Background In recent years, paid online patient-physician interaction has been incorporated into the telemedicine markets. With the development of telemedicine and telemedicine services, online feedback has been widely applied, helping other patients to identify quality services. Recently, in China, a new type of service feedback has been applied to the telemedicine markets, namely, paid feedback. Patients who are satisfied with a physician’s online service can buy a virtual gift or give a tip to the physicians. This paid feedback can improve the reliability of service feedback and reduce the proportion of false information because it increases the cost for feedback providers. Paid online feedback can benefit the physicians, such as by providing them with monetary incentives; however, research on the impacts and value of such paid feedback from the physician perspective in the telemedicine markets is scant. To fill this research gap, this study was designed to understand the role of paid feedback by developing a research model based on the theories of signaling and self-determination. Objective This study aimed to explore the effects of free and paid feedback on patients’ choice and physicians’ behaviors as well as to investigate the substitute relationship between these 2 types of feedback in the telemedicine markets. Methods A JAVA software program was used to collect online patient-doctor interaction data over a 6-month period from a popular telemedicine market in China (Good Physician Online). This study drew on a 2-equation panel model to test the hypotheses. Both fixed and random effect models were used to estimate the combined effects of paid feedback and free feedback on patients’ choice and physicians’ contribution. Finally, the Hausman test was adopted to investigate which model is better to explain our empirical results. Results The results of this study show that paid feedback has a stronger effect on patients’ choice (a 5 =0.566; t 2192 =9.160; P <.001) and physicians’ contribution (β 4 =1.332; t 2193 =11.067; P <.001) in telemedicine markets than free feedback. Moreover, our research also proves that paid feedback and free feedback have a substitute relationship in determining patients’ and physicians’ behaviors (a 6 =−0.304; t 2191 =−5.805; P <.001 and β 5 =−0.823; t 2192 =−8.136; P <.001). Conclusions Our findings contribute to the extant literature on service feedback in the telemedicine markets and provide insight for relevant stakeholders into how to design an effective f...

Background: Skin cutaneous melanoma (SKCM) is a common malignancy that is associated with increased morbidity and mortality. Complement C1Q is composed of C1QA, C1QB, and C1QC and is involved in the occurrence and development of many malignant tumours. However, the effect of C1QA, C1QB, and C1QC expression on tumour immunity and prognosis of cutaneous melanoma remains unclear.Methods: First, we analysed C1QA, C1QB, and C1QC expression levels and prognostic values using Gene Expression Profiling Interactive Analysis (GEPIA) and Tumour Immune Estimation Resource (TIMER) analysis, and further validation was performed using RT-qPCR, The Human Protein Atlas, The Cancer Genome Atlas (TCGA) dataset, and Gene Expression Omnibus dataset. We then performed univariate/multivariate Cox proportional hazard model, clinicopathological correlation, and receiver operating characteristic curve analysis using TCGA dataset and established a nomogram model. Differentially expressed genes associated with C1QA, C1QB, and C1QC in SKCM were identified and analysed using LinkedOmics, TIMER, the Search Tool for the Retrieval of Interacting Genes database, and Metascape and Cytoscape software platforms. We used TIMER, GEPIA, and single-sample gene set enrichment analysis (ssGSEA) to analyse the relationship between the three genes and the level of immune cell infiltration, biomarkers, and checkpoint expression in SKCM. Finally, GSEA was utilized to study the functional pathways of C1QA, C1QB, and C1QC enrichment in SKCM.Results: The overexpression of C1QA, C1QB, and C1QC provided significant value in the diagnosis of SKCM and has been associated with better overall survival (OS). Multivariate Cox regression analysis indicated that C1QA, C1QB, and C1QC are independent prognostic biomarkers for patients with SKCM. Immune cell infiltration, biomarkers, and checkpoints were positively correlated with the expression of C1QA, C1QB, and C1QC. Furthermore, the results of functional and pathway enrichment analysis showed that immune-related and apoptotic pathways were significantly enriched in the high-expression group of C1QA, C1QB, and C1QC.Conclusion: We found that C1QA, C1QB, and C1QC can be used as biomarkers for the diagnosis and prognosis of SKCM patients. The upregulated expression levels of these three complement components benefit patients from OS and may increase the effect of immunotherapy. This result may be due to the dual effects of anti-tumour immunity and apoptosis.

PurposeGamification design is considered an effective way of changing users' health behavior and improving their health management performance. Even though numerous studies have investigated the positive effect of gamification competition on users, little research has considered gamification's ineffectiveness and negative effects. In particular, how gamification competition affects users' technological exhaustion remains unclear.Design/methodology/approachAccording to flow theory and related research on gamification, this study discusses the nonlinear relationship between gamification competition and users' technological exhaustion. Furthermore, the authors analyze the moderating effect of user type (socializers and achievers) and users' health condition on this nonlinear relationship. Based on flow theory, the authors propose a series of research hypotheses. To test all research hypotheses, the authors collected information from 407 users via a questionnaire as the data for this study.FindingsThe empirical results found a U-shaped relationship between gamification competition and technological exhaustion. Technological exhaustion gradually decreases as competition increases until reaching the lowest point; after that, technological exhaustion gradually increases as competition increases. Further, being a socializer and health condition play a moderating role in the U-shaped relationship between competition and technological exhaustion.Originality/valueThis study's findings not only enrich the related research in flow theory and gamification, but also contribute to the effective design of gamification in health management platforms.

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BACKGROUND In recent years, paid online patient-physician interaction has been incorporated into the telemedicine markets. With the development of telemedicine and telemedicine services, online feedback has been widely applied, helping other patients to identify quality services. Recently, in China, a new type of service feedback has been applied to the telemedicine markets, namely, paid feedback. Patients who are satisfied with a physician’s online service can buy a virtual gift or give a tip to the physicians. This paid feedback can improve the reliability of service feedback and reduce the proportion of false information because it increases the cost for feedback providers. Paid online feedback can benefit the physicians, such as by providing them with monetary incentives; however, research on the impacts and value of such paid feedback from the physician perspective in the telemedicine markets is scant. To fill this research gap, this study was designed to understand the role of paid feedback by developing a research model based on the theories of signaling and self-determination. OBJECTIVE This study aimed to explore the effects of free and paid feedback on patients’ choice and physicians’ behaviors as well as to investigate the substitute relationship between these 2 types of feedback in the telemedicine markets. METHODS A JAVA software program was used to collect online patient-doctor interaction data over a 6-month period from a popular telemedicine market in China (Good Physician Online). This study drew on a 2-equation panel model to test the hypotheses. Both fixed and random effect models were used to estimate the combined effects of paid feedback and free feedback on patients’ choice and physicians’ contribution. Finally, the Hausman test was adopted to investigate which model is better to explain our empirical results. RESULTS The results of this study show that paid feedback has a stronger effect on patients’ choice (a5=0.566; t2192 =9.160; P<.001) and physicians’ contribution (β4=1.332; t2193 =11.067; P<.001) in telemedicine markets than free feedback. Moreover, our research also proves that paid feedback and free feedback have a substitute relationship in determining patients’ and physicians’ behaviors (a6=−0.304; t2191 =−5.805; P<.001 and β5=−0.823; t2192 =−8.136; P<.001). CONCLUSIONS Our findings contribute to the extant literature on service feedback in the telemedicine markets and provide insight for relevant stakeholders into how to design an effective feedback mechanism to improve patients’ service experience and physicians’ engagement.