Self-Perceived Preparedness Needs Among Caregivers of Veterans With and Without Dementia: An Exploratory Study Using Open-Ended Survey Data
Bibliographic record
Abstract
BACKGROUND: Caregivers' self-perceived preparedness for caregiving influences care recipients' and caregivers' emotional health, and care recipients' aging in place. Dementia's unique, long, and progressive nature compared to other age-related illnesses, along with associated behavioral symptoms and personality changes, may cause caregivers' preparedness to vary significantly from that of those caring for patients with other chronic conditions. OBJECTIVE: This study aimed to describe and compare specific domains and tasks in which family caregivers of veterans with and without dementia reported wanting to be better prepared. METHODS: Using the Veterans Affairs' HERO CARE (Home Excellence Resource Outcome Center to Advance, Redefine, and Evaluate Non-Institutional Care) Survey data, we analyzed caregivers' responses to one open-ended question: "Out of all the tasks that you help the veteran with, is there anything specific you would like to be better prepared for?" Response themes were deductively coded into 9 domains, and differences in reported domains between caregivers of care recipients with and without dementia were compared. RESULTS: A total of 732 caregivers were included: 301 (41.1%) caregivers of veterans with dementia and 431 (58.9%) without. Caregivers of veterans with and without dementia, respectively, were similar except in age, being spousal caregivers, working at least part-time, hours of care provision per week, and proportion with a high burden. Veterans with dementia, versus without, were older and had higher frailty and risk scores. Preparedness concerns among caregivers (N=732) included care coordination (n=164, 22.4%), emotional and social support (n=145, 19.8%), advance planning (n=116, 15.8%), nursing and health monitoring (n=94, 12.8%), personal care (n=65, 8.9%), mobility (n=79, 10.8%), household (n=58, 7.9%), caregiver self-care (n=36, 4.9%), and emergent situations (n=28, 3.8%). The commonest tasks caregivers expressed needs for included managing emotional and behavioral symptoms (n=74, 10.1%), recognizing and responding to significant changes in the veterans' condition (n=66, 9.0%), seeking medical information relevant to the veterans' needs (n=54, 7.4%), handling financial and legal matters (n=52, 7.1%), and advocating for services (n=49, 6.7%). Similar proportions of caregivers of veterans with and without dementia reported preparedness needs in all domains and tasks. CONCLUSIONS: The preparedness needs of caregivers of veterans with and without dementia were mostly similar in most domains and tasks. The commonest preparedness gaps were in the domains of care coordination, emotional and social support, and advance planning. The findings can inform interventions to prepare all caregivers to support aging in place.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".