Integrating social capital theory, social cognitive theory, and the technology acceptance model to explore a behavioral model of telehealth systems.

Chung-Hung Tsai

doi:10.3390/ijerph110504905

Abstract

Telehealth has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use. In addition, regarding the samples, the proposed model fitted considerably well. The proposed integrative psychosocial-technological model may serve as a theoretical basis for future research and can also offer empirical foresight to practitioners and researchers in the health departments of governments, hospitals, and rural communities.

Highlights

The evidence suggested that the telehealth system was remarkably useful and efficient for the health promotion of the residents, and that they were willing to overcome barriers to using it
Cronbach’s α, composite reliability and average variance extracted from the measures [55]
The following indices recommended by Hair et al [49], as the criteria for the model’s evaluation: (1) 2 /d.f. should be less than 3, (2) goodness-of-fit index (GFI) should be more than 0.9, (3) adjusted goodness-of-fit index (AGFI) should be more than 0.9, (4) root mean square error of approximation (RMSEA) should be less than 0.05, (5) root mean square residual (RMR) should be less than 0.05, (6) normed fit index (NFI) should be more than

Summary

Introduction

Developed countries worldwide are experiencing aging problems. (Republic of China, Taiwan) revealed that the senior citizen population was 7% of the total population in Taiwan in 1993. Taiwan has become an aging society, as defined by the World Health Organization. This percentage reached 10.9% at the end of 2011, and the aging index increased from 42.3% to. The population aged 65 or older is estimated to exceed 20% by 2026. The senior citizen population is estimated to be 36.97% of the total population by 2051; in other words, one senior citizen aged 65 or older for every three citizens

Objectives

Methods

Results

Discussion

Conclusion