Usefulness and acceptability of an animation to raise awareness to grief experienced by carers of individuals with dementia
Bibliographic record
Abstract
AIM: Many carers of individuals with dementia experience high levels of grief before and after the death of the person with dementia. This study aimed to determine the usefulness, acceptability, and relevance of an animation developed to raise awareness to grief experienced by carers of people with dementia. METHODS: This research had a cross-sectional survey design. We contacted carers of people with dementia over the phone or email. Participants evaluated the animation through an online or paper-based survey. We used descriptive statistics and analysed qualitative data using thematic analysis. We required a sample of 40 carers to adequately power the study with a target of 75% of carers finding the animation useful, acceptable, and relevant. RESULTS: 31/78 carers approached evaluated the animation. Ninety-four percent of participants found the animation relevant to their situation, meeting our target. However, we fell short of this target for usefulness (68%) and acceptability (73%). The qualitative responses suggested that participants felt the animation could help improve the understanding of grief among carers, family, friends, and healthcare professionals. Carers also shared that the animation would be most useful for carers of newly diagnosed people with dementia. CONCLUSION: Most carers of people with dementia in this study reported that the animation was useful, acceptable, and relevant. Dissemination of the resource may be useful for the majority of carers, with the caveat that a few carers may find it distressing and need to be referred for further support.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".