ABSTRACT
Objective: Over 6 million migrants and refugees from Venezuela have left their country in the past decade; 1 million of them reside in Peru. Venezuelan migrant and refugee women are known to have limited access to sexual and reproductive health care services (SRHS) and contraceptive usage. To date, research to understand factors influencing access to those services is limited. This study aims to determine which enabling and predisposing factors influence Venezuelan migrant and refugee women's access to SRHS and contraceptive usage. Methods: This is a retrospective cross-sectional study of the first survey administered to the Venezuelan population residing in the Peru in 2018. The survey covered six cities in the country (Metropolitan Lima, Callao, Tumbes, Cusco, Trujillo, Arequipa). The sample for the study included Venezuelan migrant women of reproductive age (15-49 years old). Anderson's Behavior Model of Health Services is the conceptual framework of the investigation. Logistic regression models were fit to examine the relationship between different predisposing and enabling factors and women's access to SRHS and contraceptive usage. Results: The sample size includes a total of 3378 Venezuelan women of reproductive age. 50.7% of the women were between the ages of 21-30 and over 90.6% of the sample were residing in Metropolitan Lima. Only 20.2% of the women reported they had access to modern contraceptives. Results from the study suggest having insurance, residing in Trujillo, and having a higher socio-economic status were associated with more access to certain sexual reproductive health care services and contraceptive usage. Conclusion: This study identified different predisposing and enabling factors relevant to the access to SRHS and contraceptive usage. Difference in access and usage are particularly pronounced based on insurance status, geographical location, and socio-economic status. Displaced Venezuelans will remain abroad for an extended period of time, if not permanently. Focus should shift from providing humanitarian aid to integrating the migrants and refugees, particularly the most vulnerable groups, into the local economic and healthcare system.
ABSTRACT
BACKGROUND: Information and emotions towards public health issues could spread widely through online social networks. Although aggregate metrics on the volume of information diffusion are available, we know little about how information spreads on online social networks. Health information could be transmitted from one to many (i.e. broadcasting) or from a chain of individual to individual (i.e. viral spreading). The aim of this study is to examine the spreading pattern of Ebola information on Twitter and identify influential users regarding Ebola messages. METHODS: Our data was purchased from GNIP. We obtained all Ebola-related tweets posted globally from March 23, 2014 to May 31, 2015. We reconstructed Ebola-related retweeting paths based on Twitter content and the follower-followee relationships. Social network analysis was performed to investigate retweeting patterns. In addition to describing the diffusion structures, we classify users in the network into four categories (i.e., influential user, hidden influential user, disseminator, common user) based on following and retweeting patterns. RESULTS: On average, 91% of the retweets were directly retweeted from the initial message. Moreover, 47.5% of the retweeting paths of the original tweets had a depth of 1 (i.e., from the seed user to its immediate followers). These observations suggested that the broadcasting was more pervasive than viral spreading. We found that influential users and hidden influential users triggered more retweets than disseminators and common users. Disseminators and common users relied more on the viral model for spreading information beyond their immediate followers via influential and hidden influential users. CONCLUSIONS: Broadcasting was the dominant mechanism of information diffusion of a major health event on Twitter. It suggests that public health communicators can work beneficially with influential and hidden influential users to get the message across, because influential and hidden influential users can reach more people that are not following the public health Twitter accounts. Although both influential users and hidden influential users can trigger many retweets, recognizing and using the hidden influential users as the source of information could potentially be a cost-effective communication strategy for public health promotion. However, challenges remain due to uncertain credibility of these hidden influential users.
