Older Latinos’ Perceptions of the Caregiving Experience
Bibliographic record
Abstract
Abstract There has been a rapid growth of Latinos age 65 and older in the United States and the population is projected to grow to 21.5 million by 2060. Latinos with Alzheimer’s disease is expected to increase 832% by 2060. Caregiving for adults with Alzheimer’s Disease and Related Dementias (ADRD) is physically, emotionally, and financially demanding, and has significant implications for caregivers’ health, personal and social life, and overall well-being. This study aimed to describe the perceived experiences of middle-aged and older Latino who were primary caregivers of relatives with ADRD. We conducted semi-structured interviews with Latino caregivers to examine their perceived experiences of providing care for a relative with ADRD. Interviews were conducted in English and Spanish and were transcribed, translated into English when needed, and coded. We conducted direct content analysis. Participants were aged 50 to 75 years (n = 16), the majority were female (n = 12), and majority were caring for either their parent or spouse. We identified six reoccurring themes in the Latino caregiving experiences: (1) caregiver burden; (2) dealing with care recipient; (3) coping strategies; (4) social support; (5) cultural values; and (6) knowledge about services. The identified themes showed that Latino caregivers need support from their family and friends for caregiving. Latino family’s structure plays an important role in caregiving experience. These themes are important to consider in future interventions that aim to reduce caregiver burden in Latinos as they influence the overall well-being of the caregiver.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 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".