Underused Methods in Developmental Science to Inform Policy and Practice

Abstract

In this article, we offer recommendations for underused innovations and advances in research methods to enhance the quality of developmental science research. We couch our recommendations in terms of measurement innovations, design innovations, and analytic advances. We discuss six methods—the visual analog scale, the retrospective pretest–posttest design, appropriate timing and units of change, the accelerated longitudinal design, missing data treatments, and integrative data analysis. We conclude by encouraging developmental scientists to continue to incorporate advances and innovations in methods as they address the essential questions surrounding our goal to understand and improve the human condition across the life span.

Longitudinal Research About, and Program Evaluations of, Positive Youth Development in Low- and Middle-Income Countries: Methodological Issues and Options

“…Simply, then, in longitudinal research or program evaluation, change-sensitive measures must be used. Several publications explain how such sensitivity can be established (e.g., Campbell & Fiske, 1959;Card, 2017;Clifton, 2019;Rioux & Little, 2020).…”

Exploring Idiographic Approaches to Children's Executive Function Performance: An Intensive Longitudinal Study

“…Time. In order to capture daily variation within individuals, we chose a day as the unit of change (Rioux & Little, 2020). A time variable (i.e., Lag) was coded as the number of days between each assessment and the first measurement occasion.…”

Introduction to the special section on developmental approaches to prevention science

“…Technology makes the implementation of some effective measurement methods easier. For example, the visual analog scale, which is more valid than the Likert-type scale, used to be difficult to implement, but can now be easily implemented when using electronic data collection methods (Funke & Reips, 2012; Rioux & Little, 2020). In addition to this increased accessibility to measurement methods that were previously difficult to implement, technology brings new avenues for measurement.…”

“…An alternative approach that is increasingly discussed is continuous-time modeling, which aims to identify a continuous process that was measured through discrete measurement occasions (Voelkle et al, 2012). While a cross-lagged panel model with measurements at appropriate time intervals (Rioux & Little, 2020) is ideal to examine a process that occurs at discrete time points, the continuous time model is particularly relevant when theory suggests that the process occurs continuously. Hecht and Voelkle (2021) provide details about this approach and an example of its application to prevention science by examining the bidirectional relationship between physical activity and health.…”