“I feel broken”: Chronicling burnout, mental health, and the limits of individual resilience in nursing
Bibliographic record
Abstract
Healthcare systems and health professionals are facing a litany of stressors that have been compounded by the pandemic, and consequently, this has further perpetuated suboptimal mental health and burnout in nursing. The purpose of this paper is to report select findings from a larger, national study exploring gendered experiences of mental health, leave of absence (LOA), and return to work from the perspectives of nurses and key stakeholders. Given the breadth of the data, this paper will focus exclusively on the qualitative results from 53 frontline Canadian nurses who were purposively recruited for their workplace insight. This paper focuses on the substantive theme of "Breaking Point," in which nurses articulated a multiplicity of stress points at the individual, organizational, and societal levels that amplified burnout and accelerated mental health LOA from the workplace. These findings exemplify the complexities that underlie nurses' mental health and burnout and highlight the urgent need for multipronged individual, organizational, and structural interventions. Robust and timely interventions are needed to restore the health of the nursing profession and sustain its future.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".