A Narrative Care approach for persons living with dementia in institutional care settings
Bibliographic record
Abstract
AIMS AND OBJECTIVES: We will provide insights in the theoretical background and key concepts of a Narrative Care approach, such as narrative cultures, narrative curiosity, narrative co-composition and narrative reflective practice. BACKGROUND: Care understood as narrative practice underscores the importance of experiences and how these shape identities. Important to the quality of care in institutional care settings is the ability of care providers to cope with complexities and uncertainties in older adults' stories, which can be realised by attending to ways that foster and co-compose evolving and forward-looking narratives. Recognising these ongoing co-compositions means that persons living in institutional care settings and care providers live, tell, retell and relive their experiences. A change in the current institutional culture is necessary to implement care as narrative practice. To support such a change, approaches are needed that foster a focus on experiences and relationships and make relational ethics central to care. METHODS: The proposed Narrative Care approach is the result of an iterative development process involving a literature review, interviews with, and observations of, care providers, dialogues with an advisory committee, and consultation with experts. MAIN CONTRIBUTIONS: The proposed Narrative Care approach aims to help care providers (a) to recognise the importance of curiosity in a person's verbal and embodied narratives-especially for those living with dementia; (b) to take note of individual experiences in all of their complexity and uncertainty; (c) to respect these narratives; (d) to open up spaces to co-compose new narratives; and (e) to allow care providers to engage in narrative reflective practices that shape who they are and are becoming. CONCLUSION: The introduced approach responds to the need of implementing strategies to think and work narratively in institutional care settings. IMPLICATIONS FOR PRACTICE: Narrative Care has the potential to reshape task-oriented, technical notions of care. Concepts such as embodied narratives, relational ethics, narrative co-composition and narrative reflective practice must be integrated in the education of all care providers.
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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 | 0.022 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".