Evidence map›Paper›PMID 37868587›Full record

ArticleFrontiers in psychology2023

Predictors of depression: lifestyle choices during the pandemic.

Sarka Tesarova, Ondrej Pekacek, Alessandro Porrovecchio

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2023. 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
0.6field-weighted citation impact, top 29% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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

3 authors at 2 institutions in 2 countries.

Sarka TesarovaInstitute of Sociological Studies, Faculty of Social Sciences, Charles University, Prague, Czechia.
Ondrej PekacekInstitute of Sociological Studies, Faculty of Social Sciences, Charles University, Prague, Czechia.
Alessandro PorrovecchioUniv. Littoral Côte d'Opale, Univ. Lille, Univ. Artois - ULR 7369 - URePSSS - Unité de Recherche Pluridisciplinaire Sport Santé Société, Dunkerque, France.
Charles University · CZUnité de Recherche Pluridisciplinaire Sport, Santé, Société · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our study intends to specify the impact of the singular pandemic stressors on the population and also quantify the contribution of different predictors of depression; some of them are stronger than others, and this research shows how the whole effect is divided into single items. This research included a structured online survey using data from 11,340 respondents from six European countries during the first months of the pandemic. The statistical analysis focused on how behavioural patterns appear in different groups of the population and how they mark the psychological wellbeing of these groups with regard to various factors. We targeted social media's role and analyzed the impact of its consumption on symptoms of depression in different groups divided by age and other characteristics. The analysis creates a mosaic of lifestyle choices and other characteristics that manifest different effects on depression inside selected groups whereas several groups generated by the cluster analysis are less vulnerable to their effect than others. Regarding our findings, the perceived reality through information sources and the manner of their processing seems to be more significant than the tangible reality (poor self-reported health correlated with depression more strongly than intrinsic health limitations).

Indexed as

COVID-19depressioneconomic worrieslifestylemental healthsocial mediasportwellbeing

Identifiers

PMID37868587
PMCPMC10585652
OpenAlexW4387364901

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.