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. 2025 Mar 19;25(1):1064.
doi: 10.1186/s12889-025-22082-y.

Catenation between mHealth application advertisements and cardiovascular diseases: moderation of artificial intelligence (AI)-enabled internet of things, digital divide, and individual trust

Syed Hassan Raza  1 , Uzma Norin  2 , Emenyeonu C Ogadimma  3 , Umer Zaman  4 , Amjad Ali Shah  2 , Shumaila Khan  5 , Hend Khalid Alkahtani  6 , Mohammed Alkhowaiter  7 , Sajid Ullah Khan  8
Affiliations

Catenation between mHealth application advertisements and cardiovascular diseases: moderation of artificial intelligence (AI)-enabled internet of things, digital divide, and individual trust

Syed Hassan Raza et al. BMC Public Health. .

Abstract

Background: World Health Organization (WHO) identified noncommunicable diseases as the foremost risk to public health globally and the cause of approximately 80% of premature deaths. However, Cardiovascular diseases account for most of these premature deaths and established threats to public health. Recently, digitization of health consultancy services through mHealth (e.g., mobile applications) using artificial intelligence (AI)-enabled Internet of Things has notably facilitated the accessibility of expert advice and continuous monitoring of Cardiac health on public health matters, making it more convenient for adoption in recent times. Nonetheless, scant attention has been paid to how digital media might encourage the adoption of digitally based health consulting services while accounting for the current IoT, Digital Divide, and Individual Trust conditions. Given this status quo, this study contributes to the body of literature by delving into an unexplored evaluation of the role digital media advertising plays in outlining the characteristics and effectiveness of AI-enabled IoT mHealth.

Method: The study used a cross-sectional online survey to collect data from 495 middle-aged adults.

Results: The findings showed that social influence, performance expectation, effort expectancy, and facilitating conditions are critical factors in predicting intention to use mobile health applications. While the advertisements of mobile health are effective in ingraining the perception of their better performance regarding evading cardiovascular diseases added with the Internet of Things is an effective tool in adopting mobile health applications.

Conclusion: The utilization of digital media to promote emerging elements like the AI-enabled Internet of Things in health consulting to counter noncommunicable diseases, e.g., cardiovascular disease, has not yet been thoroughly explored. Consequently, the effectiveness of these communication features promotion among middle-aged adults remains largely uncharted. This research examines how middle-aged adults respond to advertisements showcasing the AI-enabled Internet of Things in digital media. Drawing an analogy with a UTAUT-3 theory, this research investigates how digital media advertisement can effectively promote recently integrated AI-enabled Internet of Things mHealth consultation services. Remarkably, findings identified that trust in AI-enabled IoTs-based mHealth applications remained insignificant. However, the digital divide resulting from low digital literacy in the Global South, especially Pakistan, is the primary obstacle to adopting mHealth apps for digital health services. This study suggests organizations such as WHO, mHealth apps, and telemedicine service providers employ health messaging and instructional advertising to educate the public.

Keywords: Artificial intelligence; Digital media; Internet of things; Noncommunicable disease; Social media; UTUAT3; mHealth.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study was granted ethical approval by the Research Ethics Committee of the Institute of Media and Communication Studies, Bahauddin Zakariya University, Pakistan, and signed informed consent was obtained from the subjects 18 + years of age for data to be used for research purposes. Furthermore, all methods were carried out in accordance with relevant guidelines and regulations. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

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Measurement Model
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Structural model
See this image and copyright information in PMC

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