How paediatric nurses frame the ethics of non-disclosure directives
Bibliographic record
Abstract
BackgroundNurses caring for hospitalised children can be told not to disclose information to the patient. Such non-disclosure directives in adult care pose recognised ethical problems, as they impinge on a patient's autonomy and right to their own information, and have been discussed widely in the literature, from a physician's perspective. Despite the ethical implications, there is less discussion of the ethics of withholding information from children. Nurses are well positioned to advocate for the rights of a child while considering their best interests; hence, nurses' thinking about the ethics of non-disclosure directives is valuable.AimThe aim of this study was to explore the experiences and attitudes of nurses with truth-telling to seriously ill children, specifically how nurses frame and think about the ethical challenges when given a directive not to tell the truth to a child.DesignAn interpretive phenomenological approach was employed for this research, with data collected by semi-structured interviews.Participant PopulationTwenty-six nurses in Australia who had cared for children hospitalised with a serious illness in the previous 5 years.Ethical ConsiderationsEthics approval was granted by the University of Melbourne's Human Research Ethics Committee (37283A). Informed consent was acquired from all participants.FindingsFour themes encompass the views nurse-participants expressed about the ethics of a non-disclosure directive: (i) Lying is wrong, (ii) Children should know, (iii) It's hard for us when the child doesn't know, but (iv) It's not our place to tell. Nurse-participants described how a non-disclosure directive affected how they cared for their patients.ConclusionsNurse-participants believed they should be honest and articulated ethical reasons why children should be told the truth about their medical condition, but did not feel they were able to initiate this. It is recommended that nurses are supported in these ethically challenging situations and included in decision-making about how to respond when parents direct that information be withheld from their child.
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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 | 0.040 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".