Evidence map›Paper›PMID 36324785›Full record

ArticleFrontiers in psychology2022

Research on the influencing factors of users' information processing in online health communities based on heuristic-systematic model.

Yunyun Gao, Liyue Gong, Hao Liu, Yi Kong, Xusheng Wu, Yi Guo, DeHua Hu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yunyun GaoDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, China.
Liyue GongDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, China.
Hao LiuDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, China.
Yi KongDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, China.
Xusheng WuShenzhen Health Development Research and Data Management Center, Shenzhen, Guangdong, China.
Yi GuoDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, China.
DeHua HuDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid development of the Internet and the normalization of COVID-19 epidemic prevention and control, Online health communities (OHCs) have gradually become one of the important ways for people to obtain health information, and users have to go through a series of information processing when facing the massive amount of data. Understanding the factors influencing user information processing is necessary to promote users' health literacy, health knowledge popularization and health behavior shaping. Based on the Heuristic-Systematic Model (HSM), Information Ecology Theory, Privacy Trade-Off and Self-Efficacy Theory, we constructed a model of factors influencing user information processing in online health communities. We found that information quality and emotional support had indirect effects on heuristic and systematic information processing, and these effects were mediated by privacy concerns and self-efficacy. In our research model, systematic information processing was most positively influenced directly by self-efficacy. Privacy concerns had a direct negative correlation with both dual information processing pathways. Therefore, OHCs managers should develop relevant regulations to ensure the information quality in OHCs and improve privacy protection services to promote user information processing by improving users' self-efficacy and reducing their privacy concerns. Providing a user-friendly and interactive environment for users is also recommended to create more emotional support, thus facilitating more systematic information processing.

Indexed as

heuristic-systematic modelinfluencing factorsinformation ecologyinformation processingonline health communityprivacy trade-offself-efficacy

Identifiers

PMID36324785
PMCPMC9618707

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.