Nurses’ views of factors affecting sleep for hospitalized children and their families: A focus group study
Bibliographic record
Abstract
Light, noise, and interruptions from hospital staff lead to frequent awakenings and detrimental changes to sleep quantity and quality for children who are hospitalized and their parents who stay with them overnight. An understanding of nurses' views on how care affects sleep for the hospitalized child and parent is crucial to the development of strategies to decrease sleep disturbance in hospital. The purpose of this descriptive qualitative study was to gain an understanding of nurses' views on their role in and influence on sleep for families; perceived barriers and facilitators of patient and parent sleep at night; strategies nurses use to preserve sleep; the distribution, between parent and nurse, of care for the child at night; views of the parent as a recipient of nursing care at night; and the nature of interactions between nurses and families at night. Thirty registered nurses from general pediatric and critical care units participated in one of four semi-structured focus groups. Four main influences on sleep were identified: child factors; environmental factors; nurse-parent interaction factors; and nursing care factors. Some of these restricted nurses' ability to optimize sleep, but many factors were amenable to intervention. Balancing strategies to preserve sleep with the provision of nursing assessment and intervention was challenging and complicated by the difficult nature of work outside of usual waking hours. Nurses highlighted the need for formal policy and mentoring related to provision of nursing care at night in pediatric settings.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".