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Effect of Diabetes Online Community Engagement on Health Indicators: Cross-Sectional Study

BACKGROUND: Successful diabetes management requires ongoing lifelong self-care and can require that individuals with diabetes become experts in translating care recommendations into real-life day-to-day diabetes self-care strategies. The diabetes online community comprises multiple websites that inc...

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Autores principales: Litchman, Michelle L, Edelman, Linda S, Donaldson, Gary W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6238850/
https://www.ncbi.nlm.nih.gov/pubmed/30291079
http://dx.doi.org/10.2196/diabetes.8603
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author Litchman, Michelle L
Edelman, Linda S
Donaldson, Gary W
author_facet Litchman, Michelle L
Edelman, Linda S
Donaldson, Gary W
author_sort Litchman, Michelle L
collection PubMed
description BACKGROUND: Successful diabetes management requires ongoing lifelong self-care and can require that individuals with diabetes become experts in translating care recommendations into real-life day-to-day diabetes self-care strategies. The diabetes online community comprises multiple websites that include social media sites, blogs, and discussion groups for people with diabetes to chat and exchange information. Online communities can provide disease-specific practical advice and emotional support, allow users to share experiences, and encourage self-advocacy and patient empowerment. However, there has been little research about whether diabetes online community use is associated with better diabetes self-care or quality of life. OBJECTIVE: The aim of this study was to survey adults with diabetes who participated in the diabetes online community to better understand and describe who is using the diabetes online community, how they are using it, and whether the use of the diabetes online community was associated with health indicators. METHODS: We recruited adults diagnosed with diabetes who used at least one of 4 different diabetes-related online communities to complete an online survey. Participants’ demographics, reported glycated hemoglobin (HbA(1c)), health-related quality of life (SF-12v2), level of diabetes self-care (Self-Care Inventory-Revised), and diabetes online community use (level of intensity and engagement) were collected. We examined the relationships between demographics, diabetes online community use, and health indicators (health-related quality of life, self-care, and HbA(1c) levels). We used binary logistic regression to determine the extent to which diabetes online community use predicted an HbA(1c) <7% or ≥7% after controlling statistically for other variables in the model. RESULTS: A total of 183 adults participated in this study. Participants were mostly female (71.6%, 131/183), white (95.1%, 174/183), US citizens (82.5%, 151/183), had type 1 diabetes (69.7%, 129/183), with a mean age of 44.7 years (SD 14) and diabetes duration of 18.2 years (SD 14.6). Participants had higher diabetes self-care (P<.001, mean 72.4, SD 12.1) and better health-related quality of life (physical component summary P<.001, mean 64.8, SD 19; mental component summary P<.001, mean 66.6, SD 21.6) when compared with norms for diabetes. Diabetes online community engagement was a strong predictor of A(1c), reducing the odds of having an A(1c) ≥7% by 33.8% for every point increase in diabetes online community engagement (0-5). Our data also indicated that study participants are oftentimes (67.2%, 123/183) not informing their healthcare providers about their diabetes online community use even though most (91.2%, 161/181) are seeing their healthcare provider on a regular basis. CONCLUSIONS: Our results suggest that individuals highly engaged with diabetes online community are more likely to have better glycemic levels compared with those with lower engagement. Furthermore, diabetes online community users have high health-related quality of life and diabetes self-care levels. Supplementing usual healthcare activities with diabetes online community use may encourage knowledge and support among a population that needs to optimize its diabetes self-care. Further studies are needed to determine how diabetes online community engagement may affect health outcomes.
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spelling pubmed-62388502018-12-27 Effect of Diabetes Online Community Engagement on Health Indicators: Cross-Sectional Study Litchman, Michelle L Edelman, Linda S Donaldson, Gary W JMIR Diabetes Original Paper BACKGROUND: Successful diabetes management requires ongoing lifelong self-care and can require that individuals with diabetes become experts in translating care recommendations into real-life day-to-day diabetes self-care strategies. The diabetes online community comprises multiple websites that include social media sites, blogs, and discussion groups for people with diabetes to chat and exchange information. Online communities can provide disease-specific practical advice and emotional support, allow users to share experiences, and encourage self-advocacy and patient empowerment. However, there has been little research about whether diabetes online community use is associated with better diabetes self-care or quality of life. OBJECTIVE: The aim of this study was to survey adults with diabetes who participated in the diabetes online community to better understand and describe who is using the diabetes online community, how they are using it, and whether the use of the diabetes online community was associated with health indicators. METHODS: We recruited adults diagnosed with diabetes who used at least one of 4 different diabetes-related online communities to complete an online survey. Participants’ demographics, reported glycated hemoglobin (HbA(1c)), health-related quality of life (SF-12v2), level of diabetes self-care (Self-Care Inventory-Revised), and diabetes online community use (level of intensity and engagement) were collected. We examined the relationships between demographics, diabetes online community use, and health indicators (health-related quality of life, self-care, and HbA(1c) levels). We used binary logistic regression to determine the extent to which diabetes online community use predicted an HbA(1c) <7% or ≥7% after controlling statistically for other variables in the model. RESULTS: A total of 183 adults participated in this study. Participants were mostly female (71.6%, 131/183), white (95.1%, 174/183), US citizens (82.5%, 151/183), had type 1 diabetes (69.7%, 129/183), with a mean age of 44.7 years (SD 14) and diabetes duration of 18.2 years (SD 14.6). Participants had higher diabetes self-care (P<.001, mean 72.4, SD 12.1) and better health-related quality of life (physical component summary P<.001, mean 64.8, SD 19; mental component summary P<.001, mean 66.6, SD 21.6) when compared with norms for diabetes. Diabetes online community engagement was a strong predictor of A(1c), reducing the odds of having an A(1c) ≥7% by 33.8% for every point increase in diabetes online community engagement (0-5). Our data also indicated that study participants are oftentimes (67.2%, 123/183) not informing their healthcare providers about their diabetes online community use even though most (91.2%, 161/181) are seeing their healthcare provider on a regular basis. CONCLUSIONS: Our results suggest that individuals highly engaged with diabetes online community are more likely to have better glycemic levels compared with those with lower engagement. Furthermore, diabetes online community users have high health-related quality of life and diabetes self-care levels. Supplementing usual healthcare activities with diabetes online community use may encourage knowledge and support among a population that needs to optimize its diabetes self-care. Further studies are needed to determine how diabetes online community engagement may affect health outcomes. JMIR Publications 2018-04-24 /pmc/articles/PMC6238850/ /pubmed/30291079 http://dx.doi.org/10.2196/diabetes.8603 Text en ©Michelle L Litchman, Linda S Edelman, Gary W Donaldson. Originally published in JMIR Diabetes (http://diabetes.jmir.org), 24.04.2018. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Diabetes, is properly cited. The complete bibliographic information, a link to the original publication on http://diabetes.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Litchman, Michelle L
Edelman, Linda S
Donaldson, Gary W
Effect of Diabetes Online Community Engagement on Health Indicators: Cross-Sectional Study
title Effect of Diabetes Online Community Engagement on Health Indicators: Cross-Sectional Study
title_full Effect of Diabetes Online Community Engagement on Health Indicators: Cross-Sectional Study
title_fullStr Effect of Diabetes Online Community Engagement on Health Indicators: Cross-Sectional Study
title_full_unstemmed Effect of Diabetes Online Community Engagement on Health Indicators: Cross-Sectional Study
title_short Effect of Diabetes Online Community Engagement on Health Indicators: Cross-Sectional Study
title_sort effect of diabetes online community engagement on health indicators: cross-sectional study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6238850/
https://www.ncbi.nlm.nih.gov/pubmed/30291079
http://dx.doi.org/10.2196/diabetes.8603
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