Use of medications in the Alzheimer's disease population : physician and caregiver perspectives
Bibliographic record
Abstract
Introduction. Research into medications for Alzheimer's disease (AD) is primarily conducted in drug trials, were efficacy is assessed by changes in score on established outcome measurement scales. However, physicians' and caregivers' perspectives on efficacy, along with their perspectives on other factors that may influence prescribing (e.g., adverse effects), remain largely unexplored. The objective of this thesis is to examine these perspectives to gain a broader understanding of the factors that can influence the use of medications in AD. Methods. Two studies were conducted. The first involved all of the Province of Quebec's geriatricians, neurologists, and psychogeriatricians, as well as a random sample of Quebec's 8,115 general practitioners. The second study involved 375 caregivers who attended AD-related support groups. Questionnaires were used to collect data on the proportion of patients prescribed cholinesterase inhibitors (ChEIs), efficacy requirements for prescribing new medications, acceptance of adverse effects, physician-caregivers discussions about medications, and caregiver pressure on physicians to prescribe medications. Results. Response rates were 35.4% (physicians) and 64.4% (caregivers). More stringent efficacy requirements on the part of physicians were negatively associated with prescribing ChEIs, although effect sizes were small and associations were not always statistically significant. More stringent efficacy requirements on the part of caregivers were negatively associated with prescribing in some instances (e.g., required improvements to patients' ability to eat, OR=0.74, 95% CI=0.61 to 0.89), but not in others (e.g., required improvements to patients' speech, OR=1.02, 95% CI=0.81 to 1.19). Caregivers' willingness to accept adverse effects was positively associated with prescribing ChEIs (odds ratios for 11 adverse effects ranged from 1.83 to 8.30); however, prescribing was not associated with physicians being the first to discuss the use of medications to treat AD (OR=2.37; 95% CI=0.90 to 6.24), nor was it associated with caregiver pressure on physicians to prescribe (OR=1.33; 95% CI=0.49 to 3.58). Conclusion. This research is the first to show how physician and caregiver perspectives on issues such as efficacy and safety can affect the use of medications in AD.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".