胰岛素无针注射患者满意度调查及相关因素分析

Investigation of Patients’ Satisfaction with Insulin Needle-Free Injection and Analysis of Related Factors

摘要: 目的：调查山东地区胰岛素无针注射患者满意现状，并对相关影响因素进行分析。方法：以2020年1月~2021年7月间，应用第三代无针注射器进行胰岛素注射治疗的614例山东地区的糖尿病患者为研究对象，进行电话问卷调查。依据患者对无针注射治疗满意情况，分为满意组(569例)和不满意组(45例)。采用SPSS27.0软件，进行卡方检验、Fisher确切概率法、多因素logistic回归分析，构建满意预测模型。结果：对无针注射治疗满意的患者比例为92.7%。单因素分析结果显示：年龄、BMI、注射次数、定期筛查、饮食控制情况、运动控制情况在两组之间存在显著差异，差异具有统计学意义(P < 0.05)。Logistic回归分析显示：BMI、定期筛查是无针注射治疗满意与否的独立影响因素，差异有统计学意义(P < 0.05)。构建满意度预测模型，预测模型的ROC曲线下面积为0.704 (95% CI: 0.628~0.780)，以约登指数最大值0.364选取最佳截断值0.908。此时，ROC曲线敏感度67.5%，特异度68.9%。Hosmer-Lemeshow拟合优度检验(χ² = 10.616, P = 0.224)，说明模型拟合效果较好。结论：BMI、定期筛查是胰岛素无针注射患者满意与否的独立影响因素，logistic回归模型对其预测价值较高，有助于更精准筛选适用人群，提高患者满意度。

Abstract: Objective: To investigate the satisfaction status of insulin needle-free injection patients in Shandong region and analyze the relevant influencing factors. Methods: From January 2020 to July 2021, 614 patients with diabetes in Shandong Province who were treated with the third generation needle-free syringe for insulin injection were investigated by telephone questionnaire. According to the patients’ satisfaction degree, patients were divided into satisfactory group (569 cases) and unsatisfactory group (45 cases). χ² test, Fisher’s exact probability method, and multivariate logistic regression analysis were used to construct a satisfactory prediction model with SPSS27.0 software. Results: The proportion of patients who were satisfied with needle-free injection treatment was 92.7%. The results of univariate analysis showed that there are statistically significant differences in age, BMI, number of injections, regular screening, dietary control, and exercise control between the two groups (P < 0.05). Logistic regression analysis showed that BMI and regular screening were independent influencing factors on the satisfaction of needle-free injection therapy, there is a significant difference (P < 0.05). Prediction model with regard to satisfaction level was constructed with an area under the ROC curve of 0.704 (95% CI: 0.628~0.780). The optimal cutoff value was 0.908 with a maximum value of 0.364 for the Jordan index. At this point, the ROC curve has a sensitivity of 67.5% and a specificity of 68.9%. Hosmer-Lemeshow goodness of fit test (χ² = 10.616, P = 0.224), indicating a good fitting effect of the model. Conclusion: BMI and regular screening are independent influencing factors for the satisfaction of insulin needle-free injection patients. The logistic regression model has high predictive value for them, which helps to more accurately screen suitable populations and improve patient satisfaction.