About the Book
This book covers the science of measuring the invisible building blocks of thought processes that are useful for understanding humans, including technology users, media consumers, and consumers of goods and services. It provides:
- An explanation of what self-report measurement entails for beginners;
- A clear set of assumptions needed in order for self-report measures to yield valuable information;
- A set of principles of sound self-report measurement practice based on a hundred years of science;
- A mindset that needs to be adopted when using self-report measurement in the contexts of surveys and experiments;
- Guidance for extracting opinion from social media text content and integrating AI;
- A roadmap for quantifying the errors associated with self-report measurement.
In teaching Device and Diagnostic Design within biomedical engineering, a central challenger is understanding and addressing user needs — a critical aspect of effective design. Michael Elasmar’s approach equips students with the tools to ask the right questions, his work bridges the gap between understanding user behavior and creating impactful medical devices and diagnostics.
Joyce Y. Wong, PhD, Professor of Biomedical Engineering and Materials Science and Engineering, Boston University
Want to know what makes consumers tick? Ask them!
It’s a critical part of our research toolkit; but, it must be done with rigor and care to be effective. And no one distills this science more effectively that Dr. Elasmar. It required reading for the modern researcher.
Chris Aswad, Founder, Insight By Design, Marketing Research/Consumer Insights and Consulting Industry
Contents
Preface 1
Chapter 1: An intuitive need to measure the invisible for understanding thoughts, feelings, and behaviors 5
Chapter 2: Measuring the invisible: Practical uses and function within the method of science 18
Chapter 3: From observing behaviors to conceptualizing self-report measurement and developing a measurement mindset 25
Chapter 4: What can a researcher do to meet the self-report measurement assumptions? 56
Chapter 5: Principles and expectations: Statement content and placement 60
Chapter 6: Principles and expectations: Response category characteristics 77
Chapter 7: Principles and expectations: Motivation to self-report 96
Chapter 8: Principles and expectations: Respondent abilities 128
Chapter 9: A road map for quantifying the errors stemming from violations of the principles of self-report measurement: The Red Flags Approach (RFA) 152
Chapter 10: Implications for extracting self-report measurement from social media text content – What role can Artificial Intelligence (AI) play? 178
Chapter 11: A recap and some notes on the relevance of self-report measurement in the age of Artificial Intelligence (AI) 208
List of Figures 211
List of Tables 213
Index 215