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(A) Study on the Perception and Acceptance of Wrist- Worn Wearable Fitness Tracker and Development of Intervention Models for Enhancing the Acceptance and Prolonged Use of the Devices, Ensuring a Healthy Ageing

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It also aims to formulate interventions in the design of the Wearable Fitness technology to ensure its long-term use. Decadal growth in the elderly population in relation to the general population Period In General Population In Elderly Population.

Table 1-1. Decadal growth in the elderly population vis-a-vis that of the general population  Period  In General Population  In Elderly Population
Table 1-1. Decadal growth in the elderly population vis-a-vis that of the general population Period In General Population In Elderly Population

Self-Perception of Ageing (SPA)

A higher proportion of the older adult population has a sedentary lifestyle with the negative stereotype of aging. According to the behavioral path concept, the negative SPA acts as the barrier in an individual's path.

Review on Health Degradation with Age

Limited diversities in the social relations of the elderly also increase the higher risks of functional disability (Rodrigues, et al., 2009). The prevalence of risk factors creates the chances of disability in older age as shown in the following tables (Velayutham, et al., 2016).

Table 1-4. Risk factors associated with the Disability in older adults.
Table 1-4. Risk factors associated with the Disability in older adults.

Assistive Technology Devices for Older Adults

Assistive devices and aids provide an independent life for the elderly and provide an improved way of life. It can compensate for reduced function, helping the elderly to live independently and improve overall well-being (WHO, 2018) (Chen, 2020).

Table  1-7.  Percentage  of  older  adults  either  already  using  or  reporting  need  of  AT  in  Great  Britain
Table 1-7. Percentage of older adults either already using or reporting need of AT in Great Britain

Assistive Technology Intervention for Older Adults

In some cases, the patient can regain their previous ability to move and relearn to walk safely and efficiently (Martins, et al., 2012). According to a large sample study (using standard everyday products), 75% of participants reported problems with use (Fisk, et al., 2009).

Table 1-8. Assistive Devices for Older Adults  Category  Assistive Devices
Table 1-8. Assistive Devices for Older Adults Category Assistive Devices

Healthcare, Fitness and Older Adults

In a 6-month randomized trial with 18-month follow-up in a sample (N=174) conducted by McAuley et al., study factors were ⅰ) trial adherence, ii) emotional responses to exercise, ii) exercise value, and iv) social support of the training group. Smart fitness wearables, such as smartwatches and fitness trackers, account for approximately 60% of the total market and have been reported to be adopted by various age groups (Gupta et al., 2020).

Table 1-10. Health Care Emphasis Transition (Gardner-Bonneau & Gosbee, 1996)
Table 1-10. Health Care Emphasis Transition (Gardner-Bonneau & Gosbee, 1996)

Study design

The population for the study was selected at the age of 18 from different backgrounds and age groups. The collected data were treated with statistical practices using MS Excel, SPSS and Amos. The design intervention is constructed and validated with appropriate tools and techniques to address the existing research gap and research problem.

Flow chart

This chapter contains a comprehensive study of wrist-worn wearable fitness trackers and experiments conducted to gain insight into the perception and adoption of the devices. This chapter provides an overview of the study that was conducted in the research. Fitness bands, smartwatches, and smart wearables are estimated to account for nearly half of all wearable sales worldwide (Pal et al., 2019).

Figure 2-1. Wearable Technology (Happiest Minds)
Figure 2-1. Wearable Technology (Happiest Minds)

Fitness Tracking Under Various Physical Activity

There is a directional shift in the focus of the information system from the mindset of instrumentality and efficiency to facilitating human life in various ways through entertainment (e.g. games) and social connections (e.g. social networking applications) (Hassan, et al. , 2019) and portability (e.g. wearable fitness trackers). WFT can track physical activity in real time and allows users to track their performance to optimize long-term health benefits. WFT can monitor daily activities and suggest any behavioral changes needed for a healthy lifestyle.

Awareness of Wearable Fitness Tracking Devices among People

According to the latest market research, the table below shows the growth of sales of Wearable Devices (Needham, 2021). The study significantly concluded that demographically, women (58 percent) outnumber men in the US and are more likely to become potential buyers (npd, 2014). Numerous types of wearables available in the Indian market are smart watches, fitness monitors and internet enabled glasses.

Table  2-1.  Top 5  Wearable  Companies  by  Shipment  Volume,  Market  Share,  and  Year-Over- Year-Over-Year Growth, 2018 (shipments in millions)
Table 2-1. Top 5 Wearable Companies by Shipment Volume, Market Share, and Year-Over- Year-Over-Year Growth, 2018 (shipments in millions)

Technology Acceptance Model

There is a positive relationship between the perceived usefulness and the intention to adopt a new type of information or communication technology (Zaremohzzabieh, et al., 2015). Thereby, it influences the adoption of Wearable Fitness Technology through attitudes (Lunney, et al., 2016). According to TAM, the two primary constructs were responsible for predicting adoption: ⅰ) Perceived Usefulness and ii) Perceived Ease of Use. By increasing the perceived usefulness and preparing the logical arguments, there is a high chance of adopting the technology (Gong, et al., 2004).

Unified Theory of Acceptance and Use of Technology

Perceived health benefits represent the overview of the clients' perspective on exercise and fitness (Lunney, et al., 2016). Some researchers (Gong, et al., 2004) believe that a positive attitude plays a significant role in the acceptance of technology. Perceived health benefits are also significant factors enhancing the adoption of Wearable fitness technology in different age groups.

Unified Theory of Acceptance and Use of Technology 2

A total of four direct determinants, Performance Expectancy, Effort Expectancy, Social Influence and Facilitating conditions, were involved in UTAUT to determine Behavioral Intention, as shown in Figure 2-6. Performance expectancy and effort expectancy should closely match the characteristics of perceived usefulness and perceived ease of use, respectively. With the possibility that cost can influence consumers' Behavioral Intention, Price Value was incorporated into the new model, UTAUT2, as a determinant.

Expectation Confirmation Theory

Determination of such an effective engagement process will be incorporated into the WFT devices, motivating users to continue the device use, which is essential to generate sustained value (Windasari, et al., 2021). The various concepts and theories developed in the relevant research field were studied, which helped to narrow down the research dimension. Summed scales were used to construct the data collection method as an item analysis approach, to evaluate people's attitudes towards the WFT.

Figure 2-8. Expectation Confirmation Model
Figure 2-8. Expectation Confirmation Model

Survey

The survey of the relevant literature was carried out, which gave the direction of the research problem. At the final stage, the data analysis is done with the help of Excel, Version 1808, SPSS Statistics, Version 25 and Amos, Version 22. Consent regarding their participation was also obtained from each participant before the start of it either in written format (provided in Appendix A) or deduction option in online form.

Research Instruments

Perceived Economic Risk (PER) It refers to the distress of encountering monetary loss or risk involved in using WFT. Perceived Physical Risk (PPRa) It refers to the distress of encountering physical harm or risk involved in using WFT. Perceived privacy risk (PPRb) It refers to the fear of the risk of privacy violation associated with using WFT.

Measurement Models

The structural model was developed using 12 indicators grouped into four exogenous latent variables: Perceived Financial Risk, Perceived Physical Risk, Perceived Psychological Risk, Perceived Privacy Risk, Perceived Social Risk, and Perceived Functional Risk.

Reliability Test of Research Instruments

To understand the relationship between the associated perceived risk and behavioral intentions of people towards WFT. Cronbach alpha has been derived using SPSS for all the items representing respective exogenous and endogenous variables for different instruments in the study.

Table 2-3. Criteria for Cronbach
Table 2-3. Criteria for Cronbach's Alpha Value

Structural Equation Modelling (SEM)

KMO and Bartlett's test for continuation intention in the direction of WFT Kaiser-Meyer-Olkin measure of sampling adequacy. A measurement model fit for freedom from associated risk and behavioral intention toward WFT. The table above shows that the fit of the model approves the recommended threshold values; thus the model is considered suitable and accepted.

Table 2-8. Threshold Values of the Reliability and Validity Factors of CFA (Gaskin, 2016)
Table 2-8. Threshold Values of the Reliability and Validity Factors of CFA (Gaskin, 2016)

Demographics of study participants

The data interpreted by statistical practice are provided in the following subsections to give the data analysis's detailed layout.

Correlation study of the Various Constructs

However, existing constructs are still inadequate in determining behavioral intention and intention to continue WFT.

Table 2-28. Correlation among various constructs used to determine the Continuous Intention of WFT
Table 2-28. Correlation among various constructs used to determine the Continuous Intention of WFT

Response to Research Questions

Does awareness of the mechanism of the WFT influence the Intention to incorporate the WFT into people's daily lives. The analysis of variance test shows that there is no significant difference in WFT acceptance within the different age groups considered in the study. From the analysis, it was observed that there is no significant difference in the involvement in fitness regimes between different groups.

Table 2-30. ANOVA for Age group vs Exercise Behaviour
Table 2-30. ANOVA for Age group vs Exercise Behaviour

Experience design

A systematic approach has been taken to develop the design interventions for Wearable Fitness Trackers to address the lack of sustainability issues and increase the acceptance of Wearable Fitness Trackers among the actual and potential consumers. The following sections describe design considerations and principles addressed in this study to develop the design interventions. The 'why' tries to clarify the needs and feelings involved in any activity connected, giving a beginning to the experience.

Inclusive Designs - accessible design

Moreover, "How" is the typical realm of Interaction Designers, which deals with acting through an object at an operational, sensorimotor level to make the given functionality accessible in an aesthetically pleasing way (Hassenzahl, 2021). Regardless of age-related circumstances and decline, a person's self-efficacy plays an important role in developing healthy habits to maintain an enjoyable life and maintain it well into old age. Therefore, to reach a negotiable point where older adults and their younger counterparts will both benefit from wearable fitness devices, understanding their health behaviors and self-efficacy needs to be studied and taken into account. while designing these devices.

Self-efficacy and Health Behaviours

The existing concepts can help in learning new ones by drawing analogies between the new system and the systems that the users already understand. Design thinking and the user experience processes show that experiential purchases provide more satisfaction than materialistic purchases.

Survey

Research Instruments

Design Aesthetics (DA) It refers to the experience and pleasure gained through WFT's aesthetic experiences. Continuance Intention (CI) It refers to the positive intention to continue the service provided by WFT. Design Aesthetics (DA) It refers to the experience and pleasure gained through WFT's aesthetic experiences.

Measurement Models

Reliability Test of Research Instruments

Responses and Data Analysis

A systematic analysis was performed between the determinants to understand how the different types of self-efficacy influence one's attitude towards health technology. A systematic analysis was performed between the determinants to understand how the different constructs mediate behavioral intention towards the WFT. AVERAGE PE AVERAGE EE AVERAGE SI AVERAGE DA AVERAGE HM AVERAGE PV AVERAGE ATU AVERAGE PI AVERAGE BI.

Table 3-4. Descriptive Statistics of Different Self Efficacies and Attitude towards Health Technology
Table 3-4. Descriptive Statistics of Different Self Efficacies and Attitude towards Health Technology

Response to Research Questions

From the above, it was concluded that general and technological self-efficacy play an important role in determining attitudes towards health technology. Regression analysis shows that attitude towards health technology is linearly related to behavioral intention towards WFT. Therefore, attitude toward health technology may moderate a person's behavior toward WFT.

Table 3-15. Correlation between ATHT, ATU and BI
Table 3-15. Correlation between ATHT, ATU and BI

Structural Equation Model

A correlation analysis was performed to find the directional correlation between the Attitude towards health technology and Behavioral Intention (BI) towards WFT. A regression analysis was also performed to find the direction and relationship between the aesthetics of experience and behavioral intention towards WFT. The analysis of variance between the aesthetics of experiences and the behavioral intention towards WFT has been performed.

Table 3-19. Pattern Matrix for Perceived Risk and Behavioural Intention  Component
Table 3-19. Pattern Matrix for Perceived Risk and Behavioural Intention Component

Wearable Fitness Tracker – how it works

The components in these activity trackers are quite advanced and proficient in their respective domains as shown in the following image and table. All the components built into the fitness trackers have a significant impact on the various functionalities required for tracking the different activities that an individual performs every day. The following table provides a detailed layout and the technical specifications of WFT, with the colored bulleted labels representing the corresponding components in the adjacent images.

Figure 3-11. Sensors used in the Wearable Fitness Tracker (Nield, 2017)
Figure 3-11. Sensors used in the Wearable Fitness Tracker (Nield, 2017)

Design Considerations

Proposed Design Characteristics

Camouflaging devices with dummy clothing or accessories reduces the cost of facilitating conditions.

Table 3-44. Dimensions of Existing Wrist-Worn Fitness Tracker Models (Omondi, 2021)
Table 3-44. Dimensions of Existing Wrist-Worn Fitness Tracker Models (Omondi, 2021)

Conceptualised Design Model

Figure

Table 1-3. Top ten conditions affecting the millennials (ages 21-36) in 2017 (BCBS, 2019)
Table 1-4. Risk factors associated with the Disability in older adults.
Figure  1-13.  Passive  Orthoses  based  on  the  gravity-balancing  principle  External Devices
Figure 2-7. Unified Theory of Acceptance and Use of Technology 2 Determinants
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References

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