Averaging and summation: Positivity and choice as a function of the number and affective intensity of life events

Seta, John J.; Haire, Ashleigh; Seta, Catherine E.

doi:10.1016/j.jesp.2007.03.003

Cited by 25 publications

(34 citation statements)

References 35 publications

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“…Previous research in several domains, such as, stressors, positive life events, social facilitation/impairment, and consumer goods, has found that averaging effects occur when multiple stimuli in these domains have different valences (or similar valences and different intensities), whereas summation effects occur when they have the same valences and relatively similar intensities (e.g., Seta, Crisson, Seta, & Wang, ; Seta & Seta, , ; Seta, Haire, & Seta, , b; Seta, Seta, McCormick, & Gallagher, ). An interesting question is whether perceivers respond to multiple implications derived from a frame in much the same way as they do to multiple stimuli in the abovementioned domains.…”

Section: Implications and Future Directionsmentioning

confidence: 99%

Commonalities and Differences Among Frames: A Unification Model

Seta

McCormick

2017

Behavioral Decision Making

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We provide a review and a theoretically unifying model of framing effects. Beginning with a review of findings that prospect theory, fuzzytrace theory, and traditional dual process models do and do not explain, we develop a model of framing based partly on Bless and Schwarz's (2010) inclusion/exclusion model of assimilation and contrast. Our model is the first of its kind to be applied to all three valence framing manipulations and presents common mechanisms explaining findings in the framing literature that were previously difficult to conceptualize within a single theory (e.g., matching effects and cognitive effort). The model also accounts for why all three framing manipulations are influenced by differences between holistic/contextual versus analytic processing as well as the presence, absence, and direction of effects produced by different versions of framing manipulations. It also predicts contrast effects (Implications and Future Directions section) and applies to manipulations involving a frame and judgmental target.

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Section: Implications and Future Directionsmentioning

confidence: 99%

Commonalities and Differences Among Frames: A Unification Model

Seta

McCormick

2017

Behavioral Decision Making

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“…However, a number of experiments also show that retrospective hedonic evaluation does not completely support the peak–end rule (Ariely & Carmon, ; Ariely & Loewenstein, ; Kemp et al, ; Miron‐Shatz, ; Liersch & McKenzie, ; Seta et al, ). An extant review of the literature shows that there are two kinds of factors that reduce the peak–end effect.…”

Section: Theory and Hypotheses Developmentmentioning

confidence: 99%

“…The peak–end rule posits that people often make a retrospective evaluation of an extended experience on the basis of the most extreme affect they experienced during it (i.e., the peak affect) and near its end (i.e., the end affect; Kahneman, Fredrickson, Schreiber and Redelmeier, ). Some studies show that the peak–end rule predicts retrospective hedonic evaluation (see, e.g., Ariely, ; Fredrickson & Kahneman, ; Redelmeier & Kahneman, ; Schreiber & Kahneman, ; Do, Rupert, & Wolford, ), whereas others do not (such as Kemp, Burt, & Furneaux, ; Miron‐Shatz, ; Liersch & McKenzie, ; Seta, Haire, & Seta, ). On the basis of a review of the extant literature, we believe that these inconsistent findings flow from two issues.…”

Section: Introductionmentioning

confidence: 99%

Hedonic Evaluation over Short and Long Retention Intervals: The Mechanism of the Peak–End Rule

Geng

Chen

Lam

et al. 2013

Behavioral Decision Making

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The peak-end rule is used to explain how people make retrospective hedonic evaluations. This study advances our understanding of its mechanism by identifying the different effects of the rule on such evaluations over short and long retention intervals. The results of two experiments show that (i) respondents constructed their retrospective hedonic evaluations on the basis of the peak and end affects only over a short retention interval, not over a long one; and (ii) respondents relied on episodic information to construct their evaluations over a short retention interval, whereas they relied on both semantic and episodic information to construct their evaluations over a long retention interval. Our study also suggests that the "watershed" between short and long retention intervals is likely to lie between 3 and 7 weeks.

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“…the reverse pattern) for negative emotions. A series of experiments by Seta, Haire, and Seta (2008) where participants remembered positive live events failed to reveal significant order effects and hence evidence for the peak-end rule. Finally, Hui, Meyvis, and Assael's (2014) analysis of a large set of data containing people's momentto-moment ratings while watching TV shows failed to find evidence for a peak effect.…”

mentioning

confidence: 98%

How does the peak-end rule smell? Tracing hedonic experience with odours

Scheibehenne

Coppin

2019

Cognition and Emotion

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The peak-end rule predicts that retrospective evaluations of affective events heavily depend on their most intense and last moment and imply duration neglect. It was originally proposed for negative experiences such as painful medical procedures. It is unclear, however, to what degree it also applies to positive experiences. Previously, rigorous comparisons between the two domains were limited due to the use of qualitatively different stimuli. Hence, it is not clear if the peak-end rule holds for short positive and negative experiences alike. To address these questions in a genuinely emotional domain, we conducted two experiments (n = 48 each) in which we used odours as stimuli. Participants repeatedly evaluated continuous odour sequences delivered into their noses via an olfactometer. The sequences differed in valence (positive vs. negative), length (36 vs. 72 s), and trajectory (increasing, decreasing, U-shaped, and inverse U-shaped). Results provide evidence for the peak-end rule for both positive and negative experiences alike. Results further show an overweighting of intense negative experiences for sequences that contain both pleasant and unpleasant episodes but provide little evidence for an effect of the trajectory manipulation.

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Averaging and summation: Positivity and choice as a function of the number and affective intensity of life events

Cited by 25 publications

References 35 publications

Commonalities and Differences Among Frames: A Unification Model

Commonalities and Differences Among Frames: A Unification Model

Hedonic Evaluation over Short and Long Retention Intervals: The Mechanism of the Peak–End Rule

How does the peak-end rule smell? Tracing hedonic experience with odours

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