Abstract
BackgroundWeb-based crowdsourcing promotes the goals achieved effectively by gaining solutions from public groups via the internet, and it has gained extensive attention in both business and academia. As a new mode of sourcing, crowdsourcing has been proven to improve efficiency, quality, and diversity of tasks. However, little attention has been given to crowdsourcing in the health sector.ObjectiveCrowdsourced health care information websites enable patients to post their questions in the question pool, which is accessible to all doctors, and the patients wait for doctors to respond to their questions. Since the sustainable development of crowdsourced health care information websites depends on the participation of the doctors, we aimed to investigate the factors influencing doctors’ participation in providing health care information in these websites from the perspective of the elaboration-likelihood model.MethodsWe collected 1524 questions with complete patient-doctor interaction processes from an online health community in China to test all the hypotheses. We divided the doctors into 2 groups based on the sequence of the answers: (1) doctor who answered the patient’s question first and (2) the doctors who answered that question after the doctor who answered first. All analyses were conducted using the ordinary least squares method.ResultsFirst, the ability of the doctor who first answered the health-related question was found to positively influence the participation of the following doctors who answered after the first doctor responded to the question (βoffline1=.177, P<.001; βoffline2=.063, P=.048; βonline=.418, P<.001). Second, the reward that the patient offered for the best answer showed a positive effect on doctors’ participation (β=.019, P<.001). Third, the question’s complexity was found to positively moderate the relationships between the ability of the first doctor who answered and the participation of the following doctors (β=.186, P=.05) and to mitigate the effect between the reward and the participation of the following doctors (β=–.003, P=.10).ConclusionsThis study has both theoretical and practical contributions. Online health community managers can build effective incentive mechanisms to encourage highly competent doctors to participate in the provision of medical services in crowdsourced health care information websites and they can increase the reward incentives for each question to increase the participation of the doctors.
Highlights
BackgroundThe imbalance between the supply and demand for medical services has caused conflicts in the patient-doctor relationship, especially because the health awareness of patients has dramatically increased in recent years [1]
Based on the framework of elaboration-likelihood model (ELM), this study aims to investigate the attitude of the participating doctors toward the crowdsourced health care information websites, which is persuaded by dual-process cues, namely, central cues and peripheral cues
The results showed that all the control variables have correlations with doctor participation except patient’s age (P_Age) and D_Assistance number
Summary
BackgroundThe imbalance between the supply and demand for medical services has caused conflicts in the patient-doctor relationship, especially because the health awareness of patients has dramatically increased in recent years [1]. With the development of online health communities in China, an increasing number of people have begun to seek web-based health information and services [2,3], and these websites have become a useful complementation [4]. Only 6.1% of the doctors participate in online health communities to provide medical services [5]. The primary concern of the governments and health care organizations is to increase the number of doctors involved in the provision of web-based medical services. Online health community managers can build effective incentive mechanisms to encourage highly competent doctors to participate in the provision of medical services in crowdsourced health care information websites and they can increase the reward incentives for each question to increase the participation of the doctors
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