Affect dynamics and well-being: explanatory power of the model of intraindividual variability in affect (MIVA)

Affective experience is inherently dynamic and short-term changes in affect are supposed to offer important insights into well-being. Past years have shown a tremendous rise in investigations into the relation between affect dynamics and well-being. The indicators that have been introduced to capture unique dynamical aspects of affect, however, have been criticised for being purely statistical measures without theoretical foundation and were shown to have little added value for explaining well-being over and above mean levels of affect. To address these concerns, we applied our newly developed theory-based MIVA model to data on daily affective experience. The MIVA model allows estimating parameters for anchoring, reactivity, and regulation based on affective states in combination with daily events. Everyday affective experience was measured with a high temporal resolution, multiple indicators of well-being (e.g. life satisfaction, depression) were assessed, and the incremental value of the MIVA model parameters in predicting well-being was determined. The MIVA model parameters reflect essential processes that accounted for observed fluctuations in affective experience. Incremental validity for predicting well-being over and above mean levels of affect, however, was low. Together, our results suggest that research on affect dynamics needs to identify how affect dynamics can be assessed more validly.

Automated summary

Research has shown that the current indicators used to capture affect dynamics have limited value in predicting well-being, indicating a need to identify more valid assessment methods.