Evidence map›Paper›PMID 41902012›Full record

ArticleSensors (Basel, Switzerland)2026

Development of a Virtual Reality Program for Internationally Standardized Non-Face-to-Face Nursing Practicum Education: Design and Validation of a Sensor-Integrated XR System.

Ji Won Oak

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. 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
–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

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

1 author.

Ji Won OakDepartment of Nursing, Tongmyong University, 428, Sinseon-ro, Nam-gu, Busan 48520, Republic of Korea.

Funding

Tongmyong University Research Grant
6 · The paper itself

Abstract

Extended reality (XR) has increasingly been applied to nursing practicum education; however, most systems rely on controller-based interfaces that limit precise capture of continuous fine motor performance and objective assessment. This study developed and validated a sensor-integrated, controller-free XR nursing practicum system (Smart Nursing v1.0) grounded in continuous precision sensing. Based on internationally standardized intravenous injection protocols, the system integrated optical hand tracking and speech recognition to quantify hand kinematics, spatial accuracy, procedural sequencing, and verbal compliance. A three-phase validation framework was implemented. Internal technical verification confirmed stable real-time performance (≥60 FPS) and consistent action recognition. In a user-based study involving 63 undergraduate nursing students, XR-based automated scores demonstrated high agreement with expert instructor ratings (ICC = 0.932, 95% CI = 0.91-0.96,

Indexed as

Education, NursingVirtual RealityHumansUser-Computer Interfaceautomated performance assessmentextended reality (XR)motion sensingperformance measurement in XRsensor-integrated simulation

Identifiers

PMID41902012
PMCPMC13030812

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.