Caring for children with medical complexity: Homecare nurses’ point of view
Bibliographic record
Abstract
Objectives: Children with medical complexity (CMC) have intense care demands, dependence on medical technology, and rely on homecare nursing. This study aimed to understand home care nurses' (HCN) experiences caring for CMCs to optimize their home-based place of employment, improve HCN-patient relationships to enhance care and promote CMCs to remain at home with their families safely. Methods: Semi-structured interviews were conducted with 21 HCNs caring for CMC using medical technology. Interviews were analyzed using content analysis. Results: Two themes emerged: the unique experiences of a homecare nurse and interactions with patients and their families. Interviews revealed the role is rewarding, and HCNs developed meaningful connections with patients and their families. However, HCNs experienced several challenges in providing quality care. Conclusions: Understanding HCN's perspectives is critical to improving their experience in the role and enhancing care for their patients. These findings can inform the implementation of support needed to optimize the work experience for HCNs.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".