Proceedings of Réanimation 2020, the French Intensive Care Society International Congress
Bibliographic record
Abstract
Rationale: The intensive care units (ICU) are fertile ground for the emergence of professional stressors. Assessed by individuals as situations that weaken or are beyond their resources, work-related stressors impact the mental and physical health of workers and the quality and safety of care. Currently, many tools are used to assess caregiver stress in ICU, but do not consider the specificity of this work. The objective of this international and multicentric study was to develop a perceived stress scale specific to ICU.Patients and methods: Interviews were conducted with 166 caregivers (84 nurses and 81 physicians) in four countries (France, Italy, Spain, Canada). These interviews were recorded, transcribed and then a thematic analysis was carried out to identify stress factors. A first version of the scale was pre-tested with 70 caregivers (30 physicians and 40 nurses) in the same countries. Finally, we carried out qualitative and quantitative analyses select the most relevant items.Results: We identified 99 stressors specific to the ICU that were grouped into eight main themes: stress in relation to 1) the patient, 2) the task to be performed, 3) the institutional context, 4) the team, 5) the organization of the unit, 6) the personal dimensions, 7) the patient’s family, 8) the working conditions. Following the pre-test, 50 items were selected to constitute the PS-ICU scale.Conclusion: Our results highlight specific items related to vital risk/emergency management and ethically and morally problematic situations. These dimensions will be discussed and compared against existing scales (e.g., JCQ). The PS-ICU scale will allow to better identify and measure stressors in ICU. This scale will contribute to the development of targeted actions in terms of prevention, training and support for professionals. The creation of an internationally validated tool will make it possible to develop comparative studies on cultural and organizational factors.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.047 | 0.013 |
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".