Evidence map›Paper›PMID 37998673›Full record

ArticleBehavioral sciences (Basel, Switzerland)2023

Analysis of Psychological Well-Being from a Compositional Data Analysis Perspective: A New Approach.

María Cortés-Rodríguez, Purificación Galindo-Villardón, Mercedes Sánchez-Barba, Eusebi Jarauta-Bragulat, José David Urchaga-Litago

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Enhancing Psychological Well-Being Assessment Through Data Mining: A Case Study from Thailand.European journal of investigation in health, psychology and education · 2025
    Article
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4 · The record

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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

5 authors.

María Cortés-RodríguezDepartment of Statistics, University of Salamanca, 37008 Salamanca, Spain.ORCID 0000-0001-9446-0259
Purificación Galindo-VillardónDepartment of Statistics, University of Salamanca, 37008 Salamanca, Spain.ORCID 0000-0001-6977-7545
Mercedes Sánchez-BarbaDepartment of Statistics, University of Salamanca, 37008 Salamanca, Spain.ORCID 0000-0002-3324-5798
Eusebi Jarauta-BragulatDepartment of Civil and Environmental Engineering, North Campus, Technical University of Catalonia, 08034 Barcelona, Spain.
José David Urchaga-LitagoFaculty of Communication, Pontifical University of Salamanca, 37002 Salamanca, Spain.ORCID 0000-0001-6624-070X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Well-being is a widely studied construct in psychology. In 1989, Carol Ryff proposed the "Scale of Psychological Well-Being (SPWB)", which has been validated in multiple languages. The instrument assesses six dimensions of psychological well-being: Self-acceptance, Positive Relationships with Others, Autonomy, Environmental Mastery, Purpose in Life, and Personal Growth. In this article, we propose to enrich the traditional approach of directly interpreting the raw scores in each dimension by incorporating Compositional Data Analysis. This new approach aims to identify "what proportion" of each dimension constitutes well-being, which will allow us to analyze the interactions between the different dimensions of well-being and balance among them. To achieve this, we introduce two position ratios (PR1 and PR2) and a general adjustment indicator called the General Indicator of Subjective Psychological Well-Being (GISPW), which characterizes individuals in a compositional manner, providing a fresh perspective in the interpretation of psychological test results, specifically those related to PWB. The proposal is illustrated with three cases taken from a study involving 628 university students who completed the psychological well-being scale questionnaire. The results show that the GISPW, PR1, and PR2 obtained offer relevant information about the overall balance of each case in the different dimensions.

Indexed as

compositional data analysislog ratio general indicatorpsychological well-being

Identifiers

PMID37998673
PMCPMC10669479

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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.