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

BackgroundThe 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.ObjectiveThis article is to demonstrate the negative impact of the internet use...

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Main Authors: Yuanyuan He, Lulin Zhou, Xinglong Xu, JunShan Li, Jiaxing Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Public Health
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2022.958834/full
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author Yuanyuan He
Lulin Zhou
Xinglong Xu
JunShan Li
Jiaxing Li
author_facet Yuanyuan He
Lulin Zhou
Xinglong Xu
JunShan Li
Jiaxing Li
author_sort Yuanyuan He
collection DOAJ
description BackgroundThe 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.ObjectiveThis article is to demonstrate the negative impact of the internet use gap on population health in developing countries and to propose improvement paths.MethodsThis 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.ConclusionThe 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 doaj.art-db8ba16dc755481d91b6370563a70c372022-12-22T03:57:07ZengFrontiers Media S.A.Frontiers in Public Health2296-25652022-11-011010.3389/fpubh.2022.958834958834A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysisYuanyuan He0Lulin Zhou1Xinglong Xu2JunShan Li3Jiaxing Li4Department of Management, Jiangsu University, Zhenjiang, ChinaDepartment of Management, Jiangsu University, Zhenjiang, ChinaDepartment of Management, Jiangsu University, Zhenjiang, ChinaDepartment of Economics and Management, Jiangxi University of Chinese Medicine, Nanchang, ChinaMetropolitan College, Boston University, Boston, MA, United StatesBackgroundThe 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.ObjectiveThis article is to demonstrate the negative impact of the internet use gap on population health in developing countries and to propose improvement paths.MethodsThis 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.ConclusionThe 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.https://www.frontiersin.org/articles/10.3389/fpubh.2022.958834/fullinternet use gapinternet information dependencepopulation healthlatent category analysisregression analysis
spellingShingle Yuanyuan He
Lulin Zhou
Xinglong Xu
JunShan Li
Jiaxing Li
A study on the impact and buffer path of the internet use gap on population health: Latent category analysis and mediating effect analysis
Frontiers in Public Health
internet use gap
internet information dependence
population health
latent category analysis
regression 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 internet use gap
internet information dependence
population health
latent category analysis
regression analysis
url https://www.frontiersin.org/articles/10.3389/fpubh.2022.958834/full
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