How should neonatal clinicians act in the presence of moral distress?
Bibliographic record
Abstract
Hannah was born at 23+1 weeks. At 2 weeks of age, Hannah developed severe necrotising enterocolitis requiring extensive resection of her small bowel. She remains ventilated and dependent on inotropes. Additionally, Hannah is known to have bilateral grade IV intraventricular haemorrhages. The doctors and nurses caring for her believe that it is very unlikely she will survive and if she does, major disability is almost inevitable. The treating team has communicated its concerns to her parents several times over the past 48 hours and has suggested discontinuing life-sustaining interventions. Her parents understand the recommendation but have requested that ‘everything be done to save their baby’s life’. This leads to considerable distress among many team members who believe ongoing life-sustaining treatment is no longer in Hannah’s interests. Moral distress is increasingly recognised as an important issue affecting the well-being of clinicians. It is the anguish that occurs when clinicians are prevented from acting in accordance with their moral judgements.1 Most commonly, moral distress reflects the belief that a child is receiving disproportionate care (‘doing too much’) that is not in his or her interests,2 as in the case of Hannah. Historically, moral distress has often been framed as an institutional failing3 where medical hierarchy enforces nurses and medical residents to provided futile care against their better judgement and without a viable pathway for their concerns to be heard. The term ‘moral distress’ has therefore become something of a buzzword, used to demand action to overcome these perceived institutional failings, to empower distressed clinicians and thereby to eliminate moral distress within the institution. Within paediatric acute care settings, literature on moral distress generally implies that, to optimally address moral distress, the management plan for a patient needs to change, often to palliative care. However, that may be too narrow a view. …
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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 | 0.028 | 0.190 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.028 | 0.034 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".