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Triantafyllidis A, Kondylakis H, Katehakis D, Kouroubali A, Alexiadis A, Segkouli S, Votis K, Tzovaras D. Smartwatch interventions in healthcare: A systematic review of the literature. Int J Med Inform 2024; 190:105560. [PMID: 39033723 DOI: 10.1016/j.ijmedinf.2024.105560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 06/25/2024] [Accepted: 07/16/2024] [Indexed: 07/23/2024]
Abstract
OBJECTIVE The use of smartwatches has attracted considerable interest in developing smart digital health interventions and improving health and well-being during the past few years. This work presents a systematic review of the literature on smartwatch interventions in healthcare. The main characteristics and individual health-related outcomes of smartwatch interventions within research studies are illustrated, in order to acquire evidence of their benefit and value in patient care. METHODS A literature search in the bibliographic databases of PubMed and Scopus was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, in order to identify research studies incorporating smartwatch interventions. The studies were grouped according to the intervention's target disease, main smartwatch features, study design, target age and number of participants, follow-up duration, and outcome measures. RESULTS The literature search identified 13 interventions incorporating smartwatches within research studies with people of middle and older age. The interventions targeted different conditions: cardiovascular diseases, diabetes, depression, stress and anxiety, metastatic gastrointestinal cancer and breast cancer, knee arthroplasty, chronic stroke, and allergic rhinitis. The majority of the studies (76%) were randomized controlled trials. The most used smartwatch was the Apple Watch utilized in 4 interventions (31%). Positive outcomes for smartwatch interventions concerned foot ulcer recurrence, severity of symptoms of depression, utilization of healthcare resources, lifestyle changes, functional assessment and shoulder range of motion, medication adherence, unplanned hospital readmissions, atrial fibrillation diagnosis, adherence to self-monitoring, and goal attainment for emotion regulation. Challenges in using smartwatches included frequency of charging, availability of Internet and synchronization with a mobile app, the burden of using a smartphone in addition to a patient's regular phone, and data quality. CONCLUSION The results of this review indicate the potential of smartwatches to bring positive health-related outcomes for patients. Considering the low number of studies identified in this review along with their moderate quality, we implore the research community to carry out additional studies in intervention settings to show the utility of smartwatches in clinical contexts.
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Affiliation(s)
- Andreas Triantafyllidis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece.
| | - Haridimos Kondylakis
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
| | - Dimitrios Katehakis
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
| | - Angelina Kouroubali
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
| | - Anastasios Alexiadis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Sofia Segkouli
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Konstantinos Votis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Dimitrios Tzovaras
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
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Yang Q, Al Mamun A, Reza MNH, Naznen F. Modelling the significance of value-belief-norm framework to predict mass adoption potentials of internet of things-enabled wearable fitness devices. Heliyon 2024; 10:e30179. [PMID: 38737228 PMCID: PMC11088247 DOI: 10.1016/j.heliyon.2024.e30179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 04/18/2024] [Accepted: 04/22/2024] [Indexed: 05/14/2024] Open
Abstract
Self-health monitoring technologies have become increasingly popular in averting unanticipated health complications. However, the adoption rate of such technologies in developing countries is surprisingly low. Furthermore, empirical studies on the application of the value-belief-norm (VBN) model to elucidate intention to use IoT-enabled wearable fitness devices (IoT-enabled WFDs) are scarce. This study aimed to expand the VBN model by integrating health values, health consciousness, health knowledge-seeking, and social norms as influencing constructs. The proposed holistic framework was empirically tested to examine these constructs on users' decision-making process of adopting IoT-enabled WFDs. A web-based survey involving 866 adults in China aged 18-30 years was conducted. The gathered data were analysed using partial least squares-structural equation modeling. The results revealed the significant influence of health consciousness and health knowledge-seeking on personal health beliefs, as well as the favourable impact of personal health beliefs on personal norms and awareness of consequences. The results further demonstrated the substantial influence of awareness of consequences and ascription of responsibilities on personal norms. Besides that, personal norms and societal norms were found to have strong influence on the intention to adopt IoT-enabled WFDs, which was revealed to have significant influence on the actual usage. This study's findings offer novel theoretical insights on the behavioural characteristics of adopting IoT-enabled WFDs and serve as a practical guideline for industry experts and marketers to establish appropriate marketing strategies to support the IoT-enabled wearable sector. The findings also benefit policymakers in their efforts of developing strategies that emphasise the unique benefits of self-healthcare monitoring to encourage active lifestyle and decrease obesity and overweight-related health risks.
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Affiliation(s)
- Qing Yang
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor Darul Ehsan, Malaysia
| | - Abdullah Al Mamun
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor Darul Ehsan, Malaysia
| | - Mohammad Nurul Hassan Reza
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor Darul Ehsan, Malaysia
| | - Farzana Naznen
- UCSI Graduate Business School, UCSI University, Malaysia. No. 1, Jalan Menara Gading, UCSI Heights (Taman Connaught), Cheras, 56000, Kuala Lumpur, Malaysia
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Matsuda T, Miyamori T, Fujino Y, Nozu S, Kajiwara Y. Reliability and validity of muscle activity analysis using wearable electromyographs. J Phys Ther Sci 2024; 36:123-127. [PMID: 38434994 PMCID: PMC10904218 DOI: 10.1589/jpts.36.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 11/30/2023] [Indexed: 03/05/2024] Open
Abstract
[Purpose] The aim of this study was to develop a novel wearable surface electromyograph called NOK, and compare its reliability and validity to an existing electromyograph. [Participants and Methods] The study participants were 23 healthy university students (Seven males and 16 females; age 20.3 ± 1.1 years [mean ± standard deviation]; height 162.0 ± 6.7 cm; weight 58.4 ± 10.1 kg) who all gave informed written consent. The newly developed electromyograph (NOK) features a rubberized skin contact surface that requires no electrodes and allows the acquisition of up to 10 channels of muscle waveforms on a portable personal computer. After measuring maximal isometric elbow extension and flexion, we examined muscle waveforms during isometric contractions of elbow joint flexion and extension at approximately 50% of maximal voluntary contraction using both NOK and Delsys electromyographs and compared the results of the two devices. [Results] We found a significant moderate correlation between the measurements by the two devices for biceps and triceps. The measurements by the two devices also showed strong measure-retest reliability. Systematic errors were observed for elbow flexion and extension in the two measurements, indicating limited agreement between the two measurement methods. [Conclusion] Although the new device also has high repeatability and reliability, it is unsuitable for analyzing detailed muscle activity. However, since it can measure up to 10 channels of muscle activity, it is expected to be used in the rehabilitation and sports field in the future.
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Affiliation(s)
- Tadamitsu Matsuda
- Department of Physical Therapy, Faculty of Health Science,
Juntendo University: 3-2-12 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Takayuki Miyamori
- Department of Physical Therapy, Faculty of Health Science,
Juntendo University: 3-2-12 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yuji Fujino
- Department of Physical Therapy, Faculty of Health Science,
Juntendo University: 3-2-12 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Shojiro Nozu
- Faculty of Health and Sports Science, Juntendo University,
Japan
| | - Yuma Kajiwara
- NTT DATA INSTITUTE OF MANAGEMENT CONSULTING, Inc.,
Japan
- Graduate School of Comprehensive Human Sciences, University
of Tsukuba, Japan
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4
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Chang J, Mai Y, Zhang D, Yang X, Li A, Yan W, Wu Y, Chen J. Media Use Behavior Mediates the Association Between Family Health and Intention to Use Mobile Health Devices Among Older Adults: Cross-Sectional Study. J Med Internet Res 2024; 26:e50012. [PMID: 38373031 PMCID: PMC10912999 DOI: 10.2196/50012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 08/29/2023] [Accepted: 01/28/2024] [Indexed: 02/20/2024] Open
Abstract
BACKGROUND With the advent of a new era for health and medical treatment, characterized by the integration of mobile technology, a significant digital divide has surfaced, particularly in the engagement of older individuals with mobile health (mHealth). The health of a family is intricately connected to the well-being of its members, and the use of media plays a crucial role in facilitating mHealth care. Therefore, it is important to examine the mediating role of media use behavior in the connection between the family health of older individuals and their inclination to use mHealth devices. OBJECTIVE This study aims to investigate the impact of family health and media use behavior on the intention of older individuals to use mHealth devices in China. The study aims to delve into the intricate dynamics to determine whether media use behavior serves as a mediator in the relationship between family health and the intention to use mHealth devices among older adults. The ultimate goal is to offer well-founded and practical recommendations to assist older individuals in overcoming the digital divide. METHODS The study used data from 3712 individuals aged 60 and above, sourced from the 2022 Psychology and Behavior Investigation of Chinese Residents study. Linear regression models were used to assess the relationships between family health, media use behavior, and the intention to use mHealth devices. To investigate the mediating role of media use behavior, we used the Sobel-Goodman Mediation Test. This analysis focused on the connection between 4 dimensions of family health and the intention to use mHealth devices. RESULTS A positive correlation was observed among family health, media use behavior, and the intention to use mHealth devices (r=0.077-0.178, P<.001). Notably, media use behavior was identified as a partial mediator in the relationship between the overall score of family health and the intention to use mHealth devices, as indicated by the Sobel test (z=5.451, P<.001). Subgroup analysis further indicated that a complete mediating effect was observed specifically between family health resources and the intention to use mHealth devices in older individuals with varying education levels. CONCLUSIONS The study revealed the significance of family health and media use behavior in motivating older adults to adopt mHealth devices. Media use behavior was identified as a mediator in the connection between family health and the intention to use mHealth devices, with more intricate dynamics observed among older adults with lower education levels. Going forward, the critical role of home health resources must be maximized, such as initiatives to develop digital education tailored for older adults and the creation of media products specifically designed for them. These measures aim to alleviate technological challenges associated with using media devices among older adults, ultimately bolstering their inclination to adopt mHealth devices.
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Affiliation(s)
- Jinghui Chang
- School of Health Management, Southern Medical University, Guangzhou, China
| | - Yanshan Mai
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Dayi Zhang
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Xixi Yang
- School of Health Management, Southern Medical University, Guangzhou, China
| | - Anqi Li
- School of Health Management, Southern Medical University, Guangzhou, China
| | - Wende Yan
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Yibo Wu
- School of Public Health, Peking University, Beijing, China
| | - Jiangyun Chen
- School of Health Management, Southern Medical University, Guangzhou, China
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Jorbonyan A, Abolfathi Momtaz Y, Foroughan M, Mehrkian S. Determinants of Continuance Intention to Use Hearing Aids among Older Adults in Tehran (Iran). Healthcare (Basel) 2024; 12:487. [PMID: 38391862 PMCID: PMC10888125 DOI: 10.3390/healthcare12040487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/02/2023] [Accepted: 02/08/2024] [Indexed: 02/24/2024] Open
Abstract
The present study seeks to evaluate the factors determining the continuance intention to use hearing aids in older adults. This cross-sectional study was carried out in 2021. The technology post-acceptance model (PAM) framework was used to develop a model for the continuance intention to use hearing aids. In total, 300 hearing aid users aged ≥60 years, who were selected via a randomized stratified sampling method, completed the self-evaluation tools used in this study. With a mean age of 71.38 years (SD = 8), the participants comprised 50.7% and 49.3% females and males, respectively. The path analysis results showed that the continuance intention to use hearing aids was positively and significantly influenced by the actual use of hearing aids, the perceived benefits, satisfaction, confirmation, self-efficacy in using hearing aids, an extraverted personality trait, self-perceived hearing handicap, and perceived social support. The main results of the present study can help hearing care providers develop a better understanding of older users to design effective rehabilitation strategies and ensure their continuance intention to use hearing aids.
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Affiliation(s)
- Abdolhakim Jorbonyan
- Department of Geriatric Health, School of Health, Mazandaran University of Medical Sciences, Sari 48157-33971, Iran
| | - Yadollah Abolfathi Momtaz
- Iranian Research Center on Aging, The University of Social Welfare and Rehabilitation Sciences, Tehran 19857-13871, Iran
- Malaysian Research Institute on Ageing, University Putra Malaysia, Serdang 43400, Selangor, Malaysia
| | - Mahshid Foroughan
- Iranian Research Center on Aging, The University of Social Welfare and Rehabilitation Sciences, Tehran 19857-13871, Iran
| | - Saeideh Mehrkian
- Department of Audiology, The University of Social Welfare and Rehabilitation Sciences, Tehran 19857-13871, Iran
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Malarvizhi CAN, Al Mamun A, Reza MNH, Masud MM. Ageing well with tech: Exploring the determinants of e-healthcare services adoption in an emerging economy. Digit Health 2024; 10:20552076241272577. [PMID: 39247095 PMCID: PMC11378232 DOI: 10.1177/20552076241272577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Accepted: 07/09/2024] [Indexed: 09/10/2024] Open
Abstract
The adoption of e-healthcare services is critical for improving healthcare accessibility and efficiency, particularly in regions with diverse populations, such as Malaysia. Although e-healthcare services offer numerous advantages, their adoption is considerably low and requires a thorough understanding of the key factors that influence their use. This study investigated the determinants and dynamics of e-healthcare adoption among adults over 40 years by extending the unified theory of acceptance and use of technology. We employed a quantitative research approach, specifically a cross-sectional design. Data were collected from 393 Malaysian respondents through a structured survey questionnaire, using convenience sampling. They were analyzed using partial least-squares-structural equation modeling. The findings revealed that performance expectancy, effort expectancy, social influence, and perceived product value significantly influenced individuals' intentions to use e-healthcare services. Meanwhile, perceived risk had an insignificant negative effect. Facilitating conditions significantly influenced individuals' intentions and actual usage of e-healthcare services. Furthermore, individuals' intentions to use e-healthcare services significantly affected their actual use of these services. Additionally, the intention to use e-healthcare services mediated the relationship between the factors and usage of e-healthcare services, except for perceived risk. Surprisingly, perceived service accuracy had no significant moderating effect on the relationship between individuals' intention to use and their actual use of e-healthcare services. This study offers valuable insights for educators, practitioners, and policymakers, enriching the scholarly discourse in this field. For education, integrating e-healthcare topics into curricula can enhance digital health literacy. In practice, healthcare providers should focus on improving user experience and addressing barriers to technology adoption. For policy making, developing supportive policies, and infrastructure to facilitate e-healthcare adoption is crucial to enhancing public health outcomes.
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Affiliation(s)
| | - Abdullah Al Mamun
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, UKM Bangi, Malaysia
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7
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Yang Q, Al Mamun A, Wu M, Naznen F. Strengthening health monitoring: Intention and adoption of Internet of Things-enabled wearable healthcare devices. Digit Health 2024; 10:20552076241279199. [PMID: 39291159 PMCID: PMC11406608 DOI: 10.1177/20552076241279199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 08/13/2024] [Indexed: 09/19/2024] Open
Abstract
Objective Health self-monitoring technologies are gaining popularity worldwide, but they face low adoption rates in emerging countries. There is a deficiency in studies that have applied the value-belief-norm (VBN) model to understand the adoption of IoT-enabled wearable healthcare devices (WHDs). This study investigates the adoption of IoT-enabled WHDs among older adults in China, using the VBN model as a theoretical framework. Methods Using a convenience sampling method and a web-based cross-sectional survey method, we collected data from 476 respondents, which we analyzed using partial least squares structural equation modeling using Smart PLS version 3.3.5. Results The findings highlight the significance of health values and motivation in shaping personal health beliefs, which, in turn, influence personal norms and awareness of consequences. Particularly, awareness of consequences and attributions of responsibility significantly impact personal norms. Personal and social norms, in turn, strongly affect the intention to adopt IoT-enabled WHDs, ultimately driving their actual adoption. Conclusion This research contributes novel insights into the behavioral dynamics surrounding the adoption of IoT-enabled WHDs, providing valuable guidance for marketers and policymakers. Marketers can leverage these insights to develop tailored marketing strategies within the IoT-enabled WHD industry. Additionally, policymakers are urged to prioritize campaigns aimed at enhancing awareness and understanding of self-healthcare monitoring, with a focus on promoting the unique health benefits of IoT-enabled WHDs.
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Affiliation(s)
- Qing Yang
- UKM-Graduate School of Business, Universiti Kebangsaan Malaysia, Selangor Darul Ehsan, Malaysia
| | - Abdullah Al Mamun
- UKM-Graduate School of Business, Universiti Kebangsaan Malaysia, Selangor Darul Ehsan, Malaysia
| | - Mengling Wu
- UKM-Graduate School of Business, Universiti Kebangsaan Malaysia, Selangor Darul Ehsan, Malaysia
| | - Farzana Naznen
- UCSI Graduate Business School, UCSI University, Kuala Lumpur, Malaysia
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Bidargaddi N, Leibbrandt R, Paget TL, Verjans J, Looi JCL, Lipschitz J. Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research. Digit Health 2024; 10:20552076241260414. [PMID: 39070897 PMCID: PMC11282530 DOI: 10.1177/20552076241260414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Accepted: 05/21/2024] [Indexed: 07/30/2024] Open
Abstract
Background Mental illness remains a major global health challenge largely due to the absence of definitive biomarkers applicable to diagnostics and care processes. Although remote sensing technologies, embedded in devices such as smartphones and wearables, offer a promising avenue for improved mental health assessments, their clinical integration has been slow. Objective This scoping review, following preferred reporting items for systematic reviews and meta-analyses guidelines, explores validation studies of remote sensing in clinical mental health populations, aiming to identify critical factors for clinical translation. Methods Comprehensive searches were conducted in six databases. The analysis, using narrative synthesis, examined clinical and socio-demographic characteristics of the populations studied, sensing purposes, temporal considerations and reference mental health assessments used for validation. Results The narrative synthesis of 50 included studies indicates that ten different sensor types have been studied for tracking and diagnosing mental illnesses, primarily focusing on physical activity and sleep patterns. There were many variations in the sensor methodologies used that may affect data quality and participant burden. Observation durations, and thus data resolution, varied by patient diagnosis. Currently, reference assessments predominantly rely on deficit focussed self-reports, and socio-demographic information is underreported, therefore representativeness of the general population is uncertain. Conclusion To fully harness the potential of remote sensing in mental health, issues such as reliance on self-reported assessments, and lack of socio-demographic context pertaining to generalizability need to be addressed. Striking a balance between resolution, data quality, and participant burden whilst clearly reporting limitations, will ensure effective technology use. The scant reporting on participants' socio-demographic data suggests a knowledge gap in understanding the effectiveness of passive sensing techniques in disadvantaged populations.
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Affiliation(s)
- Niranjan Bidargaddi
- Digital Health Research Lab, College of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, Australia
| | - Richard Leibbrandt
- College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - Tamara L Paget
- Digital Health Research Lab, College of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, Australia
| | - Johan Verjans
- Australian Institute for Machine Learning, University of Adelaide, Adelaide, South Australia, Australia
- Lifelong Health, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Department of Cardiology, Royal Adelaide Hospital, Adelaide, South Australia, Australia
| | - Jeffrey CL Looi
- Academic Unit of Psychiatry & Addiction Medicine, The Australian National University School of Medicine and Psychology, Garran, Australia
| | - Jessica Lipschitz
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Hayat N, Al Mamun A, Gao J, Yang Q, Hussain WMHW. Envisaging the intention and adoption of electronic health applications among middle-aged and older adults: Evidence from an emerging economy. Digit Health 2024; 10:20552076241237499. [PMID: 38449679 PMCID: PMC10916462 DOI: 10.1177/20552076241237499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/19/2024] [Indexed: 03/08/2024] Open
Abstract
Technology plays a substantial role in our daily lives, and the spread of COVID-19 paves the way for the use of healthcare technologies to manage health in the comfort of our homes. Middle-aged and older adults face health issues and require instant healthcare advice and support. Electronic healthcare (EH) applications have emerged to facilitate middle-aged and older adults receiving healthcare support instantly while remaining in their homes. The present study empirically evaluates the intention and adoption of electronic health applications with the technological attributes of perceived compatibility, cost, product value, technology accuracy, privacy issues and health motivation among middle-aged and older adults from Malaysia. Moreover, this research examines the mediating effect of the intention to adopt EH applications between technology attributes and the adoption of EH applications. This study uses a cross-sectional method and employs an online survey to assemble quantitative data from 298 middle-aged and older Malaysian adults. It utilizes partial least squares structural equation modelling for data analysis. The data analysis reveals that perceived compatibility, cost, privacy, product value and health motivation significantly influenced the intention to use EH apps. Furthermore, the analysis shows that the intention to adopt EH apps significantly mediates the relationship between the perception of cost, personal privacy, product value, health motivation and adoption of EH apps. However, the intention to use EH apps insignificantly instigates their adoption. Finally, the study presents its implications, limitations and future research directions.
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Affiliation(s)
- Naeem Hayat
- Global Entrepreneurship Research and Innovation Centre, Universiti Malaysia Kelantan, Pengkalan Chepa, Kelantan, Malaysia
| | - Abdullah Al Mamun
- UKM – Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Selangor Darul Ehsan, Malaysia
| | - Jingzu Gao
- UKM – Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Selangor Darul Ehsan, Malaysia
| | - Qing Yang
- UKM – Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Selangor Darul Ehsan, Malaysia
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Kabir MR, Mahmud H, Hasan MK. Acceptability of a head-mounted assistive mouse controller for people with upper limb disability: An empirical study using the technology acceptance model. PLoS One 2023; 18:e0293608. [PMID: 37906562 PMCID: PMC10617718 DOI: 10.1371/journal.pone.0293608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 10/16/2023] [Indexed: 11/02/2023] Open
Abstract
Due to limited motor capabilities, people with upper limb disabilities have trouble utilizing a typical mouse while operating a computer. Different wearable Assistive Mouse Controllers (AMCs) have been developed to overcome their challenges. However, these people may not be able to realize the importance, ease of use, and social approval of these AMCs due to their fear of new technology, lack of confidence, and lack of ingenuity. These may negatively affect their attitude and intention toward accepting AMCs for equitable human-computer interaction. This study presents the development of a sensor-based head-mounted AMC, followed by an empirical analysis of its acceptance using the Technology Acceptance Model (TAM) from the socioeconomic perspective of Bangladesh. In a similar vein, we examined the effects of three additional psychological constructs-technology anxiety, confidence, and innovation, on its acceptance along with the original components of the TAM. A total of 150 individuals with stroke-induced upper limb disability participated in an online survey, and their responses were analyzed using confirmatory factor analysis and structural equation modeling, following the general least square method. Analysis revealed, about 96.44% of the participants had positive attitude towards the AMC, and almost 88.56% of them had positive intentions to accept it. Furthermore, about 68.61% of them expressed signs of anxiety, 96.35% were confident, and 94.16% of them had an innovative mindset in terms of device usage. The findings imply that individuals with an innovative mentality are more capable of comprehending the practical implications of a new technology than those without one. It is also feasible to reduce technological anxiety and boost a user's confidence while using an AMC by combining an innovative mentality with straightforward device interaction techniques. Additionally, peer encouragement and motivation can significantly enhance their positive attitude towards accepting the AMC for facilitating their interaction with a computer.
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Affiliation(s)
- Mohammad Ridwan Kabir
- Systems and Software Lab (SSL), Islamic University of Technology (IUT), Boardbazar, Gazipur, Bangladesh.
- Department of Computer Science and Engineering, Islamic University of Technology (IUT), Boardbazar, Gazipur, Bangladesh.
| | - Hasan Mahmud
- Systems and Software Lab (SSL), Islamic University of Technology (IUT), Boardbazar, Gazipur, Bangladesh.
- Department of Computer Science and Engineering, Islamic University of Technology (IUT), Boardbazar, Gazipur, Bangladesh.
| | - Md. Kamrul Hasan
- Systems and Software Lab (SSL), Islamic University of Technology (IUT), Boardbazar, Gazipur, Bangladesh.
- Department of Computer Science and Engineering, Islamic University of Technology (IUT), Boardbazar, Gazipur, Bangladesh.
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Chen S, Ye J. Understanding consumers' intentions to purchase smart clothing using PLS-SEM and fsQCA. PLoS One 2023; 18:e0291870. [PMID: 37725606 PMCID: PMC10508616 DOI: 10.1371/journal.pone.0291870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 09/07/2023] [Indexed: 09/21/2023] Open
Abstract
With the advancement of artificial intelligence (AI) and the Internet of Things (IoT), smart clothing, which has enormous growth potential, has developed to suit consumers' individualized demands in various areas. This paper aims to construct a model that integrates that technology acceptance model (TAM) and functionality-expressiveness-aesthetics (FEA) model to explore the key factors influencing consumers' smart clothing purchase intentions (PIs). Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the data, complemented by fuzzy-set qualitative comparative analysis (fsQCA). The PLS-SEM results identified that the characteristics of functionality (FUN), expressiveness (EXP), and aesthetics (AES) positively and significantly affect perceived ease of use (PEOU), and only EXP affects perceived usefulness (PU). PU and PEOU positively impact consumers' attitudes (ATTs). Subsequently, PU and consumers' ATTs positively influence PIs. fsQCA revealed the nonlinear and complex interaction effects of the factors influencing consumers' smart clothing purchase behaviors and uncovered five necessary and six sufficient conditions for consumers' PIs. This paper furthers theoretical understanding by integrating the FEA model into the TAM. Additionally, on a practical level, it provides significant insights into consumers' intentions to purchase smart clothing. These findings serve as valuable tools for corporations and designers in strategizing the design and promotion of smart clothing. The results validate theoretical conceptions about smart clothing PIs and provide useful insights and marketing suggestions for smart clothing implementation and development. Moreover, this study is the first to explain smart clothing PIs using symmetric (PLS-SEM) and asymmetric (fsQCA) methods.
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Affiliation(s)
- Shucong Chen
- Department of Fashion and Accessory Design, College of Design, Jiaxing University, Jiaxing, China
| | - Jing Ye
- Department of Fashion Design and Engineering, College of Design, Jiaxing University, Jiaxing, China
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12
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Gupta NS, Kumar P. Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine. Comput Biol Med 2023; 162:107051. [PMID: 37271113 DOI: 10.1016/j.compbiomed.2023.107051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/06/2023] [Accepted: 05/20/2023] [Indexed: 06/06/2023]
Abstract
Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.
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Affiliation(s)
- Nancy Sanjay Gupta
- Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University, India
| | - Pravir Kumar
- Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University, India.
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13
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Park SU, Jang DJ, Kim DK, Choi C. Key Attributes and Clusters of the Korean Exercise Healthcare Industry Viewed through Big Data: Comparison before and after the COVID-19 Pandemic. Healthcare (Basel) 2023; 11:2133. [PMID: 37570374 PMCID: PMC10419111 DOI: 10.3390/healthcare11152133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/19/2023] [Accepted: 07/24/2023] [Indexed: 08/13/2023] Open
Abstract
This study aims to predict the characteristics of the exercise healthcare industry in the post-pandemic era by comparing the periods before and after the coronavirus disease 2019 outbreak through big data analysis. TEXTOM, the Korean big data collection and analysis solution, was used for data collection. The pre-pandemic period was defined as 1 January 2018-31 December 2019 and the pandemic period as 1 January 2020-31 December 2021. The keywords for data collection were "exercise + healthcare + industry". Text mining and social network analysis were conducted to determine the overall characteristics of the Korean exercise healthcare industry. We identified 30 terms that appeared most frequently on social media. Four common (smart management, future technology, fitness, and research) and six different clusters (sports education, exercise leader, rehabilitation, services, business, and COVID-19) were obtained for the pre-pandemic and pandemic periods. Smart management, future technology, fitness, and research are still important values across both periods. The results provide meaningful data and offer valuable insights to explore the changing trends in exercise healthcare.
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Affiliation(s)
- Sung-Un Park
- Department of Sports and Health, Hwasung Medi-Science University, Hwaseong-si 18274, Republic of Korea;
| | - Deok-Jin Jang
- Department of Sports Medicine, Shinhan University, Uijeongbu-si 11644, Republic of Korea;
| | - Dong-Kyu Kim
- Department of Sports Science, Chungwoon University, Hongseong-gun 32224, Republic of Korea
| | - Chulhwan Choi
- Department of Physical Education, Gachon University, Seongnam-si 13120, Republic of Korea
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14
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Nath P, Mahtaba KR, Ray A. Fluorescence-Based Portable Assays for Detection of Biological and Chemical Analytes. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23115053. [PMID: 37299780 DOI: 10.3390/s23115053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 05/16/2023] [Accepted: 05/22/2023] [Indexed: 06/12/2023]
Abstract
Fluorescence-based detection techniques are part of an ever-expanding field and are widely used in biomedical and environmental research as a biosensing tool. These techniques have high sensitivity, selectivity, and a short response time, making them a valuable tool for developing bio-chemical assays. The endpoint of these assays is defined by changes in fluorescence signal, in terms of its intensity, lifetime, and/or shift in spectrum, which is monitored using readout devices such as microscopes, fluorometers, and cytometers. However, these devices are often bulky, expensive, and require supervision to operate, which makes them inaccessible in resource-limited settings. To address these issues, significant effort has been directed towards integrating fluorescence-based assays into miniature platforms based on papers, hydrogels, and microfluidic devices, and to couple these assays with portable readout devices like smartphones and wearable optical sensors, thereby enabling point-of-care detection of bio-chemical analytes. This review highlights some of the recently developed portable fluorescence-based assays by discussing the design of fluorescent sensor molecules, their sensing strategy, and the fabrication of point-of-care devices.
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Affiliation(s)
- Peuli Nath
- Department of Physics and Astronomy, University of Toledo, Toledo, OH 43606, USA
| | - Kazi Ridita Mahtaba
- Department of Physics and Astronomy, University of Toledo, Toledo, OH 43606, USA
| | - Aniruddha Ray
- Department of Physics and Astronomy, University of Toledo, Toledo, OH 43606, USA
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15
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Ferreira AF, da Silva HP, Alves H, Marques N, Fred A. Feasibility of Electrodermal Activity and Photoplethysmography Data Acquisition at the Foot Using a Sock Form Factor. SENSORS (BASEL, SWITZERLAND) 2023; 23:620. [PMID: 36679418 PMCID: PMC9865091 DOI: 10.3390/s23020620] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 12/22/2022] [Accepted: 12/24/2022] [Indexed: 06/17/2023]
Abstract
Wearable devices have been shown to play an important role in disease prevention and health management, through the multimodal acquisition of peripheral biosignals. However, many of these wearables are exposed, limiting their long-term acceptability by some user groups. To overcome this, a wearable smart sock integrating a PPG sensor and an EDA sensor with textile electrodes was developed. Using the smart sock, EDA and PPG measurements at the foot/ankle were performed in test populations of 19 and 15 subjects, respectively. Both measurements were validated by simultaneously recording the same signals with a standard device at the hand. For the EDA measurements, Pearson correlations of up to 0.95 were obtained for the SCL component, and a mean consensus of 69% for peaks detected in the two locations was obtained. As for the PPG measurements, after fine-tuning the automatic detection of systolic peaks, the index finger and ankle, accuracies of 99.46% and 87.85% were obtained, respectively. Moreover, an HR estimation error of 17.40±14.80 Beats-Per-Minute (BPM) was obtained. Overall, the results support the feasibility of this wearable form factor for unobtrusive EDA and PPG monitoring.
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Affiliation(s)
- Afonso Fortes Ferreira
- Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal
- Instituto de Telecomunicações (IT), Av. Rovisco Pais n. 1, Torre Norte—Piso 10, 1049-001 Lisboa, Portugal
| | - Hugo Plácido da Silva
- Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal
- Instituto de Telecomunicações (IT), Av. Rovisco Pais n. 1, Torre Norte—Piso 10, 1049-001 Lisboa, Portugal
| | - Helena Alves
- Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal
- Instituto de Engenharia de Sistemas e Computadores-Microsistemas e Nanotecnologias (INESC-MN), Rua Alves Redol 9, 1000-019 Lisboa, Portugal
| | - Nuno Marques
- Meia Mania Lda, Zona Industrial dos Matinhos Pav. 4/5, 3200-100 Lousã, Portugal
| | - Ana Fred
- Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal
- Instituto de Telecomunicações (IT), Av. Rovisco Pais n. 1, Torre Norte—Piso 10, 1049-001 Lisboa, Portugal
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16
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Hayat N, Salameh AA, Mamun AA, Alam SS, Zainol NR. Exploring the mass adoption potential of wearable fitness devices in Malaysia. Digit Health 2023; 9:20552076231180728. [PMID: 37325073 PMCID: PMC10265353 DOI: 10.1177/20552076231180728] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 05/22/2023] [Indexed: 06/17/2023] Open
Abstract
Objective The current study explores the formation of an intention to use wearable fitness devices (WFDs) with wearable fitness attributes and health consciousness (HCS). Moreover, the research examines the use of WFDs with the health motivation (HMT) and intention to use WFDs. The study also exposes the moderating effect of HMT between the intention to use WFDs and the use of WFDs. Methods Five hundred and twenty-five adults participated in the current study, and data were collected from January 2021 to March 2021 through the online survey of Malaysian respondents. The cross-sectional data was analyzed using the second-generation statistical method of partial least square structural equation modeling. Results HCS is insignificantly associated with the intention to use WFDs. Perceived compatibility, perceived product value, perceived usefulness, and perceived technology accuracy significantly influence the intention to use WFDs. HMT significantly impacts the adoption of WFDs; however, the intention to use WFDs negatively but significantly influences the use of WFDs. Lastly, the association between the intention to use WFDs and the adoption of WFDs is significantly moderated by HMT. Conclusions Our study findings illuminate the significant impact of technology-level attributes of WFDs on the intention to use WFDs. However, an insignificant impact of HCS on the intention to use WFDs was reported. Our result confirms that HMT plays a significant role in the use of WFDs. Such as the moderating role of HMT is vital to transform the intention to use WFDs into the adoption of WFDs.
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Affiliation(s)
- Naeem Hayat
- Global Entrepreneurship Research and Innovation Centre, Universiti Malaysia Kelantan, Kelantan, Malaysia
| | - Anas A Salameh
- College of Business Administration, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Abdullah Al Mamun
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, UKM Bangi, Selangor Darul Ehsan, Malaysia
| | - Syed Shah Alam
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, UKM Bangi, Selangor Darul Ehsan, Malaysia
| | - Noor Raihani Zainol
- Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, Kota Bharu, Kelantan, Malaysia
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17
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Li J, Zhang S, Ao W. Why is instant messaging not instant? Understanding users’ negative use behavior of instant messaging software. COMPUTERS IN HUMAN BEHAVIOR 2023. [DOI: 10.1016/j.chb.2023.107655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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18
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Ren L, Yang F, Gu C, Sun J, Liu Y. A study of factors influencing Chinese college students' intention of using metaverse technology for basketball learning: Extending the technology acceptance model. Front Psychol 2022; 13:1049972. [PMID: 36605282 PMCID: PMC9808391 DOI: 10.3389/fpsyg.2022.1049972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 11/30/2022] [Indexed: 12/24/2022] Open
Abstract
Introduction Based on the expansion of flow constructs based on the TAM model, this study assesses the impact of metaverse technology in college basketball courses. Methods We surveyed 849 effective samples using an online questionnaire survey, verified our analysis using structural equation modeling, and examined the moderating effect of gender on the path relationship. Results The perceived ease of use, the flow experience, and the perceived usefulness of the product are important predictors of behavioral intention. According to the study, perceived usefulness, and flow experience influence attitudes significantly. A moderating effect of gender is observed on perceived ease of use on the path to behavioral intention, and the results extend the theoretical research on the use of metaverse technology for basketball instruction and TAM. Discussion A metaverse-based learning experience can enhance the flow experience of basketball learning, thus increasing the willingness to use and the effectiveness of learning.
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Affiliation(s)
- Longfei Ren
- Department of Sports Science, Honam University, Gwangju, South Korea
| | - Fangfang Yang
- Department of Sports Science, Honam University, Gwangju, South Korea,*Correspondence: Fangfang Yang,
| | - Chao Gu
- Department of Culture and Arts Management, Honam University, Gwangju, South Korea
| | - Jie Sun
- Department of Culture and Arts Management, Honam University, Gwangju, South Korea
| | - Yunfeng Liu
- College of Arts and Design, Zhejiang Agriculture and Forest University, Hangzhou, China
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19
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Buckholz AP, Rosenblatt R. Remote monitoring of cognition in cirrhosis and encephalopathy: future opportunity and challenge. Metab Brain Dis 2022; 38:1737-1747. [PMID: 36507937 PMCID: PMC9743123 DOI: 10.1007/s11011-022-01134-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 11/24/2022] [Indexed: 12/14/2022]
Abstract
Hepatic Encephalopathy (HE) is a critically important complication of chronic liver disease and portal hypertension, but especially in early covert stages remains underdiagnosed and a common cause of hospitalization and morbidity. Defined by often subtle neuropsychiatric changes, significant cognitive deficits have been extensively described. While traditional methods of assessment remain underutilized in practice and subject to significant confounding with other diseases, mobile technology has emerged as a potential future tool to provide simple and dynamic cognitive assessments. This review discusses the proliferation of cognitive assessment tools, describing possible applications in encephalopathy and the challenges such an implementation may face. There are significant potential advantages to assessing cognition in real time in order to aid early detection and intervention and provide a more realistic measurement of real-world function. Despite this, there are issues with reliability, privacy, applicability and more which must be addressed prior to wide proliferation and acceptance for clinical use. Regardless, the rapid uptake of mobile technology in healthcare is likely to have significant implications for the future management of encephalopathy and liver disease at large.
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Affiliation(s)
- Adam P Buckholz
- NewYork-Presbyterian/Weill Cornell Medical College Division of Gastroenterology and Hepatology, New York, NY, 10021, USA
| | - Russell Rosenblatt
- NewYork-Presbyterian/Weill Cornell Medical College Division of Gastroenterology and Hepatology, New York, NY, 10021, USA.
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20
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Eymann J, Vach W, Fischer L, Jakob M, Gösele A. Comparing a Sensor for Movement Assessment with Traditional Physiotherapeutic Assessment Methods in Patients after Knee Surgery-A Method Comparison and Reproducibility Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:16581. [PMID: 36554461 PMCID: PMC9779175 DOI: 10.3390/ijerph192416581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 12/02/2022] [Accepted: 12/03/2022] [Indexed: 06/17/2023]
Abstract
Wearable sensors offer the opportunity for patients to perform a self-assessment of their function with respect to a variety of movement exercises. Corresponding commercial products have the potential to change the communication between patients and physiotherapists during the recovery process. Even if they turn out to be user-friendly, there remains the question to what degree the numerical results are reliable and comparable with those obtained by assessment methods traditionally used. To address this question for one specific recently developed and commercially available sensor, a method comparison study was performed. The sensor-based assessment of eight movement parameters was compared with an assessment of the same parameters based on test procedures traditionally used. Thirty-three patients recovering after arthroscopic knee surgery participated in the study. The whole assessment procedure was repeated. Reproducibility and agreement were quantified by the intra class correlation coefficient. The height of a one-leg vertical jump and the number of side hops showed high agreement between the two modalities and high reproducibility (ICC > 0.85). Due to differences in the set-up of the assessment, agreement could not be achieved for three mobility parameters, but even the correlation was only fair (r < 0.5). Knee stability showed poor agreement. Consequently, the use of the sensor can currently only be recommended for selected parameters. The variation in degree of agreement and reproducibility across different parameters clearly indicate the need for developing corresponding guidance for each new sensor put onto the market.
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Affiliation(s)
| | - Werner Vach
- Basel Academy for Quality and Research in Medicine, 4051 Basel, Switzerland
- Department of Environmental Sciences, University of Basel, 4056 Basel, Switzerland
| | | | - Marcel Jakob
- Crossklinik AG, 4054 Basel, Switzerland
- Medical Faculty, University of Basel, 4056 Basel, Switzerland
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21
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Xinyan Z, Mamun AA, Ali MH, Siyu L, Yang Q, Hayat N. Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach. Front Public Health 2022; 10:1016065. [PMID: 36388276 PMCID: PMC9650156 DOI: 10.3389/fpubh.2022.1016065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 10/12/2022] [Indexed: 01/28/2023] Open
Abstract
The world is witnessing an increasing number of senior adult residents who experience health issues. Healthcare innovation facilitates monitoring the health conditions of senior adults and reducing the burden on healthcare institutions. The study explored the effect of health improvement expectancy, effort expectancy, price value, perceived vulnerability, health consciousness, and perceived reliability on the intention and adoption of medical wearable devices (MWD) among senior adults in China. Furthermore, a cross-sectional design was adopted, while quantitative data was collected from 304 senior adults through an online survey. A hybrid approach of partial least square structural equational modeling and artificial neural network-based analysis technique was adopted. The findings demonstrated that health improvement expectancy, perceived vulnerability, price value, and perceived reliability significantly affected the intention to adopt MWDs. Moreover, the intention to adopt MWDs significantly positively affected the actual adoption of MWDs among senior adults. Although the moderating effect of the pre-existing conditions and income between the intention to use MWDs and actual adoption of MWDs was positive, it was not statistically significant. The artificial neural network analysis has proven that perceived reliability, price value, and vulnerability are the most critical factors contributing to the intention to use MWDs. The current study offered valuable insights into the factors affecting the intention and adoption of MWDs among senior adults. Following that, theoretical and practical contributions were documented to improve the ease of use and price value for the prospective users of MWDs. The correct healthcare policies could curtail the influx of senior adults into the hospital and empower these adults to track and manage their health issues at home.
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Affiliation(s)
- Zou Xinyan
- UCSI Graduate Business School, UCSI University, Kuala Lumpur, Malaysia
| | - Abdullah Al Mamun
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia,*Correspondence: Abdullah Al Mamun ;
| | - Mohd Helmi Ali
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Long Siyu
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Qing Yang
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Naeem Hayat
- Global Entrepreneurship Research and Innovation Centre, Universiti Malaysia Kelantan, Kota Bharu, Kelantan, Malaysia
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22
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Chapman BP, Lucey E, Boyer EW, Babu KM, Smelson D, Carreiro S. Perceptions on wearable sensor-based interventions for monitoring of opioid therapy: A qualitative study. Front Digit Health 2022; 4:969642. [PMID: 36339518 PMCID: PMC9634745 DOI: 10.3389/fdgth.2022.969642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 09/30/2022] [Indexed: 01/25/2023] Open
Abstract
Prescription opioid use is a risk factor for the development of opioid use disorder. Digital solutions, including wearable sensors, represent a promising opportunity for health monitoring, risk stratification and harm reduction in this treatment space. However, data on their usability and acceptability in individuals using opioids is limited. To address this gap, factors that impact usability and acceptability of wearable sensor-based opioid detection were qualitatively studied in participants enrolled in a wearable sensor-based opioid monitoring research study. At the conclusion of the monitoring period, participants were invited to take part in semi-structured interviews developed based on the technology acceptance model. Thematic analysis was conducted first using deductive, then inductive coding strategies. Forty-four participants completed the interview; approximately half were female. Major emergent themes include sensor usability, change in behavior and thought process related to sensor use, perceived usefulness in sensor-based monitoring, and willingness to have opioid use patterns monitored. Overall acceptance for sensor-based monitoring was high. Aesthetics, simplicity, and seamless functioning were all reported as key to usability. Perceived behavior changes related to monitoring were infrequent while perceived usefulness in monitoring was frequently projected onto others, requiring careful consideration regarding intervention development and targeting. Specifically, care must be taken to avoid stigma associated with opioid use and implied misuse. The design of sensor systems targeted for opioid use must also consider the physical, social, and cognitive alterations inherent in the respective disease processes compared to routine daily life.
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Affiliation(s)
- Brittany P. Chapman
- Department of Emergency Medicine, Division of Medical Toxicology, Tox(IN)novation Lab, UMass Chan Medical School, Worcester, MA, United States
| | - Evan Lucey
- Department of Emergency Medicine, Division of Medical Toxicology, Tox(IN)novation Lab, UMass Chan Medical School, Worcester, MA, United States
| | - Edward W. Boyer
- Department of Emergency Medicine, The Ohio State University, Columbus, OH, United States
| | - Kavita M. Babu
- Department of Emergency Medicine, Division of Medical Toxicology, Tox(IN)novation Lab, UMass Chan Medical School, Worcester, MA, United States
| | - David Smelson
- Department of Psychiatry, Division of Addiction Psychiatry, UMass Chan Medical School, Worcester, MA, United States
| | - Stephanie Carreiro
- Department of Emergency Medicine, Division of Medical Toxicology, Tox(IN)novation Lab, UMass Chan Medical School, Worcester, MA, United States,Correspondence: Stephanie Carreiro
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23
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Rafl J, Bachman TE, Rafl-Huttova V, Walzel S, Rozanek M. Commercial smartwatch with pulse oximeter detects short-time hypoxemia as well as standard medical-grade device: Validation study. Digit Health 2022; 8:20552076221132127. [PMID: 36249475 PMCID: PMC9554125 DOI: 10.1177/20552076221132127] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 09/22/2022] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVE We investigated how a commercially available smartwatch that measures peripheral blood oxygen saturation (SpO2) can detect hypoxemia compared to a medical-grade pulse oximeter. METHODS We recruited 24 healthy participants. Each participant wore a smartwatch (Apple Watch Series 6) on the left wrist and a pulse oximeter sensor (Masimo Radical-7) on the left middle finger. The participants breathed via a breathing circuit with a three-way non-rebreathing valve in three phases. First, in the 2-minute initial stabilization phase, the participants inhaled the ambient air. Then in the 5-minute desaturation phase, the participants breathed the oxygen-reduced gas mixture (12% O2), which temporarily reduced their blood oxygen saturation. In the final stabilization phase, the participants inhaled the ambient air again until SpO2 returned to normal values. Measurements of SpO2 were taken from the smartwatch and the pulse oximeter simultaneously in 30-s intervals. RESULTS There were 642 individual pairs of SpO2 measurements. The bias in SpO2 between the smartwatch and the oximeter was 0.0% for all the data points. The bias for SpO2 less than 90% was 1.2%. The differences in individual measurements between the smartwatch and oximeter within 6% SpO2 can be expected for SpO2 readings 90%-100% and up to 8% for SpO2 readings less than 90%. CONCLUSIONS Apple Watch Series 6 can reliably detect states of reduced blood oxygen saturation with SpO2 below 90% when compared to a medical-grade pulse oximeter. The technology used in this smartwatch is sufficiently advanced for the indicative measurement of SpO2 outside the clinic. TRIAL REGISTRATION ClinicalTrials.gov NCT04780724.
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Affiliation(s)
- Jakub Rafl
- Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic,Jakub Rafl, Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University in Prague, nam. Sitna 3105, CZ-272 01 Kladno, Czech Republic.
| | - Thomas E Bachman
- Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic
| | - Veronika Rafl-Huttova
- Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic
| | - Simon Walzel
- Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic
| | - Martin Rozanek
- Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic
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24
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Wang T, Wang W, Liang J, Nuo M, Wen Q, Wei W, Han H, Lei J. Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis. NPJ Digit Med 2022; 5:145. [PMID: 36109594 PMCID: PMC9476418 DOI: 10.1038/s41746-022-00692-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 09/01/2022] [Indexed: 11/24/2022] Open
Abstract
The mobile health (mHealth) industry is an enormous global market; however, the dropout or continuance of mHealth is a major challenge that is affecting its positive outcomes. To date, the results of studies on the impact factors have been inconsistent. Consequently, research on the pooled effects of impact factors on the continuance intention of mHealth is limited. Therefore, this study aims to systematically analyze quantitative studies on the continuance intention of mHealth and explore the pooled effect of each direct and indirect impact factor. Until October 2021, eight literature databases were searched. Fifty-eight peer-reviewed studies on the impact factors and effects on continuance intention of mHealth were included. Out of the 19 direct impact factors of continuance intention, 15 are significant, with attitude (β = 0.450; 95% CI: 0.135, 0.683), satisfaction (β = 0.406; 95% CI: 0.292, 0.509), health empowerment (β = 0.359; 95% CI: 0.204, 0.497), perceived usefulness (β = 0.343; 95% CI: 0.280, 0.403), and perceived quality of health life (β = 0.315, 95% CI: 0.211, 0.412) having the largest pooled effect coefficients on continuance intention. There is high heterogeneity between the studies; thus, we conducted a subgroup analysis to explore the moderating effect of different characteristics on the impact effects. The geographic region, user type, mHealth type, user age, and publication year significantly moderate influential relationships, such as trust and continuance intention. Thus, mHealth developers should develop personalized continuous use promotion strategies based on user characteristics.
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Affiliation(s)
- Tong Wang
- Department of Medical Informatics, School of Public Health, Jilin University, Changchun, Jilin Province, China
| | - Wei Wang
- Department of Medical Informatics, School of Public Health, Jilin University, Changchun, Jilin Province, China
| | - Jun Liang
- IT Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
- School of Public Health, Zhejiang University, Hangzhou, Zhejiang Province, China
- Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
| | - Mingfu Nuo
- Institute of Medical Technology, Health Science Center, Peking University, Beijing, China
| | - Qinglian Wen
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan Province, China
| | - Wei Wei
- Department of Gastroenterology, Wangjing hospital, Beijing, China
- Key Laboratory of Traditional Chinese Medicine Treatment of Functional Gastrointestinal Diseases, Chinese Academy of Medical Sciences, Beijing, China
| | - Hongbin Han
- Institute of Medical Technology, Health Science Center, Peking University, Beijing, China.
| | - Jianbo Lei
- Institute of Medical Technology, Health Science Center, Peking University, Beijing, China.
- Center for Medical Informatics, Health Science Center, Peking University, Beijing, China.
- School of Medical Informatics and Engineering, Southwest Medical University, Luzhou, Sichuan Province, China.
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Garikapati K, Turnbull S, Bennett RG, Campbell TG, Kanawati J, Wong MS, Thomas SP, Chow CK, Kumar S. The Role of Contemporary Wearable and Handheld Devices in the Diagnosis and Management of Cardiac Arrhythmias. Heart Lung Circ 2022; 31:1432-1449. [PMID: 36109292 DOI: 10.1016/j.hlc.2022.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 07/18/2022] [Accepted: 08/01/2022] [Indexed: 10/14/2022]
Abstract
Cardiac arrhythmias are associated with significant morbidity, mortality and economic burden on the health care system. Detection and surveillance of cardiac arrhythmias using medical grade non-invasive methods (electrocardiogram, Holter monitoring) is the accepted standard of care. Whilst their accuracy is excellent, significant limitations remain in terms of accessibility, ease of use, cost, and a suboptimal diagnostic yield (up to ∼50%) which is critically dependent on the duration of monitoring. Contemporary wearable and handheld devices that utilise photoplethysmography and the electrocardiogram present a novel opportunity for remote screening and diagnosis of arrhythmias. They have significant advantages in terms of accessibility and availability with the potential of enhancing the diagnostic yield of episodic arrhythmias. However, there is limited data on the accuracy and diagnostic utility of these devices and their role in therapeutic decision making in clinical practice remains unclear. Evidence is mounting that they may be useful in screening for atrial fibrillation, and anecdotally, for the diagnosis of other brady and tachyarrhythmias. Recently, there has been an explosion of patient uptake of such devices for self-monitoring of arrhythmias. Frequently, the clinician is presented such information for review and comment, which may influence clinical decisions about treatment. Further studies are needed before incorporation of such technologies in routine clinical practice, given the lack of systematic data on their accuracy and utility. Moreover, challenges with regulation of quality standards and privacy remain. This state-of-the-art review summarises the role of novel ambulatory, commercially available, heart rhythm monitors in the diagnosis and management of cardiac arrhythmias and their expanding role in the diagnostic and therapeutic paradigm in cardiology.
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Affiliation(s)
- Kartheek Garikapati
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Samual Turnbull
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Richard G Bennett
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Timothy G Campbell
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Juliana Kanawati
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Mary S Wong
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Stuart P Thomas
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Clara K Chow
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Saurabh Kumar
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia.
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26
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Yang F, Ren L, Gu C. A study of college students' intention to use metaverse technology for basketball learning based on UTAUT2. Heliyon 2022; 8:e10562. [PMID: 36132173 PMCID: PMC9483595 DOI: 10.1016/j.heliyon.2022.e10562] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 07/07/2022] [Accepted: 09/01/2022] [Indexed: 10/25/2022] Open
Abstract
Recent advancements in virtual reality technology have attracted increasing attention from enterprises and scholars, and many new related products have been launched. Due to the current COVID-19 epidemic, the non-face-to-face teaching environment will seriously affect students' basketball learning. We therefore combined basketball learning with metaverse technology, discussed basketball teaching in a virtual reality environment, and examined the influencing factors of college students' intentions to use metaverse technology. In the light of UTAUT2, a new research model was proposed, and quantitative research was carried out. The results of a survey of 1074 valid samples revealed that habits and attitudes are crucial factors in the success of basketball learning using a metaverse. The findings also indicate that grade and gender are moderator variables.
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Affiliation(s)
- Fangfang Yang
- Department of Sports Science of Honam University, Gwangju, 62399, South Korea
| | - Longfei Ren
- Department of Sports Science of Honam University, Gwangju, 62399, South Korea
| | - Chao Gu
- Department of Culture and Arts Management of Honam University, Gwangju, 62399, South Korea
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27
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Hayat N, Zainol NR, Salameh AA, Al Mamun A, Yang Q, Md Salleh MF. How health motivation moderates the effect of intention and usage of wearable medical devices? An empirical study in Malaysia. Front Public Health 2022; 10:931557. [PMID: 36045735 PMCID: PMC9421139 DOI: 10.3389/fpubh.2022.931557] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 07/27/2022] [Indexed: 01/24/2023] Open
Abstract
Mobile technology is popular because it facilitates users in multiple ways. This technology is revolutionising the healthcare industry, and mobile-based wearable medical devices (WMDs) are becoming common. Technology adoption is always challenging, and technology value is based on the technology attributes and personal inclination towards using the technology. This study investigates how the perceived product value is influenced by compatibility, cost, personal privacy, technology accuracy, and usefulness. The perceived product value instigates the intention to use wearable medical devices and health motivation (HMT), and the intention to use promotes the adoption of WMDs. Furthermore, the relationship between the intention to use and the adoption of WMDs is moderated by HMT. The current work employed a cross-sectional research design, and data were collected through an online survey of Malaysian adults. Data analysis was performed using partial least squares structural equation modelling (PLS-SEM). The analysis revealed that the WMDs' compatibility, cost, and technology accuracy significantly influenced the WMDs' value. Besides, the perceived product value impacted the intention to use WMDs, while HMT and intention to use WMDs insignificantly influenced the adoption of WMDs. Finally, HMT significantly moderated the relationship between the intention to use and the adoption of WMDs. This study also reports the limitations and future research opportunities.
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Affiliation(s)
- Naeem Hayat
- Global Entrepreneurship Research and Innovation Centre, Universiti Malaysia Kelantan, Kota Bharu, Malaysia
| | - Noor Raihani Zainol
- Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, Kota Bharu, Malaysia
| | - Anas A. Salameh
- College of Business Administration, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Abdullah Al Mamun
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Malaysia,*Correspondence: Abdullah Al Mamun ;
| | - Qing Yang
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Malaysia
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28
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Gomez-Correa M, Cruz-Ortiz D. Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22165931. [PMID: 36015692 PMCID: PMC9416605 DOI: 10.3390/s22165931] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/29/2022] [Accepted: 08/03/2022] [Indexed: 05/30/2023]
Abstract
Surface electromyography (sEMG) is a non-invasive measure of electrical activity generated due to muscle contraction. In recent years, sEMG signals have been increasingly used in diverse applications such as rehabilitation, pattern recognition, and control of orthotic and prosthetic systems. This study presents the development of a versatile multi-channel sEMG low-cost wearable band system to acquire 4 signals. In this case, the signals acquired with the proposed device have been used to detect hand movements. However, the WyoFlex band could be used in some sections of the arm or the leg if the section's diameter matches the diameter of the WyoFlex band. The designed WyoFlex band was fabricated using three-dimensional (3D) printing techniques employing thermoplastic polyurethane and polylactic acid as manufacturing materials. Then, the proposed wearable electromyographic system (WES) consists of 2 WyoFlex bands, which simultaneously allow the wireless acquisition of 4 sEMG channels of each forearm. The collected sEMG can be visualized and stored for future post-processing stages using a graphical user interface designed in Node-RED. Several experimental tests were conducted to verify the performance of the WES. A dataset with sEMG collected from 15 healthy humans has been obtained as part of the presented results. In addition, a classification algorithm based on artificial neural networks has been implemented to validate the usability of the collected sEMG signals.
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Affiliation(s)
- Manuela Gomez-Correa
- Medical Robotics and Biosignal Processing Laboratory, Unidad Profesional Interdisciplinaria de Biotecnología, Instituto Politécnico Nacional, Mexico City 07340, Mexico
- Facultad de Ingeniería, Universidad de Antioquia, Medellin 050010, Colombia
| | - David Cruz-Ortiz
- Medical Robotics and Biosignal Processing Laboratory, Unidad Profesional Interdisciplinaria de Biotecnología, Instituto Politécnico Nacional, Mexico City 07340, Mexico
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29
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Abir FF, Alyafei K, Chowdhury MEH, Khandakar A, Ahmed R, Hossain MM, Mahmud S, Rahman A, Abbas TO, Zughaier SM, Naji KK. PCovNet: A presymptomatic COVID-19 detection framework using deep learning model using wearables data. Comput Biol Med 2022; 147:105682. [PMID: 35714504 PMCID: PMC9170596 DOI: 10.1016/j.compbiomed.2022.105682] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 05/19/2022] [Accepted: 05/30/2022] [Indexed: 11/16/2022]
Abstract
While the advanced diagnostic tools and healthcare management protocols have been struggling to contain the COVID-19 pandemic, the spread of the contagious viral pathogen before the symptom onset acted as the Achilles' heel. Although reverse transcription-polymerase chain reaction (RT-PCR) has been widely used for COVID-19 diagnosis, they are hardly administered before any visible symptom, which provokes rapid transmission. This study proposes PCovNet, a Long Short-term Memory Variational Autoencoder (LSTM-VAE)-based anomaly detection framework, to detect COVID-19 infection in the presymptomatic stage from the Resting Heart Rate (RHR) derived from the wearable devices, i.e., smartwatch or fitness tracker. The framework was trained and evaluated in two configurations on a publicly available wearable device dataset consisting of 25 COVID-positive individuals in the span of four months including their COVID-19 infection phase. The first configuration of the framework detected RHR abnormality with average Precision, Recall, and F-beta scores of 0.946, 0.234, and 0.918, respectively. However, the second configuration detected aberrant RHR in 100% of the subjects (25 out of 25) during the infectious period. Moreover, 80% of the subjects (20 out of 25) were detected during the presymptomatic stage. These findings prove the feasibility of using wearable devices with such a deep learning framework as a secondary diagnosis tool to circumvent the presymptomatic COVID-19 detection problem.
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Affiliation(s)
- Farhan Fuad Abir
- Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, 1000, Bangladesh
| | - Khalid Alyafei
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha, 2713, Qatar
| | | | - Amith Khandakar
- Department of Electrical Engineering, Qatar University, Doha, 2713, Qatar
| | - Rashid Ahmed
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha, 2713, Qatar; Biomedical Research Centre, Qatar University, Doha, 2713, Qatar
| | | | - Sakib Mahmud
- Department of Electrical Engineering, Qatar University, Doha, 2713, Qatar
| | - Ashiqur Rahman
- Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, Japan
| | - Tareq O Abbas
- Urology Division, Surgery Department, Sidra Medicine, Doha, Qatar, 26999
| | - Susu M Zughaier
- Department of Basic Medical Sciences, College of Medicine, QU Health, Qatar University, Doha, 2713, Qatar
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30
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Yang Q, Al Mamun A, Hayat N, Jingzu G, Hoque ME, Salameh AA. Modeling the Intention and Adoption of Wearable Fitness Devices: A Study Using SEM-PLS Analysis. Front Public Health 2022; 10:918989. [PMID: 35875013 PMCID: PMC9301884 DOI: 10.3389/fpubh.2022.918989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/09/2022] [Indexed: 11/16/2022] Open
Abstract
Wearable fitness devices (WFDs) are prevalent personal technology that empowers the users' management and supervision of their personal health. The current study explored the impact of health consciousness, health motivation, perceived cost, compatibility, usefulness, and perceived technology accuracy with the intention to use the WFDs. Furthermore, the users' conspicuous consumption and intention promote the usage of WFDs. A cross-sectional and quantitative research design was utilized for the current study, followed by data collection through social media and a final analysis with 1,071 samples data. The data analysis was accomplished with the partial least square regression structural equation modeling. The findings of this study revealed that the users' level of health consciousness, perceived compatibility, usefulness, perceived cost, and technology accuracy significantly influenced the intention to use WFDs. However, the conspicuous consumption and intention indicated the support for the usage behavior of the WFDs. This behavior significantly moderated the relationship between the intention and usage behavior for the WFDs. This study contributed to the theoretical realm for prompting the intention to use the WFDs with personal protection motivation that depicts the coping strategy and technology level attributes that form the intention to use WFDs. The WFDs manufacturers should therefore focus on developing WFDs features that harness usage behavior among the adults. Developing the personal responsibility to reduce the burden of the healthcare system and taking care of personal health could promote the usage of the WFDs.
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Affiliation(s)
- Qing Yang
- UKM Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Malaysia
| | - Abdullah Al Mamun
- UKM Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Malaysia
| | - Naeem Hayat
- Global Entrepreneurship Research and Innovation Centre, Universiti Malaysia Kelantan, Kota Bharu, Malaysia
| | - Gao Jingzu
- UCSI Graduate Business School, UCSI University, Kuala Lumpur, Malaysia
| | | | - Anas A Salameh
- College of Business Administration, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
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31
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Lee JH, Lee KH, Kim HJ, Youk H, Lee HY. Effective Prevention and Management Tools for Metabolic Syndrome Based on Digital Health-Based Lifestyle Interventions Using Healthcare Devices. Diagnostics (Basel) 2022; 12:1730. [PMID: 35885634 PMCID: PMC9324676 DOI: 10.3390/diagnostics12071730] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 07/13/2022] [Accepted: 07/14/2022] [Indexed: 01/09/2023] Open
Abstract
Digital health-based lifestyle interventions (e.g., mobile applications, short messaging service, wearable devices, social media, and interactive websites) are widely used to manage metabolic syndrome (MetS). This study aimed to confirm the utility of self-care for prevention or management of MetS. We recruited 106 participants with one or more MetS risk factors from December 2019 to September 2020. Participants were provided five healthcare devices and applications. Characteristics were compared at baseline and follow-up to examine changes in risk factors, engagement, persistence, and physical activity (analyzed through device use frequency and lifestyle interventions performed). Participants with 1-2 MetS risk factors showed statistically significant reductions in waist circumference (WC) and blood pressure (BP). Participants with ≥3 MetS risk factors showed statistically significant reductions in risk factors including weight, body mass index, WC, BP, and fasting blood sugar (FBS). The prevention and improvement groups used more healthcare devices than the other groups. Smartwatch was the most frequently used device (5 times/week), and physical activity logged more than 7000 steps/week. WC, BP, and FBS of the improvement group were reduced by more than 40%. Based on engagement, persistence, and physical activity, digital health-based lifestyle interventions could be helpful for MetS prevention and management.
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Affiliation(s)
| | - Kang-Hyun Lee
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Korea; (J.-H.L.); (H.-J.K.); (H.Y.); (H.-Y.L.)
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32
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Magic of 5G Technology and Optimization Methods Applied to Biomedical Devices: A Survey. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12147096] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Wireless networks have gained significant attention and importance in healthcare as various medical devices such as mobile devices, sensors, and remote monitoring equipment must be connected to communication networks. In order to provide advanced medical treatments to patients, high-performance technologies such as the emerging fifth generation/sixth generation (5G/6G) are required for transferring data to and from medical devices and in addition to their major components developed with improved optimization methods which are substantially needed and embedded in them. Providing intelligent system design is a challenging task in medical applications, as it affects the whole behaviors of medical devices. A critical review of the medical devices and the various optimization methods employed are presented in this paper, to pave the way for designers to develop an apparatus that is applicable in the healthcare industry under 5G technology and future 6G wireless networks.
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33
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Lima FV, Kadiyala V, Huang A, Agusala K, Cho D, Freeman AM, Druz R. At the Crossroads! Time to Start Taking Smartwatches Seriously. Am J Cardiol 2022; 179:96-101. [PMID: 35842279 DOI: 10.1016/j.amjcard.2022.06.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 05/30/2022] [Accepted: 06/06/2022] [Indexed: 11/26/2022]
Abstract
Patients have demonstrated a growing interest in using wearable devices, particularly smartwatches, to monitor and improve their cardiovascular wellness. Wearable devices are now one of the fastest growing sectors of the technology industry, and big technology companies, such as Apple (Apple Watch), Google (Fitbit), and Samsung (Galaxy), have engineered smartwatch features that are capable of monitoring biometrics, such as heart rhythm, heart rate, blood pressure, and sleep. These devices hold significant potential to impact the relation between cardiologists and their patients, but concerns exist about device trustworthiness to detect pertinent data points and deliver alerts with accuracy. How these devices' features will interplay with cardiologists' workflow has also yet to be defined and requires thoughtful implementation. Furthermore, the success of smartwatches as medical devices is dependent on patients' continuous use. Keeping patients engaged with their devices through leveraging behavioral factors may lead to achieving and optimizing healthcare goals. Socioeconomic disparities and privacy concerns are other barriers in the path forward. Cardiovascular professional societies are uniquely poised to help impact how these devices are eventually accepted and used in everyday practice. In conclusion, engagement and collaboration with big tech companies will help guide how this market grows.
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Affiliation(s)
- Fabio V Lima
- Cardiovascular Institute, Warren Alpert Medical School of Brown University, Providence, Rhode Island.
| | - Vishnu Kadiyala
- Cardiovascular Institute, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Alice Huang
- Cardiovascular Institute, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Kartik Agusala
- Division of Cardiology, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - David Cho
- Division of Cardiovascular Medicine, UCLA David Geffen School of Medicine, Los Angeles, California
| | - Andrew M Freeman
- Division of Cardiology, Department of Medicine, National Jewish Health, Denver, Colorado
| | - Regina Druz
- Department of Cardiology, St. Francis Hospital, Roslyn, New York
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34
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Yang Q, Al Mamun A, Hayat N, Salleh MFM, Jingzu G, Zainol NR. Modelling the mass adoption potential of wearable medical devices. PLoS One 2022; 17:e0269256. [PMID: 35675373 PMCID: PMC9176812 DOI: 10.1371/journal.pone.0269256] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 05/17/2022] [Indexed: 11/24/2022] Open
Abstract
Digital technologies empower users to manage their health and reduce the burden on the public health system. The mass adoption of wearable medical devices (WMDs) promotes the ageing population’s confidence besides facilitating users. Thus, the current study aims to empirically evaluate the formation of perceived product value (PPV) with the WMDs’ computability, usefulness, cost, and accuracy, the intention to use WMDs influenced by health consciousness (HCS), health anxiety (HAY), product value, and perceived critical mass (PCM), and later the adoption of WMDs among Chinese adults. The study examined the mediating effect of PPV on the relationship between the intention to use WMDs and perceived compatibility (PCT), perceived cost (PCO), perceived usefulness (PUS), and perceived technology accuracy (PTA). This study adopted a cross-sectional approach and used an online survey to collect quantitative data from 1,160 Chinese adults. Data analysis was performed using the partial least squares structural equation modelling (PLS-SEM). Results showed that PCT, PUS, and PTA significant positive effect on PPV. Meanwhile, HCS, PCM, and PPV has a significant positive effect on intention to use WMDs, and the intention to use WMDs and PCM influenced the adoption of WMDs. Consequently, the analysis confirmed that PPV mediated the relationships between the intention to use WMD and PCT, PUS, and PTA. The WMD cost must be reduced to enhance the value of WMDs. Finally, the study’s implications, limitations, and suggestions for future studies are discussed.
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Affiliation(s)
- Qing Yang
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, UKM Bangi, Bangi, Malaysia
| | - Abdullah Al Mamun
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, UKM Bangi, Bangi, Malaysia
- * E-mail: ,
| | - Naeem Hayat
- Global Entrepreneurship Research and Innovation Centre, Universiti Malaysia Kelantan, Kota Bharu, Malaysia
| | - Mohd Fairuz Md. Salleh
- UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, UKM Bangi, Bangi, Malaysia
| | - Gao Jingzu
- UCSI Graduate Business School, UCSI University, Cheras, Kuala Lumpur, Malaysia
| | - Noor Raihani Zainol
- Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, Kota Bharu, Malaysia
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Stuart T, Hanna J, Gutruf P. Wearable devices for continuous monitoring of biosignals: Challenges and opportunities. APL Bioeng 2022; 6:021502. [PMID: 35464617 PMCID: PMC9010050 DOI: 10.1063/5.0086935] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 03/29/2022] [Indexed: 12/17/2022] Open
Abstract
The ability for wearable devices to collect high-fidelity biosignals continuously over weeks and months at a time has become an increasingly sought-after characteristic to provide advanced diagnostic and therapeutic capabilities. Wearable devices for this purpose face a multitude of challenges such as formfactors with long-term user acceptance and power supplies that enable continuous operation without requiring extensive user interaction. This review summarizes design considerations associated with these attributes and summarizes recent advances toward continuous operation with high-fidelity biosignal recording abilities. The review also provides insight into systematic barriers for these device archetypes and outlines most promising technological approaches to expand capabilities. We conclude with a summary of current developments of hardware and approaches for embedded artificial intelligence in this wearable device class, which is pivotal for next generation autonomous diagnostic, therapeutic, and assistive health tools.
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Affiliation(s)
- Tucker Stuart
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona 85721, USA
| | - Jessica Hanna
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona 85721, USA
| | - Philipp Gutruf
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona 85721, USA
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona 85721, USA
- Bio5 Institute, University of Arizona, Tucson, Arizona 85721, USA
- Neuroscience GIDP, University of Arizona, Tucson, Arizona 85721, USA
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36
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Bianchi C, Tuzovic S, Kuppelwieser VG. Investigating the drivers of wearable technology adoption for healthcare in South America. INFORMATION TECHNOLOGY & PEOPLE 2022. [DOI: 10.1108/itp-01-2021-0049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PurposeThis empirical study examines the drivers of consumer intention to adopt wearable technology for healthcare in a South American country. Specifically, it proposes and tests a model of nonuser consumer intention to adopt fitness trackers for healthcare purpose in Chile.Design/methodology/approachThis study draws on the technology acceptance framework UTAUT2 to develop and test a conceptual model of wearable technology adoption. Data were collected through an online survey applied to 470 nonusers of wearable technology in Santiago, Chile.FindingsFindings indicate that hedonic motivation, social influence and perceived usefulness have the strongest influence on intention to adopt fitness trackers in Chile for healthcare. In addition, health motivation is an indirect predictor of consumer's intention to adopt wearable technology through its effect on perceived usefulness.Practical implicationsThe study contributes to a better understanding of consumer intention to adopt wearable technology for healthcare objectives in a less developed country in South America. Findings are useful for wearable technology managers, retail business and public policymakers.Originality/valueDespite the vast growth and importance of wearable technology for healthcare purposes, academic research considering less developed countries is scarce, especially the South American region. The proposed model and findings can extend this research gap. Theoretical and managerial implications are discussed as well as implications for public policy.
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37
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Kim HJ, Lee KH, Lee JH, Youk H, Lee HY. The Effect of a Mobile and Wearable Device Intervention on Increased Physical Activity to Prevent Metabolic Syndrome: Observational Study. JMIR Mhealth Uhealth 2022; 10:e34059. [PMID: 35200145 PMCID: PMC8914734 DOI: 10.2196/34059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 11/30/2022] Open
Abstract
Background Research on whether wearable devices and app-based interventions can effectively prevent metabolic syndrome (MetS) by increasing physical activity (PA) among middle-aged people living in the rural areas of South Korea remains insufficient. Objective The aim of this study was to determine whether mobile and wearable device interventions can improve health indicators, including PA, in MetS risk groups in rural South Korea. Methods In this clinical trial, performed from December 2019 to June 2020, participants were asked to use a wearable device (GalaxyWatch Active1) alone (standard intervention) or the wearable device and mobile app (Yonsei Health Korea) (enhanced intervention). Clinical measures and International Physical Activity Questionnaire (IPAQ) scores were evaluated initially and after 6 months. The number of steps was monitored through the website. The primary outcome was the difference in PA and clinical measures between the enhanced intervention and standard intervention groups. The secondary outcome was the decrease in MetS factors related to the change in PA. Results A total of 267 participants were randomly selected, 221 of whom completed the 6-month study. Among the 221 participants, 113 were allocated to the enhanced intervention group and 108 were allocated to the standard intervention group. After 6 months, the body weight and BMI for the enhanced intervention group decreased by 0.6 (SD 1.87) and 0.21 (SD 0.76), respectively (P<.001). In both groups, systolic blood pressure, diastolic blood pressure, waist circumference, and glycated hemoglobin A1c (HbA1c) decreased (P<.001). The total PA was approximately 2.8 times lower in the standard intervention group (mean 44.47, SD 224.85) than in the enhanced intervention group (mean 124.36, SD 570.0). Moreover, the enhanced intervention group achieved the recommended level of moderate to vigorous physical activity (MVPA), whereas the standard intervention group did not (188 minutes/week vs 118 minutes/week). Additionally, the number of participants in the enhanced intervention group (n=113) that reached 10,000 daily steps or more after the intervention increased from 9 (8.0%) to 26 (23.1%) (P=.002), whereas this number did not increase significantly in the standard intervention group (n=108), from 8 (7.4%) to 16 (14.8%) (P=.72). The number of participants without any MetS factors increased by 12 (11%) and 8 (7%) in the enhanced and standard intervention group, respectively. Conclusions PA monitoring and an intervention using wearable devices were effective in preventing MetS in a rural population in Korea. Blood pressure, waist circumference, and HbA1c were improved in both intervention groups, which were effective in reducing MetS factors. However, only the participants in the enhanced intervention group continuously increased their MVPA and step counts above the recommended level to prevent MetS. Body weight and BMI were further improved, and a higher number of participants with zero MetS factors was attained from the enhanced intervention. Trial Registration Clinical Research Information Service KCT0005783; https://cris.nih.go.kr/cris/search/detailSearch.do/16123
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Affiliation(s)
- Hee Jin Kim
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Kang Hyun Lee
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Jung Hun Lee
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Hyun Youk
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Hee Young Lee
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
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Yoon J, Lee M, Ahn JS, Oh D, Shin SY, Chang YJ, Cho J. Development and Validation of Digital Health Technology Literacy Assessment Questionnaire. J Med Syst 2022; 46:13. [PMID: 35072816 PMCID: PMC8784987 DOI: 10.1007/s10916-022-01800-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 01/17/2022] [Indexed: 11/23/2022]
Abstract
In clinical practice, assessing digital health literacy is important to identify patients who may encounter difficulties adapting to digital health using digital technology and service. We developed the Digital Health Technology Literacy Assessment Questionnaire (DHTL-AQ) to assess the ability to use digital health technology, services, and data. The DHTL-AQ was developed in three phases. In the first phase, the conceptual framework and domains and items were generated from a systematic literature review using relevant theory and surveys. In the second phase, a cross-sectional survey with 590 adults age ≥ 18 years was conducted at an academic hospital in Seoul, Korea in January and February 2020 to test face validity of the items. Then, psychometric validation was conducted to determine the final items and cut-off scores of the DHTL-AQ. The eHealth literacy scale, the Newest Vital Sign, and 10 mobile app task ability assessments were examined to test validity. The final DHTL-AQ includes 34 items in two domains (digital functional and digital critical literacy) and 4 categories (Information and Communications Technology terms, Information and Communications Technology icons, use of an app, evaluating reliability and relevance of health information). The DHTL-AQ had excellent internal consistency (overall Cronbach’s α = 0.95; 0.87–0.94 for subtotals) and acceptable model fit (CFI = 0.821, TLI = 0.807, SRMR = 0.065, RMSEA = 0.090). The DHTL-AQ was highly correlated with task ability assessment (r = 0.7591), and moderately correlated with the eHealth literacy scale (r = 0.5265) and the Newest Vital Sign (r = 0.5929). The DHTL-AQ is a reliable and valid instrument to measure digital health technology literacy.
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Rha JY, Nam Y, Ahn SY, Kim J, Chang Y, Jang J, Kurita K, Park JY, Eom K, Moon H, Jung MH, Kim YJ, Hwang JE, Choo H. What drives the use of wearable healthcare devices? A cross-country comparison between the US and Korea. Digit Health 2022; 8:20552076221120319. [PMID: 36003315 PMCID: PMC9393678 DOI: 10.1177/20552076221120319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 07/29/2022] [Indexed: 11/15/2022] Open
Abstract
Objective Given the rapid growth of the wearable healthcare device market, we examined
the associations among health-related and technology-related characteristics
of using wearable healthcare devices and demonstrated how the associations
differ between the US and Korean users. Methods Online self-administered surveys were conducted with 4098 participants (3035
in the US and 1063 in Korea) who were recruited through two online survey
service providers based on quota sampling. The primary outcome was the use
of wearable healthcare devices. Seven health-related, two
technology-related, and five socio-demographic factors were included as
explanatory variables. Binary logistic regression analyses and a Chow test
were conducted. Results The health-related characteristics that were significantly associated with
using wearable healthcare devices included disease-related worries
(β = 0.11**), health information seeking (β = 0.26***), physical activity
(β = 0.62***), and health-related expenditures ($50–$199, β = 0.38***; $200
or more, β = 0.56***). Hedonic (β = 0.33***), social (β = 0.31***), and
cognitive innovativeness (β = 0.14*) also exhibited positive relationships.
Younger, higher earner, and individuals with a child were more likely to use
wearable healthcare devices. However, for Korean users, several associations
disappeared including health information seeking, hedonic and social
innovativeness, age, and household income. Conclusions Key drivers of using wearable healthcare devices include greater concern
about a specific illness, active engagement in health-promoting behaviors,
and hedonic and social motivation to adopt new technologies. However, more
country-specific considerations are needed in future studies to identify the
main benefits for target markets.
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Affiliation(s)
- Jong-Youn Rha
- Department of Consumer Science, Seoul National University, Seoul, Gwanak-gu, Korea
- Research Institute of Human Ecology, Seoul National University, Seoul, Gwanak-gu, Korea
| | - Youngwon Nam
- Department of Consumer Science, Seoul National University, Seoul, Gwanak-gu, Korea
- Research Institute of Human Ecology, Seoul National University, Seoul, Gwanak-gu, Korea
| | - Sun Young Ahn
- School of Business and Leadership, University of Puget Sound, Tacoma, WA, USA
| | - Jihye Kim
- Research Institute of Human Ecology, Seoul National University, Seoul, Gwanak-gu, Korea
| | - Youchung Chang
- Department of Consumer Science, Seoul National University, Seoul, Gwanak-gu, Korea
| | - Jisu Jang
- Department of Consumer Science, Seoul National University, Seoul, Gwanak-gu, Korea
| | - Keiko Kurita
- Samsung Research America, Mountain View, CA, USA
| | - Jin-Young Park
- Advanced Sensor Lab, Device Research Center, SAIT, Samsung Electronics, Suwon-si, Gyeonggi, Korea
| | - Kunsun Eom
- Advanced Sensor Lab, Device Research Center, SAIT, Samsung Electronics, Suwon-si, Gyeonggi, Korea
| | - Hyunseok Moon
- Advanced Sensor Lab, Device Research Center, SAIT, Samsung Electronics, Suwon-si, Gyeonggi, Korea
| | - Myoung Hoon Jung
- Advanced Sensor Lab, Device Research Center, SAIT, Samsung Electronics, Suwon-si, Gyeonggi, Korea
| | - Yoon Jae Kim
- Advanced Sensor Lab, Device Research Center, SAIT, Samsung Electronics, Suwon-si, Gyeonggi, Korea
| | - Jeong-Eun Hwang
- Advanced Sensor Lab, Device Research Center, SAIT, Samsung Electronics, Suwon-si, Gyeonggi, Korea
| | - HyucK Choo
- Advanced Sensor Lab, Device Research Center, SAIT, Samsung Electronics, Suwon-si, Gyeonggi, Korea
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Rha JS, Lee HH. Research trends in digital transformation in the service sector: a review based on network text analysis. SERVICE BUSINESS 2022. [PMCID: PMC8819194 DOI: 10.1007/s11628-022-00481-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Digital transformation has influenced value chain operations of both manufacturing and service firms. This study examined digital transformation in the service sector through network text analysis of 330 related articles published during the past 10 years. The selected papers’ keyword link relations were analyzed to create network maps of research topics, ranging from traditional to emerging ideas of researchers. Dominant research topics and their clusters were identified using centrality and community analyses, and research trends were identified. The results of this study will help researchers and practitioners in the relevant fields capture the overall picture of the field.
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Affiliation(s)
- Jin Sung Rha
- School of Business Administration, Dankook University, Yongin-si, 16890 South Korea
| | - Hong-Hee Lee
- Greehey School of Business, St. Mary’s University, San Antonio, TX 78228 USA
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Skare M, Riberio Soriano D. Explaining COVID-19 shock wave mechanism in the European service industry using convergence clubs analysis. SERVICE BUSINESS 2022. [PMCID: PMC8592081 DOI: 10.1007/s11628-021-00471-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
The impact of COVID-19 on the economy and business is a major issue. We define convergence clubs as countries with the same impact of COVID-19 on service turnover by using a convergence algorithm for testing and clustering. We repeat the procedure in the hospitality and food industry, information and communication, transport, and storage. The impact of COVID-19 on each convergence club identified in the study varies empirically. The findings suggest that the impact of COVID-19 varies between countries and industries depending on the firm’s agility, innovation, ownership, digital adoption, customer perception, pandemic status, and state financial assistance of companies.
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Shin Y, Hur WM, Hwang H. Impacts of customer incivility and abusive supervision on employee performance: a comparative study of the pre- and post-COVID-19 periods. SERVICE BUSINESS 2022. [PMCID: PMC8345907 DOI: 10.1007/s11628-021-00456-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
The purpose of our study was to assess the effects of customer incivility and abusive supervision on employee performance during the pre- and post-COVID-19 periods. Our two-wave panel data collected from South Korean frontline service employees revealed that the indirect effect of customer incivility on job performance through emotional exhaustion became more pronounced after the onset of the pandemic. Furthermore, during the pandemic, customer incivility exerted a greater indirect effect on job performance through emotional exhaustion than abusive supervision. These findings offer insights for effectively managing frontline service employees’ stress in times of crisis, including pandemics.
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Affiliation(s)
| | - Won-Moo Hur
- College of Business Administration, Inha University, 100 Inha-ro, Minchuhol-gu, Incheon, 22212 Korea
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Exploring the factors influencing adoption of health-care wearables among generation Z consumers in India. JOURNAL OF INFORMATION COMMUNICATION & ETHICS IN SOCIETY 2021. [DOI: 10.1108/jices-07-2021-0072] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Purpose
The purpose of this study is to identify the major factors influencing the adoption of health-care wearables in generation Z (Gen Z) customers in India. A conceptual framework using push pull and mooring (PPM) adoption theory was developed.
Design/methodology/approach
Data was collected from 208 Gen Z customers based on 5 constructs related to the adoption of health-care wearables. Confirmatory factor analysis and structural equation modelling was used to analyse the responses. The mediation paths were analysed using bootstrapping method and examination of the standardized direct and indirect effects in the model.
Findings
The study results indicated that the antecedent factors consisted of push (real-time health information availability), pull (normative environment) and mooring (decision self-efficacy) factors. The mooring factor (MOOR) was related to the push factor but not the pull factor. The MOOR, in turn, was related to the switching intention of Gen Z customers for health wearables adoption.
Research limitations/implications
The research study extended the literature related to the PPM theory in the context of the adoption of health wearables among Gen Z customers in India.
Practical implications
The study outcome would enable managers working in health wearable organizations to understand consumer behaviour towards health wearables.
Social implications
The use of health wearables among Gen Z individuals would lead to future generations adopting a healthy lifestyle resulting in an effective workforce and better economy.
Originality/value
This was one of the few studies which have explored the PPM theory to explore the factors for the adoption of health wearables among Gen Z customers in India.
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Ajmal, Boonya-Ananta T, Rodriguez AJ, Du Le VN, Ramella-Roman JC. Monte Carlo analysis of optical heart rate sensors in commercial wearables: the effect of skin tone and obesity on the photoplethysmography (PPG) signal. BIOMEDICAL OPTICS EXPRESS 2021; 12:7445-7457. [PMID: 35003845 PMCID: PMC8713672 DOI: 10.1364/boe.439893] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 09/23/2021] [Accepted: 10/05/2021] [Indexed: 08/23/2023]
Abstract
Commercially available wearable devices have been used for fitness and health management and their demand has increased over the last ten years. These "general wellness" and heart-rate monitoring devices have been cleared by the Food and Drug Administration for over-the-counter use, yet anecdotal and more systematic reports seem to indicate that their error is higher when used by individuals with elevated skin tone and high body mass index (BMI). In this work, we used Monte Carlo modeling of a photoplethysmography (PPG) signal to study the theoretical limits of three different wearable devices (Apple Watch series 5, Fitbit Versa 2 and Polar M600) when used by individuals with a BMI range of 20 to 45 and a Fitzpatrick skin scale 1 to 6. Our work shows that increased BMI and skin tone can induce a relative loss of signal of up to 61.2% in Fitbit versa 2, 32% in Apple S5 and 32.9% in Polar M600 when considering the closest source-detector pair configuration in these devices.
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Affiliation(s)
- Ajmal
- Department of Biomedical Engineering,
Florida International University, 10555 W
Flagler St, Miami, FL 33174, USA
| | - Tananant Boonya-Ananta
- Department of Biomedical Engineering,
Florida International University, 10555 W
Flagler St, Miami, FL 33174, USA
| | - Andres J. Rodriguez
- Department of Biomedical Engineering,
Florida International University, 10555 W
Flagler St, Miami, FL 33174, USA
| | - V. N. Du Le
- Department of Biomedical Engineering,
Florida International University, 10555 W
Flagler St, Miami, FL 33174, USA
| | - Jessica C. Ramella-Roman
- Department of Biomedical Engineering,
Florida International University, 10555 W
Flagler St, Miami, FL 33174, USA
- Herbert Wertheim College of Medicine,
Florida International University, 11200 SW
8th St, Miami, FL 33199, USA
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Uzir MUH, Al Halbusi H, Lim R, Jerin I, Abdul Hamid AB, Ramayah T, Haque A. Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19. TECHNOLOGY IN SOCIETY 2021; 67:101780. [PMID: 34697510 PMCID: PMC8528563 DOI: 10.1016/j.techsoc.2021.101780] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/07/2021] [Accepted: 10/11/2021] [Indexed: 05/05/2023]
Abstract
The evolution of Artificial Intelligence (AI) has revolutionized many aspects of human life, including healthcare. Amidst the Covid-19 pandemic, AI-enabled smartwatches are being used to help users to self-monitor and self-manage their health. Using a framework based on Stimulus-Organism-Response (S-O-R) theory, this present study aimed to explore the use of AI-enabled smartwatches for health purposes, in particular the effects of product quality, service quality, perceived convenience, and perceived ease of use on user experience, trust and user satisfaction. Based on a purposive survey sample of 486 smartphone users in Bangladesh, data collected was analyzed using SPSS software for elementary analyses and PLS-SEM for hypotheses testing. The findings showed that the predictors, namely product quality, service quality, perceived convenience, and perceived ease of use, significantly affected user experience and trust. Similarly, user experience and trust were influential on user satisfaction and played partial mediating roles between predictors and user satisfaction. Besides, gender and age moderate the relationships of experience and trust with customer satisfaction. These findings support the S-O-R theoretical framework and have practical implications for brand and marketing managers of smartwatches in developing product features and understanding users' attitudes and behaviours.
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Affiliation(s)
| | - Hussam Al Halbusi
- Department of Management, Ahmed Bin Mohammad Military College, Doha, Qatar
| | - Rodney Lim
- Faculty of Business, Design and Arts, Swinburne University of Technology, Sarawak Campus, Malaysia
| | - Ishraq Jerin
- Department of Management, Putra Business School, Malaysia
| | - Abu Bakar Abdul Hamid
- Department of Marketing and Supply Chain Management, Putra Business School, Malaysia
| | - Thurasamy Ramayah
- School of Management, Universiti Sains Malaysia, Minden, 11800, Penang, Malaysia
- Fakulti Pengurusan dan Perniagaan, Universiti Teknologi Mara (UiTM), Malaysia
- Department of Management, Sunway University Business School (SUBS), Malaysia
- Faculty of Accounting and Management, Universiti Tunku Abdul Rahman (UTAR), Malaysia
- Faculty of Economics and Business, Universiti Malaysia Sarawak (UNIMAS), Malaysia
| | - Ahasanul Haque
- Department of Business Administration, International Islamic University Malaysia, Box No. 10, Kuala Lumpur, 50728, Malaysia
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Han C, Song Y, Lim HS, Tae Y, Jang JH, Lee BT, Lee Y, Bae W, Yoon D. Automated Detection of Acute Myocardial Infarction Using Asynchronous Electrocardiogram Signals-Preview of Implementing Artificial Intelligence With Multichannel Electrocardiographs Obtained From Smartwatches: Retrospective Study. J Med Internet Res 2021; 23:e31129. [PMID: 34505839 PMCID: PMC8463948 DOI: 10.2196/31129] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 07/27/2021] [Accepted: 08/01/2021] [Indexed: 01/23/2023] Open
Abstract
Background When using a smartwatch to obtain electrocardiogram (ECG) signals from multiple leads, the device has to be placed on different parts of the body sequentially. The ECG signals measured from different leads are asynchronous. Artificial intelligence (AI) models for asynchronous ECG signals have barely been explored. Objective We aimed to develop an AI model for detecting acute myocardial infarction using asynchronous ECGs and compare its performance with that of the automatic ECG interpretations provided by a commercial ECG analysis software. We sought to evaluate the feasibility of implementing multiple lead–based AI-enabled ECG algorithms on smartwatches. Moreover, we aimed to determine the optimal number of leads for sufficient diagnostic power. Methods We extracted ECGs recorded within 24 hours from each visit to the emergency room of Ajou University Medical Center between June 1994 and January 2018 from patients aged 20 years or older. The ECGs were labeled on the basis of whether a diagnostic code corresponding to acute myocardial infarction was entered. We derived asynchronous ECG lead sets from standard 12-lead ECG reports and simulated a situation similar to the sequential recording of ECG leads via smartwatches. We constructed an AI model based on residual networks and self-attention mechanisms by randomly masking each lead channel during the training phase and then testing the model using various targeting lead sets with the remaining lead channels masked. Results The performance of lead sets with 3 or more leads compared favorably with that of the automatic ECG interpretations provided by a commercial ECG analysis software, with 8.1%-13.9% gain in sensitivity when the specificity was matched. Our results indicate that multiple lead-based AI-enabled ECG algorithms can be implemented on smartwatches. Model performance generally increased as the number of leads increased (12-lead sets: area under the receiver operating characteristic curve [AUROC] 0.880; 4-lead sets: AUROC 0.858, SD 0.008; 3-lead sets: AUROC 0.845, SD 0.011; 2-lead sets: AUROC 0.813, SD 0.018; single-lead sets: AUROC 0.768, SD 0.001). Considering the short amount of time needed to measure additional leads, measuring at least 3 leads—ideally more than 4 leads—is necessary for minimizing the risk of failing to detect acute myocardial infarction occurring in a certain spatial location or direction. Conclusions By developing an AI model for detecting acute myocardial infarction with asynchronous ECG lead sets, we demonstrated the feasibility of multiple lead-based AI-enabled ECG algorithms on smartwatches for automated diagnosis of cardiac disorders. We also demonstrated the necessity of measuring at least 3 leads for accurate detection. Our results can be used as reference for the development of other AI models using sequentially measured asynchronous ECG leads via smartwatches for detecting various cardiac disorders.
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Affiliation(s)
- Changho Han
- Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Yongin, Republic of Korea
| | | | - Hong-Seok Lim
- Department of Cardiology, Ajou University School of Medicine, Suwon, Republic of Korea
| | | | - Jong-Hwan Jang
- Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Yongin, Republic of Korea
| | | | - Yeha Lee
- VUNO Inc, Seoul, Republic of Korea
| | | | - Dukyong Yoon
- Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Yongin, Republic of Korea.,Center for Digital Health, Yongin Severance Hospital, Yonsei University Health System, Yongin, Republic of Korea
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Mc Keaveney C, Reid J, Carswell C, Bonner A, de Barbieri I, Johnston W, Maxwell AP, O'Riordan J, Strini V, Walsh I, Noble H. Experiences of renal healthcare practitioners during the COVID-19 pandemic: a multi-methods approach. BMC Nephrol 2021; 22:301. [PMID: 34493246 PMCID: PMC8421457 DOI: 10.1186/s12882-021-02500-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 08/14/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Globally, renal healthcare practitioners provide intensive and protracted support to a highly complex multi-morbid patient population however knowledge about the impact of COVID-19 on these practitioners is extremely limited. OBJECTIVE This study aimed to explore the experiences of COVID-19 with renal healthcare practitioners during the first global lockdown between June 2020 and September 2020. METHODS A multi-methods approach was carried out including a quantitative survey and qualitative interviews. This was a multinational study of renal healthcare practitioners from 29 countries. Quantitative: A self-designed survey on COVID-19 experiences and standardised questionnaires (General Health Questionnaire-12; Maslach Burnout Inventory). Descriptive statistics were generated for numerical data. Qualitative: Online semi-structured interviews were conducted. Data was subjected to thematic analysis. Renal healthcare practitioners (n = 251) completed an online survey. Thirteen renal healthcare practitioners took part in semi-structured interviews (12 nurses and 1 dietician). RESULTS The majority of participants surveyed were female (86.9 %; n = 218), nurses (86.9 %; n = 218) with an average 21.5 (SD = 11.1) years' experience since professional qualification, and 16.3 years (SD = 9.3) working in renal healthcare. Survey responses indicated a level of preparedness, training and satisfactory personal protective equipment during the pandemic however approximately 40.3 % experienced fear about attending work, and 49.8 % experienced mental health distress. The highest prevalence of burnout was emotional exhaustion (35.9 %). Three themes emerged from the qualitative analysis highlighting the holistic complexities in managing renal healthcare, a neglected specialist workforce, and the need for appropriate support at work during a pandemic. CONCLUSIONS Results have highlighted the psychological impact, in terms of emotional exhaustion and mental health distress in our sample of renal healthcare practitioners. As the pandemic has continued, it is important to consider the long-term impact on an already stretched workforce including the risk of developing mental health disorders. Future research and interventions are required to understand and improve the provision of psychological support for specialist medical and nursing personnel.
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Affiliation(s)
- Clare Mc Keaveney
- School of Nursing and Midwifery, Queens University Belfast, Belfast, UK
| | - Joanne Reid
- School of Nursing and Midwifery, Queens University Belfast, Belfast, UK
| | - Claire Carswell
- School of Nursing and Midwifery, Queens University Belfast, Belfast, UK
- Department of Health Sciences, University of York, York, UK
| | - Ann Bonner
- Griffith University, Brisbane, Australia
| | | | - William Johnston
- Kidney Care, Alton, UK
- Northern Ireland Kidney Patient Association, Belfast, UK
| | - Alexander P Maxwell
- Regional Nephrology Unit, Belfast City Hospital, Belfast, UK
- Centre for Public Health, Queens University Belfast, Belfast, UK
| | - Julien O'Riordan
- Galway Hospice Foundation, Galway, Ireland
- National University of Ireland, Galway, Ireland
| | | | - Ian Walsh
- School of Medicine, Dentistry and Biomedical Sciences, Queens University Belfast, Belfast, UK
| | - Helen Noble
- School of Nursing and Midwifery, Queens University Belfast, Belfast, UK.
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Development of a Self-Powered Piezo-Resistive Smart Insole Equipped with Low-Power BLE Connectivity for Remote Gait Monitoring. SENSORS 2021; 21:s21134539. [PMID: 34283073 PMCID: PMC8272025 DOI: 10.3390/s21134539] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 06/11/2021] [Accepted: 06/24/2021] [Indexed: 11/17/2022]
Abstract
The evolution of low power electronics and the availability of new smart materials are opening new frontiers to develop wearable systems for medical applications, lifestyle monitoring, and performance detection. This paper presents the development and realization of a novel smart insole for monitoring the plantar pressure distribution and gait parameters; indeed, it includes a piezoresistive sensing matrix based on a Velostat layer for transducing applied pressure into an electric signal. At first, an accurate and complete characterization of Velostat-based pressure sensors is reported as a function of sizes, support material, and pressure trend. The realization and testing of a low-cost and reliable piezoresistive sensing matrix based on a sandwich structure are discussed. This last is interfaced with a low power conditioning and processing section based on an Arduino Lilypad board and an analog multiplexer for acquiring the pressure data. The insole includes a 3-axis capacitive accelerometer for detecting the gait parameters (swing time and stance phase time) featuring the walking. A Bluetooth Low Energy (BLE) 5.0 module is included for transmitting in real-time the acquired data toward a PC, tablet or smartphone, for displaying and processing them using a custom Processing® application. Moreover, the smart insole is equipped with a piezoelectric harvesting section for scavenging energy from walking. The onfield tests indicate that for a walking speed higher than 1 ms-1, the device's power requirements (i.e., P¯=5.84 mW) was fulfilled. However, more than 9 days of autonomy are guaranteed by the integrated 380-mAh Lipo battery in the total absence of energy contributions from the harvesting section.
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Srizongkhram S, Chiadamrong N, Shirahada K. Critical Success Factors in Adoption of Wearable Technology Devices for Seniors in Thailand. INTERNATIONAL JOURNAL OF INNOVATION AND TECHNOLOGY MANAGEMENT 2021. [DOI: 10.1142/s0219877021500206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The adoption of wearable devices has been proposed as a promising approach to improve the well-being of senior in Thai care services. This study aims to find the critical success factors (CSFs) in adopting wearable technology from the stakeholder perspective. We collected data from total 27 participants from three groups of stakeholders: formal caregivers, informal caregivers, and seniors. Using the grounded theory approach, we found four types of CSFs and its variety in according to devices and stakeholders’ viewpoints. Based on the findings, this paper also discusses how to develop wearable devices to satisfy stakeholder requirements and improve their wellbeing.
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Affiliation(s)
- Shayarath Srizongkhram
- School of Knowledge Science, Japan Advanced Institute of Science and Technology, Asahidai, Nomi, Ishikawa 923-1211, Japan
- School of Manufacturing Systems and Mechanical Engineering (MSME), Sirindhorn International Institute of Technology (SIIT), Thammasat University, Paholyothin Highway Khlong Luang, Pathum Thani 12120, Thailand
| | - Navee Chiadamrong
- School of Manufacturing Systems and Mechanical Engineering (MSME), Sirindhorn International Institute of Technology (SIIT), Thammasat University, Paholyothin Highway Khlong Luang, Pathum Thani 12120, Thailand
| | - Kunio Shirahada
- School of Knowledge Science, Japan Advanced Institute of Science and Technology, Asahidai, Nomi, Ishikawa 923-1211, Japan
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Lee D, Yoon SN. Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:E271. [PMID: 33401373 PMCID: PMC7795119 DOI: 10.3390/ijerph18010271] [Citation(s) in RCA: 123] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 12/23/2020] [Accepted: 12/24/2020] [Indexed: 12/17/2022]
Abstract
This study examines the current state of artificial intelligence (AI)-based technology applications and their impact on the healthcare industry. In addition to a thorough review of the literature, this study analyzed several real-world examples of AI applications in healthcare. The results indicate that major hospitals are, at present, using AI-enabled systems to augment medical staff in patient diagnosis and treatment activities for a wide range of diseases. In addition, AI systems are making an impact on improving the efficiency of nursing and managerial activities of hospitals. While AI is being embraced positively by healthcare providers, its applications provide both the utopian perspective (new opportunities) and the dystopian view (challenges to overcome). We discuss the details of those opportunities and challenges to provide a balanced view of the value of AI applications in healthcare. It is clear that rapid advances of AI and related technologies will help care providers create new value for their patients and improve the efficiency of their operational processes. Nevertheless, effective applications of AI will require effective planning and strategies to transform the entire care service and operations to reap the benefits of what technologies offer.
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Affiliation(s)
- DonHee Lee
- College of Business Administration, Inha University, Incheon 22212, Korea;
| | - Seong No Yoon
- Department of Business Edward Waters College, Jacksonville, FL 32209, USA
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