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Record W4238784021 · doi:10.4300/jgme-05-04-38

In This Issue

2013· article· en· W4238784021 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Graduate Medical Education · 2013
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsData scienceMEDLINEComputer scienceMedicineMedical educationPolitical science

Abstract

fetched live from OpenAlex

Simpson, Yarris, and Carek define scholarly activity, drawing on classic interpretations of scholarship (p. 539). Sullivan and Artino provide practical guidance for analyzing and interpreting Likert scales, assuring researchers that it is acceptable to use parametric tests with ordinal data (p. 541).Alexander et al identify 4 types of “difficult residents,” and offer tips for identification and management (p. 547); Rocke and Lee discuss educating residents on how to disclose errors to patients and families (p. 550); and Fargen and Rosen speculate whether duty hour limits may teach residents that dishonesty is an acceptable response to a challenging situation (p. 553). Rieselbach and colleagues discuss a new funding model to help alleviate rural primary care shortages (p. 556). In an editorial, Obley and Cooney point out that workforce solutions may need to go beyond graduate medical education, and consider physicians in practice, as well as the role of nonphysician professionals and new models of care (p. 543).Sandal and colleagues review the history and foundation of grand rounds, and suggest ways for adapting a time-honored teaching strategy to current needs and constraints (p. 560).The Editors' Choice articles relate to aspects of residents' time off and on duty—from completing clinical documentation requirements to napping on the night shift, and childbearing patterns in surgical residents. Christino and colleagues conducted a national survey of residents' perceptions of clinical documentation, finding that documentation requirements consume a sizable portion of resident time, and that residents perceive them as a barrier to time with patients (p. 600). Smith et al studied childbearing patterns for surgical residents over 3 decades, finding an increase in childbearing during residency for recent cohorts (p. 625). McDonald et al found that off-duty sleep supplemented with on-duty naps was an effective strategy for sustaining vigilance, learning, and memory during night float rotations (p. 634).Two research articles address scholarly activity. Ledford et al highlight resident uncertainty about what is expected of them in research and scholarly pursuits (p. 564). Curran and colleagues studied how teaching and other forms of scholarly activity influenced career advancement for obstetrics and gynecology faculty (p. 620).Caron et al describe the development of a new assessment tool for resident skills in communicating with patients (p. 570). Chan and colleagues highlight the importance of interpersonal relationships in emergency department referrals and consultations (p. 576). In a commentary, Varpio and Regehr discuss contradictions in the role of interprofessional trust, deeming it necessary for effective collaboration, yet potentially detrimental to questioning that may enhance patient safety (p. 703).Ryan, Barlas, and Pollack explore the correlation between faculty performance assessment and in-training examination performance for emergency medicine residents (p. 582). Research from the Veterans Health Administration assessed learner perception of the learning environment, focusing on continuity and patient-centered care (Byrne and colleagues, p. 587). Sandhu et al describe a model for effective family-centered bedside rounds (p. 594). A commentary by Handel and Steckler draws on Covey's work to identify 7 habits of effective rounding (p. 705).Lenchus et al describe the development of a multi-factorial approach to assessing competence to perform invasive bedside procedures, reporting it discriminated between residents judged competent and those not judged competent (p. 605). Ross and colleagues report that education using simulation reduced the time for first-year pediatrics residents to initiate cardiopulmonary resuscitation (p. 613). Gonzalo and colleagues found errors in interns' retrospective reporting of compliance with the limit on continuous duty that may result in both overestimation and underestimation of violations (p. 630).A research curriculum with milestones, protected time, and mentoring resulted in increased numbers of grants and peer-reviewed publications (Robbins et al, p. 646). A study of barriers to continuity in resident clinics produced recommendations for scheduling changes, enhanced communication about shared patients, more effective use of nonphysician resources, and educating patients about the benefit of continuity (Wieland et al, p. 668). A longitudinal career-focused experience for third-year pediatrics residents was accepted by residents, particularly those interested in becoming hospitalists (Rosenberg et al, p. 639). An intervention to improve handoffs at a large university-based institution focused on involving resident leaders, and enhanced education and assessment of handoffs (Boggan et al, p. 652). A novel process for evaluating electronic health record competency in first-year residents identified problem areas for all residents and a group of underperforming residents for further targeted intervention (Nuovo et al, p. 658). Input from experienced providers identified aspects that increased the perceived realism of low-fidelity simulation models for use in dilation and evacuation training for obstetrics and gynecology residents (Baldwin et al, p. 662). Funding through an institutional grant overcame local barriers and produced innovative interventions across different training programs in a large university-based institution (Colletti et al, p. 665).Brief reports describe a novel curriculum for community health training for internal medicine residents (Catalanotti et al, p. 674); development of an examination to assess residents' knowledge of ambulatory geriatrics (Kalender-Rich et al, p. 678); a transitional care curriculum that introduced interns to nonhospital settings such as postacute care and home health care (Schoenborn et al, p. 681); an annual memorial service that helps trainees cope with the emotional impact of the death of patients (Schoenborn et al, p. 686); a pilot of a quality improvement curriculum for concurrent learning by residents and faculty (Wong et al, p. 689); and use of an ambulatory patient registry to help cardiology fellows improve patient care (Frederick et al, p. 694).Dougherty, Ross, and Lypson discuss tracking and ensuring resident progress through a mentored portfolio (p. 701).Letters to the editor comment on the use of Skype for Supplemental Offer and Acceptance Program interviews (Nield et al, p. 707), and a model for improving pediatrics residents' scholarly activity (Kupferman and Rapaport, p. 708). This section also features 3 top-scoring abstracts presented at the International Conference on Residency Education held in September 2013 in Calgary, Canada. Projects explored case review and supervision on clinical teaching units (Goldszmidt et al, p. 709) and resident sleep associated with different limits on continuous duty overnight (Osborne et al, p. 710). The winning abstract studied implementation fidelity in a multi-site rollout of a new assessment approach (Ross et al, p. 711).Nambudiri discusses excitement, physical examination, and coffee stains in an observation of the early clinical learning process for second-year medical students (p. 712).A companion piece to the editorial on scholarship describes the ongoing transition from an approach to scholarly activities that emphasized structure and process to an outcomes-focused model to match the outcomes of the Next Accreditation System (p. 714). Weiss and colleagues present an update on the Clinical Learning Environment Review (CLER), including new information from the first full year of CLER visits (p. 718).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.349
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2013
Admission routes1
Has abstractyes

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