Evidence map›Paper›PMID 39495771›Full record

ArticlePloS one2024

Predicting technostress: The Big Five model of personality and subjective well-being.

Dámaris Cuadrado, Inmaculada Otero, Alexandra Martínez, Tania París, Silvia Moscoso

Abstract read
In one paragraph

Article in PloS one, 2024. 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

5 authors.

Dámaris CuadradoDepartment of Political Science and Sociology, University of Santiago de Compostela, Santiago de Compostela, Spain.ORCID 0000-0002-6515-5332
Inmaculada OteroDepartment of Political Science and Sociology, University of Santiago de Compostela, Santiago de Compostela, Spain.
Alexandra MartínezDepartment of Political Science and Sociology, University of Santiago de Compostela, Santiago de Compostela, Spain.
Tania ParísDepartment of Political Science and Sociology, University of Santiago de Compostela, Santiago de Compostela, Spain.
Silvia MoscosoDepartment of Political Science and Sociology, University of Santiago de Compostela, Santiago de Compostela, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The main goal of the current study is to broaden the knowledge on the association between personality, subjective well-being (SWB) and technostress in an academic context. This research specifically examines the prevalence of technostress in a European university sample. It also explores the relationship between technostress and its dimensions with the Big Five model of personality and with SWB and its affective and cognitive components. Finally, the combined predictive validity of the Big Five and SWB on technostress is tested. The sample was composed of 346 undergraduate students. Correlational and multiple regression analyses were carried out. Results show that fatigue and anxiety are the most frequently experienced dimensions of technostress. Emotional stability, openness to experience, and SWB are negatively and significantly correlated to technostress. Multiple regression analyses show that the Big Five factors and SWB account for technostress variance, the main predictor being the affective component of SWB. These results contribute to a more comprehensive understanding of technostress and suggest that personality traits and SWB are important factors in its prediction. The theoretical and practical implications will be discussed.

Indexed as

PersonalityAdolescentAdultFemaleHumansMaleModels, PsychologicalPersonal SatisfactionStudentsUniversitiesYoung Adult

Identifiers

PMID39495771
PMCPMC11534232

What OpenQuestion holds

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Registered trials

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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.