Burnout in health care providers working in the intensive care units of a tertiary care hospital, South India—a questionnaire-based survey
Bibliographic record
Abstract
BACKGROUND: The intensive care unit (ICU) is a special section of the hospital where intense monitoring and patient care are required. Health care providers (HCPs) who work in the ICU are exposed to a stressful environment and, in the long run, this may lead to exhaustion and burnout. It is observed that the burnout in HCPs in the ICU may have an impact on patient care and the psychological wellbeing of the caregiver. Thus, we aimed to assess the burnout in HCPs working in the ICUs of a tertiary care hospital in South India. METHODS: A single-center, questionnaire-based survey was carried out by HCPs who work in the ICUs of a tertiary care hospital in South India. A Google form link was created after obtaining approval from the Institutional Ethics Committee. The link was then circulated to the HCPs who work in the ICU and the responses were collected. The Google form fetched data related to demographics, profession, area of work, duration of work per day, total days of work in the ICU during the work period, and details of night duty. The Oldenburg burnout inventory questionnaire was used to measure burnout in the HCPs. RESULTS: A total of 60 HCPs with a mean age of 23.37±2.93 years, consented and filled out the online questionnaire. Of the 60 HCPs, 41 (68.33%) were females and 19 (31.67%) were males. Most of the participants were working in adult medical ICUs. The overall burnout level in all the participants was 2.39± 0.31, with the exhaustion level being 2.45±0.43 and the disengagement level being 2.32± 0.31. Between 70% and 80% of HCPs experienced high levels of burnout while working in the ICUs. Work area, work duration, sleep duration, and clinical experience had an impact on burnout levels of the HCPs. CONCLUSION: Most of the HCPs who work in the ICU experience high levels of burnout. Lack of clinical experience in the ICU and long work hours with lack of sleep can increase burnout in the HCPs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".