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Record W4413055012 · doi:10.1186/s12912-025-03700-x

Patient safety in the ‘Room of Horrors’ simulation: a multi-method study of student, novice, and experienced nurses

2025· article· en· W4413055012 on OpenAlexaff
Seung Eun Lee, Hyun Joo Lee, V. Susan Dahinten, Won Jin Seo, Hanjoe Kim

Bibliographic record

VenueBMC Nursing · 2025
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of British Columbia
FundersMinistry of Science and ICT, South KoreaNational Research Foundation of KoreaNational Research Foundation
KeywordsDebriefingPatient safetyMedicineDescriptive statisticsNursingTest (biology)Qualitative propertyNursing researchHealth careMedical education

Abstract

fetched live from OpenAlex

BACKGROUND: Patient safety is a critical concern in healthcare, with unsafe care causing significant harm. Nurses play a vital role in promoting safety and must be equipped with the skills to identify and manage safety hazards. The Room of Horrors (ROH) simulation was developed to enhance these skills by presenting learners with a simulated patient scenario containing safety hazards. This study aimed to evaluate the effectiveness of the simulation by (1) comparing hazard recognition performance across different groups; (2) assessing changes in self-perceived patient safety competency and confidence; (3) exploring participants' simulation experiences; and (4) examining perceived benefits for clinical practice. METHODS: A multi-method design was employed, incorporating a quasi-experimental three-group pre-test, post-test, and two-week follow-up structure, and a qualitative analysis of participants' experiences and perceptions. The study involved participants from one nursing college and five hospitals in Korea. The sample (N = 90) comprised three groups: nursing students (n = 30), novice nurses (n = 30), and experienced nurses (n = 30). Participants underwent a 20-minute pre-briefing, 10-minute simulation, 10-minute self-reflection, and 40-minute debriefing session. Data were collected through structured surveys on patient safety competency, confidence, and open-ended questions about participants' experiences and perceptions. Two-week follow-up surveys evaluated perceived clinical relevance. Quantitative data were analyzed using descriptive statistics and regression analysis; qualitative data were analyzed through content analysis. RESULTS: Experienced nurses identified significantly more hazards, including those requiring two-step logical reasoning, than nursing students and novice nurses. Both novice and experienced nurses showed improvements in safety competency and confidence. Participant feedback was overwhelmingly positive, particularly highlighting the value of debriefing. The two-week follow-up indicated that almost all participants had applied the knowledge gained through the simulation in their clinical practice. CONCLUSIONS: The ROH simulation enhances self-reported patient safety competency and confidence, especially among experienced nurses, supporting its integration into nursing education and continuing professional development. Findings also suggest the importance of tailoring scenario complexity and debriefing strategies to learner readiness and highlight the potential value of integrating ROH simulations into experience-sensitive safety training programs. Further research is warranted to investigate its long-term impact on clinical practice. TRIAL REGISTRATION: Not applicable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.492
Teacher spread0.424 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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