Explanatory models describe individuals’ perceptions of their illness experiences, which can guide culturally relevant care. We constructed an explanatory model of the experience of living with human immunodeficiency virus (HIV) in the Dominican Republic. Following qualitative descriptive methodology, we conducted interviews in Spanish using a semi-structured interview guide developed using Kleinman’s explanatory model framework. Two bilingual researchers coded interview transcripts following conventional content analysis. We used deductive codes from Kleinman’s framework and inductive codes external to the framework to construct the codebook. We arranged codes by shared meaning into categories and constructed themes that reflected shared findings from inductive categories and deductive codes. Twenty-six persons living with HIV participated. They provided rich descriptions of their experiences represented by four cross-cutting themes, which informed the explanatory model. By incorporating this in-depth understanding of patients’ illness experiences into care delivery, nurses can cultivate culturally meaningful and trusting patient-centered partnerships that improve health.
Background: Everyday approximately a billion viewers watch hundreds of millions of hours on YouTube. Currently YouTube videos are used as internet based media for dissemination of public health information. To characterize viewer engagement pattern, we measured viewership, viewer-preferences and viewer-responses to the HIV/AIDS awareness and prevention related videos on YouTube. Methods: We performed a search on YouTube (www.youtube. com) using the keywords 'HIV/AIDS awareness', 'HIV/AIDS prevention', and 'HIV/AIDS education. YouTube videos possessing 5000 viewership were selected for analysis. Viewer engagement was measured by recording total number of views, likes, dislikes, shares, and comments. Views per day were calculated by dividing total number of views by number of days since upload. Number of reaction was obtained by combining number of likes and dislikes. To assess differences in continuous variables across different categories, non-parametric Kruskal-Wallis test was used for non-normal distributions.
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