Evidence map›Paper›PMID 36934137›Full record

ArticleScientific reports2023

Moderation effects of loneliness between fatalism and wellbeing during the COVID-19 pandemic.

Rafael Miranda Ayala, Cristina Torrelles-Nadal, Giancarlo Magro Lazo, Gemma Filella Guiu

Open access · goldFull text read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 3 institutions in 3 countries.

Rafael Miranda AyalaUniversidad Continental, Av San Carlos 1980, Huancayo, 12000, Peru.ORCID 0000-0001-8640-6439
Cristina Torrelles-NadalINEFC- University of Lleida, Partida La Caparrella, s/n, 25192, Lleida, Spain. ctorrelles@gencat.cat.ORCID 0000-0002-8669-110X
Giancarlo Magro LazoUniversidad Andres Bello, Santiago, Chile.ORCID 0000-0002-6707-4181
Gemma Filella GuiuUniversity of Lleida, Avinguda de L'estudi General nº4, 25001, Lleida, Spain.ORCID 0000-0002-0696-296X
Universitat de Lleida · ESUniversidad Andrés Bello · CLUniversidad Continental · PE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has put more than just our physical health at risk. Due to containment measures, people have become increasingly isolated and have drastically reduced their daily social interactions. Many studies have already shown the negative effects of these measures, including fatalism. However, research linking fatalism during COVID-19 to well-being indicators is still limited. The goal of this study is to examine the relationship between COVID-19-related fatalism and well-being indicators, as well as the role of loneliness in moderating this relationship. Data was collected from 1,036 adults in Peru through an online survey that included the Quality-of-Life Index, the Fatalism Facing COVID-19 Scale, the Loneliness Scale, and the Mood Assessment Scale. Three models were tested using linear regression and ordinary least squares with bias-corrected bootstrapping. The results indicate that fatalism has a negative impact on quality of life and a positive effect on negative affect, and loneliness moderates both relationships, supporting the conclusion that fatalism exacerbates the effect of well-being indicators and negative affect.

Indexed as

COVID-19AdultAffectHumansLonelinessPandemicsQuality of Life

Identifiers

PMID36934137
PMCPMC10024282
OpenAlexW4327857214

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read3
Read underepoch 390

Registered trials

None linked

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.