Cloudy with a chance of feelings: Affective forecasting as a resource for situation selection across the lifespan

Abstract

little is known about the resources that contribute to ER success. In two studies, we tested the hypothesis that affective forecasting, or the ability to predict how situations will make one feel, would be associated with situation selection, an ER strategy in which one chooses situations based on their emotional potential. In Study 1, 53 younger adults completed behavioral assessments of both affective forecasting and situation selection. Contrary to our predictions, there was no robust support for the hypothesis. However, a number of design limitations may have obscured the hypothesized association. Thus, we conducted a second study to retest the hypothesis after instituting several improvements in measurement and timing. In addition, we sought to test a new hypothesis that the association between affective forecasting and situation selection would vary by age. In Study 2, 54 younger and 50 older adults completed behavioral assessments of affective forecasting and situation selection. Analyses indicated that making fewer forecasting errors was associated with selecting fewer emotional relative to neutral situations. No robust age differences were found. This pattern suggests that affective forecasting may be a resource for situation selection across the lifespan.Keywords: situation selection; affective forecasting; SOC-ER; agingThe last two decades have seen a dramatic increase in the number of papers devoted to understanding emotion regulation (ER), a heterogeneous set of processes that influence the type, frequency, and intensity of the emotions people experience. The increase of interest in scholarly attention likely represents the oft-cited view that ER is essential to daily functioning, presumably because effectively managing one's emotions is conducive to meeting one's goals. According to the process model of emotion regulation (Gross, 1998), there are many family of strategies one can use to regulate an emotional experience during the emotion-generative cycle, including situation selection, situation modification, attentional deployment, cognitive change, and response modulation (Gross, 1998). AFFECTIVE FORECASTING, SITUATION SELECTION, AND AGE 3With such an extensive set of ER options, one might reasonably wonder which option is apt to be most effective for a given person in a given situation? Although popular psychotherapies like cognitive behavioral therapy (CBT) presume that cognitive changechanging how one thinks about an emotional response -is the most effective ER strategy, the Selection, Optimization, and Compensation with ER (SOC-ER; Urry & Gross, 2010) framework suggests that ER success depends upon selecting particular ER strategies, optimizing these different emotion regulatory strategies in response to particular emotion-eliciting events, and compensating with different ER strategies in the face of ER failure.Perhaps the most important theoretical contribution of SOC-ER is its suggestion that individuals select and optimize particular ER strategies based on the resources available to them.R...

Age differences in affective forecasting accuracy.

“…Other studies also support the conclusion that affective forecasting accuracy remains stable with age. One study failed to observe a significant age difference in affective forecasting accuracy for feelings generated by emotional video clips (Floerke et al, 2017), and another study failed to observe a significant age difference in how accurately people could predict changes in their choice satisfaction over time (Kim et al, 2008). These null results are also broadly consistent with other research showing that among younger adults, affective forecasting accuracy does not improve with practice or familiarity (Gilbert et al, 2004; Meyvis et al, 2010), and therefore, age-related increases in life experiences should not necessarily impact affective forecasting accuracy.…”