Research Methods

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Course Objectives

Differentiate common research study designs and recognize their strengths and limitations.
Identify common sources of bias that may influence study results and affect the reliability of published research.
Interpret basic statistical concepts commonly reported in medical literature to support evidence-based clinical decision-making.

Course Content

Course Creator//Editor: Kristen Moylen // Kirsten Hermens NCMA-P
Total CE Hours: 1 Hour
Course Number: 586-2704-26

Key Terms:

Observational study

Experimental study

Internal validity

External validity

Bias

Outcome

Exposure

Outline:

Introduction
Key Terminology
Evidence-Based Medicine
- How to read a Research paper
- Asking the right questions
Research designs
- Level 5
- Level 4
- Level 3
  - Case control study
  - Selecting cases and controls
    - Scenario
    - Scenario Application
  - Retrospective cohort study
- Level 2
  - Prospective Cohort Study
  - Randomization
  - Blinding
  - Analysis
  - Limitations
- Level 1
  - Limitations
Types of Bias
- Selection Bias
- Information Bias
- Confounding Bias
  - Scenario
  - Scenario application
- Red flags in research
Statistical Methods
- Intro to statistics
  - Hypothesis testing
  - P-values and Confidence intervals
    - Scenario
    - Scenario Application
  - Types of data
  - Common types of analysis
  - Regression models
  - Survival analysis
  - Measuring disease frequency
  - Measure association
  - Relative risk
  - Odds ratio
  - Sensitivity and specificity
    - Scenario
    - Scenario Applications
Take-home framework
Conclusion

References:

Turney, Shaun. “Null and Alternative Hypotheses | Definitions & Examples.” Scribbr, 24 Jan. 2025, https://www.scribbr.com/statistics/null-and-alternative-hypotheses/. Accessed 6 July 2026.
Elsevier. Levels of Evidence in Research. Elsevier. Retrieved March 24, 2024 from https://scientific-publishing.webshop.elsevier.com/research-process/levels-of-evidence-in-research/
Lim, Chi-Yeon, and Junyong In. “Randomization in Clinical Studies.” Korean Journal of Anesthesiology, vol. 72, no. 3, 1 June 2019, pp. 221–232, https://pmc.ncbi.nlm.nih.gov/articles/PMC6547231/, 10.4097/kja.19049. Accessed 6 July 2026.
Monaghan, T. F., Agudelo, C. W., Rahman, S. N., Wein, A. J., Lazar, J. M., Everaert, K., & Dmochowski, R. R. (2021). Blinding in Clinical Trials: Seeing the Big Picture. Medicina (Kaunas, Lithuania), 57(7), 647. https://doi.org/10.3390/medicina57070647
Ahn, E., & Kang, H. (2023). Intention-to-treat versus as-treated versus per-protocol approaches to analysis. Korean journal of anesthesiology, 76(6), 531–539. https://doi.org/10.4097/kja.23278
Cochrane. How to read a funnel plot. Cochrane. Retrieved March 24, 2024 from https://s4be.cochrane.org/blog/2023/06/27/how-to-read-a-funnel-plot/
Shi Z. (2023). Laparoscopic vs. open surgery: A comparative analysis of wound infection rates and recovery outcomes. International wound journal, 21(3), e14474. Advance online publication. https://doi.org/10.1111/iwj.14474
Temel, J. S., Greer, J. A., Muzikansky, A., Gallagher, E. R., Admane, S., Jackson, V. A., Dahlin, C. M., Blinderman, C. D., Jacobsen, J., Pirl, W. F., Billings, J. A., & Lynch, T. J. (2010). Early palliative care for patients with metastatic non-small-cell lung cancer. The New England journal of medicine, 363(8), 733–742. https://doi.org/10.1056/NEJMoa1000678
RECOVERY Collaborative Group, Horby, P., Lim, W. S., Emberson, J. R., Mafham, M., Bell, J. L., Linsell, L., Staplin, N., Brightling, C., Ustianowski, A., Elmahi, E., Prudon, B., Green, C., Felton, T., Chadwick, D., Rege, K., Fegan, C., Chappell, L. C., Faust, S. N., Jaki, T., … Landray, M. J. (2021). Dexamethasone in Hospitalized Patients with Covid-19. The New England journal of medicine, 384(8), 693–704. https://doi.org/10.1056/NEJMoa2021436
Akintoye, E., Sethi, P., Harris, W. S., Thompson, P. A., Marchioli, R., Tavazzi, L., Latini, R., Pretorius, M., Brown, N. J., Libby, P., & Mozaffarian, D. (2018). Fish Oil and Perioperative Bleeding. Circulation. Cardiovascular quality and outcomes, 11(11), e004584. https://doi.org/10.1161/CIRCOUTCOMES.118.004584
“P-Values Vs. Confidence Intervals: How to Interpret Both for Decisions.” Statstest.Com, 26 Jan. 2026, https://www.statstest.com/p-value-vs-confidence-interval-interpret-decisions. Accessed 6 July 2026.
“1.2: Data Types- Categorical Vs. Numerical.” Statistics LibreTexts, 28 Aug. 2025, https://stats.libretexts.org/Courses/Red_Rocks_Community_College/Introduction_to_Statistics_(RRCC)/01%3A_Introduction_to_Data/1.02%3A_Data_Types-_Categorical_vs._Numerical. Accessed 6 July 2026.