Simulation is an educational technique rather than a technology. It is an approach that replaces real experiences with a guided experience of a realistic replication of an actual event in a fully interactive manner that allows participants to be immersed in the learning environment for the purposes of learning, training and practice (Aebersold, 2018; Gaba, 2004; Jeffries, 2012). Realism is an important aspect of simulation as it represents things or situations in a way that is accurate or true to life (INACSL, 2021).

Simulation-based experiences (SBE) are designed with the two critical components of fidelity and modality to create realism in the simulation scenario. The level of fidelity represents the level of realism that the mannikin, environment and scenario offer (Carey & Rossler, 2020; Nehring & Lashley, 2009).

Level of Fidelity

Fidelity is related to the level of mannikin used which can be low, medium and high-fidelity and the type of realism; conceptual, physical and emotional/psychological (Carey & Rossler, 2020; Kim, Park, & Shin, 2016). The level of fidelity represents the level of realism of a simulator alongside what the simulation scenario offers (Carey & Rossler, 2020; Nehring & Lashley, 2009). The level of fidelity can be low, medium and high-fidelity. The type of fidelity or realism can be conceptual, physical, and/or emotional/psychological (Carey & Rossler, 2020; Kim, Park, & Shin, 2016). The types of fidelity in conjunction with the level of fidelity of the mannikin helps the participants to “…suspend their disbelief and accept the activity as if it is real” (Carey & Rossler, 2020, p. 2).

The Types of Fidelity

Conceptual Fidelity

Conceptual fidelity is the accuracy of the simulated scenario to the actual event in the clinical setting. The scenario must make sense and those appropriate choices such as medications, lab results, or vital signs are consistent with signs and symptoms the patient is exhibiting (Carey & Rossler, 2020).

Physical Fidelity

Physical or environmental fidelity addresses the degree to which the simulator and simulation environment can imitate the sensory experience (e.g., see, hear, feel and smell) relative to the clinical environment (Carey & Rossler, 2020).

Emotional Fidelity

Psychological or emotional fidelity is known as the mental side of training. This type of fidelity can be achieved when the simulation can successfully engage the student emotionally by mimicking the emotional response that would occur in the nursing clinical environment (Carey & Rossler, 2020).

Level of Immersion

The level of immersion refers to the environment in which simulation is conducted (Cant et al., 2019). A simulation lab can be set up to mimic a hospital room with a hospital bed, patient monitoring equipment, and much more offers an immersive experience. Non-immersive equipment such as a computer screen-based animated avatar provides a non-immersive experience because the nursing student may be at home or in a library where the environment does not reflect the clinical environment (Lee et al., 2020).

Level of Interaction

The modality is the type of simulation equipment whether it be task trainer or a low, medium, high-fidelity mannikin. Various modality types of simulators provide different levels of interaction between the nursing student and the simulator. The higher level of interaction the more engaged the student (Nehring & Lashley, 2009). If the simulation does not offer any level of interaction, this is characterized as passive simulation. The design of the simulation scenario not only depends on the proper identification of fidelity and realism to meet the learning objectives; the choice of simulation modality is just as important to have a successful simulation experience.

The concepts of fidelity and realism are part of the discourse in relation to mannikin-based simulation but are not as evolved when it comes to screen-based simulation or virtual reality. There needs to be much more work done on identifying and defining realism and fidelity to help guide the design and implementation of computer-based simulation (Cant et al., 2019; Gordon & McConigle, 2018).