Development and Validation of a Nomogram for Predicting Presenteeism Risk Among Oncology Nurses: A Cross-sectional Study
This cross-sectional study developed and validated a highly accurate nomogram incorporating eight key predictors to effectively identify oncology nurses at high risk of presenteeism, providing nursing managers with a practical tool for early intervention and improved workforce well-being.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
In the quiet corners of hospitals, a silent struggle often plays out that has nothing to do with the visible chaos of an emergency room. It is the struggle of the employee who shows up to work but cannot fully function, a phenomenon known as presenteeism. Unlike missing work, which is easy to count and manage, presenteeism is invisible. It happens when a nurse, perhaps battling exhaustion, illness, or emotional burnout, stands at their post but their mind and body are not operating at full capacity. This state is particularly dangerous in oncology, the branch of medicine dedicated to caring for people with cancer. Here, the emotional weight is immense, the treatments are complex, and the need for precise, compassionate attention is absolute. When a nurse is physically present but mentally or physically diminished, the risk of error rises, and the quality of care for vulnerable patients can slip. For years, researchers have known that this is a problem, but they have lacked a practical way to spot who is most at risk before the damage is done.
A team of researchers set out to build a tool that could change this dynamic, focusing specifically on the nurses who care for cancer patients. They wanted to move beyond simply counting how many nurses were struggling and instead create a way to predict which individuals were most likely to be suffering from this hidden burden. By looking at a wide range of factors—from how long a nurse had been working to their financial situation, their emotional resilience, and the support they felt from friends and family—the team aimed to construct a clear picture of risk. Their goal was not just to understand the problem, but to provide hospital managers with a straightforward method to identify vulnerable staff early, allowing for timely help before a nurse's health or a patient's safety was compromised.
To achieve this, the researchers gathered data from 458 oncology nurses working in eight different hospitals across Sichuan province in China. Between May and September 2025, these nurses filled out detailed surveys about their lives and work. They shared information about their age, their income, how often they worked overtime, and their job satisfaction. They also answered questions about their mental and emotional resources, such as their hopefulness and resilience, and how much support they felt from their families and friends. Crucially, they reported on their own experience of presenteeism, rating how much their health issues were interfering with their ability to do their jobs. The researchers then used a sophisticated statistical method to sift through this mountain of information, looking for the specific combination of factors that best predicted who would be struggling.
The analysis revealed that eight specific factors were the most powerful indicators of risk. These included the nurse's years of experience, the level of the hospital they worked in, how frequently they worked overtime, their monthly income, their level of job satisfaction, their psychological capital, the social support they perceived, and the type of stress they faced. The researchers found that nurses working in higher-level hospitals, those with higher incomes, and those facing specific types of work stress were more likely to be at risk. Conversely, having strong psychological resources and feeling supported by others acted as a shield. Using these eight factors, the team built a visual tool called a nomogram. This is essentially a scoring chart where a manager can plug in a nurse's specific details—such as their income bracket or years of experience—and the chart adds up the points to reveal the probability that the nurse is experiencing high levels of presenteeism.
When the researchers tested this tool, it performed with remarkable accuracy. In the group of nurses used to build the model, the tool correctly distinguished between those at high risk and those at low risk with an AUC of 0.86. When they tested it on a separate group of nurses to ensure it wasn't just a fluke, the accuracy actually improved to nearly 0.88. The tool also showed that it was very reliable in its predictions, meaning the numbers it gave were very close to the reality of the nurses' actual situations. The researchers found that the model could successfully identify nurses who were at risk, addressing the fact that presenteeism is a covert phenomenon that often goes unnoticed.
The implications of this work are significant for the daily management of healthcare teams. For hospital administrators, this tool offers a way to move from guessing who needs help to knowing with a high degree of certainty. Instead of waiting for a nurse to make a mistake or take sick leave, managers can use this scoring system to identify those who are quietly struggling. The study suggests that targeted interventions, such as adjusting workloads, offering stress management programs, or simply strengthening the support networks within the hospital, could be directed at the right people at the right time. By addressing the specific mix of personal and professional pressures that lead to presenteeism, hospitals can protect the well-being of their most dedicated staff and, in turn, ensure the safety and dignity of the patients they serve. The research confirms that while the pressures of oncology nursing are unique and intense, they are not unmanageable, provided there is a clear way to see the risks before they become crises.
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