Sindrome del burn-out: valutazione del rischio e prevenzione in un’equipe di infermieri e personale ausiliario operanti in Cure Palliative
Bibliographic record
Abstract
The burnout syndrome is a form of response to a chronic work-related distress. It affects people working in the so-called “helping professions”, in healthcare, and features a “multidimensional” etiopathogenesis. Its onset is characterised by the appearance of three psychological components, namely, emotional exhaustion, depersonalization and a reduced sense of personal accomplishment, associated with a constellation of psychosomatic and behavioural symptoms. The paper describes a screening project aimed at assessing the risk of burnout in a group of nurses and auxiliary staff working in a palliative care ward, examining the links with the personality trait of alexithymia and identifying any possible prevention criteria. The project employs the Maslach Burnout Inventory and Toronto Alexithymia Scale. Out of 83 group members, 79 (95%) participated in the study project, which revealed low levels of burnout – compared to the average Italian Normative Sample – and low levels of alexithymia as well. The risk of burnout appeared highest among the group members who were of Italian nationality, single, structured workers and dedicated to palliative care alone, among nurses and staff members with a medium-to-low self-assessment of their professional\nskills. There were no significant gender-based differences. The complex picture of the syndrome, therefore, involves cognitive and behavioural, emotional and subjective value-based aspects, as well as aspects relating to the work organization and environment, with respect to which the unanimously shared criteria for effective risk monitoring and prevention are provided.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".