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Experiencers were more sensitive to the probability of winning $1 (i.e., 10% or 90%) when probability information was made salient immediately before they reported their happiness in Experiment 4. Bars represent 1 SEM.
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Affective forecasters often exhibit an impact bias, overestimating the intensity and duration of their emotional reaction to future events. Researchers have long wondered whether the impact bias might confer some benefit. We suggest that affective forecasters may strategically overestimate the hedonic impact of events to motivate their production....
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... important, there was a significant salience probability of winning interaction, F(1, 71) 9.06, p .004, 2 .11 (see Figure 4). Replicating the findings of Experiments 1-3, experiencers in the low salience condition were equally happy having won $1, whether the proba- bility of winning was 10% (M 11.31, SD 1.85) or 90% (M 11.44, SD 1.98), F 1. In contrast, experiencers in the high salience condition were happier having won $1 when the proba- bility of winning was 10% (M 12.84, SD 0.375) than when it was 90% (M 10.50, SD 2.19), F(1, 71) 17.89, p .001, 2 .20. ...
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Citations
... Studies of affective forecasting have generally shown that individuals overestimate the extent of emotion they will feel, a finding referred to as the impact bias (see review by Miloyan & Suddendorf, 2015). It has been argued that this tendency reflects not just cognitive bias in the estimation of future emotional states (Wilson et al., 2000) but also a motivational strategy (either implicit or explicit) that serves to facilitate decision making and goal-directed action by increasing the salience of desirable and undesirable outcomes (Morewedge & Buechel, 2013). ...
Anticipated emotions are the feelings one expects if a hypothetical future event were to occur, whereas anticipatory emotions are those one experiences right now while imagining the event. There has been little direct comparison of these two forms of future-oriented emotion, and authors have typically focused on positive emotions (e.g., pleasure). Besides, their sensitivity to depressive symptoms—which may help to explain motivational problems in depression—has only recently been investigated (e.g., Anderson et al., 2023; Gamble et al., 2021). The present study (conducted September–November 2022) used innovative picture-and-text vignettes depicting everyday positive and negative future events, to which participants rated their anticipated and anticipatory responses on separate dimensions of valence (i.e., how positive or negative) and arousal (i.e., emotional intensity). Based on prior literature, anticipatory emotions were expected to be correlated with, yet weaker than, anticipated emotions, reflecting a conceptualization of anticipatory emotions as a “foretaste” of the affective response one expects in the future. We also predicted that high depressive symptoms would coincide with diminished emotion ratings overall and specifically for anticipatory emotions (tightly coupled with event expectations; Carrera et al., 2012). Results largely supported these preregistered predictions, yet anticipatory emotions (positive and negative) were only weaker in more highly depressed participants. Depressive symptoms may therefore affect how one currently feels about future possibilities without altering one’s expectations of how such events would actually feel. Implications and future research objectives arising from this are discussed.
... Actions are motivated by their expected consequences (Thorndike, 1927;Bandura, 1977;Vroom, 1964). In general, people are more motivated to engage in activities if they anticipate that the outcomes of doing so would be rewarding, such as enjoyment (Baumgartner et al., 2008;DeWall et al., 2016;Mellers & McGraw, 2001;Morewedge & Buechel, 2013). However, while engagement in a potentially rewarding activity may deliver enjoyment, doing so also is likely to have costs, the most obvious of which is the required investment of mental and physical effort. ...
... Therefore, it is important to understand whether people would make accurate affect forecasts. A large number of studies have found that people are not capable of successfully predicting the duration and intensity of their emotional response to future events (Gilbert et al., 2004;Brown and McConnell, 2011;Morewedge and Buechel, 2013;Mata et al., 2018;Barber et al., 2023). People frequently overestimate how happy they will be after positive events and how sad they will feel after negative ones, which has been named the impact bias (Wilson et al., 2000;Wilson and Gilbert, 2003). ...
... Previous research found some factors influencing affective forecasting, such as focusing illusion, i.e., people focus too much on the occurrence of the focal event and fail to consider the consequences of other events that are likely to occur (Wilson et al., 2000;Wilson and Gilbert, 2005;Lench et al., 2011), immune neglect, i.e., the tendency to overlook coping strategies and other aspects of the "psychological immune system" that can reduce future distress (Gilbert et al., 1998;Diener et al., 2006), aging (Barber et al., 2023), and motivation (Morewedge and Buechel, 2013;Pauketat et al., 2016;Geng and Jiang, 2017;Geng et al., 2018). However, based on our knowledge, few studies shed light on the influence of basic psychological needs (BPNS) on affective forecasting. ...
... Compelling evidence shows that greater satisfaction with the needs for competence, autonomy, and relatedness is directly associated with intrinsic motivation and positive emotions in different contexts (e.g., Tang et al., 2020;Stanley et al., 2021). Previous studies demonstrated that impact bias has motivated underpinnings (Morewedge and Buechel, 2013;Pauketat et al., 2016;Geng and Jiang, 2017;Geng et al., 2018). In other words, the intensity of motivation to achieve the expected outcome would increase impact bias in affective forecasting of the expected outcome. ...
Affective forecasts are people's predictions of their future feelings in response to future events. In this study, based on the self-determination theory (SDT), we examined whether satisfying basic psychological needs influence undergraduates' affective forecasting and the moderating role of subjective socioeconomic status (SES). With a total of 423 undergraduate participants (177 males, 246 females), through one pilot study and three experiments, we first manipulated participants' basic psychological need satisfaction, i.e., autonomy need satisfaction (study 1), competence need satisfaction (study 2), and relatedness need satisfaction (study 3), then we asked low-SES and high-SES participants, respectively, to predict the pleasantness of a particular new product and evaluated the actual experience with the product. Results showed that the effect of basic psychological need on affective forecasting was not significant. When the need for autonomy need and competence need was satisfied, the impact bias was greater for the high SES than the low SES. Conversely, when the relatedness need was satisfied, the impact bias was greater for the low SES than the high SES. In conclusion, subjective SES moderated the influence of basic psychological needs satisfaction on increasing the impact bias in affective forecasting.
... Affective forecasting bias could be understood as a cognitive bias with a cardinal motivational dimension: imagining future events as more unpleasant or pleasant than they will actually be may help increase proactive behaviors to reduce or increase the probability of being confronted with their consequences 3,5 . Another possibility is that affective forecasting bias is determined by an individual's ability to simulate a future event with precision and that this ability is related to the frequency with which the individual has been confronted with the event or a similar event in the past. ...
A body of research indicates that people are prone to overestimate the affective impact of future events. Here, we developed a novel experimental paradigm to study these affective forecasting biases under laboratory conditions using subjective (arousal and valence) and autonomic measures (skin conductance responses, SCRs, and heart rate). Thirty participants predicted their emotional responses to 15 unpleasant, 15 neutral, and 15 pleasant scenarios (affective forecasting phase) to which they were then exposed in virtual reality (emotional experience phase). Results showed that participants anticipated more extreme arousal and valence scores than they actually experienced for unpleasant and pleasant scenarios. The emotional experience phase was characterized by classic autonomic patterns, i.e., higher SCRs for emotionally arousing scenarios and greater peak cardiac acceleration for pleasant scenarios. During the affective forecasting phase, we found only a moderate association between arousal scores and SCRs and no valence-dependent modulation of cardiac activity. This paradigm opens up new perspectives for investigating affective forecasting abilities under lab-controlled conditions, notably in psychiatric disorders with anxious anticipations.
... Questions like these have been used to examine the estimates that people make to life eventsand whether these estimates reflect the actual experience of affect over time. Impact bias describes the phenomenon that people tend to overestimate the emotional impact of a future event (Morewedge & Buechel, 2013;Morewedge et al., 2005;Wilson & Gilbert, 2013). This overestimation may be reflected in estimates of affective intensity and/or affective duration. ...
The current research examined the naïve theories that individuals hold about how affect fades over time. In three studies (with various replications), participants read about positive and negative events and estimated the emotional impact of those events on either themselves or a hypothetical other over different time frames (i.e., 1 week, 1 month, 1 year-Studies 1a-1c) or how long it would take for specific amounts of fade to occur (Studies 2a & 2b). In a final study, participants were directly asked about their beliefs regarding affect fade. Results demonstrated that people have inaccurate expectations about affect fade for positive and negative events. Specifically, participants rate that positive events fade more in the short term, but that negative events fade more in the long term. Results are discussed in terms of how these (incorrect) naïve theories of affect fade relate to metacognitive biases in memory and emotion.
... Research on affective forecasting has focused primarily on when and why forecasts are biased, and on the costs and benefits of bias for decision making. Overestimating the emotional impact of decisions can motivate goal pursuit (Morewedge & Buechel, 2013), but it can also lead people to squander their efforts, pursuing outcomes that do not make them as happy as anticipated, and avoiding ones that do not make them as unhappy as anticipated (Gilbert et al., 2002). In this investigation, we took a new approach by examining the features of emotion people report forecasting to guide their decisions. ...
Forecasts about future emotion are often inaccurate, so why do people rely on them to make decisions? People may forecast some features of their emotional experience better than others, and they may report relying on forecasts that are more accurate to make decisions. To test this, four studies assessed the features of emotion people reported forecasting to make decisions about their careers, education, politics, and health. In Study 1, graduating medical students reported relying more on forecast emotional intensity than frequency or duration to decide how to rank residency programs as part of the process of being matched with a program. Similarly, participants reported relying more on forecast emotional intensity than frequency or duration to decide which universities to apply to (Study 2), which presidential candidate to vote for (Study 3), and whether to travel as Covid-19 rates declined (Study 4). Studies 1 and 3 also assessed forecasting accuracy. Participants forecast emotional intensity more accurately than frequency or duration. People make better decisions when they can anticipate the future. Thus, people’s reports of relying on forecast emotional intensity to guide life-changing decisions, and the greater accuracy of these forecasts, provide important new evidence of the adaptive value of affective forecasts.
... Examples from bioethics is cases where hopes and desires flavor the ethical assessment of emerging technologies [7]. Related to affective forecasting is the impact bias, which is the tendency to overestimate the impact of a future event [69]. It can be observed in bioethics debates on novel technologies where future benefits are taken for granted, e.g., on gene editing, personalized/precision medicine, BigData, and Artificial Intelligence, and relates to projection bias (see Table 2). ...
Given that biases can distort bioethics work, it has received surprisingly little and fragmented attention compared to in other fields of research. This article provides an overview of potentially relevant biases in bioethics, such as cognitive biases, affective biases, imperatives, and moral biases. Special attention is given to moral biases, which are discussed in terms of (1) Framings, (2) Moral theory bias, (3) Analysis bias, (4) Argumentation bias, and (5) Decision bias. While the overview is not exhaustive and the taxonomy by no means is absolute, it provides initial guidance with respect to assessing the relevance of various biases for specific kinds of bioethics work. One reason why we should identify and address biases in bioethics is that it can help us assess and improve the quality of bioethics work.
... Researchers have generally found that individuals tend to poorly estimate their future emotions (Dunn et al., 2003;Goetz et al., 2013). Overestimating negative emotions has been shown to lead to poor decisions (Ferrer et al., 2015;Hoerger et al., 2016); however, overestimating negative emotions has also been shown to lead to more adaptive outcomes (Morewedge & Buechel, 2013;Safer et al., 2002). For example, Safer and colleagues (2002) found that students who overestimated their anxiety for an upcoming exam studied more than those who did not overestimate anxiety. ...
Students’ perceptions of cost are important predictors of academic and motivational outcomes. Though cost has been described as the anticipated effort one must put forth on an activity and what an individual sacrifices to complete a task, no known work has examined the extent to which anticipated cost beliefs predict experienced cost or whether anticipated and experienced cost are differentially predictive of academic and motivational outcomes. We used dynamic structural equation modeling to explore four dimensions of cost (task effort, outside effort, loss of valued alternatives, emotional cost) as anticipated and experienced beliefs, to examine the extent to which each predicts mathematics achievement and STEM-career intentions in introductory college calculus courses. Data were collected using a combination of traditional surveys, diary surveys, and institutional records. Overall, students who anticipated high cost at the beginning of the semester tended to experience high cost during the course and had more variability in their experiences of cost. Cost beliefs appear to be differently associated with grades however, with anticipated cost associated with higher course grades and experienced cost associated with lower course grades. Results suggested that anticipated and experienced cost are, to a certain extent distinct phenomena with unique effects on student outcomes, and that examining them as such may have important implications for theory and practice.
... A meta-analysis found that anticipated emotions have a more substantial influence on decision-making and behavior than affect in the present (Baumeister et al., 2016). Just as people expect to remain miserable for a long time after a breakup with their partner but do not know the extent and duration of the impact moment, the effect on the predicted well-being during important real-life events is frequently overestimated (Morewedge and Buechel, 2013). Life events closely related to the individual and the future often include high self-threat situations. ...
This study explored the effect of current performance on the predicted well-being for future success and its mechanism. This empirical research consists of two experiments. In Study 1, the individual’s predicted well-being of future performance in the tests was lower in good feedback condition compared with bad feedback condition. It means that individuals have a higher expectation of future success after an unimportant loss. Study 2 focused on the moderating role of self-threat situations and the mediating role of affect and self-esteem in the effect of current performance feedback on predicted well-being. The results showed that individuals who got bad feedback have a low predicted well-being of future success only in a high self-threatening condition. Self-threat plays a moderating role between current performance and predicted well-being. The serial mediation role of affect and self-esteem in the negative effect of current performance on predicted well-being holds in high self-threat situations. By specifying the behavioral consequences and analyzing the psychological process in high and low self-threat situations, this research expands the literature on development of appropriate cognitive theories and propose novel measures and practical implications of enhancing predicted well-being.
... However, affective forecasting bias may also serve a functional purpose. Affective forecasters may strategically overestimate the hedonic impact of events to motivate themselves to produce the events that they forecast (Morewedge and Buechel, 2013). ...
Introduction
People’s forecasts of their future emotions play an essential role in their behavior and experience of well-being. However, their emotional reactions may fall short of what they expect, which has implications for subsequent decision making. The current paper investigated the accuracy of affective forecasting about resource allocations and how this (in)accuracy predicts future allocation decisions.
Methods
Two experimental studies were conducted. Study 1 (N = 84) examined the extent to which people can accurately predict how allocation decisions will feel using an ultimatum game on the part of the allocator. Study 2 tested whether the affective forecasting bias affects future allocation decisions, with 192 participants playing a two-round ultimatum game on the part of allocators.
Results
Study 1 found an affective forecasting bias, and people anticipated more powerful emotional reactions to both positive and negative allocation events than they actually experienced when the events occurred. Study 2 found that increased affective forecasting bias resulted in less generous decisions in positive event conditions and more generous decisions in negative event conditions.
Discussion
These results extend previous findings concerning affective forecasting bias and the feelings-as-information model in resource allocation interactions and show that the difference between anticipated and experienced emotion is also informative in allocation decisions. The results suggest that being more cautious when forecasting positive outcomes and more optimistic when forecasting negative outcomes can be beneficial to one’s well-being.
