Evidence map›Paper›PMID 36553956›Full record

ArticleHealthcare (Basel, Switzerland)2022

The Impact of Popular Science Articles by Physicians on Their Performance on Online Medical Platforms.

Jingfang Liu, Shiqi Wang, Huihong Jiang

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

3 authors.

Jingfang LiuSchool of Management, Shanghai University, Shanghai 201800, China.
Shiqi WangSchool of Management, Shanghai University, Shanghai 201800, China.
Huihong JiangSchool of Management, Shanghai University, Shanghai 201800, China.ORCID 0000-0003-1444-4801

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The public demand for popular science knowledge regarding health is increasing, and physicians' popular science practices on online medical platforms are becoming frequent. Few studies have been conducted to address the relationship between specific characteristics of popular science articles by physicians and their performance. This study explored the impact of the characteristics of popular science articles on physicians' performance based on the elaboration likelihood model (ELM) from the central path (topic focus and readability) and the peripheral path (form diversity). Data on four diseases, namely, lung cancer, brain hemorrhage, hypertension, and depression, were collected from an online medical platform, resulting in relevant personal data from 1295 doctors and their published popular science articles. Subsequently, the independent variables were quantified using thematic analysis and formula calculation, and the research model and hypotheses proposed in this paper were verified through empirical analysis. The results revealed that the topic focus, readability, and form diversity of popular science articles by physicians had a significant positive effect on physicians' performance. This study enriches the research perspective on the factors influencing physicians' performance, which has guiding implications for both physicians and platforms, thereby providing a basis for patients to choose physicians and enabling patients to receive popular science knowledge regarding health in an effective manner.

Indexed as

elaboration likelihood modelonline healthcarephysician performancepopular science articles

Identifiers

PMID36553956
PMCPMC9777991

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.