Abstract
Scale development and validation are critical to much of the work in the health, social, and behavioral sciences. However, the constellation of techniques required for scale development and evaluation can be onerous, jargon-filled, unfamiliar, and resource-intensive. Further, it is often not a part of graduate training. Therefore, our goal was to concisely review the process of scale development in as straightforward a manner as possible, both to facilitate the development of new, valid, and reliable scales, and to help improve existing ones. To do this, we have created a primer for best practices for scale development in measuring complex phenomena. This is not a systematic review, but rather the amalgamation of technical literature and lessons learned from our experiences spent creating or adapting a number of scales over the past several decades. We identified three phases that span nine steps. In the first phase, items are generated and the validity of their content is assessed. In the second phase, the scale is constructed. Steps in scale construction include pre-testing the questions, administering the survey, reducing the number of items, and understanding how many factors the scale captures. In the third phase, scale evaluation, the number of dimensions is tested, reliability is tested, and validity is assessed. We have also added examples of best practices to each step. In sum, this primer will equip both scientists and practitioners to understand the ontology and methodology of scale development and validation, thereby facilitating the advancement of our understanding of a range of health, social, and behavioral outcomes.
Highlights
Scales are a manifestation of latent constructs; they measure behaviors, attitudes, and hypothetical scenarios we expect to exist as a result of our theoretical understanding of the world, but cannot assess directly [1]
Expert judges evaluate each of the items to determine whether they represent the domain of interest
An increase in the number of experts has been found to increase the robustness of the ratings [25, 44]
Summary
Scales are a manifestation of latent constructs; they measure behaviors, attitudes, and hypothetical scenarios we expect to exist as a result of our theoretical understanding of the world, but cannot assess directly [1]. Scale Development and Validation leads to more accurate research findings. Thousands of scales have been developed that can measure a range of social, psychological, and health behaviors and experiences. As science advances and novel research questions are put forth, new scales become necessary. There are many steps to scale development, there is significant jargon within these techniques, the work can be costly and time consuming, and complex statistical analysis is often required. Many health and behavioral science degrees do not include training on scale development. Despite the availability of a large amount of technical literature on scale theory and development [1,2,3,4,5,6,7], there are a number of incomplete scales used to measure mental, physical, and behavioral attributes that are fundamental to our scientific inquiry [8, 9]
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