Modeling behavioral intention of using health-related WeChat official accounts through ELM and SCT factors using the PLS-SEM approach

Health-related WeChat Official Accounts are widely used in China. However, limited research has explored how cognitive processing and psychological beliefs influence user behavior on these platforms. Previous studies have rarely examined the cognitive and psychological mechanisms that underlie users...

Full description

Bibliographic Details
Main Authors: Zhang, Xin, Tang, Qingqing, Li, Shuhui
Format: Article
Language:English
Published: Nature Research 2025
Online Access:http://psasir.upm.edu.my/id/eprint/120378/
http://psasir.upm.edu.my/id/eprint/120378/1/120378.pdf
_version_ 1848868173305085952
author Zhang, Xin
Tang, Qingqing
Li, Shuhui
author_facet Zhang, Xin
Tang, Qingqing
Li, Shuhui
author_sort Zhang, Xin
building UPM Institutional Repository
collection Online Access
description Health-related WeChat Official Accounts are widely used in China. However, limited research has explored how cognitive processing and psychological beliefs influence user behavior on these platforms. Previous studies have rarely examined the cognitive and psychological mechanisms that underlie users’ behavioral intention in this context. To address this gap, this study proposes a psychologically grounded dual-pathway model that integrates the Elaboration Likelihood Model (ELM) and Social Cognitive Theory (SCT) to explain how individual information processing and self-efficacy jointly shape user behavioral intention. Data were collected through an online survey (n = 434) conducted from April 11 to May 9, 2024. PLS-SEM was applied using SmartPLS 4.1. The results show that both central and peripheral processing routes significantly influence self-efficacy, which in turn mediates their effects on behavioral intention. Gender moderates the peripheral pathway, with female users more responsive to credibility cues. However, user experience did not have a significant moderating effect. This study extends the application of ELM and SCT in digital health communication by clarifying how different processing routes influence user behavior via self-efficacy. It offers practical insights for healthcare institutions, government health departments, and nonprofit organizations seeking to improve user engagement and satisfaction with WOAs.
first_indexed 2025-11-15T14:48:11Z
format Article
id upm-120378
institution Universiti Putra Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T14:48:11Z
publishDate 2025
publisher Nature Research
recordtype eprints
repository_type Digital Repository
spelling upm-1203782025-10-01T02:11:45Z http://psasir.upm.edu.my/id/eprint/120378/ Modeling behavioral intention of using health-related WeChat official accounts through ELM and SCT factors using the PLS-SEM approach Zhang, Xin Tang, Qingqing Li, Shuhui Health-related WeChat Official Accounts are widely used in China. However, limited research has explored how cognitive processing and psychological beliefs influence user behavior on these platforms. Previous studies have rarely examined the cognitive and psychological mechanisms that underlie users’ behavioral intention in this context. To address this gap, this study proposes a psychologically grounded dual-pathway model that integrates the Elaboration Likelihood Model (ELM) and Social Cognitive Theory (SCT) to explain how individual information processing and self-efficacy jointly shape user behavioral intention. Data were collected through an online survey (n = 434) conducted from April 11 to May 9, 2024. PLS-SEM was applied using SmartPLS 4.1. The results show that both central and peripheral processing routes significantly influence self-efficacy, which in turn mediates their effects on behavioral intention. Gender moderates the peripheral pathway, with female users more responsive to credibility cues. However, user experience did not have a significant moderating effect. This study extends the application of ELM and SCT in digital health communication by clarifying how different processing routes influence user behavior via self-efficacy. It offers practical insights for healthcare institutions, government health departments, and nonprofit organizations seeking to improve user engagement and satisfaction with WOAs. Nature Research 2025 Article PeerReviewed text en cc_by_nc_nd_4 http://psasir.upm.edu.my/id/eprint/120378/1/120378.pdf Zhang, Xin and Tang, Qingqing and Li, Shuhui (2025) Modeling behavioral intention of using health-related WeChat official accounts through ELM and SCT factors using the PLS-SEM approach. Scientific Reports, 15 (1). art. no. 27475. pp. 1-17. ISSN 2045-2322 https://www.nature.com/articles/s41598-025-12138-9?error=cookies_not_supported&code=5b809b0d-ae93-4c47-8eb9-7da524646a0e 10.1038/s41598-025-12138-9
spellingShingle Zhang, Xin
Tang, Qingqing
Li, Shuhui
Modeling behavioral intention of using health-related WeChat official accounts through ELM and SCT factors using the PLS-SEM approach
title Modeling behavioral intention of using health-related WeChat official accounts through ELM and SCT factors using the PLS-SEM approach
title_full Modeling behavioral intention of using health-related WeChat official accounts through ELM and SCT factors using the PLS-SEM approach
title_fullStr Modeling behavioral intention of using health-related WeChat official accounts through ELM and SCT factors using the PLS-SEM approach
title_full_unstemmed Modeling behavioral intention of using health-related WeChat official accounts through ELM and SCT factors using the PLS-SEM approach
title_short Modeling behavioral intention of using health-related WeChat official accounts through ELM and SCT factors using the PLS-SEM approach
title_sort modeling behavioral intention of using health-related wechat official accounts through elm and sct factors using the pls-sem approach
url http://psasir.upm.edu.my/id/eprint/120378/
http://psasir.upm.edu.my/id/eprint/120378/
http://psasir.upm.edu.my/id/eprint/120378/
http://psasir.upm.edu.my/id/eprint/120378/1/120378.pdf