Purpose: Learner handover (LH) is the sharing of information about trainees between faculty supervisors. This scoping review aimed to summarize key concepts across disciplines surrounding the influence of prior performance information (PPI) on current performance ratings and implications for LH in medical education.
Method: The authors used the Arksey and O'Malley framework to systematically select and summarize the literature. Cross-disciplinary searches were conducted in six databases in 2017-2018 for articles published after 1969. To represent PPI relevant to LH in medical education, eligible studies included within-subject indirect PPI for work-type performance and rating of an individual current performance. Quantitative and thematic analyses were conducted.
Results: Of 24,442 records identified through database searches and 807 through other searches, 23 articles containing 24 studies were included. Twenty-two studies (92%) reported an assimilation effect (current ratings were biased toward the direction of the PPI). Factors modifying the effect of PPI were observed, with larger effects for highly polarized PPI, negative (vs positive) PPI, and early (vs subsequent) performances. Specific standards, rater motivation, and certain rater characteristics mitigated context effects, whereas increased rater processing demands heightened them. Mixed effects were seen with nature of the performance and with rater expertise and training.
Conclusions: PPI appears likely to influence ratings of current performance, and an assimilation effect is seen with indirect PPI. Whether these findings generalize to medical education is unknown, but they should be considered by educators wanting to implement LH. Future studies should explore PPI in medical education contexts and real-world settings.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1097/ACM.0000000000002731 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Development of a CT radiomics prognostic model for post renal tumor resection overall survival based on transformer enhanced K-means clustering.
Med Phys
January 2025
Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Background: Kidney tumors, common in the urinary system, have widely varying survival rates post-surgery. Current prognostic methods rely on invasive biopsies, highlighting the need for non-invasive, accurate prediction models to assist in clinical decision-making.
Purpose: This study aimed to construct a K-means clustering algorithm enhanced by Transformer-based feature transformation to predict the overall survival rate of patients after kidney tumor resection and provide an interpretability analysis of the model to assist in clinical decision-making.
Prenatal diagnosis following preimplantation genetic testing (PGT): recommendations of the Italian Society of Human Genetics (SIGU).
J Assist Reprod Genet
January 2025
Medical Genetics & Genomics Unit, AULSS8 Berica, Vicenza, Italy.
This document aims to provide good practice recommendations in order to support maternal-foetal medicine specialists, clinical geneticists and clinical laboratory geneticists in the management of pregnancies obtained after the transfer of an embryo tested with preimplantation genetic testing (PGT). It was drafted by geneticists expert in preimplantation genetics and prenatal genetic diagnosis belonging to the "Working Group in Cytogenomics, Prenatal and Reproductive Genetics" of the "Italian Society of Human Genetics" (SIGU). In particular, the paper addresses the diagnostic algorithm to be applied in prenatal follow-up depending on the type of PGT performed, the results obtained and the related diagnostic value based on the most recent literature data and Italian and international recommendations.
View Article and Find Full Text PDFSafety and efficacy of tirofiban in the endovascular treatment of intracranial aneurysms: a systematic evaluation and meta-analysis.
Neurosurg Rev
January 2025
Hengyang Key Laboratory of Hemorrhagic Cerebrovascular Disease, Department of Neurosurgery, the Second Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421000, Hunan, China.
Patients with intracranial aneurysms (IA) undergoing endovascular treatment face varying risks and benefits when tirofiban is used for thromboprophylaxis during surgery. Currently, there is a lack of high-level evidence summarizing this information. This study aims to conduct a systematic review and meta-analysis to evaluate the efficacy and safety of tirofiban during endovascular treatment of IA.
View Article and Find Full Text PDFBioaccumulation of perfluorooctane sulfonic acid (PFOS) and oxidative stress in snapping turtles in New York, USA.
Environ Sci Pollut Res Int
January 2025
Department of Biology, Hamilton College, Clinton, NY, USA.
Perfluorooctane sulfonic acid (PFOS) is an anthropogenic chemical found in aqueous film-forming foams (AFFFs) and many consumer products. Despite its environmental ubiquity and persistence, little is known about the effects of PFOS on stress levels in wild animals. Here, we examined PFOS bioaccumulation and correlations between PFOS exposure and oxidative stress in snapping turtles (Chelydra serpentina) downstream of Griffiss Air Force Base in Rome, New York, a known source of AFFF contamination.
View Article and Find Full Text PDFSystematic Review of Hybrid Vision Transformer Architectures for Radiological Image Analysis.
J Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!