Development and validation of Simulation Scenario Quality Instrument (SSQI).

BACKGROUND: Due to the unmet need for valid instruments that evaluate critical components of simulation scenarios, this research aimed to develop and validate an instrument that measures the quality of healthcare simulation scenarios. METHODS: A sequential transformative mixed-method research design was used to conduct the study. The development and validation of the instrument involved two phases: the qualitative phase, which included defining the instrument's theoretical background and instrument construction, followed by the quantitative phase, where the instrument was piloted and validated. The qualitative study included 17 healthcare simulation experts, where three focus group was conducted, and the first version of the instrument was constructed based on the focus group analysis and the theoretical framework constructed using the literature review. During the quantitative phase, the instrument's quantitative piloting included 125 healthcare simulation scenarios; then, the instrument went through construct validity and reliability testing. RESULTS: Content experts confirmed the theoretical model and instrument framework. The average item content validity index (I-CVI) scores and the average of the I-CVI scores (S-CVI/Ave) for all items on the scale or the average proportion relevance judged by all experts was 0.87. The conformity factor analysis results showed a good fit for the proposed 10-factor model (CFI (the comparative fit index) = 0.998, Tucker-Lewis index = 0.998, Root mean square error of approximation (RMSEA) = 0.061. The final instrument included ten domains: 1. Learning objectives, 2. Target group, 3. Culture, 4. Scenario case, 5. Scenario narrative briefing, 6. Scenario complexity, 7. Scenario flow, 8. Fidelity, 9. Debriefing, and 10. ASSESSMENT: The SSQI included 44 items that are rated on a 3-point scale (Meets Expectations = (2), Needs Improvement, (1), Inadequate (0)). CONCLUSION: This validated and reliable instrument will be helpful to healthcare educators and simulation experts who want to develop simulation-based training scenarios and ensure the quality of written scenarios.

Stability and numerical analysis via non-standard finite difference scheme of a nonlinear classical and fractional order model.

In this paper, we develop a new mathematical model for an in-depth understanding of COVID-19 (Omicron variant). The mathematical study of an omicron variant of the corona virus is discussed. In this new Omicron model, we used idea of dividing infected compartment further into more classes i.e asymptomatic, symptomatic and Omicron infected compartment. Model is asymptotically locally stable whenever R0<1 and when R0≤1 at disease free equilibrium the system is globally asymptotically stable. Local stability is investigated with Jacobian matrix and with Lyapunov function global stability is analyzed. Moreover basic reduction number is calculated through next generation matrix and numerical analysis will be used to verify the model with real data. We consider also the this model under fractional order derivative. We use Grunwald-Letnikov concept to establish a numerical scheme. We use nonstandard finite difference (NSFD) scheme to simulate the results. Graphical presentations are given corresponding to classical and fractional order derivative. According to our graphical results for the model with numerical parameters, the population's risk of infection can be reduced by adhering to the WHO's suggestions, which include keeping social distances, wearing facemasks, washing one's hands, avoiding crowds, etc.