Barriers to Nurse-Patient Communication in Cardiac Surgery Wards: A Qualitative Study
Bibliographic record
Abstract
BACKGROUND: An appropriate and effective nurse-patient communication is of the most important aspect of caring. The formation and continuation of such a relationship depends on various factors such as the conditions and context of communication and a mutual understanding between the two. A review of the literature shows that little research is carried out on identification of such barriers in hospital wards between the patients and the healthcare staff. OBJECTIVES: The present study was therefore conducted to explore the experiences of nurses and patients on communication barriers in hospital cardiac surgery wards. DESIGN AND METHODS: This qualitative research was carried out using a content analysis method (Graneheim & Lundman, 2004). The participants were selected by a purposeful sampling and consist of 10 nurses and 11 patients from the cardiac surgery wards of three teaching hospitals in Tehran, Iran. Data was gathered by unstructured interviews. All interviews were audio-taped and transcribed verbatim. RESULTS: Findings were emerged in three main themes including job dissatisfaction (with the sub-themes of workload tension and decreased motivation), routine-centered care (with the sub-themes of habitual interventions, routinized and technical interventions, and objective supervision), and distrust in competency of nurses (with the sub-themes of cultural contrast, less responsible nurses, and their apathy towards the patients). CONCLUSION: Compared to other studies, our findings identified different types of communication barriers depending on the nursing settings. These findings can be used by the ward clinical nursing managers at cardiac surgery wards to improve the quality of nursing care.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".