Ethical Quandaries at End of Life: Navigating Real-World Case Examples as a Pediatric Psychologist
Bibliographic record
Abstract
Objective: The aim of this article is to illustrate and discuss ethical dilemmas that might occur in the context of pediatric end-of-life care using case examples. The cases highlight ethical principles and are distilled by a multidisciplinary group of pediatric providers (i.e., psychologists, medical student, psychiatrist, bone marrow transplant physician), offering a unique perspective and insight. Familiarity with the principles discussed is important for pediatric psychologists working in medical settings, who might be uniquely suited to help patients, families, and medical teams navigate these challenges. Method: Two composite case examples are presented that focus on commonly encountered ethical dilemmas including: disclosing poor prognoses to patients; disagreements between families and medical teams; differing opinions on plans of care between medical team members. Important cultural considerations are also highlighted. Core ethical dilemmas are discussed and potential ways in which pediatric psychologists can offer expertise and intervention. Results: Recognition and collaboration around ethical dilemmas is essential to managing complex situations in pediatric palliative care. Moreover, it is imperative to consider the cultural factors of a family, which could provide additional insight into their preferences and values. Conclusions: Ethical challenges are prevalent in the field of pediatric palliative care. As the medical field continues to advance, pediatric psychologists are likely to encounter a range of clinical dilemmas. They should be prepared to consider the complex systemic, interpersonal, family, and cultural factors that might arise in their work. Implications for Impact Statement This article discusses ethical challenges pediatric psychologists might encounter when treating patients at the end of life. It is written by a group of multidisciplinary providers, thus offering a unique perspective. Two composite case examples are presented which demonstrate the complex ethical dilemmas that often arise when working with critically ill youth, including those with poor prognosis. Pediatric psychologists involved in pediatric palliative care might benefit from being familiar with ethical principles in order to navigate challenging and complex situations.
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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 | 0.019 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".