Evidence map›Paper›PMID 42095231›Full record

ArticleInternational journal of nursing studies advances2026

Mapping the complexity of psychomotor skills in core nursing procedures: A content analysis for simulation-based education.

Hyunsoo Kim, Ahyoung Koh, Sangmin Lee, Suhyun Jin, Myeong Hoon Hyun, Hyunsook Shin

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Article in International journal of nursing studies advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hyunsoo KimCollege of Nursing Science, Kyung Hee University, 26, Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.
Ahyoung KohCollege of Nursing Science, Kyung Hee University, 26, Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.
Sangmin LeeCollege of Nursing Science, Kyung Hee University, 26, Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.
Suhyun JinCollege of Nursing Science, Kyung Hee University, 26, Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.
Myeong Hoon HyunCollege of Nursing Science, Kyung Hee University, 26, Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.
Hyunsook ShinCollege of Nursing Science, Kyung Hee University, 26, Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With increasing demand for immersive training in nursing education, identifying psychomotor skills suited for virtual reality is essential. Clarifying how physical actions interact with cognitive processes is critical for advancing simulation-based education. Purpose: To establish a structured and theoretically grounded framework for understanding psychomotor competence in core nursing procedures, this study was conducted to clarify how physical forces, motion characteristics, and embedded cognitive behaviors interact, thereby informing the design and evaluation of effective virtual reality-based educational strategies. Methods: We used a qualitative content analysis, with quantitative data integrated to support analytic rigor and transparency. Qualitative content analysis was employed to explore and interpret patterns of psychomotor skill behaviors embedded within the simulation, with quantitative frequency counts used to descriptively summarize the distribution and relative prominence of identified codes. Six core nursing procedures commonly performed in South Korea were analyzed. Motion units were systematically extracted from documentary sources, skill elements were identified and categorized from video data based on their motion characteristics, and these characteristics were subsequently linked to associated cognitive behaviors. The analytic process comprised three sequential steps: (1) extraction of motion units from documents, (2) identification and categorization of corresponding skill elements in video recordings according to motion characteristics, and (3) thematic linking of motion characteristics to cognitive behaviors. Results: Thirteen psychomotor skills were identified and categorized with action verbs. Document analysis showed Conclusion: We established a structured classification of psychomotor skills essential to nursing practice. We demonstrated that psychomotor actions were consistently accompanied by cognitive processes, such as noticing, interpretation, and clinical judgment. Virtual reality-based simulation programs should consider, therefore, integrating cognitive and decision-making elements with technical performance. These insights may provide a foundation for immersive training design and psychomotor skill assessment in nursing education.

Indexed as

Clinical practiceCognitive processesPsychomotor performanceSimulation trainingVirtual reality

Identifiers

PMID42095231
PMCPMC13141542

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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.