Periodic Reporting for period 3 - OPTIMAL (Coming-of-age of Process Research: Connecting Theory with Measurement and Modelling)
Periodo di rendicontazione: 2023-09-01 al 2025-02-28
Recent innovations have created new data collection methods such as ambulatory assessments, experience sampling, and ecological momentary assessments, which have made it relatively easy to obtain frequent measures of what individuals are doing, thinking and feeling during their daily life. These methodological innovations have thus created the unique opportunity to study psychological processes as they unfold over time in everyday life. Combined with novel statistical models that focus on patterns of fluctuations within a person, these developments offer a radically new perspective on foundational concepts in psychology. In clinical psychology for instance, these innovations are used to study mental disorders as networks of symptoms that trigger each other over time, and this is leading to valuable new insights on the emergence and persistence of psychopathology.
How to optimally employ these new tools is a major methodological challenge, however: Researchers must determine whether to use self-reports or physiological measures, what the frequency and duration of the measures should be, and which model fits their data and allows to test their theory. The costs of choosing inapt measurement and modelling methods can be severe and include: invalid results, erroneous conclusions, poor theory building, wasting resources, diminished trust in psychological science, and outcomes that are less useful or even harmful for individuals and society.
The aim of OPTIMAL is to resolve this challenge by developing an overarching methodological framework of process research that allows psychological researchers to connect theory, measurement and modelling. To achieve this goal, we will: a) strengthen the pairwise links between theory, measurement and modelling; b) conduct literature inventories in five substantive areas to elicit information on how to measure and model particular processes; and c) develop a taxonomy of models and an interactive website that researchers can use to guide them to optimal models. The generic nature of this methodological framework guarantees that it will be applicable in virtually all substantive fields within psychology that focus on processes, thus impacting psychological science in its full breadth.
How to optimally employ these new tools is a major methodological challenge, however: Researchers must determine whether to use self-reports or physiological measures, what the frequency and duration of the measures should be, and which model fits their data and allows to test their theory. The costs of choosing inapt measurement and modelling methods can be severe and include: invalid results, erroneous conclusions, poor theory building, wasting resources, diminished trust in psychological science, and outcomes that are less useful or even harmful for individuals and society.
The aim of OPTIMAL is to resolve this challenge by developing an overarching methodological framework of process research that allows psychological researchers to connect theory, measurement and modelling. To achieve this goal, we will: a) strengthen the pairwise links between theory, measurement and modelling; b) conduct literature inventories in five substantive areas to elicit information on how to measure and model particular processes; and c) develop a taxonomy of models and an interactive website that researchers can use to guide them to optimal models. The generic nature of this methodological framework guarantees that it will be applicable in virtually all substantive fields within psychology that focus on processes, thus impacting psychological science in its full breadth.
The OPTIMAL project started in September 2020. Since then, four PhD students and a postdoc have started their projects in which they contribute to strengthening the pairwise connections between theory, measurement, and analysis in process research in psychology and related fields, and help to integrate the three. Most papers are still in preparation; one paper--discussing various models that can and have been used to analyze the data from dyads--has been accepted for publication. This paper is accompanied by a shiny app (see: https://utrecht-university.shinyapps.io/dyadic-interaction-dynamics/(si apre in una nuova finestra)) that allows the user to see what kind of patterns various models can generate, and how changing parameters changes these patterns. This shiny app is a first step towards the interactive website that will be developed as a tool for researchers who want to learn more about the various models that may be useful for them to consider.
Two other papers have been published, along with supporting websites that contain background information and computer code that researchers can use to replicate and understand the results presented in these papers.
Finally, as part of the OPTIMAL project, instruction videos have been recorded and placed on YouTube (https://www.youtube.com/channel/UCvQsqlGzozvuqmY8SL-7-uA(si apre in una nuova finestra)) which researchers and students can use to learn more about time series analysis and dynamic multilevel modeling in Mplus.
Two other papers have been published, along with supporting websites that contain background information and computer code that researchers can use to replicate and understand the results presented in these papers.
Finally, as part of the OPTIMAL project, instruction videos have been recorded and placed on YouTube (https://www.youtube.com/channel/UCvQsqlGzozvuqmY8SL-7-uA(si apre in una nuova finestra)) which researchers and students can use to learn more about time series analysis and dynamic multilevel modeling in Mplus.
The first half of this project is a period of investment; it is expected that the second half will produce most of the results, both in terms of publications and in tools (e.g. interactive website). Furthermore, we are currently making plans for organizing an expert meeting that will focus on the connection between theory and measurement.