Discrete Choice Experiment to Evaluate Factors That Influence Preferences for Antibiotic Prophylaxis in Pediatric Oncology
Bibliographic record
Abstract
BACKGROUND: Bacterial and fungal infections in pediatric oncology patients cause morbidity and mortality. The clinical utility of antimicrobial prophylaxis in children is uncertain and the personal utility of these agents is disputed. Objectives were to use a discrete choice experiment to: (1) describe the importance of attributes to parents and healthcare providers when deciding between use and non-use of antibacterial and antifungal prophylaxis; and (2) estimate willingness-to-pay for prophylactic strategies. METHODS: Attributes were chances of infection, death and side effects, route of administration and cost of pharmacotherapy. Respondents were randomized to a discrete choice experiment outlining hypothetical treatment options to prevent antibacterial or antifungal infections. Each respondent was presented 16 choice tasks and was asked to choose between two unlabeled treatment options and an opt-out alternative (no prophylaxis). RESULTS: 102 parents and 60 healthcare providers participated. For the antibacterial discrete choice experiment, frequency of administration was significantly associated with utility for parents but not for healthcare providers. Increasing chances of infection, death, side effects and cost were all significantly associated with decreased utility for parents and healthcare providers in both the antibacterial and antifungal discrete choice experiment. Parental willingness-to-pay was higher than healthcare providers for both strategies. CONCLUSION: Chances of infection, death, side effects and costs were all significantly associated with utility. Parents have higher willingness-to-pay for these strategies compared with healthcare providers. This knowledge can help to develop prophylaxis programs.
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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 | 0.022 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".