A Study of eHealth from the Perspective of Social Sciences

Uribe-Toril, Juan; Ruiz–Real, José Luis; Nievas-Soriano, Bruno José

doi:10.3390/healthcare9020108

Cited by 19 publications

(8 citation statements)

References 76 publications

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“…We used VOSviewer (version 1.6.15) for data analysis. In bibliometric analysis, mapping and clustering techniques can provide insight into network structure and are usually used together [ 28 , 29 ]; however, these 2 techniques were developed independently and rely upon different ideas and assumptions. Waltman et al [ 30 ] proposed a unified mapping approach and clustering, which is used in VOSviewer [ 31 ].…”

Section: Methodsmentioning

confidence: 99%

Exploring the Shift in International Trends in Mobile Health Research From 2000 to 2020: Bibliometric Analysis

Cao¹,

Lim²,

Sengoku³

et al. 2021

JMIR Mhealth Uhealth

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Background Smartphones have become an integral part of our lives with unprecedented popularity and a diverse selection of apps. The continuous upgrading of information technology has also enabled smartphones to display great potential in the field of health care. Objective We aimed to determine the future research direction of mobile health (mHealth) by analyzing its research trends and latest research hotspots. Methods This study collected mHealth-related literature published between 2000 and 2020 from the Web of Science database. Descriptive statistics of publication trends of mHealth research were determined by analyzing the annual number of publications in the literature and annual number of publications by country. We constructed visualization network maps of country (or regional) collaborations and author-provided keyword co-occurrences, as well as overlay visualization maps of the average publication year of author-provided keywords to analyze the hotspots and research trends in mHealth research. Results In total, 12,593 mHealth-related research papers published between 2000 and 2020 were found. The results showed an exponential growth trend in the number of annual publications in mHealth literature. JMIR mHealth and uHealth, the Journal of Medical Internet Research, and JMIR Research Protocols were the 3 top journals with respect to number of publications. The United States remained the leading contributor to the literature in this area (5294/12,593, 42.0%), well ahead of other countries and regions. Other countries and regions also showed a clear trend of annual increases in the number of mHealth publications. The 4 countries with the largest number of publications—the United States, the United Kingdom, Canada, and Australia—were found to cooperate more closely. The rest of the countries and regions showed a clear geographic pattern of cooperation. The keyword co-occurrence analysis of the top 100 authors demonstrated 5 clusters, namely, development of mHealth medical technology and its application to various diseases, use of mHealth technology to improve basic public health and health policy, mHealth self-health testing and management in daily life, adolescent use of mHealth, and mHealth in mental health. The research trends revealed a gradual shift in mHealth research from health policy and improving public health care to the development and social application of mHealth technologies. Conclusions To the best of our knowledge, the most current bibliometric analysis dates back to 2016. However, the number of mHealth research published between 2017 and 2020 exceeds the previous total. The results of this study shed light on the latest hotspots and trends in mHealth research. These findings provide a useful overview of the development of the field; they may also serve as a valuable reference and provide guidance for researchers in the digital health field.

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Section: Methodsmentioning

confidence: 99%

Exploring the Shift in International Trends in Mobile Health Research From 2000 to 2020: Bibliometric Analysis

Cao¹,

Lim²,

Sengoku³

et al. 2021

JMIR Mhealth Uhealth

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“…Various user acceptance and use frameworks have been applied to eHealth applications, such as the unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al, 2003) or the technology acceptance model (TAM) (Venkatesh & Davis, 2000). Of these two, the TAM has been most central to the development of eHealth technology frameworks (Uribe-Toril et al, 2021). Technology acceptance and use models such as the TAM show how a person's intention to use technology is influenced by user perceptions of the system, such as how useful the system will be in meeting their end goals and how easy the system is to use (e.g., does it require a lot of effort?)…”

Section: Technology Acceptance and Use Modelsmentioning

confidence: 99%

“…Analyses of eHealth technology acceptance models have been conducted in the context of various medical technologies, such as telemedicine in ambulatory care settings (Dünnebeil et al, 2012), personal health data management systems (Koivumäki et al, 2017), patient portals (Lazard et al, 2016), and mobile health applications (Shemesh & Barnoy, 2020). In general, acceptance and use models such as the TAM have proven successful at explaining many of the technology-use related factors influencing the adoption of eHealth technologies (Mohamed et al, 2011;Uribe-Toril et al, 2021). However, given that eHealth technology is changing the way people access and interact with health data (Flanders et al, 2017;Lie et al, 2019), differences in the way healthcare decisions are made can be expected (Car et al, 2017).…”

Section: Technology Acceptance and Use Modelsmentioning

confidence: 99%

“…For example, users of eHealth technologies may find it difficult to navigate legitimate and illegitimate sources of medical information on their own (Apuke & Omar, 2021), distrust the technology as a successful treatment model or to protect their personal health data (Arfi et al, 2021), or find that the technology could interfere in the doctor-patient relationship (Burke & Hall, 2015). Alongside healthcare providers, human factors professionals are addressing these challenges in implementation, acceptance, and proper use of eHealth technologies (Uribe-Toril et al, 2021). Unfortunately, while the use of technology acceptance and use frameworks has greatly improved the development of eHealth technologies, little consideration has been given to fully integrating conceptual frameworks for patient adherence with acceptance and use models.…”

Section: Introductionmentioning

confidence: 99%

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Combined Model of Technology Use and Medical Adherence in eHealth Technology Implementation

Devkota

Montalvo

McConnell

et al. 2021

Proceedings of the Human Factors and Ergonomics Society Annual

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eHealth applications are expected to improve the effectiveness and efficiency of healthcare systems by providing improved medical information flow between medical providers and patients. Although the technology is expected to empower patients, lower treatment costs, and provide real-time collection of health data, individuals may be apprehensive about the use and efficacy of eHealth technologies. Medical professionals are often unaware of human factors technology acceptance or usability models which impact the use of medically focused technology, such as eHealth applications. Similarly, human factors professionals are often unaware of treatment adherence models which map the relationship of illness factors and individual differences to treatment protocols. The present paper presents a theoretical approach through which technology acceptance and usability models should be combined with medical treatment adherence models to ensure that eHealth applications are used properly and effectively.

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“…Advances in technology have helped in developing various monitoring systems such as smart watches and diabetes monitors that can be integrated with mobile applications and transfer real-time data to hospital servers, improving the effectiveness of remote monitoring by efficiently managing the health information of the patients. eHealth, for instance, is an emerging field at the intersection of medical informatics, public health, and business, referring to the health services and information delivered or enhanced through the internet and related technologies [24]. mHealth and Telehealth are two major eHealth approaches that are being extensively used during the COVID-19 pandemic to deliver remote healthcare services.…”

Section: Introductionmentioning

confidence: 99%

Cross Sectional E-Health Evaluation Study for Telemedicine and M-Health Approaches in Monitoring COVID-19 Patients with Chronic Obstructive Pulmonary Disease (COPD)

Alsharif

2021

IJERPH

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Monitoring COVID-19 patients with COPD has become one of the major tasks in preventing transmission and delivering emergency healthcare services after vaccination in case of any issues. Most COVID-19-affected patients are suggested to self-quarantine at home or in institutionalized quarantine centers. In such cases, it is essential to provide remote healthcare services. For remote healthcare monitoring, two approaches are being considered in this study, which include mHealth and Telehealth. A mixed-methods approach is adopted, where survey questionnaires are used for collecting information from 108 patients and semi-structured interviews are used with seven physicians regarding mHealth and Telehealth approaches. Survey results indicated that mHealth is rated to be slightly more effective than Telehealth, and interview results indicated that Telehealth is identified to be slightly more effective than mHealth in relation to parameters including usefulness, ease of use and learnability, interface and interaction quality, reliability, and satisfaction. However, both physicians and patients opined that both mHealth and Telehealth have a promising future with increasing adoption. Based on the findings, it can be concluded that both mHealth and Telehealth are considered to be effective in delivering remote care for COPD patients infected with COVID-19 at home. Implications of the study findings are discussed.

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A Study of eHealth from the Perspective of Social Sciences

Cited by 19 publications

References 76 publications

Exploring the Shift in International Trends in Mobile Health Research From 2000 to 2020: Bibliometric Analysis

Exploring the Shift in International Trends in Mobile Health Research From 2000 to 2020: Bibliometric Analysis

Combined Model of Technology Use and Medical Adherence in eHealth Technology Implementation

Cross Sectional E-Health Evaluation Study for Telemedicine and M-Health Approaches in Monitoring COVID-19 Patients with Chronic Obstructive Pulmonary Disease (COPD)

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