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Background: Saudi Arabia is lagging behind developed countries in devising specific real projects, roadmaps, and policies for the Internet of Things (IoT) and big data adoption despite having a vision for providing the best-quality health care services to its citizens. As a result, Saudi Arabia is going to host an event for the third time, in 2020, promoting the widescale adoption of the IoT. While a nationwide study has identified the risk that many participants were previously undiagnosed for hypertension and other chronic diseases in Saudi Arabia, the application of the IoT and big data technologies could be very useful in minimizing such risks by predicting chronic disease earlier, and on a large scale. Materials and Methods: A framework that consists of four modules, (1) data collection, (2) data storage, (3) Hadoop/Spark cluster, and (4) Google Cloud, was developed in which decision tree and support vector machine (SVM) techniques were used for predicting hypertension. There were 140 participants in total and 20% of participants were used for training the model. Results: The results show that age and diabetes play a very significant part in diagnosing hypertension in older people. Also, it was found that the possibility of hypertension because of smoking is less than that of diabetes, and older people should have a lower intake of salty food. Moreover, it was found that SVM techniques yielded better results than C4.5 in our study. Conclusions: Although it was found that the algorithms examined in this study can be used for disease prediction, the ability to classify and predict disease is not yet sufficiently satisfactory. To achieve this, more training data and a longer duration are required. Finally, by supporting such study for developing custom-made smart wristbands, custom-made smart clothing, and custom-made smart homes that can predict and detect a wide range of chronic diseases, the Saudi government can achieve its health-related goals of Vision 2030.
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Internet de las Cosas , Anciano , Anciano de 80 o más Años , Ciencia de los Datos , Servicios de Salud , Humanos , Monitoreo Fisiológico , Arabia Saudita/epidemiologíaRESUMEN
BACKGROUND: The increasing number of older people and the dissemination of health information via the Internet have emerged and both are challenging to Chinese society. Available online health information highlights the importance of decision making processes, specially in relation to the elderly who almost have no online presence and depend on their adult children's help. The researchers mostly focus on parents' health information search for their children, however, they overlook the adult children's intention to use online health information for their aged parents. OBJECTIVE: This study fills this gap by extending the Theory of Planned Behavior (TPB) to identify the determinants of adult children's intention to use online health information for their aged parents. METHOD: Relying on survey method, the data were collected from teachers and students at different participating Universities in Wuhan, China. The Partial Least Squares (PLS), a structural equation modeling technique, was employed to test the research model. RESULTS: This study found that attitude, subjective norm, perceived behavioral control and risk (p<0.05) were the predictors of intention to use online health information, whereas, trust (p>0.05) was not listed among the predictors. CONCLUSIONS: This study is a significant addition to the literature, in that it confirms the utility of the TPB with additional variables in predicting adults' children intention to use online health information for their aged parents.
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Hijos Adultos/psicología , Actitud , Información de Salud al Consumidor/estadística & datos numéricos , Conocimientos, Actitudes y Práctica en Salud , Intención , Internet/estadística & datos numéricos , Padres/psicología , Adulto , Anciano , Niño , China , Toma de Decisiones , Femenino , Humanos , Masculino , Persona de Mediana Edad , Percepción , Encuestas y Cuestionarios , Adulto JovenRESUMEN
BACKGROUND: mHealth (mobile health) services are becoming an increasingly important form of information and communication technology (ICT) enabled delivery for healthcare, especially in low-resource environments such as developing countries like Bangladesh. Despite widespread adoption of mobile phones and the acknowledged potential of using them to improve healthcare services, the adoption and acceptance of this technology among the elderly is significantly low. However, little research has been done to draw any systematic study of the elderly's intention to adopt mHealth services. OBJECTIVE: The aim of this study was to develop a theoretical model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and then empirically test it for determining the key factors influencing elderly users' intention to adopt and use the mHealth services. METHODS: A face-to-face structured questionnaire survey method was used to collect data from nearly 300 participants of age 60 years and above from the capital city of Bangladesh. The data were analyzed using the Partial Least Squares (PLS) method, a statistical analysis technique based upon Structural Equation Modeling (SEM). RESULTS: The study determined that performance expectancy, effort expectancy, social influence, technology anxiety, and resistance to change (p<0.05) had a significant impact on the users' behavioral intention to adopt mHealth services. The study, however, revealed no significant relation between the facilitating condition and the users' behavioral intention to use the mHealth services (p>0.05). CONCLUSIONS: This study confirms the applicability of UTAUT model in the context of mHealth services among the elderly in developing countries like Bangladesh. It provides valuable information for mHealth service providers and policy makers in understanding the adoption challenges and the issues and also provides practical guidance for the successful implementation of mHealth services. Additionally the empirical findings identify implications related to the design and development of mHealth services that influence potential users. Furthermore, due to a generic approach, the findings of this study could be easily modified to assist other developing countries in the planning and up-take of mHealth services.