P107 Cultural differences in care for parents with a neurodegenerative disorder
Bibliographic record
Abstract
Abstract Introduction This study investigated differences in opinions about neurodegenerative disorders (NDD) in countries with large populations and expanded access to healthcare. Methods A 5-point Likert scale survey assessed opinions of 30–59-year-olds, pertaining to their parents and NDD conditions. 100 surveys, translated into native languages, were acquired in eight developed countries. Positive (somewhat- or strongly-agree) vs. other responses, sex, and country were submitted to logistic regression and Chi-squared analyses. Results “It is important for me to know if my parent has a risk for developing a NDD condition in the future, even if nothing can be currently done to prevent or cure those diseases” had higher positive responses in Australia (92%) compared to Germany (74%) and the USA (78%). “I believe that knowing about my parent’s risk for developing a NDD condition will help me assist in the planning of their future” had higher number of positive responses in Australia (91%) versus Japan (70%), Germany (76%), Italy (80%) and UK (80%). “If my parent(s) was found to be at risk for a NDD condition, I would want to learn more about medications and adaptive therapies that could delay onset” was responded to more positively in Australia (92%), Canada (78%), France (87%), Germany (78%), Italy (88%), UK (88%), and USA (81%) versus Japan (60%). Conclusions Australians responded more positively to questions related to care of a parent with a NDD disorder. These findings suggest cultural differences that could influence education and support systems requirements for sleep medicine providers and NDD patients.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".