The complementary and substitutive value of online health information

Blockchain-enabled cross-chain collaboration model for elderly health information from a whole process perspective

Due to people having less children and the aging population, the demand for elderly health services is increasing, which leads to an increase in demand for elderly health information. However, there is a gap between elderly medical health information and elderly care information due to different storage institutions and storage methods, which makes it difficult for the medical service industry and the elderly service industry to fully grasp and utilize the health information of the elderly. Therefore, it is difficult to provide whole process services that combine elderly medical health and elderly care. To solve the problem of the poor collaborative utilization of elderly healthcare information, this paper, based on blockchain cross-chain technology and the literature and field research, studies the specific contexts that are needed to realize elderly health information collaboration. Based on the system theory viewpoint, the component-based modular design concept is used to identify the attributes and types of current health information of the elderly from health information related to the five modules of prevention, detection, diagnosis, treatment, and rehabilitation in the process of elderly healthcare. This paper explores the structure, elements, and interactions between the medical health information chains and the elderly care information chains. We build a blockchain-enabled cross-chain collaboration model of elderly health information from the perspective of the whole process with the help of the underlying logic of virtual chain, and to realize the applicability and flexibility of cross-chain collaboration for health information for the elderly in the whole process. The research results show that the proposed cross-chain collaboration model can realize the cross-chain collaboration of health information for the elderly with easy implementation, high throughput, and strong privacy protection.

A Comparison of Women's and Men's Online Information Seeking Behaviors about Gender-Related Health Information: A German Stratified Online Survey (Preprint)

BACKGROUND

Gender-sensitive approaches to health communication aim to integrate gender perspectives at all levels of communication, as an individual's biological sex and socially assigned gender identity have an impact on whether and how one acquires what type of health information. Due to the fast and low-cost opportunity to search for a wide range of information, the internet seems to be a particularly suitable place for gender-related health information about diseases of sex-specific organs and diseases where biological differences are associated with different health risks.

OBJECTIVE

This study aims to inform gender-related information provision and acquisition in 2 ways. The first objective was to provide a theory-driven analysis of web-based health information-seeking behavior (HISB) regarding gender-related issues. Therefore, the Planned Risk Information Seeking Model (PRISM), which is one of the most integrative models of HISB, was adapted and applied. Second, we asked for gender-specific motivational determinants of gender-related web-based HISB comparing the predictors in the groups of women and men.

METHODS

Data from a stratified web-based survey of the German population (N=3000) explained gender-related web-based HISB and influencing patterns comparing women and men. The applicability of PRISM to gender-related web-based HISB was tested using structural equation modeling and a multigroup comparison.

RESULTS

The results revealed PRISM as an effective framework for explaining gender-related web-based HISB. The model accounted for 28.8% of the variance in gender-related web-based HISB. Gender-related subjective norms provided the most crucial explanatory power, followed by perceived seeking control. The multigroup comparison revealed differences in the model's explanatory power and the relevance of predictors of gender-related web-based HISB. The share of explained variances of web-based HISB is higher in men than in women. For men, norms were a more relevant promoting factor, whereas web-based HISB of women was more strongly associated with perceived seeking control.

CONCLUSIONS

The results are crucial for gender-sensitive targeting strategies and suggest gender-related health information interventions that address gender-related subjective norms. Furthermore, programs (eg, web-based learning units) should be developed and offered to improve individuals' (perceived) abilities to perform web-based searches for health information, as those with higher control beliefs are more likely to access web-based information.

Associations between Public Fear of COVID-19 and Number of COVID-19 Vaccinations: A County-Level Longitudinal Analysis

Background and Purpose: A large number of COVID-19 infections and deaths and the ensuing socioeconomic problems created widespread public fear around COVID-19. Fear around COVID-19 greatly influences people’s attitudes towards receiving the COVID-19 vaccines. The purpose of this study is examining (a) the impact of the public fear of COVID-19 (PFC) on the number of COVID-19 vaccinations at the county level; (b) the interaction effect between the PFC and per capita income, unemployment rates, and COVID-19 vaccines incentive policies, on the number of COVID-19 vaccinations at the county level. Method: This is a longitudinal analysis across states in the U.S. by using county-level data of 2856 counties from 1 February to 1 July. Random-effects models were adopted to analyze the associations between the PFC and the number of COVID-19 vaccinations. Result: the PFC was positively associated with the number of COVID-19 vaccinations at county-level, as PFC increases from 0 to 300, the predicted vaccination number increases from 10,000 to 230,000. However, the associations were divergent when the PFC interacts with county-level per capita income, unemployment rates, and incentive policies. Conclusion: public fear is an important indicator for the county-level vaccination numbers of COVID-19. However, it is critical to consider public fear and socioeconomic factors when making policies that aim to increase COVID-19 vaccination rates.