Evaluating the baseline auscultation abilities of second-year chiropractic students using simulated patients and high-fidelity manikin simulators: A pilot study

Author:

da Silva-Oolup Sophia A.,Giuliano Dominic,Stainsby Brynne,Thomas Joshua,Starmer David

Abstract

ABSTRACT Objective To assess the ability of 2nd-year students to identify normal and abnormal findings during cardiac and lung auscultation using high-fidelity manikin simulators and standardized patients. A secondary objective was to assess students' perceived competence and confidence in their abilities. Methods This was a descriptive pilot study of randomly selected 2nd-year students at 1 chiropractic training program. Participants were asked to perform cardiac and lung auscultation on high-fidelity manikins (2 stations) and standardized human patients (2 stations) with normal and abnormal auscultation sounds. Participants described the auscultated sound as “abnormal” or “normal” and were also asked to score their confidence in describing the sound and competence in performing auscultation on a 100-mm visual analog scale. Descriptive statistics were calculated for all study variables. Results Thirty-two students (23 women and 9 men) were included. For lung auscultation, 15.6% were incorrect on the human subject and 6.2% were incorrect on the manikin. For cardiac auscultation, 62.5% were incorrect on the human subject and 40.6% were incorrect on the manikin. Confidence mean scores ranged from 34.8 to 60. Competence mean scores ranged from 34.8 to 50. Conclusion Results identified that 2nd-year students from 1 institution were correct in identifying an abnormal sound during lung auscultation but reported low levels of perceived competence or confidence in their responses. They performed poorly on cardiac auscultation and reported low perceived confidence and competence in their abilities to perform cardiac auscultation and identify sounds.

Publisher

Brighthall

Subject

Chiropractics

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1. ARSteth: Enabling Home Self-Screening with AR-Assisted Intelligent Stethoscopes;The 22nd International Conference on Information Processing in Sensor Networks;2023-05-09

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