Mitigating Moral Distress in Dementia Care: Implications for Leaders in the Residential Care Sector
Bibliographic record
Abstract
In 2012, the World Health Organization estimated that the number of people living with dementia worldwide was approximately 35.6 million; they projected a doubling of this number by 2030, and tripling by 2050. Although the majority of people living with a dementia live in the community, residential facility care by nursing providers is a common part of the dementia journey in most countries. Previously published research confirms that caring for people living with dementia in such facilities often creates moral distress for nursing care providers. In this paper, the authors share additional findings from a two-year, two-phase, mixed methods study of moral distress as experienced by nursing caregivers of residents with dementia in residential care settings in a Western Canadian province. The findings relate to strategies to reduce moral distress in this caregiving group, with a particular focus on the role of supportive and responsive leadership. Important implications for practice and for leadership in the residential care sector are presented.
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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 | 0.028 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".