Influencing factors of patient loyalty for internet diagnosis and treatment based on UTAUT model
10.3760/cma.j.cn111325-20240102-00006
- VernacularTitle:基于UTAUT模型的互联网诊疗患者忠诚度影响因素研究
- Author:
Jiaqi WU
1
;
Dongfu QIAN
;
Shuyuan ZHANG
Author Information
1. 南京医科大学医政学院，南京 211166
- Keywords:
Unified theory of acceptance and use of technology model;
Internet diagnosis and treatment;
Patient trust;
Patient loyalty;
Structural equation model;
Infl
- From:
Chinese Journal of Hospital Administration
2024;40(8):619-624
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the influencing factors of patient loyalty in internet diagnosis and treatment, for references for improving the service quality and promoting the sustainable development of internet diagnosis and treatment.Methods:In November 2023, a simple random sampling method was used to select patients who had received internet diagnosis and treatment as the survey objects and conduct a questionnaire survey on performance expectations, effort expectations, social influence, promotion conditions, price values, patient trust and patient loyalty. By establishing an unified theory of acceptance and use of technology model of influencing factors of patient loyalty in internet diagnosis and treatment, the hypotheses were put forward. The structural equation model (SEM) test and mediation effect test were used to verify the hypothesis path and variable mediation effect, and explore the influencing factors of internet patient loyalty.Results:A total of 1 800 patients were included in this study, including 1 188 patients(66.0%) who received internet diagnosis and treatment≥3 times/month. According to the SEA test, performance expectations ( β=0.296, P<0.001), social influence ( β=0.146, P=0.014), promotion conditions ( β=0.366, P<0.001), price values ( β=0.452, P=0.017), and patient trust ( β=0.459, P<0.001) had a direct positive impact on patient loyalty; Social influence ( β=0.147, P<0.001) and promotion conditions ( β=0.084, P<0.001) had a direct positive impact on patient trust. According to the mediation effect test, patient trust partially mediated the relationship between social influence and patient loyalty ( β=0.071, P=0.018), as well as the relationship between promoting conditions and patient loyalty ( β=0.748, P=0.041). Conclusions:Performance expectations, social influence, promotion conditions, price values, and patient trust had a positive impact on patient loyalty, among which social influence and promotion conditions could enhance patient loyalty by strengthening patient trust. It was suggested that relevant institutions should focus on the service quality of internet diagnosis and treatment, further improve performance expectations, expand social impact, improve promotion conditions and regulate price values, so as to enhance the patient loyalty, promote the wide application and rapid development of internet diagnosis and treatment.
