Exploring the Distribution of 3D-Printed Simulator Designs Using Open-Source Databases to Facilitate Simulation-Based Learning Through a University and Nonprofit Collaboration: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Advancements in technology have enhanced education, training, and application in health care. However, limitations are present surrounding the accessibility and use of simulation technology (eg, simulators) for health profession education. Improving the accessibility of technology developed in university-based research centers by nonprofit organizations (NPOs; eg, hospitals) has the potential to benefit the health of populations worldwide. One example of such technology is 3D-printed simulators. OBJECTIVE: This scoping review aims to identify how the use of open-source databases for the distribution of simulator designs used for 3D printing can promote credible solutions for health care training while minimizing the risks of commercialization of designs for profit. METHODS: This scoping review will follow the Arksey and O'Malley methodological framework and the Joanna Briggs Institute guidance for scoping reviews. Ovid MEDLINE, CINAHL, Web of Science, and PsycINFO will be searched with an applied time frame of 2012 to 2022. Additionally, gray literature will be searched along with reference list searching. Papers that explore the use of open-source databases in academic settings and the health care sector for the distribution of simulator designs will be included. A 2-step screening process will be administered to titles and abstracts, then full texts, to establish paper eligibility. Screening and data extraction of the papers will be completed by 2 reviewers (MS and SS) for quality assurance. The scoping review will report information on the facilitation of distributing 3D-printed simulator designs through open-source databases. RESULTS: The results of this review will identify gaps in forming partnerships with NPOs and university-based research centers to share simulator designs. The scoping review will be initiated in December 2024. CONCLUSIONS: The information collected will be relevant and useful for stakeholders such as health care providers, researchers, and NPOs for the purpose of overcoming the gaps in research regarding the use and distribution of simulation technology. The scoping review has not been conducted yet. Therefore, there are currently no findings to report on. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/53167.
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 | 0.126 | 0.143 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.015 |
| Bibliometrics | 0.024 | 0.020 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.076 | 0.016 |
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".