E-inclusion: Beyond individual socio-demographic characteristics

Abstract

The changing demographic structure of the population, resulting in unparalleled growth of the elderly population, means that e-inclusion of this population group is considered to be a social and political priority in the context of the Information Society. Most research studies have only considered individual variables -such as age, gender, education, income and health- in the explanatory models of e-inclusion of senior citizens, while ignoring macro variables, such as the welfare systems and public policies in each country. Simultaneously, most studies focus on small-scale samples, lack international comparisons and do not consider the combined effect of several variables that influence Internet use. This study aims to analyse possible differences between two countries that have different welfare systems and public policies, after controlling for the effects of the individual variables that have been identified in the literature as relevant for Internet use. The study focuses on a sample of 8639 individuals, aged 50 years and over, residing in Portugal and Estonia, who participated in the SHARE project (Survey of Health, Ageing and Retirement in Europe). The results of the logistic regression analysis demonstrate that welfare systems and public policies have an impact on the likelihood of Internet use, thus reinforcing the importance of developing public policies to foster e-inclusion of senior citizens.

Integrated Care Programs for People with Multimorbidity in European Countries: eHealth Adoption in Health Systems

“…The authors partially adapted part of the text from their own previous publication concerning the same main ICARE4EU Study, with appropriate attribution (Melchiorre MG et al, eHealth in integrated care programs for people with multimorbidity in Europe: Insights from the ICARE4EU project. Health Policy, 2018;122(1): [53][54][55][56][57][58][59][60][61][62][63]. The adapted text refers to some brief parts of general sociodemographic information of the sample population, some/few general Results, Methods (as well established protocols), and Limitations.…”

“…Furthermore, different types of MM care practices may also be found in centralized and decentralized health systems [52]. Some authors also report that inequalities in ICT use are related not only to inequalities in individual social structures (e.g., sociodemographic, economic, and health variables) but also to macrosocial variables and welfare systems, e.g., economic, political, and social characteristics and public policies of the respective countries [58,59].…”

Revolución digital en salud: ¿están los pacientes con accidente cerebrovascular preparados?

“…El presente estudio muestra que, si bien un alto porcentaje de los pacientes evaluados tenía acceso a internet (74,8%), solo 28,8% de ellos lo sabía usar. Es posible que esto se deba a las características sociodemográficas de la población, donde la edad, la escolaridad y el nivel de ingresos tienen un impacto significativo en la probabilidad de usar o no internet, apoyando la evidencia disponible 2,3,5,8,9,15,16 .…”

“…En Chile, el estudio realizado por la Fundación País Digital identifica 4 factores que afectan el uso de internet: el nivel de ingresos, la edad, la escolaridad y la ruralidad 2 . Por otra parte, esta brecha puede ser aun mayor en personas con discapacidad, ya que alteraciones sensoriales, cognitivas y motoras también podrían afectar el acceso y uso de las TIC [9][10][11] .…”

Relative Influence of Diversified Factors on the Living Standard of Farmers in Pakistan: A Multivariate Analysis

“…Above all stated information and communication technologies has reshapes our diurnal lives, obscuring the edge among home-grown and the globe, in spite of promoting access to knowledge-based information and disseminating ideas and ethics [31]. In addition, ICTs has modified the people communication mode and the way wherein they build their social systems [32].…”