Nonconscious goals can shape what people want to feel

Tamir, Maya; Ford, Brett Q.; Ryan, Erin

doi:10.1016/j.jesp.2012.11.009

Cited by 33 publications

(24 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Adapting previous measures of the expected utility of emotions (e.g., , participants also rated (1 = not at all; 6 = very much) their agreement with the following item: "Sadness on Memorial Day helps me feel a part of the Israeli society." Finally, as in prior research (e.g., , Tamir, Ford, & Ryan, 2013, to assess emotional preferences, participants rated the extent to which they wanted to feel sad on Memorial Day. Such self-report measures have been proven valid in studies that established their convergence with behavioural indices of emotional preferences and their predictive validity (e.g., Tamir et al, 2013).…”

Section: Methodsmentioning

confidence: 99%

“…Finally, as in prior research (e.g., , Tamir, Ford, & Ryan, 2013, to assess emotional preferences, participants rated the extent to which they wanted to feel sad on Memorial Day. Such self-report measures have been proven valid in studies that established their convergence with behavioural indices of emotional preferences and their predictive validity (e.g., Tamir et al, 2013). These items were not rated consecutively, but instead interspersed between various other items, including unrelated items for other research projects.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Together we cry: Social motives and preferences for group-based sadness

Porat

Halperin

Mannheim³

et al. 2015

Cognition and Emotion

Self Cite

View full text Add to dashboard Cite

Group-based emotions play an important role in helping people feel that they belong to their group. People are motivated to belong, but does this mean that they actively try to experience group-based emotions to increase their sense of belonging? In this investigation, we propose that people may be motivated to experience even group-based emotions that are typically considered unpleasant to satisfy their need to belong. To test this hypothesis, we examined people's preferences for group-based sadness in the context of the Israeli National Memorial Day. In two correlational (Studies 1a and 1b) and two experimental (Studies 2 and 3) studies, we demonstrate that people with a stronger need to belong have a stronger preference to experience group-based sadness. This effect was mediated by the expectation that experiencing sadness would be socially beneficial (Studies 1 and 2). We discuss the implications of our findings for understanding motivated emotion regulation and intergroup relations.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Together we cry: Social motives and preferences for group-based sadness

Porat

Halperin

Mannheim³

et al. 2015

Cognition and Emotion

Self Cite

View full text Add to dashboard Cite

show abstract

“…Indeed, the field is becoming more interested in learning whether manipulating people's affective forecasting leads people to select situations that make them feel more positively (Quoidbach, Mikolajczak, & Gross, 2015). Given what is known about emotional goals and preferences (e.g., Tamir, Ford, & Ryan, 2013), however, it's quite possible that increasing affective forecasting ability more generally leads people to select situations that make them feel the way they want to feel, be it positive, negative, arousing, or some affective combination therein. On the other hand, if affective forecasting ability is only a resource for situation selection insofar as it serves to increase one's positive emotional outcomes, then affective forecasting might be a particularly salient resource for older adults because they might want to experience more positivity than negativity (Scheibe, & Carstensen, 2010).…”

Section: Links To Existing Literaturementioning

confidence: 99%

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

Floerke¹,

Sands²,

Isaacowitz³

et al. 2017

Preprint

View full text Add to dashboard Cite

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...

show abstract

“…Although people may consciously adopt emotion regulation goals [21], such goals may also be implicitly activated. For instance, Tamir et al [22] found that surreptitiously exposing participants to words related to a collaboration goal (versus neutral words) led participants to indicate that they wanted to feel less angry during a subsequent, unrelated task. Importantly, participants were unaware of a theme to the words that they had seen, suggesting that the effect occurred at an implicit or nonconscious level.…”

mentioning

confidence: 99%

“…This assistance can take one of two forms. First, implicit processes may activate goals or other standards regarding appropriate or desired emotional responses [22]. Second, implicit processes help people to monitor whether their emotional responses diverge from those standards.…”

mentioning

confidence: 99%