The influences of social support expressed from doctors and disclosed from peers on patient decision-making: an analysis from the online health community

Patients are turning to OHCs to deal with the stresses and complications of infertility. As a stigmatized disease, infertile patients may value informational support and emotional support differently, which is ignored in existing studies. Based on social support theory, this study aims to reveal the role of informational support and emotional support of doctors in infertile patient decision-making. We select Haodf.com as our data source and we collected information for all new patients of 2,989 doctors. we use Jieba word segmentation tool and TF-IDF algorithm to segment word and find keywords. Then random forest algorithm is used to classify 750 training texts and 250 test texts. We measure all the treatment experience of these new patients between September and December 2022 and then take the average value (TreatExpi). The sentiment analysis application program interface from Baidu AI-NLP is used to measure emotion state of patients and then the average value is included (EmoStai). In order to eliminate the influence of other factors, control variables including the number of patients online (#Patienti), the recommendation (Recommendationi), hospital level (Hleveli), doctor medical title (Mtitlei) and service price (Serpi). First, the effects of social support expressed from doctor and social support disclosed from peers show heterogeneity on patient decision-making. Second, the influences of informational support and emotional support also show difference. Third, the above relationships change with the characteristics of patients. Detecting different types and different sources of social support activities via text mining contributes to between understanding patient decision behavior in OHCs. This study contributes social support theory and OHC studies, and helps the management and design OHCs.