Mapping educational opportunities for healthcare workers on antimicrobial resistance and stewardship around the world
Bibliographic record
Abstract
BACKGROUND: Antimicrobial resistance is an important global issue facing society. Healthcare workers need to be engaged in solving this problem, as advocates for rational antimicrobial use, stewards of sustainable effectiveness, and educators of their patients. To fulfill this role, healthcare workers need access to training and educational resources on antimicrobial resistance. METHODS: To better understand the resources available to healthcare workers, we undertook a global environmental scan of educational programs and resources targeting healthcare workers on the topic of antimicrobial resistance and antimicrobial stewardship. Programs were identified through contact with key experts, web searching, and academic literature searching. We summarized programs in tabular form, including participating organizations, region, and intended audience. We developed a coding system to classify programs by program type and participating organization type, assigning multiple codes as necessary and creating summary charts for program types, organization types, and intended audience to illustrate the breadth of available resources. RESULTS: We identified 94 educational initiatives related to antimicrobial resistance and antimicrobial stewardship, which represent a diverse array of programs including courses, workshops, conferences, guidelines, public outreach materials, and online-resource websites. These resources were developed by a combination of government bodies, professional societies, universities, non-profit and community organizations, hospitals and healthcare centers, and insurance companies and industry. Most programs either targeted healthcare workers collectively or specifically targeted physicians. A smaller number of programs were aimed at other healthcare worker groups including pharmacists, nurses, midwives, and healthcare students. CONCLUSIONS: Our environmental scan shows that there are many organizations working to develop and share educational resources for healthcare workers on antimicrobial resistance and antimicrobial stewardship. Governments, hospitals, and professional societies appear to be driving action on this front, sometimes working with other types of organizations. A broad range of resources have been made freely available; however, we have noted several opportunities for action, including increased engagement with students, improvements to pre-service education, recognition of antimicrobial resistance courses as continuing medical education, and better platforms for resource-sharing online.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".