Does “hospital loyalty” matter? Factors related to the intention of using a mobile app

Figures & data

Figure 1 Research model.

Figure 2 Mobile app design – (A) assessment of behavioral and menstrual status; (B) calendar function; (C) data storage (The content of this interface has been translated into English; the original interface is in Chinese.).

Table 1 Cronbach’s α, factor loadings, and explained variance of the study variables

Study variable	Items	Cronbach’s α	Factors	Factor loading	Explained variance (%)
Hospital loyalty	3	0.88	1	0.877–0.917	80.806
Perceived usefulness	4	0.88	1	0.849–0.871	73.570
Perceived ease of use	4	0.93	1	0.837–0.953	82.761
Satisfaction	2	0.88	1	0.956	91.386
Usage intention	2	0.85	1	0.933	87.059

Table 2 Demographic characteristics

Variables	N (%)	Mean + SD
Age		32.19±7.64
20–29	16 (12.8)
30–39	90 (72)
40–49	18 (14.4)
≧50	1 (0.8)
Body mass index (BMI)		21.45±3.51
<18.5	11 (8.8)
18.5≦ BMI <24	86 (68.8)
≧24	28 (22.4)
Educational level
Senior high school	5 (4)
College	23 (18.4)
University	73 (58.4)
Graduate school	24 (19.2)
Marital status
Married	35 (28)
Single	90 (72)
Work/school duration
No	8 (6.4.9)
No fixed time/Shift	17 (13.6)
Fixed time	99 (79.2)
Missing	1 (0.8)
Obstetric and gynecological diagnoses
Yes	73 (58.4)
No	52 (41.6)
Pregnancy experience
Yes	101 (80.8)
No	24 (19.2)
Experience of childbirth
Yes	109 (87.2)
No	16 (12.8)

Figure 3 Measurement model composed of five latent variables tested through confirmatory factor analysis. All the correlations were statistically significant.

Note: L1–L3= items of hospital loyalty; U1–U4= items of perceived usefulness of the mobile app; E1–E4= items of perceived ease of use of the mobile app; S1–S2= items of Satisfaction with the mobile app use; I1–I2= items of usage intention of the mobile app.

Table 3 Standardized path coefficients for the full and parsimony models

	Paths	Full model		Parsimony model
		β (95% CI)	Result	β (95% CI)	Result
H1a	Perceived usefulness→Usage intention	0.36 (0.15, 0.58)	Support	0.40 (0.18, 0.62)	Support
H1b	Perceived ease of use→sage intention	0.12 (−0.10, 0.32)	Not support	–	–
H1c	Perceived ease of use→Perceived usefulness	0.63 (0.47, 0.78)	Support	0.63 (0.47, 0.78)	Support
H2a	Satisfaction→Usage intention	0.43 (0.17, 0.69)	Support	0.49 (0.27, 0.69)	Support
H2b	Perceived usefulness→Satisfaction→Usage intention	0.49 (0.31, 0.65)	Support	0.49 (0.32, 0.64)	Support
H2c	Perceived ease of use→Satisfaction→Usage intention	0.40 (0.24, 0.57)	Support	0.40 (0.24, 0.57)	Support
H3a	Hospital loyalty→Usage intention	0.003 (−0.11, 0.13)	Not support	–	–
H3b	Hospital loyalty→Satisfaction→Usage intention	−0.002 (−0.12, 0.12)	Not support	–	–
H3c	Hospital loyalty→Perceived usefulness→Usage intention	0.17 (−0.002, 0.33)	Support	0.17 (0.03, 0.29)	Support
H3d	Hospital loyalty→Perceived ease of use→Usage intention	0.53 (0.36, 0.66)	Support	0.53 (0.36, 0.66)	Support

Abbreviations: β, standardized regression weights; CI, confidence interval; H, hypothesis.

Table 4 Standardized direct and indirect effects on usage intention of mobile app (parsimony model)

Variables	Direct effects	Indirect effects	Total effects
Hospital loyalty	–	0.35(0.17×0.40+0.17×0.49×0.49+0.53×0.63×0.40+0.53×0.40×0.49)	0.35
Perceived usefulness	0.40	0.24 (0.49×0.49)	0.64
Perceived ease of use	0.12	0.6 (0.63×0.40+0.63×0.49×0.49+0.40×0.49)	0.72
Satisfaction	0.49	–	0.49

Figure 4 Structural equation modeling analysis of the research model (full model). The dotted line represents a nonsignificant relationship. *p<0.05.

Table S1 Study variables and corresponding items

Study variables	Item	Reference
Loyalty
L1	I think the hospital is very good.	Astuti & Nagase (2014)^Citation1
L2	I would recommend the hospital to others.
L3	I would like to use the service again.
Perceived usefulness
U1	The application is helpful for me to recall my behavior.	Davis (1989)^Citation2 and Wang et al (2006)^Citation3
U2	The application is helpful for me to recall my medication intake.
U3	The graph and consolidated table of the application are helpful to me.
U4	Overall, the application is useful for my self-care.
Perceived ease of use
E1	The interface design of the application was clear and understandable.	Davis (1989)^Citation2 and Wang et al (2006)^Citation3
E2	I could easily record my menstrual status and behavior with the application.
E3	Learning to operate the application would be easy for me.
E4	Using the application doesn’t take too much time.
Satisfaction
S1	I felt satisfied after using application.	Astuti & Nagase (2014)^Citation1
S2	I like the design of the application.
Usage intention
I1	I will use the application in the future.	Davis (1989)^Citation2 and Wang et al (2006)^Citation3
I2	I would recommend the application to my friends with menstrual discomfort symptoms.

Astuti HJ, Nagase K. Patient loyalty to healthcare organizations: relationship marketing and satisfaction. Int J Manage Marketing Res. 2014;7(2):39–56.

 Google Scholar

Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. Manage Inf Syst Q. 1989;13(3):319–340. doi:10.2307/249008

 Web of Science ®Google Scholar

Wang YS, Lin HH, Luarn P. Predicting consumer intention to use mobile service. Inf Syst J. 2006;16:157–179. doi:10.1111/j.1365-2575.2006.00213.x

 Web of Science ®Google Scholar