Burnout Syndrome in Psychiatrists in Slovakia: A National Survey
Bibliographic record
Abstract
No study that would deal with the prevalence of burnout syndrome in psychiatrists has been carried out in Slovakia to date, even though it is a high-risk profession. We have therefore investigated the symptoms of burnout in physicians within all Slovak psychiatric workplaces, in relation to individual differences. The participants filled in the Maslach Burnout Inventory and the Questionnaire for Identification of Stress Level and Burnout Syndrome. We aimed to detect their levels of emotional exhaustion, depersonalization, and personal accomplishment as well as physical, psychological, emotional, and social symptoms of work-related stress and burnout. The remaining items of our interest concerned the participants’ age, length of practice, gender, provision of the institutional emergency care, and type of workplace. Over one third of Slovak psychiatrists expressed a low degree of personal accomplishment, one quarter reported a high level of depersonalization and nearly one half suffered a high level of emotional exhaustion. Not only the levels of emotional and physical symptoms, but also the overall level of burnout, were significantly higher in female psychiatrists. More experienced psychiatrists as well as those who do not provide the institutional emergency care expressed higher levels of personal accomplishment. To address the issues revealed both in our study and the previous research we recommend implementation of measures focused on the support of mental health of healthcare workers across the whole society. In addition, more attention is needed to the active use of preventive measures at all psychiatric workplaces by both the employers and the psychiatrists themselves.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".