O4‐08‐05: PRIORITIES AND CONCERNS OF OLDER AFRICAN AMERICANS LIVING ALONE WITH COGNITIVE IMPAIRMENT: AN IN‐DEPTH PERSPECTIVE
Bibliographic record
Abstract
Older African Americans are twice as likely as Whites to have cognitive impairment. In addition, one third of older adults with cognitive impairment live alone in the United States, but there is limited knowledge about the priorities and concerns of older African Americans living alone. This gap in knowledge is concerning considering that 28% of older African Americans live alone. To address this gap, we used qualitative methods to better understand, in depth, the lived experience of older African Americans with cognitive impairment living alone. Ethnographic interviews and participant observation were used to elicit priorities and concerns of older African Americans living alone with cognitive impairment. Inclusion criteria included living alone, ability to provide consent, and a medical diagnosis of Alzheimer's disease, dementia, or mild cognitive impairment or ≤24 in the Montreal Cognitive Assessment (MoCA). Participants were recruited through healthcare and community organizations in Northern California. Using a qualitative content analysis approach, interview transcripts and fieldnotes were analyzed to identify codes and themes for participants’ priorities and concerns. Twenty older adults (12 with a MoCA score ≤24, 6 with a diagnosis of MCI, 2 with a diagnosis of dementia) were interviewed an average of 4 times per person for a total of 79 interviews. With regard to priorities, three themes emerged: 1) Attending social activities (e.g., going to church, attending study groups, interacting with family members/friends); 2) Receiving better medical care (e.g., more invested primary care physicians, better care coordination), and; 3) Establishing social boundaries. With regard to concerns, four themes emerged: 1) Self-managing multiple chronic conditions (e.g., diabetes, heart disease); 2) Limited support from family members and friends; 3) Difficulty managing financial affairs (e.g., credit card debt, fraud, eviction), and; 4) Limited understanding of their cognitive impairment. Findings underscore the need for tailored services for African Americans living alone with cognitive impairment to receive better medical care, as well as support with their financial affairs and more information about their cognitive impairment while remaining engaged in their communities. Future research is needed to identify specific priorities and concerns related to race.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".