Your browser doesn't support javascript.
Assessing the factors that influence the adoption of healthcare wearables by the older population using an extended PMT model
Technology in Society ; : 102126, 2022.
Article in English | ScienceDirect | ID: covidwho-2042157
ABSTRACT
The present study aims to assess the intention of the older population to use healthcare wearable devices (HWDs) for wellness during life-threatening situations like COVID-19. The target population for the study was senior citizens (individuals aged above 60) living in Delhi and the national capital region. The respondents were aware that smartwatches could be used to monitor their health. Data from 534 respondents was collected using a structured questionnaire and nonprobability-based sampling method. The partial least squares structure equation model (PLS-SEM) was used to test the hypothesized model derived from the protection motivation theory (PMT) and constructs from previous studies on HWDs. Healthcare wearables offer new perspectives for gauging both health and technology-related dimensions. The present study is important as unlike existing studies, it discusses not only the utilitarian characteristics of HWDs but also their health-protective dimensions, which are crucial in times of life-threatening situations such as the COVID-19 pandemic. The findings indicate that there is a significant impact of both the protective and utilitarian dimensions of HWDs. The study assesses the perceived vulnerability and severity of the older population in COVID 19 and the intention to use HWDs to handle such health crises. The study confirms that perceived usefulness and information accuracy of HWDs, as well as self-efficacy, perceived severity, and perceived vulnerability of senior citizens are high during the COVID-19 pandemic, which significantly influences their intention to use HWDs.
Keywords

Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: Technology in Society Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: Technology in Society Year: 2022 Document Type: Article