Effectiveness of web-based social sensing in health information dissemination—A review

Assessing the influence of COVID-19 protocol on online health information seeking intention of athletes in India

Purpose

The Internet is used as a tool to seek health information by individuals. Mental health concerns are the high prevalence of the novel coronavirus disease 2019 (COVID-19) and preventive steps are required to curb the illness. Therefore, to gain more insight into health concerns, it is now a common practice to seek health information on the Internet. This study propose an integrated theoretical model to explore the relationship between COVID-19 protocols and perceived online trust with online health information seeking intention (OHISI) and a moderating effect of perceived severity and perceived urgency.

Design/methodology/approach

Data are collected from 325 athletes in the category of individual and team sports through an online survey in a Likert-scale questionnaire. The analysis is performed with a quantitative methodology.

Findings

The study reveals the bright side of online health information (OHI), which brings athletes together and has played out with virtual happy hours, meetings and events. The bright side of OHI reflects social, cultural, technological and economic benefits. An OHI chatbot offers bright personalised side information to the individual seeker, which is more convenient and efficient than human capabilities.

Originality/value

The pivotal contribution is the integrated theoretical framework that is derived from multidisciplinary literature to capture the complexity of OHI. Also, it conceptualises the constructs in the context of OHI and COVID-19.

Effectiveness of Disseminating School Physical Activity Information on Facebook during a Pandemic: A Mixed-Method Analysis

BACKGROUND

Social media is an important communication tool during times of crisis because of its vast reach. Understanding the effectiveness of sharing public health guidance and promoting schoolchildren's physical activity during the COVID-19 pandemic can inform dissemination best practices.

METHODS

We classified 418 posts from parent/community members of a school-based physical activity Facebook group by content type, and used concurrent mixed methods to examine (1) differences in dissemination effectiveness (reactions, shares, and comments) between two pandemic phases and (2) themes and sentiments of comments. Phase I included school closures through the release of national school re-entry guidelines (March 1, 2020 - May 15, 2020) and Phase II extended through the school year start (May 16, 2020 - August 1, 2020).

RESULTS

Policy and guidance posts prompted more comments while feel-good stories produced more reactions compared to other content types. Members reacted more during Phase II, which mainly consisted of policy and guidance (86%). Four major themes of information and resources, personal disclosures, questions and concerns, and support for educators emerged.

CONCLUSIONS

Sharing public health guidance for schoolchildren on social media was an effective strategy to disseminate information when in-person discourse was limited. Creating social media spaces where discussion is encouraged can provide social and emotional support for parents/community members.

Research on influencing factors of information diffusion in online social networks under different themes

Purpose

This paper aims to study the factors influencing online social network (OSN) information diffusion under different themes helps to understand information diffusion in general.

Design/methodology/approach

This study collects data from the Web of Science, use the strategic consulting intelligent support system for word frequency analysis and use keyword clustering to classify themes, then research information themes as influencing factors of OSN information diffusion.

Findings

Five themes of “natural disaster”, “political event”, “product marketing”, “sport and entertainment” and “health-disease” have been identified. It is found that the research objects, research methods and research theories used by scholars under different themes have different focuses, and the factors affecting information diffusion are different.

Research limitations/implications

The limitation of this paper is that it only focuses on five typical themes, and there may be more themes.

Practical implications

The research helps other scholars to conduct in-depth research on the diffusion of OSN information under different topics and focus on the content of the research on OSN information diffusion under different topics.

Social implications

The research helps other scholars to conduct in-depth research on the diffusion of social network information under different topics, so as to better understand and predict the law of information diffusion.

Originality/value

The research summarizes the research on information diffusion in OSNs from the theme level and analyses the key points and theories and further enriches the research system on information diffusion in OSNs.

Challenges for developing health-care knowledge in the digital age

Purpose

Health-care knowledge is dispersed among different departments in a health care organization, which makes it difficult at times to provide quality care services to patients. Therefore, this study aims to identify the main challenges in adopting health information technology (HIT).

Design/methodology/approach

This study surveyed 148 stakeholders in 4 key categories [patients, health-care providers, United Arab Emirates (UAE) citizens and foresight experts] to identify the challenges they face in adopting health care technologies. Responses were analyzed using exploratory (EFA) and confirmatory factor analysis (CFA).

Findings

EFA revealed four key latent factors predicting resistance to HIT adoption, namely, organizational strategy (ORGS); technical barriers; readiness for big data and the internet of things (IoT); and orientation (ORI). ORGS accounted for the greatest amount of variance. CFA indicated that readiness for big data and the IoT was only moderately correlated with HIT adoption, but the other three factors were strongly correlated. Specific items relating to cost, the effectiveness and usability of the technology and the organization were strongly correlated with HIT adoption. These results indicate that, in addition to financial considerations, effective HIT adoption requires ensuring that technologies will be easy to implement to ensure their long-term use.

Research limitations/implications

The results indicate that readiness for big data and the IoT-related infrastructure poses a challenge to HIT adoption in the UAE context. Respondents believed that the infrastructure of big data can be helpful in more efficiently storing and sharing health-care information. On the technological side, respondents felt that they may experience a steep learning curve. Regarding ORI, stakeholders expected many more such initiatives from health-care providers to make it more knowledge-specific and proactive.

Practical implications

This study has implications for knowledge management in the health -care sector for information technologies. The HIT can help firms in creating a knowledge eco-system, which is not possible in a dispersed knowledge environment. The utilization of the knowledge base that emerged from the practices and data can help the health care sector to set new standards of information flow and other clinical services such as monitoring the self-health condition. The HIT can further influence the actions of the pharmaceutical and medical device industry.

Originality/value

This paper highlights the challenges in HIT adoption and the most prominent factors. The conceptual model was empirically tested after the collection of primary data from the UAE using stakeholder theory.

Syndromic surveillance using web data: a systematic review

During the recent years, a lot of debate is taken place about the evolution of Smart Healthcare systems. Particularly, how these systems can help people improve human conditions of health, by taking advantages of the new Information and Communication Technologies (ICT), regarding early prediction and efficient treatment. The purpose of this study is to provide a systematic review of the current literature available that focuses on information systems on syndromic surveillance using web data. All published items concern articles, books, reviews, reports, conference announcements, and dissertations. We used a variation of PRISMA Statements methodology to conduct a systematic review. The review identifies the relevant published papers from the year 2004 to 2018, systematically includes and explores them to extract similarities, gaps, and conclusions on the research that has been done so far. The results presented concern the year, the examined disease, the web data source, the geographic location/country, and the data analysis method used. The results show that influenza is the most examined infectious disease. The internet tools most used are Twitter and Google. Regarding the geographical areas explored in the published papers, the most examined country is the United States, since many scientists come from this country. There is a significant growth of articles since 2009. There are also various statistical methods used to correlate the data retrieved from the internet to the data from national authorities. The conclusion of all researches is that the Web can be a useful tool for the detection of serious epidemics and for a creation of a syndromic surveillance system using the Web, since we can predict epidemics from web data before they are officially detected in population. With the advance of ICT, Smart Healthcare can benefit from the monitoring of epidemics and the early prediction of such a system, improving national or international health strategies and policy decision. This can be achieved through the provision of new technology tools to enhance health monitoring systems toward the new innovations of Smart Health or eHealth, even with the emerging technologies of Internet of Things. The challenges and impacts of an electronic system based on internet data include the social, medical, and technological disciplines. These can be further extended to Smart Healthcare, as the data streaming can provide with real-time information, awareness on epidemics and alerts for both patients or medical scientists. Finally, these new systems can help improve the standards of human life.

Recommender systems for IoT enabled quantified-self applications

As an emerging trend in big data science, applications based onthe Quantified-Self (QS)engage individuals in the self-tracking of any kind of biological, physical, behavioral, or environmental information as individuals or groups. There are new needs and opportunities for recommender systems to develop new models/approaches to support QS application users.Recommender systemscan help to more easily identify relevant artifacts for users and thus improve user experiences. Currently recommender systems are widely and effectively used in the e-commerce domain (e.g., online music services, online bookstores). Next-generation QS applications could include more recommender tools for assisting the users of QS systems based on their personal self-tracking data streams from wearable electronics, biosensors, mobile phones, genomic data, and cloud-based services. In this paper, we propose three new recommendation approaches for QS applications:Virtual Coach,Virtual Nurse, andVirtual Sleep Regulatorwhich help QS users to improve their health conditions.Virtual Coachworks like a real fitness coach to recommend personalized work-out plans whereasVirtual Nurseconsiders the medical history and health targets of a user to recommend a suitable physical activity plan.Virtual Sleep Regulatoris specifically designed for insomnia (a kind of sleep disorder) patients to improve their sleep quality with the help of recommended physical activity and sleep plans. We explain how these proposed recommender technologies can be applied on the basis of the collected QS data to create qualitative recommendations for user needs. We present example recommendation results ofVirtual Sleep Regulatoron the basis of the dataset from a real world QS application.

Modeling Medical Services with Mobile Health Applications

The rapid development of mobile health technology (m-Health) provides unprecedented opportunities for improving health services. As the bridge between doctors and patients, mobile health applications enable patients to communicate with doctors through their smartphones, which is becoming more and more popular among people. To evaluate the influence of m-Health applications on the medical service market, we propose a medical service equilibrium model. The model can balance the supply of doctors and demand of patients and reflect possible options for both doctors and patients with or without m-Health applications in the medical service market. In the meantime, we analyze the behavior of patients and the activities of doctors to minimize patients' full costs of healthcare and doctors' futility. Then, we provide a resolution algorithm through mathematical reasoning. Lastly, based on artificially generated dataset, experiments are conducted to evaluate the medical services of m-Health applications.