Neonatal intensive care nurses’ knowledge and beliefs regarding kangaroo care in China: a national survey
Bibliographic record
Abstract
OBJECTIVE: Kangaroo care (KC), a well-established parent-based intervention in neonatal intensive care units (NICUs), with documented benefits for infants and their parents. However, in China there remains a lack of knowledge and a reluctance to implement KC in hospitals. Therefore, our aim was to investigate the current knowledge, beliefs and practices regarding KC among NICU nurses in China using the 'Kangaroo Care Questionnaire'. METHODS: A quantitative descriptive survey was designed. This questionnaire comprised 90 items classified according to four domains: knowledge, practice, barriers and perception. Data were analysed using SPSS V.20.0, and content analysis was used to summarise data derived from open-ended questions. RESULTS: The survey involved 861 neonatal nurses from maternity and general hospitals across China (response rate=95.7%). The findings showed that 47.7% (n=411) of the nurses had participated in the implementation of KC. Neonatal nurses in the 'experienced in KC' group showed an overall better understanding of KC and its benefits with a higher 'correct response' rate than those in the 'not experienced in KC' group. In the 'experienced in KC' group, over 90% considered KC beneficial to the parent-baby relationship and attachment, and over 80% believed that KC positively affected outcomes of preterm infants. The 'not experienced in KC' group perceived more barriers to KC implementation than did the 'experienced in KC' group. CONCLUSION: Although most nurses working in NICUs in China were aware of the benefits of KC, there remain substantial barriers to its routine use in practice. Education for both staff and parents is necessary, as is the provision of appropriate facilities and policies to support parents in providing this evidence-based intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".