Evidence map›Paper›PMID 40050859›Full record

ArticleBMC medical informatics and decision making2025

Offline visit intention of online patients: the Grice's maxims and patient involvement.

Xianye Cao, Yongmei Liu, Zian Fang, Zhangxiang Zhu

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Xianye CaoSchool of Business Administration, Hunan University of Technology and Business, Changsha, 410205, China.
Yongmei LiuSchool of Business, Central South University, Changsha, 410083, China. liuyongmeicn@163.com.
Zian FangSchool of Business, Central South University, Changsha, 410083, China.
Zhangxiang ZhuCollege of Tourism, Hunan Normal University, Changsha, 410081, China.

Funding

How can e-health services advance the health management gateway? Research from the perspective of "unity of knowledge and action" 72071213Patients' Medical Consulting Behaviors in the Context of Online and Offline Integration: Perspective of Patients' Information Process 72101088the Hunan Provincial Department of Education's Outstanding Young Scholars Fund 24B0567
6 · The paper itself

Abstract

Online Healthcare Consulting Services (OHCS) can benefit physicians and patients. However, it is unclear how OHCS and what types of persuasive content enhance patients' intentions to visit offline. Based on the Elaboration Likelihood Model (ELM) and Grice's maxims of the Cooperative Principle, we formulated hypotheses related to factors in the central route, peripheral route, and patient involvement that influence patients' offline visit intentions. We used the amount of information, reliability, relevance, and understandability to measure information quality. By collecting data from an online healthcare site, we employed a regression model to evaluate our hypotheses. The results revealed that central route factors (amount of information, reliability, relevance, and understandability) and peripheral cues positively affect patients' offline visits. We also verified that patient involvement increases the impact of central route factors. This study extended the application of ELM and Grice's maxims in the field of OHCS, offering insights into how patients form intentions to visit offline through persuasive online content and providing valuable practical guidance for online physicians.

Indexed as

IntentionInternetPatient ParticipationPersuasive CommunicationAdultFemaleHumansMaleMiddle AgedELMGrice’s maximsOnline healthcarePatient involvementVisit intention

Identifiers

PMID40050859
PMCPMC11887380

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Registered trials

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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.