Men’s s Health in Nursing Practice: A Survey of Senior Nurses
Bibliographic record
Abstract
Background: Australian men are likelier to die younger than women, often from preventable diseases or conditions. Gendered health promotion has improved men’s engagement with health services, with nurses playing a central role in information and healthcare design. The primary aim of this research was to survey senior clinical and executive nurses on their understanding and perception of men’s health. Methods: A cross-sectional quantitative online survey was attended by senior nurses within a single hospital setting in metropolitan Sydney between June 2022 and July 2022. Sampling selection was conducted of nurses who currently hold senior clinical or management roles within the health district (Nurse Manager, Nurse Unit Manager, Director of Nursing, Nurse Practitioner, Transitional Nurse Practitioner, Clinical Nurse Consultant, Clinical Nurse Specialist, Nurse Educator, Clinical Nurse Educator) with descriptive analysis applied to interpret the data sets. Results: A total of 84 responses were received, representing a 33% survey participation rate. A key finding was that 89.1% of senior nurses believed that traditional masculine traits affected health-seeking behaviour. However, 60.2% had not discussed men’s-specific agencies with male patients, and 33.7% of senior nurses believed that gender was not a determinant of health. There was strong endorsement (74.6%) for a men’s health education program to be developed specifically for nurses. Conclusion: The results of this single-site online survey of senior nurses illustrate that while foundational understandings of gender as a determinant of health were divided, there remained strong endorsement for targeted men’s health promotion to patients and the development of men’s health educational programs to support nurses in providing holistic care for their male 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 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 | 0.005 | 0.000 |
| 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 | 0.001 |
| 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".