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NURS 4610: Translating Evidence for Nursing Practice: Quasi-Experimental Studies

What is a Quasi-Experimental Study?

Quasi-experimental studies are a type of quantitative research.  Similar to experimental studies, they involve manipulation of the independent variable.  However, they lack certain elements of a truly experimental design.  Most commonly, they do not randomly assign participants to study groups.  Also, they sometimes lack a control group (Schmidt & Brown, 2019, p. 177).  

JBI Levels of Evidence (under Levels of Evidence for Effectiveness)

  • 2.c: Quasi-experimental prospectively controlled study
  • 2.d: Pre-test – post-test or historic/retrospective control group study

For more information, please refer to the JBI Levels of Evidence (LOE) Information in your Blackboard course site (under Module 7) or see Dr. Reuille's LOE document below: 

PRO TIPS: Quasi-Experimental Checklist

Each JBI Checklist provides tips and guidance on what to look for to answer each question.  These tips begin on page 4. 

Below are some additional Frequently Asked Questions about the Quasi-Experimental Checklist that have been asked students in previous semesters. 

Frequently Asked Question Response
In Question 1, the checklist asks whether the 'cause' and 'effect' is clear.  How do I find the cause and effect? The 'cause' refers to the independent variable that is being manipulated to observe an 'effect.' The 'effect' is the dependent variable, or the outcome. You will often find this information in the beginning of the study in the objectives/purpose/aim/research question section. Is this information clearly stated? For example: "The purpose of this study is to identify whether mindfulness-based stress reduction ('the cause') reduces anxiety ('the effect') in cancer patients."
For Question 8, how can I tell whether outcomes were reliably measured?  Check for information about the internal reliability or internal consistency of the research instruments (scales, questionnaires, surveys, tools, etc.) used in the study. Look for the Cronbach's alpha statistic which is used to indicate internal reliability of an instrument.