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Effective Care Training for Patients with COVID-19 through Social Network

Authors :
Sobhanifard, Yaser
Soltanmohammadi, Behnam
Source :
Interactive Learning Environments. 2023 31(4):2170-2184.
Publication Year :
2023

Abstract

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.

Details

Language :
English
ISSN :
1049-4820 and 1744-5191
Volume :
31
Issue :
4
Database :
ERIC
Journal :
Interactive Learning Environments
Publication Type :
Academic Journal
Accession number :
EJ1390843
Document Type :
Journal Articles<br />Reports - Research
Full Text :
https://doi.org/10.1080/10494820.2021.1875003