Interprofessional perceptions of emotional, social, and ethical effects of multidrug-resistant organisms: A qualitative study
Bibliographic record
Abstract
INTRODUCTION: Multi-drug-resistant organisms (MDRO) are usually managed by separating the infected patients to protect others from colonization and infection. Isolation precautions are associated with negative experiences by patients and their relatives, while hospital staff experience a heavier workload and their own emotional reactions. METHODS: In 2018, 35 participants (nurses, physicians, pharmacists) in an antimicrobial-stewardship program participated in facilitated discussion groups working on the emotional impact of MDRO. Deductive codings were done by four coders focusing on the five basic emotions described by Paul Ekmans. RESULTS: All five emotions revealed four to 11 codes forming several subthemes: Anger is expressed because of incompetence, workflow-impairment and lack of knowledge. Anxiety is provoked by inadequate knowledge, guilt, isolation, bad prognoses, and media-related effects. Enjoyment is seldom. Sadness is experienced in terms of helplessness and second-victim effects. Disgust is attributed to shame and bad associations, but on the other hand MDROs seem to be part of everyday life. Deductive coding yielded additional codes for bioethics and the Calgary Family Assessment Method. CONCLUSION: MDRO are perceived to have severe impact on emotions and may affect bioethical and family psychological issues. Thus, further work should concentrate on these findings to generate a holistic view of MDRO on human life and social systems.
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".