The Effect of Training on Communication Skills of Nurses with Child through Small Groups Discussion
Bibliographic record
Abstract
Background: Communication is the key role in the nursing profession. Nurse-patient communication is highly important especially when the patient is a child. Studies indicate inappropriate contact with children in the pediatric wards. This study investigated effect of training on communication skills of nurse with child through small group discussion. Methods: This study is a clinical trial with pre-test and post-test, which was done on 60, nurses in Dr. Sheikh hospital in Mashhad. Nurses were randomly assigned into either intervention or control groups.Nurses' communication skills were measured using the tools of Calgary Cambridge communication skills assessment before and after the intervention. During one-day workshops, 6-hour training for communication skills with children was provided to nurses as small group discussion. Results: The results showed there was no significant difference between the two groups in terms of mean score of nurses' verbal and nonverbal communication skills before the intervention (verbal: p = 0.495, nonverbal: p = 0.307). However, after the intervention, the mean score of nurses in verbal and nonverbal communication skills in the case group was statistically significant and higher than those in the control group (p<0.001). Conclusions: Given weakness in the relationship between nurse and child at the bedside and since nurses do not receive essential instructions on specific skills related to children communication, it seems necessary to investigate the effect of implementing various educational practices on the nurses' communication skills.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".