Abstract 353: Resuscitation Science Training Programs: A Review
Bibliographic record
Abstract
Introduction: While training in the practice of resuscitation is standardized by AHA guidelines and ACLS protocols, training in resuscitation science research has generally relied on mentorship by current researchers. Formal research-focused training programs in resuscitation science exist but the nature of such programs is not well known. We sought to determine the current state of graduate or professional-level research-focused programs in adult resuscitation science using scoping review methodology. Methods: We conducted an online web search for the phrases “resuscitation science education”, “resuscitation science training”, “resuscitation medicine education”, and “resuscitation medicine training” in May 2020. Entries were screened for relevance by their title and web text by two independent researchers. Entries were excluded if they did not contain a sizable research foundation or major project component for students. After the screening process, entries were analyzed descriptively and thematically categorized by aspects of program delivery. Results: We identified 16 programs that satisfied all inclusion criteria, consisting of 9 instructional programs and 7 research fellowships. Instructional programs were divided between stand-alone programs (4) or electives/add-ons within existing degrees (5). These programs were highly varied in their research requirements with some requiring minimal academic output. Electives/add-ons within existing degrees were generally shorter in length with most averaging only 4 weeks to completion. Two programs offered programs discussing pre-hospital, in-hospital, and post-hospital considerations for patients/caregivers and/or clinicians. Only one stand-alone program was degree-granting. Research fellowships generally varied between 1-2 years. The vast majority of all programs were limited to those with a clinical background, with emphasis on physicians specializing in emergency medicine. Conclusion: There is a relative lack of standardized research-focused training programs within resuscitation science. Moreover, existing programs tend to be constrained to those with a clinical background, presenting a barrier of entry for non-clinicians.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.020 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".