How Linguistic Frames Affect Motivational Profiles and the Roles of Quantitative versus Qualitative Research Strategies

By Yeager, Joseph; Sommer, Linda | The Qualitative Report, September 2005 | Go to article overview

How Linguistic Frames Affect Motivational Profiles and the Roles of Quantitative versus Qualitative Research Strategies


Yeager, Joseph, Sommer, Linda, The Qualitative Report


The combined tools of psycholinguistics and systems analysis have produced advances in motivational profiling resulting in numerous applications to behavioral engineering. Knowing the way people frame their motive offers leverage in causing behavior change ranging from persuasive marketing campaigns, forensic profiling, individual psychotherapy, and executive performance. Professionals study motivation in applied or theoretical settings, often with strong implicit biases toward either quantitative or qualitative strategies. Many experts habitually frame behavioral research issues with ill-fitting quantitative and qualitative strategies. The third strategic choice offered here is state-of-the-art, psycholinguistic communications modeling. The role of these research strategies is explored. Key Words: Motivational Profiling, Motivation, Motivational Frames, Psycholinguistics, Language Architecture, Behavioral Prediction, Qualitative Research, Content Analysis, Behavioral Engineering, Systems Analysis, Qualitative Strategies, Quantitative Strategies, Inferential Statistics, Mechanism of Action, and Behavior Change

Introduction

In the behavioral community "motivation" is central. Motivation, as a systematic phenomenon, operates in a complex manner dominated by linguistic mechanisms. The complex operational characteristics of motives are initiated and bounded by the ways in which a motive is framed in any given situation. The way any given motive is framed by the individual predetermines the way the motive will operate and conclude because the frames of a motive constrain its many parts to operate within its self-defined parameters.

That is, by analogy, if one frames a game as baseball, the features of football are excluded from that baseball game frame. In that vein, in day-to-day motivation, individual motives are structured in their operation by the way the individual's experience frames the motive at hand. Once an interested party knows an individual's dominant frames in a situation, the party knows the game frames of that individual's motive thus allowing prediction and modification.

While this "framing" characteristic applies to motives in general, it is also applies to those professional researchers and practitioners who study motives. Two different frameworks define how professionals frame their study of motives. Quantitative-statistical analysis of motivation dominates research design in psychology and has done so for a century.

Qualitative motivational analysis through much of the 20th century employed relatively crude methodology and was perceived as "soft" science. In the last generation, however, qualitative methods evolved linguistic technology for profiling motivation that makes obsolete many statistically based assessment strategies. If one wishes to understand motivation and its applications in engineering terms, one must know its causes and mechanisms of operation. Language is a qualitative phenomenon (Bandler & Grinder, 1975). Yet a strong tradition exists in psychometrics to add "Likert" scales to qualitative test "items" in a vain attempt to quantify behavior that is more effectively assessed with qualitative methods. Test items and their sampling strategies are designed to represent typical behavior in a given domain. The traditional conceptual domains are areas such as motivation, personality, and attitude (Shackleton & Fletcher, 1984).

The downside of this conventional numbering strategy is that it ineffectively fragments behavior and separates behavior completely from the context (or the frames) in which the behavior operates. Barrett (2003) emphasizes the shortcomings of unwarranted quantification by echoing the sentiment of Michell (2000): "psychometrics is a pathology of science" (p. 1). Barrett continues his observations with a rather strategic summary of the shifting role of psychometrics.

Where many of the 20th century developments in psychometrics were mainly concerned with finding novel ways to manipulate and work with numbers and test scores, it is expected that psychologists in the 21st century will begin to recognize that the "quantitative imperative" (Michell, 1990) is not necessary in the scientific study of psychology (p.

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