Full Answer Section

• Sample Size: Typically small and purposefully selected (not random), allowing for in-depth study.
• Methods: Interviews (structured, semi-structured, unstructured), focus groups, observations, case studies, ethnographic studies, content analysis of documents or media.

Example of Qualitative Research:

Imagine a study aiming to understand the lived experiences of nurses working in critical care units during a pandemic.

• Research Question: “How do critical care nurses describe their emotional and psychological experiences while working during a major pandemic?”
• Method: The researcher would conduct in-depth, semi-structured interviews with a small group of critical care nurses. They would ask open-ended questions like: “Can you tell me about a typical day on the unit during the peak of the pandemic?” or “How did you cope with the emotional toll of caring for severely ill patients?”
• Data Analysis: The researcher would transcribe the interviews and then use thematic analysis to identify recurring themes, patterns, and common experiences shared by the nurses, such as feelings of exhaustion, moral distress, resilience, or a sense of duty. The output would be rich descriptions and interpretations of their experiences, not numbers or statistics.

Quantitative Research Methods

Quantitative research focuses on measuring and testing theories or hypotheses using numerical data. It deals with quantifiable information, aiming to establish facts, test relationships between variables, and generalize findings to a larger population. This method seeks to answer questions like “how much,” “how many,” or “what is the relationship between X and Y.”

Key Characteristics of Quantitative Research:

• Data Type: Numerical (e.g., statistics, percentages, ratings, counts).
• Purpose: To test hypotheses, confirm theories, measure variables, establish cause-and-effect relationships, and generalize findings.
• Approach: Often deductive, moving from general theories to specific observations.
• Sample Size: Typically large and randomly selected to ensure statistical representativeness.
• Methods: Surveys with closed-ended questions, experiments, structured observations (where observations are counted or rated), statistical analysis of existing datasets.

Example of Quantitative Research:

Consider a study investigating the effectiveness of a new pain management protocol on post-surgical patient pain levels.

• Research Question: “Does the implementation of a new standardized pain management protocol significantly reduce average post-surgical pain scores compared to the previous protocol?”
• Method: The researcher could conduct a quasi-experimental study. They would collect numerical pain scores (e.g., using a 0-10 pain scale) from two groups of post-surgical patients: one group receiving the new protocol and another receiving the old protocol. This would involve collecting data from a large sample of patients.
• Data Analysis: The researcher would use statistical analysis (e.g., t-tests or ANOVA) to compare the average pain scores between the two groups. The output would be numerical data, such as average pain scores for each group, p-values indicating statistical significance, and conclusions about whether the new protocol led to a statistically significant reduction in pain.