Caring behaviors of male nurses: A descriptive qualitative study of patients' perspectives
Bibliographic record
Abstract
BACKGROUND: Caring is mostly considered a characteristic of women and men are considered hard-hearted. In the nursing profession, female nurses are considered more caring than male nurses which influence patients' views about the care provided by male nurses. There is limited knowledge about patients' beliefs and views about caring behaviors of male nurses. PURPOSE: To explore caring behaviors of male nurses from patients' perspectives. DESIGN: A descriptive qualitative study drawn from a larger convergent mixed methods study METHODS: Semi-structured interviews were conducted with a purposive sample of 15 patients from 14 medical surgical units of three private hospitals in Islamabad, Pakistan. Inductive thematic analysis was used for data analysis. FINDINGS: Patients reported that male nurses are respectful, considerate, good listener, unbiased, and supportive. CONCLUSION: These findings delineated five tangible caring behaviors that patients expect from the male nurses who care for them. It suggests that patients have specific expectations from their male nurses for providing effective nursing care. The male nurses can foster these behaviors to enhance their relationships with their patients.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".