Burnout in Anesthesiology and Resuscitation
Bibliographic record
Abstract
Background . The term “burnout” was originally developed by the psychologist Herbert Freudenberg (Germany, USA) in the seventies of the last century. Then another psychologist, Christina Maslach was a co-author of the Maslach Burnout Inventory, which was adapted to different professions and translated into different languages. According to Russian scientist professor Victor V Boyko “the emotional burnout is a form of professional distortion of an individual ...”. Anesthesiology and resuscitation are certainly among the most stressful medical disciplines, daily exposing doctors to high responsibility associated with life-threatening scenarios of patients. Therefore, burnout detection is important because it is related to the safety and quality of medical care, as well as to the life and health of intensive care specialists. Aim of study Anonymous, blind observational study of the frequency and dynamics of burnout, depression, situational and personal anxiety of anesthesiologists and resuscitation doctors and nurses of anesthesiology and intensive care departments. Material and methods. The study included 64 specialists of anesthesiology and intensive care departments (41 doctors and 23 nurses). Maslach Burnout Inventory (MBI) for Medical Personnel, Purpose in life test (Crumbaugh & Maholick, 1964), “Burnout” questionnaire of V. V. Boyko, Toronto Alexithymia Scale (TAS), Spielberger State-Trait Anxiety Inventory (STAI) in the adaptation by Y L. Khanin, Assessment of depression (HADS), and a series of general questions (gender, age, profession, working experience, marital status, number of working hours per week, how much do I love my job, how much I would like to love my job, somatic complaints, etc.). Results. According to MBI, 65.9% of examined doctors and 43.5% of nurses have high rates of certain burnout, which confirms the relevance of the studied problem. Of these, 12.19% of doctors and 8.7% of nurses have high rates of all three sub-scales of burnout syndrome. Depression, personal and situational anxiety have a positive correlation with burnout. Conclusion. According to the literature, burnout leads to a steady decrease in work productivity, destructive behavior, emergence of a variety of psychosomatic disorders, and a sense of meaninglessness of existence, despair, suicidal thoughts and committed suicides at the final stage of burnout. It is necessary to conduct regular testing of intensive care specialists to detect burnout, depression and anxiety. When the burnout is identified, it is necessary to perform psychological interventions.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".