Een ‘mixed-methods’ evaluatie-onderzoek naar voorkeuren van naasten en zorgprofessionals voor een handreiking over levenseindezorg bij dementie
Bibliographic record
Abstract
A booklet was developed in Canada in 2005 to inform family caregivers of people with dementia about end-of-life care. A Dutch version was published in 2011 after evaluation and revision. Developments in research and society call for a second revision. The aim of this study was to map out users' (family caregivers and healthcare professionals) preferences regarding the look and feel, and content of the booklet. To this end, in addition to the current paper booklet, we created a prototype website and app, along with three illustration options. Twenty-one family caregivers and nineteen healthcare professionals completed a questionnaire about their preferences. Open ended questions were analyzed using content analysis, multiple-choice questions using descriptive analysis. The participants valued the question-answer format. They perceived the text as too medically oriented and they expressed a need for more inclusive language and broader information. The participants found images of people suitable for the booklet and they preferred the illustrations to be less focused on the medical context. The participants preferred the paper booklet and a website. By understanding family caregivers' and healthcare professionals' preferences, in the second revision, the booklet can be tailored to the user. It is expected that this tailoring will support informing family caregivers about end-of-life care.
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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 | 0.146 | 0.121 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".