A study on the academic innovation ability and influencing factors of public health graduate students based on nomograms: a cross-sectional survey from Shandong, China

TL;DR

This study identifies factors influencing the academic innovation ability of public health graduate students in Shandong, China, and creates a predictive nomogram to help improve training.

Contribution

A novel nomogram is developed to predict and evaluate academic innovation ability among public health postgraduates.

Findings

Gender, student leadership, teacher-student relationship, and academic motivation influence innovation ability.

The nomogram shows strong predictive power with an AUC of 0.892.

The calibration curve confirms the nomogram's accuracy in predicting innovation levels.

Abstract

In recent years, the impact of the COVID-19 pandemic and various public crises has highlighted the importance of cultivating high-quality public health talents, especially those with innovative capabilities. This study focuses on the academic innovation ability of public health postgraduate students, which can provide important theoretical support for the cultivation of more public health workers with high innovative capabilities.

From May to October 2022, a cluster sampling method was used to select 1,076 public health postgraduate students from five universities in Shandong Province. A self-designed questionnaire survey was conducted. A chi-square test and binary logistic regression analysis were used to analyze the influencing factors of students’ academic innovation ability. Based on these factors, a nomogram was constructed to intuitively demonstrate the impact of these complex factors on students’ innovation ability.

The results showed that gender, whether serving as a student leader, teacher-student relationship, academic motivation, learning style, academic environment, and teaching mode were the influencing factors of postgraduate students’ academic innovation ability. The column-line diagram (AUC = 0.892, 95% CI = 0.803 ~ 0.833) constructed based on the above influencing factors has good differentiation. The area under the ROC curve is 0.892 (95% CI = 0.803 ~ 0.833), and the calibration curve shows that the predicted value is the same as the measured value.

The nomogram constructed in this study can be used to predict the academic innovation level of public health graduate students, which is helpful for university education administrators to evaluate students’ academic innovation ability based on nomogram scores and carry out accurate and efficient training.

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