Impact of the Price of Gifts From Patients on Physicians' Service Quality in Online Consultations: Empirical Study Based on Social Exchange Theory.

Background: Gift giving from patients to physicians, which is prohibited in traditional clinical settings in China, has been found to occur in online health communities. However, there is debate on the validity of online gifts since physicians gain an economic benefit. Moreover, the potential impact of these gifts, particularly with respect to the financial value of the gift, on the online consultation service quality remains unexplored.

How professional capital and team heterogeneity affect the demands of online team-based medical service.

Background: The provision of medical services by Medical Teams (MT) on Online Healthcare Communities (OHCs) is a novel method employed by geographically-dispersed healthcare professionals to serve one patient simultaneously, allowing patients to receive more specific, targeted and comprehensive advice. As a relatively new method of service delivery, little attention has been paid to identifying the determinants of Team-based Service Demands (TSD). Based on Upper Echelons Theory and Social Exchange Theory, this study examines the impact of both professional capital (status capital and decisional capital) and team heterogeneity (team size and dispersion) on TSD.

Service provision, pricing, and patient satisfaction in online health communities.

Unlabelled: Background The emergence of online health communities (OHCs) broadens and diversifies channels for patient-doctor interaction. In recent times, patient satisfaction has gained new attention within the context of OHCs where unique patterns are provided: a variety of services with unique attributes are available in OHCs for patients and doctors have the options of providing and pricing for different services. OHCs are given high hopes on improving medical efficiency and patient satisfaction.

Informal care and health behaviors among elderly people with chronic diseases.

Background: The mechanism by which social relationships influence health can be interpreted as a social network regulating one's health behaviors. Based on the hypothesis that relatives, friends, or neighbors are sources of social support and may monitor one's health behaviors, researchers have gotten significant and consistent results that a social network can regulate health behaviors. However, few empirical studies have been conducted to examine the role of informal care in the regulation of health behaviors, especially for elderly individuals with chronic diseases that can be controlled by healthy behaviors.

Online written consultation, telephone consultation and offline appointment: An examination of the channel effect in online health communities.

Introduction: The emergence of online health communities broadens and diversifies channels for patient-doctor interaction. Given limited medical resources, online health communities aim to provide better treatment by decreasing medical costs, making full use of available resources and providing more diverse channels for patients.

Objectives: This research examines how online channel usage affects offline channels, i.

Causal effects of informal care and health on falls and other accidents among the elderly population in China.

Purpose: This article analyzes the causal effects of informal care, mental health, and physical health on falls and other accidents (e.g., traffic accidents) among elderly people.

Exploring the impact of word-of-mouth about Physicians' service quality on patient choice based on online health communities.

Background: Health care service is a high-credence service and patients may face difficulties ascertaining service quality in order to make choices about their available treatment options. Online health communities (OHCs) provide a convenient channel for patients to search for physicians' information, such as Word-of-Mouth (WOM), particularly on physicians' service quality evaluated by other patients. Existing studies from other service domains have proved that WOM impacts consumer choice.

A Simple Score Model to Assess Prediabetes Risk Status Based on the Medical Examination Data.

Objectives: We aimed to build a risk score model to screen out the patients at high-risk status so as to prevent or delay the conversion of prediabetes to diabetes.

Methods: The population were divided into 2 groups: 1 was an exploratory population, and the other was a validation population. All the data were extracted from the electronic medical examination datasets in the School Hospital of Harbin Institute of Technology, Harbin, China.

Depression care management for adults older than 60 years in primary care clinics in urban China: a cluster-randomised trial.

Background: China's national health policy classifies depression as a chronic disease that should be managed in primary care settings. In some high-income countries use of chronic disease management principles and primary care-based collaborative-care models have improved outcomes for late-life depression; however, this approach has not yet been tested in China. We aimed to assess whether use of a collaborative-care depression care management (DCM) intervention could improve outcomes for Chinese adults with depression aged 60 years and older.

On performance of parametric and distribution-free models for zero-inflated and over-dispersed count responses.

Zero-inflated Poisson (ZIP) and negative binomial (ZINB) models are widely used to model zero-inflated count responses. These models extend the Poisson and negative binomial (NB) to address excessive zeros in the count response. By adding a degenerate distribution centered at 0 and interpreting it as describing a non-risk group in the population, the ZIP (ZINB) models a two-component population mixture.

A non-parametric model to address overdispersed count response in a longitudinal data setting with missingness.

Count responses are becoming increasingly important in biostatistical analysis because of the development of new biomedical techniques such as next-generation sequencing and digital polymerase chain reaction; a commonly met problem in modeling them with the popular Poisson model is overdispersion. Although it has been studied extensively for cross-sectional observations, addressing overdispersion for longitudinal data without parametric distributional assumptions remains challenging, especially with missing data. In this paper, we propose a method to detect overdispersion in repeated measures in a non-parametric manner by extending the Mann-Whitney-Wilcoxon rank sum test to longitudinal data.

Randomized controlled trial of interpersonal psychotherapy versus enhanced treatment as usual for women with co-occurring depression and pelvic pain.

Objective: Our study assessed the effectiveness of Interpersonal Psychotherapy (IPT) tailored for biomedical patients with depression and pain. IPT was compared to enhanced treatment as usual (E-TAU) among women with co-occurring depression and chronic pain presenting for care at a women's health or family medicine practice. We hypothesized that women presenting to urban medical practices with depression and chronic pain would benefit from IPT tailored to address their needs to a greater degree than from E-TAU.

Log-transformation and its implications for data analysis.

The log-transformation is widely used in biomedical and psychosocial research to deal with skewed data. This paper highlights serious problems in this classic approach for dealing with skewed data. Despite the common belief that the log transformation can decrease the variability of data and make data conform more closely to the normal distribution, this is usually not the case.

Causal inference for community-based multi-layered intervention study.

Estimating causal treatment effect for randomized controlled trials under post-treatment confounding, that is, noncompliance and informative dropouts, is becoming an important problem in intervention/prevention studies when the treatment exposures are not completely controlled. When confounding is present in a study, the traditional intention-to-treat approach could underestimate the treatment effect because of insufficient exposure of treatment. In the recent two decades, many papers have been published to address such confounders to investigate the causal relationship between treatment and outcome of interest based on different modeling strategies.

Social Structure and Depression in TrevorSpace.

We discover patterns related to depression in the social graph of an online community of approximately 20,000 lesbian, gay, and bisexual, transgender, and questioning youth. With survey data on fewer than two hundred community members and the network graph of the entire community (which is completely anonymous except for the survey responses), we detected statistically significant correlations between a number of graph properties and those TrevorSpace users showing a higher likelihood of depression, according to the Patient Healthcare Questionnaire-9, a standard instrument for estimating depression. Our results suggest that those who are less depressed are more deeply integrated into the social fabric of TrevorSpace than those who are more depressed.