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Microsoft-CrowdStrike outage: how a single software update was able to cause IT chaos across the globe

Feng Li , City, University of London

Massive global IT outage hits banks, airports, supermarkets – and a single software update is likely to blame

Mark A Gregory , RMIT University

An anonymous coder nearly hacked a big chunk of the internet. How worried should we be?

Sigi Goode , Australian National University

Maps shape our lives – showing us not just where we are, but who we are

Mike Duggan , King's College London

How better and cheaper software could save millions of dollars while improving Canada’s health-care  system

Joshua M. Pearce , Western University

Artificial intelligence is already in our hospitals. 5 questions people want answered

Stacy Carter , University of Wollongong ; Emma Frost , University of Wollongong ; Farah Magrabi , Macquarie University , and Yves Saint James Aquino , University of Wollongong

How will AI affect workers? Tech waves of the past show how unpredictable the path can be

Bhaskar Chakravorti , Tufts University

Remembering South Africa’s “Grand Geek” Barry Dwolatzky - engineer and programming pioneer

Estelle Trengove , University of the Witwatersrand

How hiring more women IT experts improves cybersecurity risk management

Camélia Radu , Université du Québec à Montréal (UQAM) and Nadia Smaili , Université du Québec à Montréal (UQAM)

The information age is starting to transform fishing worldwide

Nicholas P. Sullivan , Tufts University

How AI is shaping the cybersecurity arms race

Sagar Samtani , Indiana University

Instagram Kids: tech development must move from usability to safety

Fiona Carroll , Cardiff Metropolitan University and Ana Calderon , Cardiff Metropolitan University

COVID-19 revealed how sick the US health care delivery system really is

Elizabeth A. Regan , University of South Carolina

Ontario’s digital health program has a data quality problem, despite billions in spending

Linying Dong , Toronto Metropolitan University and Karim Keshavjee , University of Toronto

Australia, fighting Facebook, is the latest country to struggle against foreign influence on journalism

Vanessa Freije , University of Washington

What South Africa’s teachers brought to the virtual classroom during  COVID-19

Mmaki Jantjies , University of the Western Cape

Privacy, perceptions and effectiveness: the challenges of developing coronavirus contact-tracing apps

Roxana Ologeanu-Taddei , Université de Montpellier

South Africa would gain from co-operation among BRICS countries on beneficiation

Byelongo Elisée Isheloke , University of Cape Town

With the increase in remote work, businesses need to protect themselves against cyberattacks

Michael Parent , Simon Fraser University

The lack of women in cybersecurity leaves the online world at greater risk

Nir Kshetri , University of North Carolina – Greensboro

Related Topics

• Artificial intelligence (AI)
• Coronavirus
• Cybersecurity
• Digital economy
• Health care
• The Conversation France

Top contributors

Director of UWA Centre for Software Practice, The University of Western Australia

Senior Lecturer in Applied Ethics & CyberSecurity, Griffith University

Lecturer in Software Engineering, Monash University

Assistant Professor in Management of Information Sytems, Propedia

Head, The Cyber Academy, Edinburgh Napier University

Information Specialist, University of Sheffield

Postdoctoral research associate, Technical University of Munich

Professor of Information Sciences and Technology at Altoona campus, Penn State

External Research Professor at Santa Fe Institute, USA & Professor, Head of the Center for Fundamental Living Technology (FLinT), Head of Science Board, Initiative for Science, Society and Policy (ISSP), University of Southern Denmark

Associate Professor of Sociology, La Trobe University

Associate professor, The University of Melbourne, The University of Melbourne

ESRC Future Research Leader Fellow, The University of Edinburgh

Professor of Information Sciences & Technology, and Women's, Gender & Sexuality Studies, Penn State

Futurist at Next Scandinavia, associate at Initiative for Science, Society and Policy (ISSP) and Research Associate, University of Southern Denmark

Senior Lecturer in Information Systems, The Open University

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• v.2022; 2022

The Impact of Information and Communication Technologies (ICTs) on Health Outcomes: A Mediating Effect Analysis Based on Cross-National Panel Data

Mingxing shao.

International Business School, Beijing Foreign Studies University, Beijing, China

Zishan Huang

Mingyang chen, associated data.

All the data used in our study could be approached upon request.

When ICTs (Information and Communications Technologies) are combined with healthcare, they can make a key contribution to gradually improve national health outcomes. The global outbreak of COVID-19 in 2020 further highlighted the important role of e-Health and m-Health service modes. This research structures a mediated effect model to explore dynamic relationships between ICT factors, ICT impacts, and national health outcomes, among which ICT factors are independent variables; ICT impacts are mediating variables, and national health outcome indicators selected from United Nations Millennium Development Goals (MDGs) and World Development Indicators are dependent variables. The fixed effect model is used to process a set of 141 countries' panel data from 2012 to 2016 from World Bank and World Economic Forum, while the classical three-step test method and Sobel test combined with fixed effects are used to test the mediated effects of the panel data. The results show that there are significant associations between ICT factors and national health outcome indicators, while only some of the partial mediated effects are proved. ICT environment and ICT usage can influence both the under-five mortality rate and adolescent fertility rate via ICT social impact. However, the mediated effect of ICT social impact on maternal mortality ratio and life expectancy at birth has not been confirmed. Meanwhile, the mediated effect of ICT economic impact has not been proven. This research is an interdisciplinary research in the field of information and communication technology and public health and reveals the path and mechanism whereby ICT factors improve national health outcomes, which can help global policymakers drive the next phase of the implementation of the Sustainable Development Goals (SDGs) and continue to improve the overall health at the national level.

1. Introduction

Using ICTs to efficiently provide services to citizens is an important area where digital technologies can make a difference in generating broad-based gains. ICT is an inclusive term, covering all communication equipment or application software: for example, radio, television, mobile phone, computer, network hardware and software, and satellite system, as well as various services and application software related to it, such as video conference and distance learning. The importance of ICTs is not the technology as such, but its enabling function in facilitating enhanced access to information and communication across large distances. ICTs have been used in many innovative ways to achieve social impacts, such as promoting access to basic services including health, finance, and insurance.

In the field of healthcare, key strategic applications of ICTs include e-Health and m-Health; E-Health and m-Health are increasingly employed—in combination with tools that build capacity and address the quality of care—to improve health systems, use resources efficiently, and plan for the progressive adoption of universal health coverage. Many people regard e-Health and m-Health as the next breakthrough in health system improvement, especially in developing nations. The integration of ICTs and healthcare can make a key contribution to improve lives and well-being worldwide and especially can assist the achievement of the health-related indicators of the United Nations Millennium Development Goals (MDGs). Take the COVID-19 outbreak in 2020 as an example, this emergency brought great challenges to all countries' medical and health system. In this fight against the pandemic, e-Health and m-Health service modes, represented by online telemedicine, showed their talents and played an important role.

ICTs are likely to fundamentally change the way public health is provided by influencing the economy and society. High-income countries have the capacity to increase investment in medical information and communication technologies to control and prevent child mortality and improve maternal health [ 1 ]. Developing countries may give priority to medical information technology projects in order to achieve rapid success, especially since the economic contraction will seriously hinder the implementation of online health policy [ 2 ]. This requires the introduction of more investment in ICT infrastructure to improve the availability and utilization of citizen broadband, so as to improve the penetration and application rate of e-Health and m-Health.

In academia, the previous studies on ICTs and health outcomes mostly stay at the conceptual or micro-level, or focus on the practical application of related technologies [ 3 , 4 ], such as Blockchain technology in acquiring, managing, and sharing personal health information obtained from medical IoT (Internet of things) devices [ 5 – 8 ] or country-specific case studies or comparative studies [ 9 – 14 ]. Some studies have revealed positive relationships between ICTs and national health [ 1 , 2 , 15 – 17 ], which can confirm that ICTs ultimately improve national health outcomes by collecting and processing health information and enhancing communication and collaboration. However, through the literature review, we found that, on the one hand, the variables and dimensions used to measure ICTs in existing studies are not comprehensive; ICT factors are usually discussed as a whole and as one independent variable; on the other hand, most of the existing studies use cross-sectional data as the data resource, and there is a lack of consideration of the time dimension. Moreover, more importantly, the whole process and pathway of the effect of ICTs on the overall health level of the country are complex, and this issue has not been much explored in existing studies.

Based on the above discussion, this study explores the dynamic relationships between ICTs, the impact of ICTs, and the health levels of different countries over time. In this regard, two research questions are proposed to further explore this complex mechanism:

• Do ICT factors influence the national health outcomes of a country over time?
• What is the process and mechanism of ICT factors to improve national health outcomes?

In order to answer the above research questions, the panel data of 141 countries from 2012 to 2016 are taken as samples. ICT factors and ICT impact are extracted as independent variables and intermediary variables, respectively, from Networked Readiness Index (NRI) from the Global Information Technology Report. Four commonly used public health indicators are selected from MDGs and World Development Indicators as the explained variables. The classical stepwise regression method and Sobel test are used to test the mediated effects, so as to verify the mechanism of the relationships between the above variables.

The exploration of the above research questions is a useful addition and extension to the studies related to the impact and impact pathways of ICTs on national health outcomes. At the same time, answering these questions can help global policymakers to formulate health resource allocation and investment strategies, especially in the fields of healthcare and technology in developing countries, so as to achieve the best interests of people worldwide.

This paper is organized as follows: Section 2 discusses the literature review, Section 3 is regarding the research model and research hypothesis, Section 4 is the empirical research, Section 5 is the discussion, and Section 6 is the conclusion, limitation and future research.

2. Literature Review

2.1. determinants of national health outcomes.

The overall health of a country's population, or the national health outcomes of a country, is determined by multidimensional factors, including political, economic, social, and technological ones.

Politics has been found to have an impact on a country's national health outcomes. Multiple studies [ 18 – 20 ] discussed the relationship between political regimes and population health, finding that the level of democracy has a positive significance on population health. In particular, according to Patterson and Veenstra [ 20 ], electoral democracies are 11 years longer and 62.5% lower than other countries in terms of life expectancy and infant mortality rate, respectively. Based on an empirical analysis of India, Data [ 21 ] argued that political competition in the election can prompt the government to increase public health expenditure. Klomp and Haan [ 22 ] proposed that a higher degree of government stability usually brings about better health outcomes.

Various economic determinants of national health outcomes have been discussed in previous research. Granados [ 23 ] reviewed in detail the prior literature on the macroeconomic effects on mortality, particularly on the theory that mortality oscillates in a procyclical manner with the business cycle. Birgisdóttir and Ásgeirsdóttir [ 24 ] observed a statistically significant connection between economic recessions and a lower mortality rate in women aged 45–64. However, Burgard and Kalousova [ 25 ] suggested a weak link between the 2008 Financial Crisis and the decline of overall mortality in the US, despite an increase in suicide and mental distress among the affluent during this downturn. Apart from macroeconomic conditions, income and employment also contribute to population health. A global gradient was reported by Curran and Mahutga [ 26 ] in the association of income inequality with national health outcomes, featuring a stronger negative impact of income inequality on population health in poorer countries than in richer ones. Peckham et al. [ 27 ] discovered a relationship between employment quality and self-rated health, mental health, and occupational injury, and rendered material deprivation, employment-related stressors, and occupational risk factors the mediators between employment and health status. Employment has also been found to have an impact on maternal self-reported health [ 28 ].

Studies are rapidly emerging on social determinants of population health. Various forms of social inequality are believed to subject people to higher health risks. Clouston et al. [ 29 ] observed contributions of disparities in socioeconomic status (SES) and ethnicity to inequalities in colorectal cancer mortality, with people of lower SES as well as Black, Hispanic, and Asian races prone to higher mortality due to a dearth of age-appropriate medical testing and treatment. Cogburn [ 30 ] argued that cultural racism exacerbates multi-facet racial inequalities in health policy making, practice, and public reception. According to Harnois and Bastos [ 31 ], workplace mistreatment such as discrimination and harassment helps to shape the gender gap in workers' self-reported health. Besides, education is also a social determinant of health status, in particular of maternal–infant health status. Abreha and Zereyesus [ 32 ] pointed out a positive connection between women's empowerment by education and child health in Sub-Saharan Africa. Based on an empirical analysis of 153 countries from 1970 to 2016, Shorette and Burroway [ 33 ] found a distribution-specific advantage of women's education in reducing infant mortality; the significant impact is limited to the range of infant mortality rates from 11 to 55 deaths per 1000 live births.

Discussions over technological effects on population health lie primarily in ICT-health relations. Chauvin and Rispel [ 34 ] described the huge potential digital technologies possess to improve the health status of the mass public and health equity. Noh et al. [ 35 ] reported that mobile phones with a SIM card can lead to a substantial increase in the access to healthcare services for crisis-affected people in Afghanistan. Rafia et al. [ 36 ] confirmed ICTs' role in improving population health and longevity in Malaysia in both the short and long run. A systematic review is presented on the relationship between ICTs and health outcomes in the subsequent section.

2.2. ICTs and National Health Outcomes

Within the research of ICT factors and health outcomes, many multinational empirical studies have used similar indicators of national health development level. Mithas et al. [ 15 ], Wu [ 2 ] and Raghupathi [ 1 ] found that there is a positive correlation between ICTs and life expectancy. Mithas used a sample of 61 countries, and the other two samples are about 200 countries each. In addition, the authors studied the possible relationships between ICTs and mortality, fertility and tuberculosis in countries with different levels of development. Irawan and Koesoema [ 16 ] also found a significant relationship between ICTs, e-Health, child mortality and maternal health, mainly in developing countries, especially in sub-Saharan Africa, where maternal mortality still remains rather high; Mlambo et al. [ 37 ] proved that the use of ICTs can significantly reduce maternal mortality by enabling women' engagement in health treatment and welfare. Ahangama and Poo [ 17 ] found evidence of the moderating role of e-Health in improving infant survival in a sample of 55 countries.

All empirical studies use samples from countries with different levels of development, which may lead to some deviations. In the study of Wu [ 2 ] and Raghupathi [ 1 ], they isolated the developed countries and carried out a separate study and found that the positive correlation between ICT development and health outcomes was still widespread. The above authors tended to use the linear regression method, using cross-sectional data or panel data to test hypotheses. Tavares [ 38 ] also studied the relationship between ICTs, e-Health, and health outcomes in a sample of only 28 EU countries. Another innovation of the paper is that health outcomes are self-reported by individuals, rather than traditional population health indicators such as mortality or life expectancy.

In recent years, ICTs' role in health emergency response has garnered growing attention. Bajpai et al. [ 39 ] examined ICTs' performance in immediate relief and medical response in the context of COVID-19, including testing and diagnosis, patient-centric record keeping and case management, as well as telemedicine. Besides, ICTs are conducive to public mental health in the era of social distancing by helping people stay socially connected [ 40 ].

It is important to note that most of the studies focus on EU countries, while other regional or global studies account for a small proportion. This is due to the substantial sources of databases of the EU. Compared with WHO and the World Bank, EU indicators are more comprehensive, and most of them are numerical data, which is conducive to more complex data analysis.

2.3. ICT Impacts on Economy and Society

In view of the fact that national health indicators can reflect the overall development level and people's quality of life of a country to a certain extent, the literature review should also be extended to the broader research topic of the impact of ICTs on the economy and society.

Cisco conducted a time-series analysis to explain the positive impact of ICT investment on UK economic growth (1999–2000). It has been found that the positive impact of ICT investment is particularly evident in the job market and is achieved through human capital restructuring. Likewise, Chu [ 41 ] found that from 1987 to 2001, the profit generated by New Zealand's IT service industry was positively correlated with GDP growth. By employing Toda–Yamamoto Granger causality approach, Solarin et al. [ 42 ] investigated the impact of ICTs, financial development and economic growth on electricity consumption in Malaysia and found a positive feedback effect between ICTs and electricity consumption. Meanwhile, in the trade research area, ICTs, as the carrier of digital trade, also have been proved to be able to promote green total factor productivity (GTFP) combined with human capital factor and R&D factor [ 43 ].

In order to make comparative studies on the national ICT level of different countries, Northrop [ 44 ] introduced a path model to examine the association among economic factors, social infrastructure and information infrastructure. The model used multiple regression analysis and path analysis to study the factors influencing the transnational differences in computer penetration.

Multiple similar papers have mentioned how an economy can benefit from the development of ICTs. First of all, NIA [ 45 ] proposed the positive impact of ICTs on national competitiveness by studying how the status of cross-national ICTs is related to the national competitiveness indicators of the World Economic Forum. Secondly, in a study of 19 countries, OECD (2008) indicated that the popularity of broadband technology was related to GDP growth. Finally, it threw light on the importance of public investment based on the analysis of the broadband technology opportunity program.

Apart from their economic role, ICTs also exert a profound influence on various social aspects. Park and Lee [ 46 ] discovered specific linkages between different forms of social capital and different forms of ICTs, suggesting a positive role of cell phone use for interpersonal purposes in facilitating bonding social capital, and that of computer use for political and information purposes in promoting bridging social capital. According to Synowiec [ 47 ], ICTs contribute to rural development by creating sources of income and granting access to education. Edinyang et al. [ 48 ] believed that in the days of information explosion, social development in Nigeria can be enhanced by ICTs as a strong catalyzer for knowledge integration. In addition, the dissemination of ICTs sees its own part in innovating social protection schemes [ 49 ], bolstering family solidarity [ 50 ], and developing home-based business communities [ 51 ].

2.4. Summary of the Literature

In view of this background, we can conclude that the positive link between ICTs and public health outcomes has been widely discussed. However, most existing studies generally focus on case studies and the introduction of specific technologies in individual countries or even in a specific location within a country. In the research of related fields, some focus on the correlations among variables such as ICTs, e-Health (and related policies), digital divide, public health expenditure and a number of health indicators, and some conduct cluster analysis of countries in specific regions based on these indicators [ 52 ]. Although these studies provide detailed and rich data representation, their analysis level does not rise to the level of broader samples. Moreover, previous researchers have not studied whether ICTs indirectly affect health indicators by influencing the economy and society. After all, e-Health mentioned above is actually one of the social impacts of ICTs.

Based on prior studies, this research further subdivides ICT factors to refine the granularity of variables. Grounded on the four dimensions of NRI released by World Economic Forum, ICT environment, ICT readiness, and ICT usage three dimensions are selected as independent variables. Four health indicators from the World Bank database are selected as dependent variables. This research selects ICT economic impact and ICT social impact from the NRI as two mediating variables to represent the fourth NRI dimension, ICT impact, which is the first indicator adopted in all similar studies. It is also the first time that they have been used as mediating variables to explore their role in the relationships between ICT indicators and health levels via the mediated effect model.

3. Research Model and Research Hypothesis

3.1. ict factors and national health outcomes.

All the ICT factors used in this study are extracted from the NRI from the Global Information Technology Report, which has been annually released for the last decade. The World Economic Forum, in collaboration with INSEAD, initially began this project to explore the impact of ICTs on productivity and development, as a component of the Forum's research on competitiveness. To this end, over the past decade, the NRI has been measuring the degree to which economies across the world leverage ICTs for enhanced competitiveness. During this period, it has been helping policymakers and relevant stakeholders to track their economies' strengths and weaknesses as well as their progress over time. It is also a solid and substantial data source for the academic community to conduct empirical research.

NRI is a comprehensive index composed of 4 subindices, 10 pillars, and 53 independent indicators distributed on different pillars. The main data providers are the International Telecommunication Union (ITU), UNESCO, and other UN agencies, as well as the World Bank. The other half comes from the executive opinion survey of the World Economic Forum.

The four subindices of NRI are ICT environment, ICT readiness, ICT usage, and ICT impact. In this study, three subindices, ICT environment, ICT readiness, and ICT usage, are selected as the independent variables. The ICT environment subindex gauges the friendliness of a country's market and regulatory frameworks and their ability to support high levels of ICT uptake and the development of entrepreneurship; it also gauges the presence of innovation-prone conditions needed to maximize the potential impacts of ICTs in boosting the economy's competitiveness and its citizens' well-being. The ICT readiness subindex measures the degree to which a society is prepared to make good use of an affordable ICT infrastructure and digital content. The ICT usage subindex assesses the individual efforts of the main social agents—that is, individuals, business, and governments—to increase their capacity to use ICTs, as well as their actual use in their day-to-day activities with other agents.

The dependent variables selected in this research, health indicators, are from MDGs and World Development Indicators. These indicators are the under-five mortality rate, maternal mortality ratio, adolescent fertility rate, and life expectancy at birth. They are widely recognized and applied by international organizations such as the United Nations, and have also been used many times in previous studies.

3.1.1. Under-Five Mortality Rate

Many studies have highlighted the role of ICTs in supporting the delivery of health services, especially in maternal and child health. In terms of Goal 4-reduce child mortality from MDGs, one of the main reasons is the lack of knowledge about childhood diseases, which applies to both developed and developing countries. Access to information through the Internet, mobile communications, radio, and other ICT applications can help parents and doctors find ways to treat sick children better. In developed countries like the United States, a telemedicine program for parents of infants reports that they have 10% higher quality of care than those who do not use telemedicine systems. In developing countries, there is already global public health information and education based on SMS. Studies have shown that the percentage of parents using ICT-based health tools can measure the impact of ICTs on improving the health of infants and children, thereby reducing their mortality. Specifically, in terms of ICT environment, the friendlier a country's market and regulatory framework is, or the better its ability to support high levels of ICT uptake and entrepreneurial development is, the greater the support of ICTs for medical and health services will be, making it possible for parents and doctors, as well as hospitals, to take more effective measures to reduce child mortality. Similarly, if a country is well prepared to leverage affordable ICT infrastructure and digital content, or it has made significant efforts to improve its ability to use ICTs, it will be able to integrate ICTs with healthcare services better, which will lead to better child mortality reduction at the country-wide level. Therefore, we can make the following hypotheses:

• H1 : ICT factors are negatively related with under-five mortality rate.
• H1a : ICT environment is negatively related with under-five mortality rate.
• H1b : ICT readiness is negatively related with under-five mortality rate.
• H1c : ICT usage is negatively related with under-five mortality rate.

3.1.2. Maternal Mortality Ratio

In terms of Goal 5-improve maternal health from MDGs, 99% of maternal deaths occur in developing countries. In India, SISU Samrakshak (SSK) refers to a child protector jointly developed by the United Nations Children's Fund (UNICEF) Hyderabad Field Office, CoOptions Technologies Ltd. And the AP government in 2000. SSK deploys ICTs in regional languages to impart health, hygiene, and sanitation knowledge to illiterate communities through audio, pictures, videos, touch screens, and culturally appropriate images. It provides basic information on the different stages of a child from pregnancy to adolescence, women's health during pregnancy, nutrition, child development, safe motherhood, immunization, common diseases, and their remedies. It treats mothers as primary caregivers but allows key actors (such as front-line government workers in the health, nutrition, and education sectors) to promote community learning. Maternal mortality is a key factor in measuring the overall health of a country. If a country has the ability to support higher levels of ICT uptake and the development of entrepreneurship, the country's ICT hardware facilities and related application level will be higher, and ICTs will provide more support for social medical and health services, so that women themselves, families, doctors, and hospitals are likely to take more effective measures to reduce maternal mortality. Likewise, the full preparation to make good use of the affordable ICT infrastructure and digital content, and the higher capacity to use ICTs, will enable the whole society to better reduce maternal mortality, given that the dissemination and use of information, knowledge, and measures on maternal care will be more effective. Therefore, we can make the following hypotheses:

• H2 : ICT factors are negatively related with maternal mortality ratio.
• H2a : ICT environment is negatively related with maternal mortality ratio.
• H2b : ICT readiness is negatively related with maternal mortality ratio.
• H2c : ICT usage is negatively related with maternal mortality ratio.

3.1.3. Adolescent Fertility Rate

The adolescent fertility rate is mainly used to reflect the education level of adolescents, including basic education and sex education. The high adolescent birth rate means fewer adolescents are in education. In addition, early childbearing itself is associated with complications and less access to post-natal health care. Globally, the adolescent birth rate among women aged 15–19 has fallen 21% since 2000. However, two-thirds of all countries still have high adolescent birth rates. In general, the spread and application of ICTs can assist in the provision of health information through online health services, and then help the adolescent population to continue their education at a higher level, take preventive measures, thus reduce fertility rates. If the country offers friendly market and regulatory frameworks, and encourages business innovation and practice, it can create a good environment to improve the number of years and levels of education of young people. Meanwhile, the better readiness and preparation of ICTs, or the wider and deeper use of ICTs, will enable the whole society to better reduce the adolescent fertility rate, given that this will help popularize basic education and sex education for young people. Therefore, we can make the following hypotheses:

• H3 : ICT factors are negatively related to adolescent fertility rate.
• H3a : ICT environment is negatively related to adolescent fertility rate.
• H3b : ICT readiness is negatively related to adolescent fertility rate.
• H3c : ICT usage is negatively related to adolescent fertility rate.

3.1.4. Life Expectancy at Birth

Life expectancy at birth (or life expectancy for short) is an important indicator of life. A key goal of improving the national health is to increase people's life expectancy, and the use of ICTs can make a huge difference here. On one hand, ICT devices and applications can provide health workers with ICT-assisted functions to collect, record, and share information about health conditions of patients, thereby effectively assisting medical and treatment decision-making, improving medical standards, and resultingly increasing care rates. And on the other, ICTs can contribute overall to this goal by providing health-related information to the public through, for example, online health, and through follow-up activities to educate the public. If a country has an advanced and mature ICT environment, then it has a higher level of ICT hardware facilities and related applications, ICT support for social medical and health services will also be greater. As a result, the general population can generally benefit from this and thus increase life expectancy. Likewise, the higher readiness of ICTs, or the wider and deeper use of ICTs, will enable the whole society to better improve life expectancy, given that the dissemination and use of information, knowledge and measures on healthcare will be more effective. Therefore, we can make the following hypotheses:

• H4 : ICT factors are positively related to life expectancy at birth.
• H4a : ICT environment is positively related to life expectancy at birth.
• H4b : ICT readiness is positively related to life expectancy at birth.
• H4c : ICT usage is positively related to life expectancy at birth.

3.2. ICT Impact and the Mediation Role

ICT factors can directly improve the national health levels, but at the same time, we need to note that ICT factors are playing a different role in improving the national health levels with the direct role of treatments or medicines. They are playing a role in making the health information processing more efficient and effective, making the treatment process more convenient and intelligent, improving the economy of the nation, improving the well-being of society, and thus indirectly enhancing the national health levels. Therefore, we can hypothesize that ICT factors have different mechanisms of action, both direct and mediated, for the improvement of national health status.

In this study, we use ICT impact from NRI as mediating variable to characterize the mediating mechanism between ICT factors and national health levels. We divide this mediating mechanism into two aspects, ICT economic impact and ICT social impact, to measure the extensive economic and social impact of ICT to enhance competitiveness and welfare, reflecting the transition to ICT and technology-sensitive economy and society.

Economic impact measures the impact of ICTs on competitiveness, which is due to technological and non-technological innovation in the form of patents, new products or processes, and organizational practices. It also measures the overall shift of an economy towards knowledge-intensive activities.

Social impact aims to assess the improvement in well-being due to the impact of ICTs on the environment, education, energy consumption, health progress, or more active citizen participation. At present, due to limited data, this pillar focuses on measuring the extent to which governments have improved the use efficiency of ICTs and provided more and more online services to their citizens, thereby facilitating their online participation. It also assesses the extent of ICT application in education, reflecting the potential benefits of ICT use in education.

As mentioned above, ICTs can influence a country's economy and society and thus its overall level of development, including economic growth and the job market, sources of income and educational opportunities [ 47 ], and, of course, the level of national health that we focus on here. Therefore, we can formulate the following hypothesis:

H5 : ICT impact has a mediated effect between ICT factors and national health outcomes.

In this study, there are three independent variables, two intermediary variables, and four dependent variables. Due to the large number of variables and limited space, all sub-hypotheses of H5 are not listed here.

3.3. Theoretical Model

Totally, the purpose of this cross-national study is to empirically evaluate the two related research questions: Do ICT factors influence national health outcomes of a country over time? Do economic and social impacts of ICTs mediate the relationship between ICT factors and national health outcomes?

In addition, considering that national income will greatly affect national health, we refer to the previous literature and add GDP by country (from the World Bank) into our model as a control variable.

Based on the above discussion, this research establishes a research model, as shown in Figure 1 :

Research model.

4. Empirical Research

4.1. variables and data measurement.

This research collect data from World Bank and World Economic Forum Global Information Technology Report from 2012 to 2016. To obtain a set of balanced panel data, we took the intersection of the two databases and finally obtained 141 countries as the study samples (see Table1 for the list of countries). These 141 countries represent different continents and different economic levels and are generally representative. Regarding the measurement of the three independent variables, based on the preceding literature and analysis, this paper measures ICT environment using the pillar business and innovation environment from NRI, measures ICT readiness using the pillar affordability from NRI, and measures ICT usage using the pillar individual usage from NRI.

The list of countries.

1	Albania
2	Algeria
3	Angola
4	Argentina
5	Armenia
6	Australia
7	Austria
8	Azerbaijan
9	Bahrain
10	Bangladesh
11	Barbados
12	Belgium
13	Belize
14	Benin
15	Bhutan
16	Bolivia
17	Bosnia and Herzegovina
18	Botswana
19	Brazil
20	Brunei Darussalam
21	Bulgaria
22	Burkina Faso
23	Burundi
24	Cambodia
25	Cameroon
26	Canada
27	Chad
28	Chile
29	China
30	Colombia
31	Costa Rica
32	Croatia
33	Cyprus
34	Czech Republic
35	Denmark
36	Dominican Republic
37	Ecuador
38	El Salvador
39	Estonia
40	Ethiopia
41	Finland
42	France
43	Gabon
44	Gambia
45	Georgia
46	Germany
47	Ghana
48	Greece
49	Guatemala
50	Guinea
51	Guyana
52	Haiti
53	Honduras
54	Hungary
55	Iceland
56	India
57	Indonesia
58	Iran, Islamic Rep.
59	Ireland
60	Israel
61	Italy
62	Jamaica
63	Japan
64	Jordan
65	Kazakhstan
66	Kenya
67	Korea, Rep.
68	Kuwait
69	Kyrgyz Republic
70	Lao PDR
71	Latvia
72	Lebanon
73	Lesotho
74	Liberia
75	Libya
76	Lithuania
77	Luxembourg
78	Madagascar
79	Malawi
80	Malaysia
81	Mali
82	Malta
83	Mauritania
84	Mauritius
85	Mexico
86	Moldova
87	Mongolia
88	Montenegro
89	Morocco
90	Mozambique
91	Myanmar
92	Namibia
93	Nepal
94	Netherlands
95	New Zealand
96	Nicaragua
97	Nigeria
98	Norway
99	Oman
100	Pakistan
101	Panama
102	Paraguay
103	Peru
104	Philippines
105	Poland
106	Portugal
107	Puerto Rico
108	Qatar
109	Romania
110	Russian Federation
111	Rwanda
112	Saudi Arabia
113	Senegal
114	Serbia
115	Seychelles
116	Sierra Leone
117	Singapore
118	Slovak Republic
119	Slovenia
120	South Africa
121	Spain
122	Sri Lanka
123	Suriname
124	Sweden
125	Switzerland
126	Tajikistan
127	Tanzania
128	Thailand
129	Timor-Leste
130	Trinidad and Tobago
131	Tunisia
132	Turkey
133	Uganda
134	Ukraine
135	United Arab Emirates
136	United Kingdom
137	United States
138	Uruguay
139	Vietnam
140	Zambia
141	Zimbabwe

In order to obtain effective results in subsequent data analysis, the dependent variables and the control variable GDP are reported in logarithmic form due to the large differences among sample countries and scattered sample data. All the variables are organized in Table 2 .

Data sources and descriptive analysis.

Category	Variable	Content	Data source	Method		Mean	Sd	Min	Max
Dependent variables	Under-five mortality rate	Under-five mortality rate/MDGs-goal 4	World bank	Ln	700	2.76	1.13	0.79	4.99
	Maternal mortality ratio	Maternal mortality ratio/MDGs-goal 5	World bank	Ln	700	2.54	1.07	0.59	4.61
	Adolescent fertility rate	Adolescent fertility rate/MDGs-goal 5	World bank	Ln	705	3.38	1.07	0.38	5.19
	Life expectancy at birth	Life expectancy at birth/World development indicators	World bank	Ln	705	4.28	0.12	3.86	4.43
Independent variables	ICT environment	NRI pillar: business and innovation environment	WEF—the global information technology report	n/a	671	4.24	0.69	2.36	5.97
	ICT readiness	NRI pillar: affordability	WEF—the global information technology report	n/a	662	4.9	1.32	1	7
	ICT usage	NRI pillar: individual usage	WEF—the global information technology report	n/a	671	3.77	1.55	1.3	6.86
Mediating variables	ICT economic impact	ICT impact-economic impact	WEF—the global information technology report	n/a	671	3.45	0.95	1.83	6.15
	ICT social impact	ICT impact-social impact	WEF—the global information technology report	n/a	671	3.96	1.01	1.7	6.28
Control variables	GDP	GDP (constant 2010 US$)	World bank	Ln	705	24.91	1.99	20.89	30.55

4.2. Mediated Effect Model

The mediated effect model originates from the research in the field of psychology. Considering the influence of independent variable X on the dependent variable y , if X influences Y by influencing variable M , then M is called the mediating variable. The following regression equations and the model shown in Figure 2 can be used to describe the relationship between variables

Mediated effect model (Baron and Kenny, 1986).

Coefficient c of equation ( 1 ) is the total effect of independent variable X on the dependent variable Y . Coefficient a of equation ( 2 ) is the effect of independent variable X on mediating variable M . Coefficient b of equation ( 3 ) is the effect of mediating variable M on the dependent variable Y after controlling the influence of independent variable X . Coefficient c' is the direct effect of independent variable X on dependent variable Y after controlling the influence of intermediate variable m . e 1 , e 2 , and e 3 are residuals.

The most commonly used method to test the mediated effect is causal step regression [ 53 , 54 ]:

• Test coefficient c of equation ( 1 ). If coefficient c is not significant, then there is no need for the mediation test.
• Test coefficient a of equation ( 2 ) and coefficient b of equation ( 3 ), which is called the joint significance test [ 55 ]. If coefficient c is significant as well as coefficients a and b , then the mediated effect is significant, and proceed to step iii. If a or b or both are not significant, the Sobel test is performed to further determine whether there is a mediated effect.
• Test coefficient c' of equation ( 3 ). If c' is significant, the mediated effect is partial; otherwise, it is complete.

The mediated effect model is used as the main mechanism in this paper, in which three ICT factor variables are independent variables (X), two ICT impact variables are mediating variables (M), and four national health outcome variables are dependent variables (Y). At the same time, the balanced panel data of 141 countries from 2012 to 2016 are used in this paper, so the mediation test of panel data will be performed.

4.3. Data Analysis

The panel data analysis and corresponding mediated effect analysis are conducted in STATA. Considering individual differences between different countries, this study adopts fixed effect model to verify panel data. All the results are shown in Tables ​ Tables3 3 ​ 3 ​ – 6 .

Associations between ICT factors and national health outcomes.

Variables	(1)	(2)	(3)	(4)
	Under-five mortality rate	Maternal mortality ratio	Adolescent fertility rate	Life expectancy at birth
ICT environment	−0.0575	−0.0547	−0.0680	0.00243
	(0.0134)	(0.0128)	(0.0168)	(0.00256)
ICT readiness	−0.00257	−0.00312	0.00680	0.000210
	(0.00258)	(0.00246)	(0.00325)	(0.000493)
ICT usage	−0.0661	−0.0708	−0.0555	0.00406
	(0.00639)	(0.00611)	(0.00804)	(0.00122)
GDP	−0.425	−0.346	−0.234	0.0850
	(0.0342)	(0.0327)	(0.0431)	(0.00654)
Constant	13.84	11.67	9.667	2.130
	(0.835)	(0.798)	(1.051)	(0.160)
Observations	660	660	662	662
R-squared	0.626	0.618	0.364	0.438
Number of id	140	140	141	141

Standard errors in parentheses ∗∗∗ p < 0.01, ∗∗ p < 0.05, ∗ p < 0.1

Associations between ICT factors and ICT Impacts.

Variables	(5)	(6)
	ICT economic impact	ICT social impact
ICT environment	0.257	0.373
	(0.0497)	(0.0772)
ICT usage	0.00795	0.233
	(0.0237)	(0.0369)
GDP	0.00485	0.852
	(0.127)	(0.197)
Constant	2.176	−19.79
	(3.105)	(4.817)
Observations	662	662
R-squared	0.074	0.334
Number of id	141	141

Mediated effect model (MV is the ICT economic impact).

Variables	(7)	(8)	(9)	(10)
	Under-five mortality rate	Maternal mortality ratio	Adolescent fertility rate	Life expectancy at birth
ICT environment	−0.0644	−0.0592	−0.0725
	(0.0137)	(0.0131)	(0.0173)
ICT usage	−0.0665	−0.0711	−0.0556	0.00411
	(0.00637)	(0.00610)	(0.00804)	(0.00121)
ICT economic impact	0.0270	0.0175	0.0172	-0.00651
	(0.0119)	(0.0114)	(0.0149)	(0.00224)
GDP	−0.424	−0.346	−0.234	0.0850
	(0.0341)	(0.0327)	(0.0431)	(0.00649)
Constant	13.76	11.62	9.630	2.145
	(0.832)	(0.798)	(1.051)	(0.159)
Observations	660	660	662	662
R-squared	0.630	0.619	0.365	0.447
Number of id	140	140	141	141

Mediated effect model (MV is the ICT social impact).

Variables	(11)	(12)	(13)	(14)
	Under-five mortality rate	Maternal mortality ratio	Adolescent fertility rate	Life expectancy at birth
ICT environment	−0.0520	−0.0504	−0.0617
	(0.0136)	(0.0130)	(0.0172)
ICT usage	−0.0627	−0.0681	−0.0515	0.00388
	(0.00662)	(0.00633)	(0.00833)	(0.00127)
ICT social impact	−0.0147	−0.0116	−0.0169	0.000749
	(0.00759)	(0.00727)	(0.00958)	(0.00146)
GDP	−0.412	−0.336	−0.220	0.0843
	(0.0347)	(0.0333)	(0.0438)	(0.00666)
Constant	13.55	11.44	9.334	2.145
	(0.846)	(0.810)	(1.066)	(0.162)
Observations	660	660	662	662
R-squared	0.629	0.620	0.368	0.438
Number of id	140	140	141	141

For the first step, the associations between ICT factors and national health outcomes are tested. The association between the ICT factors and the four health indicators is summarized in Table 3 .

The results show that ICT environment has a significant negative impact on under-five mortality rate, maternal mortality ratio, and adolescent fertility rate. H1a, H2a, and H3a are confirmed, but H4a is not. The impact of ICT readiness on four national health indicators is not confirmed. ICT usage has a significant impact on the four health outcome indicators, meaning that H1c, H2c, H3c, and H4c are confirmed. Meanwhile, the influence of improving national GDP on the above four health outcome indicators is also confirmed.

Therefore, it can be proved that ICT factors have a significant role in promoting the overall national health. Improving ICT environment and ICT usage can effectively reduce under-five mortality rate, maternal mortality ratio, and adolescent fertility rate, while improving ICT usage can promote life expectancy at birth.

The hypotheses that are not confirmed in the first step will not proceed to subsequent mediation tests, and we can directly affirm that there is no mediated effect regarding these hypotheses. Therefore, the following tests will explore whether the two mediating variables, ICT economic impact and ICT social impact, have mediated effects on the relationship between ICT environment and under-five mortality rate, maternal mortality ratio, and adolescent fertility rate, and whether they can mediate between the independent variable ICT usage and the four dependent variables.

The second step is the mediation test, which should test the coefficient a in the model equation ( 2 ). Table 4 shows the relationship between ICT factors and the economic and social impact of ICTs.

It can be seen that the correlation between ICT environment and ICT economic impact, the correlation between ICT environment and ICT social impact, and the correlation between ICT usage and ICT social impact are all positively significant, that is, the coefficient “a” is significant, which can enter step 3 of the mediation test.

However, the correlations between ICT usage and ICT economic impact are not significant, so the Sobel test will be performed to further explore the possible mediated effect.

After step 2, we enter the third step of mediation test, which is to test the coefficient b and the coefficient c' in the model formula ( 3 ). Table 5 and Table 6 show the results.

Tables 5 and 6 show that when independent variables are controlled, the ICT economic impact has no significant effect on the four health indicators, meaning that their coefficient b is not significant. Therefore, all the mediated effects with ICT economic impact as the mediating variable will enter the subsequent Sobel test.

Meanwhile, we can see that when under-five mortality rate and adolescent fertility rate are dependent variables, and independent variables ICT environment and ICT usage and mediating variable ICT social impact are entered the regression model, their coefficients b and c' are all significant. Therefore, it can be directly determined that for dependent variables under-five mortality rate and adolescent fertility rate, ICT social impact has a partial mediated effect on their relationship with ICT environment and ICT usage. However, for the dependent variables maternal mortality ratio and life expectancy at birth, it is still unclear whether ICT social impact has a mediated effect, so further Sobel test is needed.

Now, we conduct a Sobel test on the above hypotheses where the mediated effect may exist but so far cannot be confirmed. During the Sobel test, we still follow the fixed effect test rule of panel data and add dummy variables representing the national individual effect into the regression model as control variables. The test results show that only ICT economic impact has a mediated effect between ICT environment and under-five mortality rate (Sobel p value = 0.377, Goodman-1(Aroian) p value = 0.0407, Goodman-2 p value = 0.0348). However, the proportion of total effect that is mediated is minus, indicating that the suppression effect occurs and the mediated effect cannot be confirmed.

In a nutshell, the partial mediated effect that has been confirmed in previous analyses is reconfirmed in the Sobel test. The proportion of the partial mediated effect and key information is summarized as follows:

The final results of the mediated effect model are displayed in Table 7 , indicating that part of H5 is proved. First, all evident mediated effects are partial mediation. This is not hard to understand. Previous research has suggested that complete mediation is rare [ 56 ]. When we conclude a complete mediation, we actually rule out exploring other mediated effects in the future [ 57 ]. Preacher and Hayes [ 58 ] called for the abandonment of the concept of complete mediation and regarded all mediated effects as partial mediation. The results of our study further verify this point.

Mediated effect result overview.

Dependent variables	Under-five mortality rate		Adolescent fertility rate
Mediating variables	ICT social impact		ICT social impact
Independent variables	ICT environment	ICT usage	ICT environment	ICT usage
Sobel Z	−1.801	−1.855	−1.654	−1.695
Sobel value	0.07163448	0.06357	0.09814432	0.09001181
Goodman-1 Z	−1.769	−1.834	−1.624	−1.676
Goodman-1 value	0.07687708	0.06662993	0.10447248	0.09375428
Goodman-2 Z	−1.836	−1.877	−1.686	−1.715
Goodman-2 value	0.06641567	0.06052563	0.09178463	0.08626387
Proportion of total effect that is mediated	0.09574541	0.0518865	0.09248442	0.07066528

Second, the results show that ICT environment and ICT usage can influence both under-five mortality rate and adolescent fertility rate via ICT social impact. In other words, ICT environment and ICT usage can reduce under-five mortality rate and adolescent fertility rate by improving the social impact of ICTs. Although it can be seen from Table 6 that the proportion of total effect that is mediated is not high, indicating the effects of the independent variables on the dependent variables are the results of a combination of multiple factors, and the ICT social impact plays a relatively weak mediating role here. At the same time, the mediated effect of ICT social impact on maternal mortality ratio and life expectancy at birth is not confirmed. The mediated effect of ICT economic impact is not confirmed either.

Based on the above studies, all the results of hypothesis testing are summarized in Table 8 :

Results of hypothesis testing.

Hypothesis	Result
H1	Partially supported
H2	Partially supported
H3	Partially supported
H4	Partially supported
H5	Partially supported

5. Discussion

5.1. icts and national health outcomes.

This paper is highly relevant to the studies of the relationship between ICT and health outcomes, especially the cross-national research methods and conclusions, which are the most crucial to enlightening this research. The unit of analysis is a national-level characteristic. Thus, the outcome of this research should be applied to the explanation of national development, not individual, within a particular country to avoid ecological fallacy.

Our results indicate that overall ICT factors substantially facilitate national public health delivery. ICT factors are usually discussed as a whole and as one independent variable in the previous literature, mostly proved conducive to promoting health outcomes. This paper, however, divides ICT factors into three detailed dimensions of ICT environment, ICT readiness, and ICT usage based on NRI and finds that not all ICT factors have a significant impact.

ICT environment shows a significant role in promoting national health outcomes, especially in reducing under-five mortality rate, maternal mortality ratio, and adolescent fertility rate. This indicates that a country can effectively promote the development of ICT infrastructure and related applications by encouraging and supporting innovation, entrepreneurship and business, which leads to greater assistance and support of ICTs for social medical and health services, bringing more widespread benefits to the population and thus effectively reducing under-five mortality rate, maternal mortality ratio, and adolescent fertility rate. Exception occurs in that ICT environment has no significant impact on life expectancy at birth. A possible reason is that what ICT environment determines is the level of maturity and advancement of a country's market and business environment, which to some extent influences the national economic development, but may make little direct impact on life expectancy at birth. Another possible reason is that the conclusions of this study are based on data from 2012 to 2016, and due to the specificity of the data from this time period, it is not yet possible to effectively prove that ICT environment has a positive effect on the life expectancy at birth of the population, so the verification of this hypothesis needs to be confirmed by data from other subsequent years.

ICT readiness measures the degree to which a society is prepared to make good use of ICT infrastructure and related applications. The empirical results of this study suggest that its impact on improving national health is only marginal and statistically insignificant. One possible reason is that ICT readiness is different from ICT usage; it simply indicates the readiness of the country and society for future ICT use, but is distinct from the direct contribution that ICT usage can bring to national health levels. Therefore, the true impact of ICT readiness on national health outcomes needs further testing.

ICT usage measures the penetration and dissemination of ICTs, including the use of hardware facilities, software applications, and data. Comparatively speaking, the use of ICTs by individuals has the most direct and effective effect on the improvement of individual health outcomes. Therefore, ICT usage has the most significant impact on reducing under-five mortality rate, maternal mortality ratio and adolescent fertility rate, as well as promoting life expectancy at birth.

In general, ICTs are playing a significant role in improving national health, especially in developing countries. When ICTs are combined with healthcare, they can make a key contribution to improve the lives and well-being of people around the world. They can also support improvements in health development. With the rapid development of ICTs and online health, relevant successful cases abound in many less developed regions of the world.

5.2. Mediated Effects

ICTs are not medicines, vaccines, or health policies, rather ICTs are technologies that enable the processing of health information much more efficiently and effectively. However, ICT factors have different acting mechanisms on health outcomes. Some ICT factors use economic influence as a mediator, some use social influence, and some may directly influence health outcomes or may use other mediating variables not included in this paper.

In terms of the empirical results of the mediated effect, the cross-comparison of the two mediating variables shows that while ICT economic impact only exerts its influence in the economic field, ICT social impact can have an effect in a broader field of people's daily life. Relevant indicators are access to basic ICT services, Internet access in schools, ICT use and government effectiveness, and people's online engagement index. ICT infrastructure first permeates through the social life of a country, and then, as the country's social life thrives, the health of its people gradually improves. This makes the influence and mediated effect of ICT social impact on national health outcomes more significant.

When ICT social impact is used as the mediating variable, ICT environment and ICT usage were the two factors with the most significant results. Both ICT environment and ICT usage can reduce under-five mortality rate and adolescent fertility rate by improving ICT social impact. That is, by improving and optimizing the country's friendliness of a country's market and regulatory frameworks, and by further popularizing usage of ICTs, it is possible to bring improvements in the well-being of the environment, education, energy consumption, or more active civic participation as a result of the use of ICTs. Thus, we can conclude that a possible path is that ICT infrastructure lays a solid foundation for the widespread dissemination of social services, including neonatal care education, government support for childbirth, and abundant Internet resources, and thus effectively improves national health outcomes. This is mainly reflected in lowering under-five mortality rate and adolescent fertility rate.

However, the mediated effect of ICT usage on maternal mortality ratio and life expectancy at birth through ICT social impact is not confirmed. Although empirical results show that ICT usage does have a direct impact on maternal mortality ratio and life expectancy at birth, there is not enough evidence to prove that this impact can have an indirect effect through ICT social impact. One possible reason is that ICT social impact is too limited to cover the major factors influencing maternal mortality ratio and life expectancy at birth. Under the NRI, ICT social impact is measured by four indicators confined to ICTs' contributions to the accessibility of basic services, Internet use for learning purposes in school, quality of government services, and the public E-participation. Maternal mortality ratio, however, is much affected by socioeconomic disparity, urban-rural differences, women empowerment, and equity, as well as social norms and culture [ 59 , 60 ], which are hardly encompassed by the NRI. Likewise, ICT social impact under the NRI overlaps little with the broad determinants of life expectancy at birth, including economy, literacy, nutritional status, and political regime [ 61 ]. Thus, limitations in the measurement of the variable ICT social impact are a possible reason for the failure of this study to effectively confirm its mediating effect between ICT use and maternal mortality ratio and life expectancy at birth.

Meanwhile, the mediated effect of ICT environment on maternal mortality ratio through ICT social impact is not confirmed. Although empirical results show that ICT environment does have a direct impact on maternal mortality ratio. One possible reason for this, in addition to the fact that the social impact of ICTs, as mentioned above, is too limited to cover the main factors influencing maternal mortality ratio, is that ICT environment, the indicator of a country's business and market environment, which gauges the normative nature of regulatory framework and the presence of innovation-prone conditions, may channel its influence primarily through corporate, market, or even political factors rather than ICT social impact.

Finally, as mentioned above, unlike that of ICT social impact, the mediated effect of ICT economic impact is not confirmed. One possible reason is that according to the data source of this study, ICT economic impact is measured by ICT impact on business model, ICT patent application, ICT impact on organizational model, and the number of knowledge-intensive jobs. It is easy to see that ICT economic impact is mainly confined to the business sector. The important impacts of ICTs are multidimensional, and while previous empirical tests show that they do affect national health outcomes, many of these impacts are not currently being translated into or reflected in business. As a result, the mediated effect of ICT economic impact in this process becomes difficult to define and measure. Although not in line with our hypotheses, we can accept that the mediated effect is relatively weak in our research paradigm. Still, we hold the possibility that the measurements of those variables can be insufficient or inappropriate and leave space for future studies.

In general, measuring the impact of ICTs is a complex task, and the development of rigorous quantitative data for this purpose is still in its infancy. It is difficult to precisely define the impact, which is one of the main obstacles, because ICTs have proved transformative in many aspects of the economy and society, affecting not only the results but also the process of providing products and services. Therefore, it is difficult and expensive to develop indicators to measure these dimensions, especially when a large number of emerging countries are involved. Moreover, even if the area of impact can be identified, it is not necessarily easy to trace a particular impact back to all its original sources. The often observed economic and social impacts are the result of a tight network of interacting factors, and ICT is only one of them. As a result, many aspects of ICT impact (such as health environment) cannot be covered, especially when these impacts are not translated into commercial activities. Therefore, the ICT impact index should be regarded as an ongoing work. With the emergence of all kinds of new data, it will continue to develop and improve new dimensions.

6. Conclusion, Limitation, and Future Research

Based on the above studies, this research clarifies that ICT factors can influence national health outcomes of a country over time and ICT social impact can play an important partial mediating role between them.

The contributions of this study can be categorized into theoretical and practical ones. Theoretically, previous studies on ICTs and health development are mostly conceptual, or remain at the micro-level, focusing on the actual operation of technology. This study raises the theoretical altitude to a micro-level, introducing a wider sample of countries from the United Nations when a large number of fellow studies only look at EU, other regional organizations or even just individual countries. Second, on top of ICT factors, we bring in ICT impacts as mediations in our model, which is an innovation in the area. We hope it can serve as a good beginning for researchers to try other theoretical models and make them more sufficient and accurate. Finally, the study aims to review the realization of MDGs (2000–2015) and provide inspiration for SDGs (2015–2030). SDGs have 17 new development goals and will continue to guide the global development work in 2015–2030 after the expiration of the 2000–2015 MDGs. The goal of sustainable development is to solve the development problems of society, economy, and environment in a comprehensive way from 2015 to 2030 and turn to the road of sustainable development. Our study can lay the foundation for future research on SDGs, as well as for the comparative study of MDGs and SDGs.

Practically, this study aims to help global policymakers formulate health resource allocation and investment strategies, especially in the fields of healthcare and technology in developing countries. As we provide a new perspective to see how ICT factors associate with its impact, developing countries can use it as a guide to get financial assistance from or cooperate with other countries or organizations to improve health deliveries from their weakest areas with the most urgent needs according to their own conditions. To promote the implementation of SDGs in the next stage, we suggest integrating and determining priorities in national development and health promotion programs and strategies, adjusting policies for basic infrastructure deployment, facilitating donor coordination and cooperation mechanisms, strengthening the participation of the private sector, and coordinating resource mobilization mechanisms.

This study has the following limitations. First of all, this study uses the secondary data research method. The data is sourced from the annual macro data released by authoritative international government organizations which always need a long cycle to collect and the completeness is not enough. Due to the redesign of the NRI system, the complete data available are only from 2012 to 2016. The NRI was suspended during 2017 and 2018 for a redesign. Data from 2019 onwards comes from a new NRI system, which is incompatible with the previous ones. Therefore, 141 countries from 2012 to 2016 are selected as samples. The total observation values of each group regression range from 660 to 662. The sample size is comparatively small. In the future, with the development of innovative technologies and the completeness of data collected by various international government organizations, ongoing tracking and research could be considered, starting with data from 2019. A before-and-after study could also be considered to further explore the ongoing changes in national health levels as ICT use and penetration increase.

Secondly, the mediated effect model in this study aims to explore the role of the economic impact and social impact of ICTs on the relationship between ICTs and national health outcomes. However, this model is still in its original stage and further correction and adjustment are needed. In addition to the mediated effect, the moderating effects should be explored, and variable selection and data sources can be constantly updated in the future.

Acknowledgments

This research was supported by the National Natural Science Foundation of China (71974018), the National Natural Science Foundation of China (71573022), the National Natural Science Foundation of China (71874018), the G20 Research Center of BFSU (G2020201003), the G20 Research Center of BFSU (G2020213001), the Fundamental Research Funds for the Central Universities (2022JJ007). The authors thank WHICEB 2021 PROCEEDINGS and experts at the conference for their help in the pre-construction of this research.

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Conflicts of interest.

The authors declare that they have no conflicts of interest.

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Josephine Wolff; How Is Technology Changing the World, and How Should the World Change Technology?. Global Perspectives 1 February 2021; 2 (1): 27353. doi: https://doi.org/10.1525/gp.2021.27353

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Technologies are becoming increasingly complicated and increasingly interconnected. Cars, airplanes, medical devices, financial transactions, and electricity systems all rely on more computer software than they ever have before, making them seem both harder to understand and, in some cases, harder to control. Government and corporate surveillance of individuals and information processing relies largely on digital technologies and artificial intelligence, and therefore involves less human-to-human contact than ever before and more opportunities for biases to be embedded and codified in our technological systems in ways we may not even be able to identify or recognize. Bioengineering advances are opening up new terrain for challenging philosophical, political, and economic questions regarding human-natural relations. Additionally, the management of these large and small devices and systems is increasingly done through the cloud, so that control over them is both very remote and removed from direct human or social control. The study of how to make technologies like artificial intelligence or the Internet of Things “explainable” has become its own area of research because it is so difficult to understand how they work or what is at fault when something goes wrong (Gunning and Aha 2019) .

This growing complexity makes it more difficult than ever—and more imperative than ever—for scholars to probe how technological advancements are altering life around the world in both positive and negative ways and what social, political, and legal tools are needed to help shape the development and design of technology in beneficial directions. This can seem like an impossible task in light of the rapid pace of technological change and the sense that its continued advancement is inevitable, but many countries around the world are only just beginning to take significant steps toward regulating computer technologies and are still in the process of radically rethinking the rules governing global data flows and exchange of technology across borders.

These are exciting times not just for technological development but also for technology policy—our technologies may be more advanced and complicated than ever but so, too, are our understandings of how they can best be leveraged, protected, and even constrained. The structures of technological systems as determined largely by government and institutional policies and those structures have tremendous implications for social organization and agency, ranging from open source, open systems that are highly distributed and decentralized, to those that are tightly controlled and closed, structured according to stricter and more hierarchical models. And just as our understanding of the governance of technology is developing in new and interesting ways, so, too, is our understanding of the social, cultural, environmental, and political dimensions of emerging technologies. We are realizing both the challenges and the importance of mapping out the full range of ways that technology is changing our society, what we want those changes to look like, and what tools we have to try to influence and guide those shifts.

Technology can be a source of tremendous optimism. It can help overcome some of the greatest challenges our society faces, including climate change, famine, and disease. For those who believe in the power of innovation and the promise of creative destruction to advance economic development and lead to better quality of life, technology is a vital economic driver (Schumpeter 1942) . But it can also be a tool of tremendous fear and oppression, embedding biases in automated decision-making processes and information-processing algorithms, exacerbating economic and social inequalities within and between countries to a staggering degree, or creating new weapons and avenues for attack unlike any we have had to face in the past. Scholars have even contended that the emergence of the term technology in the nineteenth and twentieth centuries marked a shift from viewing individual pieces of machinery as a means to achieving political and social progress to the more dangerous, or hazardous, view that larger-scale, more complex technological systems were a semiautonomous form of progress in and of themselves (Marx 2010) . More recently, technologists have sharply criticized what they view as a wave of new Luddites, people intent on slowing the development of technology and turning back the clock on innovation as a means of mitigating the societal impacts of technological change (Marlowe 1970) .

At the heart of fights over new technologies and their resulting global changes are often two conflicting visions of technology: a fundamentally optimistic one that believes humans use it as a tool to achieve greater goals, and a fundamentally pessimistic one that holds that technological systems have reached a point beyond our control. Technology philosophers have argued that neither of these views is wholly accurate and that a purely optimistic or pessimistic view of technology is insufficient to capture the nuances and complexity of our relationship to technology (Oberdiek and Tiles 1995) . Understanding technology and how we can make better decisions about designing, deploying, and refining it requires capturing that nuance and complexity through in-depth analysis of the impacts of different technological advancements and the ways they have played out in all their complicated and controversial messiness across the world.

These impacts are often unpredictable as technologies are adopted in new contexts and come to be used in ways that sometimes diverge significantly from the use cases envisioned by their designers. The internet, designed to help transmit information between computer networks, became a crucial vehicle for commerce, introducing unexpected avenues for crime and financial fraud. Social media platforms like Facebook and Twitter, designed to connect friends and families through sharing photographs and life updates, became focal points of election controversies and political influence. Cryptocurrencies, originally intended as a means of decentralized digital cash, have become a significant environmental hazard as more and more computing resources are devoted to mining these forms of virtual money. One of the crucial challenges in this area is therefore recognizing, documenting, and even anticipating some of these unexpected consequences and providing mechanisms to technologists for how to think through the impacts of their work, as well as possible other paths to different outcomes (Verbeek 2006) . And just as technological innovations can cause unexpected harm, they can also bring about extraordinary benefits—new vaccines and medicines to address global pandemics and save thousands of lives, new sources of energy that can drastically reduce emissions and help combat climate change, new modes of education that can reach people who would otherwise have no access to schooling. Regulating technology therefore requires a careful balance of mitigating risks without overly restricting potentially beneficial innovations.

Nations around the world have taken very different approaches to governing emerging technologies and have adopted a range of different technologies themselves in pursuit of more modern governance structures and processes (Braman 2009) . In Europe, the precautionary principle has guided much more anticipatory regulation aimed at addressing the risks presented by technologies even before they are fully realized. For instance, the European Union’s General Data Protection Regulation focuses on the responsibilities of data controllers and processors to provide individuals with access to their data and information about how that data is being used not just as a means of addressing existing security and privacy threats, such as data breaches, but also to protect against future developments and uses of that data for artificial intelligence and automated decision-making purposes. In Germany, Technische Überwachungsvereine, or TÜVs, perform regular tests and inspections of technological systems to assess and minimize risks over time, as the tech landscape evolves. In the United States, by contrast, there is much greater reliance on litigation and liability regimes to address safety and security failings after-the-fact. These different approaches reflect not just the different legal and regulatory mechanisms and philosophies of different nations but also the different ways those nations prioritize rapid development of the technology industry versus safety, security, and individual control. Typically, governance innovations move much more slowly than technological innovations, and regulations can lag years, or even decades, behind the technologies they aim to govern.

In addition to this varied set of national regulatory approaches, a variety of international and nongovernmental organizations also contribute to the process of developing standards, rules, and norms for new technologies, including the International Organization for Standardization­ and the International Telecommunication Union. These multilateral and NGO actors play an especially important role in trying to define appropriate boundaries for the use of new technologies by governments as instruments of control for the state.

At the same time that policymakers are under scrutiny both for their decisions about how to regulate technology as well as their decisions about how and when to adopt technologies like facial recognition themselves, technology firms and designers have also come under increasing criticism. Growing recognition that the design of technologies can have far-reaching social and political implications means that there is more pressure on technologists to take into consideration the consequences of their decisions early on in the design process (Vincenti 1993; Winner 1980) . The question of how technologists should incorporate these social dimensions into their design and development processes is an old one, and debate on these issues dates back to the 1970s, but it remains an urgent and often overlooked part of the puzzle because so many of the supposedly systematic mechanisms for assessing the impacts of new technologies in both the private and public sectors are primarily bureaucratic, symbolic processes rather than carrying any real weight or influence.

Technologists are often ill-equipped or unwilling to respond to the sorts of social problems that their creations have—often unwittingly—exacerbated, and instead point to governments and lawmakers to address those problems (Zuckerberg 2019) . But governments often have few incentives to engage in this area. This is because setting clear standards and rules for an ever-evolving technological landscape can be extremely challenging, because enforcement of those rules can be a significant undertaking requiring considerable expertise, and because the tech sector is a major source of jobs and revenue for many countries that may fear losing those benefits if they constrain companies too much. This indicates not just a need for clearer incentives and better policies for both private- and public-sector entities but also a need for new mechanisms whereby the technology development and design process can be influenced and assessed by people with a wider range of experiences and expertise. If we want technologies to be designed with an eye to their impacts, who is responsible for predicting, measuring, and mitigating those impacts throughout the design process? Involving policymakers in that process in a more meaningful way will also require training them to have the analytic and technical capacity to more fully engage with technologists and understand more fully the implications of their decisions.

At the same time that tech companies seem unwilling or unable to rein in their creations, many also fear they wield too much power, in some cases all but replacing governments and international organizations in their ability to make decisions that affect millions of people worldwide and control access to information, platforms, and audiences (Kilovaty 2020) . Regulators around the world have begun considering whether some of these companies have become so powerful that they violate the tenets of antitrust laws, but it can be difficult for governments to identify exactly what those violations are, especially in the context of an industry where the largest players often provide their customers with free services. And the platforms and services developed by tech companies are often wielded most powerfully and dangerously not directly by their private-sector creators and operators but instead by states themselves for widespread misinformation campaigns that serve political purposes (Nye 2018) .

Since the largest private entities in the tech sector operate in many countries, they are often better poised to implement global changes to the technological ecosystem than individual states or regulatory bodies, creating new challenges to existing governance structures and hierarchies. Just as it can be challenging to provide oversight for government use of technologies, so, too, oversight of the biggest tech companies, which have more resources, reach, and power than many nations, can prove to be a daunting task. The rise of network forms of organization and the growing gig economy have added to these challenges, making it even harder for regulators to fully address the breadth of these companies’ operations (Powell 1990) . The private-public partnerships that have emerged around energy, transportation, medical, and cyber technologies further complicate this picture, blurring the line between the public and private sectors and raising critical questions about the role of each in providing critical infrastructure, health care, and security. How can and should private tech companies operating in these different sectors be governed, and what types of influence do they exert over regulators? How feasible are different policy proposals aimed at technological innovation, and what potential unintended consequences might they have?

Conflict between countries has also spilled over significantly into the private sector in recent years, most notably in the case of tensions between the United States and China over which technologies developed in each country will be permitted by the other and which will be purchased by other customers, outside those two countries. Countries competing to develop the best technology is not a new phenomenon, but the current conflicts have major international ramifications and will influence the infrastructure that is installed and used around the world for years to come. Untangling the different factors that feed into these tussles as well as whom they benefit and whom they leave at a disadvantage is crucial for understanding how governments can most effectively foster technological innovation and invention domestically as well as the global consequences of those efforts. As much of the world is forced to choose between buying technology from the United States or from China, how should we understand the long-term impacts of those choices and the options available to people in countries without robust domestic tech industries? Does the global spread of technologies help fuel further innovation in countries with smaller tech markets, or does it reinforce the dominance of the states that are already most prominent in this sector? How can research universities maintain global collaborations and research communities in light of these national competitions, and what role does government research and development spending play in fostering innovation within its own borders and worldwide? How should intellectual property protections evolve to meet the demands of the technology industry, and how can those protections be enforced globally?

These conflicts between countries sometimes appear to challenge the feasibility of truly global technologies and networks that operate across all countries through standardized protocols and design features. Organizations like the International Organization for Standardization, the World Intellectual Property Organization, the United Nations Industrial Development Organization, and many others have tried to harmonize these policies and protocols across different countries for years, but have met with limited success when it comes to resolving the issues of greatest tension and disagreement among nations. For technology to operate in a global environment, there is a need for a much greater degree of coordination among countries and the development of common standards and norms, but governments continue to struggle to agree not just on those norms themselves but even the appropriate venue and processes for developing them. Without greater global cooperation, is it possible to maintain a global network like the internet or to promote the spread of new technologies around the world to address challenges of sustainability? What might help incentivize that cooperation moving forward, and what could new structures and process for governance of global technologies look like? Why has the tech industry’s self-regulation culture persisted? Do the same traditional drivers for public policy, such as politics of harmonization and path dependency in policy-making, still sufficiently explain policy outcomes in this space? As new technologies and their applications spread across the globe in uneven ways, how and when do they create forces of change from unexpected places?

These are some of the questions that we hope to address in the Technology and Global Change section through articles that tackle new dimensions of the global landscape of designing, developing, deploying, and assessing new technologies to address major challenges the world faces. Understanding these processes requires synthesizing knowledge from a range of different fields, including sociology, political science, economics, and history, as well as technical fields such as engineering, climate science, and computer science. A crucial part of understanding how technology has created global change and, in turn, how global changes have influenced the development of new technologies is understanding the technologies themselves in all their richness and complexity—how they work, the limits of what they can do, what they were designed to do, how they are actually used. Just as technologies themselves are becoming more complicated, so are their embeddings and relationships to the larger social, political, and legal contexts in which they exist. Scholars across all disciplines are encouraged to join us in untangling those complexities.

Josephine Wolff is an associate professor of cybersecurity policy at the Fletcher School of Law and Diplomacy at Tufts University. Her book You’ll See This Message When It Is Too Late: The Legal and Economic Aftermath of Cybersecurity Breaches was published by MIT Press in 2018.

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	Notes or endnotes should only be used if absolutely necessary. They should be identified in the text by consecutive numbers enclosed in square brackets. These numbers should then be listed, and explained, at the end of the article.
	All figures (charts, diagrams, line drawings, webpages/screenshots, and photographic images) should be submitted electronically. Both colour and black and white files are accepted. There are a few other important points to note:
	Tables should be typed and submitted in a separate file to the main body of the article. The position of each table should be clearly labelled in the main body of the article with corresponding labels clearly shown in the table file. Tables should be numbered consecutively in Roman numerals (e.g. I, II, etc.). Give each table a brief title. Ensure that any superscripts or asterisks are shown next to the relevant items and have explanations displayed as footnotes to the table, figure or plate.
	Where tables, figures, appendices, and other additional content are supplementary to the article but not critical to the reader’s understanding of it, you can choose to host these supplementary files alongside your article on Insight, Emerald’s content-hosting platform (this is Emerald's recommended option as we are able to ensure the data remain accessible), or on an alternative trusted online repository. All supplementary material must be submitted prior to acceptance. Emerald recommends that authors use the following two lists when searching for a suitable and trusted repository:     , you must submit these as separate files alongside your article. Files should be clearly labelled in such a way that makes it clear they are supplementary; Emerald recommends that the file name is descriptive and that it follows the format ‘Supplementary_material_appendix_1’ or ‘Supplementary tables’. All supplementary material must be mentioned at the appropriate moment in the main text of the article; there is no need to include the content of the file only the file name. A link to the supplementary material will be added to the article during production, and the material will be made available alongside the main text of the article at the point of EarlyCite publication. Please note that Emerald will not make any changes to the material; it will not be copy-edited or typeset, and authors will not receive proofs of this content. Emerald therefore strongly recommends that you style all supplementary material ahead of acceptance of the article. Emerald Insight can host the following file types and extensions: , you should ensure that the supplementary material is hosted on the repository ahead of submission, and then include a link only to the repository within the article. It is the responsibility of the submitting author to ensure that the material is free to access and that it remains permanently available. Where an alternative trusted online repository is used, the files hosted should always be presented as read-only; please be aware that such usage risks compromising your anonymity during the review process if the repository contains any information that may enable the reviewer to identify you; as such, we recommend that all links to alternative repositories are reviewed carefully prior to submission. Please note that extensive supplementary material may be subject to peer review; this is at the discretion of the journal Editor and dependent on the content of the material (for example, whether including it would support the reviewer making a decision on the article during the peer review process).
	All references in your manuscript must be formatted using one of the recognised Harvard styles. You are welcome to use the Harvard style Emerald has adopted – we’ve provided a detailed guide below. Want to use a different Harvard style? That’s fine, our typesetters will make any necessary changes to your manuscript if it is accepted. Please ensure you check all your citations for completeness, accuracy and consistency. References to other publications in your text should be written as follows: , 2006) Please note, ‘ ' should always be written in italics. A few other style points. These apply to both the main body of text and your final list of references. At the end of your paper, please supply a reference list in alphabetical order using the style guidelines below. Where a DOI is available, this should be included at the end of the reference.
	Surname, initials (year),  , publisher, place of publication. e.g. Harrow, R. (2005),  , Simon & Schuster, New York, NY.
	Surname, initials (year), "chapter title", editor's surname, initials (Ed.), , publisher, place of publication, page numbers. e.g. Calabrese, F.A. (2005), "The early pathways: theory to practice – a continuum", Stankosky, M. (Ed.),  , Elsevier, New York, NY, pp.15-20.
	Surname, initials (year), "title of article",  , volume issue, page numbers. e.g. Capizzi, M.T. and Ferguson, R. (2005), "Loyalty trends for the twenty-first century",  , Vol. 22 No. 2, pp.72-80.
	Surname, initials (year of publication), "title of paper", in editor’s surname, initials (Ed.),  , publisher, place of publication, page numbers. e.g. Wilde, S. and Cox, C. (2008), “Principal factors contributing to the competitiveness of tourism destinations at varying stages of development”, in Richardson, S., Fredline, L., Patiar A., & Ternel, M. (Ed.s),  , Griffith University, Gold Coast, Qld, pp.115-118.
	Surname, initials (year), "title of paper", paper presented at [name of conference], [date of conference], [place of conference], available at: URL if freely available on the internet (accessed date). e.g. Aumueller, D. (2005), "Semantic authoring and retrieval within a wiki", paper presented at the European Semantic Web Conference (ESWC), 29 May-1 June, Heraklion, Crete, available at: http://dbs.uni-leipzig.de/file/aumueller05wiksar.pdf (accessed 20 February 2007).
	Surname, initials (year), "title of article", working paper [number if available], institution or organization, place of organization, date. e.g. Moizer, P. (2003), "How published academic research can inform policy decisions: the case of mandatory rotation of audit appointments", working paper, Leeds University Business School, University of Leeds, Leeds, 28 March.
	(year), "title of entry", volume, edition, title of encyclopaedia, publisher, place of publication, page numbers. e.g.   (1926), "Psychology of culture contact", Vol. 1, 13th ed., Encyclopaedia Britannica, London and New York, NY, pp.765-771. (for authored entries, please refer to book chapter guidelines above)
	Surname, initials (year), "article title",  , date, page numbers. e.g. Smith, A. (2008), "Money for old rope",  , 21 January, pp.1, 3-4.
	(year), "article title", date, page numbers. e.g.   (2008), "Small change", 2 February, p.7.
	Surname, initials (year), "title of document", unpublished manuscript, collection name, inventory record, name of archive, location of archive. e.g. Litman, S. (1902), "Mechanism & Technique of Commerce", unpublished manuscript, Simon Litman Papers, Record series 9/5/29 Box 3, University of Illinois Archives, Urbana-Champaign, IL.
	If available online, the full URL should be supplied at the end of the reference, as well as the date that the resource was accessed. Surname, initials (year), “title of electronic source”, available at: persistent URL (accessed date month year). e.g. Weida, S. and Stolley, K. (2013), “Developing strong thesis statements”, available at: https://owl.english.purdue.edu/owl/resource/588/1/ (accessed 20 June 2018) Standalone URLs, i.e. those without an author or date, should be included either inside parentheses within the main text, or preferably set as a note (Roman numeral within square brackets within text followed by the full URL address at the end of the paper).
	Surname, initials (year),  , name of data repository, available at: persistent URL, (accessed date month year). e.g. Campbell, A. and Kahn, R.L. (2015),  , ICPSR07218-v4, Inter-university Consortium for Political and Social Research (distributor), Ann Arbor, MI, available at: https://doi.org/10.3886/ICPSR07218.v4 (accessed 20 June 2018)

Submit your manuscript

There are a number of key steps you should follow to ensure a smooth and trouble-free submission.

Double check your manuscript

Before submitting your work, it is your responsibility to check that the manuscript is complete, grammatically correct, and without spelling or typographical errors. A few other important points:

• Give the journal aims and scope a final read. Is your manuscript definitely a good fit? If it isn’t, the editor may decline it without peer review.
• Does your manuscript comply with our research and publishing ethics guidelines ?
• Have you cleared any necessary publishing permissions ?
• Have you followed all the formatting requirements laid out in these author guidelines?
• If you need to refer to your own work, use wording such as ‘previous research has demonstrated’ not ‘our previous research has demonstrated’.
• If you need to refer to your own, currently unpublished work, don’t include this work in the reference list.
• Any acknowledgments or author biographies should be uploaded as separate files.
• Carry out a final check to ensure that no author names appear anywhere in the manuscript. This includes in figures or captions.

You will find a helpful submission checklist on the website Think.Check.Submit .

The submission process

All manuscripts should be submitted through our editorial system by the corresponding author.

The only way to submit to the journal is through the journal’s ScholarOne site as accessed via the Emerald website, and not by email or through any third-party agent/company, journal representative, or website. Submissions should be done directly by the author(s) through the ScholarOne site and not via a third-party proxy on their behalf.

A separate author account is required for each journal you submit to. If this is your first time submitting to this journal, please choose the Create an account or Register now option in the editorial system. If you already have an Emerald login, you are welcome to reuse the existing username and password here.

Please note, the next time you log into the system, you will be asked for your username. This will be the email address you entered when you set up your account.

Don't forget to add your  ORCiD ID during the submission process. It will be embedded in your published article, along with a link to the ORCiD registry allowing others to easily match you with your work.

Don’t have one yet? It only takes a few moments to register for a free ORCiD identifier .

Visit the ScholarOne support centre  for further help and guidance.

What you can expect next

You will receive an automated email from the journal editor, confirming your successful submission. It will provide you with a manuscript number, which will be used in all future correspondence about your submission. If you have any reason to suspect the confirmation email you receive might be fraudulent, please contact the journal editor in the first instance.

Post submission

Review and decision process.

Each submission is checked by the editor. At this stage, they may choose to decline or unsubmit your manuscript if it doesn’t fit the journal aims and scope, or they feel the language/manuscript quality is too low.

If they think it might be suitable for the publication, they will send it to at least two independent referees for double anonymous peer review.  Once these reviewers have provided their feedback, the editor may decide to accept your manuscript, request minor or major revisions, or decline your work.

This journal offers an article transfer service. If the editor decides to decline your manuscript, either before or after peer review, they may offer to transfer it to a more relevant Emerald journal in this field. If you accept, your ScholarOne author account, and the accounts of your co-authors, will automatically transfer to the new journal, along with your manuscript and any accompanying peer review reports. However, you will still need to log in to ScholarOne to complete the submission process using your existing username and password. While accepting a transfer does not guarantee the receiving journal will publish your work, an editor will only suggest a transfer if they feel your article is a good fit with the new title.

While all journals work to different timescales, the goal is that the editor will inform you of their first decision within 60 days.

During this period, we will send you automated updates on the progress of your manuscript via our submission system, or you can log in to check on the current status of your paper.  Each time we contact you, we will quote the manuscript number you were given at the point of submission. If you receive an email that does not match these criteria, it could be fraudulent and we recommend you contact the journal editor in the first instance.

Manuscript transfer service

Emerald’s manuscript transfer service takes the pain out of the submission process if your manuscript doesn’t fit your initial journal choice. Our team of expert Editors from participating journals work together to identify alternative journals that better align with your research, ensuring your work finds the ideal publication home it deserves. Our dedicated team is committed to supporting authors like you in finding the right home for your research.

If a journal is participating in the manuscript transfer program, the Editor has the option to recommend your paper for transfer. If a transfer decision is made by the Editor, you will receive an email with the details of the recommended journal and the option to accept or reject the transfer. It’s always down to you as the author to decide if you’d like to accept. If you do accept, your paper and any reviewer reports will automatically be transferred to the recommended journals. Authors will then confirm resubmissions in the new journal’s ScholarOne system.

Our Manuscript Transfer Service page has more information on the process.

If your submission is accepted

Open access.

Once your paper is accepted, you will have the opportunity to indicate whether you would like to publish your paper via the gold open access route.

If you’ve chosen to publish gold open access, this is the point you will be asked to pay the APC (article processing charge).  This varies per journal and can be found on our APC price list or on the editorial system at the point of submission. Your article will be published with a Creative Commons CC BY 4.0 user licence , which outlines how readers can reuse your work.

For UK journal article authors - if you wish to submit your work accepted by Emerald to REF 2021, you must make a ‘closed deposit’ of your accepted manuscript to your respective institutional repository upon acceptance of your article. Articles accepted for publication after 1st April 2018 should be deposited as soon as possible, but no later than three months after the acceptance date. For further information and guidance, please refer to the REF 2021 website.

All accepted authors are sent an email with a link to a licence form.  This should be checked for accuracy, for example whether contact and affiliation details are up to date and your name is spelled correctly, and then returned to us electronically. If there is a reason why you can’t assign copyright to us, you should discuss this with your journal content editor. You will find their contact details on the editorial team section above.

Proofing and typesetting

Once we have received your completed licence form, the article will pass directly into the production process. We will carry out editorial checks, copyediting, and typesetting and then return proofs to you (if you are the corresponding author) for your review. This is your opportunity to correct any typographical errors, grammatical errors or incorrect author details. We can’t accept requests to rewrite texts at this stage.

When the page proofs are finalised, the fully typeset and proofed version of record is published online. This is referred to as the EarlyCite version. While an EarlyCite article has yet to be assigned to a volume or issue, it does have a digital object identifier (DOI) and is fully citable. It will be compiled into an issue according to the journal’s issue schedule, with papers being added by chronological date of publication.

How to share your paper

Visit our author rights page  to find out how you can reuse and share your work.

To find tips on increasing the visibility of your published paper, read about  how to promote your work .

Correcting inaccuracies in your published paper

Sometimes errors are made during the research, writing and publishing processes. When these issues arise, we have the option of withdrawing the paper or introducing a correction notice. Find out more about our  article withdrawal and correction policies .

Need to make a change to the author list? See our frequently asked questions (FAQs) below.

Frequently asked questions

	The only time we will ever ask you for money to publish in an Emerald journal is if you have chosen to publish via the gold open access route. You will be asked to pay an APC (article-processing charge) once your paper has been accepted (unless it is a sponsored open access journal), and never at submission. At no other time will you be asked to contribute financially towards your article’s publication, processing, or review. If you haven’t chosen gold open access and you receive an email that appears to be from Emerald, the journal, or a third party, asking you for payment to publish, please contact our support team via .
	Please contact the editor for the journal, with a copy of your CV. You will find their contact details on the editorial team tab on this page.
	Typically, papers are added to an issue according to their date of publication. If you would like to know in advance which issue your paper will appear in, please contact the content editor of the journal. You will find their contact details on the editorial team tab on this page. Once your paper has been published in an issue, you will be notified by email.
	Please email the journal editor – you will find their contact details on the editorial team tab on this page. If you ever suspect an email you’ve received from Emerald might not be genuine, you are welcome to verify it with the content editor for the journal, whose contact details can be found on the editorial team tab on this page.
	If you’ve read the aims and scope on the journal landing page and are still unsure whether your paper is suitable for the journal, please email the editor and include your paper's title and structured abstract. They will be able to advise on your manuscript’s suitability. You will find their contact details on the Editorial team tab on this page.
	Authorship and the order in which the authors are listed on the paper should be agreed prior to submission. We have a right first time policy on this and no changes can be made to the list once submitted. If you have made an error in the submission process, please email the Journal Editorial Office who will look into your request – you will find their contact details on the editorial team tab on this page.

Editor-in-Chief

• Professor Sujeet Sharma Decision Science & Information Systems Area, Indian Institute of Management Nagpur - India [email protected]

Associate Editors

• Professor Yukun Bao Huazhong University of Science and Technology - People's Republic of China
• Professor Amir H. Gandomi University of Technology Sydney - Australia
• Associate Professor Zhongyi Hu Wuhan University - People's Republic of China
• Associate Professor Biju Issac Northumbria University - UK
• Professor Heikki Karjaluoto University of Jyväskylä - Finland
• Professor Monica Lam University of Central Oklahoma - USA
• Associate Professor Rohaya Latip Universiti Putra Malaysia - Malaysia
• Associate Professor Syed Nasirin Universiti Malaysia Sabah - Malaysia
• Associate Professor Fernando Rubio Universidad Complutense de Madrid - Spain
• Professor Rosemary Stockdale Griffith University - Australia

Editorial Assistant

• Dr Abdullah I Aldarazi Institute of Public Administration - Saudi Arabia

Commissioning Editor

• Paul Kidd Emerald Publishing - UK [email protected]

Journal Editorial Office (For queries related to pre-acceptance)

• Gauri Naik Emerald Publishing [email protected]

Supplier Project Manager (For queries related to post-acceptance)

• Aarti Kakade Emerald Publishing [email protected]

Editorial Advisory Board

• Professor Richard Baskerville CIS Department, Georgia State University - USA
• Professor Paul Beynon-Davies Cardiff University - UK
• Dr. Helen Cripps School of Marketing, Edith Cowan University - Australia
• Professor Helene Delerue University of Québec at Montréal - Canada
• Professor Bill Doolin Faculty of Business, Auckland University of Technology - New Zealand
• Professor Joey F. George Iowa State University - USA
• Professor Paul Jones Swansea University - UK
• Professor Ned Florencio Kock Division of International Business and Technology Studies, Texas A&M International University - USA
• Professor Michael Kyobe University of Cape Town - South Africa
• Dr Linda S. L. Lai Macau Polytechnic University of China - People's Republic of China
• Professor Michael Myers University of Auckland Business School - New Zealand
• Professor Thomas Schildhauer Insitute of Electronic Business e.V., an affiliated institute of the University of Arts Berlin - Germany
• Professor Craig Standing School of Management, Edith Cowan University - Australia

Citation metrics

CiteScore 2023

Further information

CiteScore is a simple way of measuring the citation impact of sources, such as journals.

Calculating the CiteScore is based on the number of citations to documents (articles, reviews, conference papers, book chapters, and data papers) by a journal over four years, divided by the number of the same document types indexed in Scopus and published in those same four years.

For more information and methodology visit the Scopus definition

CiteScore Tracker 2024

(updated monthly)

CiteScore Tracker is calculated in the same way as CiteScore, but for the current year rather than previous, complete years.

The CiteScore Tracker calculation is updated every month, as a current indication of a title's performance.

Publication timeline

Time to first decision

Time to first decision , expressed in days, the "first decision" occurs when the journal’s editorial team reviews the peer reviewers’ comments and recommendations. Based on this feedback, they decide whether to accept, reject, or request revisions for the manuscript.

Data is taken from submissions between 1st June 2023 and 31st May 2024

Acceptance to publication

Acceptance to publication , expressed in days, is the average time between when the journal’s editorial team decide whether to accept, reject, or request revisions for the manuscript and the date of publication in the journal. 

Data is taken from the previous 12 months (Last updated July 2024)

Acceptance rate

The acceptance rate is a measurement of how many manuscripts a journal accepts for publication compared to the total number of manuscripts submitted expressed as a percentage %

Data is taken from submissions between 1st June 2023 and 31st May 2024 .

This figure is the total amount of downloads for all articles published early cite in the last 12 months

(Last updated: July 2024)

This journal is abstracted and indexed by

• dblp Computer Science Bibliography
• Norwegian Scientific Index
• ReadCube Discover

This journal is ranked by

• Australian Business Deans Council (B)
• Australian Council of Professors and Heads of Information Systems (C)
• Computing Research & Education (CORE) Journal Ranking (C)
• The Chartered Association of Business Schools' Academic Journal Guide (1)
• EI Compendex
• The Publication Forum (Finland)

Reviewer information

Peer review process.

This journal engages in a double-anonymous peer review process, which strives to match the expertise of a reviewer with the submitted manuscript. Reviews are completed with evidence of thoughtful engagement with the manuscript, provide constructive feedback, and add value to the overall knowledge and information presented in the manuscript.

The mission of the peer review process is to achieve excellence and rigour in scholarly publications and research.

Our vision is to give voice to professionals in the subject area who contribute unique and diverse scholarly perspectives to the field.

The journal values diverse perspectives from the field and reviewers who provide critical, constructive, and respectful feedback to authors. Reviewers come from a variety of organizations, careers, and backgrounds from around the world.

All invitations to review, abstracts, manuscripts, and reviews should be kept confidential. Reviewers must not share their review or information about the review process with anyone without the agreement of the editors and authors involved, even after publication. This also applies to other reviewers’ “comments to author” which are shared with you on decision.

Resources to guide you through the review process

Discover practical tips and guidance on all aspects of peer review in our reviewers' section. See how being a reviewer could benefit your career, and discover what's involved in shaping a review.

More reviewer information

Thank you to the 2023 Reviewers

The publishing and editorial teams would like to thank the following, for their invaluable service as 2023 reviewers for this journal. We are very grateful for the contributions made. With their help, the journal has been able to publish such high...

Editorship Opportunity: Journal of Systems and Information Technology

Emerald Publishing invites applications for the position of Editor-in-Chief of the Journal of Systems and Information Technology (JSIT).  Journal Scope The Journal provides an avenue for scholarly work t...

Literati awards

Journal of Systems and Information Technology - Literati Award Winners 2020

We are pleased to announce our 2020 Literati Award winners. Outstanding Paper A two-stage structural equation modeling-neural netwo...

The Journal of Systems and Information Technology provides an avenue for scholarly work focusing on applications of information technology, systems thinking and information analytics to research problems in built, business, cultural and natural environments.

Aims and scope

The Journal provides an avenue for scholarly work that researches systems thinking applications, information systems, electronic business, data analytics, information sciences, information management, business intelligence, and complex adaptive systems in the application domains of the business environment, health, the built environment, cultural settings, and the natural environment. Papers examine the wider implications of the systems or technology being researched. This means papers consider aspects such as social and organisational relevance, business value, cognitive implications, social implications, impact on individuals or community perspectives, and the development of solutions, rather than focusing solely on the technology.

The Journal of Systems and Information Technology is open to a wide range of research methodologies and paper styles including case studies, surveys, experiments, review papers, design science, design thinking and both theoretical and methodological papers. 

The focus of the journal will be to publish work that fits into the following broad areas of research:

• Behavioural Information Systems and Human-Computer Interaction
• Data Analytics
• Data, Information and Security
• Intelligent Systems and Applications
• Logistics and Supply Chain Management/Optimisation
• Social Media Analysis
• Technology Enhanced Learning

Latest articles

These are the latest articles published in this journal (Last updated: July 2024 )

Enterprise social media to foster digital maturity: a value creation perspective

The use of enterprise social networks for knowledge sharing: the impact of intra-organizational trust and governance, behavioral responses resulting from e-health services and the role of user satisfaction: the case of the online diabetes test, top downloaded articles.

These are the most downloaded articles over the last 12 months for this journal (Last updated: July 2024 )

Revisiting perceived gratification, consumer attitudes, and purchase impulses in cross-border e-commerce live streaming: a direct and indirect effects model

The influence of emotions on online information sharing behavior, determinants of continuous intention to use e-government services: an extension of technology continuance theory.

These are the top cited articles for this journal, from the last 12 months according to Crossref (Last updated: July 2024 )

Machine learning for sustainable development: leveraging technology for a greener future

Understanding the impact of technological flexibility at different decision levels to reap enterprise resource planning benefits.

This title is aligned with our responsible management goal

We aim to champion researchers, practitioners, policymakers and organisations who share our goals of contributing to a more ethical, responsible and sustainable way of working.

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Numbers, Facts and Trends Shaping Your World

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Internet & Technology

Why many parents and teens think it’s harder being a teen today.

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Many Israelis say social media content about the Israel-Hamas war should be censored

About half of tiktok users under 30 say they use it to keep up with politics, news, 72% of u.s. high school teachers say cellphone distraction is a major problem in the classroom, sign up for our internet, science, and tech newsletter.

New findings, delivered monthly

Support for a U.S. TikTok ban continues to decline, and half of adults doubt it will happen

The share of Americans who support the U.S. government banning TikTok now stands at 32%, down from 38% in fall 2023 and 50% in March 2023.

Most Israeli adults do not post or share about political and social issues online – including the war between Israel and Hamas.

TikTok users under 30 see its impact on democracy more positively than older users, with 45% of this group saying it’s mostly good for American democracy.

Some 72% of high school teachers say that students being distracted by cellphones is a major problem in their classroom.

How Americans Navigate Politics on TikTok, X, Facebook and Instagram

X stands out as a place people go to keep up with politics. Still, some users see political posts on Facebook, TikTok and Instagram, too.

How Americans Get News on TikTok, X, Facebook and Instagram

X is still more of a news destination than these other platforms, but the vast majority of users on all four see news-related content.

Electric Vehicle Charging Infrastructure in the U.S.

64% of Americans live within 2 miles of a public electric vehicle charging station, and those who live closest to chargers view EVs more positively.

When Online Content Disappears

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A quarter of U.S. teachers say AI tools do more harm than good in K-12 education

High school teachers are more likely than elementary and middle school teachers to hold negative views about AI tools in education.

REFINE YOUR SELECTION

Research teams, signature reports.

The State of Online Harassment

Roughly four-in-ten Americans have experienced online harassment, with half of this group citing politics as the reason they think they were targeted. Growing shares face more severe online abuse such as sexual harassment or stalking

Parenting Children in the Age of Screens

Two-thirds of parents in the U.S. say parenting is harder today than it was 20 years ago, with many citing technologies – like social media or smartphones – as a reason.

Dating and Relationships in the Digital Age

From distractions to jealousy, how Americans navigate cellphones and social media in their romantic relationships.

Americans and Privacy: Concerned, Confused and Feeling Lack of Control Over Their Personal Information

Majorities of U.S. adults believe their personal data is less secure now, that data collection poses more risks than benefits, and that it is not possible to go through daily life without being tracked.

Americans and ‘Cancel Culture’: Where Some See Calls for Accountability, Others See Censorship, Punishment

Social media fact sheet, digital knowledge quiz, video: how do americans define online harassment.

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Chemistry Education Research and Practice

The use of mobile technology in abductive inquiry-based teaching and learning of chemical bonding.

Continuous enhancement of mobile devices such as smartphones offer new opportunities for using these technologies in inquiry-based learning environments. Inquiry-based learning has followed deductive and inductive forms of inquiry, while the abductive form of inquiry that target the development of higher-order thinking skills such as critical thinking are less prevalent. This study investigated the use of mobile technology in abductive-inquiry based teaching and learning of chemical bonding for grade 11 physical sciences learners in two South African schools. The study employed an explanatory sequential mixed-methods design that entailed first collecting quantitative data and then qualitative data to help explain or elaborate on the quantitative results. Two grade 11 Physical Sciences classes were randomly designated as the experimental and control groups in each of the two different schools. The experimental group in each school experienced activities in a laboratory using mobile technology-enhanced abductive scientific inquiry through the ‘Molecular Workbench’ web-based simulation using a mobile device, while the control group in each school experienced activities in abductive scientific inquiry in a science laboratory without using mobile learning technology. The principal findings indicated that learners within the control group displayed a significant increase in their performance to create a scientifically accurate hypothesis that is the essence of abductive inquiry, whereas for the experimental group there was no significant improvement in their hypothesis generation capacity. However, participants within the experimental group felt that their use of mobile devices created a sense of learner agency amongst themselves, developed their communication skills, made them feel responsible for their own learning, and also made learning scientific concepts more fun as opposed to what they are normally exposed to.

Article information

Download citation, permissions.

J. Dunn and U. D. Ramnarain, Chem. Educ. Res. Pract. , 2024, Accepted Manuscript , DOI: 10.1039/D3RP00314K

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2024 Recipients of the Wolfe Fellowship

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The Faculty of Arts is pleased to announce that six PhD candidates have been awarded the 2024 Wolfe Fellowship.

The Wolfe Chair in Scientific and Technological Literacy supports the Wolfe Graduate Fellowship for McGill graduate students in the Faculty of Arts. The Fellowship supports the research of PhD candidates whose thesis work reflects the themes of the Chair, whose mandate is to conduct research, teach, and perform public outreach regarding the intellectual foundations, nature and methods of scientific and technological innovation and to provide support to well-rounded students capable of making constructive contributions to debates surrounding science, technology, and society.

Congratulations to all of this year’s recipients.

Discover the 2024 cohort of Wolfe Fellows

Discover the 2024 Wolfe Fellows

Name	Department:	Thesis subject/title *:
	Communication Studies	“Psychoanalysis for a Blue Humanities.”
	Art History and Communication Studies	“Long Time, First Time: A History of Call-In Radio in the United States and Canada 1945-1975.”
Jay Ritchie	English	Intermedia and the effects of digitality on poetic production, circulation, and reception from 1970 to 2020
	Anthropology	Temporary marriage among disadvantaged women in Iran
	Communication Studies
	School of Information Studies	Technologies to better support the interrelated needs of older adults living alone for physical activity.

* title mentioned where specified on the Wolfe webpage.

Emma Blackett (she/they), is a PhD candidate in Communication Studies whose work is informed by queer/feminist studies, psychoanalytic theory, film studies, and ecocriticism. Her dissertation, “Psychoanalysis for a Blue Humanities”, offers a critique of environmental subjectivity, taking as its premise the failure of public communications about ecological collapse to provoke action adequate to halting it.

Sadie Couture is a PhD candidate in the Department of Art History and Communication Studies at McGill University working at the intersection of media history, sound studies, and science and technology studies. During her tenure as a Wolfe Fellow, she will be working on my dissertation project, entitled “Long Time, First Time: A History of Call-In Radio in the United States and Canada 1945-1975” which focuses on the origins, development, and conventionalization of call-in radio and traces how technologies, policies, economies, and cultural desires impacted the format and pummeled it—imperfectly—into the shape it is today. Calling-in—using a telephone to connect to a radio station and subsequently be broadcast live—is simultaneously a technical process, a feedback system, satisfies the ‘public good’ criterion of many regulatory regimes, offers an additional way to shape an audience, and generates cheap, usable content.

Jay Ritchie, is a PhD candidate in the Department of English. His SSHRC CGS-funded doctoral research examines how poets created what Fluxus artist Dick Higgins called “intermedia” art, where two or more different artistic media are combined to create an artwork both between and beyond the artwork’s component media. Situating the turn towards intermedia in the context of the emergence of digital technology, his research examines the effects of digitality on poetic production, circulation, and reception from 1970 to 2020.

“Apart from providing vital, sustaining support for research and dissertation writing in the final year of my PhD, the Wolfe Fellowship allows me to attend conferences on digital media, the digital humanities, and science and technology more broadly,” says Jay. “The opportunity to share the research I have conducted while supported by the fellowship and to learn from other academics deepens my intellectual engagement with science and technology in the arts.”

Maryam Roosta , is a PhD candidate in the department of Anthropology at McGill University. Her doctoral dissertation is focused on the practice of temporary marriage among disadvantaged women in Iran. In Twelver Shi’a Islam, temporary marriage or mut’ah is a contract lasting anywhere from an hour to 99 years between a man and an unmarried woman. While mut’ah has traditionally been an urban phenomenon, the introduction of internet has reshaped the social arrangements between men and women who intend to contract mut’ah. Maryam’s research shows that to better understand the boundaries between mut’ah and transactional intimate relations is necessary to attend to the ways in which digital technologies such as the internet both enable and constrain women in contracting such relationships. In addition to Wolfe fellowship, her doctoral research is supported by the Fonds de Recherche du Québec - Société et Culture (FRQSC) and Wenner-Gren foundation.

Mehak Sawhney (she/her) is a PhD candidate and Vanier Canada Graduate Scholar in Communication Studies at McGill University. Her doctoral project titled Audible Waters: Sounding and Surveilling the Indian Ocean traces the production of oceanic territory through underwater sonic technologies in postcolonial India and the subcontinental Indian Ocean. Through a focus on hydrography, military security, conservation, and resource extraction, the project explores the politics of underwater monitoring technologies such as sonars as well as scientific disciplines such as underwater acoustics and bioacoustics. In so doing the project offers media theoretical reflections on the idea of the planetary, ongoing submarine colonialisms, and geopolitically situated ways to think about the relationship between sound, media and the environment.

“The Wolfe fellowship will support me in completing my dissertation as a final year PhD candidate at McGill,” says Mehak. “My dissertation titled Audible Waters: Sounding and Surveilling the Indian Ocean focuses on the production of oceanic territory through underwater sonic technologies in postcolonial India and the subcontinental Indian Ocean. It is based on ethnographic and archival research in India and the US. The fellowship will be very helpful in supporting my work and stay for the next academic session as an international student in Canada.”

Muhe Yang is a PhD candidate in the School of Information Studies at McGill University. Her doctoral research investigates how to design technologies to better support the interrelated needs of older adults living alone for physical activity. Older adults engage in physical activity for myriad purposes, including health benefits, associated sensory pleasures, and increased opportunities of socializing. Yet, older adults, especially those living alone, often encounter various barriers to maintaining their exercise routines, contributing to inactivity and falling short of recommended physical activity levels. Those barriers, including health problems, lack of motivation and social support, lack of exercise resources, not only span across individual, social, and environmental levels but also are often interrelated, as revealed in Muhe’s research findings to date.

For more information on the Wolfe Fellows please visit the Wolfe Fellowship homepage . 

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AI in prostate MRI: enhancing accuracy and reducing overdiagnosis

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