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Operationalization

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For experimental research, where interval or ratio measurements are used, the scales are usually well defined and strict. Operationalization also sets down exact definitions of each variable, increasing the quality of the results, and improving the robustness of the design.

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To evaluate someone’s length of stay in a hospital, you might ask for access to their medical records and count the days from when they were admitted to when they were discharged. Measuring a variable like income might require some more thought, though. Are you interested in this person’s individual income or the income of their family unit? This might matter if your participant does not work or is dependent on other family members for income

Do you count income from social welfare programs? Are you interested in their income per month or per year? Measures must be specific and clear. Depending on your research design, your measure may be something you put on a survey or pre/post-test that you give to your participants. For a variable like age or income, one well-worded question may suffice. Unfortunately, most variables in the social world so simple. Depression and satisfaction are multi-dimensional variables, as they each contain multiple elements. Asking someone “Are you depressed?” does not do justice to the complexity of depression, which includes issues with mood, sleeping, eating, relationships, and happiness. Asking someone “Are you satisfied with the services you received?” similarly omits multiple dimensions of satisfaction, such as timeliness, respect, meeting needs, and likelihood of recommending to a friend, among many others.

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Moving from identifying concepts to conceptualizing them and then to operationalizing them is a matter of increasing specificity. You begin the research process with a general interest, identify a few concepts that are essential for studying that interest you, work to define those concepts, and then spell out precisely how you will measure those concepts. In quantitative research, that final stage is called operationalization (Dr. Matthew DeCarlo, 2018). An operational definition consists of the following components: (1) the variable being measured, (2) the measure you will use, (3) how you plan to interpret the results of that measure. The first component, the variable, should be the easiest part. By now in quantitative research, you should have a research question that has at least one independent and at least one dependent variable. Remember that variables have to be able to vary

For example, the United States is not a variable. Country of birth is a variable, as is patriotism (Antonio Damasio, 1999). Similarly, if your sample only includes men, gender is a constant in your study…not a variable.

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In fact, it is possible to undertake a research study without the employment of detailed methodologies, a research can be more focussed with an investigative plan. Whilst this paper did not look at the many and varied tools of research methodology, it did however concentrate on useful and important processes that help ensure that correct and relevant information is gathered. The purpose of any research is to gather information on a subject or social issue. Employing methods that ensure the correct, measurable data is gathered in relation to the subject is well served using the processes of conceptualisation and operationalistion.

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Dr. Matthew DeCarlo, Scientific Inquiry in Social Work, 2018.

Antonio Damasio (1999) The Feeling of What Happens: Body and Emotion in the Making of Consciousness ch.2, p.55

Inguane, R., Gallego-Ayala, J., & Juízo, D. (2013). Decentralized water resources management in Mozambique: challenges of implementation at river basin level. Physics and Chemistry of the Earth, Parts A/B/C.

Wright, R. (2007). Statistical structures underlying quantum mechanics and social science. International Journal of Theoretical Physics, 46(8), 2026-2045.

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