Project
Affectometrics – Examining and improving the validity of the measurement of affect

The project aims to examine the processes that underly the self-report of affect. To this end, the factors believed to be influencing affect will be examined in a probabilistic reward task, including goal relevance, actual and anticipated goal incongruence and congruence, as well as reward prediction errors. To closely examine the effect of these factors on the affect responses, drift diffusion models (DDMs) will be applied to model the decision-making process involved in the affect response (e.g., Am I feeling positive/good or negative/bad?). This allows for disentangling the effects of these factors on the measured reaction times and responses (positive/negative) by estimating model parameters, such as the drift rate (rate of information accumulation regarding the affective state), the decision boundaries (how cautious the individual is at making the decision) and the starting point (the decision bias towards positive or negative affect). Applying DDMs is routinely done with two-alternative forced-choice tasks, such as a positive-negative decision. However, affect measurement in daily life is more accurately done with Likert scales or continuous sliders. As such, the DDM will have to be modified or existing modifications will have to be adapted to work with these scale types. Moreover, the use of the factors mentioned above assumes that the participants are responding truthfully, which may or may not be the case. To examine the effects of alternative strategies, careless responding and responding to comply with social norms will be examined as well by varying the time constraint on the decision and the task prompt. To increase ecological validity, experiments will be run at the lab using smartphones, before adapting the task to daily life and finally adapting the task in experience sampling (ESM) studies.

Supervisors
Prof. dr. A. M. Moors
Prof. dr. F.T. Tuerlinckx

Period
1 October 2023 – 1 October 2027