Cargando…

Identifying Factors That Predict Behavioral Intention to Stay under Lockdown during the SARS-CoV-2 Pandemic Using a Structural Equation Model

Lockdown is considered to be a successful strategy for preventing the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To predict the behavioral intention to stay under lockdown (BIKL), components of the theory of planned behavior (TPB) and the behavioral indicators of infecti...

Descripción completa

Detalles Bibliográficos
Autores principales: Padilla-Bautista, Joaquin Alberto, Galindo-Aldana, Gilberto Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8910594/
https://www.ncbi.nlm.nih.gov/pubmed/35270450
http://dx.doi.org/10.3390/ijerph19052757
_version_ 1784666528657965056
author Padilla-Bautista, Joaquin Alberto
Galindo-Aldana, Gilberto Manuel
author_facet Padilla-Bautista, Joaquin Alberto
Galindo-Aldana, Gilberto Manuel
author_sort Padilla-Bautista, Joaquin Alberto
collection PubMed
description Lockdown is considered to be a successful strategy for preventing the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To predict the behavioral intention to stay under lockdown (BIKL), components of the theory of planned behavior (TPB) and the behavioral indicators of infection were applied. Sampling was conducted between 11 April and 30 May 2020. The objective of the study was to identify factors predictive of BIKL by means of a structural equation model. Method: A correlational and comparative repeated measures study was conducted with a sample of 315 participants from different cities in Mexico. Results: Model indices were χ(2) = 505.1, SD = 228, p < 0.001, χ(2)/SD = 2.2, CFI = 0.91, RMSEA = 0.06, and SRMR = 0.06; 47% of BIKL was explained by the variables attitude (β = 0.71, p < 0.001), subjective norm (β = 0.14, p = 0.042), and behavioral control (β = 0.24, p < 0.001). Conclusions: Personal and family work conviction and persuasion are favorable for the maintenance of lockdown, including concepts of civic responsibility, a positive attitude, and a family that supports compliance with lockdown. From a governmental point of view, there is a context that promotes control over the situation and exerts a positive impact on the behavioral intention to stay under lockdown.
format Online
Article
Text
id pubmed-8910594
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-89105942022-03-11 Identifying Factors That Predict Behavioral Intention to Stay under Lockdown during the SARS-CoV-2 Pandemic Using a Structural Equation Model Padilla-Bautista, Joaquin Alberto Galindo-Aldana, Gilberto Manuel Int J Environ Res Public Health Article Lockdown is considered to be a successful strategy for preventing the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To predict the behavioral intention to stay under lockdown (BIKL), components of the theory of planned behavior (TPB) and the behavioral indicators of infection were applied. Sampling was conducted between 11 April and 30 May 2020. The objective of the study was to identify factors predictive of BIKL by means of a structural equation model. Method: A correlational and comparative repeated measures study was conducted with a sample of 315 participants from different cities in Mexico. Results: Model indices were χ(2) = 505.1, SD = 228, p < 0.001, χ(2)/SD = 2.2, CFI = 0.91, RMSEA = 0.06, and SRMR = 0.06; 47% of BIKL was explained by the variables attitude (β = 0.71, p < 0.001), subjective norm (β = 0.14, p = 0.042), and behavioral control (β = 0.24, p < 0.001). Conclusions: Personal and family work conviction and persuasion are favorable for the maintenance of lockdown, including concepts of civic responsibility, a positive attitude, and a family that supports compliance with lockdown. From a governmental point of view, there is a context that promotes control over the situation and exerts a positive impact on the behavioral intention to stay under lockdown. MDPI 2022-02-27 /pmc/articles/PMC8910594/ /pubmed/35270450 http://dx.doi.org/10.3390/ijerph19052757 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Padilla-Bautista, Joaquin Alberto
Galindo-Aldana, Gilberto Manuel
Identifying Factors That Predict Behavioral Intention to Stay under Lockdown during the SARS-CoV-2 Pandemic Using a Structural Equation Model
title Identifying Factors That Predict Behavioral Intention to Stay under Lockdown during the SARS-CoV-2 Pandemic Using a Structural Equation Model
title_full Identifying Factors That Predict Behavioral Intention to Stay under Lockdown during the SARS-CoV-2 Pandemic Using a Structural Equation Model
title_fullStr Identifying Factors That Predict Behavioral Intention to Stay under Lockdown during the SARS-CoV-2 Pandemic Using a Structural Equation Model
title_full_unstemmed Identifying Factors That Predict Behavioral Intention to Stay under Lockdown during the SARS-CoV-2 Pandemic Using a Structural Equation Model
title_short Identifying Factors That Predict Behavioral Intention to Stay under Lockdown during the SARS-CoV-2 Pandemic Using a Structural Equation Model
title_sort identifying factors that predict behavioral intention to stay under lockdown during the sars-cov-2 pandemic using a structural equation model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8910594/
https://www.ncbi.nlm.nih.gov/pubmed/35270450
http://dx.doi.org/10.3390/ijerph19052757
work_keys_str_mv AT padillabautistajoaquinalberto identifyingfactorsthatpredictbehavioralintentiontostayunderlockdownduringthesarscov2pandemicusingastructuralequationmodel
AT galindoaldanagilbertomanuel identifyingfactorsthatpredictbehavioralintentiontostayunderlockdownduringthesarscov2pandemicusingastructuralequationmodel