ECEP-133 Health and Wellness Practice

Introduction 

Wearable technology have the potential to provide ground-breaking solutions for healthcare issues. Patient management and illness management are two more applications for wearable devices. Wearable apps have the potential to have a direct influence on clinical decision-making. Some think that wearable technology, such as patient rehabilitation outside of hospitals, have the potential to increase the quality of patient care while simultaneously lowering the cost of treatment (Daffern et al., 2018). When it comes to research, the large amount of data created by wearable devices presents both a difficulty and an opportunity for those who hope to apply more artificial intelligence (AI) approaches to this data in the future. The majority of wearable technologies are still in the early phases of development. Wearable technology continues to face challenges in terms of consumer adoption, security, ethics, and big data problems, all of which must be addressed in order to improve the usability and functionality of these devices for practical use (Müller and Hein, 2019). Wearable technologies allow for the continuous monitoring of human physical activities and behaviours, as well as physiological and biochemical data, over the course of a person's day. With the use of electrocardiogram (ECG), ballistocardiogram (BCG), and other equipment, the most often recorded data includes vital indicators such as heart rate, blood pressure, and body temperature, as well as blood oxygen saturation, posture, and physical activity. Wearable picture or video equipment may be able to give extra clinical information in some situations (Smets et al., 2018). A wearable device is one that may be attached to a variety of items like shoes, eyeglasses, earrings, clothes, gloves, and watches. Wearable gadgets may potentially evolve to include skin-attachable devices in the future. It is possible to incorporate sensors into the surroundings, such as chairs, vehicle seats, and beds. When collecting information, a smartphone is often used to transfer it to a distant server where it may be stored and analysed. There are two primary types of wearable devices that are used to analyse gait patterns and they are described here. Accelerometers, multi-angle video recorders, and gyroscopes are some of the technologies that have been created to assist healthcare practitioners in monitoring walking patterns. A variety of other health-related gadgets have been created, including on-wrist activity monitors (such as the Fitbit) as well as mobile phone applications and add-ons. When performing gait assessment activities in diverse settings, wearable devices and data analysis algorithms are frequently utilised in conjunction with one another (Douglas and Cunningham, 2008). The future of smartwatches is bright since it offers up a plethora of opportunities for the healthcare system. It may also be implemented into artificial intelligence systems. The advancement of artificial intelligence may result in a major improvement in the quality of medical services provided. The analysis of patients' medical histories is thousands of times faster with artificial intelligence than it is with human intelligence. Healthcare workers no longer have to go through stacks of paperwork to determine a patient's medical history (Pingo and Narayan, 2019). Simply put, they can make advantage of the capabilities of artificial intelligence. Several experts believe that, in the near future, smartwatches will be the major technology used for medical examinations. Patients' continuous data from those devices will be available to healthcare professionals, who will be able to keep it in their systems for future analysis using artificial intelligence (AI). If smartwatches can be successfully incorporated with artificial intelligence, it would make healthcare tasks significantly easier. In addition, a significant portion of the population will receive routine medical examinations on time. Instead, individuals may overlook the need for medical checks, but the wearable technology will ensure that your health data is constantly transmitted on time to healthcare experts.

Wearable technology have the potential to provide ground-breaking solutions for healthcare issues. In this study, we did a review of the literature on the use of wearable technology in the hospital setting. Some wearable technology applications, such as weight control and physical activity monitoring, are intended to aid in the prevention of disease and the preservation of health. Patient management and illness management are two more applications for wearable devices (Denecke et al., 2019). The wearable apps have the potential to have a direct influence on clinical decision-making. Some think that wearable technology, such as patient rehabilitation outside of hospitals, have the potential to increase the quality of patient care while simultaneously lowering the cost of treatment. Large amounts of data created by wearable devices present both a difficulty and an opportunity for academics who want to use artificial intelligence algorithms to analyse the data in the future.

In order to assess their patients' health and well-being, medical doctors may request access to information about them from their patients. Adding this information to a database will result in the generation of large amounts of data. Data leaking is always a problem when dealing with large amounts of data. Commercial enterprises and financial institutions are also subject to security breaches, which can occur even when users are aware of the risks. The health indices of users are stored in the wearables database inventory. As a result, the amount of harm caused by information leaking varies depending on the user (Miele and Tirabeni, 2020). Wearables that are continually linked offer a potential security hole that hackers and fraudsters may use to their advantage. Obtaining critical private information, such as petition information, private photographs and videos, bank information, and text messages.

Aim 

The present study aims to investigate the use of wearable in health and wellbeing.

Objective 

• To evaluate the role wearable in healthcare and wellbeing
• To evaluate the recent development in the area of wearable for healthcare and wellbeing of the patient
• To provide recommendations how wearable can be used in healthcare practice for the wellbeing of the patients

Literature Review 

It was discovered in the study conducted by (Papa et al., 2020) that, in accordance with the United Nations Sustainable Development Goal No. 3 (SDG – Goal 3), it is essential to ensure health and well-being across all ages for sustainable development, and that this can only be achieved through effective and continuous healthcare monitoring. However, despite the fact that healthcare is inexpensive in India and other third-world nations, healthcare monitoring is substandard when compared to other countries in the globe. The worldwide healthcare smart wearable healthcare (SWH) devices market is anticipated to grow at a compound annual growth rate (CAGR) of 5.6 percent over the next five years, and it is expected to reach 25 billion dollars by 2020. (GVR Report, 2016). Some of the key causes driving this development appear to be the increasing prevalence of lifestyle illnesses, a sedentary lifestyle, hectic work schedules, technical improvements in healthcare monitoring equipment, and the rising use of remote gadgets. Abbott Laboratories, Philips Healthcare, Life Watch, GE Healthcare, Omron Healthcare, Siemens Healthcare, and Honeywell International Inc., to name a few of the main companies in this area. In spite of the fact that healthcare monitoring devices are predicted to be technologically innovative and to provide both basic and advanced health care monitoring features, and that they are available in a variety of price ranges based on the features, we wanted to empirically investigate the attitude toward adoption of such devices in India. When it comes to healthcare monitoring, India has always taken an extremely casual approach. What would be the elements that would influence the adoption of SWH devices in such a situation? When used properly, remote health monitoring can improve the quality of health administration while also lowering the overall cost of human services. This is accomplished by avoiding unnecessary hospitalizations and ensuring that individuals who require critical attention receive it as soon as possible. This empirical research will give a thorough understanding of how these wearable Internet of Things devices might usher in a revolution in the healthcare business if carried out. The report would also discuss the future prospects of Internet of Things devices in this industry, as well as how the likelihood of increasing utilisation may be enhanced over time. Although the implications of wearable GPS tracking devices are still poorly understood, according to a study conducted by Jones, Marshall, and Denison (2016), these devices have become commonplace coaching aids across professional field sports in order to improve sports performances and reduce injury rates. To investigate how British Super League teams use wearable GPS technology, as well as to investigate the dominant 'truth' that promotes surveillance technologies as being "universally beneficial" to athlete sports performance, health, and well-being, the disciplinary analysis of Michel Foucault was used in conjunction with a case study. The information in this study was gathered through semi-structured interviews with three performance analysts/strength and conditioning coaches from three different Super League clubs located around the northern hemisphere. Participants admitted that data supplied by wearable GPS devices is frequently ignored, despite the fact that it was created expressly to safeguard athletes' health and well-being. When GPS data is used to normalise and force players into complying with potentially harmful physical and psychological demands of a professional playing career, it is referred to as a 'disciplinary tool.' Importantly, the usage of wearable GPS devices was consistently and thoroughly adopted, regardless of how GPS data was used. This was particularly true for the military. When mishandled or used as a coercive disciplinary weapon, the continual surveillance that professional football players are subjected to amplifies the uncertainty and fear of failure that are essential to the major difficulties that occur throughout a working football career. This results in the acceptance of dysfunctional standards that are harmful to one's physical, psychological, and emotional well-being. It is imperative that coaches control or re-think the use of GPS and other surveillance-based performance analysis technology in sports in order to prevent introducing new risks to athletes' health and well-being. It was discovered in the study done by Lin and Windasari (2018) that health and wellbeing is regarded to be the most significant issue in service research at this time. The concept of well-being as a public health problem has evolved through time; for example, the World Health Organization (WHO) now places greater emphasis on people's quality of life and healthy behaviour across all life phases. The trend toward using technology to improve health services is being accompanied by a growing interest in preserving personal health through the use of self-tracking gadgets, such as wearable fitness trackers, which are becoming increasingly popular (WFT). According to research, wearing a pedometer has a strong association with engaging in physical activity. Treatments utilising both wearable devices and mobile phone applications, on the other hand, failed to demonstrate any evidence of improving people's health when compared to continuous behavioural change and interventions. According to the findings of a study done by Mettler and Wulf (2018), wearables combined with data analytics and machine learning algorithms that assess physiological (and other) characteristics are steadily making their way into our workplace. Several studies have reported positive effects from the use of such "physiolytics" devices, with the implication that they may lead to significant improvements in workplace safety or increased awareness among employees regarding unhealthy work practises and other job-related health and well-being issues. However, no such studies have been conducted. As a result of this, physiolytics may result in an over-reliance on technology and the introduction of new restrictions on privacy, individuality, and personal freedom. However, while it is simple to see why companies are adopting physiolytics, it is still unknown what employees think about the use of wearables at their place of employment. Therefore, we investigate the mental models of workers who are confronted with the introduction of physiolytics as part of corporate wellness or security initiatives via the perspective of affordance theory and cognitive dissonance. According to the findings of a study done by Lee et al. (2017), wearable sensors (e.g., activity trackers and physiological monitors) have allowed individualised objective monitoring of workers' health and wellbeing. Furthermore, the TWH idea is important to construction employees, particularly roofing workers, because they are exposed to high levels of on-the-job health and safety concerns and have low off-the-job quality of life. TWH cannot be done merely by providing workers with wearable gadgets and incentives to engage in off-duty activities. It is critical to identify the core causes of workers' hazardous behaviours and fatigue exposures in order to eliminate these issues that are interfering with their ability to meet the demands of their jobs. We might ultimately explain how effectively and favourably a worker's physiological reactions may affect his or her job demands, as well as his or her safety and productivity performances, if we used wearable sensors and collected data on a regular basis at the individual level. This type of information will fundamentally alter our present approach to occupational safety and health in the construction industry in a variety of ways, both at the individual and organisational levels.

Because of the current state of wearable technology, it is more likely to be used simply for self-monitoring and feedback purposes. Further development of wearable devices could result in a broader range of potential value propositions as well as more meaningful experiences that go beyond simple tracking capabilities (King et al., 2017). Based on the outcomes of this study, we have developed guidelines for practitioners who are aiming to deliver long-term wearable health services. The ultimate aims of technology-assisted personal health management include enhanced well-being as well as the continued usage of the device over an extended period of time. As an alternative to offering a single, all-in-one gadget, service providers might give effective triggers by mapping their target market depending on the motivation and capacity of the users. custom-tailored and users of wearables are dynamic, and their requirements are always changing, making adaptable features crucial to their success (Petäjäjärvi et al., 2017). Wearables manufacturers must design products that are successful, whether they are targeting consumers with low self-efficacy or not. Triggers are used to allow users to incorporate the features of the gadget into their daily routines. Use interactive designs to produce relevant feedback, such as tailored smart alerts drawn from users' created physical records and connected with back-end data, as well as game-like features to keep users involved with their surroundings, such as contests or social media sharing (Khakurel, Melkas and Porras, 2018). Users will be more likely to remain with the gadget if they have a meaningful experience with it. It is most effective for people who have a high sense of self-efficacy. It is possible that this will have positive consequences for their own well-being. The problem is that they have a strong belief in their own skills rather than relying on the assistance of technology, which makes it difficult to please them unless the device is capable of adjusting its functioning to test users' previously undiscovered abilities (Chuah, 2019). Target users with poor technological efficacy play an important role in removing adoption hurdles, and frontline staffplay a key part in this process as well. Simple guides or personal assistants can be provided as an additional service package by a service provider, not only to minimise client dropouts but also to investigate what values emerge throughout the course of the service. A wearable service provider should, on the other hand, cater to consumers who have high technical efficacy by providing them with more high-end features that match their needs (Cavusoglu and Demirbag-Kaplan, 2017). For example, we may incorporate data-driven features such as real-time GPS tracking of workout routes, adaptive user interfaces, and blood pressure monitoring into our products. The widespread advancement of wearable sensing and mobile computing technologies, as well as the increasing variety of sensor modalities, has opened up new avenues for the collecting of health and well-being data outside of laboratory settings, and in a longitudinal fashion, in recent years. In the future, wearable and mobile technologies may be able to provide low-cost, objective measurements of physical activity, therapeutically useful data for patient evaluation, and scalable behaviour tracking in large groups of people. Both interventional and observational research can benefit from this data, which can be utilised to gain new insights into the relationship between behaviour and health. in order to enhance the customization and efficacy of commercial wellness apps, as well as to combat illness and disease. In the last year, approximately 400,000 individuals in epidemiological studies throughout the world have had their activity recorded prospectively using accelerometers. Self-report measures of physical activity and sleep have traditionally been relied upon by epidemiologists and clinicians. While these measures are useful in the absence of alternatives, they are subject to bias and often provide partial or incomplete information. Sensor-assessed, objective measures of physical behaviours are being developed, which overcome the limitations of self-report measures. A further benefit of the use of artificial intelligence (AI), sensor fusion, and signal processing to data collected by wearable sensors is the improvement in human activity identification and behavioural phenotyping. In this paper, we evaluate the current state of the art in wearable and mobile sensing technologies in epidemiology and clinical medicine, as well as how artificial intelligence is transforming the area of medical research and practise (Perez-Pozuelo, Spathis and Clifton, 2021). After a verified diagnosis has been made, according to the findings of a research done by Silva-Tawil et al. (2020), healthcare systems devote the majority of their resources to treating the patient's illness. Through constant monitoring of health and wellness in all individuals, the growing area of precision health aspires to early identification and personalised treatment of medical problems. Through the use of continuous, portable, and implanted health-monitoring equipment, it is possible to perform active monitoring and evaluation, which provides a full picture of human health and behaviour. Precision health has the potential to be accelerated by the development of new technologies. Users' involvement and data gathering will be supported for a lengthy period of time if unobtrusive monitoring solutions are developed. Innovative technologies are continuously developing and becoming more accessible. A deeper understanding of the landscape of available and upcoming technologies that can contribute to data collecting for precision health is required as a result of this development. A study done by (Birenboim et al., 2019) revealed that improvements in commercial wearable devices are progressively allowing the gathering and analysis of everyday physiological data, according to the findings. In this study, physiological markers such as heart rate, heart rate variability, and skin conductance were assessed in fifteen subjects. When the participants went on an outside stroll, their signals were captured and monitored using a Global Positioning System (GPS) logger. Several different sorts of settings, including green, blue, and urban places, as well as a more stressful road crossing, were considered in the creation of this walk. In order to show how biosensor information may be contextualised and supplemented using location information, the data that was collected was used. When exposed to a stressful road crossing, significant episodic alterations in physiological signals were seen, but these changes were not observed in the other types of settings studied. Despite the challenges and limitations of current off-the-shelf wearable technologies, the use of these devices provides novel opportunities for evaluating episodic changes in physiological signals as a marker for mental state during everyday activities, including those performed in outdoor environments.

Methodology 

Research designs are the processes that are used in research projects to collect, analyse, interpret, and report the data collected. Each of them represents a distinctive model for conducting research, and each of these models is distinguished by its own set of terms and processes. It is critical to have rigorous research designs because they guide the methodological decisions that researchers must make throughout their investigations and provide the logic by which they must draw conclusions at the conclusion of their studies. Having chosen the mixed methods approach for a study, the following step is to identify which specific design will be used to solve the research topic in question (Shannonhouse, Barden and McDonald, 2017). In order to verify and expand on the quantitative findings from a survey, researchers utilise the validating quantitative data model, which includes certain qualitative questions that may be answered in any way they want. As part of this paradigm, the researcher uses a single survey instrument to capture both sorts of information (DeCuir-Gunby, 2020). In most cases, qualitative items are added on top of a quantitative survey, therefore the items do not result in a comprehensive qualitative data collection. They do, however, supply the researcher with intriguing quotations that may be utilised to confirm and enrich the findings of the quantitative survey, which is beneficial to both parties. A significant amount of time and knowledge is required, particularly due to the simultaneous data collecting and the fact that each data type is often given equal weight. This can be addressed by forming a research team that includes members who have both quantitative and qualitative expertise, by including researchers who have both quantitative and qualitative expertise on graduate committees, or by training single researchers in both quantitative and qualitative research methods and methods of data analysis. When the quantitative and qualitative results do not agree, researchers may be faced with the dilemma of what to do next. These discrepancies might be difficult to reconcile and may necessitate the acquisition of more data in order to be resolved (Hulland, Baumgartner and Smith, 2017). One of the fundamental assumptions of this architecture is that a single data collection is insufficient, that multiple questions must be answered, and that different types of data are required to answer each type of inquiry. A qualitative or quantitative data set is used in this design when researchers need to address a research question with qualitative or quantitative data in a study that is primarily quantitative or qualitative. If, as in the case of an experimental or correlational design, a qualitative component must be embedded inside a quantitative design, this design is very helpful. If we look at the experimental example, the investigator incorporates qualitative data for a variety of reasons. For example, the investigator may want to use the data to develop a treatment, to examine the process of an intervention or to determine the mechanisms that link variables, or to follow up on the results of an experiment. Prior to conducting the qualitative phase, the researcher must select which qualitative data will be used in the quantitative phase and how the quantitative phase will be planned. This is especially true for before-intervention methods. Once again, qualitative data collection should be carefully planned to ensure that it corresponds to the intended use of qualitative data, such as the development of an instrument or the shaping of an intervention. When using during-intervention techniques, the qualitative data collecting may bring possible treatment bias into the trial, which might have an impact on the results. Decisions must be made on which parts of the trial will be further investigated following intervention, and the researcher must describe the criteria used to choose the individuals who will be included in the follow-up data collection.

Project Design 

 

Ethical Consideration 

It is in and of itself an extremely ethical practise: it maximises the value of any (public) investment in data collection, it reduces the burden on respondents, it ensures the replicability of study findings, and thus increases transparency of research procedures and the integrity of research findings. Second-hand information, on the other hand, may only be fully realised if the advantages outweigh the dangers, which include the possibility of re-identification of persons and the exposure of sensitive information.

In order for this to occur, the use of secondary data must satisfy certain important ethical requirements:

• Before data is released to the researcher, it must be de-identified.
• It is reasonable to assume that research volunteers have given their consent.
• The results of the analysis must not be able to be used to re-identify individuals.
• The data must not be used in a way that causes harm or discomfort to anybody.

Anyone who is involved in the collection of data from patients has an ethical obligation to protect the autonomy of each individual participant. Any survey should be done in an ethical way and in accordance with current best research practises, if possible. If you're conducting a survey, confidentiality and informed permission are two essential ethical considerations to keep in mind. Respect for the respondent's right to confidentiality, as well as compliance with any applicable legal obligations for data protection, should always be maintained. When conducting the vast majority of surveys, it is essential that the patient be properly informed about the survey's objectives and that the patient's agreement to participate in the survey is acquired and recorded. A survey research report must meet the same high standards of research practise as any other type of research report. Journal editors and the larger research community will assess a report on survey research with the same level of rigour as any other type of research report. To be clear, this does not imply that survey research should be particularly difficult or complex; rather, the point to emphasise is that researchers should be aware of the steps that are required in survey research, as well as systematic and thoughtful in the planning, implementation, and reporting of the project.

Gant Chart 

References

Cavusoglu, L. and Demirbag-Kaplan, M. (2017). Health commodified, health communified: navigating digital consumptionscapes of well-being. European Journal of Marketing, 51(11/12), pp.2054–2079.

Chuah, S.H.-W. (2019). You inspire me and make my life better: Investigating a multiple sequential mediation model of smartwatch continuance intention. Telematics and Informatics, 43, p.101245.

Daffern, H., Camlin, D.A., Egermann, H., Gully, A.J., Kearney, G., Neale, C. and Rees-Jones, J. (2018). Exploring the potential of virtual reality technology to investigate the health and well being benefits of group singing. International Journal of Performance Arts and Digital Media, 15(1), pp.1–22.

DeCuir-Gunby, J.T. (2020). Using critical race mixed methodology to explore the experiences of African Americans in education. Educational Psychologist, 55(4), pp.244–255.

Denecke, K., Gabarron, E., Grainger, R., Konstantinidis, S.Th., Lau, A., Rivera-Romero, O., Miron-Shatz, T. and Merolli, M. (2019). Artificial Intelligence for Participatory Health: Applications, Impact, and Future Implications. Yearbook of Medical Informatics, 28(01), pp.165–173.

Douglas, E.M. and Cunningham, J.M. (2008). Recommendations from child fatality review teams: results of a US nationwide exploratory study concerning maltreatment fatalities and social service delivery. Child Abuse Review, 17(5), pp.331–351.

Hulland, J., Baumgartner, H. and Smith, K.M. (2017). Marketing survey research best practices: evidence and recommendations from a review of JAMS articles. Journal of the Academy of Marketing Science, 46(1), pp.92–108.

Jones, L., Marshall, P. and Denison, J. (2016). Health and well-being implications surrounding the use of wearable GPS devices in professional rugby league: A Foucauldian disciplinary analysis of the normalised use of a common surveillance aid. Performance Enhancement & Health, 5(2), pp.38–46.

Khakurel, J., Melkas, H. and Porras, J. (2018). Tapping into the wearable device revolution in the work environment: a systematic review. Information Technology & People, 31(3), pp.791–818.

King, R.C., Villeneuve, E., White, R.J., Sherratt, R.S., Holderbaum, W. and Harwin, W.S. (2017). Application of data fusion techniques and technologies for wearable health monitoring. Medical Engineering & Physics, 42, pp.1–12.

Lee, W., Lin, K.-Y., Seto, E. and Migliaccio, G.C. (2017). Wearable sensors for monitoring on-duty and off-duty worker physiological status and activities in construction. Automation in Construction, 83, pp.341–353.

Lin, F. and Windasari, N.A. (2018). Continued use of wearables for wellbeing with a cultural probe. The Service Industries Journal, 39(15-16), pp.1140–1166.

Mettler, T. and Wulf, J. (2018). Physiolytics at the workplace: Affordances and constraints of wearables use from an employee’s perspective. Information Systems Journal, 29(1), pp.245–273.

Miele, F. and Tirabeni, L. (2020). Digital technologies and power dynamics in the organization: A conceptual review of remote working and wearable technologies at work. Sociology Compass, p.e12795.

Müller, S.M. and Hein, A. (2019). Tracking and Separation of Smart Home Residents through Ambient Activity Sensors. Proceedings, 31(1), p.29.

Papa, A., Mital, M., Pisano, P. and Del Giudice, M. (2020). E-health and wellbeing monitoring using smart healthcare devices: An empirical investigation. Technological Forecasting and Social Change, 153, p.119226.

Petäjäjärvi, J., Mikhaylov, K., Yasmin, R., Hämäläinen, M. and Iinatti, J. (2017). Evaluation of LoRa LPWAN Technology for Indoor Remote Health and Wellbeing Monitoring. International Journal of Wireless Information Networks, 24(2), pp.153–165.

Pingo, Z. and Narayan, B. (2019). “My smartwatch told me to see a sleep doctor”: a study of activity tracker use. Online Information Review, ahead-of-print(ahead-of-print).

Shannonhouse, L.R., Barden, S.M. and McDonald, C.P. (2017). Mixed Methodology in Group Research: Lessons Learned. The Journal for Specialists in Group Work, 42(1), pp.87–107.

Smets, E., Rios Velazquez, E., Schiavone, G., Chakroun, I., D’Hondt, E., De Raedt, W., Cornelis, J., Janssens, O., Van Hoecke, S., Claes, S., Van Diest, I. and Van Hoof, C. (2018). Large-scale wearable data reveal digital phenotypes for daily-life stress detection. npj Digital Medicine, 1(1).

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