Moral Distress of Clinicians in Canadian Pediatric and Neonatal ICUs*
Bibliographic record
Abstract
OBJECTIVE: To quantify moral distress in neonatal ICU and PICU clinicians and to identify associated factors. DESIGN: A national cross-sectional survey of clinicians working in an neonatal ICU or PICU. Moral distress was assessed with the Moral Distress Scale-Revised and by self-rating. Depersonalization was assessed on the subscale of the Maslach Burnout Inventory. Respondents reported their attendance at each of six hospital supports that may serve to mitigate moral distress in frontline staff. Analyses compared outcomes across respondent characteristics and hierarchical linear regression evaluated individual, ICU, hospital, and regional effects. SETTING: Eligible ICUs were PICUs and level-3 neonatal ICUs in Canada. SUBJECTS: Eligible participants had worked in the participating ICU for more than 3 months. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We identified 54 eligible ICUs from 31 hospitals. Forty-nine Canadian neonatal ICUs and PICUs (91%) contributed 2,852 complete responses for a 45.2% response rate. Most respondents were nurses (64.9%) or from a neonatal ICU (66.5%). The median and interquartile range Moral Distress Scale-Revised were 79 (52-113); 997 respondents (34.2%) had Moral Distress Scale-Revised scores greater than or equal to 100, and 234 respondents (8.3%) strongly agreed that work caused them significant moral distress. Nurses had a median (interquartile range) Moral Distress Scale-Revised score of 85 (57-121), 19 points higher than physicians and 8 points higher than respiratory therapists (p < 0.0001). Moral Distress Scale-Revised scores increased from 53 (35-79) for those working in ICU less than 1 year to 83 (54-120) in those working in ICU more than 30 years (p < 0.0001); 22.5% reported high degrees of depersonalization, which was associated with moral distress (p < 0.0001). Variability in Moral Distress Scale-Revised scores was explained by individual-level (92%), hospital-level (5%), and ICU-level effects (1%). Frequency of participation in potentially mitigating hospital supports had small effects (< 10 points) on mean Moral Distress Scale-Revised scores. CONCLUSIONS: Moral distress is common in clinicians working in ICUs for children. Addressing moral distress will require interventions tailored to individuals in higher-risk groups.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".