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Cited by 417

The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.

The Optimum Level of Well-Being: Can People Be Too Happy?

Oishi, Shigehiro, Diener, Ed, Lucas, Richard E.·2007·Perspectives on Psychological Science

Abstract

Psychologists, self-help gurus, and parents all work to make their clients, friends, and children happier. Recent research indicates that happiness is functional and generally leads to success. However, most people are already above neutral in happiness, which raises the question of whether higher levels of happiness facilitate more effective functioning than do lower levels. Our analyses of large survey data and longitudinal data show that people who experience the highest levels of happiness are the most successful in terms of close relationships and volunteer work, but that those who experience slightly lower levels of happiness are the most successful in terms of income, education, and political participation. Once people are moderately happy, the most effective level of happiness appears to depend on the specific outcomes used to define success, as well as the resources that are available.

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Crossref · 10.1111/j.1745-6916.2007.00048.x

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Metadata

Authors
Oishi, S., Diener, E., & Lucas, R. E.
Venue
Perspectives on Psychological Science
Published
2007-12
Volume
2
Issue
4
Pages
346-360
ISSN
  • 1745-6916 (ISSN-L)
  • 1745-6924
OpenAlex
W2152274216
Cited by
417
References
85
FWCI
22.20
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Optimum Level of Well-Being: Can People Be Too Happy? https://app.cochat.ai/papers/10.1111/j.1745-6916.2007.00048.x
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Oishi, S., Diener, E., & Lucas, R. E. (2007). The Optimum Level of Well-Being: Can People Be Too Happy? Perspectives on Psychological Science. https://doi.org/10.1111/j.1745-6916.2007.00048.x

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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.