Abstract
BACKGROUND: Children and adolescents with reproductive health issues may require immediate or emergency care, however in many countries availability of the pediatric and adolescent gynecology (PAG) service is low. That being said, teaching PAG examination to OBGYN, pediatrics and emergency medicine residents seems reasonable, and cannot be underestimated. In order to provide residents with opportunity to learn PAG examination, a high-fidelity hybrid simulation workshop was implemented in our institution. METHODS: The study aimed to investigate learners' attitudes towards the high-fidelity simulation (HFS) hybrid model as compared with task trainer-SP (simulated patient)-voice model in the HFS environment and the factors connected to learners' attitudes towards the hybrid model that could influence learning in high-fidelity simulation (HFS). The concept of attitude was used as the theoretical framework and the mixed method approach to study design was utilized with simultaneous collection of quantitative (original questionnaires) and qualitative data (semi-structured interviews). RESULTS: Residents valued the HFS hybrid model higher over task trainer-SP-voice model in regards to all three attitude components: cognitive (95%), affective (87.5%) and behavioral (83.7%). Analysis of qualitative data revealed six themes important to learners and informing learning of PAG examination in HFS. Further analysis of the themes allowed to develop a conceptual model, in which six factors connected to attitude components influenced learning. These factors were: task difficulty, attention, emotional realism of the simulation, patient's emotions, physical realism of the simulation, and technical issues. CONCLUSIONS: Participants of our study appreciated learning experience with the HFS hybrid model more, based on attitude questionnaire. Moreover, findings revealed that multiple, various factors connected to attitude may influence learning of PAG examination in HFS with hybrid model, and we propose a conceptual model illustrating relationships between those factors.