The DOI matches its Crossref record; 286 of the 286 references it cites were found in a registry or an index.
Measuring objective and subjective well-being: dimensions and data sources
Open accessAbstract
Well-being is an important value for people’s lives, and it could be considered as an index of societal progress. Researchers have suggested two main approaches for the overall measurement of well-being, the objective and the subjective well-being. Both approaches, as well as their relevant dimensions, have been traditionally captured with surveys. During the last decades, new data sources have been suggested as an alternative or complement to traditional data. This paper aims to present the theoretical background of well-being, by distinguishing between objective and subjective approaches, their relevant dimensions, the new data sources used for their measurement and relevant studies. We also intend to shed light on still barely unexplored dimensions and data sources that could potentially contribute as a key for public policing and social development.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Ryan, R. M., & Deci, E. L. (2000) · American Psychologist · doi:10.1037//0003-066x.55.1.68 · Cited by 54,599
Development and validation of brief measures of positive and negative affect: The PANAS scales.
Watson, D., Clark, L. A., & Tellegen, A. (1988) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.54.6.1063 · Cited by 32,433
Diener, E. (1984) · Psychological Bulletin · doi:10.1037/0033-2909.95.3.542 · Cited by 11,023
Diener, E. (2009) · Social Indicators Research Series · doi:10.1007/978-90-481-2350-6_2 · Cited by 10,950
Prediction of coronary heart disease using risk factor categories
Wilson, P. W. F., D’Agostino, R. B., Levy, D., Belanger, A. M., Silbershatz, H., & Kannel, W. B. (1998) · Circulation · doi:10.1161/01.cir.97.18.1837 · Cited by 9,581
Взаимосвязь статуса занятости и пола с уровнем психологического благополучия
М.Р., Н., & С.И., Б. (2026) · Cifra LLC Journals · doi:10.60797/irj.2026.170.43 · Cited by 7,950
Well-being : the foundations of hedonic psychology
Kahneman, D. J., Diener, E. F., & Schwarz, N. (1999) · Cited by 7,466
An alternative "description of personality": The Big-Five factor structure.
Goldberg, L. R. (1990) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.59.6.1216 · Cited by 6,652
Ecological momentary assessment
Shiffman, S., Stone, A. A., & Hufford, M. R. (2008) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.3.022806.091415 · Cited by 6,454
Understanding individual human mobility patterns
González, M. C., Hidalgo, C. A., & Barabási, A.-L. (2008) · Nature · doi:10.1038/nature06958 · Cited by 6,059
Cited by
Pappalardo, L., Simini, F., Barlacchi, G., & Pellungrini, R. (2022) · Journal of Statistical Software · doi:10.18637/jss.v103.i04 · Cited by 102
Self-citationExploring the relationship between regenerative grazing and Ranchers’ wellbeing
Vivas, J., & Hodbod, J. (2024) · Journal of Rural Studies · doi:10.1016/j.jrurstud.2024.103267 · Cited by 11
An individual-level ground truth dataset for home location detection
Pappalardo, L., Ferres, L., Sacasa, M., Cattuto, C., & Bravo, L. (2020) · arXiv · doi:10.48550/arxiv.2010.08814 · Cited by 7
Self-citationDepartment of Information Science, O. U., BAGHERI, S., KOURTIT, K., Management Department, O. U., NIJKAMP, P., & Erasmus University Rotterdam, R. (2025) · Transylvanian Review of Administrative Sciences · doi:10.24193/tras.si2025.1 · Cited by 1
Metadata
- Authors
- Voukelatou, V., Gabrielli, L., Miliou, I., Cresci, S., Sharma, R., Tesconi, M., & Pappalardo, L.
- Venue
- International Journal of Data Science and Analytics
- Published
- 2020-06-29
- Volume
- 11
- Issue
- 4
- Pages
- 279-309
- ISSN
- 2364-415X (ISSN-L)
- 2364-4168
- OpenAlex
- W3039901811
- Cited by
- 365
- References
- 286
- FWCI
- 40.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Measuring objective and subjective well-being: dimensions and data sources. https://app.cochat.ai/papers/10.1007/s41060-020-00224-2
- The paper
- Voukelatou, V., Gabrielli, L., Miliou, I., Cresci, S., Sharma, R., Tesconi, M., & Pappalardo, L. (2021). Measuring objective and subjective well-being: dimensions and data sources. International Journal of Data Science and Analytics. https://doi.org/10.1007/s41060-020-00224-2
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.
