Learning From Recruitment Challenges: Barriers to Diagnosis, Treatment, and Research Participation for Latinos With Symptoms of Alzheimer's Disease
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
This article discusses barriers to diagnosis and treatment of Alzheimer's disease (AD) and concomitantly to participation in AD research as elicited from 29 potential Latino participants who ultimately did not enroll in a study evaluating a caregiver intervention. Nearly half of all individuals contacting the researcher about the intervention study failed to meet criteria stipulating an existing AD diagnosis. Barriers to obtaining a diagnosis include lack of knowledge about AD, perceptions of memory loss as normal aging, and structural barriers to accessing care. A quarter of caregivers contacting the researcher felt too overwhelmed to participate. Many of these barriers have been previously identified as challenges to treatment, suggesting this is not just a methodological research problem, but inextricably tied to larger issues of AD knowledge and service accessibility. Engaging Latino communities equitably in the assessment of needs and the process of addressing them, thus ensuring the validity and applicability of the research and findings, is important both for increasing this group's participation in relevant studies and for addressing existing health disparities.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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