The Impact of Using mHealth Apps on Improving Public Health Satisfaction during the COVID-19 Pandemic: A Digital Content Value Chain Perspective
Abstract
:1. Introduction
2. Theoretical Background and Hypothesis Development
2.1. Digital Content Value Chain Framework
2.2. Main Values of mHealth App during the COVID-19 Pandemic
3. Research Model and Questionnaire Survey
3.1. Digital Content-Value Chain Framework
3.2. Questionnaire Survey
4. Methods
5. Results
5.1. Pretest Results
5.2. Common Method Bias Test Results
5.3. Measurement Model Results
5.4. Structural Model Results
5.5. Mediation Effect Results
6. Discussion and Implications
6.1. Discussion of Key Findings
6.2. Theoretical Contribution
6.3. Practical Contribution
6.4. Limitations and Future Research
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Factor | Serial Num. | Item | Reference |
Healthcare assurance capacity (HAC) | HAC1 | During the COVID-19 pandemic, the health management function in the mhealth app encouraged me. | Akter et al. [61] |
HAC 2 | During the COVID-19 pandemic, because of the health management function in the mhealth app, I feel safe. | ||
HAC 3 | During the COVID-19 pandemic, the health management function in the mhealth app can solve my health problems. | ||
Healthcare confidence (ACO) | ACO1 | During the COVID-19 pandemic, the information provided by mhealth apps allows me to know enough about my health. | Benson et al. [67] |
ACO2 | During the COVID-19 pandemic, the information provided by mhealth apps makes me feel that I can take care of my health. | ||
ACO3 | During the COVID-19 pandemic, the information provided by mhealth apps helped me when I needed it. | ||
ACO4 | During the COVID-19 pandemic, the information provided by mhealth apps helped me make decisions about health management. | ||
Parasocial relationships (PSR) | PSR1 | When I use mhealth app during the COVID-19 pandemic, the doctor I chose to make me feel like a friend. | Sokolova and Perez [68] |
PSR2 | When I use mhealth apps during the COVID-19 pandemic, my communication with the doctor is very comfortable. | Zafar et al. [69] | |
PSR3 | When I use mhealth apps during the COVID-19 pandemic, I can rely on the doctor to provide me with a diagnosis. | ||
PSR4 | When I use mhealth apps during the COVID-19 pandemic, there was a small error in the doctor’s diagnosis immediately, and I will forgive him. | ||
User–function interaction (UFI) | UFI1 | The health management function in mhealth apps is safe and reliable. | Kim and Kim [22] |
UFI2 | The health management function in mhealth apps is easy to use. | ||
UFI3 | The steps of using health management in mhealth apps are easy to learn. | ||
UFI4 | The health management function in mhealth apps meets individual needs. | ||
User–information interaction (UII) | UII1 | The information and user interaction in mhealth apps are accurate. | Kim and Kim [22] |
UII2 | Information and user interaction in mhealth apps are useful. | ||
UII3 | The interaction between the information and the user in mhealth apps is effective. | ||
UII4 | The information in mhealth apps can interact with the user quickly. | ||
User–doctor interaction (UDI) | UDI1 | Mhealth apps improve the interaction between users and doctors. | Kim and Kim [22] |
UDI2 | Mhealth apps improve communication between users and doctors. | ||
UDI3 | Mhealth apps allow users and doctors to interact with various types of information. | ||
UDI4 | Mhealth apps simplify the exchange of information between users and doctors. | ||
Satisfaction with public health (SPH) | SPH1 | During the COVID-19 pandemic, the public medical resources available to me satisfy me. | Akter, Ambra and Ray [70] |
SPH2 | During the COVID-19 pandemic, I can conveniently use public medical resources. | ||
SPH3 | During the COVID-19 pandemic, I am very happy that I can use public medical resources. | ||
SPH4 | During the COVID-19 pandemic, I can use public medical resources at any time. |
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Items | Options | Frequency (Total = 316) | Percentage (%) |
---|---|---|---|
Gender | Male | 128 | 40.5 |
Female | 188 | 59.5 | |
Age | 18–20 | 55 | 17.4 |
21–30 | 84 | 26.6 | |
31–40 | 87 | 27.5 | |
41–50 | 44 | 13.9 | |
51 years or above | 46 | 14.6 | |
Income (Per month) | RMB 1000–2000 | 47 | 14.9 |
RMB 2001–3000 | 80 | 25.3 | |
RMB 3001–4000 | 71 | 22.5 | |
RMB 4001–5000 | 68 | 21.5 | |
More than RMB 5000 | 50 | 15.8 | |
Education | High School | 140 | 44.3 |
Bachelor’s Degree | 154 | 48.7 | |
Master or PhD Degree | 22 | 7 | |
mHealth app Brand | Pingan Health App | 74 | 23.4 |
Chunyu Doctor App | 70 | 22.2 | |
Dinxiang Doctor App | 66 | 20.9 | |
Other | 106 | 33.5 |
Group | N | Mean (SD) | t-Value | Df | p-Value |
---|---|---|---|---|---|
mhealth users | 316 | 3.063 (0.640) | 9.972 | 291.203 | 0.000 |
Non-mhealth users | 172 | 2.356 (0.801) |
Latent Variable | Item | Loading | Mean (SD) | Cronbach’s a | CR | AVE |
---|---|---|---|---|---|---|
HAC | HAC1 | 0.927 | 3.044 (1.136) | 0.856 | 0.913 | 0.777 |
HAC2 | 0.846 | |||||
HAC3 | 0.869 | |||||
ACO | ACO1 | 0.922 | 3.300 (1.080) | 0.909 | 0.937 | 0.787 |
ACO2 | 0.818 | |||||
ACO3 | 0.848 | |||||
ACO4 | 0.955 | |||||
PSR | PSR1 | 0.857 | 2.726 (0.672) | 0.840 | 0.892 | 0.674 |
PSR2 | 0.777 | |||||
PSR3 | 0.734 | |||||
PSR4 | 0.889 | |||||
UFI | UFI1 | 0.832 | 3.258 (0.807) | 0.827 | 0.884 | 0.656 |
UFI2 | 0.791 | |||||
UFI3 | 0.810 | |||||
UFI4 | 0.805 | |||||
UII | UII1 | 0.908 | 3.407 (0.855) | 0.885 | 0.921 | 0.747 |
UII2 | 0.798 | |||||
UII3 | 0.798 | |||||
UII4 | 0.942 | |||||
UDI | UDI1 | 0.902 | 3.058 (0.769) | 0.817 | 0.880 | 0.648 |
UDI2 | 0.719 | |||||
UDI3 | 0.787 | |||||
UDI4 | 0.801 | |||||
SPH | SPH1 | 0.882 | 3.062 (0.640) | 0.837 | 0.891 | 0.673 |
SPH2 | 0.785 | |||||
SPH3 | 0.708 | |||||
SPH4 | 0.892 |
HAC | ACO | PSR | UFI | UII | UDI | SPH | |
---|---|---|---|---|---|---|---|
HAC | |||||||
ACO | 0.12 | ||||||
PSR | 0.434 | 0.284 | |||||
UFI | 0.441 | 0.536 | 0.314 | ||||
UII | 0.346 | 0.454 | 0.267 | 0.439 | |||
UDI | 0.396 | 0.348 | 0.478 | 0.302 | 0.326 | ||
SPH | 0.334 | 0.44 | 0.344 | 0.559 | 0.392 | 0.517 |
HAC | ACO | PSR | UFI | UII | UDI | SPH | |
---|---|---|---|---|---|---|---|
HAC | 0.881 | ||||||
ACO | 0.106 | 0.887 | |||||
PSR | 0.377 | 0.265 | 0.821 | ||||
UFI | 0.383 | 0.473 | 0.276 | 0.81 | |||
UII | 0.307 | 0.413 | 0.243 | 0.385 | 0.864 | ||
UDI | 0.331 | 0.305 | 0.404 | 0.272 | 0.279 | 0.805 | |
SPH | 0.296 | 0.394 | 0.308 | 0.491 | 0.346 | 0.447 | 0.82 |
Hypotheses | ß | STDEV | t-Statistics | p-Values | Result |
---|---|---|---|---|---|
H1a: HAC → UFI | 0.323 | 0.045 | 7.148 | 0.000 | Support |
H1b: HAC → UII | 0.248 | 0.053 | 4.705 | 0.000 | Support |
H1c: HAC →UDI | 0.207 | 0.054 | 3.817 | 0.000 | Support |
H2a: ACO → UFI | 0.428 | 0.043 | 9.933 | 0.000 | Support |
H2b: ACO → UII | 0.373 | 0.05 | 7.513 | 0.000 | Support |
H2c: ACO → UDI | 0.211 | 0.057 | 3.705 | 0.000 | Support |
H3a: PSR → UFI | 0.041 | 0.05 | 0.819 | 0.413 | Reject |
H3b: PSR → UII | 0.051 | 0.055 | 0.931 | 0.352 | Reject |
H3c: PSR → UDI | 0.270 | 0.056 | 4.814 | 0.000 | Support |
H4a: UFI → SPH | 0.359 | 0.052 | 6.874 | 0.000 | Support |
H4b: UII →SPH | 0.120 | 0.049 | 2.456 | 0.014 | Support |
H4c: UDI → SPH | 0.316 | 0.052 | 6.051 | 0.000 | Support |
Path | ß | STDEV | t-Statistics | p-Values |
---|---|---|---|---|
HAC → UFI → SPH | 0.116 | 0.024 | 4.749 | 0.000 |
ACO → UFI → SPH | 0.154 | 0.026 | 5.877 | 0.000 |
PSR → UFI → SPH | 0.015 | 0.018 | 0.812 | 0.417 |
HAC → UII → SPH | 0.03 | 0.014 | 2.089 | 0.037 |
ACO → UII → SPH | 0.045 | 0.02 | 2.253 | 0.024 |
PSR → UII → SPH | 0.006 | 0.008 | 0.783 | 0.434 |
HAC → UDI → SPH | 0.066 | 0.02 | 3.21 | 0.001 |
ACO → UDI → SPH | 0.067 | 0.02 | 3.331 | 0.001 |
PSR → UDI → SPH | 0.085 | 0.025 | 3.392 | 0.001 |
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Cao, J.; Zhang, G.; Liu, D. The Impact of Using mHealth Apps on Improving Public Health Satisfaction during the COVID-19 Pandemic: A Digital Content Value Chain Perspective. Healthcare 2022, 10, 479. https://doi.org/10.3390/healthcare10030479
Cao J, Zhang G, Liu D. The Impact of Using mHealth Apps on Improving Public Health Satisfaction during the COVID-19 Pandemic: A Digital Content Value Chain Perspective. Healthcare. 2022; 10(3):479. https://doi.org/10.3390/healthcare10030479
Chicago/Turabian StyleCao, Junwei, Guihua Zhang, and Dong Liu. 2022. "The Impact of Using mHealth Apps on Improving Public Health Satisfaction during the COVID-19 Pandemic: A Digital Content Value Chain Perspective" Healthcare 10, no. 3: 479. https://doi.org/10.3390/healthcare10030479