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Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population

Objective: To determine the characteristics of members of online diabetes communities as well as those factors affecting the provision and acceptance of social support. Methods: A cross-sectional STAR questionnaire survey was conducted among patients with diabetes who were members of online diabetes...

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Autores principales: Liang, Dan, Fan, Guanhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216204/
https://www.ncbi.nlm.nih.gov/pubmed/32325783
http://dx.doi.org/10.3390/ijerph17082806
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author Liang, Dan
Fan, Guanhua
author_facet Liang, Dan
Fan, Guanhua
author_sort Liang, Dan
collection PubMed
description Objective: To determine the characteristics of members of online diabetes communities as well as those factors affecting the provision and acceptance of social support. Methods: A cross-sectional STAR questionnaire survey was conducted among patients with diabetes who were members of online diabetes groups. Univariate and multivariate binary logistic regression analysis were adopted to explore the relative analysis of providing and accepting social support compared with the characteristics of members in virtual diabetics’ groups. Results: A total of 1297 respondents were collected. The map distribution of patients in China was mainly located in the Guangdong, Jiangsu, Shandong, Henan, and Hebei provinces. As for their demographic characteristics, respondents had diabetes or prediabetes and were between the ages of 21 and 50 years (Median age was 35.0 (interquartile range from 28.0 to 44.0)). Most respondents were married and lived in cities. The education level of patients was mainly distributed throughout junior high, technical secondary, high school, junior college, and undergraduate levels. Age, marital status, and education level varied by gender, and the total score of the patients aged 41 to 50 for social support had a statistical significance between male and female. In addition, when group members were in junior high school or below, or were undergraduate students, their total social support scores varied by gender. Binary logistic regression showed that in 21 independent variables the total score and the total score grade of relationship intensity in the online group and reorganize of age were significant. The patients’ social support acceptance of the map of respondents score grading of relationship intensity in the online group was 5.420 times higher than that of the lower score grading of relationship intensity in the group. At the same time, the patients’ social support acceptance of the patients at the age of less than or equal to 31 years old was 19.608 times higher than that of group members aged more than 31 years old. Conclusion: Age and education background of the patients affects scores of social supports between males and females. The higher the total score and the score grade of relationship intensity in the online group, the higher the patients’ social support acceptance. The younger patients had a better utilization of social support.
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spelling pubmed-72162042020-05-22 Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population Liang, Dan Fan, Guanhua Int J Environ Res Public Health Article Objective: To determine the characteristics of members of online diabetes communities as well as those factors affecting the provision and acceptance of social support. Methods: A cross-sectional STAR questionnaire survey was conducted among patients with diabetes who were members of online diabetes groups. Univariate and multivariate binary logistic regression analysis were adopted to explore the relative analysis of providing and accepting social support compared with the characteristics of members in virtual diabetics’ groups. Results: A total of 1297 respondents were collected. The map distribution of patients in China was mainly located in the Guangdong, Jiangsu, Shandong, Henan, and Hebei provinces. As for their demographic characteristics, respondents had diabetes or prediabetes and were between the ages of 21 and 50 years (Median age was 35.0 (interquartile range from 28.0 to 44.0)). Most respondents were married and lived in cities. The education level of patients was mainly distributed throughout junior high, technical secondary, high school, junior college, and undergraduate levels. Age, marital status, and education level varied by gender, and the total score of the patients aged 41 to 50 for social support had a statistical significance between male and female. In addition, when group members were in junior high school or below, or were undergraduate students, their total social support scores varied by gender. Binary logistic regression showed that in 21 independent variables the total score and the total score grade of relationship intensity in the online group and reorganize of age were significant. The patients’ social support acceptance of the map of respondents score grading of relationship intensity in the online group was 5.420 times higher than that of the lower score grading of relationship intensity in the group. At the same time, the patients’ social support acceptance of the patients at the age of less than or equal to 31 years old was 19.608 times higher than that of group members aged more than 31 years old. Conclusion: Age and education background of the patients affects scores of social supports between males and females. The higher the total score and the score grade of relationship intensity in the online group, the higher the patients’ social support acceptance. The younger patients had a better utilization of social support. MDPI 2020-04-18 2020-04 /pmc/articles/PMC7216204/ /pubmed/32325783 http://dx.doi.org/10.3390/ijerph17082806 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liang, Dan
Fan, Guanhua
Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population
title Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population
title_full Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population
title_fullStr Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population
title_full_unstemmed Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population
title_short Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population
title_sort social support and user characteristics in online diabetes communities: an in-depth survey of a large-scale chinese population
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216204/
https://www.ncbi.nlm.nih.gov/pubmed/32325783
http://dx.doi.org/10.3390/ijerph17082806
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