An Ontological, Anthropological, and Psychoanalytic Perspective on Physician Burnout
Bibliographic record
Abstract
Post-industrialization, societies have evolved with profound changes in ways of life. However, it was not until just recently that the overall impact of its deleterious and pernicious effects has been widely recognized, studied, and accepted. In the last few years, increased rates of stress and burnout (BO) not only affect clinicians, personally, but health care systems across the nation. The understanding of BO in the realm of current nosological limitations lacks context and is often unrecognized given the stigma associated with mental illness. However, the emerging data regarding this syndrome is highly concerning. Its impact on professionals and leaders across various disciplines is puzzling and underscores the nature and extent of the problem. A search of PubMed, PsycINFO, Cochrane Library, and Google Scholar was conducted from the date of inception until June 2022 using the keywords Burnout", "Mental Health"," Physicians", "Addiction", "Health Care Workers", "Anthropology", "Psychopathology", Philosophy", "Wellness". The search resulted in the identification of 135 articles; 56 articles met the inclusion criteria for the review. Post-pandemic BO has reached distressing levels. BO remains poorly understood highly complex and has multifactorial etiology which is now included in the 11th Revision of the International Classification of Diseases (ICD-11) as an occupational phenomenon. Besides being linked with known factors such as long work hours, administrative burdens, and a lack of control over one's work environment there are many confounders. It is a serious issue that can have negative consequences for both the physician and the patient, and therefore mitigation strategies are needed. The awareness of these unmanifested conflicts, mindfulness training, limiting addictive habits, and efforts toward wellness may provide some alternative solutions. Lastly, developing a coherent philosophy may be useful for distress tolerance, dealing with ambiguity related to the profession, and paving the way to a more meaningful life.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".