Telemedicine has great potential for diabetes management. The COVID-19 pandemic has boosted the development of telemedicine. However, the factors influencing the behavioral intentions to use and use behaviors of telemedicine in patients with diabetes in China are not clear.
We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China.
Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use.
In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (β=.463, P<.001; β=.153, P=.02; and β=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01).
Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.

Chronic disease incidence among the elderly is increasing, which is correlated with the acceleration of population aging. Evolving internet technologies may help prevent and provide interventions for chronic diseases in an accelerating aging process. However, the impact of daily internet use on the incidence of chronic diseases is not well understood.
This study aims to investigate whether daily internet use by middle-aged and older adults may inhibit or promote the occurrence of chronic diseases.
We included participants from the China Health and Retirement Longitudinal Study (CHARLS), a longitudinal survey of Chinese residents aged ≥45 years. We assessed 8-year data from wave 1 (June 2011-March 2012) to wave 4 (July-September 2018) in CHARLS. Data from wave 4 were used for a cross-sectional study, and data from all 4 waves were used for a longitudinal study. Self-reported data were used to track variables, including internet use, use frequency, and the incidence of different chronic diseases. Cox proportional hazards modeling was applied in the longitudinal study to examine the relationship between daily internet use and chronic diseases among middle-aged and older adults, while adjusting for sociodemographic characteristics and health behaviors. In addition, longitudinal data were used to analyze internet usage trends, and cross-sectional data were used to analyze the factors influencing internet use.
Among the 20,113 participants included in the longitudinal analyses, internet use increased significantly, from 2% to 12.3%, between 2011 and 2018. The adjusted model found statistically significant relationships between daily internet use and a lower incidence of the following chronic diseases: hypertension (hazard ratio [HR] 0.78, 95% CI 0.65-0.95, P=.01), chronic lung disease (HR 0.74, 95% CI 0.57-0.97, P=.03), stroke (HR 0.69, 95% CI 0.50-0.94, P=.02), digestive disease (HR 0.73, 95% CI 0.58-0.91, P=.005), memory-related disorders (HR 0.58, 95% CI 0.37-0.91, P=.02), arthritis or rheumatism (HR 0.60, 95% CI 0.48-0.76, P<.001), asthma (HR 0.52, 95% CI 0.33-0.84, P=.007), depression (HR 0.80, 95% CI 0.71-0.89, P<.001), and vision impairment (HR 0.83, 95% CI 0.74-0.93, P=.004). Moreover, our study also showed that with increasing frequency of internet use, the risk of some chronic diseases decreases.
This study found that middle-aged and older adults who use the internet have a reduced risk of developing chronic diseases versus those who do not use the internet. The increasing prevalence of daily internet use among middle-aged and older adults may stimulate contemplation of the potential role of internet platforms in future research on chronic disease prevention.

Although digital health technologies (DHTs) help many people maintain a healthy life, including those of advanced age, these technologies are of little use to older adult populations if they are not being adopted in daily life. Thus, it is critical to identify ways to help older adults recognize and try new technologies and maintain their use of them to maximize the benefits of these technologies in a digital-based society.
Our study aimed (1) to assess the current usage of DHT among older adults in Hong Kong and (2) to examine how high and low levels of eHealth literacy in this group affects the relationship between the Technology Readiness and Acceptance Model (TRAM) and attitudes and intention toward DHT.
A total of 306 adults over 60 years of age in Hong Kong participated in this study. After conducting confirmatory factor analysis to validate the measurement model, the hypothesized model was tested using structural equation modeling.
Optimism was significantly related to perceived usefulness, while optimism, innovativeness, and discomfort were significantly associated with perceived ease of use. Both perceived usefulness and perceived ease of use were significantly linked to attitude toward the use of DHTs. Meanwhile, attitude significantly predicted usage intention. Additionally, the results revealed the differences in the relationships of the TRAM between participants with high and low levels of eHealth literacy. The influence of optimism and innovativeness on perceived ease of use was stronger for the higher-level group than for the lower-level group, and the influence of discomfort for the higher-level group was much weaker.
The findings provided partial support for the impact of eHealth literacy on encouraging older adults to use DHT and obtain health benefits from it. This study also suggests providing assistance and guidelines for older adults to narrow the aging-related technology gap and to further explore the associations of eHealth literacy, the TRAM, and actual behaviors.

Although recent research has demonstrated spouse support for technology use among older adults, by treating them as a homogeneous group, it has overlooked differences caused by socio-demographic dimensions in their digital engagement. Following the approach of the grounded theory and interviewing 15 couples in a developing aging region (Wuzhi County, Henan, China), this study paints a fuller picture of couple support for technology adoption among older adults in terms of their psychological motivations by dividing older adults into two categories: technology supports and technology recipients. The resulting concepts of motivation (e.g., social norms, benefit driven, perceptual elements, and value satisfaction), particularly limiting motivational factors (e.g.,individual status) reveal the psychological mechanisms behind this process and are conceptualized as a \"motivation\" model of couple support for digital technology use among rural older adults. Our study has strong implications for active and healthy aging, as policymakers can stimulate external motivation for technology adoption among older adults by fostering a sense of family responsibility and social ethos that encourages couples to help each other. In addition, local communities as stakeholders can educate older adults about the usefulness, ease of use, and risk-averse means of digital technology, and satisfy their altruistic and egoistic psychological needs to increase the inner value satisfaction they gain from the couple support process. By doing this, motivation and engagement are thereby increased, and ultimately, technology adoption in disadvantaged socioeconomic groups may be improved.

BACKGROUND: Since expanding the use of appropriate and effective health technologies will greatly benefit the diagnosis and treatment of some major diseases at an early stage, understanding the mechanism of technology use is crucial for its successful implementation. Few previous studies focused on the healthcare providers and involved multi-facets factors at individual, technical, organizational, and environmental levels.
OBJECTIVE: To examine the influencing mechanism of technology use among Chinese physicians by integrating multilevel factors, Des-gamma-Carboxy Prothrombin (DCP) was taken as an example.
METHODS: Through multistage random sampling, a cross-sectional questionnaire survey was conducted among physicians in charge of direct use of DCP of sampled secondary and tertiary hospitals. Since the sample data comprised two hierarchical levels (physicians and hospitals), multilevel structural equation modeling was used to link five aspects of factors with physicians\' technology use and estimate the effects.
RESULTS: Totally, 229 physicians completed the investigation. The use of DCP appears to be at a relatively low level. Intra-class coefficients of the null model (unadjusted baseline model) suggested that physicians\' DCP use has a significant variation between hospitals. The final model identified that value cognition (B = 0.447, P < 0.01), experienced organizational practice (B = 0.203, P < 0.05), and perceived organizational atmosphere (B = -0.237, P < 0.01) contributed directly to physicians\' DCP use. Additionally, technical assessment, perceived organizational atmosphere, and perceived environmental pressure had indirect impacts on physicians\' DCP use that were mediated by value cognition and experienced organizational practice (P < 0.05).
CONCLUSIONS: This study incorporated and determined the significant direct or indirect role of value cognition, technical assessment, experienced organizational practice, perceived organizational atmosphere, and perceived environmental pressure. This influencing mechanism with integrated multilevel factors could serve as a theoretical basis for tailoring interventions to promote technology use among Chinese physicians.

This article provides a method from which the breadth of adoption and use of digital technologies may be evaluated. Whilst the method can be used for individual devices, it was designed as a means for understanding the well-being of all devices within a site, and especially as an overview method for multiple institutions within a city or in far larger studies involving multiple organisations over large geographical distances. Our method is digital technology neutral. Digital technologies may be of any types, belonging to any category but can be extended to include both emerging and unconventional systems as long as the variables provided in this article can act as metrics for their evaluation. The approach used here is a mixture of quantitative and qualitative evaluation. Qualitative evaluation using thematic analysis is applied for the understanding of phenomenon identified within our quantitative methods. •Technology neutral approach to understanding the institutional adoption and use of digital systems•Broad evaluation method suited to the evaluation of multiple digital technologies at the institutional level, or large studies involving multiple organisations over large geographical distances.•Uses a mixture of quantitative analysis for revealing trends and qualitative evaluation for understanding phenomenon.