and recognise common errors in their interpretation.
Statistical Significance
Evaluate whether findings are unlikely to be explained by chance under the null hypothesis.
Clinical Significance
Determine whether the size and practical importance of an effect are meaningful in real-world practice.
Type I and Type II Errors
Understand false-positive and false-negative conclusions in statistical hypothesis testing.
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Relationships and Prediction
Correlation and Regression
Learners will develop a practical understanding of how statistical methods are used to examine relationships between variables and estimate the effects of workplace exposures.
The focus is placed on interpreting findings rather than complex mathematical calculation.
Correlation
Understand the strength and direction of association between variables.
Linear Regression
Interpret relationships between continuous variables and predicted outcomes.
Logistic Regression
Understand modelling where outcomes are categorical or binary.
Adjusted Analysis
Explore how statistical models account for confounding variables.
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Test Performance
Screening Tests and Diagnostic Accuracy
Sensitivity
Understand the ability of a test to correctly identify people who have the condition.
Specificity
Understand the ability of a test to correctly identify people who do not have the condition.
Positive Predictive Value
Interpret the probability that a person with a positive test result has the condition.
Negative Predictive Value
Interpret the probability that a person with a negative test result does not have the condition.
Likelihood Ratios
Understand how test results change the probability that a condition is present.
Screening Programme Performance
Evaluate test quality, prevalence, harms, benefits, follow-up, and suitability for workplace use.
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Practical Application
Occupational Health Applications
Epidemiology and statistics are applied throughout modern Occupational Health practice.
✓ Workplace Health Surveillance Data
✓ Occupational Exposure Studies
✓ Screening Programmes
✓ Outbreak Investigations
✓ Workplace Risk Communication
✓ Evidence-Based Guidelines
✓ Workplace Intervention Evaluation
✓ Occupational Disease Prevention
✓ Policy Development
✓ Service Quality Improvement
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Clinical Decision Making
Evidence-Based Occupational Health Practice
A strong emphasis is placed on making complex statistical concepts understandable and clinically relevant.
Rather than focusing on mathematical calculations alone, learners will develop the practical skills required to interpret published evidence, critically appraise research papers, and make informed Occupational Health decisions based on high-quality evidence.
Evidence-based practice requires the integration of research evidence, clinical expertise, workplace information, employee circumstances, legal considerations, and organisational context.
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Ask
Formulate a clear and answerable Occupational Health question.
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Acquire
Locate relevant and reliable research evidence.
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Appraise
Evaluate validity, relevance, precision, and limitations.
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Apply
Use the evidence within the clinical and workplace context.
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Assess
Review outcomes and improve future decisions.
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Knowledge Assessment
Tests and Mock Examination
Single Best Answer Questions
Test research methodology, epidemiology, statistics, screening, critical appraisal, and practical application.
Knowledge Assessments
Practise answering questions under structured examination conditions and identify areas requiring revision.
Full Mock Examination
Complete a comprehensive examination designed to support professional Occupational Medicine preparation.
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Course Outcomes
By the End of This Course
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Understand research methodology, scientific reasoning, hypothesis testing, and research ethics.
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Interpret incidence, prevalence, risk, rates, relative risk, and odds ratios.
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Critically evaluate common study designs, evidence hierarchies, bias, confounding, and causation.
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Interpret confidence intervals, p-values, statistical significance, clinical significance, correlation, and regression.
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Evaluate screening-test performance using sensitivity, specificity, predictive values, and likelihood ratios.
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Apply research and statistical evidence confidently to Occupational Health practice and workplace decision making.
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Course Instructor
Dr Syed Ahmed
Learn with an academic author and experienced Occupational Health Physician practising in the United Kingdom.