The Impact of Social Media on Children's Mental Health: A Systematic Scoping Review.

Background: In the digital age, safeguarding children's mental health (CMH) has emerged as one of the most pressing challenges. The rapid evolution of social media (SM) from a basic networking platform to a multifaceted tool has introduced numerous conveniences. However, it has also posed significant challenges to children's mental well-being.

Automatic kidney stone identification: an adaptive feature-weighted LSTM model based on urine and blood routine analysis.

Kidney stones are the most common urinary system diseases, and early identification is of great significance. The purpose of this study was to use routine urine and blood detection indices to build a deep learning (DL) model to identify the presence of kidney stones in the early stage. A retrospective analysis was conducted on patients with kidney stones who were treated at West China Hospital of Sichuan University from January 2020 to June 2023.

3MT-Net: A Multi-modal Multi-task Model for Breast Cancer and Pathological Subtype Classification Based on a Multicenter Study.

Breast cancer significantly impacts women's health, with ultrasound being crucial for lesion assessment. To enhance diagnostic accuracy, computer-aided detection (CAD) systems have attracted considerable interest. This study introduces a prospective deep learning architecture called "Multi-modal Multi-task Network" (3MT-Net).

Public health education using social learning theory: a systematic scoping review.

Background: Public health education (PHE) in social environments plays a crucial role in mitigating the impact of public health events, especially with the recent surge in global incidents. Social learning theory (SLT) provides a strong theoretical foundation for implementing PHE. The objective of this study is to conduct a systematic scoping review of PHE using SLT, synthesizing the target populations, types of research, main findings, and future directions.

Using Google Analytics with Health Information-Seeking Model to Evaluate the Design of Health Information Websites.

Health information websites can be useful for information seekers, and their design is crucial for the success of accessing the needed information. While web analytical tools (e.g.

Predicting Patients' Satisfaction With Mental Health Drug Treatment Using Their Reviews: Unified Interchangeable Model Fusion Approach.

Background: After the COVID-19 pandemic, the conflict between limited mental health care resources and the rapidly growing number of patients has become more pronounced. It is necessary for psychologists to borrow artificial intelligence (AI)-based methods to analyze patients' satisfaction with drug treatment for those undergoing mental illness treatment.

Objective: Our goal was to construct highly accurate and transferable models for predicting the satisfaction of patients with mental illness with medication by analyzing their own experiences and comments related to medication intake.

Focus-RCNet: a lightweight recyclable waste classification algorithm based on focus and knowledge distillation.

Waste pollution is a significant environmental problem worldwide. With the continuous improvement in the living standards of the population and increasing richness of the consumption structure, the amount of domestic waste generated has increased dramatically, and there is an urgent need for further treatment. The rapid development of artificial intelligence has provided an effective solution for automated waste classification.

Participatory Design and Evaluation of the "Stem Cells Australia" Website for Delivering Complex Health Knowledge: Mixed Methods Study.

Background: The internet has become a commonly used information source for people seeking to understand their health care options. However, inconsistent representation about what stem cell treatments are available and from whom, coupled with the lack of transparency about what has been shown to work or is even safe, can distract and mislead users. Given these challenges, there is a need to develop effective evidence-based tools for delivering information about health care options involving stem cells.

Changes in Doctor-Patient Relationships in China during COVID-19: A Text Mining Analysis.

Doctor-patient relationships (DPRs) in China have been straining. With the emergence of the COVID-19 pandemic, the relationships and interactions between patients and doctors are changing. This study investigated how patients' attitudes toward physicians changed during the pandemic and what factors were associated with these changes, leading to insights for improving management in the healthcare sector.

Social Media Engagement in Two Governmental Schemes during the COVID-19 Pandemic in Macao.

Social media engagement is a vehicle for effective communication and engagement between governments and individuals, especially in crises such as the COVID-19 pandemic. Additionally, it can be used to communicate resilience measures and receive feedback. This research aims to investigate public social media engagement with resilience measures related to COVID-19 in Macao.

Engagement of Government Social Media on Facebook during the COVID-19 Pandemic in Macao.

Government social media is widely used for providing updates to and engaging with the public in the COVID-19 pandemic. While Facebook is one of the popular social media used by governments, there is only a scant of research on this platform. This paper aims to understand how government social media should be used and how its engagement changes in prodromal, acute and chronic stages of the pandemic.

The Twitter Adventure of #MyHealthRecord: An Analysis of Different User Groups During the Opt-Out Period.

My Health Record (MHR), which is an online health summary for Australians, was changed from the opt-in to the opt-out model, and therefore sparked a vast discussion on Twitter. In order to understand the debate, the information dissemination and the levels of engagement, we have analysed tweets posted from July 2018 to February 2019. In this paper, we report on the findings of the patterns of discussion, the hashtags and the numbers of retweets and likes from different user categories.

The Use of Web-Based Technologies in Health Research Participation: Qualitative Study of Consumer and Researcher Experiences.

Background: Health consumers are often targeted for their involvement in health research including randomized controlled trials, focus groups, interviews, and surveys. However, as reported by many studies, recruitment and engagement of consumers in academic research remains challenging. In addition, there is scarce literature describing what consumers look for and want to achieve by participating in research.

Online Health Seeking Behaviours: What Information Is Sought by Women Experiencing Miscarriage?

One in four pregnancies ends in miscarriage, a distressing event which can cause significant psychosocial impacts for many women, and yet often remains unseen and unspoken. Many would-be mothers turn to the internet for information and emotional support, and to share their experiences. In this paper, we present the results from 12 semi-structured interviews with women, investigating how and what online information they searched for at the time of miscarriage.

Engaging Consumers with Musculoskeletal Conditions in Health Research: A User-Centred Perspective.

Consumers are frequently involved in different kinds of health research, such as clinical trials, focus groups, and surveys. As pointed out by different studies, recruiting and involving consumers to participate in academic research can be challenging. While different research and guidelines are provided to instruct researchers to recruit participants ethically, they seldom consider the needs and expectations of consumers.

Finding and Exploring Health Information with a Slider-Based User Interface.

Despite the fact that search engines are the primary channel to access online health information, there are better ways to find and explore health information on the web. Search engines are prone to problems when they are used to find health information. For instance, users have difficulties in expressing health scenarios with appropriate search keywords, search results are not optimised for medical queries, and the search process does not account for users' literacy levels and reading preferences.

Designing Health Websites Based on Users' Web-Based Information-Seeking Behaviors: A Mixed-Method Observational Study.

Background: Laypeople increasingly use the Internet as a source of health information, but finding and discovering the right information remains problematic. These issues are partially due to the mismatch between the design of consumer health websites and the needs of health information seekers, particularly the lack of support for "exploring" health information.

Objective: The aim of this research was to create a design for consumer health websites by supporting different health information-seeking behaviors.