PNAE Oral and Poster Presentations
Bibliographic record
Abstract
Introduction: Caring for a child who has an unexpected ALTE in hospital can be stressful. An ALTE may include a cardiac arrest, respiratory arrest or call for immediate assistance. An international survey of practice was conducted to identify any existing interventions to inform a PhD program of work aimed at reducing the stress from these events through preparation and support. Purpose: The purpose of the survey was threefold: (1) Describe ‘normal’ practice when it comes to preparing staff or providing psychological support after caring for a child who has had an ALTE. (2) Determine if there are any interventions to prepare clinical staff for potential psychological effects of caring for a child who has an ALTE. (3) Determine if there are any interventions to provide support for clinical staff after caring for a child who has an ALTE. Material - Methods: An 18 item semi structured questionnaire was designed for the study to allow respondent to describe practices within their institution and outline their opinions and professional experiences. Clinicians from selected children’s and adult hospitals in Australia, Canada, New Zealand, United Kingdom and the United States of America were contacted by telephone. Following consent they were given the option to complete the survey via the telephone, by post or online. Results: Of the 61 hospitals approached 44 (72%) clinicians responded. Eighteen (41%) respondents identified interventions in place to prepare nurses for an ALTE ranging from (but not limited to) ad hoc discussions during life support training through to structured simulation training. Thirty-six (82%) respondents identified that they had interventions in place to support nurses after an ALTE ranging from (but not limited to) debriefing through to structured case reviews. Conclusions: Interventions varied across institutions, with no outcome or evaluation data for the interventions published to date.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.828 | 0.619 |
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".