Reducing complexity of patient decision aids for community-based older adults with dementia and their caregivers: multiple case study of Decision Boxes
Bibliographic record
Abstract
OBJECTIVES: To identify patient decision aids' features to limit their complexity for older adults with dementia and their family caregivers. DESIGN: Mixed method, multiple case study within a user-centred design (UCD) approach. SETTING: Community-based healthcare in the province of Quebec in Canada. PARTICIPANTS: 23 older persons (aged 65+ years) with dementia and their 27 family caregivers. RESULTS: During three UCD evaluation-modification rounds, participants identified strengths and weaknesses of the patient decision aids' content and visual design that influenced their complexity. Weaknesses of content included a lack of understanding of the decision aids' purpose and target audience, missing information, irrelevant content and issues with terminology and sentence structure. Weaknesses of visual design included critics about the decision aids' general layout (density, length, navigation) and their lack of pictures. In response, the design team implemented a series of practical features and design strategies, comprising: a clear expression of the patient decision aids' purpose through simple text, picture and personal stories; systematic and frequent use of pictograms illustrating key points and helping structure patient decision aids' general layout; a glossary; removal of scientific references from the main document; personal stories to clarify more difficult concepts; a contact section to facilitate implementation of the selected option; GRADE ratings to convey the quality of the evidence; a values clarification exercise formatted as a checklist and presented at the beginning of the document to streamline navigation; involvement of a panel of patient/caregiver partners to guide expression of patient priorities; editing of the text to a sixth grade reading level; UCD process to optimise comprehensiveness and relevance of content and training of patients/caregivers in shared decision-making. CONCLUSIONS: The revised template for patient decision aids is designed to meet the needs of adults living with dementia and their caregivers better, which may translate into fewer evaluation-modification rounds.
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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 | 0.029 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".