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Subjective Well-Being
Open accessAbstract
The literature on subjective well-being (SWB), including happiness, life satisfaction, and positive affect, is reviewed in three areas: measurement, causal factors, and theory. Psychometric data on single-item and multi-item subjective well-being scales are presented, and the measures are compared. Measuring various components of subjective well-being is discussed. In terms of causal influences, research findings on the demographic correlates of SWB are evaluated, as well as the findings on other influences such as health, social contact, activity, and personality. A number of theoretical approaches to happiness are presented and discussed: telic theories, associationistic models, activity theories, judgment approaches, and top-down versus bottom-up conceptions. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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The satisfaction with life scale
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Global Judgments of Subjective Well-Being: Situational Variability and Long-Term Stability
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What is social comparison and how should we study it?
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Savoring Beliefs Inventory (SBI): A scale for measuring beliefs about savouring
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A systematic review and meta-analysis of psychological interventions to improve mental wellbeing
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What are the differences between happiness and self-esteem?
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Metadata
- Authors
- Diener, E.
- Venue
- Social Indicators Research Series
- Publisher
- Springer Netherlands
- Published
- 2009
- Volume
- 95
- Issue
- 3
- Pages
- 11-58
- ISSN
- 1387-6570 (ISSN-L)
- OpenAlex
- W2039859502
- Cited by
- 10,950
- References
- 11
- FWCI
- 32.14
- Type
- book chapter
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
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.