‘Talking about my experiences … at times disturbing yet positive’: Producing narratives with people living with dementia
Bibliographic record
Abstract
BACKGROUND: This research investigated narrative production and use with families living with dementia. We hypothesised that the process of narrative production would be beneficial to people with dementia and carers, and would elicit important learning for health and social care professionals. METHOD: Through third sector partners, we recruited community-dwelling people with dementia and carers who consented to develop written, audiotaped or videotaped narratives. Audio-taped narratives were transcribed verbatim and handwritten narratives word-processed. After checking by participants, completed narratives were analysed thematically using qualitative data analysis computer software. A summary of the analysis was circulated to participants, inviting feedback: the analysis was then reviewed. A feedback questionnaire was subsequently circulated to participants, and responses were analysed thematically. RESULTS: Twenty-one carers and 20 people with dementia participated in the project. Four themes of support were identified: 'relationships', 'services', 'prior experience of coping' and having an 'explanation for the dementia'. Three themes were identified as possible additional stresses: 'emotions', 'physical health' and 'identity'. We suggest a model incorporating all these themes, which appeared to contribute to three further themes; 'experience of dementia', 'approaches to coping' and 'looking to the future'. In participant feedback, the main themes identified were 'emotions', 'putting things in perspective', 'sharing or not sharing the narrative' and 'actions resulting'. CONCLUSIONS: Producing a narrative is a valuable and engaging experience for people with dementia and carers, and is likely to contribute to the quality of dementia care. Further research is needed to establish how narrative production could be incorporated into routine practice.
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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 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".