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Abstract：
Telemedicine has great potential for diabetes management. The COVID-19 pandemic has boosted the development of telemedicine. However, the factors influencing the behavioral intentions to use and use behaviors of telemedicine in patients with diabetes in China are not clear.
We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China.
Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use.
In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (β=.463, P<.001; β=.153, P=.02; and β=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01).
Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.
We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China.
Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use.
In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (β=.463, P<.001; β=.153, P=.02; and β=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01).
Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.
摘要：
背景：远程医疗在糖尿病管理方面具有巨大潜力。COVID-19大流行促进了远程医疗的发展。然而,我国糖尿病患者使用远程医疗行为意向和使用行为的影响因素尚不明确。
目的：我们旨在基于扩展的接受和使用技术统一理论模型来了解使用远程医疗的行为意愿的决定因素，并确定与中国糖尿病患者使用远程医疗相关的人口统计学因素。
方法：从2023年2月1日至2月7日对年龄≥18岁的糖尿病患者进行调查。将调查链接分布在3个微信群中,共988名门诊糖尿病患者或长沙市中心医院出院患者。使用结构方程模型来了解行为意图的决定因素。使用多变量逻辑回归分析来确定与远程医疗使用相关的人口统计学因素。
结果：总计，收集问卷514份。在受访者中，186例（36.2%）被诊断为COVID-19。测量模型显示出可接受的可靠性，收敛有效性，判别效度，和数据拟合指数。该模型解释了63.8%的行为意图方差。社会影响力,预期性能，和便利条件对行为意图有积极影响(分别为β=.463，P<.001；β=.153，P=.02；和β=.257，P=.004)。感知易感性，感知的严重性，努力预期对行为意向无显著影响(P>0.05)。远程医疗的总体使用率为20.6%(104/514)。调整行为意向得分后，多元回归分析显示,年龄,教育,家庭收入与远程医疗的使用有关。在40至59岁和18至39岁年龄组中，远程医疗的使用高于≥60岁年龄组（比值比[OR]4.35，95％CI1.84-10.29，P=.001；OR9.20，95％CI3.40-24.88，P<.001）。高中和大学的远程医疗使用率较高，而初中教育组较低（OR2.45，95％CI1.05-5.73，P=.04；OR2.63，95％CI1.11-6.23，P=.03）。家庭收入较高的患者比家庭年收入≤10,000日元的患者使用远程医疗的频率更高（1元人民币=0.1398美元；10,000日元-50,000日元组：OR3.90，95％CI1.21-12.51，P=.02；50,000日元-100,000日元组：OR3.91，95％CI1.19-12.79，P=.02；>100,000日元组：OR4.63
结论：社会影响力，预期性能，和便利条件对糖尿病患者使用远程医疗的行为意愿有积极影响。年轻患者,受过高等教育的病人，家庭收入高的患者使用远程医疗的频率更高。促进行为意向，特别关注老年患者的需求，低收入患者，教育水平低的患者需要鼓励使用远程医疗。
目的：我们旨在基于扩展的接受和使用技术统一理论模型来了解使用远程医疗的行为意愿的决定因素，并确定与中国糖尿病患者使用远程医疗相关的人口统计学因素。
方法：从2023年2月1日至2月7日对年龄≥18岁的糖尿病患者进行调查。将调查链接分布在3个微信群中,共988名门诊糖尿病患者或长沙市中心医院出院患者。使用结构方程模型来了解行为意图的决定因素。使用多变量逻辑回归分析来确定与远程医疗使用相关的人口统计学因素。
结果：总计，收集问卷514份。在受访者中，186例（36.2%）被诊断为COVID-19。测量模型显示出可接受的可靠性，收敛有效性，判别效度，和数据拟合指数。该模型解释了63.8%的行为意图方差。社会影响力,预期性能，和便利条件对行为意图有积极影响(分别为β=.463，P<.001；β=.153，P=.02；和β=.257，P=.004)。感知易感性，感知的严重性，努力预期对行为意向无显著影响(P>0.05)。远程医疗的总体使用率为20.6%(104/514)。调整行为意向得分后，多元回归分析显示,年龄,教育,家庭收入与远程医疗的使用有关。在40至59岁和18至39岁年龄组中，远程医疗的使用高于≥60岁年龄组（比值比[OR]4.35，95％CI1.84-10.29，P=.001；OR9.20，95％CI3.40-24.88，P<.001）。高中和大学的远程医疗使用率较高，而初中教育组较低（OR2.45，95％CI1.05-5.73，P=.04；OR2.63，95％CI1.11-6.23，P=.03）。家庭收入较高的患者比家庭年收入≤10,000日元的患者使用远程医疗的频率更高（1元人民币=0.1398美元；10,000日元-50,000日元组：OR3.90，95％CI1.21-12.51，P=.02；50,000日元-100,000日元组：OR3.91，95％CI1.19-12.79，P=.02；>100,000日元组：OR4.63
结论：社会影响力，预期性能，和便利条件对糖尿病患者使用远程医疗的行为意愿有积极影响。年轻患者,受过高等教育的病人，家庭收入高的患者使用远程医疗的频率更高。促进行为意向，特别关注老年患者的需求，低收入患者，教育水平低的患者需要鼓励使用远程医疗。
