“It Is Difficult to Always Be an Antagonist”: Ethical, Professional, and Moral Dilemmas as Potentially Psychologically Traumatic Events among Nurses in Canada
Bibliographic record
Abstract
AIMS: We explore social and relational dynamics tied to an unexplored potentially psychologically traumatic event (PPTE) that can impact nurses' well-being and sense of their occupational responsibilities: namely, the moral, ethical, or professional dilemmas encountered in their occupational work. DESIGN: We used a semi-constructed grounded theory approach to reveal prevalent emergent themes from the qualitative, open-ended component of our survey response data as part of a larger mixed-methods study. METHODS: We administered a national Canadian survey on nurses' experiences of occupational stressors and their health and well-being between May and September 2019. In the current study, we analyzed data from four open text fields in the PPTE section of the survey. RESULTS: In total, at least 109 participants noted that their most impactful PPTE exposure was a moral, professional, and/or ethical dilemma. These participants volunteered the theme as a spontaneous addition to the list of possible PPTE exposures. CONCLUSIONS: Emergent theme analytic results suggest that physicians, other nurses, staff, and/or the decision-making power of patients' families can reduce or eliminate a nurse's perception of their agency, which directly and negatively impacts their well-being and may cause them to experience moral injury. Nurses also report struggling when left to operationalize patient care instructions with which they disagree. IMPACT: Nurses are exposed to PPTEs at work, but little is known about factors that can aggravate PPTE exposure in the field, impact the mental wellness of nurses, and even shape patient care. We discuss the implications of PPTE involving moral, professional, and ethical dilemmas (i.e., potentially morally injurious events), and provide recommendations for nursing policy and practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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".