Factors that predict the acceptance and adoption of smart home technology by seniors in Australia: a structural equation model with longitudinal data.

Smart Home Technology presents an exciting opportunity to support seniors living independently in their homes. Despite widespread interest in Smart Homes, seniors' readiness to adopt Smart Home Technology is low. To determine the factors underpinning Australian seniors' acceptance and adoption of Smart Home Technology using an extended UTAUT model that includes Trust, Resistance to Change and Technology Anxiety. A longitudinal study was conducted to validate the proposed model prior to and after the implementation of a pilot Smart Home Modification program for seniors. Structural Equation Modeling has been applied to test the proposed hypotheses using a sample of 60 seniors in regional Australia. Perceived Usefulness is an important predictor of Smart Home Technology adoption by seniors. Trust was found to indirectly predict adoption of Smart Home Technology via Perceived Usefulness. This study showed that Perceived Usefulness and Trust are critical factors for the acceptance and use of SHT by seniors, validating the extension of UTAUT with a Trust factor. This makes a unique theoretical contribution to the literature with implications for aged care providers and policymakers to consider seniors' perceived usefulness and trust in the design, development, and implementation of Smart Home solutions.

Smart home technology to support older people's quality of life: A longitudinal pilot study.

AIM: This pilot study aimed to explore the impact of Smart Home technology to support older people's quality of life, particularly for those who live alone. BACKGROUND: There has been an increased interest in using innovative technologies and artificial intelligence to enable Smart Home technology to support older people to age independently in their own homes. METHODS: This study used a pre-and post-test design. The seven item Personal Wellbeing Index was used to measure participants' subjective quality of life across seven quality of life domains. Participants (n = 60) aged between 68 and 90 years (M = 80.10, SD = 5.56) completed a 12-week personalised Smart Home technology program. RESULTS: Approximately half of the participants lived alone (48.3%). Participants' quality of life significantly increased (p = 0.010) after Smart Home use. Two domains, "achieving in life" (p = 0.026) and "future security" (p = 0.004), were also significantly improved after participating in the Smart Home technology program. Improvements in quality of life did not vary as a function of living arrangement (all ps > .152, all η p 2  > .00). CONCLUSION: The current study provides preliminary evidence for the role of Smart Home technology in supporting older people's quality of life, particularly their sense of achieving in life and future security.

Critical disease burdens of Australian adults with cystic fibrosis: Results from an online survey.

BACKGROUND: The objective of this study was to conduct a web-based questionnaire to investigate self-reported phenotypes and disease burdens of individuals living in Australia and diagnosed with cystic fibrosis (CF) using a case-control study design. METHODS: An online questionnaire was distributed to individuals with CF and healthy control subjects. Overall health rating, medications, family history, education, clinical indicators of disease, and symptoms, including their severity and frequency, were evaluated. RESULTS: There was a total of 119 respondents consisting of 59 people living with CF and 60 controls. The CF cohort had significantly lower tertiary educational levels compared to controls. The analysis specific to the CF cohort depicted a significant correlation between the frequency of hospitalizations and the level of education in the CF cohort. Of the 26 self-reported symptoms of CF that were analyzed, 14 were significantly higher in the people living with CF. The CF cohort reporting symptoms of chronic pain (25%) described an increase in the burden of disease, depicting a 30% longer mean hospitalization, increased consumption of medications and significant relationships with four other symptoms, including muscle aches, digestive issues, pancreatic insufficiency, and abdominal swelling. CONCLUSIONS: The nationwide survey identified a diverse range of clinical manifestations experienced by the Australian CF population. Chronic pain, linked to aging and the changing landscape of disease, was a significant indicator of the burden of disease. A comprehensive understanding of the phenotypic profiles and symptom variability will contribute to future research and provide insights into the impacts of disease and the burden of therapy, particularly in children, at the start of their health journey.