Western Digital

R. Houghton, O. E. Sawy, P. Gray, C. Donegan, A. Joshi

Max J. Western, E. S. Smit, T. Gültzow, E. Neter, F. Sniehotta, Olivia S Malkowski, Charlene Wright, H. Busse, Carmen Peuters, L. Rehackova, Angelo Gabriel Oteșanu, B. Ainsworth, C. Jones, Michael Kilb, A.M. Rodrigues, O. Perski, Alison J. Wright, L. König

ABSTRACT Background: Digital health interventions have the potential to improve health at a large scale globally by improving access to healthcare services and health-related information, but they tend to benefit more affluent and privileged groups more than those less privileged. Methods: In this narrative review, we describe how this ‘digital health divide’ can manifest across three different levels reflecting inequalities in access, skills and benefits or outcomes (i.e. the first, second, and tertiary digital divide). We also discuss four key causes of this digital divide: (i)) digital health literacy as a fundamental determinant; (ii) other personal, social, community, and societal level determinants; (iii) how technology and intervention development contribute to; and (iv) how current research practice exacerbates the digital health divide by developing a biased evidence base. Finally, we formulate implications for research, policy, and practice. Results: Specific recommendations for research include to keep digital health interventions and measurement instruments up to date with fastpaced technological changes, and to involve diverse populations in digital intervention development and evaluation research. For policy and practice, examples of recommendations are to insist on inclusive and accessible design of health technology and to ensure support for digital health intervention enactment prioritises those most vulnerable to the digital divide. Conclusion: We conclude by highlighting the importance of addressing the digital health divide to ensure that as digital technologies' inevitable presence grows, it does not leave those who could benefit most from innovative health technology behind.

Xiaying Feng, Xiaoya Ma, Jianbo Lu, Qingyan Tang, Zihan Chen

Jing Liu, C. Puah, M. Arip, Meng-Chang Jong

This study aims to investigate the influence of digital financial inclusion on China’s urban–rural income disparity. A comparative analysis on income differences between western and eastern regions in China was conducted in this paper. The study utilized a static panel approach as it consisted of 22 provinces in China that covered the period from 2011 to 2020. This paper employs Stata software for the data analysis. The dependent variable of this study is the urban–rural income gap. Meanwhile, the independent variables consist of the total index level, breadth of coverage, depth of use, degree of digitization, digital payment level, digital insurance level, and digital credit level. The control variables employed in this article are education level, financial support, economic transformation, technological progress, and trade openness. The empirical outcomes indicate that the seven independent variables potentially minimize the urban–rural income gap between the two regions. However, digital financial inclusion appears to have a more significant effect in lessening the urban–rural gap in the western region compared to the eastern region in China. The findings demonstrate that all the variables exhibit a higher degree of influence on the urban–rural income differences in the west than in the east, except for the credit index. The outcome reveals that the effect of the credit index in the western region (0.10%) is slightly lower than the eastern region (0.11%). In general, the present findings can provide valuable insights for policy makers in their efforts to address the urban–rural income gap in the two regions through the implementation of digital financial inclusion initiatives. The study should be conducted regularly to observe the trend of the income disparities between the western and eastern regions in China. Future studies can also focus on other regions or narrow the focus to provincial and city levels to capture more detailed information.

L. Wai, Winai Wongsurawat