Abstract

MyBodyHealthScan Pro, a type of wearable health device, will become widely accepted, used, and available. It will be a useful wearable tool for scanning and gaining insight into the health of wearers of the device without a hospital visit in the very near future. This is an integration of the common health wearable devices and a body health scanner. In ten years, this device will dominate the health wearable industry. It is, therefore, necessary to promote its acceptance, use, and reasonable availability and reduce the barrier to the rapid advancement in technology and healthcare.

Introduction

Health wearable devices are devices designed to be worn on the body. They are portable electronic devices and are used to monitor and collect health-related data. These devices have gained significant popularity in recent years due to their potential to improve health and wellness by providing real-time information about various physiological parameters (Lu et al., 2020).

Integrating a body health scanner, which can completely scan an individual’s body, with a health wearable device would be a groundbreaking advancement in the field of medical and health technology. This integration would allow users to obtain detailed and real-time information about their health status, enabling proactive management of their well-being.

Scope

The body health scanner named MyBodyHealthScan Pro will be equipped with advanced sensors such as spectrometers, infrared sensors, and high-resolution cameras, which can capture detailed data about various health parameters. These may include body composition, skin health, hydration levels, vital signs, and even early signs of certain diseases. The wearable device acts as a hub, collecting data from the body health scanner through wireless connectivity (Haghi et al., 2017).

It is designed with an intuitive and user-friendly mobile app interface to visualize data collected from body scans, historical trends of body scans, and personalized recommendations. The algorithm implemented for real-time data processing will be top-notch for accurate and meaningful insight into an individual’s health. This will be protected with end-to-end encryption to secure the data collected and during processing of the data.

One of the limitations envisaged for this wearable is the accuracy of the sensors. Despite advancements, sensors used in wearables may still have limitations in terms of accuracy, especially in comparison to medical-grade devices. Inaccurate readings can lead to misinformation and impact user trust in the device.

Purpose and Goals

MyBodyHealthScan Pro aims to revolutionize personal health management by integrating advanced sensors and cutting-edge technology to measure, record, and analyze body composition, vital signs, skin health assessment, and hydration level measurement. This integration lets users obtain detailed and real-time information about their health status, enabling proactive management of their well-being. Most wearables offer wireless connectivity options such as Bluetooth, Wi-Fi, or cellular technology. These allow data synchronization with smartphones, tablets, or computers. Users can view their health data in real time, set goals, and receive notifications and alerts (Smuck et al., 2021).

They are typically paired with companion apps installed on smartphones or tablets. These apps provide user-friendly interfaces to display health data, track progress, set goals, and offer personalized recommendations. Health monitoring and fitness tracking, health insights, and predictive analytics data collected by wearables can also be stored in the cloud, allowing users and healthcare professionals to access historical data for in-depth analysis.

Supporting forces for MyBodyHealthScan Pro

Technological Advancements

Advances in Sensors and Data Processing: Ongoing advancements in sensor technologies, including improvements in accuracy, miniaturization, and cost-effectiveness, enhance the capabilities of body health scanning wearables (Zheng, 2014). Similarly, developments in data processing algorithms, including artificial intelligence and machine learning, enable more precise and insightful analysis of health metrics, augmenting the device's overall functionality and user experience.

Increased Health Awareness and Focus on Prevention

The growing health consciousness of society has increased the awareness of the importance of health and wellness. These have motivated individuals to actively monitor and manage their well-being. Wearable devices that offer comprehensive health scanning cater to this growing demand, providing users with the tools to make informed decisions about their lifestyle, diet, and exercise routines. Furthermore, the focus of healthcare providers and organizations is increasingly on preventive measures to reduce the burden on healthcare systems. Body health scanning wearables align with these initiatives, enabling early detection of health issues and promoting proactive health management, ultimately reducing the prevalence of chronic diseases.

Economic

It is estimated that the wearable technology market will grow by about 13.06% from 2023 to 2032, with global sales of $138 in 2023 to $492 in 2032.

Challenges

Privacy and Security Concerns

Collecting sensitive health data raises concerns about user privacy. Users may be hesitant to use health scanning wearables due to fears of data breaches, unauthorized access, or misuse of their health information. Also, wearables are susceptible to cybersecurity threats such as hacking and data theft. It is, therefore, critical to ensure that robust security measures exist to prevent unauthorized access, theft, and use of user data.

Regulatory and Ethical Challenges

Health scanning wearables may need to comply with stringent regulations and certifications, which vary across different countries and regions. Navigating complex regulatory landscapes can pose challenges and delays in the development and deployment of these devices.

Another challenge to developing and adopting this innovation is the ethical use of health data, especially in research and data analysis. Balancing the need for data-driven insights with ethical considerations related to user consent, data anonymization, and transparency has always been a complex challenge (Canali et al., 2022).

Methodology

The Delphi Method, also known as the Delphi technique, a qualitative approach to data analysis, will be used for this plan. Although this technology seems like one that has been accepted by society, a thorough methodology that involves the selection of a panel of experts in fields such as wearable technology, healthcare, data security, and user experience design will be adopted. The experts are provided with a detailed overview of the sociotechnical plan for the body health scanning wearable devices. A series of online surveys where the experts anonymously offer their opinions and feedback on areas like technological advancements, user engagement strategies, resource allocation, regulatory compliance, and competitive analysis will be conducted. The responses from each round are collated and shared among the experts without revealing the respondents. This will lead to subsequent surveys until a consensus is reached.

Analytical Plan

This plan will only be recognized as a success when impact assessments of user experience are conducted. This will be in the form of regular surveys of user experience, app usability, and the effectiveness of personalized recommendations. Also, the effectiveness of the healthcare collaboration involving the secure and seamless integration of the wearables with the Electronic Health Records (EHR) will be measured. This will include the ability to share their data with the healthcare facilities' EHR systems to facilitate seamless information exchange, the ability of users to share their scanned data securely with healthcare professionals for remote consultations and expert guidance, and the usability of the data received from MyBodyHealthScan Pro.

Anticipated Results

It is anticipated that in the next 10 -15 years, this wearable will be relied upon heavily by the healthcare industry. This invention, being more involved in preventive and early detection rather than palliative medicine, will be advocated for and used by the healthcare industry and will reduce the need to send patients for several different scans and wait for results. This will provide a lead time for treating serious ailments and better outcomes.

Social change refers to the way human interactions and relationships transform cultural and social institutions over time, having a profound impact on society. Social change can occur gradually or rapidly, and it can be driven by a variety of factors, including technological innovations, natural disasters, population growth, and social movements (de la Sablonnière, 2017). Social change is a complex and multifaceted phenomenon that can have a profound impact on society. It can transform cultural and social institutions, cultural norms, and personal relationships, and it can have both positive and negative influences on society.

Social change could come as an institutional change, in which case it helps in the transformation of social institutions such as the legal system and educational and religious organizations (Vadrot, 2020). This has been expressed variously as workers’ rights, civil rights, women’s rights, and other social movements, which have resulted in profound changes to policies and laws. Social change has also been implicated in personal and cultural changes. Changes to technologies have changed the ways people interact with one another.

Conclusion

Healthcare and the cost of healthcare, even with outcomes that are other than desired, are astronomical and painful to bear. MyBodyHealthScan Pro will help to reduce that and improve preventative and early detection. This will contribute to lower healthcare costs and better and more desirable health outcomes.

Diffusion of innovation refers to the process by which new ideas, products, or services spread through a population or social system. According to Cool et al. (1997), in an organization, innovation diffusion can occur through various channels, including formal and informal communication, training programs, and leadership support. By understanding the diffusion process, organizations can effectively implement new ideas, products, or services to improve their operations and achieve their goals.

This means organizations should understand that diffusion of innovation within an organization is a complex process usually involving varying stages and steps of awareness, interest, evaluation, trial, and adoption. This can be achieved through formal and informal communication channels, training programs, and leadership support (Mohammadi et al., 2018).

The following phases are crucial to a successful diffusion of innovation (Dearing & Cox, 2018).

Awareness

The first stage of innovation diffusion is awareness. The organization must make individuals become aware of the new idea, product, or service. This can occur through formal communication channels, such as company-wide emails or meetings, or informal channels, such as word-of-mouth communication.

Interest

Once individuals become aware of the innovation, they must become interested in it. This can occur through training programs, demonstrations, or other forms of education that highlight the benefits of the new idea or invention.

Evaluation

After individuals become interested in the innovation, they must evaluate it to determine if it is valuable to them and the organization. This can occur through pilot programs or other forms of testing that allow individuals to try out the innovation before committing to it.

Trial

If individuals determine the innovation is valuable, they will try it out. This can occur through small-scale or phased implementation or other forms of experimentation that allow individuals to test the innovation in a controlled but stable environment.

Adoption

Finally, if the innovation is successful during the trial phase, it will be adopted by the organization. This can occur through formal implementation, such as the integration of the innovation into existing processes and procedures, or informal implementation, such as the adoption of new behaviors or practices.

Areas of Future Research

The field of health wearable technology is continuously evolving and this opens numerous opportunities for future research and innovation. Researchers should xplore how wearable data can be leveraged to gain insights into users' behavior, facilitating the development of interventions and nudges to promote healthier habits.

It may also be fascinating to investigate the effectiveness of personalized interventions based on wearable data, including personalized fitness plans, diet recommendations, and stress management techniques.

References

Canali, S., Schiaffonati, V., & Aliverti, A. (2022). Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness. PLOS digital health, 1(10), e0000104. https://doi.org/10.1371/journal.pdig.0000104

Cool, K. O., Dierickx, I., & Szulanski, G. (1997). Diffusion of Innovations within Organizations: Electronic Switching in the Bell System, 1971-1982. Organization Science, 8(5), 543–559. http://www.jstor.org/stable/2635221

de la Sablonnière, R. (2017). Toward a Psychology of Social Change: A Typology of Social Change. Frontiers in Psychology, 8, 397. https://doi.org/10.3389/fpsyg.2017.00397

Dearing, J.W. & Cox, G.C. (2018). Diffusion Of Innovations Theory, Principles, And Practice. (2018). Health Affairs, 37(2), 183-190. https://doi.org/10.1377/hlthaff.2017.1104

Haghi, M., Thurow, K., & Stoll, R. (2017). Wearable Devices in Medical Internet of Things: Scientific Research and Commercially Available Devices. Healthcare informatics research, 23(1), 4–15. https://doi.org/10.4258/hir.2017.23.1.4

Lu, L., Zhang, J., Xie, Y., Gao, F., Xu, S., Wu, X., & Ye, Z. (2020). Wearable Health Devices in Health Care: Narrative Systematic Review. JMIR mHealth and uHealth, 8(11), e18907. https://doi.org/10.2196/18907

Mohammadi, M. M., Poursaberi, R., & Salahshoor, M. R. (2018). Evaluating the adoption of evidence-based practice using Rogers's diffusion of innovation theory: a model testing study. Health promotion perspectives, 8(1), 25–32. https://doi.org/10.15171/hpp.2018.03

Smuck, M., Odonkor, C. A., Wilt, J. K., Schmidt, N., & Swiernik, M. A. (2021). The emerging clinical role of wearables: factors for successful implementation in healthcare. npj Digital Medicine, 4(1), 45. https://doi.org/10.1038/s41746-021-00418-3

Vadrot, A. B. M. (2020). Re-thinking the conditions for social change and innovation. Innovation: The European Journal of Social Science Research, 33(1), 1-3. https://doi.org/10.1080/13511610.2020.1713455

Zheng, Y. L., Ding, X. R., Poon, C. C., Lo, B. P., Zhang, H., Zhou, X. L., Yang, G. Z., Zhao, N., & Zhang, Y. T. (2014). Unobtrusive sensing and wearable devices for health informatics. IEEE transactions on bio-medical engineering, 61(5), 1538–1554. https://doi.org/10.1109/TBME.2014.2309951

Search This Blog

Beyond me thoughts

Final Sociotechnical Plan MyBodyHealthScan Pro