mHealth Advertisements and Cardiovascular Health: Navigating the Digital Landscape
The World Health Organization (WHO) identifies noncommunicable diseases (NCDs) as a leading global health threat, responsible for approximately 80% of premature deaths. Cardiovascular diseases (CVDs) are a significant contributor, representing a major public health concern. The increasing use of mHealth applications leveraging artificial intelligence (AI)-enabled Internet of Things (IoT) technologies offers new avenues for health consultancy and continuous cardiovascular monitoring, making expert advice more accessible. However, the impact of digital media advertisements on the adoption of these services, alongside the current environment of IoT, the digital divide, and individual trust, requires thorough investigation.
This study investigates the role of digital media advertisements in promoting AI-enabled IoT mHealth applications. The aim is to understand how middle-aged adults respond to these ads and how factors like the UTAUT-3 model, the digital divide, and individual trust influence their intention to adopt these services. A cross-sectional online survey was conducted with 495 middle-aged adults to collect data.
Key Findings:
The research findings highlight the importance of social influence, performance expectancy, effort expectancy, and facilitating conditions in predicting the intention to use mobile health applications. The study also found that while mHealth advertisements effectively convey the potential of these apps to mitigate cardiovascular diseases, and the Internet of Things is recognized as a useful tool, trust in AI-enabled IoT-based applications was found to be insignificant.
The primary obstacle to adopting mHealth apps in the Global South, particularly in Pakistan, is the digital divide stemming from low digital literacy.
This research suggests that the WHO, mHealth app developers, and telemedicine providers should emphasize educational health messaging and advertising to increase public awareness. The study also used the UTAUT-3 framework to look at how digital media advertisements can effectively promote recently integrated AI-enabled Internet of Things mHealth consultation services. Based on this model, this study tested several hypotheses. This study underscores the necessity for tailored communication strategies to address the specific challenges and opportunities observed within this context.
Public Health Challenges and the Role of Digital Health
The WHO recognizes NCDs as a critical global health concern, with CVDs being a primary cause of premature mortality, accounting for 32% of all deaths globally. These conditions, encompassing heart and blood vessel diseases, are often preventable through healthy behaviors, such as physical activity and avoiding tobacco and excessive alcohol consumption. The early identification of CVD through efficient monitoring is crucial for prompt intervention and counseling, thereby highlighting the significance of technology-driven health monitoring. Public health entities are increasingly exploring digital technologies to give monitoring and consultation services.
Digital health, a focus area for the WHO, involves the application of digital innovations to enhance health outcomes, including mHealth, eHealth, telehealth, AI, IoT, and big data. The digital health market is rapidly growing, expected to reach USD 504.4 billion by the close of 2025. It offers an accessible and affordable approach, especially for those with limited access to conventional healthcare, therefore, offering a crucial tool in attaining global development targets. The healthcare sector increasingly depends on digital technology, which includes consultations, diagnostics, treatments, health education, and continuous monitoring, specifically in developed regions. With a worldwide presence, mHealth apps which include AI-enabled IoT technologies (e.g., wearable devices) aid effective health data management and supervision. This integration is growing the applicability of mHealth by improving critical facets of public health.
Addressing Challenges and Opportunities
While mHealth and AI-enabled IoT technology grow, mobile and wireless technology has unparalleled potential in the Global South, specifically low- and middle-income countries, in order to address public health issues like inadequate vaccination. As in other areas of the world, the utilization of mHealth applications adds value because of their accessibility and ease of use. For example, SMS for Life, a text message initiative in Sub-Saharan Africa, is used for health reporting and monitoring. However, some issues are associated with the use of varied digital health interventions, such as mHealth and AI-enabled IoT devices, that can encourage CVD management. These technologies support self-care involvement and communication maintenance. The digital divide (e.g., individual’s perception of one’s capability of utilizing the technology) and trust are the central constraints in using digital health consultancy services in the Global South. The research identified technology savvy as among the most critical issues that diminish the adoption of digital health services. It also identified gender, home IT resources, and socioeconomic status as factors which can influence an individual’s digital divide perceptions.
Digital platforms like social networking sites have been employed for health messaging to heighten patient engagement in digital health consultancy services to overcome these challenges. A need exists to understand the opportunities and hurdles when participating in healthcare interventions.
This research assesses the factors that can incrementally determine the intention to employ digital health consultancy services by drawing on the framework of the UTUAT 3 model. The study evaluates the UTAUT-3 in understanding digital health adaptation and identifies the variables which shape the acceptability of the use of the digital media in healthcare, based on people involved in the field. This study explores the use of digital media and its impact on the UTAUT-3 paradigm. Results identified that trust in AI-enabled IoTs-based mHealth applications remained insignificant in the context of Pakistan.
Literature Review and Theoretical Framework
Several theoretical models, including the Technology Acceptance Model (TAM), Diffusion of Innovation Theory, and the Unified Theory of Acceptance and Use of Technology (UTAUT), explain the concepts of technological adoption and usage. The UTAUT model was advanced to include social influences, with UTAUT2 incorporating Hedonic Motivation (HM), Price Value (PV), and Habit. The UTAUT3 framework, used in this study, extends this model by incorporating eight determinants of technology acceptance, with individual trust as an added new moderator.
mHealth applications use mobile devices to support health services, improving the efficacy of healthcare information delivery. The mHealth apps market is expected to surpass $111 billion by 2025. While adoption rates are low, the successful adoption of these apps relies on how quickly users can adopt and retain the apps. mHealth apps in this study offer advice, reminders, and tracking of health data. These apps increase [1] self-knowledge, [2] the effectiveness of healthcare services, and [3] the accessibility of health consultation. However, sustained usage often wanes after initial adoption, necessitating inquiry into the factors influencing long-term engagement. The user’s sustained usage of mHealth apps includes cognitive and emotional factors like healthcare self-efficacy and perceived risks.
Key Variables in Technology Acceptance
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Performance Expectancy (PE): This reflects an individual’s belief that employing specific technologies will simplify task completion. The healthcare sector utilizes mHealth apps, and those using these apps can get health consultations, providing efficient communication. Past research has observed a positive link between PE and a person’s intent to utilize new technology. In the context of cardiovascular diseases, PE helps develop satisfying health experiences.
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Effort Expectancy (EE): This indicates the perceived ease of using technological advancements in products and services. A user’s EE substantially impacts their decisions involving digital health, such as the adoption of AI-driven chatbots. For those in the context of CVDs, it can be hypothesized that less effort will be a facilitator.
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Social Influence (SI): This refers to an individual’s perception of what significant people in their social circle think if they embraced new technology. Most individuals are influenced by the viewpoints of their family and friends. Social Influence is among the most critical factors in the usage of mHealth apps. In collectivist societies, individuals depend on each other. It can be postulated that social influence will be a critical factor in mHealth applications.
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Facilitating Conditions (FC): FC is the degree to which an individual perceives access to the necessary infrastructure to support implementing technological advancement. In digital health consultancy services, using mHealth is supporting the degree of technical support available to an individual to use mHealth applications. People will need to be offered sufficient facilitating conditions to adopt the mHealth consultation services.
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Price Value (PV): This reflects an individual’s cognitive trade-off of the perceived benefit and the expense of purchasing that innovative product. The PV can affect middle-aged individuals vulnerable to CVDs. For this reason, the assumption here is that mHealth is a paid service.
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Personal Innovativeness (PI): This is a person’s inclination to test new technologies and is determined by the relationship between technology and the level of receptiveness to innovation. Individuals with greater innovativeness enjoy change and are likelier to obtain technological product information.
AI, the Internet of Things, and Moderators
The Internet of Things (IoT) is a modern technology that can connect all things to a network without involving anyone. The AI-enabled Internet of Things play an important role in the enhanced delivery to middle-aged individuals vulnerable to cardiovascular diseases. The use of IoT can connect and link physical objects to the Internet. This enables the processing and communication of social networks and mobile devices. The Internet of Things (IoT) is a three-layer interactive process connecting people with networks, intelligent objects, and operational intelligence.
IoT applications are used in various sectors, including telecommunications and electricity. Artificial intelligence increases the efficiency of these technologies. Various studies have examined the hurdles associated with implementing technology. mHealth applications offering AI-enabled IoT might intensify the link between advertisement and digital service adoption. Positive attitudes and beliefs about trust play a role in shaping the intention to trust. Trust stands out as the most crucial factor in people embracing an electronic health system.
Methods and Data Collection
The study used an online cross-sectional survey to gather data from middle-aged adults aged 40 to 60 in Pakistan. This was suitable for validating the proposed hypotheses based on digital platforms for health services to verify the AI-enabled IoT for monitoring and predicting heart health. Data was collected from 495 respondents from July 2023 to October 2023 using Google Forms and circulated through digital platforms like Facebook in order to find the study’s target population. These applications mainly use digital health platforms for their promotion, therefore the use of digital platforms to collect data is appropriate. Subjects were asked a filter question to verify their age group and were also asked to consent to participate in the study. Those who agreed were then introduced to the phenomenon of mobile applications for health consultancy. The ethical approval of the Research Ethics Committee of the Institute of Media and Communication Studies, Bahauddin Zakariya University, Pakistan, was granted for the study, and consent was obtained. All methods were carried out per relevant procedures and regulations.
Measurement Scales
- Performance expectancy (four items) [2]
- Effort expectancy (three items) [3]
- Facilitation conditions (three items) [4]
- Social influence (three items) [5]
- Personal innovativeness (three items)
- Price value (three items)
- mHealth advertisements (four-item scale)
- Intention to use mHealth apps (3-item scale)
- AI-enabled Internet of Things (3-items)
- Individual trust (3-item scale)
- Digital divide (3-item scale)
Eight content experts (academicians, IT professionals, advertising, and IT) looked at the questionnaire before the main study. A pilot study was performed using fifty students. The data was then analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).
Results of Analysis
The results of the path analysis revealed a positive influence of digital health apps advertisement on performance expectancy, with H1 accepted. The findings also showed that performance expectancy, facilitating conditions, effort expectancy, and social influence directly influenced the intention to use digital health apps (H2, H3, H4, and H5 were accepted). The analysis showed no direct influence of personal innovativeness and price value in the intention of digital health use, leading to H6 and H7 not being supported. The analysis then revealed that the Internet of Things and the digital divide moderate the relationship between digital health apps advertisements and performance expectancy, leading to H8 and H9 being accepted. However, trust was not found to have a moderating influence; thus, H10 was rejected.
Discussion and Implications
These AI-and IoT-based mHealth applications aid from information management to effectively delivering services to individuals. It is important to note some issues regarding the use of mHealth in middle-aged adults to avoid cardiovascular diseases. Advertisements for mHealth applications are essential in order to introduce these applications to vulnerable age groups. To illustrate, these mHealth applications are useful for consultancy services.
The results show that the primary constraint is the digital divide. To facilitate adoption of mHealth solutions, appropriate levels of digital literacy need to be established. This study suggests that health messaging can educate the targeted age group. While mobile devices have intensified over the past decade, their use to address public health issues needs attention.
This study offers empirical evidence on the key factors driving mHealth adoption, contributing to maximizing digital health consultancy for the CVDs. A theory-testing effort was achieved by assessing the UTAUT-3 model’s reliability by using empirical data to validate the study’s model. Overall, the results underscore the need for appropriate customer experience, confidence, and skill. The findings are helpful for instructors, policymakers, and administrators to develop their online strategy and can increase the acceptance of digital health consultancy services. Digital health consultancy can address common issues such as travel concerns, financial limitations, and time constraints. Digital health consultancy promotes information delivery across time and space.
Limitations and Future Directions
Due to time and scope constraints, the study has inherent limitations. Only the individual perceptions regarding the adoption of the mHealth applications have been examined, and future studies should consider other user perceptions. Longitudinal studies, integrating data from patients and doctors, may also be useful.
Conclusion
AI- and IoT-enabled mHealth apps have transformed healthcare delivery. This study emphasizes the significance of addressing the digital divide and the importance of educational health messaging and advertising for promoting these solutions. The results reveal that social influence, performance and effort expectancy, and facilitating conditions are critical to mHealth adoption. To maximize the acceptance of digital health services, a multifaceted approach that promotes the benefits, while dealing with the digital divide, is needed. The study offers insights for healthcare providers looking to expand digital interventions. The findings presented further highlight the importance of mHealth apps in supporting the health sector.
