A Not So Perfect Score: Factors Associated with the Rate of Straight Line Scoring in Oncology Training Programs.
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ABSTRACT:
SUBMITTER: Hinchcliff E
PROVIDER: S-EPMC8274252 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDiscussions with patients with cancer about cardiopulmonary resuscitation directives (code status) are often led by residents. This study was carried out in Canada to identify current educational practices and gaps in training for this communication skill.MethodsCanadian medical and radiation oncology residents and program directors (pds) were surveyed about teaching practices, satisfaction with current education, and barriers to teaching code status discussion skills. Relative frequencies of categorical and ordinal responses were calculated.ResultsBetween November 2016 and February 2017, 95 (58.6%) of 162 residents and 17 (63%) of 27 pds completed surveys. Only 54.1% and 48.3% of medical and radiation oncology residents, respectively, had received any code status communication training before entering an oncology program. While 41% of residents expected to receive formal teaching on this topic during residency, 47.1% of pds endorsed inclusion of this topic in curricula. Only 20% of residents reported receiving formal evaluation of this skill while 41.2% of pds indicated that evaluations are provided. The importance of this communication skill in oncology was strongly supported. Among residents, 88% desired more training, and 82.3% of pds identified the need for new educational resources. Lack of time, resources, and evaluation tools were among the most commonly identified barriers to teaching.ConclusionsOncology residency pds and trainees feel that code status communication is important, but teaching and evaluation of this skill are limited. Barriers to teaching and skill-building have been identified. Further work is underway to develop novel educational resources for code status communication training.
| S-EPMC7755451 | biostudies-literature
Project description:The Next Accreditation System (NAS) increases the focus on educational outcomes and meaningful evaluation of learners. This requires that key clinical faculty develop new assessment formats such as entrustable professional activities (EPAs).To build and develop milestone-based assessment tools supporting 5 EPAs for a hematology/oncology fellow continuity clinic, and to educate key clinical faculty regarding the Clinical Competency Committee (CCC) and the NAS.Program directors from 2 hematology/oncology fellowship programs developed 5 EPAs for continuity clinic evaluation supported by milestone-based assessment. The program directors met to create a unified CCC charter. Key clinical faculty helped to develop a milestone-based evaluation of fellow continuity clinic through creation of 5 hematology/oncology-specific EPAs. Formal entrustment regarding EPAs was deliberated by the CCC.A total of 18 fellows were evaluated. Clinical Competency Committee deliberation at each institution took approximately 10 minutes per fellow for discussion and decision regarding entrustment for all 5 EPAs supporting continuity clinic. One-third of postgraduate year (PGY)-4s, 50% of PGY-5s, and 100% of PGY-6s were deemed competent in all 5 EPAs by the CCC.All hematology/oncology trainees in San Antonio were evaluated using milestone-based assessment for continuity clinic, and entrustment decisions regarding 5 EPAs were made by the CCC. This project may provide other programs with a sound basis for adoption and further development of the next generation of evaluation tools at their institutions. Entrustable professional activities that are rotation specific should be used as a starting point for linking to the competencies, subcompetencies, and the reporting milestones.
| S-EPMC4507897 | biostudies-other
Project description:BackgroundDifferent professionals working in healthcare organizations (e.g., physicians, veterinarians, pharmacists, biologists, engineers, etc.) must be able to properly manage scarce resources to meet increasingly complex needs and demands. Due to the lack of specific courses in curricular university education, particularly in the field of medicine, management training programs have become an essential element in preparing health professionals to cope with global challenges. This study aims to examine factors influencing the effectiveness of management training programs and their outcomes in healthcare settings, at middle-management level, in general and by different groups of participants: physicians and non-physicians, participants with or without management positions.MethodsA survey was used for gathering information from a purposive sample of professionals in the healthcare field attending management training programs in Italy. Factor analysis, a set of ordinal logistic regressions and an unpaired two-sample t-test were used for data elaboration.ResultsThe findings show the importance of diversity of pedagogical approaches and tools and debate, and class homogeneity, as effectiveness factors. Lower competencies held before the training programs and problems of dialogue and discussion during the course are conducive to innovative practice introduction. Interpersonal and career outcomes are greater for those holding management positions.ConclusionsThe study reveals four profiles of participants with different gaps and needs. Training programs should be tailored based on participants' profiles, in terms of pedagogical approaches and tools, and preserve class homogeneity in terms of professional backgrounds and management levels to facilitate constructive dialogue and solution finding approach.
| S-EPMC11308623 | biostudies-literature
Project description:Moving along a straight path is a surprisingly difficult task. This is because, with each ensuing step, noise is generated in the motor and sensory systems, causing the animal to deviate from its intended route. When relying solely on internal sensory information to correct for this noise, the directional error generated with each stride accumulates, ultimately leading to a curved path. In contrast, external compass cues effectively allow the animal to correct for errors in its bearing. Here, we studied straight-line orientation in two different sized dung beetles. This allowed us to characterize and model the size of the directional error generated with each step, in the absence of external visual compass cues (motor error) as well as in the presence of these cues (compass and motor errors). In addition, we model how dung beetles balance the influence of internal and external orientation cues as they orient along straight paths under the open sky. We conclude that the directional error that unavoidably accumulates as the beetle travels is inversely proportional to the step size of the insect, and that both beetle species weigh the two sources of directional information in a similar fashion.
| S-EPMC6731515 | biostudies-literature
Project description:The statistical validation of peptide and protein identifications in mass spectrometry proteomics is a critical step in the analytical workflow. This is particularly important in discovery experiments to ensure only confident identifications are accumulated for downstream analysis and biomarker consideration. However, the inherent nature of discovery proteomics experiments leads to scenarios where the search space will inflate substantially due to the increased number of potential proteins that are being queried in each sample. In these cases, issues will begin to arise when the machine learning algorithms that are trained on an experiment specific basis cannot accurately distinguish between correct and incorrect identifications and will struggle to accurately control the false discovery rate. Here, we propose an alternative validation algorithm trained on a curated external data set of 2.8 million extracted peakgroups that leverages advanced machine learning techniques to create a generalizable peakgroup scoring (GPS) method for data independent acquisition (DIA) mass spectrometry. By breaking the reliance on the experimental data at hand and instead training on a curated external dataset, GPS can confidently control the false discovery rate while increasing the number of identifications and providing more accurate quantification in different search space scenarios. To first test the performance of GPS in a standard experimental environment and to provide a benchmark against other methods, a novel spike-in data set with known varying concentrations was analyzed. When compared to existing methods GPS increased the nunmber of identifications by 5-18\% and was able to provide more accurate quantification by increasing the number of ratio validated identifications by 24-74\%. To evaluate GPS in a larger search space, a novel data set of 141 blood plasma samples from patients developing acute kidney injury after sepsis was searched with a human tissue spectral library (10000+ proteins). Using GPS, we were able to provide a 207-377\% increase in the number of candidate differentially abundant proteins compared to the existing methods while maintaining competitive numbers of global identifications. Finally, using an optimized human tissue library and workflow we were able to identify 1205 proteins from the 141 plasma samples and increase the number of candidate differentially abundant proteins by 70.87\%. With the addition of machine learning aided differential expression, we were able to identify potential new biomarkers for stratifying subphenotypes of acute kidney injury in sepsis. These findings suggest that by using a generalized model such as GPS in tandem with a massive scale spectral library it is possible to expand the boundaries of discovery experiments in DIA proteomics. GPS is open source and freely available on github at (\url{https://github.com/InfectionMedicineProteomics/gps})
2023-07-20 | PXD038367 | Pride
Project description:IntroductionA significant number of patient encounters are perceived to be difficult. Residents receive little training in managing difficult clinical encounters, and lectures or traditional simulated patient encounters may not provide the opportunity to practice learned skills. Deliberate practice has been shown to be effective in training clinical skills. We used simulation with deliberate practice and feedback to train residents in difficult patient encounters.MethodsTwelve second-year residents in the University of Missouri Family and Community Medicine residency program participated in simulated patient encounters with difficult patients. The patients represented challenging personalities identified in a resident focus group. Resident performance was scored by the standardized patient, resident observers, and faculty instructor. Following debriefing with feedback, the residents repeated the clinical encounter incorporating the feedback. The sessions were scored again by the same individuals.ResultsAll scores improved from the first to second clinical encounter, except those that were at 100% for both encounters. The most improvement seen was in standardized patient scores. The smallest improvement was in provider self-scores.ConclusionResident performance improved according to all observers and their own self-assessments. These results are consistent with other studies that have demonstrated the effectiveness of deliberate practice in improving skills in other areas of medical education. Simulation-based learning with deliberate practice has the potential to improve resident management of difficult patient encounters.
| S-EPMC7279112 | biostudies-literature
Project description:Target fishing often relies on the use of reverse docking to identify potential target proteins of ligands from protein database. The limitation of reverse docking is the accuracy of current scoring funtions used to distinguish true target from non-target proteins. Many contemporary scoring functions are designed for the virtual screening of small molecules without special optimization for reverse docking, which would be easily influenced by the properties of protein pockets, resulting in scoring bias to the proteins with certain properties. This bias would cause lots of false positives in reverse docking, interferring the identification of true targets. In this paper, we have conducted a large-scale reverse docking (5000 molecules to 100 proteins) to study the scoring bias in reverse docking by DOCK, Glide, and AutoDock Vina. And we found that there were actually some frequency hits, namely interference proteins in all three docking procedures. After analyzing the differences of pocket properties between these interference proteins and the others, we speculated that the interference proteins have larger contact area (related to the size and shape of protein pockets) with ligands (for all three docking programs) or higher hydrophobicity (for Glide), which could be the causes of scoring bias. Then we applied the score normalization method to eliminate this scoring bias, which was effective to make docking score more balanced between different proteins in the reverse docking of benchmark dataset. Later, the Astex Diver Set was utilized to validate the effect of score normalization on actual cases of reverse docking, showing that the accuracy of target prediction significantly increased by 21.5% in the reverse docking by Glide after score normalization, though there was no obvious change in the reverse docking by DOCK and AutoDock Vina. Our results demonstrate the effectiveness of score normalization to eliminate the scoring bias and improve the accuracy of target prediction in reverse docking. Moreover, the properties of protein pockets causing scoring bias to certain proteins we found here can provide the theory basis to further optimize the scoring functions of docking programs for future research.
| S-EPMC5308821 | biostudies-literature
Project description:BackgroundProgram directors (PDs) in emergency medicine (EM) receive an abundance of applications for very few residency training spots. It is unclear which selection strategies will yield the most successful residents. Many authors have attempted to determine which items in an applicant's file predict future performance in EM.ObjectivesThe purpose of this scoping review is to examine the breadth of evidence related to the predictive value of selection factors for performance in EM residency.MethodsThe authors systematically searched four databases and websites for peer-reviewed and gray literature related to EM admissions published between 1992 and February 2019. Two reviewers screened titles and abstracts for articles that met the inclusion criteria, according to the scoping review study protocol. The authors included studies if they specifically examined selection factors and whether those factors predicted performance in EM residency training in the United States.ResultsAfter screening 23,243 records, the authors selected 60 for full review. From these, the authors selected 15 published manuscripts, one unpublished manuscript, and 11 abstracts for inclusion in the review. These studies examined the United States Medical Licensing Examination (USMLE), Standardized Letters of Evaluation, Medical Student Performance Evaluation, medical school attended, clerkship grades, membership in honor societies, and other less common factors and their association with future EM residency training performance.ConclusionsThe USMLE was the most common factor studied. It unreliably predicts clinical performance, but more reliably predicts performance on licensing examinations. All other factors were less commonly studied and, similar to the USMLE, yielded mixed results.
| S-EPMC7369487 | biostudies-literature
Project description:Mass spectrometry remains an important method for analysis of modified nucleosides ubiquitously present in cellular RNAs, in particular for ribosomal and transfer RNAs that play crucial roles in mRNA translation and decoding. Furthermore, modifications have effect on the lifetimes of nucleic acids in plasma and cells and are consequently incorporated into RNA therapeutics. To provide an analytical tool for sequence characterization of modified RNAs, we developed Pytheas, an open-source software package for automated analysis of tandem MS data for RNA. This dataset contains the 95 MS/MS spectra of 3-14 nts-long oligomers, used for the training and validation of Pytheas' scoring function.
2022-05-04 | PXD030435 | Pride
Project description:The aim of this study is to describe the kinematic gait characteristics of straight line walk in clinically sound dairy cows using body mounted Inertial Measurement Units (IMUs) at multiple anatomical locations. The temporal parameters used are speed and non-speed normalized stance duration, bipedal and tripedal support durations, maximal protraction and retraction angles of the distal limbs and vertical displacement curves of the upper body. Gait analysis was performed by letting 17 dairy cows walk in a straight line at their own chosen pace while equipped with IMU sensors on tubera sacrale, left and right tuber coxae (LTC and RTC), back, withers, head, neck and all four lower limbs. Data intervals with stride by stride regularity were selected based on video data. For temporal parameters, the median was calculated and 95% confidence intervals (CI) were estimated based on linear mixed model (LMM) analysis, while for limb and vertical displacement curves, the median and most typical curves were calculated. The temporal parameters and distal limb angles showed consistent results with low variance and LMM analysis showed non-overlapping CI for all temporal parameters. The distal limb angle curves showed a larger and steeper retraction angle range for the distal front limbs compared with the hind limbs. The vertical displacement curves of the sacrum, withers, LTC and RTC showed a consistent sinusoidal pattern while the head, back and collar curves were less consistent and showed more variation between and within cows. This kinematic description might allow to objectively differentiate between normal and lame gait in the future and determine the best anatomical location for sensor attachment for lameness detection purposes.
| S-EPMC8294546 | biostudies-literature