Evidence map›Paper›PMID 36360350›Full record

ArticleChildren (Basel, Switzerland)2022

Development and Application of AR-Based Assessment System for Infant Airway Obstruction First Aid Training.

Pao-Ju Chen, Wei-Kai Liou

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Children (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06843694 (Effect of Video Game Training on Student Nurses' Intervention in Adult Airway Obstruction), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 17% 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.

NCT06843694 nacompletednot on this mapstarted 2024, after this paper: background citation

Effect of Video Game Training on Student Nurses' Intervention in Adult Airway Obstruction: a Mixed Methods Study

TypeinterventionalSponsorKahramanmaras Sutcu Imam UniversityRan2024 to 2025Enrolled60ConditionsAirway ObstructionArmsvideo game
3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  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

2 authors at 2 institutions in 1 country.

Pao-Ju ChenDepartment of Nursing, College of Healthcare and Management, Asia Eastern University of Science and Technology, New Taipei City 220303, Taiwan.ORCID 0000-0001-6208-0630
Wei-Kai LiouCollege of Management and Design, Ming-Chi University of Technology, New Taipei City 243303, Taiwan.
Asia University · TWMing Chi University of Technology · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Airway obstruction refers to suffocation caused by blockage of the airway due to a foreign body and is a common cause of accidental death in infants below one year of age. However, the current infant CPR manikins used for training in first aid for foreign body airway obstruction can only be applied to one single scenario. Furthermore, trainees' first aid skills cannot be recorded and quantified with a digital system and, consequently, assessment of their skills is difficult to conduct. This study aims to overcome the technical limitations by developing an AR-based assessment system for training in first aid for infant airway obstruction. With this assessment system, trainees can learn first aid more efficiently and correctly and conduct a quantitative assessment of their skills digitally. For instructors, the time required for assessment, potential human error, and the cost of training can also be reduced. The system can be a practical learning tool that helps trainees assess emergencies and integrate their knowledge and skills.

Indexed as

assessment systemaugmented realityfirst aid trainingforeign body airway obstruction

Identifiers

PMID36360350
PMCPMC9688683
OpenAlexW4307552302

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.