Caregivers attitudes for very premature infants: what if they knew?
Bibliographic record
Abstract
BACKGROUND: Decisions about resuscitation of extremely premature babies are controversial. Such decisions may reflect poor understanding of outcomes. OBJECTIVE: To compare caregivers' attitudes towards the resuscitation of a premature infant if they are only told the infant's gestational age or if they are only given prognostic information for infants at that gestational age. DESIGN/METHODS: Residents and nurses involved in perinatal care were asked whether they would resuscitate a depressed AGA 24-week gestation infant at birth. In another question they were asked whether they would resuscitate a depressed preterm infant with a 50% chance of survival, knowing that of those who survived, 50% would have a development 'within normal limits', 20-25% a serious handicap and 40% with behavioural and/or learning disability. RESULTS: Two hundred and seventy-nine caregivers responded (91% response rate). In the scenario that only presented gestational age, 21% of respondents would resuscitate. In the scenario that only presented prognostic statistics, 51% of respondents would resuscitate (p<0.05). CONCLUSIONS: Providers of perinatal health care respond to vignettes differently depending upon the format in which information is provided. The relative unwillingness to resuscitate a baby of 24-week gestation is surprising since outcomes for such babies are the same or better than those we described in the scenario that provided only outcome data without specifying gestational age. Two explanations are possible: (1) respondents have irrational negative associations with low gestational ages or (2) respondents are unaware of actual outcomes.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".