Family caregivers’ perspectives on their interaction and relationship with people living with dementia in a nursing home: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Social interactions are important for people living with dementia in a nursing home. However, not much is known about interactions and relationships between residents and family caregivers and related experiences of family caregivers. We aim to advance the knowledge on how family caregivers interact with people living with dementia in a nursing home and how they maintain or redesign a meaningful connection. METHODS: Qualitative research using interviews with family caregivers (n = 31) to explore perspectives on their interaction and relationship with the person living with dementia. Interviews were held during the reopening of nursing homes after the first COVID-19 lockdown in the Netherlands. In this situation, family caregivers became more aware of their interaction and relationship with the resident, which provided a unique opportunity to reflect on this. The interviews explored the interaction and relationship in a broad sense, not specifically for the COVID-19 situation. Thematic analysis was performed to analyze the data. RESULTS: We were able to identify three key themes reflecting the experiences of family caregivers: (1) changes in the interaction and relationship, (2) strategies to promote connection, and (3) appreciation of the interaction and relationship. From the viewpoint of family caregivers, the interaction and relationship are important for both the resident living with dementia and for themselves, and family caregivers have different strategies for establishing a meaningful connection. Nevertheless, some appear to experience difficulties with constructing such a connection with the resident. CONCLUSIONS: Our results provide a basis for supporting family caregivers in perceiving and establishing mutuality and reciprocity so that they can experience togetherness.
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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".