Evidence map›Paper›PMID 34149525›Full record

ArticleFrontiers in psychology2021

A Bifactor Model of Subjective Well-Being at Personal, Community, and Country Levels: A Case With Three Latin-American Countries.

Javier Torres-Vallejos, Joel Juarros-Basterretxea, Juan Carlos Oyanedel, Masatoshi Sato

Abstract read
In one paragraph

Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Javier Torres-VallejosFacultad de Educación y Ciencias Sociales, Universidad Andres Bello, Santiago, Chile.
Joel Juarros-BasterretxeaCentro Universitario de la Defensa de Zaragoza, Zaragoza, Spain.
Juan Carlos OyanedelFacultad de Educación y Ciencias Sociales, Universidad Andres Bello, Santiago, Chile.
Masatoshi SatoFacultad de Educación y Ciencias Sociales, Universidad Andres Bello, Santiago, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improving citizens' subjective well-being (SWB) has become an increasingly visible policy goal across industrialized countries. Although an increasing number of studies have investigated SWB at the individual level, little is known about subjective evaluation at social levels, such as the community and national levels. While the relationships between these levels have been analyzed in previous research, these assessments, which are part of the same unique construct of SWB, are under-investigated. The purpose of this study was to examine the dimensionality and reliability of a single measure of SWB, which contained individual, community, and national levels across three Latin-American countries (Argentina, Chile, and Venezuela), using a bifactor model analysis. Findings showed that the bifactor model exhibited a good fit to the data for the three countries. However, invariance testing between countries was not fully supported because of each item's specific contribution to both specific and general constructs. The analyses of each country showed that the SWB construct was in a gray area between unidimensionality and multidimensionality; some factors contributed more to the general factor and others to the specific level, depending on the country. These findings call for integrating more distant levels (community and country levels) into the understanding of SWB at the individual level, as they contribute not only to an overall construct, but they make unique contributions to SWB, which must be considered in public policy making.

Indexed as

bifactor modelcommunitycountrymeasurementsubjective well-being

Identifiers

PMID34149525
PMCPMC8209295

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.