Evidence map›Paper›PMID 36247861›Full record

ArticleContrast media & molecular imaging2022

Nursing Teaching Curriculum Setting by Introducing Postcompetency Model under the Vision of Internet Informatization.

Lan Xiao, Yi Men

RetractedAbstract readRetracted Publication
In one paragraph

Article in Contrast media & molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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

5 · Who and what money

Authors and funding

2 authors.

Lan XiaoDepartment of Head and Neck Oncology, West China School of Stomatology, Sichuan University, Chengdu, Sichuan, China.
Yi MenDepartment of Head and Neck Oncology, West China School of Stomatology, Sichuan University, Chengdu, Sichuan, China.ORCID 0000-0001-9234-4131

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The nursing curriculum is to be modernized to improve the student's skills in meeting the recent trends in medical and healthcare fields. The curriculum improvements are based on expert recommendations, authors, and informative data from different web sources. The challenging task is to improve the readability and understandability of the curriculum to real-time standards. Considering the above facts, this article introduces a refined curriculum with Internet information analysis (RC-IIA) method. The proposed method incorporates the distributed Internet, journal, and previous curriculum information within the active nursing syllabus. This prevents repetitions and less-informative content within the active curriculum. Besides, classification learning for knowledge-based representations is used within the curriculum to improve competency. Based on the refined information, a recommendation-based curriculum is preferred for varying information across different standards. The proposed analysis method relies on existing and distributed information across multiple curriculum providers for leveraging the visibility and prolonging the stealth of the nursing curriculum.

Indexed as

CurriculumInternetHumans

Identifiers

PMID36247861
PMCPMC9534662

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.