Modeling Consumer Acceptance and Usage Behaviors of m-Health: An Integrated Model of Self-Determination Theory, Task-Technology Fit, and the Technology Acceptance Model

• Published in: Healthcare (Basel) Vol. 11; no. 11; p. 1550
• Main Authors: Tao, Da, Chen, Zhixi, Qin, Mingfu, Cheng, Miaoting
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 25-05-2023; MDPI
• Subjects: Acceptance testing; Behavior; Consumer behavior; Consumers; Decision making; demographic characteristics; E-health; Health informatics; Health services; Hypotheses; Internet; m-health; Marketing research; Motivation; Online instruction; Perceptions; self-determination theory; Self-determination theory (Psychology); task–technology fit; technology acceptance; Technology Acceptance Model; China; m-health; demographic characteristics; technology acceptance; task–technology fit; self-determination theory
• ISSN: 2227-9032; 2227-9032
• DOI: 10.3390/healthcare11111550

Although mobile health (m-health) has great potential to reduce the cost of medical care and improve its quality and efficiency, it is not widely accepted by consumers. In addition, there is still a lack of comprehensive insight into m-health acceptance, especially among consumers with different demographic characteristics. This study aimed to explore the factors affecting consumers' acceptance and usage behaviors of m-health and to examine whether their roles differ by demographic characteristics. A comprehensive m-health acceptance model was proposed by integrating factors from the Self-Determination Theory, Task-Technology Fit, and Technology Acceptance Model. Survey data were collected from 623 Chinese adults with at least 6 months of m-health usage experience and analyzed using structural equation modeling techniques. Multi-group analyses were performed to assess whether the model relationships were different across gender, age, and usage experience. The results indicated that relatedness and competence were significant motivational antecedents of perceived ease of use. Task-technology fit and the perceived ease of use significantly affected the perceived usefulness. The perceived ease of use and perceived usefulness were significant determinants of consumer usage behaviors of m-health and together explained 81% of its variance. Moreover, the relationships among autonomy, perceived usefulness, and usage behaviors of m-health were moderated by gender. Consumer usage behaviors of m-health were affected by factors such as self-motivation (i.e., relatedness and competence), technology perceptions (i.e., perceived ease of use and perceived usefulness), and task-technology fit. These findings provide a theoretical underpinning for future research on m-health acceptance and provide empirical evidence for practitioners to promote the better design and use of m-health for healthcare activities.