Nationwide Cross‐Sectional Online Survey of Australian Clinicians' Pain Management Practices for Newborns During Heel Lance Procedures
Bibliographic record
Abstract
ABSTRACT The analgesic effects of breastfeeding (BF), skin‐to‐skin care (SSC), and oral sucrose/glucose for neonates during painful procedures are well‐established. Although parents report wanting to comfort their babies during painful procedures, use of these strategies is inconsistent. This study investigated clinicians' support/use of BF, SSC and sucrose during newborn heel lance in Australia and perceptions of a clinician‐targeted video demonstrating how to perform heel lance while newborns were BF/SSC. A cross‐sectional online survey was conducted. Snowball sampling and distribution via partner organizations were used. Descriptive statistics and content analysis were used for quantitative and qualitative data, respectively. Respondents included 729 nurses, midwives, and phlebotomists, caring for healthy newborns (39%, n = 283); sick newborns (41% n = 300) and both sick and healthy newborns (20%, n = 146). Most respondents caring for healthy newborns were “very likely” to support BF (80%, n = 199) and SSC (65%, n = 162). Most (89%, n = 237) caring for sick newborns were “very likely” to use sucrose; one third “very likely” to support mothers to BF (29%, n = 78) and 32% (n = 85) to use SSC. Barriers to BF and SSC included parents being absent and critically ill newborns. Most considered the video applicable (81%, n = 488) and likely to increase BF or SSC (84%, n = 502). Analysis from comment data identified two categories: “healthcare context and practice” and “parent and baby.” The key findings that clinicians reported the video to be highly useful and that BF and SSC during heel lance for healthy newborns was high confirm that further research is needed to examine parents' use of BF and SSC during painful procedures.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".