Research On Influencing Factors Of Mobile Health APP Users' Willingness And Behavior Based On UTAUT

Objectives:This study was based on Unified Theory of Acceptance and Use of Technology.Combined with the characteristics of mobile APP and health care,two new variables of individual innovation and perception risk were added on the basis of UTAUT to identify whether UTAUT adapted with mobile health area.Then the influencing factors on users' acceptance and usage to mobile health APP were analyzed by survey data.According to the analyzing result,to put forward developing strategies for mobile health APP,to research and develop APP for hospitals and mobile health APP development suppliers,and to provide government sectors with basis and data support for the establishment of relevant regulatory policies.Methods:(1)Through the review of some literature at home and abroad,to build a theoretical basis model to analyze the mobile medical APP users' willingness and behavior.(2)The questionnaire,the rationality of the model variable settings and the correctness of the statement were designed by the group discussion.(3)625 questionnaires were collected from outpatients of three provincial hospitals in Hangzhou,616 questionnaires were retrieved.The valid recovery rate was 98.56%.(4)The survey data was inputted by Epidata 3.1,and SPSS 20.0 and AMOS 21.0 software for statistical analysis modeling,using some statistical methods: reliability test,validity test,spearman correlation,ANOVA and linear regression analysis and structural equation model.Results:(1)The each dimension Cronbach's ? coefficients of questionnaire were above 0.65,and the questionnaire overall Cronbach's ? coefficients was 0.903,KMO was 0.903,P<0.05,the total explained variance rate was 75.586%.(2)441 subjects had used the mobile health APP,accounting for 71.6%.The number of usage on Zhejiang appointment registration APP was the largest,accounting for 31.6%.Scheduled registration was the most frequently used functions,accounting for 40.5%.20 to 29-year-old subjects accounted for the most,more than 6 percent of the subjects were educated college or undergraduate.Occupation for business/company staffs accounted for 33.8%.Family income per month of 4001-6000 yuan accounted for 33.1%.27 investigators did not have medical insurance,89 investigators were suffering from chronic disease.(3)The spearman coefficients for Individual Innovation,Effort Expectancy,Social Influence,Performance Expectancy,Facilitating Conditions,Perception Risk with Use Willingness were 0.317,0.493,0.338,0.619,0.570,-0.298,those variables were statistically significant(P<0.05).The spearman coefficients for Individual Innovation,Effort Expectancy,Social Influence,Performance Expectancy,Facilitating Conditions,Use Willingness with Use Behavior were 0.332,0.288,0.126,0.464,0.330,0.432.Individual Innovation,Effort Expectancy,Performance Expectancy,Facilitating Conditions,Use Willingness were statistically significant(P<0.05).(4)The Perception Risk score of the group was decreased with the increase of the Use Willingness.The scores of Individual Innovation,Effort Expectancy,Social Influence,Performance Expectancy,Facilitating Conditions were increased with the increse of the Use Willingness.They were statistically significant(P<0.05).The scores of Individual Innovation,Effort Expectancy,Performance Expectancy,Facilitating Conditions,Use Willingness were increased with the increse of the Use Behavior.They were statistically significant(P<0.05).(5)Female(0.134),Performance Expectancy(0.321),Facilitating Conditions(0.256),Effort Expectancy(0.224),Social Influence(0.100)entered the equation of Use Willingness.They were statistically significant(P<0.05).Use Willingness(0.215),Performance Expectancy(0.241),Individual Innovation(0.179),entered the equation of Use Behavior,and they were positive correlation(P<0.05).And Perception Risk(-0.148)negativly influenced Use Behavior(P<0.05).(6)Modified the Use Willingness model fit index: CMIN/DF value was 2.980,GFI value was 0.937,AGFI value was 0.914,RMSEA value was 0.057,NFI value was 0.932,CFI value was 0.953,IFI value was 0.954,TLI value was 0.943;Modified the Use Behavior model fit index: CMIN/DF value was 2.371,GFI value was 0.917,AGFI value was 0.892,RMSEA value was 0.056,NFI value was 0.905,CFI value was 0.942,IFI value was 0.943,TLI value was 0.932.Fit indexes were reached to the ideal standards which could better explain the mobile medical APP users' willingness and behavior.(6)In the Use Willingness model,the influence coefficient of Facilitating Conditions,Individual Innovation,Effort Expectancy,Performance Expectancy were 0.411,0.407,0.328,0.261.In the Use Behavior model,the influence coefficient of Facilitating Conditions,Individual Innovation,Effort Expectancy,Performance Expectancy,Use Willingness were 0.220,0.180,0.143,0.127,0.446.Conclusion:The models proved that Facilitating Conditions,Individual Innovation,Effort Expectancy,Performance Expectancy had positive impact on Use Willingness,and Facilitating Conditions,Individual Innovation,Effort Expectancy,Performance Expectancy,Use Willingness had positive impact on Use Behavior.This study had not found that Social Influence,Perception Risk effect the variable of Use Willingness and Behavior.And the regulation of gender and age on the models had not been demonstrated in this study.