English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This study explores effective care training factors for patients with coronavirus disease 2019 (COVID-19) through social network message combining qualitative and quantitative methods. The research was conducted in two phases. In the first phase, based on the theoretical saturation approach, active social networking audiences were sampled and questioned in the field of COVID-19 learning. In this regard, 38 audiences interviewed and based on thematic analysis 20 non-repetitive features (basic them), five organizing themes, and a thematic network extracted. In the second phase, 11 experts were used to rank these extracted basic and organizing themes using the DEMATEL as a quantitative method. Finally, the results were tested using a one-sample T-test and Spearman correlation by a more significant number of social network users. The thematic analysis results introduce 20 basic themes, five organizing themes, and network themes for effective care training factors for patients with COVID-19 through the social network. Indeed, it can be concluded that the performed network themes and DEMATEL entails a unique model in this context. This model shows useful messages for COVID-19 training in the social network under the influence of five factors: simplicity, multimedia, validity, availability, and generalization.

Effective care training for patients with COVID-19 through social network