Abstract
BACKGROUND: Diabetes management is a growing health care challenge worldwide. eHealth can revolutionize diabetes care, the success of which depends on end user acceptance. OBJECTIVE: This study aims to understand the readiness and acceptance of eHealth services for diabetes care among the general population, perceived advantages and disadvantages of eHealth, and factors associated with eHealth readiness and acceptance in a multiethnic Asian country. METHODS: In this cross-sectional epidemiological study, participants (N=2895) were selected through disproportionate stratified random sampling from a population registry. Citizens or permanent residents of Singapore aged >18 years were recruited. The data were captured through computer-assisted personal interviews. An eHealth questionnaire was administered in one of four local languages (English, Chinese, Malay, or Tamil), as preferred by the participant. Bivariate chi-square analyses were performed to compare the sociodemographic characteristics and perception of advantages and disadvantages of eHealth services between the diabetes and nondiabetes groups. Multivariable logistic regression models were used to determine factors associated with eHealth readiness and acceptance. All analyses were weighted using survey weights to account for the complex survey design. RESULTS: The sample comprised participants with (n=436) and without (n=2459) diabetes. eHealth readiness was low, with 47.3% of the overall sample and 75.7% of the diabetes group endorsing that they were not ready for eHealth (P<.001). The most acceptable eHealth service overall was booking appointments (67.4%). There was a significantly higher preference in the diabetes group for face-to-face sessions for consultation with the clinician (nondiabetes: 83.5% vs diabetes: 92.6%; P<.001), receiving prescriptions (61.9% vs 79.3%; P<.001), referrals to other doctors (51.4% vs 72.2%; P<.001), and receiving health information (34% vs 63.4%; P<.001). The majority of both groups felt that eHealth requires users to be computer literate (90.5% vs 94.3%), does not build clinician-patient rapport compared with face-to-face sessions (77.5% vs 81%), and might not be credible (56.8% vs 64.2%; P=.03). Age (≥35 years), ethnicity (Indian), and lower education status had lower odds of eHealth readiness. Age (≥35 years), ethnicity (Indian), lower education status (primary school), BMI (being underweight), and marital status (being single) were associated with a lower likelihood of eHealth acceptance. Among only those with diabetes, a longer duration of diabetes (4-18 years), higher education (degree or above), and younger age (23-49 years) were associated with eHealth readiness, whereas younger age and income (SGD 2000-3999 [US $1481-$2961]) were associated with acceptance. CONCLUSIONS: Overall, an unfavorable attitude toward eHealth was observed, with a significantly higher number of participants with diabetes reporting their unwillingness to use these services for their diabetes care. Sociodemographic factors associated with acceptance and readiness identified a group of people who were unlikely to accept the technology and thus need to be targeted for eHealth literacy programs to avoid health care disparity. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2020-037125.