More than just a task: intimate care delivery in the nursing home
Bibliographic record
Abstract
Purpose: Intimate care procedures, such as bathing and toileting, are often regarded as simple, humble tasks. However, the provision of such care transforms a very private, personal activity into a social process. Understanding this complex process and the psychological impact it has on those providing and receiving care is critical in order to mitigate potential distress. The purpose of this study to examine the experience of delivering and receiving intimate personal care in the NH.Methods: A focused ethnographic approach with participant observation, semi-structured interviews, focus groups and drop-in sessions, document review, and field notes. Data were analysed using constant comparative analysis.Results: Quality care in this context is predicated on the care provider recognition of the emotional impact of care delivery on the care recipient. Our analysis identified that the overarching theme, of providing quality person-centred intimate care, requires creating and maintaining a relational space that promotes integrity.Conclusions: The provision of intimate personal care consists of a complex interplay at the level of resident/care provider interaction (micro level); health care organization (meso level); and policy (macro level). Each of these levels interacts with and influences the other two. The components identified in our model may provide the basis from which to further examine resident experiences of quality intimate personal care.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".