Exploring How Organizations Can Support Psychological Self-care and Protect its Workers From Moral Distress
Bibliographic record
Abstract
Context: While health-care workers (HCW) spend their working hours caring for others, many are challenged to find the time and energy for self-care and suffer because of it. Objective: To examine facilitators and barriers facing organizations to a) support health-care workers psychological self-care and b) protect them from moral distress. Study Design and Analysis: Key informants were identified through scholarly and grey literature reviews and snowball recruitment. Potential informants were invited to participate in a one-hour, semi-structured interview. Interviews were audio recorded, transcribed verbatim and analyzed using a thematic approach in NVivo 12. Setting: Interviews were conducted between November 2021 and February 2022 with HCW from multiple disciplines and health-care sectors across Canada. Population Studied: Anyone who self-identified as working in the health-care field, including front line workers and administrators. Instrument: An interview guide was developed for this study informed by the literature review. Outcome Measures: Facilitators and barriers to a) supporting psychological self-care and, b) protection from moral distress at the individual, team, and organizational levels. Results: A total of 29 interviews were completed with 30 participants. Facilitators to supporting psychological self-care included prioritizing self-care and utilization of available resources, positive peer relationships, and supportive leadership, policies, and guidelines. Barriers included hesitancy among HCW to identify themselves as feeling burnt out, an existing unsupportive culture as well as management who were unable to relate to their workers. HCW identified several facilitators to protection from moral distress, including a feeling that their work was making a difference, open communication within teams, and supportive resources such as a wellness team. In contrast, some HCW felt that moral distress was not well understood, and that an unhealthy culture of overwork coupled with a lack of resources were key barriers to protection. Conclusions: In this exploration of psychological health and safety in health-care workplaces across Canada we uncovered a multitude of opportunities for improvement. Participants not only spoke of their challenges to supporting psychological self-care and being able to protect themselves from moral distress but offered many suggestions that organizational leaders can implement in the short-term and longer-term.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".