1.Clinical analysis of 495 elderly patients with eyelid neoplasms
Jibing YU ; Ling WANG ; Jingfang HAO ; Hongkui ZHANG ; Lu YANG
Chinese Journal of Geriatrics 2017;36(9):1002-1004
2.Exploration and reflection on the innovative incentive path of medical youth based on two-factor theory under high-quality development
Jingfang YANG ; Xue WANG ; Kuo LIANG ; Xiuhai GUO ; Junwei HAO
Chinese Journal of Medical Science Research Management 2022;35(6):453-457
Objective:According to the requirements of high-quality development of public hospitals, to explore the innovative incentive path for medical youth based on the two-factor theory, and provide a reference for promoting the high-quality development of public hospitals.Methods:Using the literature analysis method, the two-factor theory, hospital scientific research incentive mechanism, and scientific research incentive mechanism for young talents were investigated. Meanwhile, combining the two-factor theory and practical experience, the problems that existed in the innovation incentive policy of public hospitals for young medical talents were analyzed, and the corresponding countermeasures were proposed to build the innovation incentive path of young medical talents under the two-factor theory.Results:Based on analyzing the demand characteristics of young medical talents, managers should distinguish health care factors and incentive factors, and implement incentives from both aspects. Provide incentives through improving the personal sense of achievement, creating a personal growth environment, and promoting professional titles to stimulate young talents' innovation motivation; implement health care factors from aspects of working conditions, material benefits, salary levels, etc.Conclusions:As a new concept of development, high-quality development is not only reflected in scientific and technological innovation-driven, but also in the innovation of management mechanisms so that institutional innovation becomes the driving force for high-quality development.
3.Construction and validation of a risk prediction model for health risk stress perception in patients with systemic lupus erythematosus
Jingmei WU ; Xiaoqing LYU ; Jieyu WANG ; Jingjing LI ; Wangqin TANG ; Xiao XU ; Min HAO ; Qingyun ZHU ; Jingfang HONG
Chinese Journal of Modern Nursing 2022;28(11):1443-1449
Objective:To analyze the risk factors of stress perception in patients with systemic lupus erythematosus (SLE) , and construct and validate a risk prediction model for health risk stress perception in SLE patients.Methods:This study is a cross-sectional study. From October 2020 to March 2021, totals of 310 SLE inpatients and outpatients in the Department of Rheumatology and Immunology from 4 general hospitals in Anhui Province were selected as the modeling object. According to the patients' stress perception score, they were divided into the group with health risk stress ( n=132) and the group without health risk stress ( n=178) . The general data, SLE disease activity, general self-efficacy, emotional intelligence, resilience, sleep disturbance, anxiety, depression were compared between the two groups, and independent risk factors were screened out and Logistic regression was used to construct a risk prediction model. Hosmer-Lemeshow and receiver operator characteristic curve (ROC) area were used to test the fit and prediction effect of the model, respectively, and 206 patients were included for model validation. Results:Binary Logistic regression analysis showed that SLE disease activity, resilience, anxiety, payment type, and family monthly income were the influencing factors of stress perception in SLE patients, and the difference was statistically significant ( P<0.05) . Hosmer-Lemeshow fit test showed χ 2=6.123, P=0.633. Besides, the area under the ROC, maximum Youden index, predictive critical value, sensitivity and specificity were 0.903, 0.660, 0.497, 0.795 and 0.865 respectively. Conclusions:This study is based on five independent risk factors of SLE patients' stress perception, namely SLE disease activity, resilience, anxiety, payment type, and family monthly income. The risk prediction model has good sensitivity and specificity, which can provide a reference for clinical assessment of health risk stress perception in SLE patients.