Psychological Safety in High-Fidelity Simulation Scale – Japanese Version

Abstract

The Psychological Safety in High-Fidelity Simulation Scale – Japanese Version (PS-HFS-J) is an empirically validated psychometric instrument designed to evaluate the degree of psychological safety experienced by undergraduate nursing students engaged in immersive, simulation-based healthcare education. Adapted from the original Korean instrument developed by Park (2021), this Japanese version addresses critical pedagogical and sociocultural dynamics that influence student engagement, clinical vulnerability, and cognitive processing during high-acuity scenario learning. In high-fidelity simulation, learners are routinely confronted with unexpected clinical crises, real-time diagnostic challenges, and immediate observation by peers and faculty; without a supportive learning climate, this exposure can precipitate debilitating evaluation apprehension, defensive silence, and cognitive overload. The PS-HFS-J operationalizes psychological safety across 14 items organized into four distinct latent factors: Dealing with Uncertainty, Being Exposed, Being Unsupported, and Interpersonal Risk. Methodologically grounded in the COSMIN (Consensus-based Standards for the selection of health Measurement INstruments) taxonomy, the cross-cultural adaptation rigorously established content validity, structural validity, and temporal stability. In psychometric evaluations comprising 263 Japanese undergraduate nursing students across all four collegiate years, the scale exhibited exemplary internal consistency (overall Cronbach’s α = 0.906) and temporal stability via test-retest intraclass correlation coefficients ranging from 0.859 to 0.914 across dimensions. Confirmatory factor analysis (CFA) affirmed the theoretical four-factor architecture, yielding superior model fit indices (χ² p = 0.142; CFI = 0.990; TLI = 0.988; RMSEA = 0.026 [90% CI: 0.000–0.060]). By providing an objective, culturally sensitive metric, the PS-HFS-J serves as an essential tool for simulation educators, clinical preceptors, and educational researchers to quantify the socio-emotional learning climate, refine prebriefing and debriefing protocols, and optimize experiential clinical learning environments.

Keywords

Psychological safety, High-fidelity simulation, Nursing education, Psychometrics, Cross-cultural adaptation, Japanese nursing students, Experiential learning, Confirmatory factor analysis, Clinical simulation, Debriefing, Educational environment, COSMIN methodology

Authors

The translation, cross-cultural adaptation, and psychometric validation of the Psychological Safety in High-Fidelity Simulation Scale – Japanese Version were conducted by a collaborative research team across leading academic nursing institutions in Japan:

• Keisuke Nojima, MSN, RN (Corresponding Author)
  Affiliation: Faculty of Nursing, Kyoto Tachibana University, Kyoto, Japan
  Email: [email protected]
• Makoto Tsukuda, PhD, RN
  Affiliation: Department of Nursing, Hyogo Medical University, Nishinomiya, Japan
  Email: [email protected]
• Kosuke Kawamura, PhD, RN
  Affiliation: Faculty of Nursing, Kyoto Tachibana University, Kyoto, Japan
  Email: [email protected]
• Junko Honda, PhD, RN, PHN
  Affiliation: Research Institute of Nursing Care for People and Community, University of Hyogo, Akashi, Japan
  Email: [email protected]
• Mie Murozumi, PhD, RN
  Affiliation: Faculty of Nursing, Kyoto Tachibana University, Kyoto, Japan
  Email: [email protected]

Purpose

High-fidelity simulation (HFS) has emerged as an indispensable pedagogical paradigm in contemporary nursing education and healthcare training worldwide. By integrating advanced computerized manikins, simulated clinical environments, and realistic physiological feedback, HFS replicates high-stakes clinical crises without compromising patient safety. However, the pedagogical efficacy of immersive simulation hinges entirely upon the experiential state of the learner. While high-fidelity simulations provide fertile ground for the cultivation of clinical judgment, technical proficiency, and diagnostic problem-solving, they simultaneously impose acute psychological vulnerability upon learners. During simulated scenarios, students are compelled to perform unfamiliar clinical procedures, make critical real-time decisions, and articulate their internal diagnostic reasoning while under active observation by faculty instructors and academic peers. In the absence of a robust climate of psychological safety, this exposure triggers intense evaluation anxiety, emotional paralysis, and defensive posturing, ultimately neutralizing the reflective learning processes that simulation aims to cultivate.

In East Asian pedagogical contexts, and particularly within Japanese higher education, these inherent challenges are compounded by pervasive sociocultural norms. Traditional Japanese educational milieus frequently emphasize hierarchical authority structures, strong deference to faculty, collective conformity, and an acute aversion to making public mistakes or disrupting interpersonal harmony (often conceptualized through cultural phenomena such as enryo-sigh or public self-effacement). In such environments, the risk of negative peer evaluation, public embarrassment, or perceived incompetence can lead students to adopt passive, risk-avoidant behaviors, such as deliberate silence or minimal participation during simulation scenarios and subsequent debriefing sessions. Prior to the validation of the PS-HFS-J, nurse educators in Japan lacked a standardized, culturally calibrated measurement scale capable of quantifying this psychological phenomenon within simulation-based learning environments.

The primary purpose of the PS-HFS-J is to establish a rigorous, psychometrically sound diagnostic instrument to measure the subjective psychological safety of Japanese nursing students during high-fidelity simulation learning. From an educational and instructional standpoint, the scale allows academic faculty to systematically assess how various curricular interventions, prebriefing strategies, instructor communication styles, and structured debriefing models impact student vulnerability. By identifying specific deficits across distinct sub-dimensions—such as excessive anxiety regarding uncertainty or acute perceptions of interpersonal exposure—educators can proactively adjust instructional scaffolds, normalize clinical error as an essential medium of learning, and cultivate an emotionally secure simulation milieu. From a scientific perspective, the tool enables cross-cultural research into the psychological underpinnings of experiential learning, clinical decision-making, and stress inoculation across diverse international nursing cohorts.

Psychological Construct

The theoretical construct measured by the PS-HFS-J is psychological safety in clinical simulation, operationalized as a multidimensional cognitive and emotional state wherein learners perceive their educational environment to be secure enough to embrace vulnerability, express genuine confusion, execute independent clinical decisions, and commit errors without fearing negative social, academic, or professional repercussions. Building on the foundational conceptualization established in simulation nursing research by Park (2021), the construct comprises four interrelated yet distinct sub-dimensions:

1. Dealing with Uncertainty

This dimension evaluates the learner’s emotional equilibrium, cognitive resilience, and psychological comfort when navigating ambiguous, evolving, or unpredictable patient care trajectories. Clinical simulation scenarios frequently incorporate incomplete diagnostic data, deteriorating physiological parameters, and ambiguous clinical signs to mirror authentic clinical practice. Students with high psychological safety in this domain perceive ambiguity not as a punitive trap designed to expose their ignorance, but as a normative clinical challenge. Conversely, students exhibiting low safety in this dimension experience cognitive freezing, severe distress when standardized protocols fail to provide immediate solutions, and an inability to adapt clinical interventions in real time.

2. Being Exposed

The Being Exposed dimension operationalizes the profound emotional vulnerability and self-consciousness triggered by public performance and observation. In high-fidelity simulation, students operate behind one-way mirrors, under video recording apparatuses, or in direct view of faculty observers and peer cohorts. This dimension measures the extent to which a student feels acutely self-conscious, judged, or stripped of protective psychological boundaries during simulated clinical execution. High scores in this domain reflect an unmanageable fear of having personal knowledge deficits, motor clumsiness, or clinical hesitancy laid bare before others.

3. Being Unsupported

This sub-dimension captures the student’s subjective perception of institutional, pedagogical, and relational abandonment. Specifically, it assesses whether learners perceive a lack of instructional scaffolding, psychological backing, or empathetic guidance from simulation facilitators and peer team members. In an optimal simulation climate, psychological safety is fostered through clear prebriefing, explicit “fiction contracts,” and the establishment of psychological containment. When students score high on the Being Unsupported dimension, they experience the simulation as an unguided trial by fire, perceiving educators as critical inquisitors rather than supportive mentors committed to their professional growth.

4. Interpersonal Risk

Grounded in the classic social psychology literature, Interpersonal Risk assesses the subjective fear of negative social consequences resulting from active engagement, questioning, or clinical failure. In simulation, interpersonal risks include being mocked by peers, damaging one’s academic standing, earning the disapproval of respected clinical faculty, or being branded as incompetent by classmates. In educational settings characterized by elevated interpersonal risk, students prioritize self-preservation and image management over active inquiry, choosing passive compliance over authentic, exploratory clinical action.

Theoretical Framework

The conceptual foundation of the PS-HFS-J synthesizes classical theories from organizational psychology, adult learning, and socio-cognitive development, translating them into the specialized arena of medical and nursing education.

Edmondson’s Team Psychological Safety Paradigm

The bedrock of the construct originates in the seminal work of Amy Edmondson (1999), who conceptualized psychological safety as a shared belief held by members of a team that the team is safe for interpersonal risk-taking. Edmondson demonstrated that within complex, high-reliability organizations—such as acute healthcare environments—effective error detection, organizational learning, and process innovation occur only when team members are confident that speaking up, questioning prevailing assumptions, or reporting near-misses will not lead to humiliation, rejection, or professional retribution. The PS-HFS-J translates Edmondson’s organizational-level construct into an individual-level perceptual state within the context of experiential nursing education, recognizing that a student simulation team functions as a temporary micro-team governed by identical psychological forces.

Kolb’s Experiential Learning Theory

The scale is deeply anchored in David Kolb’s Experiential Learning Theory, which posits that learning is a continuous, four-stage cyclical process involving Concrete Experience (CE), Reflective Observation (RO), Abstract Conceptualization (AC), and Active Experimentation (AE). In high-fidelity simulation, the scenario constitutes the concrete experience, while debriefing represents the vital phase of reflective observation. However, as educational theorists have established, progression from concrete experience to deep reflective observation requires high emotional regulation. If learners experience acute threat during the scenario, their reflective cognitive capacity is hijacked by amygdala-driven defensive mechanisms. Psychological safety provides the essential emotional holding environment that allows learners to dismantle cognitive defenses, examine their own clinical errors objectively during debriefing, and successfully formulate new conceptual schemas for future clinical practice.

Bandura’s Social Cognitive Theory and Evaluative Threat

The framework also integrates elements of Albert Bandura’s Social Cognitive Theory, particularly the interplay between self-efficacy beliefs, physiological emotional arousal, and vicarious learning. Bandura established that heightened emotional distress and anxiety directly undermine perceived self-efficacy. When clinical simulation evokes excessive evaluative threat, learners experience decrements in working memory capacity, clinical reasoning, and psychomotor fluency. The PS-HFS-J explicitly quantifies the psychological barriers that impede self-efficacy development, enabling educators to design instructional environments that mitigate socio-evaluative stress.

Validity

The validation of the Psychological Safety in High-Fidelity Simulation Scale – Japanese Version adhered stringently to the international methodological criteria outlined by the COSMIN guidelines, ensuring thorough assessment across multiple validity domains.

Content Validity and Cross-Cultural Equivalence

Content validity was established through a multi-stage translation and cross-cultural adaptation protocol involving forward translation, synthesis, backward translation, and comprehensive expert committee evaluation. The expert panel comprised nursing faculty with doctoral preparation, certified simulation educators, and psychometricians. Panelists evaluated each translated item for linguistic clarity, conceptual relevance, and cultural congruence with Japanese higher education practices. The quantitative assessment of content validity yielded exceptional results:

• Item-Level Content Validity Index (I-CVI): Ranged from 0.80 to 1.00 across all 14 individual items, indicating that every item was judged as highly relevant and clear by the expert panel.
• Scale-Level Content Validity Index / Average (S-CVI/Ave): Achieved a score of 0.94, substantially surpassing the established methodological benchmark of 0.80 for high content validity.

Following expert review, cognitive pre-testing was conducted with undergraduate nursing students to confirm semantic comprehensibility, face validity, and the absence of linguistic ambiguity within the target demographic.

Construct and Structural Validity

Construct validity was formally tested using a cross-sectional sample of 263 undergraduate nursing students enrolled in an accredited university nursing program in Japan. The sample spanned all four years of undergraduate training (First-year: n = 44, 16.7%; Second-year: n = 62, 23.6%; Third-year: n = 88, 33.5%; Fourth-year: n = 69, 26.2%), capturing varying degrees of clinical and simulation experience. Confirmatory factor analysis (CFA) demonstrated that the empirical data fit the theoretical four-factor model exceptionally well, confirming that the construct dimensions identified in the original Korean instrument were fully preserved within the Japanese educational context.

Reliability

The reliability of the PS-HFS-J was evaluated across two core psychometric dimensions: internal consistency reliability and temporal stability (test-retest reliability).

Internal Consistency

The internal consistency of the 14-item PS-HFS-J was evaluated using Cronbach’s alpha (α) coefficient. For the full 14-item scale, the overall Cronbach’s α was 0.906, demonstrating outstanding internal consistency that well exceeds the universally accepted psychometric standard of 0.70 for research instruments and 0.80 for evaluative educational tools. This high alpha value confirms that the scale items correlate coherently while avoiding excessive redundancy.

Test-Retest Reliability and Temporal Stability

Temporal stability was assessed using a longitudinal subsample of 52 undergraduate nursing students who completed the PS-HFS-J at two distinct time points under stable educational conditions. Stability was quantified using the Intraclass Correlation Coefficient (ICC) employing a two-way mixed-effects model with absolute agreement. The subscale-level ICC values ranged from 0.859 to 0.914:

• Dealing with Uncertainty: High temporal reproducibility (ICC ≥ 0.85).
• Being Exposed: Excellent temporal stability across repeated testing (ICC > 0.88).
• Being Unsupported: Robust longitudinal consistency (ICC > 0.86).
• Interpersonal Risk: Superior test-retest reliability exceeding 0.90.

In psychometric measurement theory, ICC values exceeding 0.85 denote excellent temporal stability, verifying that the PS-HFS-J is resistant to random transient error and suitable for longitudinal research, pre-intervention/post-intervention curricular evaluations, and semester-long educational tracking.

Factor Analysis

The dimensional architecture of the PS-HFS-J was empirically tested via Confirmatory Factor Analysis (CFA) applying maximum likelihood estimation. Rather than relying on exploratory approaches, CFA was specified to evaluate the strict theoretical four-factor framework established during the original instrument’s inception.

Model Fit Parameters

The hypothesized four-factor model exhibited superior goodness-of-fit indices, satisfying the most rigorous contemporary psychometric cutoffs (such as those established by Hu and Bentler):

• Chi-Square (χ²) Test of Model Fit: Produced a non-significant result (p = 0.142). In structural equation modeling, a non-significant chi-square indicates that the observed sample covariance matrix does not differ significantly from the model-implied covariance matrix, providing strong global confirmation of structural fit.
• Comparative Fit Index (CFI): Reached 0.990, substantially outperforming the conservative ≥ 0.95 benchmark for superior model fit.
• Tucker-Lewis Index (TLI): Reached 0.988, confirming that the model retains parsimonious fit when penalizing for model complexity.
• Root Mean Square Error of Approximation (RMSEA): Was estimated at 0.026, well below the stringent ≤ 0.05 threshold for close fit, with a tight 90% confidence interval ranging from 0.000 to 0.060.

Structural Factor Structure

All 14 items demonstrated statistically significant, high standardized factor loadings onto their designated latent constructs without evidence of cross-loading or problematic residual covariance. The four confirmed latent factors cleanly mapped onto:

1. Factor 1: Dealing with Uncertainty — Reflecting cognitive-emotional security when encountering unexpected, non-linear clinical events.
2. Factor 2: Being Exposed — Reflecting the threat of public observation, evaluation apprehension, and clinical visibility.
3. Factor 3: Being Unsupported — Reflecting perceived deficits in facilitator containment, safety framing, and peer solidarity.
4. Factor 4: Interpersonal Risk — Reflecting the perceived danger of reputational damage, social humiliation, or academic penalty.

Instrument / Measurement Tool

• Instrument Name: Psychological Safety in High-Fidelity Simulation Scale – Japanese Version (PS-HFS-J)
• Test Type: Standardized self-report psychometric questionnaire / Educational rating scale
• Target Population: Undergraduate and graduate nursing students, practicing registered nurses undergoing simulation training, and allied healthcare professionals in Japan
• Administration Format: Self-administered paper-and-pencil instrument or online electronic survey platform
• Item Count: 14 items
• Factor Structure: Multidimensional (4 latent dimensions)
  • Dimension 1: Dealing with Uncertainty
  • Dimension 2: Being Exposed
  • Dimension 3: Being Unsupported
  • Dimension 4: Interpersonal Risk
• Response Scale: 14 items (standard multi-point rating format reflecting degree of agreement or subjective frequency as validated by original developers)
• Administration Time: Approximately 3 to 5 minutes to complete
• Scoring Procedures: Subscale scores are calculated by summing or averaging the items corresponding to each of the four designated dimensions. An aggregate overall psychological safety score can be derived, with negatively worded threat items appropriately reverse-coded so that higher composite values reflect higher levels of psychological safety in the simulation environment.
• Intended Context of Use: Administered immediately following high-fidelity clinical simulations and debriefing sessions to assess the emotional and instructional climate of simulation-based educational interventions.

Permissions & Fee and Test Year

• Test Year of Japanese Validation: 2025
• Original Scale Publication: 2021 (Park, Nurse Education Today)
• Permissions: Formal permission for the cross-cultural translation, linguistic adaptation, and psychometric validation of the scale into the Japanese language was officially granted by the original scale developer (Dr. Park).
• Copyright & Usage Fee: Academic and non-commercial educational use of the PS-HFS-J is permitted for research and quality improvement purposes upon obtaining formal authorization from the corresponding author. The instrument is proprietary and is not distributed in an unmonitored open repository. Commercial entities, healthcare institutions, or external testing organizations seeking to integrate the PS-HFS-J into proprietary curricula or learning management platforms must contact the primary author ([email protected]) to negotiate explicit licensing terms.

References

• Abe, Y., Kawahara, C., Yamashina, A., & Tsuboi, R. (2013). Repeated scenario simulation to improve competency in critical care: A new approach for nursing education. American Journal of Critical Care, 22(1), 33–40. https://doi.org/10.4037/ajcc2013229
• Banks, F. (2016). Behind Japanese students’ silence in English classrooms. Accents Asia, 8(2), 54–65.
• Cho, M. K., & Kim, M. Y. (2023). Factors associated with student satisfaction and self-confidence in simulation learning among nursing students in Korea. Healthcare, 11(8), 1060. https://doi.org/10.3390/healthcare11081060
• Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383. https://doi.org/10.2307/2666999
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning.
• Ito, A., Kurita, K., & Yagami, S. (2022). A concept analysis of psychological safety: Further understanding for application to health care. Nursing Open, 9(1), 467–483. https://doi.org/10.1002/nop2.1086
• Kim, J., Park, J. H., & Shin, S. (2016). Effectiveness of simulation-based nursing education depending on fidelity: A meta-analysis. BMC Medical Education, 16, 152. https://doi.org/10.1186/s12909-016-0672-7
• Koo, T. K., & Li, M. Y. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163. https://doi.org/10.1016/j.jcm.2016.02.012
• Lackie, K., Hayward, K., & Bainbridge, L. (2022). Creating psychological safety in interprofessional simulation for health professional learners: A scoping review of the barriers and enablers. Journal of Interprofessional Care, 36(2), 187–196. https://doi.org/10.1080/13561820.2021.1884587
• Lei, X. Y., Huang, C. H., & Zhang, Y. (2022). Effects of high-fidelity simulation teaching on nursing students’ knowledge, professional skills and clinical ability: A meta-analysis and systematic review. Nurse Education in Practice, 60, 103306. https://doi.org/10.1016/j.nepr.2022.103306
• Li, Y. P., Chen, F. Y., & Wang, S. (2022). High-fidelity simulation in undergraduate nursing education: A meta-analysis. Nurse Education Today, 111, 105291. https://doi.org/10.1016/j.nedt.2022.105291
• McKenna, L., Boyle, M., & Williams, B. (2019). The influence of anxiety on student nurse performance in a simulated clinical setting: A mixed methods design. International Journal of Nursing Studies, 98, 57–63. https://doi.org/10.1016/j.ijnurstu.2019.06.006
• Mokkink, L. B., Terwee, C. B., Patrick, D. L., Alonso, J., Stratford, P. W., Knol, D. L., Bouter, L. M., & de Vet, H. C. W. (2010). The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: An international Delphi study. Quality of Life Research, 19(4), 539–549. https://doi.org/10.1007/s11136-010-9606-8
• Nojima, K., Tsukuda, M., Kawamura, K., Honda, J., & Murozumi, M. (2025). Psychological Safety in High-Fidelity Simulation Scale – Japanese Version. Nursing Reports, 15(7), 257. https://doi.org/10.3390/nursrep15070257
• Nojima, K., Murozumi, M., & Kawamura, K. (2024). Changes in the professional identity and self-efficacy of nursing students engaged in the Objective Structured Clinical Examination using simulation learning. Cureus, 16(8), e68568. https://doi.org/10.7759/cureus.68568
• Park, S. Y. (2021). Nursing students’ Psychological Safety in High fidelity Simulations: Development of a new scale for psychometric evaluation. Nurse Education Today, 105, 105017. https://doi.org/10.1016/j.nedt.2021.105017
• Park, S. Y., & Kim, J. H. (2021). Nursing students’ experiences of psychological safety in simulation education: A qualitative study. Nurse Education in Practice, 55, 103163. https://doi.org/10.1016/j.nepr.2021.103163
• Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research, 99(6), 323–338. https://doi.org/10.3200/JOER.99.6.323-338
• Shearer, J. E. (2016). Anxiety, nursing students, and simulation: State of the science. Journal of Nursing Education, 55(10), 551–554. https://doi.org/10.3928/01484834-20160914-02
• Silva, G. O., Oliveira, A. C., & Santos, P. R. (2022). Effect of simulation on stress, anxiety, and self-confidence in nursing students: Systematic review with meta-analysis and meta-regression. International Journal of Nursing Studies, 133, 104282. https://doi.org/10.1016/j.ijnurstu.2022.104282
• Somerville, S., & Feather, R. (2023). Twelve tips for the pre-brief to promote psychological safety in simulation-based education. Medical Teacher, 45(12), 1349–1354. https://doi.org/10.1080/0142159X.2023.2214305
• Song, Y., & Kim, M. (2020). Effects of integrative simulation practice on nursing knowledge, critical thinking, problem-solving ability, and immersion in problem-based learning among nursing students. Korean Journal of Women Health Nursing, 26(1), 61–71. https://doi.org/10.4069/kjwhn.2020.03.15.1
• Tamaki, T., Saneyoshi, A., & Harada, K. (2019). The effectiveness of end-of-life care simulation in undergraduate nursing education: A randomized controlled trial. Nurse Education Today, 76, 1–7. https://doi.org/10.1016/j.nedt.2019.01.005
• Tsuneyoshi, R. (2001). The Japanese Model of Schooling: Comparisons with the United States. Routledge.
• Turner, S., & Harder, N. (2023). Psychological safety in simulation: Perspectives of nursing students and faculty. Nurse Education Today, 122, 105712. https://doi.org/10.1016/j.nedt.2023.105712
• Vangone, P., Cuzzupoli, R., & Piro, A. (2024). The efficacy of high-fidelity simulation on knowledge and performance in undergraduate nursing students: An umbrella review of systematic reviews and meta-analysis. Nurse Education Today, 139, 106231. https://doi.org/10.1016/j.nedt.2024.106231
• Walsh, K., & Broadbent, M. (2022). The use of guided reflection in simulation-based education with prelicensure nursing students: An integrative review. Journal of Nursing Education, 61(2), 73–80. https://doi.org/10.3928/01484834-20211213-01

Items of the Scale