Experimental, quasi-experimental, and nonexperimental research

• Evaluation of Effectiveness: The strength of an experimental design lies in its ability to establish cause-and-effect relationships. Key evaluation criteria include:
  • Randomization: Was randomization truly random and adequate to minimize bias?
  • Control: How well were extraneous variables controlled? Were there any confounding variables that could have influenced the results?
  • Sample Size: Was the sample size large enough to provide sufficient statistical power?
  • Blinding: Were participants and/or researchers blinded to group assignment to minimize bias?

2. Quasi-Experimental Research:

• Example: A hospital wants to evaluate the impact of a new handwashing protocol on infection rates. They implement the new protocol in one unit of the hospital and compare the infection rates in that unit to the infection rates in a similar unit that did not implement the new protocol. They cannot randomly assign patients to units.
• Key Features: Manipulation of an independent variable (handwashing protocol), but lack of random assignment. Often used when random assignment is not feasible or ethical.
• Evaluation of Effectiveness: Quasi-experimental designs are weaker than true experiments in establishing cause-and-effect because of the lack of randomization. Evaluation focuses on:
  • Comparison Groups: How similar were the comparison groups? Were there any pre-existing differences between the units that could have influenced infection rates?
  • Threats to Internal Validity: What other factors (e.g., changes in staffing, seasonal variations) could have influenced the results? How were these addressed?
  • Statistical Controls: Were statistical methods used to control for potential confounding variables?

3. Non-Experimental Research:

• Example: A researcher surveys older adults about their experiences with ageism. They analyze the survey data to identify common themes and patterns.
• Key Features: No manipulation of an independent variable, no random assignment. Descriptive or correlational in nature.
• Types: Includes surveys, observational studies, case studies, and correlational studies.
• Evaluation of Effectiveness: Non-experimental research cannot establish cause-and-effect. Evaluation focuses on:
  • Sample Representativeness: How well does the sample represent the population of interest?
  • Measurement Validity and Reliability: Are the measures used accurate and consistent?
  • Potential for Bias: What are the potential sources of bias in the data collection or analysis?
  • Appropriate Statistical Analyses: Were the statistical methods used appropriate for the type of data collected?

Evaluating Two Examples (Hypothetical):

Let's imagine you found these two studies in the GCU Library:

1. Quasi-experimental: A study examining the effect of a new stress-reduction program on nurses' burnout in a specific hospital unit.

2. Non-experimental (Correlational): A study exploring the relationship between social media use and body image satisfaction among college students.

Evaluation:

• Quasi-experimental study: You would evaluate how well the researchers addressed the lack of randomization. Were the two units being compared similar in terms of staffing, patient demographics, and other factors that might influence burnout? What other events might have occurred during the study period that could have affected burnout levels? Did the researchers use any statistical techniques to control for these potential confounding variables?

• Non-experimental study: You would evaluate the sampling method used. Was the sample of college students representative of all college students? How did the researchers measure social media use and body image satisfaction? Were these measures reliable and valid? Correlation does not equal causation, so you'd be looking to see if the researchers appropriately interpreted their findings, avoiding causal language. What other factors might explain the observed correlation?

By applying these evaluation criteria, you can critically assess the quality and rigor of the research studies you find in the GCU Library. Remember to consider the specific research question being addressed and the limitations of each research design.

Experimental Research:

• Example: A researcher wants to study the effect of a new teaching method on student test scores. They randomly assign students to two groups: one group receives the new teaching method (experimental group), and the other group receives the traditional teaching method (control group). The researcher then compares the test scores of the two groups.
• Key Features: Manipulation of an independent variable (teaching method), random assignment of participants to groups, control group for comparison.