Operationalization

Operationalization

Operationalization is the process in which a phenomenon that cannot be directly measured is defined through indicating its existence by another phenomenon (Saldanha & O’Brien, 2014). In empirical observations operationalization can be said to be the process of defining a fuzzy concept, therefore, making it easy to distinguish, measure and understand. Operationalization enables the fuzzy concepts to be measurable quantitatively and empirically especially when coming into conclusion or solving the research question or a hypothesis during a research (Saldanha & O’Brien, 2014).

How to operationalize research ideas

A good example can be in a health research where this could be operationalized using some indicators like feeding habits, the environment, smoking of tobacco, drug abuse and body mass index (Institute of Medicine, 2013). Operationalization can be done using alternative operationalization through a process known as robustness check (Saldanha & O’Brien, 2014). The factors mentioned above directly or indirectly affect people’s health, and therefore their variations or alterations could have huge effects on people’s lives. This, therefore, means that the study can vary one indicator keeping all the others constant to assess its effects on people’s health in a target population. The process can be repeated using all the other factors and comparing the results to observe if the variations are too huge to come up with conclusive results that can be used in generalizing or drawing a conclusion. This is meant to ensure that the results are a true representation of the entire target population or rather can give a clear picture in hypothesis testing or answer the research questions through consideration of the various indicators in the study. This is done to show if different indicators or factors have an effect on the result and if the results are substantially unchanged, the researcher can refer to the results as robust against the operationalization used in this case being the variables considered

References

Institute of Medicine (U.S.). (2013). Toward quality measures for population health and the leading health indicators.

Saldanha, G., & O’Brien, S. (2014). Research Methodologies in Translation Studies. Hoboken: Taylor and Francis.

 

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