Summary
Recent innovations in measurement such as ambulatory assessments and experience sampling, have created the unique opportunity to study psychological processes as they unfold over time in everyday life. Combined with novel statistical models that focus on within-person dynamics, 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, I 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, I 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.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/865468 |
| Start date: | 01-09-2020 |
| End date: | 31-08-2025 |
| Total budget - Public funding: | 2 000 000,00 Euro - 2 000 000,00 Euro |
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Original description
Recent innovations in measurement such as ambulatory assessments and experience sampling, have created the unique opportunity to study psychological processes as they unfold over time in everyday life. Combined with novel statistical models that focus on within-person dynamics, 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, I 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.
Status
SIGNEDCall topic
ERC-2019-COGUpdate Date
27-04-2024
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