Introduction – Quantitative Research
Learning Objectives
By the end of this section, you will be able to:
- Identify and describe quantitative research designs.
- Identify and explain methods of quantitative data collection.
- Identify and apply quantitative sampling techniques and calculate sample size for cross-sectional studies.
- Design a survey.
- Identify and interpret types of quantitative data analysis.
Welcome to Chapter 8: Quantitative Research
Welcome to Chapter 8, a quantitative research journey. Quantitative research is one of the primary approaches used to build nursing knowledge and inform evidence-based practice. While qualitative research seeks to understand the meaning of human experiences, quantitative research focuses on measuring variables, testing relationships, and evaluating the effects of interventions using numerical data and statistical analysis. It helps answer questions such as: Does this intervention improve patient outcomes?, Is there a relationship between these variables?, or How common is this health problem?
This chapter provides an overview of quantitative research and introduces the language commonly used by nurse researchers. You will explore the philosophical foundations of quantitative inquiry, the role of hypotheses and variables, and the characteristics of experimental, quasi-experimental, and non-experimental research designs. The chapter also introduces key concepts such as measurement, control, randomization, validity, reliability, and the use of numerical data to answer nursing research questions.
Like qualitative research, quantitative research follows a systematic research process. Throughout this chapter, you will see how researchers move from identifying a research problem to selecting an appropriate design, recruiting participants, collecting data, analyzing results, and interpreting findings. These concepts are introduced here to provide a broad understanding of quantitative inquiry. The headings are set up so you can revisit many of these topics, including sampling, data collection, research quality, and critical appraisal, as you learn how to evaluate and apply quantitative evidence in nursing practice. In this chapter, we have listed questions to consider to critically evaluate a quantitative study. We encourage you to find a quantitative study report or manuscript and see if you can use the guidelines to assist in your assessment of the quality of the study.
Neither qualitative nor quantitative research is inherently “better” than the other. Rather, each approach answers different types of questions and contributes unique knowledge to nursing science. Understanding both approaches allows nurses to critically evaluate research and use the best available evidence to improve patient care, education, leadership, and health policy.
Key Terms for a Quantitative Researcher
Control Group: The comparison group in a study that does not receive the intervention or receives standard care.
Dependent Variable: The outcome that is measured to determine the effect of the independent variable.
Experimental Research: A quantitative research design in which the researcher manipulates an independent variable and uses random assignment to examine cause-and-effect relationships.
Hypothesis: A testable prediction about the expected relationship between two or more variables.
Independent Variable: The variable that is manipulated or introduced by the researcher.
Internal Validity: The degree to which the observed results can be attributed to the intervention rather than other factors.
Non-Experimental Research: Quantitative research that observes variables as they naturally occur without manipulating an intervention.
Quantitative Research: A systematic approach to research that collects and analyzes numerical data to examine relationships, differences, or the effects of interventions.
Quasi-Experimental Research: A research design that includes an intervention but lacks random assignment and/or a true control group.
Random Assignment: The process of assigning participants to study groups by chance to reduce bias.
Reliability: The consistency and stability of a measurement or instrument.
Statistical Significance: Evidence that an observed finding is unlikely to have occurred by chance alone.
Variable: A characteristic or attribute that can be measured or observed and may vary between individuals or groups.
Validity: The extent to which a tool or study accurately measures what it is intended to measure.
Remixed from:
- An Introduction to Research Methods for Undergraduate Health Profession Student by Faith Alele and Bunmi Malau-Aduli published by pressbooks under a CC BY-NC-SA license.
References
Alele, F., Malau-Aduli, B. (2023). Chapter 3: “Navigating quantitative research.” In An Introduction to Research Methods for Undergraduate Health Profession Students. James Cook University. https://jcu.pressbooks.pub/intro-res-methods-health/part/2-planning-a-research-project/
The comparison group in a study that does not receive the intervention or receives standard care.
The variable the experimenter measures (it is the presumed effect).
A study design that tests whether a specific intervention or treatment causes a change in an outcome
A micro-theory; a best guess or prediction about what one expects to find about the variable outlined in the study.
The variable the experimenter manipulates.
The degree to which the observed results can be attributed to the intervention rather than other factors.
A research that lacks the manipulation of an independent variable.
A research approach that collects and analyzes numerical data to examine relationships, measure variables, or test hypotheses.
A research design that includes an intervention but lacks random assignment and/or a true control group.
The process of assigning participants to study groups by chance to reduce bias.
The extent to which a tool or study produces consistent and repeatable results
Evidence that an observed finding is unlikely to have occurred by chance alone.
A characteristic, behaviour, or factor that can be measured or observed and may change between individuals or over time. Variables are commonly examined in quantitative research to explore relationships or differences.
The degree to which a measurement or study accurately reflects the concept it is supposed to assess.