Staff Nurse Utilization of Kangaroo Care as an Intervention for Procedural Pain in Preterm Infants
Bibliographic record
Abstract
BACKGROUND: Skin-to-skin contact between mother and infant, commonly referred to as Kangaroo Care (KC), has demonstrated efficacy as a pain-relieving strategy for infants, yet, it remains underutilized in clinical practice. PURPOSE: To evaluate changes in neonatal intensive care unit staff nurse beliefs, utilization, and challenges related to practice change in implementing KC as an intervention for management of procedural pain in preterm infants between 2 time points. METHODS: Nurses who participated in a larger clinical trial examining the sustained efficacy of KC were asked to complete a questionnaire at 2 time points: 1- and 6 month(s) following study initiation. Identified benefits, expectations, frequency of use, and challenges related to practice change uptake were described using frequencies and percentages. Data from the 2 different time points were compared using χ analysis. RESULTS: Of the 40 nurses approached, all completed the questionnaire (19 at the 1-month and 21 at the 6-month time point). Of the sample (n = 40), 97% of participants indicated that they expected KC to provide good pain relief or better. Staff nurses reported significantly improved preconceived ideas (χ = 22.68, P < .01) and significantly fewer concerns (χ = 22.10, P = .01) related to using KC as a pain-relieving intervention between the 2 time points. No significant differences were seen in the frequency of using KC as an intervention between time points. IMPLICATIONS FOR RESEARCH AND PRACTICE: Despite increasingly positive preconceived ideas and reduced concerns, the frequency of using KC for procedural pain relief remained unchanged. Further research addressing ways to overcome barriers to utilizing KC as an intervention for procedural pain is warranted.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".