Validity determines whether a study instrument actually assess what it was designed to and whether the findings can be genera
Quantitative Research Design
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Internal Validity
Validity determines whether a study instrument actually assess what it was designed to and whether the findings can be generalized in the society. Specifically, internal validity deals with whether alterations conducted to a dependent variable can really influence and change the independent variable. In so doing, it assess whether the study instrument measures what it purports to determine (Polit & Beck, 2017). In this regard, in case high internal validity exists, the dependent variable has the ability to change the independent variable. On the other hand, low internal validity is a product of confounding variable, which greatly influence the independent variable (Cantrell, 2011).
Potential Concerns and Dangers
Various factors influence the internal validity of the research. Some of these include the history, maturation, testing, instrumentation, and statistical regression (Cantrell, 2011). For instance, some events can take place between the first and second period of data collection. In addition, modification of scorers, observers, and instrument can generate modifications in the results, which affects the internal validity (Polit & Beck, 2017). Moreover, the pre-test can also affect the internal validity if it form parts of the treatment group. Furthermore, selection of study subjects creates biases, which may affect comparison group selection.
Recommendations
In a quantitative study, the internal validity can be enhanced in various ways. For instance, the researcher can utilize the double blind and single blind techniques (Cantrell, 2011). A double bling ensures that the researcher and study respondent are unaware on the assigned groups whereas in the single blind, only the participant who is uninformed of the assigned group. The strategy helps to eliminate little demand features especially when person in a particular group begin to behave in a manner to conform to the expected results (Cantrell, 2011). It also reduces experimenter impacts because they do reduce bias in some group.
References
Cantrell, M. A. (2011). Demystifying the research process: Understanding a descriptive comparative research design. Pediatric Nursing, 37(4), 188.
Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice. Lippincott Williams & Wilkins.