Cargando…

Getting Connected to M-Health Technologies through a Meta-Analysis

The demand for mobile e-health technologies (m-health) continues with constant growth, stimulating the technological advancement of such devices. However, the customer needs to perceive the utility of these devices to incorporate them into their daily lives. Hence, this study aims to identify users’...

Descripción completa

Detalles Bibliográficos
Autores principales: Calegari, Luiz Philipi, Tortorella, Guilherme Luz, Fettermann, Diego Castro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001891/
https://www.ncbi.nlm.nih.gov/pubmed/36901379
http://dx.doi.org/10.3390/ijerph20054369
_version_ 1784904256426344448
author Calegari, Luiz Philipi
Tortorella, Guilherme Luz
Fettermann, Diego Castro
author_facet Calegari, Luiz Philipi
Tortorella, Guilherme Luz
Fettermann, Diego Castro
author_sort Calegari, Luiz Philipi
collection PubMed
description The demand for mobile e-health technologies (m-health) continues with constant growth, stimulating the technological advancement of such devices. However, the customer needs to perceive the utility of these devices to incorporate them into their daily lives. Hence, this study aims to identify users’ perceptions regarding the acceptance of m-health technologies based on a synthesis of meta-analysis studies on the subject in the literature. Using the relations and constructs proposed in the UTAUT2 (Unified Theory of Acceptance and Use of Technology 2) technology acceptance model, the methodological approach utilized a meta-analysis to raise the effect of the main factors on the Behavioral Intention to Use m-health technologies. Furthermore, the model proposed also estimated the moderation effect of gender, age, and timeline variables on the UTAUT2 relations. In total, the meta-analysis utilized 84 different articles, which presented 376 estimations based on a sample of 31,609 respondents. The results indicate an overall compilation of the relations, as well as the primary factors and moderating variables that determine users’ acceptance of the studied m-health systems.
format Online
Article
Text
id pubmed-10001891
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-100018912023-03-11 Getting Connected to M-Health Technologies through a Meta-Analysis Calegari, Luiz Philipi Tortorella, Guilherme Luz Fettermann, Diego Castro Int J Environ Res Public Health Article The demand for mobile e-health technologies (m-health) continues with constant growth, stimulating the technological advancement of such devices. However, the customer needs to perceive the utility of these devices to incorporate them into their daily lives. Hence, this study aims to identify users’ perceptions regarding the acceptance of m-health technologies based on a synthesis of meta-analysis studies on the subject in the literature. Using the relations and constructs proposed in the UTAUT2 (Unified Theory of Acceptance and Use of Technology 2) technology acceptance model, the methodological approach utilized a meta-analysis to raise the effect of the main factors on the Behavioral Intention to Use m-health technologies. Furthermore, the model proposed also estimated the moderation effect of gender, age, and timeline variables on the UTAUT2 relations. In total, the meta-analysis utilized 84 different articles, which presented 376 estimations based on a sample of 31,609 respondents. The results indicate an overall compilation of the relations, as well as the primary factors and moderating variables that determine users’ acceptance of the studied m-health systems. MDPI 2023-02-28 /pmc/articles/PMC10001891/ /pubmed/36901379 http://dx.doi.org/10.3390/ijerph20054369 Text en © 2023 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
Calegari, Luiz Philipi
Tortorella, Guilherme Luz
Fettermann, Diego Castro
Getting Connected to M-Health Technologies through a Meta-Analysis
title Getting Connected to M-Health Technologies through a Meta-Analysis
title_full Getting Connected to M-Health Technologies through a Meta-Analysis
title_fullStr Getting Connected to M-Health Technologies through a Meta-Analysis
title_full_unstemmed Getting Connected to M-Health Technologies through a Meta-Analysis
title_short Getting Connected to M-Health Technologies through a Meta-Analysis
title_sort getting connected to m-health technologies through a meta-analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001891/
https://www.ncbi.nlm.nih.gov/pubmed/36901379
http://dx.doi.org/10.3390/ijerph20054369
work_keys_str_mv AT calegariluizphilipi gettingconnectedtomhealthtechnologiesthroughametaanalysis
AT tortorellaguilhermeluz gettingconnectedtomhealthtechnologiesthroughametaanalysis
AT fettermanndiegocastro gettingconnectedtomhealthtechnologiesthroughametaanalysis