It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
An understanding of healthcare super-utilizers’ online behaviors could better identify experiences to inform interventions. In this retrospective case-control study, we analyzed patients’ social media posts to better understand their day-to-day behaviors and emotions expressed online. Patients included those receiving care in an urban academic emergency department who consented to share access to their historical Facebook posts and electronic health records. Super-utilizers were defined as patients with more than six visits to the Emergency Department (ED) in a year. We compared posts by super-utilizers with a matched group using propensity scoring based on age, gender and Charlson comorbidity index. Super-utilizers were more likely to post about confusion and negativity (D = .65, 95% CI-[.38, .95]), self-reflection (D = .63 [.35, .91]), avoidance (D = .62 [.34, .90]), swearing (D = .52 [.24, .79]), sleep (D = .60 [.32, .88]), seeking help and attention (D = .61 [.33, .89]), psychosomatic symptoms, (D = .49 [.22, .77]), self-agency (D = .56 [.29, .85]), anger (D = .51, [.24, .79]), stress (D = .46, [.19, .73]), and lonely expressions (D = .44, [.17, .71]). Insights from this study can potentially supplement offline community care services with online social support interventions considering the high engagement of super-utilizers on social media.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details

1 Penn Medicine Center for Digital Health, Philadelphia, USA; University of Pennsylvania, Department of Computer and Information Science, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Perelman School of Medicine, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972)
2 Penn Medicine Center for Digital Health, Philadelphia, USA (GRID:grid.25879.31); Penn Medicine Center for Health Care Innovation, Philadelphia, USA (GRID:grid.25879.31)
3 Penn Medicine Center for Digital Health, Philadelphia, USA (GRID:grid.25879.31); University of Pennsylvania, Department of Computer and Information Science, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, The Wharton School, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972)
4 University of Pennsylvania, Perelman School of Medicine, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); Penn Medicine Center for Health Care Innovation, Philadelphia, USA (GRID:grid.25879.31); University of Pennsylvania, The Wharton School, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); Cpl Michael J Crescenz VA Medical Center, Philadelphia, USA (GRID:grid.410355.6) (ISNI:0000 0004 0420 350X)
5 Penn Medicine Center for Digital Health, Philadelphia, USA (GRID:grid.410355.6); University of Pennsylvania, Perelman School of Medicine, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); Penn Medicine Center for Health Care Innovation, Philadelphia, USA (GRID:grid.25879.31)