Moving From Moral Distress to Moral Resilience Using Acceptance and Commitment Therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Moral distress (MD) is a problematic experience for healthcare workers, with career engagement implications including burnout, job turnover, and career turnover. Instances of MD have been increasing since the start of the COVID-19 pandemic, threatening greater problems for the healthcare system. Although a range of interventions have been explored, no evidence-based treatment has been identified. Because of how embedded ethical decision-making is in the healthcare field, it is unlikely that MD will be eradicated; however, it is suggested that MD can be learned from and transformed into moral resilience. Evidence indicates that healthcare workers could benefit from mindfulness-based and emotion regulation skills, alongside values-based and action strategies, to support the development of moral resilience. This article proposes the applicability of Acceptance and Commitment Therapy (ACT) and its six core skills—acceptance, cognitive defusion, mindfulness, self-as-context, values, and commitment—to the work of career practitioners as a means of developing moral resilience skills among healthcare workers and supporting career sustainability.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it