The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
Extracting meaning from past affective experiences: The importance of peaks, ends, and specific emotions
Abstract
This article reviews existing empirical research on the peak-and-end rule. This rule states that people's global evaluations of past affective episodes can be well predicted by the affect experienced during just two moments: the moment of peak affect intensity and the ending. One consequence of the peak-and-end rule is that the duration of affective episodes is largely neglected. Evidence supporting the peak-and-end rule is robust, but qualified. New directions for future work in this emerging area of study are outlined. In particular, the personal meanings associated with specific moments and with specific emotions should be assessed. It is hypothesised that moments rich with self-relevant information will dominate people's global evaluations of past affective episodes. The article concludes with a discussion of ways to measure and optimise objective happiness.
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Cited by
Fredrickson, B. L. (2001) · American Psychologist · doi:10.1037//0003-066x.56.3.218 · Cited by 18,025
Self-citationPositive affect and the complex dynamics of human flourishing
Fredrickson, B. L., & Losada, M. F. (2005) · American Psychologist · doi:10.1037/0003-066x.60.7.678 · Cited by 2,334
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Self-citationRace, race-based discrimination, and health outcomes among African Americans
Mays, V. M., Cochran, S. D., & Barnes, N. W. (2007) · Annual Review of Psychology · doi:10.1146/annurev.psych.57.102904.190212 · Cited by 889
Metadata
- Authors
- Fredrickson, B. L.
- Venue
- Cognition & Emotion
- Publisher
- Informa UK Limited
- Published
- 2000-07
- Volume
- 14
- Issue
- 4
- Pages
- 577-606
- ISSN
- 0269-9931 (ISSN-L)
- 1464-0600
- OpenAlex
- W2078381966
- Cited by
- 656
- References
- 71
- FWCI
- 2.65
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.