The Nurse-Physician Relationship During the COVID-19 Pandemic in Shanghai, China: Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: The nurse-physician relationship is important for the stability of collaboration. The COVID-19 pandemic has put unprecedented pressure on the health care system and has placed greater demands on nurse-physician collaboration. Nurses and physicians often struggle to share mutual responsibility and communicate effectively. OBJECTIVE: This study aimed to evaluate the relationship between nurses and physicians during the COVID-19 pandemic and construct a new model combining the attitude and behaviors of the 2 groups to assess various factors' impacts on job satisfaction and confrontational behavior. METHODS: We conducted this quantitative cross-sectional study to assess the relationship between nurses and physicians based on the attitudes and behaviors toward nurse-physician collaboration. We first investigated the satisfaction of nurses and physicians with their relationship and how they thought the COVID-19 pandemic had affected that relationship. We used an adapted and modified Jefferson Scale of Attitudes Toward Physician-Nurse Collaboration questionnaire that consisted of 17 items under 5 dimensions. Structural equation modeling was used to assess the relationships between domains. Ordinal logistic regression was used to evaluate the relationship between different domains of the questionnaire and the satisfaction of the current nurse-physician relationship. RESULTS: We included a total of 176 nurses and 124 physicians in this study. Compared to 7.2% (9/124) of physicians, 22.7% (40/176) of nurses were dissatisfied with the current nurse-physician relationship. Most physicians (101/124, 81.5%) and nurses (131/176, 74.5%) agreed that the nurse-physician relationship had become better because of the COVID-19 pandemic and that the public had greater respect for them. However, significantly fewer nurses (59/176, 33.5% vs 79/124, 63.7%; P<.001) thought that physicians and nurses were treated with the same respect. Nurses scored significantly higher scores in caring versus curing (mean 16.27, SD 2.88 vs mean 17.43, SD 2.50; P<.001) and physician's authority (mean 8.72, SD 3.21 vs mean 7.24, SD 3.32; P<.001) subscales compared with physicians. The shared education and collaboration subscale had a significantly positive relationship with the nurse's autonomy subscale (standardized coefficient=0.98; P<.001). Logistic regression showed that 4 subscales (shared education and collaboration: P<.001; caring versus curing: P<.001; nurse's autonomy: P<.001; and confrontation: P=.01) were significantly associated with the level of satisfaction of the current nurse-physician relationship. CONCLUSIONS: This study showed that nurses were more dissatisfied with the current nurse-physician relationship than physicians in Shanghai. Policy makers and managers in the medical and educational system should emphasize an interprofessional collaboration between nurses and physicians. Positive attitudes toward shared collaboration and responsibility may help to improve the relationship between the 2 parties.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".