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Simulation for non-pedagogical purposes has begun to emerge. Examples include quality improvement initiatives, testing and evaluating of new interventions, the co-designing of new models of care, the exploration of human and organizational behaviour, comparing of different sectors and the identification of latent safety threats. However, the literature related to these types of simulation is scattered across different disciplines and has many different associated terms, thus making it difficult to advance the field in both recognition and understanding. This paper, therefore, aims to enhance and formalize this growing field by generating a clear set of terms and definitions through a concept taxonomy of the literature. Due to the lack of alignment in terminology, a combination of pearl growing, snowballing and citation searching approach was taken. The search was conducted between November 2020 and March 2023. Data were extracted and coded from the included papers according to seven Simulation-Based I’s (SBIs; Innovation, Improvement, Intervention, Involvement, Identification, Inclusion and Influence). Eighty-three papers were identified from around the world, published from 2008 to 2023. Just over half were published in healthcare simulation journals. There were 68 different terms used to describe this form of simulation. Papers were categorized according to a primary and secondary Simulation-Based ‘I’. The most common primary SBI was Simulation-Based Identification. Selected categorized papers formed a descriptive narrative for each SBI. This review and taxonomy has revealed the breadth of an emerging and distinct field within healthcare simulation. It has identified the rate at which this field is growing, and how widespread it is geographically. It has highlighted confusion in terminology used to describe it, as well as a lack of consistency in how it is presented throughout the literature. This taxonomy has created a grounding and step change for this work which is embedded in the literature, providing a rich and varied resource of how it is being utilized globally.
Simulation for non-pedagogical purposes has begun to emerge. Examples include quality improvement initiatives, testing and evaluating of new interventions, the co-designing of new models of care, the exploration of human and organizational behaviour, comparing of different sectors and the identification of latent safety threats. However, the literature related to these types of simulation is scattered across different disciplines and has many different associated terms, thus making it difficult to advance the field in both recognition and understanding. This paper, therefore, aims to enhance and formalize this growing field by generating a clear set of terms and definitions through a concept taxonomy of the literature. Due to the lack of alignment in terminology, a combination of pearl growing, snowballing and citation searching approach was taken. The search was conducted between November 2020 and March 2023. Data were extracted and coded from the included papers according to seven Simulation-Based I’s (SBIs; Innovation, Improvement, Intervention, Involvement, Identification, Inclusion and Influence). Eighty-three papers were identified from around the world, published from 2008 to 2023. Just over half were published in healthcare simulation journals. There were 68 different terms used to describe this form of simulation. Papers were categorized according to a primary and secondary Simulation-Based ‘I’. The most common primary SBI was Simulation-Based Identification. Selected categorized papers formed a descriptive narrative for each SBI. This review and taxonomy has revealed the breadth of an emerging and distinct field within healthcare simulation. It has identified the rate at which this field is growing, and how widespread it is geographically. It has highlighted confusion in terminology used to describe it, as well as a lack of consistency in how it is presented throughout the literature. This taxonomy has created a grounding and step change for this work which is embedded in the literature, providing a rich and varied resource of how it is being utilized globally.
Background The aging of the population highlights the need to establish empathetic connections with older adults. To achieve this, age simulation suits have been designed, allowing users to experience the physical limitations associated with aging. This study aimed to evaluate the experience of dental students with these devices, using psychometric tools to measure the impact on their understanding and empathy. Methods A pre/post-test study was conducted with the participation of 63 dental students from Rey Juan Carlos University who were fitted with an age simulation suit and asked to perform different tasks. Psychometric tools were used to assess specific parameters. Empathy was measured using the Jefferson Empathy Scale, emotional intelligence was assessed with the Trait Meta-Mood Scale-24 (TMMS-24), and the emotional attention dimension was analyzed using the Positive and Negative Affect Schedule (PANAS). Results The scores on the Jefferson Empathy Scale significantly improved from 88.44 ± 6.8 to 91.06 ± 10.11 after using the simulation suit (P < 0.026). Pearson’s product moment correlation analysis showed no significant positive association or correlation between age and scores from the three questionnaires. In the rest, a positive and significant correlation was observed (P < 0.0001). Conclusions Age simulation activities effectively enhance empathy among dental students. However, more studies are needed to foster positive attitudes toward aging and prevent negative stereotypes.
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