Divergent directions of bias: affective forecasting in younger vs. older adults and the role of affective working memory.

Background: Affective forecasting is crucial for decision-making. Age-related differences in forecasting accuracy are documented, but the underlying cognitive mechanisms, such as affective working memory (AWM), remain unclear. This study examined whether AWM capacity moderates age differences in affective forecasting accuracy. Methods: We recruited younger and older adults to complete an affective forecasting task. Participants forecasted their emotional responses to positive and negative events based on verbal descriptions, and reported their actual emotions 1 week later upon viewing related images. AWM was assessed using an affect maintenance task. We employed linear mixed models (LMMs) with random intercepts for participants to account for repeated measures (forecast and experience), examining the effects of age group, event valence, and AWM on forecasting accuracy (bias score). Cluster-bootstrap confidence intervals (1,000 resamples) were computed for simple effects to obtain robust interval estimates. Results: Both age groups showed significant affective forecasting bias, but the pattern differed: older adults underestimated future positive emotions, whereas younger adults overestimated them. As predicted, AWM capacity was lower in older adults. However, contrary to our hypothesis, AWM did not significantly moderate the relationship between age and forecasting accuracy. The observed age differences in bias direction were not explained by variations in AWM. Conclusions: The findings confirm that age-related positivity effects manifest differently in affective forecasting, leading to divergent bias patterns. Importantly, the AWM decline in aging does not directly account for these differences in forecasting accuracy. This suggests that other cognitive or motivational factors may be more central. The results highlight the need to look beyond single-mechanism explanations when designing interventions to improve emotional prediction and decision-making in later life.