Knowledge, perspectives and health outcome expectations of antibiotic therapy in hospitalized patients
Bibliographic record
Abstract
The World Health Organization (WHO) has recognized antimicrobial resistance (AMR) as a top threat to global health. However, the public has an incomplete understanding of AMR and its consequences. The aim of this study was to explore patients’ understanding, perspective and health outcome expectations for antibiotic therapy within an inpatient internal medicine population. A mixed methods study, combining a cross-sectional survey with qualitative methods. Fourteen questions (10 paper survey and four open ended interview questions) were used, and were completed by the participant in one sitting. Participants were recruited from General Internal Medicine units at two academic hospitals in Canada (convenience sample). Thirty participants were included. Out of a scale of 1–100%, participants indicated moderate concern (mean of 40%) about getting an infection that could not be cured by antibiotics. The majority agreed that they trusted their healthcare team to decide on appropriate antibiotic therapy (mean of 81%). The participants strongly agreed (mean of 90%) that it was important to understand the rationale for their antibiotic therapy. Three themes emerged from the qualitative analysis: 1) varying levels of knowledge; 2) viewing antibiotics as beneficial while emphasizing effectiveness; and 3) trusting the healthcare team with expectations for inclusion in decision making. The study results showed varying levels of patients’ antibiotic knowledge and large gaps in awareness related to AMR. Exploring the role and workflow of interdisciplinary healthcare professionals may be a potential strategy to minimize patients’ knowledge gap related to antimicrobial therapy and AMR.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".