When a child says ‘no’: experiences of nurses working with children having invasive procedures
Bibliographic record
Abstract
UNLABELLED: Experiencing invasive medical procedures can be a devastating experience for some children and their parents. The potential impact on staff who perform the procedure and who may have to restrain the child who is unwilling to have an essential procedure is a neglected area of research. Children's distress and their coping are affected by those around them so it is important to understand how nurses react in these situations. AIM: To explore the experiences of nursing staff involved in facilitating invasive procedures for children who do not want them. METHOD: Participants were selected at random from staff lists of one hospital in the West Midlands. Data collection was undertaken using unstructured qualitative interviews with ten paediatric nurses and in two focus groups. Theories generated from each interview were tested and validated with participants in subsequent interviews and then in the focus groups. FINDINGS: The most common experiences reported by the participants were 'getting upset' and 'getting stressed' by some aspect of the medical procedure, either because the child or parents became upset or the procedure had gone wrong in some way. Procedural protocols that exist to protect children, for example, by limiting the number of unsuccessful attempts to undertake the procedure, also protect staff by providing a framework to manage emotions during the procedure. Being able to explain the process and need for the procedure to the child and parents, obtaining consent where possible for the use of certain techniques, such as restraint, and having the time to adequately prepare a child for a procedure, all helped minimise the likelihood of an unsuccessful procedure, thereby reducing the risk of the nurse being emotionally affected by a distressed child. CONCLUSION: Nurses working with children who are unwilling to undergo invasive procedures experience negative emotions but these are short lived due to a combination of protective factors and coping strategies. Further research is needed to understand the experiences of medical staff and of nurses working outside paediatric environments who may not experience the same support and protection as those in paediatric 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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".