Evidence map›Paper›PMID 37082249›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2023

Analysis of the Clinical Effect of Visual Electrophysiological Examination Combined with Targeted Health Education Nursing in Children.

Yanan Qiu, Lan Xiong

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2023. 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 It has been retracted, and should not be counted.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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Yanan QiuDepartment of Ophthalmology, Lanzhou University Second Hospital, Lanzhou, Gansu 730000, China.
Lan XiongDepartment of Ophthalmology, Lanzhou University Second Hospital, Lanzhou, Gansu 730000, China.ORCID https://orcid.org/0000-0002-7616-5739
Lanzhou University Second Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To analyze the clinical effect of visual electrophysiological examination combined with targeted health education nursing in children. Methods: A total of 100 children who underwent visual electrophysiological examinations in the Ophthalmology Department of our hospital from March 2019 to March 2021 were selected as the study subjects. The children were randomly divided into two groups, the control group and the observation group, with 50 children in each group. Children in the control group received routine nursing, while those in the observation group received a combination of routine nursing and targeted health education nursing. The nursing satisfaction, degree of cooperation with examination, examination time, changes in the psychological state, and the stress response of the children and their families were then compared and analyzed. Results: The nursing satisfaction of the observation group was higher than that of the control group (94.0% vs. 80.0%) ( Conclusion: The combination of visual electrophysiological examination and targeted health education nursing in children has a remarkable clinical effect. It improves the children's degree of comfort as well as the parents' degree of satisfaction. It also reduces the time spent on examinations, facilitates the smooth completion of examinations, and improves the efficiency of examinations. This nursing method is one that merits more widespread promotion and clinical application.

Identifiers

PMID37082249
PMCPMC10113048
OpenAlexW4365142392

What OpenQuestion holds

Textmetadata
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.