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A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysis

BACKGROUND: The development of Internet information technology will generate an Internet use gap, which will have certain adverse effects on health, but internet information dependence can alleviate these negative effects. OBJECTIVE: This article is to demonstrate the negative impact of the internet...

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Autores principales: He, Yuanyuan, Zhou, Lulin, Xu, Xinglong, Li, JunShan, Li, Jiaxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667051/
https://www.ncbi.nlm.nih.gov/pubmed/36407977
http://dx.doi.org/10.3389/fpubh.2022.958834
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author He, Yuanyuan
Zhou, Lulin
Xu, Xinglong
Li, JunShan
Li, Jiaxing
author_facet He, Yuanyuan
Zhou, Lulin
Xu, Xinglong
Li, JunShan
Li, Jiaxing
author_sort He, Yuanyuan
collection PubMed
description BACKGROUND: The development of Internet information technology will generate an Internet use gap, which will have certain adverse effects on health, but internet information dependence can alleviate these negative effects. OBJECTIVE: This article is to demonstrate the negative impact of the internet use gap on population health in developing countries and to propose improvement paths. METHODS: This article used the 2018 China Family Tracking Survey database (N = 11086). The research first used Latent class analysis (LCA) to identify potential categories of users with different Internet usage situations, then used the Bolck, Croon, and Hagenaars (BCH) method to perform latent class modeling with a continuous distal outcome, and finally built an intermediary model about Internet information dependence based on the model constraint function in Mplus software. RESULTS: (1) The Internet users can be divided into light-life users (C1: N = 1,061, 9.57%), all-around users (N = 1,980, 17.86%(C2: N = 1,980, 17.86%), functional users (C3: N = 1,239, 11.18%), and pure-life users (C4: N = 6,806, 61.39%). (2) We examined individual characteristics, social characteristics and different living habits, and health differences between the latent classes. For example, there are certain structural differences on the effect of different categories of Internet use on health (C1: M = 3.089, SE = 0.040; C2: M = 3.151, SE = 0.037; C3: M = 3.070, SE = 0.035; C4: M = 2.948, SE = 0.016; P < 0.001). (3) The Internet use gap can affect health through the indirect path of Internet information dependence, and some of the mediation effects are significant. When the functional user group (C3) was taken as the reference group, the mediating effect values of light-life users (C1) and all-around users (C4) on health were −0.050 (SE = 0.18, Est./SE = −3.264, P = 0.001) and −0.080 (SE = 0.010, Est./SE = −8.412, P = 0.000) through Internet information dependence, respectively. However, the effect of categories on health was not significant after adding indirect paths. CONCLUSION: The Internet use gap has a significant effect on health, and Internet information dependence plays an intermediary role in this effect path. The study proposes that attention should be paid to the diversified development of Internet use, the positive guiding function of Internet information channels should be made good use of, and the countermeasures and suggestions of marginalized groups in the digital age should also be paid attention to and protected.
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spelling pubmed-96670512022-11-17 A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysis He, Yuanyuan Zhou, Lulin Xu, Xinglong Li, JunShan Li, Jiaxing Front Public Health Public Health BACKGROUND: The development of Internet information technology will generate an Internet use gap, which will have certain adverse effects on health, but internet information dependence can alleviate these negative effects. OBJECTIVE: This article is to demonstrate the negative impact of the internet use gap on population health in developing countries and to propose improvement paths. METHODS: This article used the 2018 China Family Tracking Survey database (N = 11086). The research first used Latent class analysis (LCA) to identify potential categories of users with different Internet usage situations, then used the Bolck, Croon, and Hagenaars (BCH) method to perform latent class modeling with a continuous distal outcome, and finally built an intermediary model about Internet information dependence based on the model constraint function in Mplus software. RESULTS: (1) The Internet users can be divided into light-life users (C1: N = 1,061, 9.57%), all-around users (N = 1,980, 17.86%(C2: N = 1,980, 17.86%), functional users (C3: N = 1,239, 11.18%), and pure-life users (C4: N = 6,806, 61.39%). (2) We examined individual characteristics, social characteristics and different living habits, and health differences between the latent classes. For example, there are certain structural differences on the effect of different categories of Internet use on health (C1: M = 3.089, SE = 0.040; C2: M = 3.151, SE = 0.037; C3: M = 3.070, SE = 0.035; C4: M = 2.948, SE = 0.016; P < 0.001). (3) The Internet use gap can affect health through the indirect path of Internet information dependence, and some of the mediation effects are significant. When the functional user group (C3) was taken as the reference group, the mediating effect values of light-life users (C1) and all-around users (C4) on health were −0.050 (SE = 0.18, Est./SE = −3.264, P = 0.001) and −0.080 (SE = 0.010, Est./SE = −8.412, P = 0.000) through Internet information dependence, respectively. However, the effect of categories on health was not significant after adding indirect paths. CONCLUSION: The Internet use gap has a significant effect on health, and Internet information dependence plays an intermediary role in this effect path. The study proposes that attention should be paid to the diversified development of Internet use, the positive guiding function of Internet information channels should be made good use of, and the countermeasures and suggestions of marginalized groups in the digital age should also be paid attention to and protected. Frontiers Media S.A. 2022-11-02 /pmc/articles/PMC9667051/ /pubmed/36407977 http://dx.doi.org/10.3389/fpubh.2022.958834 Text en Copyright © 2022 He, Zhou, Xu, Li and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
He, Yuanyuan
Zhou, Lulin
Xu, Xinglong
Li, JunShan
Li, Jiaxing
A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysis
title A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysis
title_full A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysis
title_fullStr A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysis
title_full_unstemmed A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysis
title_short A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysis
title_sort study on the impact and buffer path of the internet use gap on population health: latent category analysis and mediating effect analysis
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667051/
https://www.ncbi.nlm.nih.gov/pubmed/36407977
http://dx.doi.org/10.3389/fpubh.2022.958834
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