Ángel Díaz-Chao

Modelling and predicting eHealth usage in Europe: A multidimensional approach from an online survey of 13,000 European Union Internet users

Background More advanced methods and models are needed to evaluate the participation of patients and citizens in the shared health care model that eHealth proposes. Objective The goal of our study was to design and evaluate a predictive multidimensional model of eHealth usage. Methods We used 2011 survey data from a sample of 13,000 European citizens aged 16–74 years who had used the Internet in the previous 3 months. We proposed and tested an eHealth usage composite indicator through 2-stage structural equation modelling with latent variables and measurement errors. Logistic regression (odds ratios, ORs) to model the predictors of eHealth usage was calculated using health status and sociodemographic independent variables. Results The dimensions with more explanatory power of eHealth usage were health Internet attitudes, information health Internet usage, empowerment of health Internet users, and the usefulness of health Internet usage. Some 52.39% (6811/13,000) of European Internet users’ eHealth usage was more intensive (greater than the mean). Users with long-term health problems or illnesses (OR 1.20, 95% CI 1.12–1.29) or receiving long-term treatment (OR 1.11, 95% CI 1.03–1.20), having family members with long-term health problems or illnesses (OR 1.44, 95% CI 1.34–1.55), or undertaking care activities for other people (OR 1.58, 95% CI 1.40–1.77) had a high propensity toward intensive eHealth usage. Sociodemographic predictors showed that Internet users who were female (OR 1.23, 95% CI 1.14–1.31), aged 25–54 years (OR 1.12, 95% CI 1.05–1.21), living in larger households (3 members: OR 1.25, 95% CI 1.15–1.36; 5 members: OR 1.13, 95% CI 0.97–1.28; ≥6 members: OR 1.31, 95% CI 1.10–1.57), had more children <16 years of age (1 child: OR 1.29, 95% CI 1.18–1.14; 2 children: OR 1.05, 95% CI 0.94–1.17; 4 children: OR 1.35, 95% CI 0.88–2.08), and had more family members >65 years of age (1 member: OR 1.33, 95% CI 1.18–1.50; ≥4 members: OR 1.82, 95% CI 0.54–6.03) had a greater propensity toward intensive eHealth usage. Likewise, users residing in densely populated areas, such as cities and large towns (OR 1.17, 95% CI 1.09–1.25), also had a greater propensity toward intensive eHealth usage. Educational levels presented an inverted U shape in relation to intensive eHealth usage, with greater propensities among those with a secondary education (OR 1.08, 95% CI 1.01–1.16). Finally, occupational categories and net monthly income data suggest a higher propensity among the employed or self-employed (OR 1.07, 95% CI 0.99–1.15) and among the minimum wage stratum, earning ≤€1000 per month (OR 1.66, 95% CI 1.48–1.87). Conclusions We provide new evidence of inequalities that explain intensive eHealth usage. The results highlight the need to develop more specific eHealth practices to address different realities.

Information and Communication Technologies, Innovation, and Firm Productivity in Small and Medium-Sized Travel Agencies New Evidence from Spain

This article analyzes new co-innovative sources of firm labor productivity. Using survey data for 120 small and medium-sized travel agencies based in Catalonia (a region in the northeast of Spain) and partial least square–structural equation modeling (PLS-SEM) estimation techniques, three main findings emerged from the study. First, labor productivity is directly explained by those agencies’ capacity to exploit their assets, to use local networks, and to make international transactions. Second, the analysis of indirect effects on labor productivity suggests a circular causality, which is determined by the influence of the workers’ local network use on a firm’s export capacity. In this circular relationship, a firm’s capacity to generate market-leading product innovations and the stock of human capital and training play a decisive role. Third, co-innovation practices exert a negative effect, which may be related to difficulties in terms of securing productivity improvements in the short term.

A Measurement for the Evolution of Renewable Energies: The Case of the European Union

When it comes to the construction of an index, one of the main problems is determining the weights that each variable carries. In this article, through models based on the Structural Equation Modelling methodology, an index for the measurement of the evolution of renewable energies is developed, and applied for a group of countries in the European Union. The results show that, in Europe, there are two groups clearly differentiated in terms of their level of development in renewable energy. In the first group, Germany, Spain, France, and Italy stand out while the second group is led by the United Kingdom, and includes countries like Portugal, Finland, and Greece.

Modeling The Relationship Between Industrial Employment And Information And Communication Technologies

In this paper, we develop a model to measure the effects of Information and Communication Technologies (ICT) on the labor market, aiming to settle down its net effect on employment creation. The main findings are: 1) Related with the sector services, where the regions with worse evolution of the industrial employment showed growth in the information society sector services, being it intensive in technology, and a certain negative incidence employment growth in the sector services in general and in the industrial one, 2) Related with the ICT, where two variables have a negative effect on the employment growth: the extranet and the own wireless net. This negative incidence has its base on the positive relationship between productivity and technology. This way, the ICT integration into the industry causes smaller new workers needs. 3) A second group of estimates highlights some of the factors that have influenced the recent industry evolution. The most prominent effect is the incidence of the ICT on the added value. The regions where there is more penetration of the ICT are the ones having bigger industry relevance in the Spanish economy. 4) In addition, the difficulties to find ICT skilled workers specialist is a factor that hinders the added value growth. These results reveal the need of a public policy favoring the skilled labor and the company’s technological advances. The conjunction of both factors will improve the industry long-term benefits. 5) A last effects group reveals that regions with bigger industrial production growth have also a bigger growth of the employment in the services sector.

Modeling and Predicting Outcomes of eHealth Usage by European Physicians: Multidimensional Approach from a Survey of 9196 General Practitioners

Background The literature has noted the need to use more advanced methods and models to evaluate physicians’ outcomes in the shared health care model that electronic health (eHealth) proposes. Objective The goal of our study was to design and evaluate a predictive multidimensional model of the outcomes of eHealth usage by European physicians. Methods We used 2012-2013 survey data from a sample of 9196 European physicians (general practitioners). We proposed and tested two composite indicators of eHealth usage outcomes (internal practices and practices with patients) through 2-stage structural equation modeling. Logistic regression (odds ratios, ORs) to model the predictors of eHealth usage outcomes indicators were also calculated. Results European general practitioners who were female (internal practices OR 1.15, 95% CI 1.10-1.20; practices with patients OR 1.19, 95% CI 1.14-1.24) and younger—aged <35 years (internal practices OR 1.14, 95% CI 1.02-1.26; practices with patients OR 1.32, 95% CI 1.13-1.54) and aged 36-45 years (internal practices OR 1.16, 95% CI 1.06-1.28; practices with patients OR 1.21, 95% CI 1.10-1.33)—had a greater propensity toward favorable eHealth usage outcomes in internal practices and practices with patients. European general practitioners who positively valued information and communication technology (ICT) impact on their personal working processes (internal practices OR 5.30, 95% CI 4.73-5.93; practices with patients OR 4.83, 95% CI 4.32-5.40), teamwork processes (internal practices OR 4.19, 95% CI 3.78-4.65; practices with patients OR 3.38, 95% CI 3.05-3.74), and the doctor-patient relationship (internal practices OR 3.97, 95% CI 3.60-4.37; practices with patients OR 6.02, 95% CI 5.43-6.67) had a high propensity toward favorable effects of eHealth usage on internal practices and practices with patients. More favorable eHealth outcomes were also observed for self-employed European general practitioners (internal practices OR 1.33, 95% CI 1.22-1.45; practices with patients OR 1.10, 95% CI 1.03-1.28). Finally, general practitioners who reported that the number of patients treated in the last 2 years had remained constant (internal practices OR 1.08, 95% CI 1.01-1.17) or increased (practices with patients OR 1.12, 95% CI 1.03-1.22) had a higher propensity toward favorable eHealth usage outcomes. Conclusions We provide new evidence of predictors (sociodemographic issues, attitudes toward ICT impacts, and working conditions) that explain favorable eHealth usage outcomes. The results highlight the need to develop more specific policies for eHealth usage to address different realities.

gender inequalities in job quality during the recession

Purpose This article empirically analyses gender differences in job quality during the first years of the economic crisis in Spain. Design/methodology/approach The article use microdata from the Quality of Working Life Survey. A representative sample of 5,381 and 4,925 Spanish employees (men and women) in 2008 and 2010, and a two-stage Structural Equation Modelling (SEM) are empirically tested. Findings The study revealed three main results. First, the improvement in job quality was more favorable to men than it was to women. Second, the gender differences in the explanation of job quality increased considerably in favor of men. Third, this increase in gender-related job inequality in favor of men is explained by a worsening of 4 of the 5 explanatory dimensions thereof: intrinsic job quality; work organization and workplace relationships; working conditions, work intensity and health and safety at work; and extrinsic rewards. Only inequality in the work-life balance dimension remained stable. Research lim...