Mothers’ knowledge regarding peripheral intravenous catheter caring and complications among pediatric patients: A cross-sectional study
Bibliographic record
Abstract
Objective: Pediatric patients are considered at risk for Peripheral intravenous catheters (PIVCs) complications more than adults. This study aimed to assess the level of mothers’ knowledge of PIVC maintenance, caring, and complications among pediatric patients. It was also aimed to investigate the association between maintenance and complication knowledge of PIVC. Furthermore, demographic factors were investigated to assess associations on mothers’ knowledge of PIVC.Methods: The study adopted a cross-sectional design. This study was performed on a convenience sample of 193 mothers from a tertiary hospital in Jordan in 2020.Results: Mothers’ knowledge regarding complications was higher than their knowledge of maintenance and caring of PIVC. Mothers’ knowledge toward caring for PIVC was positively correlated with their knowledge about PIVC complications. Mothers’ age and the number of hospital admissions were found to be significantly associated with the level of maintenance and caring knowledge of PIVC but not with complication knowledge of PIVC. The higher the educational level of a mother the less prone she is to complications of PIVC in pediatric patients.Conclusions: It is recommended that health professionals working in pediatric engage mothers in educational sessions to improve maintenance, care, and to prevent complications of PIVC among pediatric patients.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".