Exploring perceptions of online calculators for identifying community-dwelling older people at risk of dying: A qualitative study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objectives: This study aimed to assess the acceptability, value, and perceived barriers of using electronic risk calculators for predicting and communicating the risk of death in community-dwelling older adults. Methods: One focus group and eight interviews were conducted with 16 participants with experience caring for patients or family members at end of life. A prototype mortality risk tool was used to anchor discussions. Data were analysed using a qualitative content analysis approach. Results: Five themes emerged: acceptability, communication, barriers to use, broadening the circle of care, and tool limitations. Participants found the tool helpful for preparation, planning, and providing care, but disagreed on its community availability. Personalized risk estimates were valued for facilitating early goals of care conversations and normalizing discussions about death. However, concerns were raised about the tool's interpretation for individuals with different language, cultural, or educational backgrounds. Conclusions: While electronic risk calculators were found to be acceptable, balancing autonomy with varying preferences for receiving the information and potential need for support is crucial. Innovation: Providing patient-oriented life-expectancy estimates can enhance decisional capacity and facilitate shared decision-making between patients, their families, and healthcare professionals. Further research is needed to explore effective communication of personalized risk tools and additional benefits, harms, and barriers to implementation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it