Exploring the Incentive Function of Virtual Academic Degrees in a Chinese Online Smoking Cessation Community: Qualitative Content Analysis.

Background: Previous studies on online smoking cessation communities (OSCCs) have shown how such networks contribute to members' health outcomes from behavior influence and social support perspectives. However, these studies rarely considered the incentive function of OSCCs. One of the ways OSCCs motivate smoking cessation behaviors is through digital incentives.

Rapid Review on Publicly Available Datasets for Health Misinformation Detection.

The proliferation of health misinformation in recent years has prompted the development of various methods for detecting and combatting this issue. This review aims to provide an overview of the implementation strategies and characteristics of publicly available datasets that can be used for health misinformation detection. Since 2020, a large number of such datasets have emerged, half of which are focused on COVID-19.

Predicting Family Implementation of Complementary and Alternative Medicine in Autism Online Communities.

Complementary and alternative medicine (CAM) is widely adopted by families with autistic children. This study aims to predict family caregivers' CAM implementation in Autism online communities. Dietary interventions were reported as a case study.

Exploring the landscape, hot topics, and trends of bariatric metabolic surgery with machine learning and bibliometric analysis.

Background: This study aimed to analyze the landscape of publications on bariatric metabolic surgery through machine learning and help experts and scholars from various disciplines better understand bariatric metabolic surgery's hot topics and trends.

Methods: In January 2021, publications indexed in PubMed under the Medical Subject Headings (MeSH) term 'Bariatric Surgery' from 1946 to 2020 were downloaded. Python was used to extract publication dates, abstracts, and research topics from the metadata of publications for bibliometric evaluation.

Understanding the Adoption of Dietary Interventions Within a Chinese Autism Online Community: A Diffusion of Innovations Perspective.

Dietary interventions are common but controversial treatments for autistic people. This study aims to understand the adoption of dietary interventions based on diffusion of innovations theory in the autism online community from four aspects: popularity, adoption process, the influence of opinion leaders, and post-adoption feedback. Our data was extracted from a Chinese autism community named Baidu Tieba autism forum.

Do Informational and Emotional Elements Differ between Online Psychological and Physiological Disease Communities in China? A Comparative Study of Depression and Diabetes.

Disease-specific online health communities provide a convenient and common platform for patients to share experiences, change information, provide and receive social support. This study aimed to compare differences between online psychological and physiological disease communities in topics, sentiment, participation, and emotional contagion patterns using multiple methods as well as to discuss how to satisfy the users' different informational and emotional needs. We chose the online depression and diabetes communities on the Baidu Tieba platform as the data source.

Privacy Policy Compliance of Chronic Disease Management Apps in China: Scale Development and Content Evaluation.

Background: With the development of mobile health (mHealth), chronic disease management apps have brought not only the possibility of reducing the burden of chronic diseases but also huge privacy risks to patients' health data.

Objective: The purpose of the study was to analyze the extent to which chronic disease management apps in China comply with the Personal Information Security Specification (PI Specification).

Methods: The compliance of 45 popular chronic disease management apps was evaluated from the perspective of the information life cycle.

Characterizing the COVID-19 Infodemic on Chinese Social Media: Exploratory Study.

Background: The COVID-19 infodemic has been disseminating rapidly on social media and posing a significant threat to people's health and governance systems.

Objective: This study aimed to investigate and analyze posts related to COVID-19 misinformation on major Chinese social media platforms in order to characterize the COVID-19 infodemic.

Methods: We collected posts related to COVID-19 misinformation published on major Chinese social media platforms from January 20 to May 28, 2020, by using PythonToolkit.