Surveillance of an Online Social Network to Assess Population-level

Elissa R Weitzman, Skyler Keleman, Kenneth Mandl


Objective: Test a novel health monitoring approach by engaging an international online diabetes social network (SN) in consented health surveillance.

Methods: Collection of structured self-reports about preventive and self-care practices and health status using a software application (“app”) that supports SN-mediated health research. Comparison of SN measures by diabetes type; and, SN with Behavioral Risk Factor Surveillance System (BRFSS) data, for US-residing insulin dependent respondents, using logistic regression.

Results: Of 2,414 SN app users, 82% (n=1979) provided an A1c and 41% (n=996) completed a care survey of which 931 have diabetes. Of these: 65% and 41% were immunized against influenza and pneumonia respectively, 90% had their cholesterol checked, 82% and 66%, had their eyes and feet checked, respectively. Type 1/LADA respondents were more likely than Type 2/pre-diabetic respondents to report all five recommended practices (Adjusted OR (95% CI) 2.2 (1.5, 3.2)). Past year self-care measures were: 58% self-monitored their blood glucose (SMBG) ≥ 5 times daily, 37% saw their diabetes nutritionist, 56% saw a diabetes nurse educator, 53% saw a doctor for their diabetes ≥ 4 times. Reports of health status did not differ by diabetes type in the SN sample. The SN group was more likely than the BRFSS comparator group to use all five preventive care practices (Adjusted OR (95% CI) 1.8 (1.4, 2.1) and SMBG ≥ 5 times daily (Adjusted OR (95% CI) 10.1 (6.8, 14.9).

Conclusions: Rapid assessment of diabetes care practices using a novel, SN-mediated approach can extend the capability of standard health surveillance systems.

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Online Journal of Public Health Informatics * ISSN 1947-2579 *