ArticleMedEdPORTAL : the journal of teaching and learning resources2021
Respiratory Auscultation Lab Using a Cardiopulmonary Auscultation Simulation Manikin.
Article in MedEdPORTAL : the journal of teaching and learning resources, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Interstitial Lung Disease: Comparing Lecture and Large Group Case-Based Learning for Preclinical Medical Students.Cureus · 2024Article
- Assessment of performance and confidence level of simulation based clinical examination of respiratory system in undergraduate medical students of a medical college: a comparative cross-sectional study.Annals of medicine and surgery (2012) · 2024Article
- Article
- User Experience of Training Pediatric Students on Interactive Simulator During COVID-19 Pandemic.Advances in medical education and practice · 2022Article
- A comparative study of the effects of multimedia training materials on mini CEX scores of internal medicine residents in Isfahan University of Medical Sciences.Journal of education and health promotion · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Mastery of respiratory auscultation skills is fundamental for clinicians to develop. We created a case-based educational session utilizing a high-fidelity simulator to teach lung sound auscultation to medical students at our institution. We employed a hypothesis-driven approach and deliberate practice to enhance students' learning experience and retention of acquired skills. Methods: We developed the session to teach second-year medical students how to discriminate between normal and pathological respiratory sounds within the context of clinical vignettes. Faculty facilitators, in conjunction with near-peer educators, made use of a high-fidelity auscultation manikin to guide students through case-based problem sets. Students were given the opportunity to auscultate the manikin while being observed and receiving feedback from the faculty. Results: We introduced the manikin in 2016, with a total of 759 second-year medical students from four class years having participated in the session since then. Students evaluated the session through an end-of-the-week and end-of-unit survey. The survey showed an overall improvement in learner satisfaction over previous years. Survey results and feedback were used to make adjustments to the session. Discussion: Our respiratory auscultation session was well received overall. Proper faculty development is crucial for implementing the session. Because of the focus on deliberate practice, adequate time must be allotted to hold the session. This program is reproducible with similar high-fidelity simulators.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.