An Investigation of Patients’ Decisions to Use eHealth

eHealth service has received increasing attention. Patients can consult online doctors via the Internet, and then physically visit the doctors for further diagnosis and treatments. Although extant research has focused on the adoption of eHealth services, the decision-making process from online to offline health services still remains unclear. This study aims to examine patients’ decisions to use online and offline health services by integrating the extended valence framework and the halo effect. By analyzing 221 samples with online consultation experiences, the results show that trust significantly influences perceived benefits and perceived risks, while trust, perceived benefits, and perceived risks significantly influence the intention to consult. The intention to consult positively influences the intention to visit. Considering the moderating effects of payment types, the influence of perceived risks on the intention to consult is larger for the free group than for the paid group. The findings are useful to better understand patients’ decisions to use eHealth.

Use of Health Information Technology by Adults With Diabetes in the United States: Cross-sectional Analysis of National Health Interview Survey Data (2016-2018)

Background The use of health information technology (HIT) has been proposed to improve disease management in patients with type 2 diabetes mellitus. Objective This study aims to report the prevalence of HIT use in adults with diabetes in the United States and examine the factors associated with HIT use. Methods We analyzed data from 7999 adults who self-reported a diabetes diagnosis as collected by the National Health Interview Survey (2016-2018). All analyses were weighted to account for the complex survey design. Results Overall, 41.2% of adults with diabetes reported looking up health information on the web, and 22.8% used eHealth services (defined as filled a prescription on the web, scheduled an appointment with a health care provider on the web, or communicated with a health care provider via email). In multivariable models, patients who were female (vs male: prevalence ratio [PR] 1.16, 95% CI 1.10-1.24), had higher education (above college vs less than high school: PR 3.61, 95% CI 3.01-4.33), had higher income (high income vs poor: PR 1.40, 95% CI 1.23-1.59), or had obesity (vs normal weight: PR 1.11, 95% CI 1.01-1.22) were more likely to search for health information on the web. Similar associations were observed among age, race and ethnicity, education, income, and the use of eHealth services. Patients on insulin were more likely to use eHealth services (on insulin vs no medication: PR 1.21, 95% CI 1.04-1.41). Conclusions Among adults with diabetes, HIT use was lower in those who were older, were members of racial minority groups, had less formal education, or had lower household income. Health education interventions promoted through HIT should account for sociodemographic factors.

Can Artificial Intelligence and Big Data Improve Gamified Healthcare Services and Devices?

Systems that aim to maintain and improve the health of citizens are steadily gaining importance. Digital transformation is having a positive impact on healthcare. Gamification motivates individuals to maintain and improve their physical and mental well-being. In the era of artificial intelligence and big data, healthcare is not only digital, but also predictive, proactive, and preventive. Big data and artificial intelligence techniques are called to play an essential role in gamified eHealth services and devices allowing to offer personalized care. This chapter aims to explore the possibilities of artificial intelligence and big data techniques to support and improve gamified eHealth services and devices, including wearable technology, which are essential for digital natives but also increasingly important for digital immigrants. These services and devices can play an important role in the prevention and diagnosis of diseases, in the treatment of illnesses, and in the promotion of healthy lifestyle habits.

eHealth and mHealth Development in Spain: Promise or Reality?

In the last decades, the use of Information and Communication Technologies (ICTs) has progressively spread to society and public administration. Health is one of the areas in which the use of ICTs has more intensively developed through what is now known as eHealth. That area has recently included mHealth. Spanish health system has stood out as one of the benchmarks of this technological revolution. The development of ICTs applied to health, especially since the outbreak of the pandemic caused by SARS Cov-2, has increased the range of health services delivered through smartphones and the development of subsequent specialized apps. Based on the data of a Survey on Use and Attitudes regarding eHealth in Spain, the aim of this research was to conduct a comparative analysis of the different eHealth and mHealth user profiles. The results show that the user profile of eHealth an mHealth services in Spain is not in a majority. Weaknesses are detected both in the knowledge and use of eHealth services among the general population and in the usability or development of their mobile version. Smartphones can be a democratizing vector, as for now, access to eHealth services is only available to wealthy people, widening inequality.

Placing equity at the heart of eHealth implementation: A qualitative pilot study

Background There is a growing urgency to tackle issues of equity and justice in the implementation of eHealth technologies. Methods Qualitative interviews were conducted with 19 multidisciplinary health professionals to explore the implementation and uptake of eHealth technologies in practice. Results were analysed using Nancy Fraser’s social justice framework to identify key dimensions and patterns of distribution, recognition, and participation in the implementation of digital health services. Results Health professionals reported that eHealth offered their clients a greater sense of safety, convenience, and flexibility, allowing them to determine the nature and pace of their healthcare, and giving them more control over their treatment and recovery. However, they also expressed concerns about the use of eHealth with clients whose home environment is unsafe. Application of Fraser’s social justice framework revealed that eHealth technologies may not always provide a secure clinical space in which the voices of vulnerable clients can be recognised and heard. It also highlighted critical systemic and cultural barriers that hinder the representation of clients’ voices in the decision to use eHealth technologies and perpetuate inequalities in the distribution of eHealth services. Conclusions To facilitate broad participation, eHealth tools need to be adaptable to the needs and circumstances of diverse groups. Future implementation science efforts must also be directed at identifying and addressing the underlying structures that hinder equitable recognition, representation, and distribution in the implementation of eHealth resources.

Readiness and Acceptance of eHealth Services for Diabetes Care in the General Population: Cross-sectional Study

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

Digital Citizenship in a Swedish Marginalised Neighbourhood

We investigate digital citizenship by exploring attitudes and experiences of digital inclusion and eHealth with data from a survey study based on face-to-face interviews in different languages, in a marginalised hard to survey neighbourhood. Through public eHealth services, people can exercise digital citizenship. We explore differences between the marginalised neighborhood and the national level, and among residents in the neighbourhood, with disaggregated data. The results show that the respondents in Skäggetorp report lower usage of the internet, lower access to smartphones, a somewhat lower usage of BankID, higher concern for surveillance, and a higher number of respondents feel excluded from digital society in comparison to the nationwide survey. The results in the disaggregated data show some differences in attitudes to and experience of digital inclusion among residents in Skäggetorp. We conclude that the studies of digital citizenship need to be broadened to address feeling included, social rights, and difference.

Profiles of eHealth Adoption in Persons with Multiple Sclerosis and Their Caregivers

(1) Background: Persons with multiple sclerosis (pwMS) are often characterized as ideal adopters of new digital healthcare trends, but it is worth thinking about whether and which pwMS will be targeted and served by a particular eHealth service like a patient portal. With our study, we wanted to explore needs and barriers for subgroups of pwMS and their caregivers when interacting with eHealth services in care and daily living. (2) Methods: This study comprises results from two surveys: one collecting data from pwMS and their relatives (as informal caregivers) and another one providing information on the opinions and attitudes of healthcare professionals (HCPs). Data were analyzed descriptively and via generalized linear models. (3) Results: 185 pwMS, 25 informal caregivers, and 24 HCPs in the field of MS participated. Nine out of ten pwMS used information technology on a daily base. Individual impairments like in vision and cognition resulted in individual needs like the desire to actively monitor their disease course or communicate with their physician in person. HCPs reported that a complete medication overview, additional medication information, overview of future visits and a reminder of medication intake would be very helpful eHealth features for pwMS, while they themselves preferred features organizing and enriching future visits. (4) Conclusions: A closer look at the various profiles of eHealth adoption in pwMS and their caregivers indicated that there is a broad and robust enthusiasm across several subgroups that does not exclude anyone in general, but constitutes specific areas of interest. For pwMS, the focus was on eHealth services that connect previously collected information and make them easily accessible and understandable.

Psychiatry in the Digital Age: A Blessing or a Curse?

Social distancing and the shortage of healthcare professionals during the COVID-19 pandemic, the impact of population aging on the healthcare system, as well as the rapid pace of digital innovation are catalyzing the development and implementation of new technologies and digital services in psychiatry. Is this transformation a blessing or a curse for psychiatry? To answer this question, we conducted a literature review covering a broad range of new technologies and eHealth services, including telepsychiatry; computer-, internet-, and app-based cognitive behavioral therapy; virtual reality; digital applied games; a digital medicine system; omics; neuroimaging; machine learning; precision psychiatry; clinical decision support; electronic health records; physician charting; digital language translators; and online mental health resources for patients. We found that eHealth services provide effective, scalable, and cost-efficient options for the treatment of people with limited or no access to mental health care. This review highlights innovative technologies spearheading the way to more effective and safer treatments. We identified artificially intelligent tools that relieve physicians from routine tasks, allowing them to focus on collaborative doctor–patient relationships. The transformation of traditional clinics into digital ones is outlined, and the challenges associated with the successful deployment of digitalization in psychiatry are highlighted.