Core Competencies or a Competent Core? A Scoping Review and Realist Synthesis of Invasive Bedside Procedural Skills Training in Internal Medicine
Bibliographic record
Abstract
PURPOSE: Invasive bedside procedures are core competencies for internal medicine, yet no formal training guidelines exist. The authors conducted a scoping review and realist synthesis to characterize current training for lumbar puncture, arthrocentesis, paracentesis, thoracentesis, and central venous catheterization. They aimed to collate how educators justify using specific interventions, establish which interventions have the best evidence, and offer directions for future research and training. METHOD: The authors systematically searched Medline, Embase, the Cochrane Library, and ERIC through April 2015. Studies were screened in three phases; all reviews were performed independently and in duplicate. The authors extracted information on learner and patient demographics, study design and methodological quality, and details of training interventions and measured outcomes. A three-step realist synthesis was performed to synthesize findings on each study's context, mechanism, and outcome, and to identify a foundational training model. RESULTS: From an initial 6,671 studies, 149 studies were further reduced to 67 (45%) reporting sufficient information for realist synthesis. Analysis yielded four types of procedural skills training interventions. There was relative consistency across contexts and significant differences in mechanisms and outcomes across the four intervention types. The medical procedural service was identified as an adaptable foundational training model. CONCLUSIONS: The observed heterogeneity in procedural skills training implies that programs are not consistently developing residents who are competent in core procedures. The findings suggest that researchers in education and quality improvement will need to collaborate to design training that develops a "competent core" of proceduralists using simulation and clinical rotations.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".