A Student’s Guide to the Classification and Operationalization of Variables in the Conceptualization and Design of a Clinical Study: Part 1

• Published in: Indian journal of psychological medicine Vol. 43; no. 2; pp. 177 - 179
• Main Author: Andrade, Chittaranjan
• Format: Journal Article
• Language: English
• Published: New Delhi, India SAGE Publications 01.03.2021; Sage Publications, New Delhi India; SAGE Publishing
• Subjects: Confounding (Statistics); Learning Curve; Variables; operationalization of variables; confounding variable; Independent variable; hypothesis; dependent variable
• ISSN: 0253-7176; 0975-1564; 0975-1564
• DOI: 10.1177/0253717621994334

Students without prior research experience may not know how to conceptualize and design a study. This article explains how an understanding of the classification and operationalization of variables is the key to the process. Variables describe aspects of the sample that is under study; they are so called because they vary in value from subject to subject in the sample. Variables may be independent or dependent. Independent variables influence the value of other variables; dependent variables are influenced in value by other variables. A hypothesis states an expected relationship between variables. A significant relationship between an independent and dependent variable does not prove cause and effect; the relationship may partly or wholly be explained by one or more confounding variables. Variables need to be operationalized; that is, defined in a way that permits their accurate measurement. These and other concepts are explained with the help of clinically relevant examples.