[Systematic review of digital technology acceptance in older adults. Perspective of TAM models]

In this study, a systematic review of researches published about the determining factors in the intention of the use of devices and digital technology in older adults has been carried out. The technology acceptance model is the framework used. The main result of the analysis of 60 scientific articles published between 2010 and 2020 has been summarized after a bibliographic research and a subsequent selection process in the most important bibliographic databases: Web of Science (n=45), Scopus (n=66) and Google Scholar (n=224). It has been proved the predominance of quantitative studies with a prevalence of study factors that associate the intention to use technology with: Facilitating conditions, experience, health, social support, emotions, perceived enjoyment, perceived satisfaction in using technology, anxiety, perceived risk, motivation, cost, subjective norm and social influence. The results of the systematic review allow us to conclude the urgent need to incorporate new research on the identification and influence of these factors that stand between older adults and technology, as possible barriers or facilitators of use.

Factors in the 4-week Acceptance of a Computer-Based, Chronic Disease Self-Monitoring System in Patients with Type 2 Diabetes Mellitus and/or Hypertension

BACKGROUND

Health information technology (HIT) interventions developed to support patients' self-care for chronic diseases have become popular, but people may not always accept and sustain their use.

INTRODUCTION

This study examined factors that affected patients' acceptance of a computer-based, chronic disease self-monitoring system over a 4-week period.

MATERIALS AND METHODS

A research model was developed to test the relationships between the perceived usefulness, perceived ease of use, attitude, and subjective norm and the patients' behavioral intention to use the system (i.e., acceptance). Data were collected with surveys of 42 patients with type 2 diabetes mellitus and/or hypertension at baseline, 2 weeks after implementation, and 4 weeks after implementation. Path analysis was used for model testing.

RESULTS

Perceived usefulness affected behavioral intention indirectly at 2 weeks and directly at 4 weeks; perceived ease of use affected behavioral intention indirectly at 2 and 4 weeks; attitude directly affected behavioral intention at 2 weeks; and subjective norm affected behavioral intention indirectly at 2 weeks and directly at baseline and at 4 weeks.

CONCLUSIONS

Patients' acceptance of HIT is affected by the factors proposed in our research model. It is suggested that healthcare stakeholders consider and address the effects of these factors and their variations over time before implementing HIT.

Investigating the preferences of older people for telehealth as a new model of health care service delivery: A discrete choice experiment

Introduction Telehealth approaches to health care delivery can potentially improve quality of care and clinical outcomes, reduce mortality and hospital utilisation, and complement conventional treatments. However, substantial research into the potential for integrating telehealth within health care in Australia, particularly in the provision of services relevant to older people, including palliative care, aged care and rehabilitation, is lacking. Furthermore, to date, no discrete choice experiment (DCE) studies internationally have sought the views and preferences of older people about the basic features that should make up a telehealth approach to these services. Methods Using a DCE, we investigated the relative importance of six salient features of telehealth (what aspects of care are to be pursued during telehealth sessions, distance to the nearest hospital or clinic, clinicians' attitude to telehealth, patients' experience of using technology, what types of assessments should be conducted face-to-face versus via telehealth sessions and the costs associated with receiving telehealth). Data were obtained from an online panel of older people aged 65 years and above, drawn from the Australian general population. Results The mean age for 330 study participants was 69 years. In general, individuals expressed strong preferences for telehealth services that offered all aspects of care, were relatively inexpensive and targeted specifically at individuals living in remote regions without easy access to a hospital or clinic. Participants also preferred telehealth services to be offered to individuals with some prior experience of using technology, provided by clinicians who were positive about telehealth but wanted all or some pre-telehealth health assessments to take place in a hospital or clinic. Preferences only differed by gender. Additionally, respondents did not feel that telehealth led to loss of privacy and confidentiality. Discussion Our findings indicate a preference amongst respondents for face-to-face pre-telehealth health assessments and, thereafter, a comprehensive telehealth model (in terms of services offered) targeted at those with some technological know-how as a substitute for attendance at hospitals and clinics, especially where these health facilities were far away from older people's homes. The findings may be usefully incorporated into the design of future telehealth models of service delivery for older people.

An Exploratory Study of Home Healthcare Robots Adoption Applying the UTAUT Model

The home healthcare initiative is aimed to reduce readmission costs, transportation costs, and hospital medical errors, and to improve post hospitalization healthcare quality, and enhance patient home independency. Today, it is almost unimaginable to consider this initiative without information technology. Home healthcare robots are one of such emerging technologies. Several robots have been developed to facilitate home healthcare such as remote presence robots (e.g., RP2) and Paro. Most previous research in this area has focused on technology and implementation issues of home healthcare robots, but ignored the factors that influence their adoption. To address the limitation, the current research applied and extended the UTAUT model to the home healthcare domain. The model was tested using survey questionnaire. The empirical results not only confirmed the effects of some constructs from the original UTAUT model but also identified perceived security as a new factor that directly affects usage intention of home healthcare robots. In addition, effort expectancy did not show a direct effect but an indirect effect through performance expectancy on usage intention. Several practical and theoretical implications are also discussed.