Moving and Handling Children After Death: An Inductive Thematic Analysis of the Factors That Influence Decision Making by Children's Hospice Staff
Bibliographic record
Abstract
Hospices for children and adolescents in the United Kingdom provide care to the bodies of deceased children in specially designed chilled bedrooms called “cool rooms.” In an effort to develop resources to support hospice practitioners to provide this specialist area of care, this study aimed to identify the factors that influence decision making when moving and handling children's bodies after death in a hospice cool bedroom. An internet-based survey was sent to all practitioners employed by 1 children's hospice. A total of 94.9% of eligible staff responded (n = 56). An inductive approach to thematic analysis was undertaken, using a 6-phase methodological framework. Three core themes were identified that inform practitioners' perception of the appropriateness of moving and handling decisions: care of the body, stages of care, and method of handling. The complexity of decision making and variation in practice was identified. Practitioners relied on both analytical and initiative decision making, with more experienced practitioners using an intuitive approach. Evidence-based policy and training influence the perception of appropriateness and the decisions and behavior of practitioners. The development of a policy and education framework would support practitioners in caring for children's bodies after death, standardizing expectations and measures of competence in relation to moving and handling tasks.
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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 | 0.038 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".