Moral distress and burnout among cardiovascular surgery intensive care unit healthcare professionals: A prospective cross-sectional survey.
Bibliographic record
Abstract
BACKGROUND: The intensive care unit (IGU) is a busy, high stress, complex environment in which health care professionals routinely provide numerous forms of advanced life support and life sustaining measures to a wide mix of critically ill patients. Frontline ICU professionals directly involved in patient care may be subjected to considerable psychosocial stressors and be susceptible to moral distress and burnout. PURPOSE: To describe and compare the prevalence and contributing factors to moral distress and burnout among ICUprofessionals in a large quaternary cardiovascular surgery ICU (CVICU). METHODS: Web-based survey of ICU professionals (registered nurses [RN]/nurse practitioners [NP]; registered respiratory therapists [RRT]; allied health [AH] and physicians [MD]) working in a 24-bed CVICU at the Mazankowski Alberta Heart Institute, between June 15-29, 2015. The survey captured sociodemographic data and integrated the Moral Distress Scale-Revised, the Maslach Burnout Inventory', and a validated job satisfaction questionnaire. FINDINGS: One hundred sixty-nine providers completed the sur- vey (response rate 88%). The majority of respondents were aged 26-34 years old (45%), female (79%), married or common law (50%), full-time employed (78%) and had been working in the CVICU for >5 years (46%). Moral distress scores were highest among RN/NP (med [IQR] 80 [57-110]) and RRT (85 [61-104]) compared to AH (54 [39-66]) and physicians (66 [43-82], p=0.05). The highest-ranked sources of moral distress were related to controversies on end-of-life care ("Continue to participate in the care for a hopelessly ill person who is being sustained on a ventilator, when no one will make a decision to withdrawal support") and poor communication ("witness healthcare providers giving false hope' to a patient or family"). High, moderate and low levels of burnout syndrome were found in 64.0%, 22.7% and 13.3% of respondents with significantly greater levels among non-physician professionals (p<0.001). Job satisfaction was highest for physicians compared with other professionals (p<0.001). The item "the recognition you get for good work" was consistently rated as poor across all groups. Moral distress and burnout scores were positively correlated (p<0. 001), whereas both were neg- atively correlated with job satisfaction (p<0.001 for both). This was primarily driven by RN/NP scores. CONCLUSION: Moral distress and burnout are common in health- care professionals in a large academic cardiovascular surgery ICU, in particular among nurses and respiratory therapists. Both moral distress and burnout have a negative perception on job satisfaction. These findings will direct strategies to mitigate moral distress and burnout along with enhancing patient care and improving the workplace environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".