Equitable formal care access: examining processes for Hispanic/Latino family dementia caregivers’ decision-making
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Although there are benefits to formal care, Hispanic/Latino family caregivers of people with dementia face multiple barriers to access. Moreover, the decision-making processes Hispanic/Latino family caregivers use when considering formal care are unclear. The present study examines how Hispanic/Latino family caregivers make formal care decisions, explores why they choose to use or avoid formal care, and identifies accessible methods of disseminating information about formal care options. RESEARCH DESIGN AND METHODS: We conducted virtual interviews with 14 Hispanic/Latino caregivers of people with dementia in the United States. These interviews were guided by the Ottawa Decision Support Framework, conducted in English and Spanish, and analyzed deductively using thematic analysis. RESULTS: Four main themes were identified: (1) reasons family caregivers may not choose formal care, (2) perceived benefits of formal care, (3) how family caregivers choose formal care, and (4) recommendations for delivering information about formal care options. Although Hispanic/Latino family caregivers recognize formal care provides respite and support, many prefer to use it when their caregiving responsibilities become overwhelming. Researchers also found that participants' ability to embrace Hispanic/Latino culture and Spanish proficiency were crucial. Participants expressed the importance of guidance from doctors and the efficiency of online methods in disseminating information. DISCUSSION AND IMPLICATIONS: This study provides a foundation for addressing ethnic disparities in access to formal care. It also lays crucial groundwork for the future development of decision-support interventions by examining decisional needs, identifying accessible methods for disseminating information, and centering the Hispanic/Latino experience.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".