Perceived ease of use and health literacy as determinants of mHealth app usage among older adults in India: a SEM approach

Abstract

Perceived Ease of Use (PEU), Health Literacy (HL), and Usage Behavior (UAOA) are three important categories that are the focus of this study, which examines the factors that influence older individuals in Pune, India, when using mobile health (mHealth) applications. The research, which was informed by Health Literacy theory and the Technology Acceptance Model (TAM), aimed to investigate how these characteristics affect an elderly metropolitan population's initial uptake and ongoing engagement with mHealth applications. An online survey link was sent to roughly 3479 prospective participants via a variety of outreach channels, such as social media sites constructs. Structural Equation Modeling (SEM) was used to analyze the data and test the proposed connections between PEU, HL, and UAOA. This methodological approach made it possible to evaluate several connected variables at once, providing a thorough picture of the factors impacting older individuals' use of mHealth in Pune. The results show that mHealth usage is considerably and favorably influenced by both PEU and HL, with HL being the more reliable predictor. Higher PEU scores demonstrated the significance of intuitive design, straightforward navigation, and low cognitive load, whereas higher health literacy was linked to increased confidence in utilizing app features and comprehending health information. The report also highlights the need for focused solutions by identifying enduring obstacles such generational digital divides, technology phobia, privacy concerns and personal referral networks, to start the data gathering process. The goal of this strategy was to reach as many older persons as possible and promote their involvement. 953 people out of the entire outreach answered the survey. After that, a thorough data purification procedure was started, which included checking for statistical outliers, duplicate entries, inconsistent responses, and incomplete submissions. 700 valid responses were kept for analysis following the implementation of these quality control procedures, offering a strong and representative sample for the goals of the study. 30 items on a five-point Likert scale made up the final survey instrument, which was intended to gauge participants' opinions on the three. These observations have the following two implications: In theory, they broaden TAM by incorporating HL into the context of senior citizens in poor nations. To encourage uptake, they advise politicians, healthcare providers, and app developers to give priority to user-friendly interface design, digital health literacy training, and localized content. Promotion in the community that uses family members and medical professionals as reliable influencers could increase consumption even further. In addition to providing a basis for future research examining longterm health outcomes, the effects of certain app features, and the role of social influence in maintaining engagement, this study increases knowledge of mHealth uptake among aging urban populations.