190. Which antibiotic are you? Evaluation of a global antibiotic awareness personality quiz
Bibliographic record
Abstract
Abstract Background Improving understanding of the impact of antibiotic overuse is a key component of the global action plan to address antibiotic resistance. Play is an underutilized opportunity to engage adults in learning about antibiotic resistance and the importance of appropriate antibiotic use in mitigating this public health threat. Our objective was to evaluate the reach of a web-based antibiotic awareness personality quiz. Figure 1. Antibiotic Personality Quiz Participants Methods A personality quiz (http://www.tiny.cc/antibioticquiz) was developed using an online platform (Tryinteract.com). The quiz included a series of short personality-based questions. Once complete, based on the responses provided, the respondent was automatically assigned an antibiotic that best matched their personality. This result was accompanied by key teaching points about the assigned antibiotic, a statement about the importance of appropriate antibiotic use and links to find more information. The quiz was launched in November 2017 to coincide with World Antibiotic Awareness Week and disseminated via social media. It was updated iteratively each year. We evaluated usage statistics from November 7 2017 to June 7 2020. Results During the 31-month evaluation period, there were 287,868 views of the quiz, and it was completed 207,148 times. The quiz was shared extensively on social media (Facebook 1667 shares, Twitter 1390 clicks). From a subset of 37,825 recent participants who were asked about their profession, most identified as non-infectious diseases healthcare professionals (n= 18,235, 48.2%), followed by infectious disease healthcare professionals (n=8,119, 21.8%), and healthcare students (n=6,986, 18.5%) (Figure 1). Respondents were well-represented globally, including US, Canada, Spain, France, India, United Kingdom, and Indonesia. Conclusion This exploratory analysis suggests incorporation of play into social media campaigns may augment the size of the receiving audience. An antibiotic awareness personality quiz engaged a high volume and broad range of non-infectious disease experts in learning more about antibiotic resistance. Antimicrobial stewards and public health campaign leaders should incorporate play into awareness opportunities and evaluate their impact. Disclosures All Authors: No reported disclosures
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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".