Understanding the transition to long-term care: Perceptions of family care partners of older adult Veterans
Bibliographic record
Abstract
Introduction: Veterans and their family care partners represent a unique demographic with specific needs that may differ from those of the general population. The transition to a long-term-care home (LTCH) has the potential to profoundly affect older adult Veterans and their care partners, yet research on how this move affects them is limited. This study explored the experiences and needs of older adult Veterans and their family care partners transitioning to a LTCH from the perspective of the care partner. Methods: A qualitative descriptive design was used for this project. One-time semi-structured interviews were conducted with nine family care partners of older adult Veterans living in LTCHs across Canada. Coding and thematic analysis were used to iteratively categorize and synthesize the data. Results: The analysis revealed three overarching themes with the following sub-themes: 1) information gaps and knowledge use, 2) feeling valued, recognized, and supported, and 3) the health and well-being of the Veteran and family care partner. These sub-themes were seen throughout all stages of the move to a LTCH, including the pre-, during-, and post-transition stages, and served to either impede or assist in a positive transition. Discussion: The results of this study will lead to an increased awareness of the specific challenges and facilitators faced by care partners and Veterans transitioning to a LTCH, ultimately leading to recommended changes in how they are supported throughout this move.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 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".