Academic journal article Journal of Theory Construction and Testing

Making Assumptions Explicit

Academic journal article Journal of Theory Construction and Testing

Making Assumptions Explicit

Article excerpt

Assumptions are seldom made explicit for the reader of a research article. Sometimes this is the fault of authors, who fail to acknowledge the taken-for-granted beliefs underpinning their research (Burns & Grove, 2001). At other times, however, authors will diligently explicate their assumptions only to have a ruthless editor banish them from the final article due to the journal's space limitations. Recognizing assumptions and making them explicit strengthens a research report. In this editorial, I will outline and discuss strategies that enable researchers to recognize and explicitly state their research assumptions.

At least five assumptions operate in almost every research study. In one way or another, these five assumptions reflect the researcher's beliefs about the theory, the methodology, and the substantive phenomenon under investigation (Brinberg & McGrath, 1985; Fain, 2004). Although these core assumptions are most easily translated into a quantitative framework, they are also suitable (with a few modifications) for naturalistic modes of inquiry.

When researchers pause to reflect on the theoretical, methodological, and substantive aspects of their research, they knowingly (or unknowingly) employ two criteria: veracity and sensitivity. Veracity refers to adherence or conformity to facts or truths; it is a judgment about the appropriateness or accuracy of a theory, method, or substantive phenomenon. Sensitivity refers to perception or susceptibility to prevailing attitudes, feelings, or circumstances; it is an evaluation of the receptivity or responsiveness of a theory or method. Because a substantive phenomenon is what it is. the sensitivity criterion is not relevant for judging the phenomenon under investigation1.

Theoretical fit. The first assumption in many research studies could be stated like this: "The theory of X explains phenomenon Y" or "model X fits the observed data." The theory or conceptual framework is often assumed to be an accurate reflection of the phenomenon studied. Frequently a theory or framework is selected because the researcher believes that it provides an adequate explanation of the substantive phenomenon or because it justifies the instruments used for data collection. In some instances, however, these statements are not assumed. For instance, Doswell and associates (2003), whose study of early teen sexual behavior appears in this issue, use structural equation modeling (SEM) and a "goodness of fit" index to test the Theory of Reasoned Action (TRA). They conclude that the hypothesized TRA model provides a good fit for their sample data. Their findings challenge conventional wisdom in the social sciences concerning peer influence on adolescent behavior. Theoretical fit assumes a theory's veracity.

Conceptual coherence. The second assumption in many research studies might be stated: "Model X hangs together logically" or "relationships among concepts in theory X are necessary, sufficient, and clear." Unless researchers have confidence that concepts cohere, they cannot hope to generate testable, relational hypotheses or produce valid scientific explanations. Buck and Ryan-Wenger (2003), who propose a new taxonomy for early adolescents' definitions of health, are engaged in precisely this kind of work. Based upon their knowledge of human development, these authors assert that extant health taxonomies are not adequate to classify the meaning of health revealed by young teens. Consequently, they use content analysis to derive new categories and schema describing developmental nuances among definitions of health garnered from middle school-aged children. Conceptual coherence is a function of a theory's sensitivity.

Operational logic. The third assumption in many research studies could be stated in these terms: "Instruments X, Y and Z are congruent with the study's conceptual framework" or "the measurement model and data analysis adequately capture core concepts in theory A. …

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