Clinical Research: Subjects and Variables

Study Subjects

• Clinical research involves studying a population with defined inclusion and exclusion criteria
• Generalizability and cost are also key considerations in study subject selection
• Recruitment is an important step that is closely related to the study sampling design

Study Variables

• Studies involve predictor variables, which include:
  • Exposures
  • Interventions
  • Independent variables
• Studies measure outcome variables to assess the impact of predictor variables
• Confounding variables are also measured

Example of Variables in a Clinical Trial

• A clinical trial evaluates CardioMed's effectiveness in reducing heart attack risk in high cholesterol patients

Predictor Variables

• Factors can influence or predict the outcome of a study
• Specific risk factors or conditions that participants may have been subjected to during the study, exposures are used
• Exposures can include high cholesterol levels
• Interventions involve specific treatments or actions that are taken to affect the outcome in a study
• Independent variables are manipulated to observe their effect on the outcome
• Administration of CardioMed vs. a placebo, or dietary habits are potential interventions
• Outcome variables include clinical events whose incidence is measured or some lab values that change in response to the intervention
• External factors that may influence the outcome are potentially skewing results if not controlled

Statistical Issues

• A statement of hypothesis needs to be specific
• For example, stating that 50- to 69-year-old women with CHD who take fish oil will have a lower risk of recurrent myocardial infarction than those who do not
• Statistical significance applies to analytical studies
• Purely descriptive studies do not involve tests of statistical significance
• Sample size is also considered

Goal of Clinical Research

• The goal is to draw inferences
  • Internal validity is the first inference, drawing correct conclusions from what happened in the study
  • External validity is the second inference, drawing conclusions applicable to people outside the study

Designing the Study

• Selection of a representative sample of subjects
• The variables chosen must represent the phenomena of interest

Implementing the Study

• Implementation involves matching the actual study to the planned study

Types of Research Error

• Random errors are mistakes due to chance with no predictable pattern
• Variability in sample selection can cause random errors
• These are minimized by increasing sample size and improving measurement instruments
• Systematic errors are biases that skew results in one direction
• Systematic biases in data collection can cause systematic errors
• Misclassification of dementia diagnoses influenced by health plan policies are a type of systematic error
• Systematic errors are minimized by reducing biases and gathering additional information
• Selection bias affects the generalizability of results. It occurs when the sample is not representative
• Drawing a sample only from a local health plan creates selection bias
• Selection bias is minimized with diverse sample selection and multiple settings
• Measurement error affects the accuracy of collected data
• Measurement error is due to poorly designed instruments that cause variation in responses
• Measurement error is minimized with validated instruments, and pilot test questionnaires

Key factors for Research

• Random errors can be reduced by increasing sample size
• Systematic errors require addressing systemic biases directly
• Selection and measurement errors threaten research findings validity
• Errors are minimized through careful study design and data collection methods

Understanding Errors in Research

• All studies have errors

Main Concern

• The main concern is whether the errors are significant enough to render study conclusions unreliable

Research Errors

• Research is like negotiation, starting with an ideal scenario
• Adjustments must balance internal/external validity and feasibility

Key Considerations for Research Errors

• What is essential for the study?
• What can be realistically achieved?

Evaluating the Study Plan

• Post-formulation review involves assessing if the plan addresses the research question adequately
• Ensuring implementation can maintain acceptable error levels is crucial
• Overlooking evaluation can lead to unviable studies

Moving Forward in Research

• Adaptability is important
• Good scientists identify and discard flawed ideas
• Refining and seeking better research is essential to improvement