Understanding Delivery of Collectively Built Protocols in an Online Health Community for Discontinuation of Psychiatric Drugs

2021 ◽  
Vol 5 (CSCW2) ◽  
pp. 1-29
Author(s):  
Alexandra Papoutsaki ◽  
Samuel So ◽  
Georgia Kenderova ◽  
Bryan Shapiro ◽  
Daniel A. Epstein
Keyword(s):  
Online Health Community ◽  
Psychiatric Drugs ◽  
Health Community

scholarly journals Social value creation through digital activism in an online health community

2020 ◽  
Vol 31 (1) ◽  
pp. 94-119
Author(s):  
Petros Chamakiotis ◽  
Dimitra Petrakaki ◽  
Niki Panteli
Keyword(s):  
Value Creation ◽  
Social Value ◽  
Digital Activism ◽  
Online Health Community ◽  
Health Community ◽  
Social Value Creation

Using data from an online health community to examine the impact of prostate cancer on sleep

2020 ◽  
Vol 125 (5) ◽  
pp. 634-635 ◽  
Author(s):  
Rebecca Robbins ◽  
Girardin Jean-Louis ◽  
Nicholas Chanko ◽  
Penelope Combs ◽  
Nataliya Byrne ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Online Health Community ◽  
Health Community ◽  
Using Data ◽  
The Impact

scholarly journals Impact of Patient Crowdvotes Aggregated Service Diversity on Doctors� Service Sales in Online Health Community: a Retrospective Study (Preprint)

2018 ◽  
Author(s):  
Hai-Yan Yu ◽  
Jying-Nan Wang ◽  
Ya-Ling Chiu ◽  
Hang Qiu ◽  
Ling Xiao
Keyword(s):  
Retrospective Study ◽  
Good Doctor ◽  
Lorenz Curves ◽  
Online Health Communities ◽  
Online Health Community ◽  
Health Community ◽  
Main Effect ◽  
Health Communities ◽  
Log Linear ◽  
Disease Understanding

BACKGROUND An increasing number of people visit online health communities to esquire health information with doctors. In the online health community (OHC), patient crowds tended to label and vote the doctors’ specialties with encountered disease. Understanding how patients’ online labels can help us understand the service diversity for patients in online health communities and provide constructive suggestions for doctors serving more patients online. OBJECTIVE Our goal was to understand: (1) what kind of patterns are the labels of patient crowdvotes aggregated service diversity, including encountered disease labels and online votes, in a OHC? (2) wheather the patient crowdvotes aggregated service diversity make doctors’ service sales difference in OHC? (3) how can managers in OHC perform to improve doctors’ service sales with the feedback of crowdvotes aggregated service diversity? METHODS We designed a retrospective study with data collected from the largest OHC (Good Doctor website) in China. We first used descriptive statistics to investigate the patient crowdvotes aggregated service diversity. Then a multiple log-linear relationship was adapted to investigate the main and the interaction impact of service diversity on doctors’ service sales. RESULTS Our sample consists of 9,841 doctors from 1,255 different hospitals widely distributed in China. 18,997,018 patients had been serviced by these doctors since they became members of the study OHC. 704,467 votes of doctors’ clinical specialties were labeled by patient crowds in recent two years (Aug.26, 2015-Aug. 25, 2017). Gini coefficient of serviced patients is very high, 0.626, followed by the volume of votes (0.562). Based on the regression model, we found that the coefficients of the control variables, doctor review rating and clinic title, were 0.810(0.041), and 1.735 (0.027), respectively. For the breadth of voted specialties, volume of votes and degree of voted diversity, the standardized coefficient of the main effect were 0.309 (0.038), 0.745 (0.014) and 0.073 (0.018), respectively. All of the estimates are statistically significant at a 0.1% level. CONCLUSIONS Our study provided empirical evidence that the patterns of both the labels of patient crowdvotes aggregated service diversity and doctors’ service sales were of inequality (as illustrated in Lorenz curves) in the distribution of its size of serviced patients in a OHC. Patient crowds’ online labels also leaded to differences in the doctors’ service sales online. The treads of the doctors’ service sales kept increasing as the patient crowdvotes aggregated service diversity increased. Finally, our findings suggested that the higher breadth of voted specialties and degree of voted diversity displayed a greater service sales with a higher review rating, deploying less inequality of Doctors’ service sales.

Sign in / Sign up

Export Citation Format

Share Document